For more information please visit my English website.
Emneord:
biostatistikk,
kreft,
risiko prediksjon,
integrerende genomikk,
genetikk,
epidemiologi
Publikasjoner
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Sveen, Anita; Stenersen, Jakob Mørkved; Asenso, Theophilus Quachie; Klokkerud, Solveig Knoph; Kranjec, Christian & Eilertsen, Ina
[Vis alle 11 forfattere av denne artikkelen]
(2026).
Exceptional treatment responses and molecular markers among 103 colorectal cancer cell lines.
Molecular Biomedicine.
7.
doi:
10.1186/s43556-026-00551-z.
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Patients with colorectal cancer have few molecularly guided treatment options. Cancers with exceptional treatment response are valuable models for discovery of molecular response mechanisms and might reveal new predictive biomarkers to guide treatment selection. However, the rarity of events is a clinical challenge. We performed integrated high-throughput drug sensitivity testing (n = 620 drugs) and molecular analyses of 103 colorectal cancer cell lines to build an in vitro foundation for exceptional treatment responses and their molecular markers. Exceptional responses were scored by a two-way outlier detection approach and were identified in 67 unique cell line-drug pairs (0.13% of all pairs tested). This involved 35 cell lines (34.0%) and 49 drugs (7.9%) representing standard, experimental, and non-oncology drugs of diverse classes. Plausible response mechanisms on the gene, protein, and/or pathway expression levels were identified at baseline in 89.6% of the 67 pairs. Experimental validation confirmed treatment-induced marker suppression in seven of eight selected pairs, including target engagement of kinase inhibitors and downregulation of markers of extended response mechanisms. Recurrent exceptional sensitivity to the same drug in different cell lines involved functionally convergent molecular mechanisms, but rarely precisely the same marker. Most exceptional sensitivities (77.8%) could be predicted with multivariable transcriptomic models. In conclusion, this study provides in vitro support for biomarker-guided prescreening to potentially obtain exceptional treatment response to diverse drugs and therapeutic targets in colorectal cancer. Most exceptional responses have a clear molecular underpinning. The study also provides a large and openly available pharmaco-transcriptomics resource for colorectal cancer cell lines.
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Balaguera, Nathalia Chica; Andersen, Aram Nikolai; Munoz, Sara Orellana; Llorente, Ignacio Garcia; P, Aurélie Nguéa & Nakken, Sigve
[Vis alle 14 forfattere av denne artikkelen]
(2026).
Time-resolved functional genomics using deep learning reveals global hierarchical control of autophagy.
Nature Cell Biology.
ISSN 1465-7392.
28(3),
s. 465–479.
doi:
10.1038/s41556-025-01837-0.
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Recycling of cellular components through autophagy maintains homeostasis in changing nutrient environments. Although its core mechanisms are extensively studied, understanding of its systems-wide dynamic regulation remains limited, particularly regarding how autophagy is inactivated once nutrients are restored. Here we mapped the genetic network that controls activation and inactivation of autophagy during nitrogen changes by combining time-resolved high-content imaging, deep learning and latent feature analysis. This dataset, termed AutoDRY, categorizes 5,919 mutants based on nutrient response kinetics and their contributions to autophagosome formation and clearance. Integrating these profiles with functional and genetic network data uncovered hierarchical and multilayered control of autophagy and revealed multiple new regulatory pathways. Notably, we identified the retrograde pathway as a pivotal time-varying modulator that tunes the expression of core autophagy genes and plays a central role in autophagy inactivation. Together, this study establishes a systems-level resource to guide future investigations of autophagy.
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Mathisen, Charlotte Bache-Wiig; Nyström, Niklas; Bazov, Igor; Øyås, Ove; Zucknick, Manuela & Andersen, Svend
[Vis alle 23 forfattere av denne artikkelen]
(2026).
A novel diagnostic serum protein signature for pediatric inflammatory bowel disease.
Journal of Pediatric Gastroenterology and Nutrition - JPGN.
ISSN 0277-2116.
doi:
10.1002/jpn3.70379.
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Abstract Objectives Diagnostic delay is common in pediatric inflammatory bowel disease (PIBD), and fecal calprotectin (FCP) is often limited by challenges with sample collection. Therefore, we aimed to identify and validate a blood‐based diagnostic protein signature of PIBD. Methods Proteins were analyzed using proximity extension assay in plasma samples from treatment‐naïve pediatric patients in a Swedish inception cohort referred for suspected inflammatory bowel disease (IBD) and validated in an independent Norwegian population‐based pediatric inception cohort. Diagnostic performance was estimated by the area under the curve (AUC) with 95% confidence intervals (CIs). Results The discovery cohort included 58 patients with PIBD and 36 symptomatic controls without evidence of IBD, while the validation cohort consisted of 79 patients with PIBD and 37 symptomatic controls. In total, 154 proteins were examined. Univariable analyses identified 26 differentially regulated proteins for PIBD versus symptomatic controls in the discovery cohort ( q < 0.05), whereas 29 proteins were differentially regulated in the validation cohort. Using regularized logistic regression, we identified a diagnostic model of 31 proteins that differentiated PIBD from symptomatic controls in the discovery cohort (AUC = 0.83; 95% CI: 0.74–0.90). The protein signature was further reduced to a clinically relevant biomarker consisting of high‐sensitivity C‐reactive protein (hsCRP) and seven other proteins with diagnostic capacity (AUC = 0.85, 95% CI: 0.78–0.92) outperforming hsCRP in the validation cohort ( p = 0.006). Conclusions We identified and validated a blood‐based protein signature for PIBD with superior diagnostic performance compared to hsCRP. Given the challenges of fecal sample collection, further assay development may enable integration of these biomarkers into diagnostic pathways for PIBD. Trial Registration ClinicalTrials.gov identifier: NCT02727959.
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Pickering, Sarah Jai Hazell; Galigniana, Natalia Maricel; Abdelhalim, Mohamed; Sørensen, Anita Løvstad; Madsen-Østerbye, Julia-Kristina & Zucknick, Manuela
[Vis alle 8 forfattere av denne artikkelen]
(2026).
Multimodal epigenetic and enhancer network remodeling shape the transcriptional landscape of human beige adipocytes.
Communications Biology.
doi:
10.1038/s42003-025-09469-8.
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Abstract Epigenetic regulation is a key determinant of adipocyte fate, driving the differentiation toward white or thermogenic beige phenotypes in response to environmental cues. To dissect the mechanisms orchestrating this plasticity in human adipocytes, we conducted an integrative analysis of transcriptomic, epigenomic and enhancer connectome dynamics throughout white and beige adipogenesis. Using a machine learning approach, we show that the white transcriptional program is tightly linked to promoter-level modulation of H3K27ac and chromatin accessibility, whereas the beige-specific induction of mitochondrial genes is driven by promoter remodeling of H3K4me3, underscoring distinct epigenetic mechanisms for white or beige specification. Adipocyte beiging is accompanied by a targeted reorganization of the 3D genome, characterized by increased recruitment of short-range enhancers controlling thermogenesis genes, enriched for C/EBP transcription factor binding sites. Our findings highlight the multimodal regulation of the beige adipocyte fate, driven by the interplay of chromatin state transitions, enhancer rewiring, and transcription factor dynamics.
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Dalessandro, Matteo; Asenso, Theophilus Quachie & Zucknick, Manuela
(2025).
Integrating Multiple Data Sources With Interactions in Multi-Omics Using Cooperative Learning.
Statistics in Medicine.
ISSN 0277-6715.
44(13-14).
doi:
10.1002/sim.70148.
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Modeling with multi-omics data presents multiple challenges such as the high-dimensionality of the problem (p ≫ n), the presence of interactions between features, and the need for integration between multiple data sources. We establish an interaction model that allows for the inclusion of multiple sources of data from the integration of two existing methods, pliable lasso and cooperative learning. The integrated model is tested both on simulation studies and on real multi-omics datasets for predicting labor onset and cancer treatment response. The results show that the model is effective in modeling multi-source data in various scenarios where interactions are present, both in terms of prediction performance and selection of relevant variables.
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Westerberg, Ane Cecilie; Degnes, Maren-Helene Langeland; Andresen, Ina Jungersen; Sellevoll, Hilde Bastøe; Lekva, Tove & Ueland, Thor
[Vis alle 11 forfattere av denne artikkelen]
(2025).
Placenta-Derived Proteins in Preeclampsia: A Human In Vivo Study.
Hypertension.
ISSN 0194-911X.
82(12),
s. 2125–2139.
doi:
10.1161/hypertensionaha.125.24886.
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BACKGROUND: Placental dysfunction, a key feature of preeclampsia, has been linked to altered placental release of proteins into the maternal circulation. However, the identity of placenta-derived proteins in preeclampsia is unclear due to the inaccessibility of the placenta during pregnancy. This study aimed to identify placenta-derived proteins in preeclampsia, characterize their associated biological processes, and assess their biomarker potential. METHODS: We used the 4-vessel sampling method to collect blood from the ingoing and outgoing vessels of the placenta during cesarean section to identify proteins secreted from the placenta. Prospectively collected samples from a separate pregnancy cohort were also included. Proteins were quantified on the SomaLogic 5000-plex platform. RESULTS: We identified 620 placenta-derived proteins, including 229 proteins released in both healthy pregnancies and in preeclampsia, 345 proteins released in preeclampsia only, and 46 proteins released in healthy controls only. Biological process gene ontologies linked to oxidative stress and cellular turnover were enriched among the placenta-derived proteins in preeclampsia, but not in healthy pregnancies. In the prospective cohort, 21 of the 620 placenta-derived proteins had altered levels in preeclampsia at least 3 weeks before, and on average >7 weeks before delivery. Among these, prediction performance for preeclampsia was promising for 11 biomarker candidates in single protein models (area under the curve >0.7) and 17 significantly improved prediction when combined with clinical variables as compared with a clinical model alone. CONCLUSIONS: Using a unique in vivo sampling method, we identified placenta-derived proteins in preeclampsia, several of which showed promising biomarker potential.
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Ramberg, Håkon; Zucknick, Manuela; Barletta, Francesco; Davik, Petter; Nybøen, Åsmund & Eri, Lars Magne
[Vis alle 15 forfattere av denne artikkelen]
(2025).
Development and evaluation of a lymph node invasion risk prediction model in intermediate- and high-risk prostate cancer patients.
Acta Oncologica.
ISSN 0284-186X.
64,
s. 1446–1454.
doi:
10.2340/1651-226x.2025.43970.
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Background and purpose:
Many prostate cancer patients undergoing pelvic lymph node dissection (PLND) have no sign of lymph node invasion (LNI) during final pathological assessment. To improve preoperative staging accuracy, we developed the Oslo model, which estimates the risk of LNI based on clinical, histopathological, and magnetic resonance imaging (MRI) variables.
Patients/materials and methods:
We utilized data from 903 prostate cancer patients treated at Oslo University Hospital (OUS) to develop the model using Bayesian logistic regression. The Oslo model was validated with data from 189 patients at IRCCS Ospedale San Raffaele (HRS), 157 from St. Olav’s Hospital, and 231 from OUS. We assessed its performance against the Memorial Sloan Kettering Cancer Centre (MSKCC) and Briganti 2019 nomograms using metrics like AUC, R², decision curve analysis, and calibration plots.
Results:
The Oslo model outperformed Briganti 2019, demonstrating a higher net benefit and a 10% reduction in interventions at a 7% cutoff. Key variables included clinical T stage on MRI, Prostate Specific Antigen (PSA), prostate volume, International Society of Urological Pathology grade group, and maximum lesion length on MRI. Validation showed strong reliability in the OUS and HRS cohorts but weaker performance in the St. Olav’s cohort. The AUCs were 77% for the Oslo model, 74% for Briganti 2019, and 66% for MSKCC. Limitations include small and heterogeneous validation cohorts.
Interpretation:
The Oslo model enhances predictive performance in intermediate- and high-risk patients using easily accessible clinical and MRI data, potentially reducing unnecessary PLND interventions and assisting clinicians in treatment decision-making.
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Grindedal, Eli Marie; Zucknick, Manuela; Hovland, Sigrid Tronsli; Grimsrud, Tom Kristian & Mæhle, Lovise Olaug
(2025).
A prospective observational study of pancreatic cancer risk in men and women with pathogenic variants in BRCA1 or BRCA2.
BJC Reports.
3(1).
doi:
10.1038/s44276-025-00199-2.
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Background
BRCA1 and BRCA2 carriers have increased risk of pancreatic cancer (PC). We have studied prospective incidence rate and cumulative risk of PC in a large cohort of confirmed carriers.
Methods
BRCA1/2 carriers without PC prior to genetic testing were identified from the clinical registry at Section for Hereditary Cancer, Oslo University Hospital. Cancer diagnoses were collected from Cancer Registry of Norway (CRN). Standardized incidence ratios (SIRs) were derived from national reference rates. The Kaplan-Meier method was used to calculate cumulative risk.
Results
Among 2681 BRCA1 carriers, we observed 13 cases versus 4.73 expected (SIR 2.75, 95% CI 1.46–4,70). In 1476 BRCA2 carriers, we observed 9 cases versus 1.89 expected (SIR 4.76, 95% CI 2.18–9.04). Suggestively, there were higher risks among female BRCA2 carriers (SIR 6.52, 95% CI 2.82–12.85, 8 cases) and male BRCA1 carriers (SIR 5.51, 95% CI 2.52–10.47, 9 cases), who had cumulative risks at 70 years of 1.2% and 2.5% respectively.
Conclusions
BRCA1/2 carriers had three times more cases of PC than expected, suggestively higher among female BRCA2 and male BRCA1 carriers. Cumulative risk of PC at 70 years in the latter two groups was less than 3% (0.5% and 0.7% in all Norwegian males and females observed until age 70 based on population data).
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Smajdor, Anna; Frigessi, Arnoldo & Zucknick, Manuela
(2025).
WHAT IS RIGHT FOR ‘THIS’ PATIENT? AUTONOMY, TRUST AND TRANSPARENCY IN THE ERA OF MEDICAL AI.
Síntesis: Revista de Filosofia.
ISSN 2452-4476.
52(164),
s. 611–611.
doi:
10.20911/21769389v52n164p611/2025.
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In this paper we compare the capabilities and limitations of AI algorithms and human doctors in the context of treatment recommendations. Ethical concerns have been raised in the literature about transparency, accountability, and interpretability in relation to AI algorithms in the medical context. Patients’ autonomy is not likely to be respected if treatment recommendations are opaque or incomprehensible. Medical AI algorithms are programmed to prioritise predefined goals that may not align with patients’ preferences, potentially undermining their autonomy without their awareness. Yet human doctors often face similar challenges, such as reliance on clinical trial data with endpoints that may not be fully understood by patients. We conclude that there are opportunities now to integrate patient autonomy considerations into AI algorithms at the design stage, and that these goals and any relevant weightings are made explicit to end users, including both doctors and patients.
Keywords: Artificial intelligence. Autonomy Alignment. Medical ethics.
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Kanduri, Chakravarthi; Mamica, Maria Anna; Olstad, Emilie Willoch; Zucknick, Manuela; Jessica, Li, Jingyi & Sandve, Geir Kjetil Ferkingstad
(2025).
Beware of counter-intuitive levels of false discoveries in datasets with strong intra-correlations.
Genome Biology.
ISSN 1465-6906.
26.
doi:
10.1186/s13059-025-03734-z.
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The false discovery rate (FDR) controlling method by Benjamini and Hochberg (BH) is a popular choice in the omics fields. Here, we demonstrate that in datasets with a large degree of dependencies between features, FDR correction methods like BH can sometimes counter-intuitively report very high numbers of false positives, potentially misleading researchers. We call the attention of researchers to use suited multiple testing strategies and approaches like synthetic null data (negative control) to identify and minimize caveats related to false discoveries, as in the cases where false findings do occur, they may be numerous.
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Asenso, Theophilus Quachie & Zucknick, Manuela
(2025).
A novel multi-response regression with overlapping groups and interaction effects motivated by large-scale pharmacogenomic screens.
Journal of Applied Statistics.
ISSN 0266-4763.
s. 1–30.
doi:
10.1080/02664763.2025.2567981.
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In this paper, we consider the regularised multi-response regression problem where there exists some structural relation within the responses and also between the covariates and a set of modifying variables. To handle this problem, we propose MADMMplasso, a novel regularised regression method. This method is able to find covariates and their corresponding interactions, with some joint association with multiple related responses. We allow the interaction term between covariate and modifying variable to be included in a (weak) asymmetrical hierarchical manner by considering whether the corresponding covariate main term is in the model. For parameter estimation, we develop an ADMM algorithm that allows us to implement the overlapping groups in a simple way. The results from the simulations and analysis of a pharmacogenomic screen dataset show that the proposed method has an advantage in handling correlated responses and interaction effects, with respect to prediction and variable selection performance.
