Publications
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Koch, Elise; Parker, Nadine; Mohammad, Helin; Lenk, Hasan Cagin; Ystaas, Lars Andreas Rømo & Jaholkowski, Piotr Pawel
[Show all 13 contributors for this article]
(2026).
Genetic overlap between treatment-resistant schizophrenia and smoking initiation.
International Journal of Neuropsychopharmacology.
ISSN 1461-1457.
29(7).
doi:
10.1093/ijnp/pyag035.
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Background
Early detection of treatment-resistant schizophrenia (TRS) is of substantial clinical importance. While TRS is heritable, the associated genetic variants have been difficult to identify. Cigarette smoking is associated with non-response to antipsychotics, and smoking behavior and schizophrenia have a shared genetic basis. Thus, TRS may also have a shared genetic basis with smoking behavior.
Objective
Here, we aim to identify genetic variants associated with TRS by leveraging overlapping genetic variants with smoking initiation to increase statistical power.
Methods
We analyzed genome-wide data for TRS and smoking initiation with the conditional/conjunctional false discovery rate (cond/conjFDR) to identify shared loci, and LD score regression to determine genetic correlations. To investigate potential causal effects of shared loci, we performed Mendelian randomization analyses. Shared loci were mapped to genes, which were further investigated for enrichment of drug target genes.
Results
We observed a significant positive genetic correlation between TRS and smoking initiation (rg = 0.47 P = .0002). Leveraging the genetic overlap between TRS and smoking initiation, we identified four novel loci jointly associated with TRS and smoking initiation. The condFDR results improved polygenic prediction of TRS. Mendelian randomization indicates putative evidence for a causal effect of genetic liability to TRS on smoking initiation. The functional genetic analyses suggest that alpha-1-adrenergic receptors may be involved in the pathophysiology of TRS and possibly related to the efficacy of clozapine versus other antipsychotic drugs.
Conclusion
In conclusion, our results show that shared genetic mechanisms influence both TRS and smoking behavior, which provide new insights into the biological underpinnings of TRS.
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Stinson, Sara E.; Shadrin, Alexey; Rahman, Mohammad Zillur; Rødevand, Linn; Broce, Iris J. & Selbæk, Geir
[Show all 17 contributors for this article]
(2026).
Distinct metabolic signatures of Alzheimer's and Parkinson's disease revealed through genetic overlap.
EBioMedicine.
127.
doi:
10.1016/j.ebiom.2026.106254.
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Background: Metabolic dysfunction is a major risk factor for neurodegeneration, yet the genetic architecture linking systemic metabolism to Alzheimer's disease (AD) and Parkinson's disease (PD) remains unclear.
Methods: We integrated genome-wide association data for 249 circulating metabolites and proglucagon with summary statistics for AD, PD, and cardiometabolic traits. Genetic correlations, polygenic overlap, causal relationships, and shared genetic loci were quantified using linkage disequilibrium score regression, high-definition likelihood, bivariate mixture modelling, Mendelian randomisation, and conjunctional false discovery rate analyses, followed by functional and tissue-specific enrichment analyses.
Findings: AD displayed a metabolic-genetic profile aligned with body mass index, type 2 diabetes, coronary artery disease, and stroke, whereas PD exhibited largely opposing patterns (Spearman's rs = −0.26). Mendelian randomization analyses supported causal effects of lipoprotein subclasses, glutamine, and proglucagon on AD risk, with opposite or null effects in PD. Shared loci between metabolites and AD were enriched for lipid metabolism and cholesterol transport, whereas PD-associated loci were enriched for mitochondrial function, vesicle trafficking, and stress-response signalling.
Interpretation: AD and PD are shaped by fundamentally distinct metabolic-genetic architectures. Metabolically targeted interventions, particularly those modulating lipid, amino acid, and proglucagon pathways, may require disease-specific and genetically informed strategies for prevention and treatment of neurodegenerative diseases.
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Shorter, John R.; Pasman, Joëlle A.; Kurvits, Siim; Jangmo, Andreas; Naamanka, Joonas & Harder, Arvid
[Show all 31 contributors for this article]
(2025).
