scholarly journals Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK Biobank

2016 ◽  
Author(s):  
David M. Howard ◽  
Lynsey S. Hall ◽  
Jonathan D. Hafferty ◽  
Yanni Zeng ◽  
Mark J. Adams ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Replication Cohort ◽  
Discovery Cohort ◽  
Major Depressive ◽  
Genome Wide ◽  
Generation Scotland ◽  
A Genome

ABSTRACTGenome-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 × 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.

scholarly journals Genome-wide haplotype-based association analysis of major depressive disorder in Generation Scotland and UK Biobank

2017 ◽  
Vol 7 (11) ◽  
Author(s):  
David M. Howard ◽  
Lynsey S. Hall ◽  
Jonathan D. Hafferty ◽  
Yanni Zeng ◽  
Mark J. Adams ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Association Analysis ◽  
Uk Biobank ◽  
Major Depressive ◽  
Genome Wide ◽  
Generation Scotland

scholarly journals Genome-wide interaction study of a proxy for stress-sensitivity and its prediction of major depressive disorder

2017 ◽  
Author(s):  
Aleix Arnau-Soler ◽  
Mark J. Adams ◽  
Caroline Hayward ◽  
Pippa A. Thomson ◽  
◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Stress Sensitivity ◽  
Negative Regulator ◽  
Risk Scores ◽  
Uk Biobank ◽  
Major Depressive ◽  
Polygenic Risk ◽  
Genome Wide ◽  
Generation Scotland

AbstractIndividual response to stress is correlated with neuroticism and is an important predictor of both neuroticism and the onset of major depressive disorder (MDD). Identification of the genetics underpinning individual differences in response to negative events (stress-sensitivity) may improve our understanding of the molecular pathways involved, and its association with stress-related illnesses. We sought to generate a proxy for stress-sensitivity through modelling the interaction between SNP allele and MDD status on neuroticism score in order to identify genetic variants that contribute to the higher neuroticism seen in individuals with a lifetime diagnosis of depression compared to unaffected individuals. Meta-analysis of genome-wide interaction studies (GWIS) in UK Biobank (N = 23,092) and Generation Scotland: Scottish Family Health Study (N = 7,155) identified no genome-wide significance SNP interactions. However, gene-based tests identified a genome-wide significant gene, ZNF366, a negative regulator of glucocorticoid receptor function implicated in alcohol dependence (p = 1.48×10-7; Bonferroni-corrected significance threshold p < 2.79×10-6). Using summary statistics from the stress-sensitivity term of the GWIS, SNP heritability for stress-sensitivity was estimated at 5.0%. In models fitting polygenic risk scores of both MDD and neuroticism derived from independent GWAS, we show that polygenic risk scores derived from the UK Biobank stress-sensitivity GWIS significantly improved the prediction of MDD in Generation Scotland. This study may improve interpretation of larger genome-wide association studies of MDD and other stress-related illnesses, and the understanding of the etiological mechanisms underpinning stress-sensitivity.

scholarly journals The overlap of genetic susceptibility to schizophrenia and cardiometabolic disease can be used to identify metabolically different groups of individuals

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Rona J. Strawbridge ◽  
Keira J. A. Johnston ◽  
Mark E. S. Bailey ◽  
Damiano Baldassarre ◽  
Breda Cullen ◽  
...  
Keyword(s):  
Bipolar Disorder ◽  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
European Ancestry ◽  
Cardiometabolic Disease ◽  
Metabolic Profiles ◽  
Genome Wide Association Studies ◽  
Uk Biobank ◽  
Major Depressive ◽  
Increased Risk

AbstractUnderstanding why individuals with severe mental illness (Schizophrenia, Bipolar Disorder and Major Depressive Disorder) have increased risk of cardiometabolic disease (including obesity, type 2 diabetes and cardiovascular disease), and identifying those at highest risk of cardiometabolic disease are important priority areas for researchers. For individuals with European ancestry we explored whether genetic variation could identify sub-groups with different metabolic profiles. Loci associated with schizophrenia, bipolar disorder and major depressive disorder from previous genome-wide association studies and loci that were also implicated in cardiometabolic processes and diseases were selected. In the IMPROVE study (a high cardiovascular risk sample) and UK Biobank (general population sample) multidimensional scaling was applied to genetic variants implicated in both psychiatric and cardiometabolic disorders. Visual inspection of the resulting plots used to identify distinct clusters. Differences between these clusters were assessed using chi-squared and Kruskall-Wallis tests. In IMPROVE, genetic loci associated with both schizophrenia and cardiometabolic disease (but not bipolar disorder or major depressive disorder) identified three groups of individuals with distinct metabolic profiles. This grouping was replicated within UK Biobank, with somewhat less distinction between metabolic profiles. This work focused on individuals of European ancestry and is unlikely to apply to more genetically diverse populations. Overall, this study provides proof of concept that common biology underlying mental and physical illness may help to stratify subsets of individuals with different cardiometabolic profiles.