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Andresen, Ina Jungersen; Westerberg, Ane Cecilie; Roland, Marie Cecilie; Zucknick, Manuela & Michelsen, Trond Melbye
(2025).
Maternal Plasma Proteins Associated with Birth Weight: A Longitudinal, Large Scale Proteomic Study.
Journal of Proteome Research.
ISSN 1535-3893.
24,
s. 3247–3260.
doi:
10.1021/acs.jproteome.4c00940.
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Small infants for gestational age (SGA) and large infants for gestational age (LGA) have increased risk of complications during delivery and later in life. Prediction of the fetal weight is currently limited to biometric parameters obtained by ultrasound scans that can be imprecise. Biomarkers of fetal growth would be crucial for tailoring clinical management and optimizing outcomes for the mother and child. Seventy pregnant women participated in the current study, including 58, 7, and 5 giving birth to adequate for gestational age (AGA), SGA, and LGA infants, respectively. Maternal venous blood was drawn at gestational weeks 12–19, 21–27, and 28–34 and quantified for nearly 5000 proteins on the SomaLogic platform. We used machine learning algorithms with leave-one-out cross-validation to construct multiprotein models for prediction of birth weight groups. Random forest models using only 20 predefined proteins (selected by moderated t tests) were able to predict LGA with good discrimination (AUC > 0.8) at all three visits, while prediction of SGA was less successful. Protein differential abundance analysis revealed 148 proteins with higher abundance in LGA compared to AGA pregnancies, while only four proteins were differentially abundant between the SGA and AGA. The principal findings indicate that the maternal plasma proteome may hold potential biomarkers of LGA.
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Vigeland, Maria Dehli; Flåm, Siri Tennebø; Vigeland, Magnus Dehli; Zucknick, Manuela; Wigemyr, Monica & Bråten, Lars Christian Haugli
[Vis alle 11 forfattere av denne artikkelen]
(2025).
Gene Expression Correlates with Disability and Pain Intensity in Patients with Chronic Low Back Pain and Modic Changes in a Sex-Specific Manner.
International Journal of Molecular Sciences.
ISSN 1661-6596.
26(2).
doi:
10.3390/ijms26020800.
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Chronic low back pain (cLBP) lacks clear physiological explanations, and the treatment options are of limited effect. We aimed to elucidate the underlying biology of cLBP in a subgroup of patients with Modic changes type I (suggestive of inflammatory vertebral bone marrow lesions) by correlating gene expression in blood with patient-reported outcomes on disability and pain intensity and explore sex differences. Patients were included from the placebo group of a clinical study on patients with cLBP and Modic changes. Blood was collected at the time of inclusion, after three months, and after one year, and gene expression was measured at all time points by high-throughput RNA sequencing. The patients reported disability using the Roland–Morris Disability Questionnaire, and pain intensity was assessed as a mean of three scores on a 0–10 numeric rating scale: current LBP, worst LBP within the last two weeks, and mean LBP within the last two weeks. The gene expression profiles were then correlated to the reported outcomes. Changes in gene expression over time correlated significantly with changes in both disability and pain. The findings showed distinct patterns in men and women, with negligible overlap in correlated genes between the sexes. The genes involved were enriched in immunological pathways, particularly T cell receptor complex and immune responses related to neutrophils. Several of the genes harbour polymorphisms that previously have been found to be associated with chronic pain. Taken together, our results indicate gender differences in the underlying biology of disability and pain intensity in patients with low back pain.
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Gjerdalen, Oda Skancke; Zucknick, Manuela; Westlie, Ingvild Tvedt; Bull, Helen; Evensen, Stig & Falkum, Erik
[Vis alle 17 forfattere av denne artikkelen]
(2025).
An exploratory study of the relevance of therapy format and therapist’ training in individual cognitive behavioral therapy for psychosis.
Frontiers in Psychiatry.
16.
doi:
10.3389/fpsyt.2025.1527549.
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Introduction: Cognitive Behavioral Therapy for psychosis (CBTp) is an evidence-based intervention that can be delivered in various formats, including as part of vocational rehabilitation. However, due to scarcity of resources, CBTp is currently accessible to only a minority of individuals with psychosis. This secondary analysis aims to explore potential differences in clinical outcomes between distinct CBTp formats and to examine whether therapist training influences treatment effect. Exploring these aspects is of importance, as they may influence the scalability and accessibility of CBTp in routine care.
Material and methods: Data in this study is sourced from two independent projects; KATOslo and JUMP, comprising a total of 200 participants with broad schizophrenia-spectrum disorders. The current study compares CBTp delivered as either symptom-focused individual therapy (KATOslo) or as an add-on to a vocational rehabilitation (VR) program (JUMP), with two reference groups; VR combined with cognitive remediation (JUMP) and treatment as usual (KATOslo). Using a series of mixed effects models for repeated measurements, we examined differences between the groups in terms of general functioning and psychiatric symptom severity. Emphasis was placed on potential differences between the two groups receiving CBTp, considering both average differences across assessment points and trajectories over time.
Results: In line with expectations, all groups demonstrated overall improvements in functioning and symptom levels. After adjusting for relevant confounders, no statistically significant differences were found between the two groups receiving CBTp following treatment initiation.
Conclusions: These findings suggest that CBTp may be effective across different delivery formats and levels of therapist training in terms of similar, positive clinical outcomes for this patient group. This has potential implications for service design and broader implementation of CBTp in real-world settings.
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Li, Gaoyang; Kolan, Shrikant; Grimolizzi, Franco; Sexton, Joseph; Malachin, Giulia & Goll, Guro Løvik
[Vis alle 12 forfattere av denne artikkelen]
(2025).
Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study.
Frontiers of Medicine.
ISSN 2095-0217.
12.
doi:
10.3389/fmed.2025.1526708.
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Introduction: Achieving remission is a critical therapeutic goal in the management of rheumatoid arthritis (RA). Despite methotrexate being the cornerstone of early RA treatment, a significant proportion of patients fail to achieve remission. This study aims to predict 6-month non-remission in 222 disease-modifying antirheumatic drug (DMARD)-naïve RA patients initiating methotrexate monotherapy, using baseline patient characteristics from the ARCTIC trial. Methods: Machine learning models were developed utilizing twenty-one baseline demographic, clinical and laboratory features to predict non-remission according to ACR/EULAR Boolean, SDAI and CDAI criteria. The model employed a super learner algorithm that combine three base algorithms of elastic net, random forest and support vector machine. The model performance was evaluated through five independent unseen tests with nested 5-fold cross-validation. The predictive power of each feature was assessed using a composite measure derived from individual algorithm estimates. Results: The model demonstrated a mean AUC-ROC of 0.75-0.76, with mean sensitivity of 0.77-0.81, precision (also referred to as Positive Predictive Value) of 0.77-0.79 and specificity of 0.63-0.66 across the criteria. Predictive power analysis of each feature identified the baseline Rheumatoid Arthritis Impact of Disease (RAID) score as the strongest predictor of non-remission. A simplified model using RAID score alone demonstrated comparable performance to the full-feature model. Conclusion: These findings highlight the potential utility of baseline RAID scorebased model as an effective tool for early identification of patients at risk of nonremission in clinical practise.
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Zhao, Zhi; Zobolas, John; Zucknick, Manuela & Aittokallio, Tero Antero
(2024).
Tutorial on survival modeling with applications to omics data.
Bioinformatics.
ISSN 1367-4803.
40(3).
doi:
10.1093/bioinformatics/btae132.
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Motivation Identification of genomic, molecular and clinical markers prognostic of patient survival is important for developing personalized disease prevention, diagnostic and treatment approaches. Modern omics technologies have made it possible to investigate the prognostic impact of markers at multiple molecular levels, including genomics, epigenomics, transcriptomics, proteomics and metabolomics, and how these potential risk factors complement clinical characterization of patient outcomes for survival prognosis. However, the massive sizes of the omics datasets, along with their correlation structures, pose challenges for studying relationships between the molecular information and patients’ survival outcomes. Results We present a general workflow for survival analysis that is applicable to high-dimensional omics data as inputs when identifying survival-associated features and validating survival models. In particular, we focus on the commonly used Cox-type penalized regressions and hierarchical Bayesian models for feature selection in survival analysis, which are especially useful for high-dimensional data, but the framework is applicable more generally. Availability and implementation A step-by-step R tutorial using The Cancer Genome Atlas survival and omics data for the execution and evaluation of survival models has been made available at https://ocbe-uio.github.io/survomics.
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Andresen, Ina Jungersen; Zucknick, Manuela; Degnes, Maren-Helene Langeland; Angst, Martin S.; Aghaeepour, Nima & Romero, Roberto
[Vis alle 10 forfattere av denne artikkelen]
(2024).
Prediction of late-onset preeclampsia using plasma proteomics: a longitudinal multi-cohort study.
Scientific Reports.
14(1).
doi:
10.1038/s41598-024-81277-2.
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Preeclampsia is a pregnancy disorder with substantial perinatal and maternal morbidity and mortality. Pregnant women at risk of preeclampsia would benefit from early detection for follow-up, timely interventions and delivery. Several attempts have been made to identify protein biomarkers of preeclampsia, but findings vary with demographics, clinical characteristics, and time of sampling. In the current study, we combined three independent longitudinal pregnancy cohorts (Detroit, Stanford and Oslo) resulting in 124 late-onset preeclampsia (LOPE) cases and 178 gestational age matched controls, and analyzed > 1000 proteins in maternal plasma sampled between 12 and 34 weeks of gestation. Differential abundance analysis of combined protein data revealed increased deviation in protein abundance trajectories throughout gestation in women destined to develop LOPE compared to controls. There were no differentially abundant proteins at time interval T1 (12–19 weeks), yet 31 differentially abundant proteins were found at time interval T2 (19–27 weeks), and 48 proteins at time interval T3 (27- 34 weeks). Multi-protein random forest models assessed via cross-validation predicted LOPE with an area under the ROC curve of 0.72 (0.65–0.78), 0.76 (0.71–0.81) and 0.80 (0.75–0.85) at time interval T1, T2 and T3, respectively. The results at T3 were confirmed using a leave-one-cohort-out analysis suggesting cross-cohort consistency, and at T1 and T2 when the largest two cohorts were used as training sets.
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Degnes, Maren-Helene Langeland; Westerberg, Ane Cecilie; Andresen, Ina Jungersen; Henriksen, Tore; Roland, Marie Cecilie & Zucknick, Manuela
[Vis alle 7 forfattere av denne artikkelen]
(2024).
Protein biomarker signatures of preeclampsia - a longitudinal 5000-multiplex proteomics study.
Scientific Reports.
14(1).
doi:
10.1038/s41598-024-73796-9.
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We aimed to explore novel biomarker candidates and biomarker signatures of late-onset preeclampsia (LOPE) by profiling samples collected in a longitudinal discovery cohort with a high-throughput proteomics platform. Using the Somalogic 5000-plex platform, we analyzed proteins in plasma samples collected at three visits (gestational weeks (GW) 12–19, 20–26 and 28–34 in 35 women with LOPE (birth ≥ 34 GW) and 70 healthy pregnant women). To identify biomarker signatures, we combined Elastic Net with Stability Selection for stable variable selection and validated their predictive performance in a validation cohort. The biomarker signature with the highest predictive performance (AUC 0.88 (95% CI 0.85–0.97)) was identified in the last trimester of pregnancy (GW 28–34) and included the Fatty acid amid hydrolase 2 (FAAH2), HtrA serine peptidase 1 (HTRA1) and Interleukin-17 receptor C (IL17RC) together with sFLT1 and maternal age, BMI and nulliparity. Our biomarker signature showed increased or similar predictive performance to the sFLT1/PGF-ratio within our data set, and we were able to validate the biomarker signature in a validation cohort (AUC ≥ 0.90). Further validation of these candidates should be performed using another protein quantification platform in an independent cohort where the negative and positive predictive values can be validly calculated.
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Grindedal, Eli Marie; Zucknick, Manuela; Stormorken, Astrid T.; Rønne, Elin; Tandstad, Nora Martinussen & Isaacs, William B.
[Vis alle 8 forfattere av denne artikkelen]
(2024).
Outcomes of 10 years of PSA screening for prostate cancer in Norwegian men with Lynch syndrome.
The Prostate.
ISSN 0270-4137.
84(10),
s. 945–953.
doi:
10.1002/pros.24711.
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Background Pathogenic germline variants in the mismatch repair (MMR) genes are associated with an increased risk of prostate cancer (PCa). Since 2010 we have recommended MMR carriers annual PSA testing from the age of 40. Prospective studies of the outcome of long-term PSA screening are lacking. This study aimed to investigate the incidence and characteristics of PCa in Norwegian MMR carriers attending annual PSA screening (PSA threshold >3.0 ng/mL) to evaluate whether our recommendations should be continued. Methods This is a prospective observational study of 225 male MMR carriers who were recommended annual PSA screening by the Section of Inherited Cancer, Oslo University Hospital from 2010 and onwards. Incidence and tumor characteristics (age, PSA at diagnosis, Gleason score, TNM score) were described. IHC and MSI-analyses were done on available tumors. Standardized incidence ratio (SIR) was calculated based on data from the Cancer Registry of Norway. Results Twenty-two of 225 (9.8%) had been diagnosed with PCa, including 10/69 (14.5%) MSH2 carriers and 8/61 (13.1%) MSH6 carriers. Ten of 20 (50%) tumors had Gleason score ≥4 + 3 on biopsy and 6/11 (54.5%) had a pathological T3a/b stage. Eight of 17 (47.1%) tumors showed abnormal staining on IHC and 3/13 (23.1%) were MSI-high. SIR was 9.54 (95% CI 5.98–14.45) for all MMR genes, 13.0 (95% CI 6.23–23.9) for MSH2 and 13.74 for MSH6 (95% CI 5.93–27.08). Conclusions Our results indicate that the MMR genes, and especially MSH2 and MSH6, are associated with a significant risk of PCa, and a high number of tumors show aggressive characteristics. While the impact of screening on patient outcomes remains to be more firmly established, the high SIR values we observe provide support for continued PSA screening of MSH2 and MSH6 carriers. Studies are needed to provide optimal recommendations for PSA-threshold and to evaluate whether MLH1 and PMS2 carriers should not be recommended screening.
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Hsieh, Ping-Han; Lopes-Ramos, Camila Miranda; Zucknick, Manuela; Sandve, Geir Kjetil Ferkingstad; Glass, Kimberly & Kuijjer, Marieke
(2023).
Adjustment of spurious correlations in co-expression measurements from RNA-Sequencing data.
Bioinformatics.
ISSN 1367-4803.
39(10).
doi:
10.1093/bioinformatics/btad610.
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Abstract Motivation Gene co-expression measurements are widely used in computational biology to identify coordinated expression patterns across a group of samples. Coordinated expression of genes may indicate that they are controlled by the same transcriptional regulatory program, or involved in common biological processes. Gene co-expression is generally estimated from RNA-Sequencing data, which are commonly normalized to remove technical variability. Here, we demonstrate that certain normalization methods, in particular quantile-based methods, can introduce false-positive associations between genes. These false-positive associations can consequently hamper downstream co-expression network analysis. Quantile-based normalization can, however, be extremely powerful. In particular, when preprocessing large-scale heterogeneous data, quantile-based normalization methods such as smooth quantile normalization can be applied to remove technical variability while maintaining global differences in expression for samples with different biological attributes. Results We developed SNAIL (Smooth-quantile Normalization Adaptation for the Inference of co-expression Links), a normalization method based on smooth quantile normalization specifically designed for modeling of co-expression measurements. We show that SNAIL avoids formation of false-positive associations in co-expression as well as in downstream network analyses. Using SNAIL, one can avoid arbitrary gene filtering and retain associations to genes that only express in small subgroups of samples. This highlights the method’s potential future impact on network modeling and other association-based approaches in large-scale heterogeneous data. Availability and implementation The implementation of the SNAIL algorithm and code to reproduce the analyses described in this work can be found in the GitHub repository https://github.com/kuijjerlab/PySNAIL.
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Vigeland, Maria Dehli; Flåm, Siri Tennebø; Vigeland, Magnus Dehli; Espeland, Ansgar; Zucknick, Manuela & Wigemyr, Monica
[Vis alle 14 forfattere av denne artikkelen]
(2023).
