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 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 association of major depression: description of samples for the GAIN Major Depressive Disorder Study: NTR and NESDA biobank projects

2008 ◽  
Vol 16 (3) ◽  
pp. 335-342 ◽  
Author(s):  
Dorret I Boomsma ◽  
Gonneke Willemsen ◽  
Patrick F Sullivan ◽  
Peter Heutink ◽  
Piet Meijer ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Major Depression ◽  
Depressive Disorder ◽  
Genome Wide Association ◽  
Major Depressive ◽  
Genome Wide
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