Genome-wide association analyses identify distinct genetic architectures for early-onset and late-onset depression.
Nature Genetics.
ISSN 1061-4036.
57,
p. 2972–2979.
doi:
10.1038/s41588-025-02396-8.
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Major depressive disorder (MDD) is a common and heterogeneous disorder of complex etiology. Studying more homogeneous groups stratified according to clinical characteristics, such as age of onset, can improve the identification of the underlying genetic causes and lead to more targeted treatment strategies. We leveraged Nordic biobanks with longitudinal health registries to investigate differences in the genetic architectures of early-onset (eoMDD; n = 46,708 cases) and late-onset (loMDD; n = 37,168 cases) MDD. We identified 12 genomic loci for eoMDD and two for loMDD. Overall, the two MDD subtypes correlated moderately (genetic correlation, r g = 0.58) and differed in their genetic correlations with related traits. These findings suggest that eoMDD and loMDD have partially distinct genetic signatures, with a specific developmental brain signature for eoMDD. Importantly, we demonstrate that polygenic risk scores (PRS) for eoMDD predict suicide attempts within the first 10 years after the initial diagnosis: the absolute risk for suicide attempt was 26% in the top PRS decile, compared to 12% and 20% in the bottom decile and the intermediate group, respectively. Taken together, our findings can inform precision psychiatry approaches for MDD.
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Koch, Elise; Puusepp, Tuuli; Einarsson, Guðmundur; Mitchell, Brittany L.; Harder, Arvid & Lin, Yuhao
[Show all 31 contributors for this article]
(2025).
Genome-wide meta-analyses of non-response to antidepressants provide insights into underlying molecular genetics and suggest potential pharmacotherapies.
Molecular Psychiatry.
ISSN 1359-4184.
doi:
10.1038/s41380-025-03357-7.
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Antidepressants exhibit a considerable variation in efficacy, and increasing evidence suggests that individual genetics contribute to antidepressant treatment response. Here, we combined data on antidepressant non-response measured using rating scales for depressive symptoms, questionnaires of treatment effect, and data from electronic health records, to increase statistical power to detect genomic loci associated with non-response to antidepressants in a total sample of 135,471 individuals prescribed antidepressants (25,255 non-responders and 110,216 responders). We performed genome-wide association meta-analyses, genetic correlation analyses, leave-one-out polygenic prediction, and bioinformatics analyses for genetically informed drug prioritization. We identified one novel locus (rs1106260) associated with non-response to selective serotonin reuptake inhibitors (SSRIs), and one novel locus (rs60847828) associated with non-response to SSRIs and serotonin-norepinephrine reuptake inhibitors (SNRIs) and showed significant polygenic prediction in independent samples. Genetic correlation analyses show positive associations between non-response to antidepressants and most psychiatric traits, and negative associations with cognitive traits and subjective well-being. In addition, we investigated drugs that target proteins likely involved in mechanisms underlying antidepressant non-response, and shortlisted drugs that warrant further replication and validation of their potential to reduce depressive symptoms in individuals who do not respond to first-line antidepressant medications. These results suggest that meta-analyses of GWAS utilizing real-world measures of treatment outcomes can increase sample sizes to improve the discovery of variants associated with non-response to antidepressants.
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Koch, Elise; Shadrin, Alexey; Parker, Nadine; Lock, Siobhan K.; Smith, Robert Løvsletten & Frei, Oleksandr
[Show all 11 contributors for this article]
(2025).
Polygenic overlap with granulocyte counts identifies novel loci for clozapine metabolism and clozapine-induced agranulocytosis.
Neuropsychopharmacology.
ISSN 0893-133X.
50,
p. 947–955.
doi:
10.1038/s41386-025-02054-x.