Long-Term Use of Amoxicillin Is Associated with Changes in Gene Expression and DNA Methylation in Patients with Low Back Pain and Modic Changes.
Antibiotics.
12(7).
doi:
10.3390/antibiotics12071217.
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Long-term antibiotics are prescribed for a variety of medical conditions, recently including low back pain with Modic changes. The molecular impact of such treatment is unknown. We conducted longitudinal transcriptome and epigenome analyses in patients (n = 100) receiving amoxicillin treatment or placebo for 100 days in the Antibiotics in Modic Changes (AIM) study. Gene expression and DNA methylation were investigated at a genome-wide level at screening, after 100 days of treatment, and at one-year follow-up. We identified intra-individual longitudinal changes in gene expression and DNA methylation in patients receiving amoxicillin, while few changes were observed in patients receiving placebo. After 100 days of amoxicillin treatment, 28 genes were significantly differentially expressed, including the downregulation of 19 immunoglobulin genes. At one-year follow-up, the expression levels were still not completely restored. The significant changes in DNA methylation (n = 4548 CpGs) were mainly increased methylation levels between 100 days and one-year follow-up. Hence, the effects on gene expression occurred predominantly during treatment, while the effects on DNA methylation occurred after treatment. In conclusion, unrecognized side effects of long-term amoxicillin treatment were revealed, as alterations were observed in both gene expression and DNA methylation that lasted long after the end of treatment.
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Zhao, Zhi; Banterle, Marco; Lewin, Alex & Zucknick, Manuela
(2023).
Multivariate Bayesian structured variable selection for pharmacogenomic studies.
Journal of the Royal Statistical Society, Series C (Applied Statistics).
ISSN 0035-9254.
73(2),
s. 420–443.
doi:
10.1093/jrsssc/qlad102.
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Abstract Cancer drug sensitivity screens combined with multi-omics characterisation of the cancer cells have become an important tool to determine the optimal treatment for each patient. We propose a multivariate Bayesian structured variable selection model for sparse identification of multi-omics features associated with multiple correlated drug responses. Our model uses known structure between drugs and their targeted genes via a Markov random field (MRF) prior in sparse seemingly unrelated regression. The use of MRF prior can improve the model performance compared to other common priors. The proposed model is applied to the Genomics of Drug Sensitivity in Cancer data.
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Vilming, Bente; Dahl, Jørgen Fallås; Bentzen, Anne Gry; Ingebrigtsen, Vibeke Anett; Nilsen, Elisabeth Berge & Vistad, Ingvild
[Vis alle 12 forfattere av denne artikkelen]
(2023).
Real-world data on niraparib maintenance treatment in patients with non-gBRCA mutated platinum-sensitive recurrent ovarian cancer.
International Journal of Gynecological Cancer.
ISSN 1048-891X.
33(12),
s. 1898–1905.
doi:
10.1136/ijgc-2023-004484.
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Objectives The aim of this study was to provide real-world efficacy and safety data on niraparib maintenance treatment in patients with non-germline (gBRCA)1/2 mutated platinum-sensitive recurrent ovarian cancer. Methods This retrospective multi-center cohort study included 94 platinum-sensitive recurrent ovarian cancer patients without known gBRCA1/2 mutation treated in an individual patient access program in Norway. The primary outcome was time from start of niraparib treatment to first subsequent treatment. Secondary endpoints included progression-free survival, safety, and tolerability. Results After median follow-up of 13.4 months (95% confidence interval (CI) 10.0 to 16.8), 68.1% had progressed and 22.3% had died. Of the entire cohort, 61.7% had commenced a new line of treatment, and 24.5% were still receiving niraparib. The median duration of niraparib treatment was 5.0 months (range 0.4 to 27.3), and the median time to first subsequent treatment was 10.7 months (95% CI 8.4 to 13.0). Patients with elevated CA125 prior to start of niraparib had shorter time to first subsequent treatment (7.3 months, 95% CI 4.2 to 10.3) than patients with normalized CA125 (12.2 months, 95% CI 10.9 to 13.7 (p=0.002). Patients who started on individual dose based on weight and platelet counts had fewer dose reductions (p<0.001) and interruptions (p=0.02). Conclusion In a real-world setting, niraparib maintenance treatment in patients with non-gBRCA1/2 mutated recurrent platinum-sensitive ovarian cancer showed effectiveness comparable with published phase III studies and acceptable safety. Individualized dosing is essential to minimize adverse events. CA125 levels at start of niraparib treatment may help to estimate the individual prognosis.
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Brynjulvsen, Marit; Solli, Elise; Walewska, Maria; Zucknick, Manuela; Djirackor, Luna & Langmoen, Iver Arne
[Vis alle 10 forfattere av denne artikkelen]
(2023).
Functional and Molecular Heterogeneity in Glioma Stem Cells Derived from Multiregional Sampling.
Cancers.
15(24).
doi:
10.3390/cancers15245826.
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Glioblastoma (GBM) is an aggressive and highly heterogeneous primary brain tumor. Glioma stem cells represent a subpopulation of tumor cells with stem cell traits that are presumed to be the cause of tumor relapse. There exists complex tumor heterogeneity in drug sensitivity patterns between glioma stem cell (GSC) cultures derived from different patients. Here, we describe that heterogeneity also exists between GSC cultures derived from multiple biopsies within a single tumor. From biopsies harvested within spatially distinct regions representing the entire tumor mass, we established seven GSC cultures and compared their stem cell properties, mutations, gene expression profiles, and drug sensitivity patterns against 115 different anticancer drugs. The results were compared to 14 GSC cultures derived from other patients. Between the multiregional-derived GSC cultures, we observed only minor differences in their phenotype, proliferative capacity, and global gene expression. Further, they displayed intratumoral heterogeneity in mutational profiles and sensitivity patterns to anticancer drugs. This heterogeneity, however, did not exceed the extensive heterogeneity found between GSC cultures derived from other GBM patients. Our results suggest that the use of GSC cultures from one single focal biopsy may underestimate the overall complexity of the GSC population and display the importance of including GSC cultures reflecting the entire tumor mass in drug screening strategies.
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Rønneberg, Leiv; Kirk, Paul D. W. & Zucknick, Manuela
(2023).
Dose–response prediction for in-vitro drug combination datasets: a probabilistic approach.
BMC Bioinformatics.
24.
doi:
10.1186/s12859-023-05256-6.
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In this paper we propose PIICM, a probabilistic framework for dose–response prediction in high-throughput drug combination datasets. PIICM utilizes a permutation invariant version of the intrinsic co-regionalization model for multi-output Gaussian process regression, to predict dose–response surfaces in untested drug combination experiments. Coupled with an observation model that incorporates experimental uncertainty, PIICM is able to learn from noisily observed cell-viability measurements in settings where the underlying dose–response experiments are of varying quality, utilize different experimental designs, and the resulting training dataset is sparsely observed. We show that the model can accurately predict dose–response in held out experiments, and the resulting function captures relevant features indicating synergistic interaction between drugs.
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Alavi, Dena Treider; Henriksen, Hege Berg; Lauritzen, Peter Mæhre; Zucknick, Manuela; Bøhn, Siv Kjølsrud & Henriksen, Christine
[Vis alle 9 forfattere av denne artikkelen]
(2023).
Effect of a one-year personalized intensive dietary intervention on body composition in colorectal cancer patients: Results from a randomized controlled trial.
Clinical Nutrition ESPEN.
ISSN 2405-4577.
57,
s. 414–422.
doi:
10.1016/j.clnesp.2023.06.037.
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Background & aims Changes in body composition may affect colorectal cancer (CRC) patient's risk of cancer recurrence, secondary cancer, and other chronic diseases. The suggested interventions for changes in body composition such as low muscle mass or high fat mass, are diet and physical activity. Nevertheless, there is limited evidence of how dietary intervention alone can impact body composition. This study aimed to investigate the effect of a 6 and 12 month dietary intervention with a focus on healthy eating according to Norwegian food-based dietary guidelines on weight and body composition in patients with CRC stage I-III, post-surgery.<p> <p>Methods This study included participants from the randomized controlled trial CRC-NORDIET study 2–9 months after surgery. The intervention group received an intensive dietary intervention, while the control group underwent similar measurements, but no dietary intervention. Body composition was measured with Lunar iDXA, and the results were analyzed using linear mixed models. <p>Results A total of 383 participants were included, 192 in the intervention group and 191 in the control group. After 6 months, the intervention group showed a 0.7 kg lower mean weight gain (p = 0.020) and 0.6 kg lower fat mass gain (p = 0.019) than the control group, but no difference at 12 months. Moreover, the fat mass increase was 0.5 percentage points lower at 6 months (p = 0.012), and 0.7 percentage points lower at 12 months (p = 0.011) in the intervention group compared to the controls. At 6 months, the intervention group had 63 g lower gain of visceral adipose tissue compared to the control group (p = 0.031). No differences were seen for fat-free mass or subcutaneous adipose tissue at any time point. The intervention group showed a lower increase in the ratio between fat mass and fat-free mass at both 6 months (p = 0.025) and 12 months (p = 0.021). <p>Conclusion The dietary intervention reduced the increases in total weight and fat masses, without changing fat-free mass. Although the individual changes are small, the dietary intervention may have resulted in an overall more favourable body composition profile. These findings suggest that dietary intervention may be part of a treatment strategy for prevention of weight and fat mass gain in CRC survivors.
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Klevberg, Gunvor Lilleholt; Zucknick, Manuela; Jahnsen, Reidun Birgitta & Eliasson, Ann-Christin
(2023).
Development of Hand Use with and Without Intensive Training Among Children with Unilateral Cerebral Palsy in Scandinavia.
Developmental Neurorehabilitation.
ISSN 1751-8423.
26(3),
s. 163–171.
doi:
10.1080/17518423.2023.2193256.
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Aim To describe hand use development in children with unilateral cerebral palsy who did/did not participate in constraint-induced movement therapy (CIMT) before 7 years of age. Method The study included 334 participants (18 months–12 years) who were assessed with 1,565 Assisting Hand Assessments (AHAs) and categorized into no intensive training (NIT), CIMT (18 months–7 years), and Baby-CIMT (<18 months) groups. Results AHA performance at 18 months (AHA-18) was positively associated with development regardless of training. The CIMT group had lower AHA-18 performance than the NIT group (p = .028), but higher stable limit (p = .076). The age when 90% of development was reached was highest in the CIMT group (p = .014). Although non-significant, the Baby-CIMT group had higher mean curve than NIT and CIMT combined (AHA-18 p = .459, limit p = .477). Conclusion The CIMT group improved more over time than the NIT group. Intensive training extended the window of development, and Baby-CIMT might promote early development.
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Schmutz, Maximilian; Zucknick, Manuela; Schlenk, Richard F.; Mertens, Daniel; Benner, Axel & Weichenhan, Dieter
[Vis alle 11 forfattere av denne artikkelen]
(2023).
Predictive value of DNA methylation patterns in AML patients treated with an azacytidine containing induction regimen.
Clinical Epigenetics.
15(1).
doi:
10.1186/s13148-023-01580-z.
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Background Acute myeloid leukemia (AML) is a heterogeneous disease with a poor prognosis. Dysregulation of the epigenetic machinery is a significant contributor to disease development. Some AML patients benefit from treatment with hypomethylating agents (HMAs), but no predictive biomarkers for therapy response exist. Here, we investigated whether unbiased genome-wide assessment of pre-treatment DNA-methylation profiles in AML bone marrow blasts can help to identify patients who will achieve a remission after an azacytidine-containing induction regimen. Results A total of n = 155 patients with newly diagnosed AML treated in the AMLSG 12-09 trial were randomly assigned to a screening and a refinement and validation cohort. The cohorts were divided according to azacytidine-containing induction regimens and response status. Methylation status was assessed for 664,227 500-bp-regions using methyl-CpG immunoprecipitation-seq, resulting in 1755 differentially methylated regions (DMRs). Top regions were distilled and included genes such as WNT10A and GATA3. 80% of regions identified as a hit were represented on HumanMethlyation 450k Bead Chips. Quantitative methylation analysis confirmed 90% of these regions (36 of 40 DMRs). A classifier was trained using penalized logistic regression and fivefold cross validation containing 17 CpGs. Validation based on mass spectra generated by MALDI-TOF failed (AUC 0.59). However, discriminative ability was maintained by adding neighboring CpGs. A recomposed classifier with 12 CpGs resulted in an AUC of 0.77. When evaluated in the non-azacytidine containing group, the AUC was 0.76. Conclusions Our analysis evaluated the value of a whole genome methyl-CpG screening assay for the identification of informative methylation changes. We also compared the informative content and discriminatory power of regions and single CpGs for predicting response to therapy. The relevance of the identified DMRs is supported by their association with key regulatory processes of oncogenic transformation and support the idea of relevant DMRs being enriched at distinct loci rather than evenly distribution across the genome. Predictive response to therapy could be established but lacked specificity for treatment with azacytidine. Our results suggest that a predictive epigenotype carries its methylation information at a complex, genome-wide level, that is confined to regions, rather than to single CpGs. With increasing application of combinatorial regimens, response prediction may become even more complicated.
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Mørk, Marianne; Hoksrud, Aasne Fenne; Søberg, Helene L.; Zucknick, Manuela; Heide, Marte & Groven, Karen Synne
[Vis alle 7 forfattere av denne artikkelen]
(2022).
“Psychometric properties of the Norwegian foot function index revised short form”.
BMC Musculoskeletal Disorders.
23(1),
s. 1–10.
doi:
10.1186/s12891-022-05374-x.
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Background
Foot disorders affect up to one quarter of the adult population. Plantar fasciopathy is a common cause of foot pain associated with decreased activity level and quality of life. Patient-reported outcome measures are important in assessing the burden of a condition as well as in research on the effects of interventions. The Foot Function Index revised short form (FFI-RS) is a region specific questionnaire frequently used in research. This study aimed to cross-culturally adapt the FFI-RS into Norwegian and to test its psychometric properties.
Methods
The FFI-RS was translated into Norwegian (FFI-RSN) following international guidelines. 139 patients with foot disorders (88% with plantar fasciopathy) were included at baseline to measure internal consistency, explorative factor analysis, construct validity and floor and ceiling effects. 54 patients were included after 1 week for test-retest reliability and smallest detectable change analyses. 100 patients were included for responsiveness and minimal important change at 3 months.
Results
Cronbach’s alpha for internal consistency was 0.97 and factor analysis supported the use of the total score of the FFI-RSN. Two out of three predefined hypotheses were confirmed by assessing the construct validity with Spearman’s correlation coefficient. Quadratic weighted Kappa for test-retest reliability showed 0.91 (95% CI 0.86–0.96) and the smallest detectable change was 6.5%. The minimal important change was 8.4% and the area under the receiver operating characteristic curve for responsiveness was 0.78 (95% CI 0.69–0.87). We found no floor or ceiling effects on the total score of the FFI-RSN.
Conclusions
The present study showed excellent reliability of the FFI-RSN and supports the use of the total score of the questionnaire. Furthermore, we found the FFI-RSN to have acceptable responsiveness in relation to change in general health. Smallest detectable change, minimal important change and responsiveness were presented as novel results of the total score of the FFI-RS. FFI-RSN can be used to evaluate global foot health in clinical or research settings with Norwegian patients suffering from plantar fasciopathy.
Trial registration
Clinical Trials.gov NCT04207164. Initial release 01.11.19.
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Vitelli, Valeria; Fleischer, Thomas; Ankill, Jørgen; Arjas, Elja; Frigessi, Arnoldo & Kristensen, Vessela N.
[Vis alle 7 forfattere av denne artikkelen]
(2022).
Transcriptomic pan-cancer analysis using rank-based Bayesian inference.
Molecular Oncology.
ISSN 1574-7891.
00(0),
s. 1–16.
doi:
10.1002/1878-0261.13354.
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The analysis of whole genomes of pan-cancer data sets provides a challenge for researchers, and we contribute to the literature concerning the identification of robust subgroups with clear biological interpretation. Specifically, we tackle this unsupervised problem via a novel rank-based Bayesian clustering method. The advantages of our method are the integration and quantification of all uncertainties related to both the input data and the model, the probabilistic interpretation of final results to allow straightforward assessment of the stability of clusters leading to reliable conclusions, and the transparent biological interpretation of the identified clusters since each cluster is characterized by its top-ranked genomic features. We applied our method to RNA-seq data from cancer samples from 12 tumor types from the Cancer Genome Atlas. We identified a robust clustering that mostly reflects tissue of origin but also includes pan-cancer clusters. Importantly, we identified three pan-squamous clusters composed of a mix of lung squamous cell carcinoma, head and neck squamous carcinoma, and bladder cancer, with different biological functions over-represented in the top genes that characterize the three clusters. We also found two novel subtypes of kidney cancer that show different prognosis, and we reproduced known subtypes of breast cancer. Taken together, our method allows the identification of robust and biologically meaningful clusters of pan-cancer samples.
