scholarly journals Cross-Disorder Genomics Data Analysis Elucidates a Shared Genetic Basis Between Major Depression and Osteoarthritis Pain

2021 ◽  
Vol 12 ◽  
Author(s):  
Sophie Barowsky ◽  
Jae-Yoon Jung ◽  
Nicholas Nesbit ◽  
Micah Silberstein ◽  
Maurizio Fava ◽  
...  

Osteoarthritis (OA) and major depression (MD) are two debilitating disorders that frequently co-occur and affect millions of the elderly each year. Despite the greater symptom severity, poorer clinical outcomes, and increased mortality of the comorbid conditions, we have a limited understanding of their etiologic relationships. In this study, we conducted the first cross-disorder investigations of OA and MD, using genome-wide association data representing over 247K cases and 475K controls. Along with significant positive genome-wide genetic correlations (rg = 0.299 ± 0.026, p = 9.10 × 10–31), Mendelian randomization (MR) analysis identified a bidirectional causal effect between OA and MD (βOA→MD = 0.09, SE = 0.02, z-score p-value < 1.02 × 10–5; βMD→OA = 0.19, SE = 0.026, p < 2.67 × 10–13), indicating genetic variants affecting OA risk are, in part, shared with those influencing MD risk. Cross-disorder meta-analysis of OA and MD identified 56 genomic risk loci (Pmeta ≤ 5 × 10–8), which show heightened expression of the associated genes in the brain and pituitary. Gene-set enrichment analysis highlighted “mechanosensory behavior” genes (GO:0007638; Pgene_set = 2.45 × 10–8) as potential biological mechanisms that simultaneously increase susceptibility to these mental and physical health conditions. Taken together, these findings show that OA and MD share common genetic risk mechanisms, one of which centers on the neural response to the sensation of mechanical stimulus. Further investigation is warranted to elaborate the etiologic mechanisms of the pleiotropic risk genes, as well as to develop early intervention and integrative clinical care of these serious conditions that disproportionally affect the aging population.

SLEEP ◽  
2020 ◽  
Vol 43 (9) ◽  
Author(s):  
Om Prakash Kafle ◽  
Shiqiang Cheng ◽  
Mei Ma ◽  
Ping Li ◽  
Bolun Cheng ◽  
...  

Abstract Study Objectives Insomnia is a common sleep disorder and constitutes a major issue in modern society. We provide new clues for revealing the association between environmental chemicals and insomnia. Methods Three genome-wide association studies (GWAS) summary datasets of insomnia (n = 113,006, n = 1,331,010, and n = 453,379, respectively) were driven from the UK Biobank, 23andMe, and deCODE. The chemical–gene interaction dataset was downloaded from the Comparative Toxicogenomics Database. First, we conducted a meta-analysis of the three datasets of insomnia using the METAL software. Using the result of meta-analysis, transcriptome-wide association studies were performed to calculate the expression association testing statistics of insomnia. Then chemical-related gene set enrichment analysis (GSEA) was used to explore the association between chemicals and insomnia. Results For GWAS meta-analysis dataset of insomnia, we identified 42 chemicals associated with insomnia in brain tissue (p < 0.05) by GSEA. We detected five important chemicals such as pinosylvin (p = 0.0128), bromobenzene (p = 0.0134), clonidine (p = 0.0372), gabapentin (p = 0.0372), and melatonin (p = 0.0404) which are directly associated with insomnia. Conclusion Our study results provide new clues for revealing the roles of environmental chemicals in the development of insomnia.


2018 ◽  
Vol 2 (21) ◽  
pp. 2862-2878 ◽  
Author(s):  
Vanessa Sue Wacleche ◽  
Amélie Cattin ◽  
Jean-Philippe Goulet ◽  
Dominique Gauchat ◽  
Annie Gosselin ◽  
...  