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While clozapine is the most effective antipsychotic drug, its use is limited due to hematological adverse effects involving the reduction of granulocyte counts with potential life-threatening agranulocytosis. It is not yet possible to predict or prevent the risk of agranulocytosis, and the mechanisms are unknown but likely related to clozapine metabolism. Genome-wide association studies (GWASs) of clozapine metabolism and clozapine-induced agranulocytosis have identified few genetic loci. We used the largest available GWAS summary statistics of clozapine metabolism (clozapine-to-norclozapine ratio) and clozapine-induced agranulocytosis, applying the conditional false discovery rate (condFDR) method to increase power for genetic discovery by conditioning on granulocyte counts variants. To investigate potential causal effects of shared loci, we performed Mendelian Randomization analyses. After conditioning on granulocyte counts, we identified two novel loci associated with clozapine-to-norclozapine ratio. These loci were significantly associated with clozapine metabolism in a validation sample of 392 clozapine-treated individuals. For clozapine-induced agranulocytosis, five loci were identified after conditioning on granulocyte counts. These five loci were significantly associated with reduced granulocyte counts in a small independent sample of clozapine-treated individuals. Genetic liability to slow clozapine metabolism (high clozapine-to-norclozapine ratio) showed evidence of a causal effect on reduced neutrophil counts, and genetic liability to low neutrophil counts exhibited weak evidence of a causal effect on clozapine-induced agranulocytosis. Our findings of shared genetic variants associated with clozapine metabolism and granulocyte counts may form the basis for developing prediction models for clozapine-induced agranulocytosis.
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O'Connell, Kevin Sean; Koromina, Maria; Veen, Tracy van der; Boltz, Toni; David, Friederike S. & Yang, Jessica Mei Kay
[Show all 313 contributors for this article]
(2025).
Genomics yields biological and phenotypic insights into bipolar disorder.
Nature.
ISSN 0028-0836.
639,
p. 968–975.
doi:
10.1038/s41586-024-08468-9.
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Bipolar disorder is a leading contributor to the global burden of disease1. Despite high heritability (60–80%), the majority of the underlying genetic determinants remain unknown2. We analysed data from participants of European, East Asian, African American and Latino ancestries (n = 158,036 cases with bipolar disorder, 2.8 million controls), combining clinical, community and self-reported samples. We identified 298 genome-wide significant loci in the multi-ancestry meta-analysis, a fourfold increase over previous findings3, and identified an ancestry-specific association in the East Asian cohort. Integrating results from fine-mapping and other variant-to-gene mapping approaches identified 36 credible genes in the aetiology of bipolar disorder. Genes prioritized through fine-mapping were enriched for ultra-rare damaging missense and protein-truncating variations in cases with bipolar disorder4, highlighting convergence of common and rare variant signals. We report differences in the genetic architecture of bipolar disorder depending on the source of patient ascertainment and on bipolar disorder subtype (type I or type II). Several analyses implicate specific cell types in the pathophysiology of bipolar disorder, including GABAergic interneurons and medium spiny neurons. Together, these analyses provide additional insights into the genetic architecture and biological underpinnings of bipolar disorder.
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Wiström, Erik David; O'Connell, Kevin Sean; Koch, Elise; Jaholkowski, Piotr Pawel; Hindley, Guy & Steen, Nils Eiel
[Show all 14 contributors for this article]
(2025).
The genetic overlap between major depressive disorder, white blood cell counts and interleukin 6.
Journal of Affective Disorders Reports.
20,
p. 1–10.
doi:
10.1016/j.jadr.2025.100889.
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Background: Immune dysregulation may contribute to the pathophysiology of major depressive disorder (MDD). Here we aimed to identify genetic architecture jointly associated with MDD, white blood cell (WBC) count and interleukin 6 (IL-6) levels.
Methods: Using genome-wide association studies summary statistics on MDD (330,173 cases and 727,595 controls), WBC counts (nmax = 563,946) and IL-6 (n = 52,654), we performed linkage disequilibrium (LD) score regression, bivariate causal mixture model (MiXeR), conjunctional false discovery rate (conjFDR) and Mendelian randomization (MR) analyses. Additionally, we used an independent MDD dataset (9,582 cases and 84,670 controls) from the Norwegian Mother, Father and Child Cohort Study for polygenic risk score (PRS) analyses.