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Kolan, Shrikant; Li, Gaoyang; Grimolizzi, Franco; Sexton, Joseph; Kvien, Tore Kristian & Goll, Guro Løvik
[Vis alle 11 forfattere av denne artikkelen]
(2022).
Identification of SNPs associated with methotrexate treatment outcomes in patients with early rheumatoid arthritis.
Frontiers in Pharmacology.
13.
doi:
10.3389/fphar.2022.1075603.
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Methotrexate is one of the cornerstones of rheumatoid arthritis (RA) therapy. Genetic factors or single nucleotide polymorphisms (SNPs) are responsible for 15%–30% of the variation in drug response. Identification of clinically effective SNP biomarkers for predicting methotrexate (MTX) sensitivity has been a challenge. The aim of this study was to explore the association between the disease related outcome of MTX treatment and 23 SNPs in 8 genes of the MTX pathway, as well as one pro-inflammatory related gene in RA patients naïve to MTX. Categorical outcomes such as Disease Activity Score (DAS)-based European Alliance of Associations for Rheumatology (EULAR) non-response at 4 months, The American College of Rheumatology and EULAR (ACR/EULAR) non-remission at 6 months, and failure to sustain MTX monotherapy from 12 to 24 months were assessed, together with continuous outcomes of disease activity, joint pain and fatigue. We found that the SNPs rs1801394 in the MTRR gene, rs408626 in DHFR gene, and rs2259571 in AIF-1 gene were significantly associated with disease activity relevant continuous outcomes. Additionally, SNP rs1801133 in the MTHFR gene was identified to be associated with improved fatigue. Moreover, associations with p values at uncorrected significance level were found in SNPs and different categorical outcomes: 1) rs1476413 in the MTHFR gene and rs3784864 in ABCC1 gene are associated with ACR/EULAR non-remission; 2) rs1801133 in the MTHFR gene is associated with EULAR response; 3) rs246240 in the ABCC1 gene, rs2259571 in the AIF-1 gene, rs2274808 in the SLC19A1 gene and rs1476413 in the MTHFR gene are associated with failure to MTX monotherapy after 12–24 months. The results suggest that SNPs in genes associated with MTX activity may be used to predict MTX relevant-clinical outcomes in patients with RA.
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Zhao, Zhi; Zucknick, Manuela & Aittokallio, Tero Antero
(2022).
EnrichIntersect: an R package for custom set enrichment analysis and interactive visualization of intersecting sets.
Bioinformatics Advances.
2(1).
doi:
10.1093/bioadv/vbac073.
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Abstract Summary Enrichment analysis has been widely used to study whether predefined sets of genes or other molecular features are over-represented in a ranked list associated with a disease or other phenotype. However, computational tools that perform enrichment analysis and visualization are usually limited to predefined sets available from public databases. To make such analyses more flexible, we introduce an R package, EnrichIntersect, which enables enrichment analyses among any ranked features and user-defined custom sets. For interactive visualization of multiple covariates, such as genes or other features, which are associated with multiple phenotypes and multiple sample groups, such as drug responses in various cancer types, EnrichIntersect illustrates all associations at a glance, hence explicitly indicating intersecting covariates between multiple phenotypic variables and between multiple sample groups. Availability and implementation The EnrichIntersect R package is available at https://CRAN.R-project.org/package=EnrichIntersect via an open-source MIT license. A package installation process is described on CRAN at https://cran.r-project.org/. A user-manual description of features and function calls can be found from the vignette of our package on CRAN.
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Hanes, Robert; Ayuda-Duran, Maria del Pilar; Rønneberg, Leiv; Nakken, Sigve; Hovig, Eivind & Zucknick, Manuela
[Vis alle 7 forfattere av denne artikkelen]
(2022).
screenwerk: a modular tool for the design and analysis of drug combination screens.
Bioinformatics.
ISSN 1367-4803.
39(1).
doi:
10.1093/bioinformatics/btac840.
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Abstract Motivation There is a rapidly growing interest in high-throughput drug combination screening to identify synergizing drug interactions for treatment of various maladies, such as cancer and infectious disease. This creates the need for pipelines that can be used to design such screens, perform quality control on the data and generate data files that can be analyzed by synergy-finding bioinformatics applications. Results screenwerk is an open-source, end-to-end modular tool available as an R-package for the design and analysis of drug combination screens. The tool allows for a customized build of pipelines through its modularity and provides a flexible approach to quality control and data analysis. screenwerk is adaptable to various experimental requirements with an emphasis on precision medicine. It can be coupled to other R packages, such as bayesynergy, to identify synergistic and antagonistic drug interactions in cell lines or patient samples. screenwerk is scalable and provides a complete solution for setting up drug sensitivity screens, read raw measurements and consolidate different datasets, perform various types of quality control and analyze, report and visualize the results of drug sensitivity screens. Availability and implementation The R-package and technical documentation is available at https://github.com/Enserink-lab/screenwerk; the R source code is publicly available at https://github.com/Enserink-lab/screenwerk under GNU General Public License v3.0; bayesynergy is accessible at https://github.com/ocbe-uio/bayesynergy. Selected modules are available through Galaxy, an open-source platform for FAIR data analysis at https://oncotools.elixir.no Supplementary information Supplementary data are available at Bioinformatics online.
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Kristiansen, Oddrun; Roland, Marie Cecilie; Zucknick, Manuela; Reine, Trine M.; Kolset, Svein Olav & Henriksen, Tore
[Vis alle 8 forfattere av denne artikkelen]
(2022).
Maternal body mass index and placental weight: a role for fetal insulin, maternal insulin and leptin.
Journal of Endocrinological Investigation.
ISSN 0391-4097.
45,
s. 2105–2121.
doi:
10.1007/s40618-022-01842-2.
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Purpose
Placental weight (PW) has been found to mediate the main effect of maternal BMI on fetal size. Still, the BMI–PW association is poorly understood. Therefore, we aimed to explore potential explanatory variables, including gestational weight gain (GWG), early- and late-pregnancy circulating levels of maternal glucose, insulin, leptin, adiponectin, triglycerides, LDL-C, and HDL-C, and fetal insulin.
Methods
We included two studies of pregnant women from Oslo University Hospital, Norway: the prospective STORK (n = 263) and the cross-sectional 4-vessel method study (4-vessel; n = 165). We used multiple linear regression for data analyses. A non-linear BMI-PW association was observed, which leveled off from BMI25. Therefore, BMI <25 and ≥25 were analyzed separately (n = 170/122 and 93/43 for STORK/4-vessel). Confounding variables included maternal age, parity, and gestational age.
Results
PW increased significantly per kg m−2 only among BMI <25 (univariate model’s std.β[p] = 0.233 [0.002] vs. 0.074[0.48]/0.296[0.001] vs. −0.030[0.85] for BMI <25 vs. ≥25 in STORK/4-vessel). Maternal early- but not late-pregnancy insulin and term fetal insulin were associated with PW. The estimated effect of early pregnancy insulin was similar between the BMI groups but statistically significant only among BMI <25 (std.β[p] = 0.182[0.016] vs. 0.203[0.07] for BMI <25 vs. ≥25). Late pregnancy leptin was inversely associated with PW with a 1.3/1.7-fold greater effect among BMI ≥25 than BMI <25 in the STORK/4-vessel.
Conclusions
The BMI–PW association was non-linear: an association was observed for BMI <25 but not for BMI ≥25. Leptin may be involved in the non-linear association through a placental–adipose tissue interplay. Maternal early pregnancy insulin and fetal insulin at term were associated with PW.
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Zhao, Zhi; Wang, Shixiong; Zucknick, Manuela & Aittokallio, Tero Antero
(2022).
Tissue-specific identification of multi-omics features for pan-cancer drug response prediction.
iScience.
25(8).
doi:
10.1016/j.isci.2022.104767.
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Current statistical models for drug response prediction and biomarker identification fall short in leveraging the shared and unique information from various cancer tissues and multi-omics profiles. We developed mix-lasso model that introduces an additional sample group penalty term to capture tissue-specific effects of features on pan-cancer response prediction. The mix-lasso model takes into account both the similarity between drug responses (i.e., multi-task learning), and the heterogeneity between multi-omics data (multi-modal learning). When applied to large-scale pharmacogenomics dataset from Cancer Therapeutics Response Portal, mix-lasso enabled accurate drug response predictions and identification of tissue-specific predictive features in the presence of various degrees of missing data, drug-drug correlations, and high-dimensional and correlated genomic and molecular features that often hinder the use of statistical approaches in drug response modeling. Compared to tree lasso model, mix-lasso identified a smaller number of tissue-specific features, hence making the model more interpretable and stable for drug discovery applications.
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Degnes, Maren-Helene Langeland; Westerberg, Ane Cecilie; Zucknick, Manuela; Powell, Theresa L.; Jansson, Thomas & Henriksen, Tore
[Vis alle 8 forfattere av denne artikkelen]
(2022).
Placenta-derived proteins across gestation in healthy pregnancies—a novel approach to assess placental function?
BMC Medicine.
20.
doi:
10.1186/s12916-022-02415-z.
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ackground
Placenta-derived proteins in the systemic maternal circulation are suggested as potential biomarkers for placental function. However, the identity and longitudinal patterns of such proteins are largely unknown due to the inaccessibility of the human placenta and limitations in assay technologies. We aimed to identify proteins derived from and taken up by the placenta in the maternal circulation. Furthermore, we aimed to describe the longitudinal patterns across gestation of placenta-derived proteins as well as identify placenta-derived proteins that can serve as reference curves for placental function.
Methods
We analyzed proteins in plasma samples collected in two cohorts using the Somalogic 5000-plex platform. Antecubital vein samples were collected at three time points (gestational weeks 14–16, 22–24, and 30–32) across gestation in 70 healthy pregnancies in the longitudinal STORK cohort. In the cross sectional 4-vessel cohort, blood samples were collected simultaneously from the maternal antecubital vein (AV), radial artery (RA), and uterine vein (UV) during cesarean section in 75 healthy pregnancies. Placenta-derived proteins and proteins taken up by the placenta were identified using venoarterial differences (UV-RA). Placenta-derived proteins were defined as placenta-specific by comparison to the venoarterial difference in the antecubital vein-radial artery (AV-RA). These proteins were described longitudinally based on the STORK cohort samples using a linear mixed effects model per protein. Using a machine learning algorithm, we identified placenta-derived proteins that could predict gestational age, meaning that they closely tracked gestation, and were potential read-outs of placental function.
Results
Among the nearly 5000 measured proteins, we identified 256 placenta-derived proteins and 101 proteins taken up by the placenta (FDR < 0.05). Among the 256 placenta-derived proteins released to maternal circulation, 101 proteins were defined as placenta-specific. These proteins formed two clusters with distinct developmental patterns across gestation. We identified five placenta-derived proteins that closely tracked gestational age when measured in the systemic maternal circulation, termed a “placental proteomic clock.”
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Zhao, Zhi; Banterle, Marco; Bottolo, Leonardo; Richardson, Sylvia; Lewin, Alexandra & Zucknick, Manuela
(2021).
BayesSUR: An R package for high-dimensional multivariate Bayesian variable and covariance selection in linear regression.
Journal of Statistical Software.
100(11),
s. 1–32.
doi:
10.18637/jss.v100.i11.
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In molecular biology, advances in high-throughput technologies have made it possible to study complex multivariate phenotypes and their simultaneous associations with high-dimensional genomic and other omics data, a problem that can be studied with high-dimensional multi-response regression, where the response variables are potentially highly correlated. To this purpose, we recently introduced several multivariate Bayesian variable and covariance selection models, e.g., Bayesian estimation methods for sparse seemingly unrelated regression for variable and covariance selection. Several variable selection priors have been implemented in this context, in particular the hotspot detection prior for latent variable inclusion indicators, which results in sparse variable selection for associations between predictors and multiple phenotypes. We also propose an alternative, which uses a Markov random field (MRF) prior for incorporating prior knowledge about the dependence structure of the inclusion indicators. Inference of Bayesian seemingly unrelated regression (SUR) by Markov chain Monte Carlo methods is made computationally feasible by factorization of the covariance matrix amongst the response variables. In this paper we present BayesSUR, an R package, which allows the user to easily specify and run a range of different Bayesian SUR models, which have been implemented in C++ for computational efficiency. The R package allows the specification of the models in a modular way, where the user chooses the priors for variable selection and for covariance selection separately. We demonstrate the performance of sparse SUR models with the hotspot prior and spike-and-slab MRF prior on synthetic and real data sets representing eQTL or mQTL studies and in vitro anti-cancer drug screening studies as examples for typical applications.
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Madjar, Katrin; Zucknick, Manuela; Ickstadt, Katja & Rahnenführer, Jörg
(2021).
Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression.
BMC Bioinformatics.
22(1),
s. 1–29.
doi:
10.1186/s12859-021-04483-z.
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Background Important objectives in cancer research are the prediction of a patient’s risk based on molecular measurements such as gene expression data and the identification of new prognostic biomarkers (e.g. genes). In clinical practice, this is often challenging because patient cohorts are typically small and can be heterogeneous. In classical subgroup analysis, a separate prediction model is fitted using only the data of one specific cohort. However, this can lead to a loss of power when the sample size is small. Simple pooling of all cohorts, on the other hand, can lead to biased results, especially when the cohorts are heterogeneous. Results We propose a new Bayesian approach suitable for continuous molecular measurements and survival outcome that identifies the important predictors and provides a separate risk prediction model for each cohort. It allows sharing information between cohorts to increase power by assuming a graph linking predictors within and across different cohorts. The graph helps to identify pathways of functionally related genes and genes that are simultaneously prognostic in different cohorts. Conclusions Results demonstrate that our proposed approach is superior to the standard approaches in terms of prediction performance and increased power in variable selection when the sample size is small.
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Heinicke, Fatima; Zhong, Xiangfu; Flåm, Siri Tennebø; Breidenbach, Johannes; Leithaug, Magnus & Mæhlen, Marthe Thoresen
[Vis alle 14 forfattere av denne artikkelen]
(2021).
MicroRNA Expression Differences in Blood-Derived CD19+ B Cells of Methotrexate Treated Rheumatoid Arthritis Patients.
Frontiers in Immunology.
12.
doi:
10.3389/fimmu.2021.663736.
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Rheumatoid arthritis (RA) is a complex disease with a wide range of underlying susceptibility factors. Recently, dysregulation of microRNAs (miRNAs) in RA have been reported in several immune cell types from blood. However, B cells have not been studied in detail yet. Given the autoimmune nature of RA with the presence of autoantibodies, CD19+ B cells are a key cell type in RA pathogenesis and alterations in CD19+ B cell subpopulations have been observed in patient blood. Therefore, we aimed to reveal the global miRNA repertoire and to analyze miRNA expression profile differences in homogenous RA patient phenotypes in blood-derived CD19+ B cells. Small RNA sequencing was performed on CD19+ B cells of newly diagnosed untreated RA patients (n=10), successfully methotrexate (MTX) treated RA patients in remission (MTX treated RA patients, n=18) and healthy controls (n=9). The majority of miRNAs was detected across all phenotypes. However, significant expression differences between MTX treated RA patients and controls were observed for 27 miRNAs, while no significant differences were seen between the newly diagnosed patients and controls. Several of the differentially expressed miRNAs were previously found to be dysregulated in RA including miR-223-3p, miR-486-3p and miR-23a-3p. MiRNA target enrichment analysis, using the differentially expressed miRNAs and miRNA-target interactions from miRTarBase as input, revealed enriched target genes known to play important roles in B cell activation, differentiation and B cell receptor signaling, such as STAT3, PRDM1 and PTEN. Interestingly, many of those genes showed a high degree of correlated expression in CD19+ B cells in contrast to other immune cell types. Our results suggest important regulatory functions of miRNAs in blood-derived CD19+ B cells of MTX treated RA patients and motivate for future studies investigating the interactive mechanisms between miRNA and gene targets, as well as the possible predictive power of miRNAs for RA treatment response.
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Kristiansen, Oddrun; Zucknick, Manuela; Reine, Trine M.; Kolset, Svein Olav; Jansson, Thomas & Powell, Theresa L.
[Vis alle 9 forfattere av denne artikkelen]
(2021).
Mediators linking maternal weight to birthweight and neonatal fat mass in healthy pregnancies.
Journal of Clinical Endocrinology and Metabolism (JCEM).