Abstract Classical CD16− vs intermediate/nonclassical CD16+ monocytes differ in their homing potential and biological functions, but whether they differentiate into dendritic cells (DCs) with distinct contributions to immunity against bacterial/viral pathogens remains poorly investigated. Here, we employed a systems biology approach to identify clinically relevant differences between CD16+ and CD16− monocyte-derived DCs (MDDCs). Although both CD16+ and CD16− MDDCs acquire classical immature/mature DC markers in vitro, genome-wide transcriptional profiling revealed unique molecular signatures for CD16+ MDDCs, including adhesion molecules (ITGAE/CD103), transcription factors (TCF7L2/TCF4), and enzymes (ALDH1A2/RALDH2), whereas CD16− MDDCs exhibit a CDH1/E-cadherin+ phenotype. Of note, lipopolysaccharides (LPS) upregulated distinct transcripts in CD16+ (eg, CCL8, SIGLEC1, MIR4439, SCIN, interleukin [IL]-7R, PLTP, tumor necrosis factor [TNF]) and CD16− MDDCs (eg, MMP10, MMP1, TGM2, IL-1A, TNFRSF11A, lysosomal-associated membrane protein 1, MMP8). Also, unique sets of HIV-modulated genes were identified in the 2 subsets. Further gene set enrichment analysis identified canonical pathways that pointed to “inflammation” as the major feature of CD16+ MDDCs at immature stage and on LPS/HIV exposure. Finally, functional validations and meta-analysis comparing the transcriptome of monocyte and MDDC subsets revealed that CD16+ vs CD16− monocytes preserved their superior ability to produce TNF-α and CCL22, as well as other sets of transcripts (eg, TCF4), during differentiation into DC. These results provide evidence that monocyte subsets are transcriptionally imprinted/programmed with specific differentiation fates, with intermediate/nonclassical CD16+ monocytes being precursors for pro-inflammatory CD103+RALDH2+TCF4+ DCs that may play key roles in mucosal immunity homeostasis/pathogenesis. Thus, alterations in the CD16+/CD16− monocyte ratios during pathological conditions may dramatically influence the quality of MDDC-mediated immunity.


Author(s):  
Shuai Yuan ◽  
Maria Bruzelius ◽  
Susanna C. Larsson

AbstractWhether renal function is causally associated with venous thromboembolism (VTE) is not yet fully elucidated. We conducted a two-sample Mendelian randomization (MR) study to determine the causal effect of renal function, measured as estimated glomerular filtration rate (eGFR), on VTE. Single-nucleotide polymorphisms associated with eGFR were selected as instrumental variables at the genome-wide significance level (p < 5 × 10−8) from a meta-analysis of 122 genome-wide association studies including up to 1,046,070 individuals. Summary-level data for VTE were obtained from the FinnGen consortium (6913 VTE cases and 169,986 non-cases) and UK Biobank study (4620 VTE cases and 356,574 non-cases). MR estimates were calculated using the random-effects inverse-variance weighted method and combined using fixed-effects meta-analysis. Genetically predicted decreased eGFR was significantly associated with an increased risk of VTE in both FinnGen and UK Biobank. For one-unit decrease in log-transformed eGFR, the odds ratios of VTE were 2.93 (95% confidence interval (CI) 1.25, 6.84) and 4.46 (95% CI 1.59, 12.5) when using data from FinnGen and UK Biobank, respectively. The combined odds ratio was 3.47 (95% CI 1.80, 6.68). Results were consistent in all sensitivity analyses and no horizontal pleiotropy was detected. This MR-study supported a casual role of impaired renal function in VTE.


2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Jovana Maksimovic ◽  
Alicia Oshlack ◽  
Belinda Phipson

AbstractDNA methylation is one of the most commonly studied epigenetic marks, due to its role in disease and development. Illumina methylation arrays have been extensively used to measure methylation across the human genome. Methylation array analysis has primarily focused on preprocessing, normalization, and identification of differentially methylated CpGs and regions. GOmeth and GOregion are new methods for performing unbiased gene set testing following differential methylation analysis. Benchmarking analyses demonstrate GOmeth outperforms other approaches, and GOregion is the first method for gene set testing of differentially methylated regions. Both methods are publicly available in the missMethyl Bioconductor R package.