scholarly journals SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): joint mapping of common and rare variation affecting complex traits

2021 ◽  
Author(s):  
Richard F Oppong ◽  
Pau Navarro ◽  
Chris S Haley ◽  
Sara Knott
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Complex Traits ◽  
Health Study ◽  
P Value ◽  
Major Depressive ◽  
Genome Wide ◽  
A Genome ◽  
Joint Mapping ◽  
Genomic Regions

We describe a genome-wide analytical approach, SNP and Haplotype Regional Heritability Mapping (SNHap-RHM), that provides regional estimates of the heritability across locally defined regions in the genome. This approach utilises relationship matrices that are based on sharing of SNP and haplotype alleles at local haplotype blocks delimited by recombination boundaries in the genome. We implemented the approach on simulated data and show that the haplotype-based regional GRMs capture variation that is complementary to that captured by SNP-based regional GRMs, and thus justifying the fitting of the two GRMs jointly in a single analysis (SNHap-RHM). SNHap-RHM captures regions in the genome contributing to the phenotypic variation that existing genome-wide analysis methods may fail to capture. We further demonstrate that there are real benefits to be gained from this approach by applying it to real data from about 20,000 individuals from the Generation Scotland: Scottish Family Health Study. We analysed height and major depressive disorder (MDD). We identified seven genomic regions that are genome-wide significant for height, and three regions significant at a suggestive threshold (p-value <1x10^(-5) ) for MDD. These significant regions have genes mapped to within 400kb of them. The genes mapped for height have been reported to be associated with height in humans, whiles those mapped for MDD have been reported to be associated with major depressive disorder and other psychiatry phenotypes. The results show that SNHap-RHM presents an exciting new opportunity to analyse complex traits by allowing the joint mapping of novel genomic regions tagged by either SNPs or haplotypes, potentially leading to the recovery of some of the "missing" heritability.

scholarly journals Genome-wide DNA methylation in 1-year-old infants of mothers with major depressive disorder

2016 ◽  
Vol 28 (4pt2) ◽  
pp. 1413-1419 ◽  
Author(s):  
Dante Cicchetti ◽  
Susan Hetzel ◽  
Fred A. Rogosch ◽  
Elizabeth D. Handley ◽  
Sheree L. Toth
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Low Income ◽  
Neuronal Development ◽  
Colonic Neoplasms ◽  
Major Depressive ◽  
Process Networks ◽  
Genome Wide ◽  
A Genome ◽  
Depressed Mothers

AbstractA genome-wide methylation study was conducted among a sample of 114 infants (M age = 13.2 months, SD = 1.08) of low-income urban women with (n = 73) and without (n = 41) major depressive disorder. The Illumina HumanMethylation450 BeadChip array with a GenomeStudio Methylation Module and Illumina Custom model were used to conduct differential methylation analyses. Using the 5.0 × 10–7p value, 2,119 loci were found to be significantly different between infants of depressed and nondepressed mothers. Infants of depressed mothers had greater methylation at low methylation sites (0%–29%) compared to infants of nondepressed mothers. At high levels of methylation (70%–100%), the infants of depressed mothers were predominantly hypomethylated. The mean difference in methylation between the infants of depressed and infants of nondepressed mothers was 5.23%. Disease by biomarker analyses were also conducted using GeneGo MetaCore Software. The results indicated significant cancer-related differences in biomarker networks such as prostatic neoplasms, ovarian and breast neoplasms, and colonic neoplasms. The results of a process networks analysis indicated significant differences in process networks associated with neuronal development and central nervous system functioning, as well as cardiac development between infants of depressed and nondepressed mothers. These findings indicate that early in development, infants of mothers with major depressive disorder evince epigenetic differences relative to infants of well mothers that suggest risk for later adverse health outcomes.

scholarly journals Genome-Wide Significance for PCLO as a Gene for Major Depressive Disorder

2017 ◽  
Vol 20 (4) ◽  
pp. 267-270 ◽  
Author(s):  
Hamdi Mbarek ◽  
Yuri Milaneschi ◽  
Jouke-Jan Hottenga ◽  
Lannie Ligthart ◽  
Eco J. C. de Geus ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Genome Wide Association Study ◽  
Major Depressive ◽  
Significance Level ◽  
Functional Studies ◽  
Genome Wide ◽  
A Genome ◽  
Genome Wide Significance

In 2009, the first genome-wide association study (GWAS) for major depressive disorder (MDD) highlighted an association with PCLO locus on chromosome 7, although not reaching genome-wide significance level. In the present study, we revisited the original GWAS after increasing the overall sample size and the number of interrogated SNPs. In an analysis comparing 1,942 cases with lifetime diagnosis of MDD and 4,565 controls, PCLO showed a genome-wide significant association with MDD at SNP (rs2715157, p = 2.91 × 10−8) and gene-based (p = 1.48 × 10−7) level. Our results confirm the potential role of the PCLO gene in MDD, which is worth further replication and functional studies.

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