Post doc Francesco Bettella
Development of novel statistical tools and application of these to investigate the genetic makeup of psychiatric illnesses.
Several psychiatric disorders are assumed to result from the sum of many environmental and genetic factors as well as the interactions thereof.
We seek to improve our understanding of the genetic makeup of some complex psychiatric disorders with the aid of recently established non-conventional statistical methods. An important role is played here by the approach adopted by O. Andreassen, A. Dale, A. Schork, W. Thompson and others hence forth referred to as covariate-modulated (CM) approach. While several incarnations of the CM exist to date, what they all have in common is to leverage information that is ignored in the standard approach, the rationale behind it being that some genes might be more likely to be influence the illness than others.
The microRNA transcription region mir-137 gene variant previously found to be associated with schizophrenia happens to be situated in a region of modern human DNA that has most diverged from its Neanderthal's counterpart and may therefore have evolved relatively recently. The question arises then of whether this is a generalizable feature of psychiatric susceptibility regions of the DNA, and to what extent.
There exists a number of ways to measure the age of DNA:
a) ratio between mutations that don't change the protein and mutation that do;
b) extension of hetero/homozygosity;
c) conservation across species in more or less extended families;
d) direct comparison with other species (e.g. primates).
The CM approach can be adopted in this context as well. We endeavor to apply it to a number of evolutionary properties of genes and investigate whether such properties are in any measure related to psychiatric (and for the sake of comparison also non-psychiatric) traits.