GWAS and systems biology analysis of depressive symptoms among smokers from the COPDGene cohort

Genomic Loci Influencing Cue-Reactivity in Heterogeneous Stock Rats

Addiction vulnerability is associated with the tendency to attribute incentive salience to reward predictive cues; both addiction and the attribution of incentive salience are influenced by environmental and genetic factors. To characterize the genetic contributions to incentive salience attribution, we performed a genome-wide association study (GWAS) in a cohort of 1,645 genetically diverse heterogeneous stock (HS) rats. We tested HS rats in a Pavlovian conditioned approach task, in which we characterized the individual responses to food-associated stimuli ("cues"). Rats exhibited either cue-directed "sign-tracking" behavior or food-cup directed "goal-tracking" behavior. We then used the conditioned reinforcement procedure to determine whether rats would perform a novel operant response for unrewarded presentations of the cue. We found that these measures were moderately heritable (SNP heritability, h2 = .189-.215). GWAS identified 14 quantitative trait loci (QTLs) for 11 of the 12 traits we examined. Interval sizes of these QTLs varied widely. 7 traits shared a QTL on chromosome 1 that contained a few genes (e.g. Tenm4, Mir708) that have been associated with substance use disorders and other mental health traits in humans. Other candidate genes (e.g. Wnt11, Pak1) in this region had coding variants and expression-QTLs in mesocorticolimbic regions of the brain. We also conducted a Phenome-Wide Association Study (PheWAS) on other behavioral measures in HS rats and found that regions containing QTLs on chromosome 1 were also associated with nicotine self-administration in a separate cohort of HS rats. These results provide a starting point for the molecular genetic dissection of incentive salience and provide further support for a relationship between attribution of incentive salience and drug abuse-related traits.

GWAS of depression in 4,520 individuals from the Russian population highlights the role of MAGI2 (S-SCAM) in the gut-brain axis

We present the results of the depression Genome-wide association studies study performed on a cohort of Russian-descent individuals, which identified a novel association at chromosome 7q21 locus. Gene prioritization analysis based on already known depression risk genes indicated MAGI2 (S-SCAM) as the most probable gene from the locus and potential susceptibility gene for the disease. Brain and gut expression patterns were the main features highlighting functional relatedness of MAGI2 to the previously known depression risk genes. Local genetic covariance analysis, analysis of gene expression, provided initial suggestive evidence of hospital anxiety and depression scale and diagnostic and statistical manual of mental disorders scales having a different relationship with gut-brain axis disturbance. It should be noted, that while several independent methods successfully in silico validate the role of MAGI2, we were unable to replicate genetic association for the leading variant in the MAGI2 locus, therefore the role of rs521851 in depression should be interpreted with caution.

Implication of Melanocortin Receptor Genes in the Familial Comorbidity of Type 2 Diabetes and Depression

The melanocortin receptors are G-protein-coupled receptors, which are essential components of the hypothalamic–pituitary–adrenal axis, and they mediate the actions of melanocortins (melanocyte-stimulating hormones: α-MSH, β-MSH, and γ-MSH) as well as the adrenocorticotropin hormone (ACTH) in skin pigmentation, adrenal steroidogenesis, and stress response. Three melanocortin receptor genes (MC1R, MC2R, and MC5R) contribute to the risk of major depressive disorder (MDD), and one melanocortin receptor gene (MC4R) contributes to the risk of type 2 diabetes (T2D). MDD increases T2D risk in drug-naïve patients; thus, MDD and T2D commonly coexist. The five melanocortin receptor genes might confer risk for both disorders. However, they have never been investigated jointly to evaluate their potential contributing roles in the MDD-T2D comorbidity, specifically within families. In 212 Italian families with T2D and MDD, we tested 11 single nucleotide polymorphisms (SNPs) in the MC1R gene, 9 SNPs in MC2R, 3 SNPs in MC3R, 4 SNPs in MC4R, and 2 SNPs in MC5R. The testing used 2-point parametric linkage and linkage disequilibrium (LD) (i.e., association) analysis with four models (dominant with complete penetrance (D1), dominant with incomplete penetrance (D2), recessive with complete penetrance (R1), and recessive with incomplete penetrance (R2)). We detected significant (p ≤ 0.05) linkage and/or LD (i.e., association) to/with MDD for one SNP in MC2R (rs111734014) and one SNP in MC5R (rs2236700), and to/with T2D for three SNPs in MC1R (rs1805007 and rs201192930, and rs2228479), one SNP in MC2R (rs104894660), two SNPs in MC3R (rs3746619 and rs3827103), and one SNP in MC4R genes (Chr18-60372302). The linkage/LD/association was significant across different linkage patterns and different modes of inheritance. All reported variants are novel in MDD and T2D. This is the first study to report risk variants in MC1R, MC2R, and MC3R genes in T2D. MC2R and MC5R genes are replicated in MDD, with one novel variant each. Within our dataset, only the MC2R gene appears to confer risk for both MDD and T2D, albeit with different risk variants. To further clarity the role of the melanocortin receptor genes in MDD-T2D, these findings should be sought among other ethnicities as well.