ISSN 0021-972X.
106(7),
s. 1977–1993.
doi:
10.1210/clinem/dgab166.
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Abstract Context Lifestyle interventions have not efficaciously reduced complications caused by maternal weight on fetal growth, requiring insight into explanatory mediators. Objective We hypothesized that maternal mediators, including adiponectin, leptin, insulin, and glucose, mediate effects of pregestational BMI (pBMI) and gestational weight gain (GWG) on birthweight and neonatal fat mass percentage (FM%) through placental weight and fetal mediators, including insulin levels (Ifv) and venous-arterial glucose difference (ΔGfva). Hypothesized confounders were maternal age, gestational age, and parity. Methods A cross-sectional study of healthy mother-offspring-pairs (n = 165) applying the 4-vessel in vivo sampling method at Oslo University Hospital, Norway. We obtained pBMI, GWG, birthweight, and placental weight. FM% was available and calculated for a subcohort (n = 84). We measured circulating levels of adiponectin, leptin, glucose, and insulin and performed path analysis and traditional mediation analyses based on linear regression models. Results The total effect of pBMI and GWG on newborn size was estimated to be 30 g (range, 16-45 g) birthweight and 0.17 FM% (range, 0.04-0.29 FM%) per kg∙m–2 pBMI and 31 g (range, 18-44 g) and 0.24 FM% (range, 0.10-0.37 FM%) per kg GWG. The placental weight was the main mediator, mediating 25-g birthweight and 0.11 FM% per kg∙m–2 pBMI and 25-g birthweight and 0.13 FM% per kg GWG. The maternal mediators mediated a smaller part of the effect of pBMI (3.8-g birthweight and 0.023 FM% per kg∙m–2 pBMI) but not GWG. Conclusion Placental weight was the main mediator linking pBMI and GWG to birthweight and FM%. The effect of pBMI, but not GWG, on birthweight and FM%, was also mediated via the maternal and fetal mediators.
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Klevberg, Gunvor Lilleholt; Jahnsen, Reidun Birgitta; Elkjær, Sonja & Zucknick, Manuela
(2021).
Hand use development in children with unilateral cerebral palsy.
Developmental Medicine & Child Neurology.
ISSN 0012-1622.
63(12),
s. 1462–1468.
doi:
10.1111/dmcn.14957.
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Aim To describe the development of hand use during bimanual activities among children with unilateral cerebral palsy (CP). Method A cohort of 166 children (79 females, 87 males; age range 18mo–13y, mean [SD] age at first assessment 37.6mo [20.5mo]) with unilateral CP, registered in the Norwegian CP Follow-up Program with two or more Assisting Hand Assessments (AHAs), were included in this longitudinal study comprising 524 AHAs. Developmental limits and rates were estimated by non-linear mixed effects models and compared between a stable limit model (SLM) and a peak and decline model. Development was described according to Manual Ability Classification System (MACS) levels and AHA performance at 18 months of age (AHA-18). Results Children in MACS level I, or in the high AHA-18 group, reached highest limits and had the most rapid development (p<0.001). The developmental trajectories were different between MACS levels I, II, and III and between the high, moderate, and low AHA-18 groups. Seventy-five per cent of the children reached 90% of their estimated limit at 5 years 10 months or earlier. The SLM showed the best model fit (Akaike information criterion: 4008.99). Interpretation Most children approached a steady performance limit before 6 years of age. Although children in MACS levels I and II reached 90% of the expected limit at 3 and 4 years respectively, the corresponding age was 8 years for children in MACS level III. The better model fit for the SLM indicates that children with unilateral CP maintain their attained limit of hand use to at least the age of 13 years.
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Schellhorn, Till; Zucknick, Manuela; Askim, Torunn; Munthe-Kaas, Ragnhild; Ihle-Hansen, Hege & Seljeseth, Yngve Müller
[Vis alle 13 forfattere av denne artikkelen]
(2021).
Pre-stroke cognitive impairment is associated with vascular imaging pathology: a prospective observational study.
BMC Geriatrics.
21:362(362),
s. 1–10.
doi:
10.1186/s12877-021-02327-2.
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Background: Chronic brain pathology and pre-stroke cognitive impairment (PCI) is predictive of post-stroke
dementia. The aim of the current study was to measure pre-stroke neurodegenerative and vascular disease burden
found on brain MRI and to assess the association between pre-stroke imaging pathology and PCI, whilst also
looking for potential sex differences.
Methods: This prospective brain MRI cohort is part of the multicentre Norwegian cognitive impairment after stroke
(Nor-COAST) study. Patients hospitalized with acute ischemic or hemorrhagic stroke were included from five
participating stroke units. Visual rating scales were used to categorize baseline MRIs (N = 410) as vascular,
neurodegenerative, mixed, or normal, based on the presence of pathological imaging findings. Pre-stroke cognition
was assessed by interviews of patients or caregivers using the Global Deterioration Scale (GDS). Stroke severity was
assessed with the National Institute of Health Stroke Scale (NIHSS). Univariate and multiple logistic regression
analyses were performed to investigate the association between imaging markers, PCI, and sex.
Results: Patients’ (N = 410) mean (SD) age was 73.6 (±11) years; 182 (44%) participants were female, the mean (SD)
NIHSS at admittance was 4.1 (±5). In 68% of the participants, at least one pathological imaging marker was found. Medial temporal lobe atrophy (MTA) was present in 30% of patients, white matter hyperintensities (WMH) in 38% of patients and lacunes in 35% of patients. PCI was found in 30% of the patients. PCI was associated with
cerebrovascular pathology (OR 2.5; CI = 1.4 to 4.5, p = 0.001) and mixed pathology (OR 3.4; CI = 1.9 to 6.1, p = 0.001) but was not associated with neurodegeneration (OR 1.0; CI = 0.5 to 2.2; p = 0.973). Pathological MRI markers,
including MTA and lacunes, were more prevalent among men, as was a history of clinical stroke prior to the index
stroke. The OR of PCI for women was not significantly increased (OR 1.2; CI = 0.8 to 1.9; p = 0.3).
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Rønneberg, Leiv; Cremaschi, Andrea; Hanes, Robert; Enserink, Jorrit & Zucknick, Manuela
(2021).
bayesynergy: flexible Bayesian modelling of synergistic interaction effects in in vitro drug combination experiments.
Briefings in Bioinformatics.
ISSN 1467-5463.
22(6),
s. 1–12.
doi:
10.1093/bib/bbab251.
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Abstract The effect of cancer therapies is often tested pre-clinically via in vitro experiments, where the post-treatment viability of the cancer cell population is measured through assays estimating the number of viable cells. In this way, large libraries of compounds can be tested, comparing the efficacy of each treatment. Drug interaction studies focus on the quantification of the additional effect encountered when two drugs are combined, as opposed to using the treatments separately. In the bayesynergy R package, we implement a probabilistic approach for the description of the drug combination experiment, where the observed dose response curve is modelled as a sum of the expected response under a zero-interaction model and an additional interaction effect (synergistic or antagonistic). Although the model formulation makes use of the Bliss independence assumption, we note that the posterior estimates of the dose–response surface can also be used to extract synergy scores based on other reference models, which we illustrate for the Highest Single Agent model. The interaction is modelled in a flexible manner, using a Gaussian process formulation. Since the proposed approach is based on a statistical model, it allows the natural inclusion of replicates, handles missing data and uneven concentration grids, and provides uncertainty quantification around the results. The model is implemented in the open-source Stan programming language providing a computationally efficient sampler, a fast approximation of the posterior through variational inference, and features parallel processing for working with large drug combination screens.
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Helset, Elin; Nordøy, Ingvild; Sporsem, Hilde Margrete; Bakke, Victoria Desiree; Bugge, Jan F & Gammelsrud, Karianne Wiger
[Vis alle 8 forfattere av denne artikkelen]
(2020).
Factors increasing the risk of inappropriate vancomycin therapy in ICU patients: A prospective observational study.
Acta Anaesthesiologica Scandinavica.
ISSN 0001-5172.
64(9),
s. 1295–1304.
doi:
10.1111/aas.13658.
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Pietka, Wojciech; Sundnes, Olav; Hammarström, Clara Louise; Zucknick, Manuela; Khnykin, Denis & Haraldsen, Guttorm
(2020).
Lack of interleukin-33 and its receptor does not prevent calcipotriol-induced atopic dermatitis-like inflammation in mice.
Scientific Reports.
10:6451,
s. 1–8.
doi:
10.1038/s41598-020-63410-z.
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Current studies addressing the influence of interleukin-33 or its receptor (IL-33R/ST2) on development of atopic dermatitis-like inflammation in mice have reported conflicting results. We compared the response in single- and double-deficient IL-33−/−/ST2−/− C57BL/6J BomTac mice in the well-established calcipotriol-induced model of atopic dermatitis. All genotypes (groups of up to 14 mice) developed atopic dermatitis-like inflammation yet we observed no biologically relevant difference between groups in gross anatomy or ear thickness. Moreover, histological examination of skin revealed no differences in mononuclear leukocyte and granulocyte infiltration nor Th2 cytokine levels (IL-4 and IL-13). Finally, skin CD45+ cells and CD3+ cells were found at similar densities across all groups. Our findings indicate that lack of interleukin-33 and its receptor ST2 does not prevent the development of AD-like skin inflammation.
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Langseth, Miriam Sjåstad; Andersen, Geir Øystein; Husebye, Trygve Guttorm; Arnesen, Harald; Zucknick, Manuela & Solheim, Svein
[Vis alle 10 forfattere av denne artikkelen]
(2020).
Neutrophil extracellular trap components and myocardial recovery in post-ischemic acute heart failure.
PLOS ONE.
15:e0241333(10),
s. 1–14.
doi:
10.1371/journal.pone.0241333.
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Objective The role of neutrophil extracellular traps (NETs) in acute heart failure is unknown. We recently showed that interleukin 8, a putative NETs stimulator, was associated with myocardial recovery in acute heart failure complicating ST-elevation myocardial infarction (STEMI). In this exploratory post-hoc study, we aimed to investigate the role of NETs components in relation to myocardial function and interleukin 8 in STEMI patients with symptomatic acute heart failure. Methods In 61 STEMI patients developing acute heart failure within 48 hours of successful revascularization, wall motion score index (WMSI), global longitudinal strain (GLS) and left ventricular ejection fraction (LVEF) were assessed by echocardiography at baseline and on day 5. Blood drawn at baseline and days 1, 2 and 5 was used to quantify double-stranded DNA (dsDNA), myeloperoxidase-DNA complexes (MPO-DNA) and citrullinated histone 3 (CitH3). The area under the curve (AUC) of each NETs marker and interleukin 8 was approximated for the first 5 days. Results dsDNAAUC and MPO-DNAAUC correlated significantly with change in WMSI from baseline to day 5 (rs = 0.28 for both, p≤0.05), whereas NETs AUCs did not correlate with changes in GLS and LVEF. dsDNAAUC was significantly correlated with interleukin 8AUC (r = 0.40, p = 0.003). However, mixed model regression could not identify a significant effect of the NETs components on myocardial function parameters. Conclusions In this cohort with acute heart failure complicating STEMI, NETs components were partly correlated with myocardial function and interleukin 8 levels, yet no causal relationship between NETs components and myocardial recovery could be established.
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Heinicke, Fatima; Zhong, Xiangfu; Zucknick, Karola Manuela; Breidenbach, Johannes; Sundaram, Arvind Yegambaram Meenakshi & Flåm, Siri Tennebø
[Vis alle 11 forfattere av denne artikkelen]
(2020).
An extension to: Systematic assessment of commercially available low-input miRNA library preparation kits.
RNA Biology.
ISSN 1547-6286.
17(9),
s. 1284–1292.
doi:
10.1080/15476286.2020.1761081.
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High-throughput sequencing has emerged as the favoured method to study microRNA (miRNA) expression, but biases introduced during library preparation have been reported. We recently compared the performance (sensitivity, reliability, titration response and differential expression) of six commercially-available kits on synthetic miRNAs and human RNA, where library preparation was performed by the vendors. We hereby supplement this study with data from two further commonly used kits (NEBNext, NEXTflex) whose manufacturers initially declined to participate. NEXTflex demonstrated the highest sensitivity, which may reflect its use of partially-randomized adapter sequences, but overall performance was lower than the QIAseq and TailorMix kits. NEBNext showed intermediate performance. We reaffirm that biases are kit specific, complicating the comparison of miRNA datasets generated using different kits.
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Mai, The Tien; Rønneberg, Leiv; Zhao, Zhi; Zucknick, Manuela & Corander, Jukka
(2020).
Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure.
Lecture Notes in Computer Science (LNCS).
ISSN 0302-9743.
12313,
s. 67–79.
doi:
10.1007/978-3-030-63061-4_7.
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Guldvik, Ingrid Jenny; Zuber, Verena; Braadland, Peder Rustøen; Grytli, Helene Hartvedt; Ramberg, Håkon Andre & Lilleby, Wolfgang
[Vis alle 18 forfattere av denne artikkelen]
(2020).
Identification and Validation of Leucine-rich alpha-2-glycoprotein 1 as a Noninvasive Biomarker for Improved Precision in Prostate Cancer Risk Stratification.
European Urology Open Science.
ISSN 2666-1691.
21,
s. 51–61.
doi:
10.1016/j.euros.2020.08.007.
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Background More accurate risk assessments are needed to improve prostate cancer management. Objective To identify blood-based protein biomarkers that provided prognostic information for risk stratification. Design, setting, and participants Mass spectrometry was used to identify biomarker candidates from blood, and validation studies were performed in four independent cohorts retrospectively collected between 1988 and 2015. Outcome measurements and statistical analysis The primary outcome objectives were progression-free survival, prostate cancer–specific survival (PCSS), and overall survival. Statistical analyses to assess survival and model performance were performed. Results and limitation Serum leucine-rich α-2-glycoprotein 1 (LRG1) was found to be elevated in fatal prostate cancer. LRG1 provided prognostic information independent of metastasis and increased the accuracy in predicting PCSS, particularly in the first 3 yr. A high LRG1 level is associated with an average of two-fold higher risk of disease-progression and mortality in both high-risk and metastatic patients. However, our study design, with a retrospective analysis of samples spanning several decades back, limits the assessment of the clinical utility of LRG1 in today’s clinical practice. Thus, independent prospective studies are needed to establish LRG1 as a clinically useful biomarker for patient management. Conclusions High blood levels of LRG1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer, and LRG1 increased the accuracy of risk stratification of prostate cancer patients. Patient summary High blood levels of leucine-rich α-2-glycoprotein 1 are unfavourable in newly diagnosed high-risk and metastatic prostate cancer.
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Bragstad, Line Kildal; Hjelle, Ellen Gabrielsen; Zucknick, Manuela; Sveen, Unni; Thommessen, Bente & Bronken, Berit Arnesveen
[Vis alle 13 forfattere av denne artikkelen]
(2020).
The effects of a dialogue-based intervention to promote psychosocial well-being after stroke: a randomized controlled trial.
Clinical Rehabilitation.
ISSN 0269-2155.
34(8),
s. 1056–1071.
doi:
10.1177/0269215520929737.
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Objective:
To evaluate the effect of a dialogue-based intervention targeting psychosocial well-being at 12 months post-stroke.
Design:
Multicenter, prospective, randomized, assessor-blinded, controlled trial with two parallel groups.
Setting:
Community.
Subjects:
Three-hundred and twenty-two adults (⩾18 years) with stroke within the last four weeks were randomly allocated into intervention group (n = 166) or control group (n = 156).
Interventions:
The intervention group received a dialogue-based intervention to promote psychosocial well-being, comprising eight individual 1–1½ hour sessions delivered during the first six months post-stroke.
Main measures:
The primary outcome measure was the General Health Questionnaire-28 (GHQ-28). Secondary outcome measures included the Stroke and Aphasia Quality of Life Scale-39g, the Sense of Coherence scale, and the Yale Brown single-item questionnaire.
Results:
The mean (SD) age of the participants was 66.8 (12.1) years in the intervention group and 65.7 (13.3) years in the control group. At 12 months post-stroke, the mean (SE) GHQ-28 score was 20.6 (0.84) in the intervention group and 19.9 (0.85) in the control group. There were no between-group differences in psychosocial well-being at 12 months post-stroke (mean difference: −0.74, 95% confidence interval (CI): −3.08, 1.60). The secondary outcomes showed no statistically significant between-group difference in health-related quality of life, sense of coherence, or depression at 12 months.
Conclusion:
The results of this trial did not demonstrate lower levels of emotional distress and anxiety or higher levels of health-related quality of life in the intervention group (dialogue-based intervention) as compared to the control group (usual care) at 12 months post-stroke.
