scholarly journals Genetic Associations with Aging Muscle: A Systematic Review

Cells ◽  
2019 ◽  
Vol 9 (1) ◽  
pp. 12 ◽  
Author(s):  
Jedd Pratt ◽  
Colin Boreham ◽  
Sean Ennis ◽  
Anthony W. Ryan ◽  
Giuseppe De Vito
Keyword(s):  
Skeletal Muscle ◽  
Genetic Association ◽  
Functional Disability ◽  
Association Studies ◽  
Final Analysis ◽  
Dna Polymorphisms ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Muscle Properties ◽  
Age Related

The age-related decline in skeletal muscle mass, strength and function known as ‘sarcopenia’ is associated with multiple adverse health outcomes, including cardiovascular disease, stroke, functional disability and mortality. While skeletal muscle properties are known to be highly heritable, evidence regarding the specific genes underpinning this heritability is currently inconclusive. This review aimed to identify genetic variants known to be associated with muscle phenotypes relevant to sarcopenia. PubMed, Embase and Web of Science were systematically searched (from January 2004 to March 2019) using pre-defined search terms such as “aging”, “sarcopenia”, “skeletal muscle”, “muscle strength” and “genetic association”. Candidate gene association studies and genome wide association studies that examined the genetic association with muscle phenotypes in non-institutionalised adults aged ≥50 years were included. Fifty-four studies were included in the final analysis. Twenty-six genes and 88 DNA polymorphisms were analysed across the 54 studies. The ACTN3, ACE and VDR genes were the most frequently studied, although the IGF1/IGFBP3, TNFα, APOE, CNTF/R and UCP2/3 genes were also shown to be significantly associated with muscle phenotypes in two or more studies. Ten DNA polymorphisms (rs154410, rs2228570, rs1800169, rs3093059, rs1800629, rs1815739, rs1799752, rs7412, rs429358 and 192 bp allele) were significantly associated with muscle phenotypes in two or more studies. Through the identification of key gene variants, this review furthers the elucidation of genetic associations with muscle phenotypes associated with sarcopenia.

scholarly journals Hearing difficulty is linked to Alzheimer’s disease by common genetic vulnerability, not shared genetic architecture

2021 ◽  
Vol 7 (1) ◽  
Author(s):  
Fatin N. Zainul Abidin ◽  
Helena R. R. Wells ◽  
Andre Altmann ◽  
Sally J. Dawson
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Genetic Correlation ◽  
Genetic Architecture ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Age Related ◽  
Hearing Difficulty ◽  
Shared Genetic

AbstractAge-related hearing loss was recently established as the largest modifiable risk factor for Alzheimer’s disease (AD), however, the reasons for this link remain unclear. We investigate shared underlying genetic associations using results from recent large genome-wide association studies (GWAS) on adult hearing difficulty and AD. Genetic correlation and Mendelian randomization (MR) analysis do not support a genetic correlation between the disorders, but suggest a direct causal link from AD genetic risk to hearing difficulty, driven by APOE. Systematic MR analyses on the effect of other traits revealed shared effects of glutamine, gamma-glutamylglutamine, and citrate levels on reduced risk of both hearing difficulty and AD. In addition, pathway analysis on GWAS risk variants suggests shared function in neuronal signalling pathways as well as etiology of diabetes and cardiovascular disease. However, after multiple testing corrections, neither analysis led to statistically significant associations. Altogether, our genetic-driven analysis suggests hearing difficulty and AD are linked by a shared vulnerability in molecular pathways rather than by a shared genetic architecture.

scholarly journals A Compendium of Age-Related PheWAS and GWAS Traits for Human Genetic Association Studies, Their Networks and Genetic Correlations

2021 ◽  
Vol 12 ◽  
Author(s):  
Seung-Soo Kim ◽  
Adam D. Hudgins ◽  
Brenda Gonzalez ◽  
Sofiya Milman ◽  
Nir Barzilai ◽  
...  
Keyword(s):  
Genetic Association ◽  
Heart Diseases ◽  
Association Studies ◽  
Genetic Correlations ◽  
Genetic Association Studies ◽  
Brain Diseases ◽  
Genome Wide Association Studies ◽  
Medical Subject Headings ◽  
Age Related ◽  
Rich Data