Findings: We found a significant positive genetic correlation (rg = 0.22) between MDD and IL-6. MiXeR estimates indicated substantial differences in the polygenicity of MDD (13.7K variants), WBC subgroups (0.8K-1.8K variants), and IL-6 (0.2K variants), with 10.1 %-31.4 % of the variants influencing WBC subgroups overlapping with MDD. We identified MDD risk loci shared with basophils (8), eosinophils (17), lymphocytes (23), monocytes (14), neutrophils (20), and total WBC counts (20), as well as two loci shared between MDD and IL-6, at conjFDR <0.05. PRS analysis showed a weak, but significantly increased risk for MDD dependent on monocyte count.
Limitations: The analyses only included European ancestry samples, and the causal genes associated with the identified genetic loci were not experimentally validated.
Conclusions: MDD shares genetic underpinnings with immune system components, which implicates immune-mediated pathways in the pathophysiology of MDD. However, this connection may only be relevant for a minority of patients.
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Meer, Dennis van der; Rahman, Mohammad Zillur; Ottas, Aigar; Parekh, Pravesh; Kutrolli, Gleda & Stinson, Sara Elizabeth
[Show all 37 contributors for this article]
(2025).
Pleiotropic and sex-specific genetic mechanisms of circulating metabolic markers.
Nature Communications.
16(1).
doi:
10.1038/s41467-025-60058-z.
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Metabolites in plasma form biosignatures of a range of common complex human diseases. Discovering variants with pleiotropic effects across metabolites can reveal underlying biological mechanisms. We therefore performed uni- and multivariate genome-wide association studies (GWAS) on 249 circulating metabolic markers across 328,006 UK Biobank and Estonian Biobank participants. We investigated rare variation through whole exome sequencing gene burden tests, analysed the role of body mass index through Mendelian randomization, and performed genome-wide interaction analyses with sex. We discovered 15,585 loci summed over the univariate GWAS, with high pleiotropy across markers, linked to a wide range of disorders. Findings from common and rare variant gene tests converged on lipid homeostasis pathways. 31 loci interacted with sex, mapped to genes involved in cholesterol processing. The findings offer insights into the genetic architecture of circulating metabolites, revealing pleiotropic loci, highlighting the role of rare variation, and uncovering sex-specific molecular mechanisms of lipid metabolism.
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Jaholkowski, Piotr Pawel; Bahrami, Shahram; Fominykh, Vera; Hindley, Guy; Tesfaye, Markos & Parekh, Pravesh
[Show all 23 contributors for this article]
(2024).
Charting the shared genetic architecture of Alzheimer's disease, cognition, and educational attainment, and associations with brain development.
Neurobiology of Disease.
ISSN 0969-9961.
203.
doi:
10.1016/j.nbd.2024.106750.
