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Depression and obesity are highly prevalent major public health problems that frequently co-occur. Shared aetiological factors have been found between depression and obesity. The role of the fat mass and obesity associated (FTO) gene in body mass index (BMI) and obesity has been confirmed in many independent studies. Recently, we reported the first study implicating FTO in the association between depression and obesity.
We aimed to confirm these findings by investigating the FTO rs9939609 polymorphism in a meta-analysis of 13,701 individuals.
The sample consists of 6,902 depressed cases and 6,799 controls from five studies (Radiant, PsyCoLaus, GSK, MARS and NESDA/NTR). Common inclusion criteria were information available on a lifetime DSM-IV diagnosis of major depressive disorder (MDD), BMI and genotype data. Linear regression models for quantitative traits assuming an additive genetic model were performed to test for association and interaction between rs9939609, BMI and depression. Fixed and random-effects meta-analyses were performed.
Fixed-effects meta-analyses support a significant association between rs9939609 polymorphism and BMI (whole-sample: ß=0.07, p=1.29×10-12, depressive-cases: ß=0.12, p=6.92×10-12). No association was found in controls (ß=0.02, p=0.15). Meta-analyses further support a significant interaction between FTO, BMI and depression (fixed-effects: ß=0.13, p=3.087×10-7; random-effects: ß=0.12, p=0.027), wherein depressed carriers of the risk allele have an additional increase of 2.2% in BMI.
This meta-analysis demonstrates a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. Depression-related alterations in key biological processes may interact with the rs9939609 FTO risk allele to increase obesity risk.
Strategies to dissect phenotypic and genetic heterogeneity of major depressive disorder (MDD) have mainly relied on subphenotypes, such as age at onset (AAO) and recurrence/episodicity. Yet, evidence on whether these subphenotypes are familial or heritable is scarce. The aims of this study are to investigate the familiality of AAO and episode frequency in MDD and to assess the proportion of their variance explained by common single nucleotide polymorphisms (SNP heritability).
For investigating familiality, we used 691 families with 2–5 full siblings with recurrent MDD from the DeNt study. We fitted (square root) AAO and episode count in a linear and a negative binomial mixed model, respectively, with family as random effect and adjusting for sex, age and center. The strength of familiality was assessed with intraclass correlation coefficients (ICC). For estimating SNP heritabilities, we used 3468 unrelated MDD cases from the RADIANT and GSK Munich studies. After similarly adjusting for covariates, derived residuals were used with the GREML method in GCTA (genome-wide complex trait analysis) software.
Significant familial clustering was found for both AAO (ICC = 0.28) and episodicity (ICC = 0.07). We calculated from respective ICC estimates the maximal additive heritability of AAO (0.56) and episodicity (0.15). SNP heritability of AAO was 0.17 (p = 0.04); analysis was underpowered for calculating SNP heritability of episodicity.
AAO and episodicity aggregate in families to a moderate and small degree, respectively. AAO is under stronger additive genetic control than episodicity. Larger samples are needed to calculate the SNP heritability of episodicity. The described statistical framework could be useful in future analyses.
Although usually thought of as external environmental stressors, a significant heritable component has been reported for measures of stressful life events (SLEs) in twin studies.
We examined the variance in SLEs captured by common genetic variants from a genome-wide association study (GWAS) of 2578 individuals. Genome-wide complex trait analysis (GCTA) was used to estimate the phenotypic variance tagged by single nucleotide polymorphisms (SNPs). We also performed a GWAS on the number of SLEs, and looked at correlations between siblings.
A significant proportion of variance in SLEs was captured by SNPs (30%, p = 0.04). When events were divided into those considered to be dependent or independent, an equal amount of variance was explained for both. This ‘heritability’ was in part confounded by personality measures of neuroticism and psychoticism. A GWAS for the total number of SLEs revealed one SNP that reached genome-wide significance (p = 4 × 10−8), although this association was not replicated in separate samples. Using available sibling data for 744 individuals, we also found a significant positive correlation of R2 = 0.08 in SLEs (p = 0.03).
These results provide independent validation from molecular data for the heritability of reporting environmental measures, and show that this heritability is in part due to both common variants and the confounding effect of personality.
Depression frequently co-occurs with somatization, and somatic complaints have been reported as a vulnerability marker for affective disorders observable before disease onset. Somatization is thought to result from an increased attention to somatic sensations, which should be reflected in long-latency somatosensory evoked electroencephalogram (EEG) potentials (SSEPs) at the physiological level. Previous studies revealed that SSEPs are altered in depressed patients and suggested late SSEP components as vulnerability markers for affective disorders. Neurotransmitters such as serotonin, γ-aminobutyric acid (GABA) and the neuropeptide substance P may play an important role for both affective disorders and somatosensory processing.
We investigated the associations between SSEPs and polymorphisms within candidate genes of the serotonergic, GABAergic as well as the substance P system in subjects at high risk for affective disorders. The sample was composed of high-risk families participating in the Munich Vulnerability Study and genetic association analyses were calculated using qfam (family-based association tests for quantitative traits) implemented in PLINK 1.05.
We observed significant associations (false discovery rate <0.05) withstanding correction for multiple testing between late SSEP components (response strength 170–370 ms after stimulation) and four single nucleotide polymorphisms within the GABA transaminase (ABAT) gene region coding for a protein responsible for GABA degradation. No effects were found with the classical disease trait approach, suggesting SSEP marker specificity of the observed associations.
Our findings point to a possible role of ABAT gene-regulated GABA catabolism for an altered processing of somatosensory stimuli as a potential vulnerability marker for affective disorders.
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