Meta-analysis of association between TPH2 single nucleotide poiymorphism and depression

Tryptophan hydroxylase 2 (TPH2) plays a crucial role in the human brain. Although the association between the TPH2 gene and depression has been suggested in previous meta-analyses, studies based on Chinese subjects are often neglected. Therefore, we included some previous studies based on Chinese subjects to explore the relationship between TPH2 polymorphisms and depression via conducting an extensive meta-analysis. We reviewed 40 research papers that included data on TPH2 gene single nucleotide polymorphisms (SNPs) from 5766 patients with depression and 5988 healthy subjects. The analysis showed an association between polymorphisms in the TPH2 gene and depression, and some results were significant in 24 studies that included Chinese Han study participants. The results of our meta-analysis showed that rs4570625, rs17110747, rs120074175, rs4290270, rs120074175, and rs4290270 may be significantly associated with depression, and that rs11178997 (A/A genotype) may be a significant risk factor for depression in the Chinese subjects. Based on the results of this study, biological experiments should be performed in the future to explore how different SNPs affect depression.

Association between genetic polymorphisms of miRNAs (miR-8079 and miR-5007) and susceptibility of chronic obstructive pulmonary disease in Chinese people

BACKGROUND

Chronic obstructive pulmonary disease (COPD) has been recognized as a heterogeneous disease, which is caused by biological heterogeneity. The purpose of our study is to determine the association between the single nucleotide polymorphisms (SNPs) of miRNAs (miR-8079 and miR-5007) and the susceptibility to COPD in Chinese population.

METHODS

We conducted a 'case-control' study involving 315 COPD patients and 314 healthy individuals. Three SNPs of miR-8079 (rs9533803, rs9525927, rs7981875) and three SNPs of miR-5007 (rs9527345, rs2252932, rs2997119) were selected, then we used logistic regression to analyze the association between candidate SNPs and COPD susceptibility under different genetic models. Multi-factor dimensionality reduction (MDR) was used to analyze the interaction of "SNP-SNP" in COPD risk studies. Finally, we used univariate and ANOVA to analyze the differences in clinical characteristics among different genotypes.

RESULTS

Our results showed that miR-8079-rs9525927 was significant associated with COPD susceptibility whether in overall and stratified analysis. miR-5007-rs2997119 was associated with the increased risk of COPD in women under multiple genetic models; miR-8079-rs9525927 and miR-5007-rs9527345 had a certain association with clinical indicator Fev_1 of COPD patients; rs9527345 or rs2252932 on miR-5007 was associated with the risk of COPD with wheezing dyspnea or wheezing.

CONCLUSION

Our results suggested that the genetic polymorphisms of miR-8079 or miR-5007 were potentially associated with COPD risk, of which miR-8079-rs9525927 was more prominent.

Fate or coincidence: do COPD and major depression share genetic risk factors?

Major depressive disorder (MDD) is a common comorbidity in chronic obstructive pulmonary disease (COPD), affecting up to 57% of patients with COPD. Although the comorbidity of COPD and MDD is well established, the causal relationship between these two diseases is unclear. A large-scale electronic health record clinical biobank and genome-wide association study summary statistics for MDD and lung function traits were used to investigate potential shared underlying genetic susceptibility between COPD and MDD. Linkage disequilibrium score regression was used to estimate genetic correlation between phenotypes. Polygenic risk scores (PRS) for MDD and lung function traits were developed and used to perform a phenome-wide association study (PheWAS). Multi-trait-based conditional and joint analysis identified single-nucleotide polymorphisms (SNPs) influencing both lung function and MDD. We found genetic correlations between MDD and all lung function traits were small and not statistically significant. A PRS-MDD was significantly associated with an increased risk of COPD in a PheWAS [odds ratio (OR) = 1.12, 95% confidence interval (CI): 1.09-1.16] when adjusting for age, sex and genetic ancestry, but this relationship became attenuated when controlling for smoking history (OR = 1.08, 95% CI: 1.04-1.13). No significant associations were found between the lung function PRS and MDD. Multi-trait-based conditional and joint analysis identified three SNPs that may contribute to both traits, two of which were previously associated with mood disorders and COPD. Our findings suggest that the observed relationship between COPD and MDD may not be driven by a strong shared genetic architecture.

Automated feature extraction from population wearable device data identified novel loci associated with sleep and circadian rhythms

Wearable devices have been increasingly used in research to provide continuous physical activity monitoring, but how to effectively extract features remains challenging for researchers. To analyze the generated actigraphy data in large-scale population studies, we developed computationally efficient methods to derive sleep and activity features through a Hidden Markov Model-based sleep/wake identification algorithm, and circadian rhythm features through a Penalized Multi-band Learning approach adapted from machine learning. Unsupervised feature extraction is useful when labeled data are unavailable, especially in large-scale population studies. We applied these two methods to the UK Biobank wearable device data and used the derived sleep and circadian features as phenotypes in genome-wide association studies. We identified 53 genetic loci with p<5×10-8 including genes known to be associated with sleep disorders and circadian rhythms as well as novel loci associated with Body Mass Index, mental diseases and neurological disorders, which suggest shared genetic factors of sleep and circadian rhythms with physical and mental health. Further cross-tissue enrichment analysis highlights the important role of the central nervous system and the shared genetic architecture with metabolism-related traits and the metabolic system. Our study demonstrates the effectiveness of our unsupervised methods for wearable device data when additional training data cannot be easily acquired, and our study further expands the application of wearable devices in population studies and genetic studies to provide novel biological insights.