The rich data from the genome-wide association studies (GWAS) and phenome-wide association studies (PheWAS) offer an unprecedented opportunity to identify the biological underpinnings of age-related disease (ARD) risk and multimorbidity. Surprisingly, however, a comprehensive list of ARDs remains unavailable due to the lack of a clear definition and selection criteria. We developed a method to identify ARDs and to provide a compendium of ARDs for genetic association studies. Querying 1,358 electronic medical record-derived traits, we first defined ARDs and age-related traits (ARTs) based on their prevalence profiles, requiring a unimodal distribution that shows an increasing prevalence after the age of 40 years, and which reaches a maximum peak at 60 years of age or later. As a result, we identified a list of 463 ARDs and ARTs in the GWAS and PheWAS catalogs. We next translated the ARDs and ARTs to their respective 276 Medical Subject Headings diseases and 45 anatomy terms. The most abundant disease categories are neoplasms (48 terms), cardiovascular diseases (44 terms), and nervous system diseases (27 terms). Employing data from a human symptoms-disease network, we found 6 symptom-shared disease groups, representing cancers, heart diseases, brain diseases, joint diseases, eye diseases, and mixed diseases. Lastly, by overlaying our ARD and ART list with genetic correlation data from the UK Biobank, we found 54 phenotypes in 2 clusters with high genetic correlations. Our compendium of ARD and ART is a highly useful resource, with broad applicability for studies of the genetics of aging, ARD, and multimorbidity.

scholarly journals Genetic Associations Between IL-6 and the Development of Autoimmune Arthritis Are Gender-Specific

2021 ◽  
Vol 12 ◽  
Author(s):  
Jianqiao Hong ◽  
Zihao Qu ◽  
Xiaoxiao Ji ◽  
Congsun Li ◽  
Geng Zhang ◽  
...  
Keyword(s):  
Genetic Association ◽  
Sexual Difference ◽  
Association Studies ◽  
Autoimmune Arthritis ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Male Population ◽  
Female Population ◽  
Genome Wide ◽  
Mr Study

ObjectivesTo find out the genetic association between IL6 and autoimmune arthritis.MethodsWe performed a two-sample Mendelian randomization (MR) study using multiple genome-wide association studies (GWAS) datasets. Furthermore, a sex-stratified MR study was performed to identify sexual dimorphism in the association between IL6 and autoimmune arthritis. Then, LocusZoom plots were displayed based on the IL6R gene region to present evidence of genetic colocalization between diseases.ResultsThe MR result denoted a genetic association between the increased level of IL-6 signaling and risk of RA (β=0.325, 95%CI 0.088, 0.561, p=7.08E-03) and AS (β=1.240, 95%CI 0.495, 1.980, p=1.1E-03). Accordingly, sIL6R was found to have negatively correlation with the onset of RA (β=-0.020, 95%CI -0.0320, -0.008, p=1.18E-03) and AS (β=-0.125, 95%CI -0.177, -0.073, p=2.29E-06). However, no genetic association between IL6/sIL6R and PsA was detected. The gender-stratified MR analysis showed that IL6 was associated with AS in the male population, with RA in the female population, and with PsA in the male population. Additionally, ADAR, a gene identified by a sensitive test, could be the reason for the nonsignificant association between IL6 and PsA in a pooled population.ConclusionOur findings showed that the overactive IL6 signal pathway led to autoimmune arthritis, especially in RA and AS. Sexual difference was also observed in IL6-intermediate susceptibility to autoimmune arthritis.

scholarly journals Penalized partial least squares for pleiotropy

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Camilo Broc ◽  
Therese Truong ◽  
Benoit Liquet
Keyword(s):  
Least Squares ◽  
Partial Least Squares ◽  
Association Studies ◽  
A Priori ◽  
Simulated Data ◽  
Real Data ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Multiple Traits ◽  
Application Fields

