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Depression and obesity are highly prevalent, and major impacts on public health frequently co-occur. Recently, we reported that having depression moderates the effect of the FTO gene, suggesting its implication in the association between depression and obesity.
To confirm these findings by investigating the FTO polymorphism rs9939609 in new cohorts, and subsequently in a meta-analysis.
The sample consists of 6902 individuals with depression and 6799 controls from three replication cohorts and two original discovery cohorts. Linear regression models were performed to test for association between rs9939609 and body mass index (BMI), and for the interaction between rs9939609 and depression status for an effect on BMI. Fixed and random effects meta-analyses were performed using METASOFT.
In the replication cohorts, we observed a significant interaction between FTO, BMI and depression with fixed effects meta-analysis (β=0.12, P = 2.7 × 10−4) and with the Han/Eskin random effects method (P = 1.4 × 10−7) but not with traditional random effects (β = 0.1, P = 0.35). When combined with the discovery cohorts, random effects meta-analysis also supports the interaction (β = 0.12, P = 0.027) being highly significant based on the Han/Eskin model (P = 6.9 × 10−8). On average, carriers of the risk allele who have depression have a 2.2% higher BMI for each risk allele, over and above the main effect of FTO.
This meta-analysis provides additional support for a significant interaction between FTO, depression and BMI, indicating that depression increases the effect of FTO on BMI. The findings provide a useful starting point in understanding the biological mechanism involved in the association between obesity and depression.
Bipolar disorder is a highly heritable polygenic disorder. Recent
enrichment analyses suggest that there may be true risk variants for
bipolar disorder in the expression quantitative trait loci (eQTL) in the
We sought to assess the impact of eQTL variants on bipolar disorder risk
by combining data from both bipolar disorder genome-wide association
studies (GWAS) and brain eQTL.
To detect single nucleotide polymorphisms (SNPs) that influence
expression levels of genes associated with bipolar disorder, we jointly
analysed data from a bipolar disorder GWAS (7481 cases and 9250 controls)
and a genome-wide brain (cortical) eQTL (193 healthy controls) using a
Bayesian statistical method, with independent follow-up replications. The
identified risk SNP was then further tested for association with
hippocampal volume (n = 5775) and cognitive performance
(n = 342) among healthy individuals.
Integrative analysis revealed a significant association between a brain
eQTL rs6088662 on chromosome 20q11.22 and bipolar disorder (log Bayes
factor = 5.48; bipolar disorder P =
5.85×10–5). Follow-up studies across multiple independent
samples confirmed the association of the risk SNP (rs6088662) with gene
expression and bipolar disorder susceptibility (P =
3.54×10–8). Further exploratory analysis revealed that
rs6088662 is also associated with hippocampal volume and cognitive
performance in healthy individuals.
Our findings suggest that 20q11.22 is likely a risk region for bipolar
disorder; they also highlight the informative value of integrating
functional annotation of genetic variants for gene expression in
advancing our understanding of the biological basis underlying complex
disorders, such as bipolar disorder.
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