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The observation that the risk of developing Alzheimer's disease is reduced in individuals with high premorbid cognitive functioning, higher educational attainment, and occupational status has led to the ‘cognitive reserve’ hypothesis. This hypothesis suggests that individuals with greater cognitive reserve can tolerate a more significant burden of neuropathological changes before the onset of cognitive decline. The underpinnings of cognitive reserve remain poorly understood, although a shared genetic basis between measures of cognitive reserve and Alzheimer's disease has been suggested. Using the largest samples to date and novel statistical tools, we aimed to investigate shared genetic variants between Alzheimer's disease, and measures of cognitive reserve; cognition and educational attainment to identify molecular and neurobiological foundations. We applied the causal mixture model (MiXeR) to estimate the number of trait-influencing variants shared between Alzheimer's disease, cognition, and educational attainment, and condFDR/conjFDR to identify shared loci. To provide biological insights loci were functionally characterized. Subsequently, we constructed a Structural Equation Model (SEM) to determine if the polygenic foundation of cognition has a direct impact on Alzheimer's disease risk, or if its effect is mediated through established risk factors for the disease, using a case-control sample from the UK Biobank. Univariate MiXeR analysis (after excluding chromosome 19) revealed that Alzheimer's disease was substantially less polygenic (450 trait-influencing variants) compared to cognition (11,100 trait-influencing variants), and educational attainment (12,700 trait-influencing variants). Bivariate MiXeR analysis estimated that Alzheimer's disease shared approximately 70 % of trait-influencing variants with cognition, and approximately 40 % with educational attainment, with mixed effect directions. Using condFDR analysis, we identified 18 loci jointly associated with Alzheimer's disease and cognition and 6 loci jointly associated with Alzheimer's disease and educational attainment. Genes mapped to shared loci were associated with neurodevelopment, expressed in early life, and implicated the dendritic tree and phosphatidylinositol phosphate binding mechanisms. Spatiotemporal gene expression analysis of the identified genes showed that mapped genes were highly expressed during the mid-fetal period, further suggesting early neurodevelopmental stages as critical periods for establishing cognitive reserve which affect the risk of Alzheimer's disease in old age. Furthermore, our SEM analysis showed that genetic variants influencing cognition had a direct effect on the risk of developing Alzheimer's disease, providing evidence in support of the neurodevelopmental hypothesis of the disease.
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Koch, Elise Mirjam; Pardiñas, Antonio F.; O'Connell, Kevin Sean; Selvaggi, Pierluigi; Camacho-Collados, Jose & Babic, Aleksandar
[Show all 26 contributors for this article]
(2024).
How real-world data can facilitate the development of precision medicine treatment in psychiatry.
Biological Psychiatry.
ISSN 0006-3223.
96,
p. 543–551.
doi:
10.1016/j.biopsych.2024.01.001.
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Precision medicine has the ambition to improve treatment response and clinical outcomes through patient stratification and holds great potential for the treatment of mental disorders. However, several important factors are needed to transform current practice into a precision psychiatry framework. Most important are 1) the generation of accessible large real-world training and test data including genomic data integrated from multiple sources, 2) the development and validation of advanced analytical tools for stratification and prediction, and 3) the development of clinically useful management platforms for patient monitoring that can be integrated into health care systems in real-life settings. This narrative review summarizes strategies for obtaining the key elements—well-powered samples from large biobanks integrated with electronic health records and health registry data using novel artificial intelligence algorithms—to predict outcomes in severe mental disorders and translate these models into clinical management and treatment approaches. Key elements are massive mental health data and novel artificial intelligence algorithms. For the clinical translation of these strategies, we discuss a precision medicine platform for improved management of mental disorders. We use cases to illustrate how precision medicine interventions could be brought into psychiatry to improve the clinical outcomes of mental disorders.
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Lenk, Hasan Cagin; Koch, Elise Mirjam; O'Connell, Kevin Sean; Smith, Robert Løvsletten; Akkouh, Ibrahim Ahmed & Djurovic, Srdjan
[Show all 8 contributors for this article]
(2024).
Genome-wide association analysis of treatment resistant schizophrenia for variant discovery and polygenic assessment.
Human Genomics.
ISSN 1473-9542.
18(1).
doi:
10.1186/s40246-024-00673-x.