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Maros, Máté E.; Capper, David; Jones, David T.; Hovestadt, Volker; Deimling, Andreas von & Pfister, Stefan M
[Vis alle 9 forfattere av denne artikkelen]
(2020).
Machine learning workflows to estimate class probabilities for precision cancer diagnostics on DNA methylation microarray data.
Nature Protocols.
ISSN 1754-2189.
15,
s. 479–512.
doi:
10.1038/s41596-019-0251-6.
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DNA methylation data-based precision cancer diagnostics is emerging as the state of the art for molecular tumor classification. Standards for choosing statistical methods with regard to well-calibrated probability estimates for these typically highly multiclass classification tasks are still lacking. To support this choice, we evaluated well-established machine learning (ML) classifiers including random forests (RFs), elastic net (ELNET), support vector machines (SVMs) and boosted trees in combination with post-processing algorithms and developed ML workflows that allow for unbiased class probability (CP) estimation. Calibrators included ridge-penalized multinomial logistic regression (MR) and Platt scaling by fitting logistic regression (LR) and Firth’s penalized LR. We compared these workflows on a recently published brain tumor 450k DNA methylation cohort of 2,801 samples with 91 diagnostic categories using a 5 × 5-fold nested cross-validation scheme and demonstrated their generalizability on external data from The Cancer Genome Atlas. ELNET was the top stand-alone classifier with the best calibration profiles. The best overall two-stage workflow was MR-calibrated SVM with linear kernels closely followed by ridge-calibrated tuned RF. For calibration, MR was the most effective regardless of the primary classifier. The protocols developed as a result of these comparisons provide valuable guidance on choosing ML workflows and their tuning to generate well-calibrated CP estimates for precision diagnostics using DNA methylation data. Computation times vary depending on the ML algorithm from <15 min to 5 d using multi-core desktop PCs. Detailed scripts in the open-source R language are freely available on GitHub, targeting users with intermediate experience in bioinformatics and statistics and using R with Bioconductor extensions.
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Joshi, Sarita; Angelis, Paula De; Zucknick, Manuela; Schjølberg, Aasa Rambæk; Andersen, Solveig Norheim & Clausen, Ole Petter Fraas
(2020).
Role of the Wnt signaling pathway in keratoacanthoma.
Cancer Reports.
3(2),
s. 1–11.
doi:
10.1002/cnr2.1219.
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Zhao, Zhi & Zucknick, Manuela
(2020).
Structured penalized regression for drug sensitivity prediction.
Journal of the Royal Statistical Society, Series C (Applied Statistics).
ISSN 0035-9254.
69(3),
s. 525–545.
doi:
10.1111/rssc.12400.
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Large‐scale in vitro drug sensitivity screens are an important tool in personalized oncology to predict the effectiveness of potential cancer drugs. The prediction of the sensitivity of cancer cell lines to a panel of drugs is a multivariate regression problem with high dimensional heterogeneous multiomics data as input data and with potentially strong correlations between the outcome variables which represent the sensitivity to the different drugs. We propose a joint penalized regression approach with structured penalty terms which enable us to utilize the correlation structure between drugs with group‐lasso‐type penalties and at the same time address the heterogeneity between ‘omics’ data sources by introducing data‐source‐specific penalty factors to penalize different data sources differently. By combining integrative penalty factors (IPFs) with the tree‐guided group lasso, we create a method called ‘IPF‐tree‐lasso’. We present a unified framework to transform more general IPF‐type methods to the original penalized method. Because the structured penalty terms have multiple parameters, we demonstrate how the interval search ‘Efficient parameter selection via global optimization’ algorithm can be used to optimize multiple penalty parameters efficiently. Simulation studies show that IPF‐tree‐lasso can improve the prediction performance compared with other lasso‐type methods, in particular for heterogeneous sources of data. Finally, we employ the new methods to analyse data from the ‘Genomics of drug sensitivity in cancer’ project.
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Hjelle, Ellen Gabrielsen; Bragstad, Line Kildal; Zucknick, Manuela; Kirkevold, Marit; Thommessen, Bente & Sveen, Unni
(2019).
The General Health Questionnaire-28 (GHQ-28) as an outcome measurement in a randomized controlled trial in a Norwegian stroke population.
BMC Psychology.
7(18).
doi:
10.1186/s40359-019-0293-0.
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Background: Several studies have documented the variety of post-stroke psychosocial challenges, which are complex, multifaceted, and affect a patient’s rehabilitation and recovery. Due to the consequences of these challenges, psychosocial well-being should be considered an important outcome of the stroke rehabilitation. Thus, a valid and reliable instrument that is appropriate for the stroke population is required. The factor structure of the Norwegian version of GHQ-28 has not previously been examined when applied to a stroke population. The purpose of this study was to explore the psychometric properties of the GHQ-28 when applied in the stroke population included in the randomized controlled trial; “Psychosocial well-being following stroke”, by evaluating the internal consistency, exploring the factor structure, construct validity and measurement invariance. Methods: Data were obtained from 322 individuals with a stroke onset within the past month. The Kaiser-Meyer-Olkin (KMO) test was used to test the sampling adequacy for exploratory factor analysis, and the Bartlett’s test of sphericity was used to test equal variances. Internal consistency was analysed using Cronbach’s alpha. The factor structure of the GHQ-28 was evaluated by exploratory factor analysis (EFA), and a confirmatory factor analysis (CFA) was used to determine the goodness of fit to the original structure of the outcome measurement. Measurement invariance for two time points was evaluated by configural, metric and scalar invariance. Results: The results from the EFA supported the four-factor dimensionality, but some of the items were loaded on different factors compared to those of the original structure. The differences resulted in a reduced goodness of fit in the CFA. Measurement invariance at two time points was confirmed. Conclusions: The change in mean score from one to six months on the GHQ-28 and the factor composition are assumed to be affected by characteristics in the stroke population. The results, when applying the GHQ-28 in a stroke population, and sub-factor analysis based on the original factor structure should be interpreted with caution. Trial registration: ClinicalTrials.gov, NCT02338869, registered 10/04/2014.
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Nguyen, Chinh BKrong; Kumar, Surendra; Zucknick, Manuela; Kristensen, Vessela N.; Gjerstad, Johannes & Nilsen, Hilde Loge
[Vis alle 7 forfattere av denne artikkelen]
(2019).
Associations between clinical symptoms, plasma norepinephrine and deregulated immune gene networks in subgroups of adolescent with Chronic Fatigue Syndrome.
Brain, Behavior, and Immunity.
ISSN 0889-1591.
76,
s. 82–96.
doi:
10.1016/j.bbi.2018.11.008.
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Background
Chronic Fatigue Syndrome (CFS) is one of the most important causes of disability among adolescents while limited knowledge exists on genetic determinants underlying disease pathophysiology.
Methods
We analyzed deregulated immune-gene modules using Pathifier software on whole blood gene expression data (29 CFS patients, 18 controls). Deconvolution of immune cell subtypes based on gene expression profile was performed using CIBERSORT. Supervised consensus clustering on pathway deregulation score (PDS) was used to define CFS subgroups. Associations between PDS and immune, neuroendocrine/autonomic and clinical markers were examined. The impact of plasma norepinephrine level on clinical markers over time was assessed in a larger cohort (91 patients).
Results
A group of 29 immune-gene sets was shown to differ patients from controls and detect subgroups within CFS. Group 1P (high PDS, low norepinephrine, low naïve CD4+ composition) had strong association with levels of serum C-reactive protein and Transforming Growth Factor-beta. Group 2P (low PDS, high norepinephrine, high naïve CD4+ composition) had strong associations with neuroendocrine/autonomic markers. The corresponding plasma norepinephrine level delineated 91 patients into two subgroups with significant differences in fatigue score.
Conclusion
We identified 29 immune-gene sets linked to plasma norepinephrine level that could delineate CFS subgroups. Plasma norepinephrine stratification revealed that lower levels of norepinephrine were associated with higher fatigue. Our data suggests potential involvement of neuro-immune dysregulation and genetic stratification in CFS.
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Heinicke, Fatima; Zhong, Xiangfu; Zucknick, Manuela; Breidenbach, Johannes; Sundaram, Arvind Yegambaram Meenakshi & Flåm, Siri Tennebø
[Vis alle 21 forfattere av denne artikkelen]
(2019).
Systematic assessment of commercially available low-input miRNA library preparation kits.
RNA Biology.
ISSN 1547-6286.
17(1),
s. 75–86.
doi:
10.1080/15476286.2019.1667741.
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High-throughput sequencing is increasingly favoured to assay the presence and abundance of microRNAs (miRNAs) in biological samples, even from low RNA amounts, and a number of commercial vendors now offer kits that allow miRNA sequencing from sub-nanogram (ng) inputs. Although biases introduced during library preparation have been documented, the relative performance of current reagent kits has not been investigated in detail. Here, six commercial kits capable of handling <100ng total RNA input were used for library preparation, performed by kit manufactures, on synthetic miRNAs of known quantities and human total RNA samples. We compared the performance of miRNA detection sensitivity, reliability, titration response and the ability to detect differentially expressed miRNAs. In addition, we assessed the use of unique molecular identifiers (UMI) sequence tags in one kit. We observed differences in detection sensitivity and ability to identify differentially expressed miRNAs between the kits, but none were able to detect the full repertoire of synthetic miRNAs. The reliability within the replicates of all kits was good, while larger differences were observed between the kits, although none could accurately quantify the relative levels of the majority of miRNAs. UMI tags, at least within the input ranges tested, offered little advantage to improve data utility. In conclusion, biases in miRNA abundance are heavily influenced by the kit used for library preparation, suggesting that comparisons of datasets prepared by different procedures should be made with caution. This article is intended to assist researchers select the most appropriate kit for their experimental conditions.
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Øystese, Kristin Astrid Berland; Hisanawi, Sheren; Zucknick, Manuela; Bollerslev, Jens & Ringstad, Geir
(2019).
Are volume measurements of non-functioning pituitary adenomas reliable?
Endocrine.
ISSN 1355-008X.
63(1),
s. 171–176.
doi:
10.1007/s12020-018-1752-8.
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Hjelle, Ellen Gabrielsen; Bragstad, Line Kildal; Kirkevold, Marit; Zucknick, Manuela; Bronken, Berit Arnesveen & Martinsen, Randi
[Vis alle 11 forfattere av denne artikkelen]
(2019).
Effect of a dialogue-based intervention on psychosocial well-being 6 months after stroke in Norway: A randomized controlled trial.
Journal of Rehabilitation Medicine.
ISSN 1650-1977.
51(8),
s. 557–565.
doi:
10.2340/16501977-2585.
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Abstract
Objective: To evaluate the effect of a dialogue-based intervention on psychosocial well-being 6 months after stroke.
Design: Multicentre, prospective, randomized controlled trial.
Subjects: Adults (aged ≥ 18 years) who had their first or recurrent stroke within the last month, were medically stable, had sufficient cognitive functioning to participate and understood and spoke Norwegian.
Methods: A total of 322 participants were randomly assigned to the intervention (n = 166) or control (n = 156) group. Participants in the intervention group received up to 8 individual sessions aimed at supporting the coping and life skills of stroke survivors in addition to usual care. The primary outcome was the proportion of participants with normal mood measured by the General Health Questionnaire-28 (GHQ-28). The secondary outcomes included health-related quality of life (Stroke and Aphasia Quality of Life Scale; SAQOL-39g), depression (Yale-Brown single-item questionnaire; Yale) and sense of coherence (SOC-13).
Results: After controlling for the baseline values, no significant benefit was found in the intervention group over the control group (odds ratio (OR): 0.898: 95% confidence interval (95% CI): 0.54-1.50, p = 0.680) 6 months post-stroke.
Conclusion: Psychosocial well-being improved during the first 6 months after stroke in both arms of the trial, but no statistically significant benefit of the dialogue-based intervention was found compared with usual care.
Lay Abstract
The aim of this study was to evaluate the effect of a dialogue-based intervention on psychosocial well-being 6 months after stroke. A total of 322 participants were assigned to an intervention (= 166) or control (= 156) group. Participants in the intervention group received up to 8 individual sessions aimed at supporting the coping and life skills of stroke survivors in addition to usual care. Psychosocial well-being improved during the first 6 months after the stroke in both arms of the trial. However, no benefit of the dialogue-based intervention was found compared with usual care.
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Menden, Michael P.; Wang, Dennis; Mason, Mike J.; Szalai, Bence; Bulusu, Krishna C. & Guan, Yuanfang
[Vis alle 27 forfattere av denne artikkelen]
(2019).
Community assessment to advance computational prediction of cancer drug combinations in a pharmacogenomic screen.
Nature Communications.
10:2674,
s. 1–17.
doi:
10.1038/s41467-019-09799-2.
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The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number of possible combinations is vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large drug combination dataset, consisting of 11,576 experiments from 910 combinations across 85 molecularly characterized cancer cell lines, and results of a DREAM Challenge to evaluate computational strategies for predicting synergistic drug pairs and biomarkers. 160 teams participated to provide a comprehensive methodological development and benchmarking. Winning methods incorporate prior knowledge of drug-target interactions. Synergy is predicted with an accuracy matching biological replicates for >60% of combinations. However, 20% of drug combinations are poorly predicted by all methods. Genomic rationale for synergy predictions are identified, including ADAM17 inhibitor antagonism when combined with PIK3CB/D inhibition contrasting to synergy when combined with other PI3K-pathway inhibitors in PIK3CA mutant cells.
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Schulze-Edinghausen, Lena; Dürr, Claudia; Öztürk, Selcen; Zucknick, Manuela; Benner, Axel & Kalter, Verena
[Vis alle 12 forfattere av denne artikkelen]
(2019).
Dissecting the Prognostic Significance and Functional Role of Progranulin in Chronic Lymphocytic Leukemia.
Cancers.
11(6),
s. 822–822.
doi:
10.3390/cancers11060822.
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Chronic lymphocytic leukemia (CLL) is known for its strong dependency on the tumor microenvironment. We found progranulin (GRN), a protein that has been linked to inflammation and cancer, to be upregulated in the serum of CLL patients compared to healthy controls, and increased GRN levels to be associated with an increased hazard for disease progression and death. This raised the question of whether GRN is a functional driver of CLL. We observed that recombinant GRN did not directly affect viability, activation, or proliferation of primary CLL cells in vitro. However, GRN secretion was induced in co-cultures of CLL cells with stromal cells that enhanced CLL cell survival. Gene expression profiling and protein analyses revealed that primary mesenchymal stromal cells (MSCs) in co-culture with CLL cells acquire a cancer-associated fibroblast-like phenotype. Despite its upregulation in the co-cultures, GRN treatment of MSCs did not mimic this effect. To test the relevance of GRN for CLL in vivo, we made use of the Eμ-TCL1 CLL mouse model. As we detected strong GRN expression in myeloid cells, we performed adoptive transfer of Eμ-TCL1 leukemia cells to bone marrow chimeric Grn−/− mice that lack GRN in hematopoietic cells. Thereby, we observed that CLL-like disease developed comparable in Grn−/− chimeras and respective control mice. In conclusion, serum GRN is found to be strongly upregulated in CLL, which indicates potential use as a prognostic marker, but there is no evidence that elevated GRN functionally drives the disease.
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Volchenkov, Roman; Matthews, Jason; Zucknick, Manuela & Skålhegg, Bjørn Steen
(2019).
Shared epitope is associated with the reactivity of Th17 cells to cigarette smoke extract regardless of smoking history.
Cellular & Molecular Immunology.
ISSN 1672-7681.
16(7),
s. 674–675.
doi:
10.1038/s41423-019-0230-4.
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Klevberg, Gunvor Lilleholt; Elvrum, Ann-Kristin; Zucknick, Manuela; Elkjær, Sonja; Østensjø, Sigrid & Krumlinde-Sundholm, Lena
[Vis alle 8 forfattere av denne artikkelen]
(2018).
Development of bimanual performance in young children with cerebral palsy.
Developmental Medicine & Child Neurology.
ISSN 0012-1622.
60(5),
s. 490–497.
doi:
10.1111/dmcn.13680.
