Making sense out of GWAS findings – starting from the individualThe genetic overlap between major depression and body mass index

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Obesity is a worldwide major health burden and a relevant comorbid condition of depressive disorder (MDD). A commonly used parameter to define obesity is body mass index (BM). The latest genetic association study of BMI identified 97 genome-wide hits most of them located in genes that are highly expressed in the human brain. Thus, the BMI-associated variants supported the important role of the central nervous system involving pathways for synaptic function, glutamate signaling and key brain sites of central appetite regulation. In the recent study for MDD from the PGC a significant genetic correlation between MDD and BMI was found and the two most significant hits for MDD were located near genes previously associated with BMI and obesity. Another study from our PGC MDD research group found that MDD patients reporting symptoms of “increased weight” carried a higher number of genetic risk variants for BMI. These findings support the hypothesis of obesity as a brain related disorder and the potentially shared biological mechanisms underlying this association.Here we introduce our individual-based approach for disentangling the putative impact of genetic risk variants for BMI features in MDD. This approach is a novel way making sense out of GWAS findings starting from the specific genetic and disease burden of an individual and thus revealing insights to the shared underlying biology of BMI and MDD. This approach was previously tested for schizophrenia, a disorder with a high genetic heritability and 108 genome-wide significant variants. Specific compositions of risk variants could be attributed to an autistic and affective SCZ subtype. Our approach will highlight the association between MDD and BMI following different analytic strategies starting from an individual: 1. We will select MDD subjects that exhibit an extreme genotype constellation regarding the BMI associated variants in our genotype-driven approach. These subjects will be analyzed regarding their specific MDD symptoms and subtypes in association with their genetic factors for BMI. 2. In our phenotype-driven approach we will select obese subjects with a striking psychiatric comorbidity regarding MDD and analyze their common genetic risk factors for BMI. 3. In another genetically-driven approach we will select two potentially interesting groups (high genetic load for BMI but low BMI / low genetic load for BMI but high BMI) to analyze if the deviation from the genetic association between BMI genetic variants and BMI is driven by psychiatric comorbidities in gene by environment interaction analyses. In the best case, alterations in specific genes/pathways would be linked to MDD subtypes and symptoms. This knowledge could be of major benefit for medical targets and interventions. All hypotheses will be tested in our general population studies (SHIP-LEGEND N=2400, SHIP-TREND N=4422) and in the patient cohort GANI_MED (N=4371). Replication will be performed in PGC cohorts.