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Background Treatment resistant schizophrenia (TRS) is broadly defined as inadequate response to adequate treatment and is associated with a substantial increase in disease burden. Clozapine is the only approved treatment for TRS, showing superior clinical effect on overall symptomatology compared to other drugs, and is the prototype of atypical antipsychotics. Risperidone, another atypical antipsychotic with a more distinctive dopamine 2 antagonism, is commonly used in treatment of schizophrenia. Here, we conducted a genome-wide association study on patients treated with clozapine (TRS) vs. risperidone (non-TRS) and investigated whether single variants and/or polygenic risk score for schizophrenia are associated with TRS status. We hypothesized that patients who are treated with clozapine and risperidone might exhibit distinct neurobiological phenotypes that match pharmacological profiles of these drugs and can be explained by genetic differences. The study population (n = 1286) was recruited from a routine therapeutic drug monitoring (TDM) service between 2005 and 2022. History of a detectable serum concentration of clozapine and risperidone (without TDM history of clozapine) defined the TRS (n = 478) and non-TRS (n = 808) group, respectively. Results We identified a suggestive association between TRS and a common variant within the LINC00523 gene with a significance just below the genome-wide threshold (rs79229764 C > T, OR = 4.89; p = 1.8 × 10−7). Polygenic risk score for schizophrenia was significantly associated with TRS (OR = 1.4, p = 2.1 × 10−6). In a large post-mortem brain sample from schizophrenia donors (n = 214; CommonMind Consortium), gene expression analysis indicated that the rs79229764 variant allele might be involved in the regulation of GPR88 and PUDP, which plays a role in striatal neurotransmission and intellectual disability, respectively. Conclusions We report a suggestive genetic association at the rs79229764 locus with TRS and show that genetic liability for schizophrenia is positively associated with TRS. These results suggest a candidate locus for future follow-up studies to elucidate the molecular underpinnings of TRS. Our findings further demonstrate the value of both single variant and polygenic association analyses for TRS prediction.
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Supiyev, Adil; Karlsson, Robert; Wang, Yunzhang; Koch, Elise; Hägg, Sara & Kauppi, Karolina
(2023).
Independent role of Alzheimer's disease genetics and C-reactive protein on cognitive ability in aging.
Neurobiology of Aging.
ISSN 0197-4580.
126,
p. 103–112.
doi:
10.1016/j.neurobiolaging.2023.02.006.
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Apolipoprotein E (APOE) ε4, the strongest genetic risk factor for late onset Alzheimer's disease (LOAD), has been associated with cognitive decline independent from AD pathology, but the role for other LOAD risk genes in normal cognitive aging is less studied. We examined the effect of APOE ε4 and several different polygenic risk scores (PRS) for LOAD on cognitive level and decline in aging, using longitudinal data from the UK Biobank. While PRS-LOAD including all variants (except APOE) predicted cognitive level, APOE ε4 and PRS-LOAD based on 17 non-APOE gene variants with strong association to AD (p < 5e-8) predicted age-related decline in verbal numeric reasoning. The effect on decline were partly driven by 4 variants involved in the immune system. Those variants also predicted serum levels of the inflammatory marker C-reactive protein (CRP), but CRP did not mediate the effect on decline. Those findings suggest genetic variations in immune functions play a role in aspects of cognitive aging that may be independent of LOAD pathology as well as systemic inflammation measured by CRP.
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O'Connell, Kevin Sean; Koch, Elise; Lenk, Hasan Cagin; Akkouh, Ibrahim Ahmed; Hindley, Guy Frederick Lanyon & Jaholkowski, Piotr Pawel
[Show all 16 contributors for this article]
(2023).
Polygenic overlap with body-mass index improves prediction of treatment-resistant schizophrenia.
Psychiatry Research.
ISSN 0165-1781.
325.
doi:
10.1016/j.psychres.2023.115217.
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Treatment resistant schizophrenia (TRS) is characterized by repeated treatment failure with antipsychotics. A recent genome-wide association study (GWAS) of TRS showed a polygenic architecture, but no significant loci were identified. Clozapine is shown to be the superior drug in terms of clinical effect in TRS; at the same time it has a serious side effect profile, including weight gain. Here, we sought to increase power for genetic discovery and improve polygenic prediction of TRS, by leveraging genetic overlap with Body Mass Index (BMI). We analysed GWAS summary statistics for TRS and BMI applying the conditional false discovery rate (cFDR) framework. We observed cross-trait polygenic enrichment for TRS conditioned on associations with BMI. Leveraging this cross-trait enrichment, we identified 2 novel loci for TRS at cFDR <0.01, suggesting a role of MAP2K1 and ZDBF2. Further, polygenic prediction based on the cFDR analysis explained more variance in TRS when compared to the standard TRS GWAS. These findings highlight putative molecular pathways which may distinguish TRS patients from treatment responsive patients. Moreover, these findings confirm that shared genetic mechanisms influence both TRS and BMI and provide new insights into the biological underpinnings of metabolic dysfunction and antipsychotic treatment.
