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

肥胖是世界范围内的主要健康负担，也是抑郁症（MDD）的相关合并症。定义肥胖的一个常用参数是身体质量指数（BM）。最新的BMI基因关联研究发现了97个全基因组的突变点，其中大多数位于人类大脑中高度表达的基因中。因此，bmi相关变异支持中枢神经系统的重要作用，包括突触功能、谷氨酸信号传导和中枢食欲调节的关键脑部位。在最近的一项来自PGC的MDD研究中发现，MDD和BMI之间存在显著的遗传相关性，其中两个最显著的MDD位点位于先前与BMI和肥胖相关的基因附近。我们PGC重度抑郁症研究小组的另一项研究发现，报告“体重增加”症状的重度抑郁症患者携带的BMI遗传风险变异数量更高。这些发现支持了肥胖是一种大脑相关疾病的假设，以及这种关联背后潜在的共同生物学机制。在这里，我们介绍了我们基于个体的方法来解开MDD中遗传风险变异对BMI特征的假定影响。这种方法是一种新颖的方法，从个体的特定遗传和疾病负担出发，从GWAS的发现中找到意义，从而揭示了BMI和重度抑郁症共同的潜在生物学原理。这种方法先前在精神分裂症中进行了测试，精神分裂症是一种具有高遗传力和108个全基因组显著变异的疾病。风险变异的特定组成可归因于自闭症和情感SCZ亚型。我们的方法将从个体出发，遵循不同的分析策略，强调重度抑郁症和BMI之间的关联：在我们的基因型驱动方法中，我们将选择在BMI相关变异方面表现出极端基因型星座的重度抑郁症受试者。这些受试者将被分析其特定的重度抑郁症症状和与BMI遗传因素相关的亚型。2. 在我们的表型驱动方法中，我们将选择与重度抑郁症相关的显著精神共病的肥胖受试者，并分析他们的BMI共同遗传风险因素。3. 在另一种基因驱动的方法中，我们将选择两个可能有趣的群体（BMI高遗传负荷但BMI低/ BMI低遗传负荷但BMI高），通过环境相互作用分析，分析BMI遗传变异和BMI之间遗传关联的偏差是否由基因中的精神合并症驱动。在最好的情况下，特定基因/途径的改变将与重度抑郁症亚型和症状有关。这方面的知识可能对医疗目标和干预措施有重大益处。所有假设都将在我们的一般人群研究（SHIP-LEGEND N=2400, SHIP-TREND N=4422）和患者队列GANI_MED （N=4371）中进行检验。复制将在PGC队列中进行。

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.