scholarly journals SNP and Haplotype Regional Heritability Mapping (SNHap-RHM): Joint Mapping of Common and Rare Variation Affecting Complex Traits

2022 ◽  
Vol 12 ◽  
Author(s):  
Richard F. Oppong ◽  
Thibaud Boutin ◽  
Archie Campbell ◽  
Andrew M. McIntosh ◽  
David Porteous ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Complex Traits ◽  
Simulated Data ◽  
Health Study ◽  
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 < 1 × 10−5) for MDD. These significant regions have genes mapped to within 400 kb of them. The genes mapped for height have been reported to be associated with height in humans. Similarly, 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 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.

scholarly journals Using genetic drug-target networks to develop new drug hypotheses for major depressive disorder

2018 ◽  
Author(s):  
Héléna A Gaspar ◽  
Zachary Gerring ◽  
Christopher Hübel ◽  
Christel M Middeldorp ◽  
Eske M Derks ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Drug Target ◽  
Model Systems ◽  
Genome Wide Association ◽  
Multiple Testing Correction ◽  
Major Depressive ◽  
Expression Levels ◽  
Genome Wide ◽  
A Genome

AbstractThe major depressive disorder (MDD) working group of the Psychiatric Genomics Consortium (PGC) has published a genome-wide association study (GWAS) for MDD in 130,664 cases, identifying 44 risk variants. We used these results to investigate potential drug targets and repurposing opportunities. We built easily interpretable bipartite drug-target networks integrating interactions between drugs and their targets, genome-wide association statistics and genetically predicted expression levels in different tissues, using our online tool Drug Targetor (drugtargetor.com). We also investigated drug-target relationships and drug effects on gene expression that could be impacting MDD. MAGMA was used to perform pathway analyses and S-PrediXcan to investigate the directionality of tissue-specific expression levels in patients vs. controls. Outside the major histocompatibility complex (MHC) region, 25 druggable genes were significantly associated with MDD after multiple testing correction, and 19 were suggestively significant. Several drug classes were significantly enriched, including monoamine reuptake inhibitors, sex hormones, antipsychotics and antihistamines, indicating an effect on MDD and potential repurposing opportunities. These findings require validation in model systems and clinical examination, but also show that GWAS may become a rich source of new therapeutic hypotheses for MDD and other psychiatric disorders that need new – and better – treatment options.

scholarly journals Genome-wide association analyses identify 44 risk variants and refine the genetic architecture of major depressive disorder

2017 ◽  
Author(s):  
Naomi R Wray ◽  
Stephan Ripke ◽  
Manuel Mattheisen ◽  
Maciej Trzaskowski ◽  
Enda M Byrne ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Educational Attainment ◽  
Body Mass ◽  
Genetic Risk ◽  
Genome Wide Association ◽  
Continuous Measure ◽  
Major Depressive ◽  
Genome Wide ◽  
A Genome

Major depressive disorder (MDD) is a notably complex illness with a lifetime prevalence of 14%.1 It is often chronic or recurrent and is thus accompanied by considerable morbidity, excess mortality, substantial costs, and heightened risk of suicide.2-7 MDD is a major cause of disability worldwide.8 We conducted a genome-wide association (GWA) meta-analysis in 130,664 MDD cases and 330,470 controls, and identified 44 independent loci that met criteria for statistical significance. We present extensive analyses of these results which provide new insights into the nature of MDD. The genetic findings were associated with clinical features of MDD, and implicated prefrontal and anterior cingulate cortex in the pathophysiology of MDD (regions exhibiting anatomical differences between MDD cases and controls). Genes that are targets of antidepressant medications were strongly enriched for MDD association signals (P=8.5×10−10), suggesting the relevance of these findings for improved pharmacotherapy of MDD. Sets of genes involved in gene splicing and in creating isoforms were also enriched for smaller MDD GWA P-values, and these gene sets have also been implicated in schizophrenia and autism. Genetic risk for MDD was correlated with that for many adult and childhood onset psychiatric disorders. Our analyses suggested important relations of genetic risk for MDD with educational attainment, body mass, and schizophrenia: the genetic basis of lower educational attainment and higher body mass were putatively causal for MDD whereas MDD and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for MDD, and a continuous measure of risk underlies the observed clinical phenotype. MDD is not a distinct entity that neatly demarcates normalcy from pathology but rather a useful clinical construct associated with a range of adverse outcomes and the end result of a complex process of intertwined genetic and environmental effects. These findings help refine and define the fundamental basis of MDD.