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Aim To describe the development of bimanual performance among young children with unilateral or bilateral cerebral palsy (CP). Method A population‐based sample of 102 children (53 males, 49 females), median age 28.5 months (interquartile range [IQR] 16mo) at first assessment and 47 months (IQR 18mo) at last assessment, was assessed half‐yearly with the Assisting Hand Assessment (AHA) or the Both Hands Assessment (BoHA) for a total of 329 assessments. Developmental limits and rates were estimated by nonlinear mixed‐effects models. Developmental trajectories were compared between levels of manual ability (Mini‐Manual Ability Classification System [Mini‐MACS] and MACS) and AHA or BoHA performance at 18 months of age (AHA‐18/BoHA‐18) for both CP subgroups, and additionally between children with bilateral CP with symmetric or asymmetric hand use. Results For both CP subgroups, children classified in Mini‐MACS/MACS level I, and those with high AHA‐18 or BoHA‐18 reached the highest limits of performance. For children with bilateral CP the developmental change was small, and children with symmetric hand use reached the highest limits. Interpretation Mini‐MACS/MACS levels and AHA‐18 or BoHA‐18 distinguished between various developmental trajectories both for children with unilateral and bilateral CP. Children with bilateral CP changed their performance to a smaller extent than children with unilateral CP.
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Tanbo, Tom Gunnar; Zucknick, Manuela & Eskild, Anne
(2018).
Maternal concentrations of human chorionic gonadotrophin in very early IVF pregnancies and duration of pregnancy: a follow-up study.
Reproductive Biomedicine Online.
ISSN 1472-6483.
37(2),
s. 208–215.
doi:
10.1016/j.rbmo.2018.04.048.
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Research question Are maternal concentrations of human chorionic gonadotropin (HCG) on a fixed day after embryo transfer associated with duration of pregnancy? Design A follow-up study of 1917 singleton pregnancies after IVF was performed. Embryos were cultured for 2 days and maternal HCG concentration quantified on day 12 after embryo transfer. Duration of pregnancy was obtained from the Medical Birth Registry of Norway. Association of HCG concentration (log2-transformed) with duration of pregnancy was estimated as hazard ratios (HR) with 95% confidence intervals (CI) by applying Cox regression proportional hazard models, where time to delivery for pregnancies shortened because of planned Caesarean delivery or induction of labour was treated as censored. Results The estimated median duration of pregnancy from embryo transfer was 266 days (95% CI 266–267 days). Maternal concentration of HCG on day 12 after embryo transfer varied from 1 to 588 IU/l (median 117 IU/l). Duration of pregnancy decreased by increasing HCG concentration, significantly in pregnancies delivered at full term ((257–270 days after embryo transfer; HR 1.127, 95% CI 1.026–1.238, P = 0.012). For each doubling of HCG concentration on day 12 after embryo transfer, duration of pregnancy was shortened by 0.51 days. Adjustment for maternal age, prepregnancy body mass index, being a first-time mother and number of embryos transferred did not change the association. Conclusion High maternal HCG concentration on a fixed day after embryo transfer is likely to indicate early embryo implantation. After embryo transfer, pregnancies with early implantation are shorter than pregnancies with late implantation.
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Henriksen, Hege; Berntsen, Sveinung; Paur, Ingvild; Zucknick, Manuela; Skjetne, Anne Juul & Bøhn, Siv Kjølsrud
[Vis alle 10 forfattere av denne artikkelen]
(2018).
Validation of two short questionnaires assessing physical activity in colorectal cancer patients.
BMC sports science, medicine and rehabilitation.
10:8(8),
s. 1–12.
doi:
10.1186/s13102-018-0096-2.
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Background In order to investigate the impact of adherence to recommendations of physical activity and sedentary time on health outcomes in clinical trials, there is a need for feasible tools such as questionnaires that can give representative estimates of these measures. The primary aim of the present study was to validate two such questionnaires and their ability to estimate adherence to the recommendations of physical activity defined as moderate-to- vigorous physical activity or moderate physical activity of at least 150 min/week in colorectal cancer patients. Secondarily, self-reported sedentary time from the HUNT-PAQ was also evaluated. Methods Participants from 'The Norwegian dietary guidelines and colorectal cancer survival-study’ (CRC-NORDIET study) completed two short questionnaires; the NORDIET-FFQ (n = 78) and the HUNT-PAQ (n = 77). The physical activity monitor SenseWear Armband Mini was used as the reference method during seven consecutive days. Results The NORDIET-FFQ provided better estimates of time in moderate-to- vigorous physical activity and moderate physical activity than the HUNT-PAQ. The NORDIET-FFQ was unable to rank individual time in moderate-to- vigorous physical activity and moderate physical activity (Spearman’s rho = 0.08, p = 0.509 and Spearman’s rho rho = 0.01, p = 0.402, respectively). All intensities were under-reported by the HUNT-PAQ, but ranking of individual time in moderate physical activity and sedentary time were acceptable among women only (Spearman’s rho = 0.37, p = 0.027 and Spearman’s rho = 0.36, p = 0.035, respectively). The HUNT-PAQ correctly classified 71% of those not meeting the recommendations (sensitivity), and the NORDIET-FFQ correctly classified 63% of those who met the recommendations (specificity). About 67% and 33% reported to meet the recommendation of moderate-to- vigorous physical activity with the NORDIET-FFQ and HUNT-PAQ, respectively, whereas 55% actually met the moderate-to- vigorous physical activity according to the SenseWear Armband Mini. Conclusions The NORDIET-FFQ provided better specificity and better estimates of PA than the HUNT-PAQ. The HUNT-PAQ provided better sensitivity, and provided better ranking of PA and sedentary time among women than NORDIET-FFQ. It is important to be aware of the limitations documented in the present study. Trial registration The study is registered on the National Institutes of Health Clinical Trials (Identifier: NCT01570010). Registered 4 April 2012.
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Opheim, Gun Lisbeth; Zucknick, Manuela; Henriksen, Tore & Haugen, Guttorm
(2018).
A maternal meal affects clinical Doppler parameters in the fetal middle cerebral artery.
PLOS ONE.
13(12).
doi:
10.1371/journal.pone.0209990.
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Introduction Middle cerebral artery (MCA) and umbilical artery (UA) Doppler blood flow pulsatility indices (PIs) and MCA peak systolic velocity (PSV) are essential variables for clinically evaluating fetal well-being. Here we examined how a maternal meal influenced these Doppler blood flow velocity variables. Methods This prospective cohort study included 89 healthy Caucasian women with normal singleton pregnancies (median age, 32 years). Measurements were performed at gestational weeks 30 and 36, representing the start and near the end of the energy-depositing period. Measured variables included the MCA-PI, UA-PI, fetal heart rate (FHR) and MCA-PSV. The cerebroplacental ratio (CPR) was calculated as the ratio of MCA-PI to UA-PI. The first examination was performed in the fasting state at 08:30 a.m. Then participants ate a standard breakfast (approximate caloric intake, 400kcal), and the examination was repeated ~105 min after the meal. Results Without adjustment for FHR, fetal MCA-PI decreased after the meal at week 30 (‒0.115; p = 0.012) and week 36 (‒0.255; p < 0.001). All PI values were negatively correlated with FHR. After adjustment for FHR, MCA-PI still decreased after the meal at week 30 (‒0.087; p = 0.044) and week 36 (‒0.194; p < 0.001). The difference between the two gestational weeks was non-significant (p = 0.075). UA-PI values did not significantly change at week 30 (p = 0.253) or week 36 (p = 0.920). CPR revealed significant postprandial decreases of −0.17 at week 30 (p = 0.006) and −0.22 at week 36 (p = 0.001). Compared to fasting values, MCA-PSV was significantly higher after food intake: +3.9 cm/s at week 30 (p < 0.001) and +5.9 cm/s at week 36 (p < 0.001). Conclusion In gestational weeks 30 and 36, we observed a postprandial influence that was apparently specific to fetal cerebral blood flow.
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Jabeen, Shakila; Zucknick, Manuela; Nome, Marianne Eikhom; dannenfelser, ruth; Fleischer, Thomas & Kumar, Surendra
[Vis alle 15 forfattere av denne artikkelen]
(2018).
Serum cytokine levels in breast cancer patients during neoadjuvant treatment with bevacizumab.
Oncoimmunology.
ISSN 2162-4011.
7(11),
s. e1457598-1–e1457598-15.
doi:
10.1080/2162402X.2018.1457598.
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A high concentration of circulating vascular endothelial growth factor (VEGF) in cancer patients is associated with an aggressive tumor phenotype. Here, serum levels of 27 cytokines and blood cell counts were assessed in breast cancer patients receiving neoadjuvant chemotherapy with or without bevacizumab (Bev) in a randomized cohort of 132 patients with non-metastatic HER2-negative tumors. Cytokine levels were determined prior to treatment and at various time-points. The cytotoxic chemotherapy regimen of fluorouracil, epirubicin, and cyclophosphamide (FEC) had a profound impact on both circulating white blood cells and circulating cytokine levels. At the end of FEC treatment, the global decrease in cytokine levels correlated with the drop in white blood cell counts and was significantly greater in the patients of the Bev arm for cytokines, such as VEGF-A, IL-12, IP-10 and IL-10. Among patients who received Bev, those with pathological complete response (pCR) exhibited significantly lower levels of VEGF-A, IFN-γ, TNF-α and IL-4 than patients without pCR. This effect was not observed in the chemotherapy-only arm. Certain circulating cytokine profiles were found to correlate with different immune cell types at the tumor site. For the Bev arm patients, the serum cytokine levels correlated with higher levels of cytotoxic T cells at the end of the therapy regimen, which was indicative of treatment response. The higher response rate for Bev-treated patients and stronger correlations between serum cytokine levels and infiltrating CD8T cells merits further investigation. KEYWORDS: Bevacizumab, VEGF-A, neoadjuvant, cytokines, immunity
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Zimmo, Kaled; Laine, Katariina; Fosse, Erik; Zimmo, Mohammed; Ali-Masri, Hadil & Böttcher, Bettina
[Vis alle 9 forfattere av denne artikkelen]
(2018).
Impact of animated instruction on tablets and hands-on
training in applying bimanual perineal support on episiotomy rates: an
intervention study.
International Urogynecology Journal.
ISSN 0937-3462.
s. 1–8.
doi:
10.1007/s00192-018-3711-6.
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Introduction and hypothesis In Palestine, episiotomy is frequently used among primiparous women.This study assesses the effect of training birth attendants in applying bimanual perineal support during delivery by either animated instruction on tablets or hands-on training on episiotomy rates among primiparous women. Methods An interventional cohort study was performed from 15 October 2015 to 31 January 2017, including all primiparous women with singletons and noninstrumental vaginal deliveries at six Palestinian hospitals. Intervention 1 (animated instructions on tablets) was conducted in Hospitals 1, 2, 3, and 4. Intervention 2 (bedside hands-on training) was applied in Hospitals 1 and 2 only. Hospitals 5 and 6 did not receive interventions. Differences in episiotomy rates in intervention and nonintervention hospitals were assessed before and after the interventions and presented as p values using chi-square test, and odds ratios (OR) with 95% confidence intervals (CI). Differences in the demographic and obstetric characteristics were presented as p values using the Kruskal–Wallis test. Results Of 46,709 women, 12,841 were included. The overall episiotomy rate in the intervention hospitals did not change significantly after intervention 1, from 63.1 to 62.1% (OR = 0.96, 95% CI 0.84–1.08), but did so after intervention 2, from 61.1 to 38.1% (OR = 0.39, 95% CI 0.33–0.47). Rates after Intervention 2 changed from 65.0 to 47.3% (OR = 0.52, 95% CI 0.40–0.67) in Hospital 1 and from 39.4 to 25.1% (OR = 0.49, 95% CI 0.35–0.68) in Hospital 2. Conclusions Hands-on training of bimanual perineal support during delivery of primiparous women was significantly more effective in reducing episiotomy rates than animated instruction videos alone.
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Zimmo, Kaled; Laine, Katariina; Fosse, Erik; Zimmo, Mohammed; Ali, Hadil & Zucknick, Manuela
[Vis alle 8 forfattere av denne artikkelen]
(2018).
Episiotomy practice in six Palestinian hospitals: a population-based cohort study among singleton vaginal births.
BMJ Open.
8(7).
doi:
10.1136/bmjopen-2018-021629.
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Objective To explore the rates, characteristics and indications for episiotomy among women delivering vaginally for the first time, as well as parous women. Study design A prospective, population-based birth cohort study. Setting Obstetric departments in six Palestinian government hospitals. Participants All women with singleton vaginal births (n=29 165) from 1 March 2015 until 1 March 2016. Methods All women were divided into two groups: first vaginal birth group (n=9108), including primiparous women and women with their first vaginal birth after one caesarean section, and the parous group (n=20 057). Each group was analysed separately. Data were presented as numbers and percentages or range. Differences in rates were assessed by the p values of χ2 test, or Fisher’s exact test if there are cell counts less than 5. Main outcome measures Episiotomy rates and indications among women of singleton births. Results The overall episiotomy rate was 28.7%: 78.8% for women with first vaginal birth (range 56.6%–86.0%) and 5.9% for parous women (range 1.0%–9.5%). The most common indications for episiotomy were ‘primiparity’ in the first vaginal birth group (69.9%) and ‘protecting the perineum’ in the parous group (59.5%). The least common indications were prolonged second stage (1.5%) and fetal distress (6.9%), respectively. Conclusion In Palestine, the majority of women who delivered vaginally for the first time had an episiotomy. Education of birth attendants, clinical audits, educational interventions and adherence to the updated guidelines may help to decrease the routine overuse of episiotomy.
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Øystese, Kristin Astrid Berland; Berg, Jens Petter; Normann, Kjersti Ringvoll; Zucknick, Manuela; Casar-Borota, Olivera & Bollerslev, Jens
(2018).
The role of E and N-cadherin in the postoperative course of gonadotroph pituitary tumours.
Endocrine.
ISSN 1355-008X.
62(2),
s. 351–360.
doi:
10.1007/s12020-018-1679-0.
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Jabeen, Shakila; Espinoza, Jaime; Torland, Lilly Anne; Zucknick, Manuela; Kumar, Surendra & Haakensen, Vilde Drageset
[Vis alle 15 forfattere av denne artikkelen]
(2018).
Noninvasive profiling of serum cytokines in breast cancer patients and clinicopathological characteristics.
Oncoimmunology.
ISSN 2162-4011.
:e1537691.
doi:
10.1080/2162402X.2018.1537691.
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Cancers elicit an immune response by modifying the microenvironment. The immune system plays a pivotal role in cancer recognition and eradication. While the potential clinical value of infiltrating lymphocytes at the tumor site has been assessed in breast cancer, circulating cytokines – the molecules coordinating and fine-tuning immune response – are still poorly characterized. Using two breast cancer cohorts (MicMa, n = 131, DCTB, n = 28) and the multiplex Luminex platform, we measured the levels of 27 cytokines in the serum of breast cancer patients prior to treatment. We investigated the cytokine levels in relation to clinicopathological characteristics and in perspective of the tumor infiltrating immune cells predicted from the bulk mRNA expression data. Unsupervised clustering analysis of the serum cytokine levels in the MicMa cohort identified a cluster of pro-inflammatory, pro-angiogenic, and Th2-related cytokines which was associated with poor prognosis. Notably high levels of platelet derived growth factor BB (PDGF) reflected a more aggressive tumor phenotype and larger tumor size. A significant positive correlation between serum levels of interferon gamma-induced protein 10 (IP10) and its mRNA expression at the tumor site suggested that tumor-IP10-production may outflow to the bloodstream. High IP10 serum levels were associated with a worse prognosis. Finally, we found serum levels of both PDGF and IP10 associated with enrichment scores of specific tumor infiltrating immune cells. Our study suggests that monitoring cytokine circulating levels in breast cancer could be used to characterize breast cancers and the immune composition of their microenvironment through readily available biological material. KEYWORDS: Breast cancer, cytokines, pathological markers, immune response, prognosis
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LeBlanc, Marissa; Nustad, Haakon Egdetveit; Zucknick, Manuela & Page, Christian
(2018).
Quality control for Illumina 450K methylation data in the absence of iDat files using correlation structure in pedigrees and repeated measures.
BMC Genetics.
19.
doi:
10.1186/s12863-018-0636-5.
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Background An important feature in many genomic studies is quality control and normalization. This is particularly important when analyzing epigenetic data, where the process of obtaining measurements can be bias prone. The GAW20 data was from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN), a study with multigeneration families, where DNA cytosine-phosphate-guanine (CpG) methylation was measured pre- and posttreatment with fenofibrate. We performed quality control assessment of the GAW20 DNA methylation data, including normalization, assessment of batch effects and detection of sample swaps. Results We show that even after normalization, the GOLDN methylation data has systematic differences pre- and posttreatment. Through investigation of (a) CpGs sites containing a single nucleotide polymorphism, (b) the stability of breeding values for methylation across time points, and (c) autosomal gender-associated CpGs, 13 sample swaps were detected, 11 of which were posttreatment. Conclusions This paper demonstrates several ways to perform quality control of methylation data in the absence of raw data files and highlights the importance of normalization and quality control of the GAW20 methylation data from the GOLDN study.