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Håglin, Sofia; Koch, Elise Mirjam; Hackenhaar, Fernanda; Nyberg, Lars & Kauppi, Karolina
(2023).
APOE ɛ4, but not polygenic Alzheimer’s disease risk, is related to longitudinal decrease in hippocampal brain activity in non-demented individuals.
Scientific Reports.
13(1).
doi:
10.1038/s41598-023-35316-z.
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Abstract The hippocampus is affected early in Alzheimer’s disease (AD) and altered hippocampal functioning influences normal cognitive aging. Here, we used task-based functional MRI to assess if the APOE ɛ4 allele or a polygenic risk score (PRS) for AD was linked to longitudinal changes in memory-related hippocampal activation in normal aging (baseline age 50–95, n = 292; n = 182 at 4 years follow-up, subsequently non-demented for at least 2 years). Mixed-models were used to predict level and change in hippocampal activation by APOE ɛ4 status and PRS based on gene variants previously linked to AD at p ≤ 1, p < 0.05, or p < 5e−8 (excluding APOE ). APOE ɛ4 and PRS p <5e−8 significantly predicted AD risk in a larger sample from the same study population (n = 1542), while PRS p ≤1 predicted memory decline. APOE ɛ4 was linked to decreased hippocampal activation over time, with the most prominent effect in the posterior hippocampi, while PRS was unrelated to hippocampal activation at all p-thresholds. These results suggests a link for APOE ɛ4, but not for AD genetics in general, on functional changes of the hippocampi in normal aging.
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Cheng, Weiqiu; Parker, Nadine; Karadag, Naz; Koch, Elise; Hindley, Guy Frederick Lanyon & Icick, Romain
[Show all 22 contributors for this article]
(2023).
The relationship between cannabis use, schizophrenia, and bipolar disorder: a genetically informed study.
The Lancet Psychiatry.
ISSN 2215-0374.
10(6),
p. 441–451.
doi:
10.1016/S2215-0366(23)00143-8.
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Background The relationship between psychotic disorders and cannabis use is heavily debated. Shared underlying genetic risk is one potential explanation. We investigated the genetic association between psychotic disorders (schizophrenia and bipolar disorder) and cannabis phenotypes (lifetime cannabis use and cannabis use disorder). Methods We used genome-wide association summary statistics from individuals with European ancestry from the Psychiatric Genomics Consortium, UK Biobank, and International Cannabis Consortium. We estimated heritability, polygenicity, and discoverability of each phenotype. We performed genome-wide and local genetic correlations. Shared loci were identified and mapped to genes, which were tested for functional enrichment. Shared genetic liabilities to psychotic disorders and cannabis phenotypes were explored using causal analyses and polygenic scores, using the Norwegian Thematically Organized Psychosis cohort. Findings Psychotic disorders were more heritable than cannabis phenotypes and more polygenic than cannabis use disorder. We observed positive genome-wide genetic correlations between psychotic disorders and cannabis phenotypes (range 0·22–0·35) with a mixture of positive and negative local genetic correlations. Three to 27 shared loci were identified for the psychotic disorder and cannabis phenotype pairs. Enrichment of mapped genes implicated neuronal and olfactory cells as well as drug–gene targets for nicotine, alcohol, and duloxetine. Psychotic disorders showed a causal effect on cannabis phenotypes, and lifetime cannabis use had a causal effect on bipolar disorder. Of 2181 European participants from the Norwegian Thematically Organized Psychosis cohort applied in polygenic risk score analyses, 1060 (48·6%) were females and 1121 (51·4%) were males (mean age 33·1 years [SD 11·8]). 400 participants had bipolar disorder, 697 had schizophrenia, and 1044 were healthy controls. Within this sample, polygenic scores for cannabis phenotypes predicted psychotic disorders independently and improved prediction beyond the polygenic score for the psychotic disorders. Interpretation A subgroup of individuals might have a high genetic risk of developing a psychotic disorder and using cannabis. This finding supports public health efforts to reduce cannabis use, particularly in individuals at high risk or patients with psychotic disorders. Identified shared loci and their functional implications could facilitate development of novel treatments.