Abstract Background The increasing number of genome-wide association studies (GWAS) has revealed several loci that are associated to multiple distinct phenotypes, suggesting the existence of pleiotropic effects. Highlighting these cross-phenotype genetic associations could help to identify and understand common biological mechanisms underlying some diseases. Common approaches test the association between genetic variants and multiple traits at the SNP level. In this paper, we propose a novel gene- and a pathway-level approach in the case where several independent GWAS on independent traits are available. The method is based on a generalization of the sparse group Partial Least Squares (sgPLS) to take into account groups of variables, and a Lasso penalization that links all independent data sets. This method, called joint-sgPLS, is able to convincingly detect signal at the variable level and at the group level. Results Our method has the advantage to propose a global readable model while coping with the architecture of data. It can outperform traditional methods and provides a wider insight in terms of a priori information. We compared the performance of the proposed method to other benchmark methods on simulated data and gave an example of application on real data with the aim to highlight common susceptibility variants to breast and thyroid cancers. Conclusion The joint-sgPLS shows interesting properties for detecting a signal. As an extension of the PLS, the method is suited for data with a large number of variables. The choice of Lasso penalization copes with architectures of groups of variables and observations sets. Furthermore, although the method has been applied to a genetic study, its formulation is adapted to any data with high number of variables and an exposed a priori architecture in other application fields.

scholarly journals Fine scale human genetic structure in three regions of Cameroon reveals episodic diversifying selection

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Kevin K. Esoh ◽  
Tobias O. Apinjoh ◽  
Steven G. Nyanjom ◽  
Ambroise Wonkam ◽  
Emile R. Chimusa ◽  
...  
Keyword(s):  
Genetic Structure ◽  
Ethnic Groups ◽  
Genetic Association ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Genomic Region ◽  
Sub Saharan Africa ◽  
Genome Wide Association Studies ◽  
Fine Scale ◽  
Sub Saharan

AbstractInferences from genetic association studies rely largely on the definition and description of the underlying populations that highlight their genetic similarities and differences. The clustering of human populations into subgroups (population structure) can significantly confound disease associations. This study investigated the fine-scale genetic structure within Cameroon that may underlie disparities observed with Cameroonian ethnicities in malaria genome-wide association studies in sub-Saharan Africa. Genotype data of 1073 individuals from three regions and three ethnic groups in Cameroon were analyzed using measures of genetic proximity to ascertain fine-scale genetic structure. Model-based clustering revealed distinct ancestral proportions among the Bantu, Semi-Bantu and Foulbe ethnic groups, while haplotype-based coancestry estimation revealed possible longstanding and ongoing sympatric differentiation among individuals of the Foulbe ethnic group, and their Bantu and Semi-Bantu counterparts. A genome scan found strong selection signatures in the HLA gene region, confirming longstanding knowledge of natural selection on this genomic region in African populations following immense disease pressure. Signatures of selection were also observed in the HBB gene cluster, a genomic region known to be under strong balancing selection in sub-Saharan Africa due to its co-evolution with malaria. This study further supports the role of evolution in shaping genomes of Cameroonian populations and reveals fine-scale hierarchical structure among and within Cameroonian ethnicities that may impact genetic association studies in the country.

scholarly journals Polygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum

2020 ◽  
Author(s):  
Niccolo’ Tesi ◽  
Sven J van der Lee ◽  
Marc Hulsman ◽  
Iris E Jansen ◽  
Najada Stringa ◽  
...  
Keyword(s):  
Older Adults ◽  
Cellular Response ◽  
Molecular Mechanisms ◽  
Association Studies ◽  
Risk Scores ◽  
Human Longevity ◽  
Polygenic Risk Score ◽  
Genome Wide Association Studies ◽  
Polygenic Risk ◽  
Age Related

Abstract Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p = .02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ε4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.

scholarly journals Genetic association studies of alterations in protein function expose recessive effects on cancer predisposition

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Nadav Brandes ◽  
Nathan Linial ◽  
Michal Linial
Keyword(s):  
Cancer Risk ◽  
Protein Function ◽  
Association Studies ◽  
Genetic Effects ◽  
Cancer Predisposition ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Gene Damage ◽  
Genomic Regions