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Nustad, Haakon Egdetveit; Page, Christian; Reiner, Andrew Henry; Zucknick, Manuela & LeBlanc, Marissa
(2018).
A Bayesian mixed modeling approach for estimating heritability.
BMC Proceedings.
12(31),
s. 117–122.
doi:
10.1186/s12919-018-0131-z.
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Background
A Bayesian mixed model approach using integrated nested Laplace approximations (INLA) allows us to construct flexible models that can account for pedigree structure. Using these models, we estimate genome-wide patterns of DNA methylation heritability (h2), which are currently not well understood, as well as h2 of blood lipid measurements.
Methods
We included individuals from the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study with Infinium 450 K cytosine-phosphate-guanine (CpG) methylation and blood lipid data pre- and posttreatment with fenofibrate in families with up to three-generation pedigrees. For genome-wide patterns, we constructed 1 model per CpG with methylation as the response variable, with a random effect to model kinship, and age and gender as fixed effects.
Results
In total, 425,791 CpG sites pre-, but only 199,027 CpG sites posttreatment were found to have nonzero heritability. Across these CpG sites, the distributions of h2 estimates are similar in pre- and posttreatment (pre: median = 0.31, interquartile range [IQR] = 0.16; post: median = 0.34, IQR = 0.20). Blood lipid h2 estimates were similar pre- and posttreatment with overlapping 95% credibility intervals. Heritability was nonzero for treatment effect, that is, the difference between pre- and posttreatment blood lipids. Estimates for triglycerides h2 are 0.48 (pre), 0.42 (post), and 0.21 (difference); likewise for high-density lipoprotein cholesterol h2 the estimates are 0.61, 0.68, and 0.10.
Conclusions
We show that with INLA, a fully Bayesian approach to estimate DNA methylation h2 is possible on a genome-wide scale. This provides uncertainty assessment of the estimates, and allows us to perform model selection via deviance information criterion (DIC) to identify CpGs with strong evidence for nonzero heritability.
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Dürr, Claudia; Hanna, Bola S.; Schulz, Angela; Lucas, Fabienne; Zucknick, Manuela & Benner, Axel
[Vis alle 16 forfattere av denne artikkelen]
(2018).
Tumor necrosis factor receptor signaling is a driver of chronic lymphocytic leukemia that can be therapeutically targeted by the flavonoid wogonin.
Haematologica.
ISSN 0390-6078.
103(4),
s. 688–697.
doi:
10.3324/haematol.2017.177808.
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Chronic lymphocytic leukemia is a malignancy of mature B cells that strongly depend on microenvironmental factors, and their deprivatio n has been ide nt ified as a promising treatmen t approach for this incurable disease. Cytokine array screening of 247 chronic lymphocytic leukemia serum samples revealed elevated levels of tumor necrosis factor (TNF) receptor-1 which were associated with poor clinical outcome. We detected a microenvironment-induced expression of TNF receptor-1 in chronic lymphocytic leukemia cells in vitro, and an aberrantly high expression of this receptor in the proliferation centers of patients’ lymph nodes. Stimulation of TNF receptor-1 with TNF-α enhanced nuclear factor κ-light-chain-enhancer of activated B cells (NFκB) activity and viability of chronic lymphocytic leukemia cells, which was inhibited by wogonin. The therapeutic effects of wogonin were analyzed in mice after adoptive transfer of Em-T-cell leukemia 1 (TCL1) leukemic cells. Wogonin treatment prevented leukemia development when given early after transplantation. The treatment of fullblown leukemia resulted in the loss of the TNF receptor-1 on chronic lymphocytic leukemia cells and their mobilization to blood. Targeting TNF receptor-1 signaling is therefore proposed for the treatment of chronic lymphocytic leukemia.
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Treppmann, Tabea; Ickstadt, Katja & Zucknick, Manuela
(2017).
Integration of multiple genomic data sources in a Bayesian Cox model for variable selection and prediction.
Computational & Mathematical Methods in Medicine.
ISSN 1748-670X.
2017.
doi:
10.1155/2017/7340565.
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Bayesian variable selection becomes more and more important in statistical analyses, in particular when performing variable selection in high dimensions. For survival time models and in the presence of genomic data, the state of the art is still quite unexploited. One of the more recent approaches suggests a Bayesian semiparametric proportional hazards model for right censored time-to-event data. We extend this model to directly include variable selection, based on a stochastic search procedure within a Markov chain Monte Carlo sampler for inference. This equips us with an intuitive and flexible approach and provides a way for integrating additional data sources and further extensions. We make use of the possibility of implementing parallel tempering to help improve the mixing of the Markov chains. In our examples, we use this Bayesian approach to integrate copy number variation data into a gene-expression-based survival prediction model. This is achieved by formulating an informed prior based on copy number variation. We perform a simulation study to investigate the model’s behavior and prediction performance in different situations before applying it to a dataset of glioblastoma patients and evaluating the biological relevance of the findings.
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Øystese, Kristin Astrid Berland; Casar-Borota, Olivera; Normann, Kjersti Ringvoll; Zucknick, Manuela; Berg, Jens Petter & Bollerslev, Jens
(2017).
Estrogen Receptor α, a Sex-Dependent Predictor of Aggressiveness in Nonfunctioning Pituitary Adenomas: SSTR and Sex Hormone Receptor Distribution in NFPA.
Journal of Clinical Endocrinology and Metabolism (JCEM).
ISSN 0021-972X.
102(9),
s. 3581–3590.
doi:
10.1210/jc.2017-00792.
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Øystese, Kristin Astrid Berland; Zucknick, Manuela; Casar-Borota, Olivera; Ringstad, Geir & Bollerslev, Jens
(2017).
Early postoperative growth in non-functioning pituitary adenomas; A tool to tailor safe follow-up.
Endocrine.
ISSN 1355-008X.
57(1),
s. 35–45.
doi:
10.1007/s12020-017-1314-5.
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Holm, Maia Blomhoff; Bastani, Nasser Ezzatkhah; Holme, Ane Moe; Zucknick, Manuela; Jansson, Thomas & Refsum, Helga
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(2017).
Uptake and release of amino acids in the fetal-placental unit in human pregnancies.
PLOS ONE.
12(10).
doi:
10.1371/journal.pone.0185760.
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Objectives: The current concepts of human fetal-placental amino acid exchange and metabolism are mainly based on animal-, in vitro- and ex vivo models. We aimed to determine and assess the paired relationships between concentrations and arteriovenous differences of 19 amino acids on the maternal and fetal sides of the human placenta in a large study sample. Methods: This cross-sectional in vivo study included 179 healthy women with uncomplicated term pregnancies. During planned cesarean section, we sampled blood from incoming and outgoing vessels on the maternal (radial artery and uterine vein) and fetal (umbilical vein and artery) sides of the placenta. Amino acid concentrations were measured by liquid chromatography—tandem mass spectrometry. We calculated paired arteriovenous differences and performed Wilcoxon signed-rank tests and Spearman’s correlations. Results: In the umbilical circulation, we observed a positive venoarterial difference (fetal uptake) for 14 amino acids and a negative venoarterial difference (fetal release) for glutamic acid (p<0.001). In the maternal circulation, we observed a positive arteriovenous difference (uteroplacental uptake) for leucine (p = 0.005), isoleucine (p = 0.01), glutamic acid (p<0.001) and arginine (p = 0.04) and a negative arteriovenous difference (uteroplacental release) for tyrosine (p = 0.002), glycine (p = 0.01) and glutamine (p = 0.02). The concentrations in the maternal artery and umbilical vein were correlated for all amino acids except tryptophan, but we observed no correlations between the uteroplacental uptake and the fetal uptake or the umbilical vein concentration. Two amino acids showed a correlation between the maternal artery concentration and the fetal uptake. Conclusions: Our human in vivo study expands the current insight into fetal-placental amino acid exchange, and discloses some differences from what has been previously described in animals. Our findings are consistent with the concept that the fetal supply of amino acids in the human is the result of a dynamic interplay between fetal and placental amino acid metabolism and interconversions.
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Henriksen, Hege; Ræder, Hanna; Bøhn, Siv Kjølsrud; Paur, Ingvild; Kværner, Ane Sørlie & Billington, Siv Åshild
[Vis alle 14 forfattere av denne artikkelen]
(2017).
The Norwegian dietary guidelines and colorectal cancer survival (CRC-NORDIET) study: A food-based multicentre randomized controlled trial.
BMC Cancer.
17(1).
doi:
10.1186/s12885-017-3072-4.
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Background Colorectal cancer survivors are not only at risk for recurrent disease but also at increased risk of comorbidities such as other cancers, cardiovascular disease, diabetes, hypertension and functional decline. In this trial, we aim at investigating whether a diet in accordance with the Norwegian food-based dietary guidelines and focusing at dampening inflammation and oxidative stress will improve long-term disease outcomes and survival in colorectal cancer patients. Methods/design This paper presents the study protocol of the Norwegian Dietary Guidelines and Colorectal Cancer Survival study. Men and women aged 50–80 years diagnosed with primary invasive colorectal cancer (Stage I-III) are invited to this randomized controlled, parallel two-arm trial 2–9 months after curative surgery. The intervention group (n = 250) receives an intensive dietary intervention lasting for 12 months and a subsequent maintenance intervention for 14 years. The control group (n = 250) receives no dietary intervention other than standard clinical care. Both groups are offered equal general advice of physical activity. Patients are followed-up at 6 months and 1, 3, 5, 7, 10 and 15 years after baseline. The study center is located at the Department of Nutrition, University of Oslo, and patients are recruited from two hospitals within the South-Eastern Norway Regional Health Authority. Primary outcomes are disease-free survival and overall survival. Secondary outcomes are time to recurrence, cardiovascular disease-free survival, compliance to the dietary recommendations and the effects of the intervention on new comorbidities, intermediate biomarkers, nutrition status, physical activity, physical function and quality of life. Discussion The current study is designed to gain a better understanding of the role of a healthy diet aimed at dampening inflammation and oxidative stress on long-term disease outcomes and survival in colorectal cancer patients. Since previous research on the role of diet for colorectal cancer survivors is limited, the study may be of great importance for this cancer population. Trial registration ClinicalTrials.gov Identifier: NCT01570010 .
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Zucknick, Manuela
(2025).
The potential of Bayesian modelling for complex biomedical data.
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Biomedical data are characterised by large heterogeneity. Technical challenges result in noise and biases, e.g. through measurement errors, but more importantly, biological variability between individuals and conditions is large. This is even more the case in disease, which is a deviation from the normal healthy state, and each patient differs from this norm in a different way. Statistical modelling is concerned with delineating and understanding the different sources of heterogeneity. Bayesian statistics offers a unified approach to the modelling, which allows us to keep track of all sources of variability, even in complex hierarchical model setups. I will illustrate the potential of Bayesian modelling for complex biomedical data structures through examples from precision medicine and cancer drug screens.
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Zucknick, Manuela; Frigessi, Arnoldo & Smajdor, Anna
(2024).
Autonomy and decision-making in the era of medical AI: the red pill or the blue?
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Frigessi, Arnoldo; Smajdor, Anna & Zucknick, Manuela
(2023).
The Importance of Reward Functions in Machine Learning Algorithms and Why These Should be Regulated.
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Session III: AI in Practice
Presentation: The Importance of Reward Functions in Machine Learning Algorithms and Why These Should be Regulated
presented by Frigessi
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Raftemo, Anne Elisabeth Ross; Jahnsen, Reidun Birgitta; Brandvik, Siri; Hollung, Sandra Julsen; Zucknick, Manuela & Andersen, Guro Lillemoen
(2022).
Spasticity treatments and orthopedic surgeries in lower extremities in children with cerebral palsy – a longitudinal population based study.
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Background/objectives:
Intramuscular injections of Botulinum toxin A (BoNT-A) have been used to reduce spasticity in children with cerebral palsy (CP) for several decades. Despite extensive use, there is a lack of evidence-based treatment guidelines, and the optimal use of BoNT-A injections and other treatments to reduce tone and prevent contractures in children with CP is a matter of discussion. The aim of this study is to describe the use of BoNT-A treatments, Intrathecal baclofen and orthopedic surgery over a 20-year period in children with CP in Norway.
Study design:
National register-based longitudinal study
Study participants & setting:
Children with spastic, dyskinetic or unclassified CP born 2002 to 2010 with information on gross motor function recorded from 2002 to 2019 in the Norwegian Quality and Surveillance Registry for Cerebral Palsy (NorCP) were included.
Materials/methods:
We present a descriptive analysis of the distributions (N, %) of BoNT-A treatment, Intrathecal baclofen and orthopedic surgery by age, the Gross Motor Function Classification System (GMFCS) level, CP diagnosis, by muscle (BoNT-A) and type of surgery. Lexis diagrams describe the change in distributions of BoNT-A treatment, Intrathecal baclofen and orthopedic surgery for age cohorts over time.
Results:
Among 1010 eligible children 567 (56%) received BoNT-A in the lower extremities at least once. Among these 447 (88%) received the first treatment before the age of eight years. BoNT-A treatment was most often given to children on GMFCS level III (44, 77%). Most children received BoNT-A injections in the gastrocnemius muscle (387, 71%), the soleus muscle (251, 46%) and the hamstrings muscles (198, 37%). Among the eligible children 61 (6%) were treated with Intrathecal baclofen, and 58 (95%) of these were classified on GMFCS level IV and V. Of the 345 children (35%) who received orthopedic surgery, the highest proportion had spastic quadriplegia (93, 66%) and GMFCS level IV (53, 63%).
Conclusions/significance:
A high proportion of children with CP in Norway received BoNT-A, most often in the gastrocnemius muscle. Lexis diagrams will describe the changes in distributions of the treatments for age cohorts over time. This information will be used to support healthcare planning for children with CP in Norway.
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Madjar, Katrin; Zucknick, Manuela; Ickstadt, Katja & Rahnenführer, Jörg
(2022).
Correction to: Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression (BMC Bioinformatics, (2021), 22, 1, (586), 10.1186/s12859-021-04483-z).
BMC Bioinformatics.
23(1).
doi:
10.1186/s12859-021-04552-3.
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Hjelle, Ellen Gabrielsen; Bragstad, Line Kildal; Kirkevold, Marit; Zucknick, Manuela; Bronken, Berit Arnesveen & Martinsen, Randi
[Vis alle 11 forfattere av denne artikkelen]
(2019).
The effect of a psychosocial intervention on well-being 6 months after stroke – a multicentre prospective randomized controlled trial.
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Pickering, Sarah Jai Hazell; Briand, Nolwenn; Collas, Philippe & Zucknick, Manuela
(2025).
White and beige adipogenesis: Transcriptomic and epigenetic insights into human adipocyte plasticity.
Universitetet i Oslo.
ISSN 9788234806742.
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Adipose tissue plasticity plays a critical role in maintaining metabolic homeostasis and represents an important focus of research in a world with a growing prevalence of obesity and type 2 diabetes. The presence of thermogenic beige adipocytes within white adipose tissue correlates with a lean, metabolically healthy phenotype in adults. Yet, the mechanisms underlying individual variations in thermogenic capacity remain poorly understood.
To understand the regulation of beige adipocyte identity and lineage specification, we investigated the transcriptome and 3D epigenome of human white and beige mature adipocytes and mapped early adipogenic differentiation at single-cell resolution. As a model, we differentiated primary adipose stem cells isolated from six unrelated individuals in the presence or absence of the beiging agent rosiglitazone, generating matched beige and white adipocytes.
We define a range of cell states among adipose progenitors during early white and beige adipogenesis, including several bipotential progenitor populations that can produce both white and beige adipocytes.
Further, we characterised the transcriptomic and epigenetic landscape of mature adipocytes and found that alternative isoform usage makes a significant contribution to the functional transcriptome of beige versus white adipocytes. We discovered a novel beige-specific isoform of PEMT and alternative TSS usage of key transcription factor PPARy.
In addition, we identified increased active epigenetic marks and enhancer contacts in beige adipocytes. White adipocytes, in comparison, have an enrichment for different epigenetic markers, highlighting distinctive features of the epigenome between beige and white adipocytes.
Together this thesis provides insights into the transcriptional heterogeneity of adipose progenitors, early adipogenesis and the epigenetic regulation of healthy white and beige cultured adipocytes.
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Publisert
5. jan. 2015 12:32
- Sist endret
13. mars 2026 15:32