2011 ◽  
Vol 10 (4) ◽  
pp. 3856-3887 ◽  
Author(s):  
Q.Y. Ning ◽  
J.Z. Wu ◽  
N. Zang ◽  
J. Liang ◽  
Y.L. Hu ◽  
...  

2020 ◽  
Author(s):  
Eshim S Jami ◽  
Anke R Hammerschlag ◽  
Hill F Ip ◽  
Andrea G Allegrini ◽  
Beben Benyamin ◽  
...  

Internalising symptoms in childhood and adolescence are as heritable as adult depression and anxiety, yet little is known of their molecular basis. This genome-wide association meta-analysis of internalising symptoms included repeated observations from 64,641 individuals, aged between 3 and 18. The N-weighted meta-analysis of overall internalising symptoms (INToverall) detected no genome-wide significant hits and showed low SNP heritability (1.66%, 95% confidence intervals 0.84-2.48%, Neffective=132,260). Stratified analyses showed rater-based heterogeneity in genetic effects, with self-reported internalising symptoms showing the highest heritability (5.63%, 95% confidence intervals 3.08-8.18%). Additive genetic effects on internalising symptoms appeared stable over age, with overlapping estimates of SNP heritability from early-childhood to adolescence. Gene-based analyses showed significant associations with three genes: WNT3 (p=1.13×10-06), CCL26 (p=1.88×10-06), and CENPO (p=2.54×10-06). Of these, WNT3 was previously associated with neuroticism, with which INToverall also shared a strong genetic correlation (rg=0.76). Genetic correlations were also observed with adult anxiety, depression, and the wellbeing spectrum (|rg|> 0.70), as well as with insomnia, loneliness, attention-deficit hyperactivity disorder, autism, and childhood aggression (range |rg|=0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa. Overall, childhood and adolescent internalising symptoms share substantial genetic vulnerabilities with adult internalising disorders and other childhood psychiatric traits, which could explain both the persistence of internalising symptoms over time, and the high comorbidity amongst childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.


2018 ◽  
Author(s):  
David M. Howard ◽  
Mark J. Adams ◽  
Toni-Kim Clarke ◽  
Jonathan D. Hafferty ◽  
Jude Gibson ◽  
...  

AbstractMajor depression is a debilitating psychiatric illness that is typically associated with low mood, anhedonia and a range of comorbidities. Depression has a heritable component that has remained difficult to elucidate with current sample sizes due to the polygenic nature of the disorder. To maximise sample size, we meta-analysed data on 807,553 individuals (246,363 cases and 561,190 controls) from the three largest genome-wide association studies of depression. We identified 102 independent variants, 269 genes, and 15 gene-sets associated with depression, including both genes and gene-pathways associated with synaptic structure and neurotransmission. Further evidence of the importance of prefrontal brain regions in depression was provided by an enrichment analysis. In an independent replication sample of 1,306,354 individuals (414,055 cases and 892,299 controls), 87 of the 102 associated variants were significant following multiple testing correction. Based on the putative genes associated with depression this work also highlights several potential drug repositioning opportunities. These findings advance our understanding of the complex genetic architecture of depression and provide several future avenues for understanding aetiology and developing new treatment approaches.


2020 ◽  
pp. annrheumdis-2020-219209
Author(s):  
Xianyong Yin ◽  
Kwangwoo Kim ◽  
Hiroyuki Suetsugu ◽  
So-Young Bang ◽  
Leilei Wen ◽  
...  

ObjectiveSystemic lupus erythematosus (SLE), an autoimmune disorder, has been associated with nearly 100 susceptibility loci. Nevertheless, these loci only partially explain SLE heritability and their putative causal variants are rarely prioritised, which make challenging to elucidate disease biology. To detect new SLE loci and causal variants, we performed the largest genome-wide meta-analysis for SLE in East Asian populations.MethodsWe newly genotyped 10 029 SLE cases and 180 167 controls and subsequently meta-analysed them jointly with 3348 SLE cases and 14 826 controls from published studies in East Asians. We further applied a Bayesian statistical approach to localise the putative causal variants for SLE associations.ResultsWe identified 113 genetic regions including 46 novel loci at genome-wide significance (p<5×10−8). Conditional analysis detected 233 association signals within these loci, which suggest widespread allelic heterogeneity. We detected genome-wide associations at six new missense variants. Bayesian statistical fine-mapping analysis prioritised the putative causal variants to a small set of variants (95% credible set size ≤10) for 28 association signals. We identified 110 putative causal variants with posterior probabilities ≥0.1 for 57 SLE loci, among which we prioritised 10 most likely putative causal variants (posterior probability ≥0.8). Linkage disequilibrium score regression detected genetic correlations for SLE with albumin/globulin ratio (rg=−0.242) and non-albumin protein (rg=0.238).ConclusionThis study reiterates the power of large-scale genome-wide meta-analysis for novel genetic discovery. These findings shed light on genetic and biological understandings of SLE.