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 copy number variation-, validation- and screening study implicates a novel copy number polymorphism associated with suicide attempts in major depressive disorder

2019 ◽  
Author(s):  
Shitao Rao ◽  
Mai Shi ◽  
Xinyu Han ◽  
Marco Ho Bun Lam ◽  
Guangming Liu ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Copy Number ◽  
Suicide Attempts ◽  
Copy Number Variations ◽  
P Value ◽  
Major Depressive ◽  
Global Rate ◽  
Genome Wide ◽  
A Genome

AbstractBackgroundThe genetic basis of suicide attempts (SA) remained unclear, especially for the copy number variations (CNVs) involved. The present study aimed to identify the susceptibility variants associated with SA among major depressive disorder (MDD) patients in Chinese, covering both single-nucleotide polymorphisms and CNVs.MethodsWe conducted GWAS on MDD patients with or without SA and top results were tested in a replication study. A genome-wide CNV study was performed. Subsequently, a validation assay using the qRT-PCR technology was performed to confirm the existence of the associated CNV and then applied to the entire cohort to examine the association.ResultsIn CNV analysis, we found that the global rate of CNV was higher in SA compared to non-SA subjects (p=0.023). The genome-wide CNV study revealed a SA-associated CNV region that achieved genome-wide significance (corrected p-value=0.014). The associated CNV was successfully validated and identified to be a common variant in this cohort and its deletion rate was higher in suicide attempters (OR=2.05). Based on the GTEx database, genetic variants that probe this CNV was significantly associated with the expression level of ZNF33B in two brain regions (p-value<4.2e-05). Besides, there was a significant interaction between neuroticism and the CNV in affecting suicidal risk; the CNV showed a significant effect (OR=2.58) in subjects with high neuroticism only.ConclusionsWe identified a new common CNV that may be involved in the etiology of SA. These findings imply an important role of common CNVs in the etiology of SA, which suggests a new promising avenue for investigating the genetic architecture of SA.

Genome-wide linkage scan of major depressive disorder in two Dagestan genetic isolates

Open Medicine ◽  
2011 ◽  
Vol 6 (5) ◽  
pp. 616-624
Author(s):  
Kazima Bulayeva ◽  
Todd Lencz ◽  
Stephen Glatt ◽  
Toru Takumi ◽  
Farida Gurgenova ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Major Depressive ◽  
Extended Pedigrees ◽  
Genome Wide ◽  
Genetic Isolates ◽  
Genomic Regions ◽  
Short Tandem Repeat Markers ◽  
Significant Linkage ◽  
Short Tandem

AbstractWe conducted a 10-cM genome-wide linkage scan in two extended pedigrees, ascertained from two diverse Dagestan genetic isolates with high aggregation of major depressive disorder (MDD) and suicides. Using genome wide multipoint parametric linkage analyses with short tandem repeat markers, we found two previously undetected genomic regions with significant linkage in isolate #6007 with LODs=3.1–3.4 at 2p13.2–p11.2 (and some signal in same region for #6008) and in 14q31.12–q32.13. We also obtained suggestive evidence for linkage with MDD at 9q33.3–q34.2 (#6008), 13q31.1–q31.2(#6007), 11p15(#6008), 17q25.3(#6007) and 19q13.31–q13.33 (#6008). Five regions (1p36.1–p35.2, 2p13.2–p11.2, 17q25.3, 18q22 and 22q12.3) demonstrated at least nominal linkage in both isolates’ pedigrees, while all other linkage regions demonstrated population-specific genetic heterogeneity.

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