Final Report Summary - GMI (Genetics of Mental Illness)
For AP and AD, as well as for other complex traits including Borderline Personality Disorder (BPD), Obsessive Compulsive Symptoms (OCS), cognition, migraine and addiction, a switch took place between 2008 and 2013 from candidate gene studies to genome-wide association (GWA) scans, prediction of phenotype outcomes based on polygenic scores, and heritability analyses based on measured genetic variants. The first generation of GWA studies for psychiatric disorders has led to new insights regarding the genetic architecture of these disorders, namely that a very large number of genes, each with a small contribution, explain their heritability. The contribution of a large number of genes to complex traits can be analyzed at the level of the individual with genome-wide profiling. Polygenic scores for depression are significantly associated with different measures of depression and anxiety, confirming the presence of many genetic loci of small effect. Remarkably, the predictive value was as large in the elderly as in middle-aged adults. The same methodological approach was pioneered to investigate the mechanisms underlying the genetic overlap of migraine and depression. Results suggest that the 'pure' forms of migraine and MDD are genetically distinct disorders. The subgroup of individuals with comorbid depression and migraine were genetically most similar to depressed patients. These results indicate that in at least a subset of migraine patients with MDD, migraine is a symptom or consequence of depression. Polygenic scores based on the meta-analysis of the Psychiatric Genetics Consortium for childhood Attention Deficit Hyperactivity Disorder (ADHD) were used to predict AP in the population-based cohorts, testing the hypothesis that the clinical diagnosis represents the extreme end of a continuous distribution of inattentive and hyperactive behaviors. The ADHD polygenic risk scores significantly predicted both parent and teacher ratings of AP in preschool and school-age children, providing evidence for a dimensional model of ADHD. Future GWA studies on ADHD can likely benefit from the inclusion of population-based cohorts and the analysis of continuous scores.
Analyses of SNP-phenotype data using genomic-relatedness-matrix restricted maximum likelihood (GREML) and density estimation (DE) methods to estimate the proportion of phenotypic variance explained by genome- or chromosome-wide SNPs for complex traits (depression, borderline personality disorder, neuroticism, nicotine addiction and others) showing polygenic heritability predicted from SNPs consonant with estimates from twin and family data.
In summary, the genetics of common mental disorders indicate a high degree of polygenic inheritance, explaining the heritability of these disorders; a high degree of genetic pleiotropy, explaining the mutual comorbidity and the comorbidity with somatic disease; and a high degree of genetic stability across the lifespan, explaining the persistence of mental disorders.