Biology subjects

Yanni Zeng

Publications and source records attributed to Yanni Zeng.

4 recordsLinked to original sources

bioRxiv2016

Shared genetics and couple-associated environment are major contributors to the risk of both clinical and self-declared depression

BackgroundBoth genetic and environmental contributions to risk of depression have been identified, but estimates of their effects are limited. Commonalities between major depressive disorder (MDD) and self-declared depression (SDD) are also unclear. Dissecting the genetic and environmental contributions to these traits and their correlation would inform the design and interpretation of genetic studies.\n\nMethodsUsing data from a large Scottish family-based cohort (GS:SFHS, N=21,387), we estimated the genetic and environmental contributions to MDD and SDD. Genetic effects associated with common genome-wide genetic variants (SNP heritability) and additional pedigree-associated genetic variation and Non-genetic effects associated with common environments were estimated using linear mixed modeling (LMM).\n\nFindingsBoth MDD and SDD had significant contributions from effects of common genetic variants, the additional genetic effect of the pedigree and the common environmental effect shared by couples. The correlation between SDD and MDD was high (r=1*00, se=0*21) for common-variant-associated genetic effects and moderate for both the additional genetic effect of the pedigree (r=0*58, se=0*08) and the couple-shared environmental effect (r=0*53, se=0*22).\n\nInterpretationBoth genetics and couple-shared environmental effects were the major factors influencing liability to depression. SDD may provide a scalable alternative to MDD in studies seeking to identify common risk variants. Rarer variants and environmental effects may however differ substantially according to different definitions of depression.\n\nFundingStudy supported by Wellcome Trust Strategic Award 104036/Z/14/Z. GS:SFHS funded by the Scottish Government Health Department, Chief Scientist Office, number CZD/16/6.

Genetics↗

bioRxiv2016

A genome-wide haplotype association analysis of major depressive disorder identifies two genome-wide significant haplotypes

Genome-wide association studies using genotype data have had limited success in the identification of variants associated with major depressive disorder (MDD). Haplotype data provide an alternative method for detecting associations between variants in weak linkage disequilibrium with genotyped variants and a given trait of interest. A genome-wide haplotype association study for MDD was undertaken utilising a family-based population cohort, Generation Scotland: Scottish Family Health Study (n = 18 773), as a discovery cohort with UK Biobank used as a population-based cohort replication cohort (n = 25 035). Fine mapping of haplotype boundaries was used to account for overlapping haplotypes potentially tagging the same causal variant. Within the discovery cohort, two haplotypes exceeded genome-wide significance (P < 5 x 10-8) for an association with MDD. One of these haplotypes was nominally significant in the replication cohort (P < 0.05) and was located in 6q21, a region which has been previously associated with bipolar disorder, a psychiatric disorder that is phenotypically and genetically correlated with MDD. Several haplotypes with P < 10-7 in the discovery cohort were located within gene coding regions associated with diseases that are comorbid with MDD. Using such haplotypes to highlight regions for sequencing may lead to the identification of the underlying causal variants.

Genetics↗

bioRxiv2016

Do Regional Brain Volumes and Major Depressive Disorder Share Genetic Architecture: a study in Generation Scotland (n=19,762), UK Biobank (n=24,048) and the English Longitudinal Study of Ageing (n=5,766)

Major depressive disorder (MDD) is a heritable and highly debilitating condition. It is commonly associated with subcortical volumetric abnormalities, the most replicated of these being reduced hippocampal volume. Using the most recent published data from ENIGMA consortiums genome-wide association study (GWAS) of regional brain volume, we sought to test whether there is shared genetic architecture between 8 subcortical brain volumes and MDD. Using LD score regression utilising summary statistics from ENIGMA and the Psychiatric Genomics Consortium, we demonstrated that hippocampal volume was positively genetically correlated with MDD (rG=0.46, P=0.02), although this did not survive multiple comparison testing. None of other six brain regions studied were genetically correlated and amygdala volume heritability was too low for analysis. We also generated polygenic risk scores (PRS) to assess potential pleiotropy between regional brain volumes and MDD in three cohorts (Generation Scotland; Scottish Family Health Study (n=19,762), UK Biobank (n=24,048) and the English Longitudinal Study of Ageing (n=5,766). We used logistic regression to examine volumetric PRS and MDD and performed a meta-analysis across the three cohorts. No regional volumetric PRS demonstrated significant association with MDD or recurrent MDD. In this study we provide some evidence that hippocampal volume and MDD may share genetic architecture, albeit this did not survive multiple testing correction and was in the opposite direction to most reported phenotypic correlations. We therefore found no evidence to support a shared genetic architecture for MDD and regional subcortical volumes.

Genetics↗

bioRxiv2016

Genetic and environmental risk for chronic pain and the contribution of risk variants for psychiatric disorders. Results from Generation Scotland: Scottish Family Health Study and UK Biobank

BackgroundChronic pain is highly prevalent worldwide and a significant source of disability, yet its genetic and environmental risk factors are poorly understood. Its relationship with psychiatric illness, and major depressive disorder (MDD) in particular, is of particular importance. We sought to test the contribution of genetic factors and shared and unique environment to risk of chronic pain and its correlation with MDD in Generation Scotland: Scottish Family Health Study (GS:SFHS). We then sought to replicate any significant findings in the UK Biobank study.\n\nMethodsUsing family-based mixed-model analyses, we examined the contribution of genetics and environment to chronic pain using spouse, sibling and household groups as measures of shared environment. We then examined the correlation between chronic pain and MDD and estimated the contribution of genetic factors and shared environment. Finally, we used data from two independent genome-wide association studies to test whether chronic pain has a polygenic risk architecture and examine whether genomic risk of psychiatric disorder predicted chronic pain and whether genomic risk of chronic pain predicted MDD.\n\nResultsChronic pain is a moderately heritable trait (narrow sense heritability = 38.4%) which is more likely to be concordant in spouses and partners (variance explained 18.7%). Chronic pain is positively correlated with depression (rho = 0.13, p = 2.72x10-68) and it shows a tendency to cluster within families for genetic reasons (genetic correlation rho = 0.51, p = 8.24x10-19). Polygenic risk profiles for pain, generated using independent GWAS data, predicted chronic pain in both GS:SFHS (maximum {beta} = 6.18x10-2, p = 4.3x10-4) and UK Biobank (maximum {beta} = 5.68 x 10-2, p < 3x10-4). Genomic risk of MDD is also significantly associated with chronic pain in both GS:SFHS (maximum {beta} = 6.62x10-2, p = 4.3x10-4) and UK Biobank (maximum {beta} = 2.56x10-2, p < 3x10-4).\n\nConclusionsGenetic factors and chronic pain in a partner or spouse contribute substantially to the risk of chronic pain in the general population. Chronic pain is genetically correlated with MDD, has a polygenic architecture and is predicted by polygenic risk of MDD.

Genomics↗