AbstractThe characterization of germline genetic variation affecting cancer risk, known as cancer predisposition, is fundamental to preventive and personalized medicine. Studies of genetic cancer predisposition typically identify significant genomic regions based on family-based cohorts or genome-wide association studies (GWAS). However, the results of such studies rarely provide biological insight or functional interpretation. In this study, we conducted a comprehensive analysis of cancer predisposition in the UK Biobank cohort using a new gene-based method for detecting protein-coding genes that are functionally interpretable. Specifically, we conducted proteome-wide association studies (PWAS) to identify genetic associations mediated by alterations to protein function. With PWAS, we identified 110 significant gene-cancer associations in 70 unique genomic regions across nine cancer types and pan-cancer. In 48 of the 110 PWAS associations (44%), estimated gene damage is associated with reduced rather than elevated cancer risk, suggesting a protective effect. Together with standard GWAS, we implicated 145 unique genomic loci with cancer risk. While most of these genomic regions are supported by external evidence, our results also highlight many novel loci. Based on the capacity of PWAS to detect non-additive genetic effects, we found that 46% of the PWAS-significant cancer regions exhibited exclusive recessive inheritance. These results highlight the importance of recessive genetic effects, without relying on familial studies. Finally, we show that many of the detected genes exert substantial cancer risk in the studied cohort determined by a quantitative functional description, suggesting their relevance for diagnosis and genetic consulting.

scholarly journals Heterogeneous Network Edge Prediction: A Data Integration Approach to Prioritize Disease-Associated Genes

2014 ◽  
Author(s):  
Daniel S Himmelstein ◽  
Sergio E Baranzini
Keyword(s):  
Data Integration ◽  
Protein Interactions ◽  
Heterogeneous Network ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Protein Coding ◽  
Multiple Node ◽  
Pathogenic Variants ◽  
Disease Associated Genes

The first decade of Genome Wide Association Studies (GWAS) has uncovered a wealth of disease-associated variants. Two important derivations will be the translation of this information into a multiscale understanding of pathogenic variants, and leveraging existing data to increase the power of existing and future studies through prioritization. We explore edge prediction on heterogeneous networks—graphs with multiple node and edge types—for accomplishing both tasks. First we constructed a network with 18 node types—genes, diseases, tissues, pathophysiologies, and 14 MSigDB (molecular signatures database)collections—and 19 edge types from high-throughput publicly-available resources. From this network composed of 40,343 nodes and 1,608,168 edges, we extracted features that describe the topology between specific genes and diseases. Next, we trained a model from GWAS associations and predicted the probability of association between each protein-coding gene and each of 29 well-studied complex diseases. The model, which achieved 132-fold enrichment in precision at 10% recall, outperformed any individual domain, highlighting the benefit of integrative approaches. We identified pleiotropy, transcriptional signatures of perturbations, pathways, and protein interactions as fundamental mechanisms explaining pathogenesis. Our method successfully predicted the results (with AUROC = 0.79) from a withheld multiple sclerosis (MS) GWAS despite starting with only 13 previously associated genes. Finally, we combined our network predictions with statistical evidence of association to propose four novel MS genes, three of which (JAK2, REL, RUNX3) validated on the masked GWAS. Furthermore, our predictions provide biological support highlighting REL as the causal gene within its gene-rich locus. Users can browse all predictions online (http://het.io). Heterogeneous network edge prediction effectively prioritized genetic associations and provides a powerful new approach for data integration across multiple domains.

Abstract 49: Adipose-Specific Knockout of Trib1 Reduces Plasma Lipids and Diet-Induced Insulin Resistance, and Increases Circulating Adiponectin

2017 ◽  
Vol 37 (suppl_1) ◽  
Author(s):  
Mikhaila A Smith ◽  
Jian Cui ◽  
Sumeet A Kheterpal ◽  
Daniel J Rader ◽  
Robert C Bauer
Keyword(s):  
Body Mass ◽  
Plasma Lipids ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Tissue Mass ◽  
Fed State ◽  
Plasma Adiponectin ◽  
Metabolic Role