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Koch, Elise; Nyberg, Lars; Lundquist, Anders & Kauppi, Karolina
(2022).
Polygenic risk for schizophrenia has sex-specific effects on brain activity during memory processing in healthy individuals.
Genes.
doi:
10.3390/genes13030412.
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Koch, Elise; Kauppi, Karolina & Chen, Chi-Hua
(2022).
Candidates for drug repurposing to address the cognitive symptoms in schizophrenia.
Progress in Neuro-psychopharmacology and Biological Psychiatry.
ISSN 0278-5846.
120.
doi:
10.1016/j.pnpbp.2022.110637.
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Koch, Elise & Demontis, Ditte
(2022).
Drug repurposing candidates to treat core symptoms in autism spectrum disorder.
Frontiers in Pharmacology.
13.
doi:
10.3389/fphar.2022.995439.
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Autism spectrum disorder (ASD) is characterized by high heritability and clinical heterogeneity. The main core symptoms are social communication deficits. There are no medications approved for the treatment of these symptoms, and medications used to treat non-specific symptoms have serious side effects. To identify potential drugs for repurposing to effectively treat ASD core symptoms, we studied ASD risk genes within networks of protein-protein interactions of gene products. We first defined an ASD network from network-based analyses, and identified approved drugs known to interact with proteins within this network. Thereafter, we evaluated if these drugs can change ASD-associated gene expression perturbations in genes in the ASD network. This was done by analyses of drug-induced versus ASD-associated gene expression, where opposite gene expression perturbations in drug versus ASD indicate that the drug could counteract ASD-associated perturbations. Four drugs showing significant ( p &lt; 0.05) opposite gene expression perturbations in drug versus ASD were identified: Loperamide, bromocriptine, drospirenone, and progesterone. These drugs act on ASD-related biological systems, indicating that these drugs could effectively treat ASD core symptoms. Based on our bioinformatics analyses of ASD genetics, we shortlist potential drug repurposing candidates that warrant clinical translation to treat core symptoms in ASD.
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Koch, Elise Mirjam; Johnell, Kristina & Kauppi, Karolina
(2022).
Longitudinal effects of using and discontinuing central nervous system medications on cognitive functioning.
Pharmacoepidemiology and Drug Safety.
ISSN 1053-8569.
doi:
10.1002/pds.5569.
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Purpose To investigate the longitudinal effect of using and discontinuing central nervous system (CNS) medications on cognitive performance. Methods Using longitudinal cognitive data from population representative adults aged 25–100 years (N = 2188) from four test waves 5 years apart, we investigated both the link between use of CNS medications (opioids, anxiolytics, hypnotics and sedatives) on cognitive task performance (episodic memory, semantic memory, visuospatial ability) across 15 years, and the effect of discontinuing these medications in linear mixed effects models. Results We found that opioid use was associated with decline in visuospatial ability whereas using anxiolytics, hypnotics and sedatives was not associated with cognitive decline over 15 years. A link between drug discontinuation and cognitive improvement was seen for opioids as well as for anxiolytics, hypnotics and sedatives. Conclusions Although our results may be confounded by subjacent conditions, they suggest that long-term use of CNS medications may have domain-specific negative effects on cognitive performance over time, whereas the discontinuation of these medications may partly reverse these effects. These results open up for future studies that address subjacent conditions on cognition to develop a more complete understanding of the cognitive effects of CNS medications.
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Koch, Elise; Nyberg, Lars; Lundquist, Anders; Pudas, Sara; Adolfsson, Rolf & Kauppi, Karolina
(2021).
Sex-specific effects of polygenic risk for schizophrenia on lifespan cognitive functioning in healthy individuals.
Translational Psychiatry.
doi:
10.1038/s41398-021-01649-4.
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June 9, 2022 11:10 AM
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Sep. 19, 2026 1:48 PM