Blood ◽  
2019 ◽  
Vol 133 (9) ◽  
pp. 967-977 ◽  
Author(s):  
Paul S. de Vries ◽  
Maria Sabater-Lleal ◽  
Jennifer E. Huffman ◽  
Jonathan Marten ◽  
Ci Song ◽  
...  

Abstract Factor VII (FVII) is an important component of the coagulation cascade. Few genetic loci regulating FVII activity and/or levels have been discovered to date. We conducted a meta-analysis of 9 genome-wide association studies of plasma FVII levels (7 FVII activity and 2 FVII antigen) among 27 495 participants of European and African ancestry. Each study performed ancestry-specific association analyses. Inverse variance weighted meta-analysis was performed within each ancestry group and then combined for a trans-ancestry meta-analysis. Our primary analysis included the 7 studies that measured FVII activity, and a secondary analysis included all 9 studies. We provided functional genomic validation for newly identified significant loci by silencing candidate genes in a human liver cell line (HuH7) using small-interfering RNA and then measuring F7 messenger RNA and FVII protein expression. Lastly, we used meta-analysis results to perform Mendelian randomization analysis to estimate the causal effect of FVII activity on coronary artery disease, ischemic stroke (IS), and venous thromboembolism. We identified 2 novel (REEP3 and JAZF1-AS1) and 6 known loci associated with FVII activity, explaining 19.0% of the phenotypic variance. Adding FVII antigen data to the meta-analysis did not result in the discovery of further loci. Silencing REEP3 in HuH7 cells upregulated FVII, whereas silencing JAZF1 downregulated FVII. Mendelian randomization analyses suggest that FVII activity has a positive causal effect on the risk of IS. Variants at REEP3 and JAZF1 contribute to FVII activity by regulating F7 expression levels. FVII activity appears to contribute to the etiology of IS in the general population.


2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Emrin Horgusluoglu-Moloch ◽  
◽  
Shannon L. Risacher ◽  
Paul K. Crane ◽  
Derrek Hibar ◽  
...  

Abstract Adult neurogenesis occurs in the dentate gyrus of the hippocampus during adulthood and contributes to sustaining the hippocampal formation. To investigate whether neurogenesis-related pathways are associated with hippocampal volume, we performed gene-set enrichment analysis using summary statistics from a large-scale genome-wide association study (N = 13,163) of hippocampal volume from the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium and two year hippocampal volume changes from baseline in cognitively normal individuals from Alzheimer’s Disease Neuroimaging Initiative Cohort (ADNI). Gene-set enrichment analysis of hippocampal volume identified 44 significantly enriched biological pathways (FDR corrected p-value < 0.05), of which 38 pathways were related to neurogenesis-related processes including neurogenesis, generation of new neurons, neuronal development, and neuronal migration and differentiation. For genes highly represented in the significantly enriched neurogenesis-related pathways, gene-based association analysis identified TESC, ACVR1, MSRB3, and DPP4 as significantly associated with hippocampal volume. Furthermore, co-expression network-based functional analysis of gene expression data in the hippocampal subfields, CA1 and CA3, from 32 normal controls showed that distinct co-expression modules were mostly enriched in neurogenesis related pathways. Our results suggest that neurogenesis-related pathways may be enriched for hippocampal volume and that hippocampal volume may serve as a potential phenotype for the investigation of human adult neurogenesis.


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