Tribbles-1 (TRIB1) was recently identified through genome-wide association studies as a novel mediator of plasma lipids and coronary artery disease in humans. While subsequent in vivo mouse work confirmed a role for hepatic TRIB1 in these associations, little is known about metabolic roles for extra-hepatic Trib1. Interestingly, SNPs near the TRIB1 gene are significantly associated with circulating adiponectin levels in humans, suggesting a metabolic role for adipose TRIB1 . To further investigate this, we generated adipose-specific Trib1 KO mice (Trib1_ASKO) by crossing Trib1 cKO mice to transgenic Adiponectin-Cre mice. Chow-fed Trib1_ASKO mice exhibited no differences in adipose tissue mass and overall body mass as compared to control littermates (N=8/group). However, Trib1_ASKO mice had reduced total (-16.9%, p <0.01), HDL (-16.7%, p <0.01), and non-HDL cholesterol (-17.3%, p =0.068), as well as plasma triglycerides (-28.6%, p <0.001) as compared to WT mice. Trib1_ASKO mice also had increased plasma adiponectin levels, a finding more pronounced in female mice (+33.3%, p <0.001) than in males (+16.4%, p =0.072). Despite this increase, transcript levels of adipoQ were moderately decreased in Trib1_ASKO mice, suggesting a post-transcriptional mode of regulation. Transcript and protein levels of C/EBPα, the best described target of Trib1 and a key regulator of adipogenesis, remained unchanged. To further investigate the metabolic consequences of adipose-specific KO of Trib1 , WT and Trib1_ASKO mice were fed high-fat diet (HFD, 45% kCal fat) for 12 weeks to induce obesity. HFD-fed Trib1_ASKO mice had reduced fasting plasma glucose (-22.3%, p <0.05), insulin (-38.2%, p <0.05), and glucose tolerance (-19.8% AUC, p <0.05) compared to control mice. Body mass and fat mass of HFD-fed Trib1_ASKO mice remained unchanged from WT, and the reductions in plasma lipids and increase in plasma adiponectin persisted in the HFD-fed state. In summary, we present here the first in vivo validation of the human genetic association between TRIB1 and plasma adiponectin, and provide evidence suggesting that adipose TRIB1 contributes to the genetic associations observed in humans between TRIB1 and multiple metabolic parameters.

Timing of pubertal development and midlife blood pressure in men and women: A Mendelian randomization study

2021 ◽  
Author(s):  
Io Ieong Chan ◽  
Man Ki Kwok ◽  
C Mary Schooling
Keyword(s):  
Blood Pressure ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Pubertal Development ◽  
Sensitivity Analyses ◽  
Age At Menarche ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Pubertal Maturation ◽  
Pubertal Growth

Abstract Introduction Observational studies suggest earlier puberty is associated with higher adulthood blood pressure (BP), but these findings have not been replicated using Mendelian randomization (MR). We examined this question sex-specifically using larger genome-wide association studies (GWAS) with more extensive measures of pubertal timing. Methods We obtained genetic instruments proxying pubertal maturation (age at menarche (AAM) or voice breaking (AVB)) from the largest published GWAS. We applied them to summary sex-specific genetic associations with systolic and diastolic BP z-scores, and self-reported hypertension in women (n=194174) and men (n=167020) from the UK Biobank, using inverse-variance weighting meta-analysis. We conducted sensitivity analyses using other MR methods, including multivariable MR adjusted for childhood obesity proxied by body mass index (BMI). We used late pubertal growth as a validation outcome. Results AAM (beta per one-year later = -0.030 [95% confidence interval (CI) -0.055, -0.005] and AVB (beta -0.058 [95% CI -0.100, -0.015]) were inversely associated with systolic BP independent of childhood BMI, as were diastolic BP (-0.035 [95% CI -0.060, -0.009] for AAM and -0.046 [95% CI -0.089, -0.004] for AVB) and self-reported hypertension (odds ratios 0.89 [95% CI 0.84, 0.95] for AAM and 0.87 [95% CI 0.79, 0.96] for AVB). AAM and AVB were positively associated with late pubertal growth, as expected. The results were robust to sensitivity analysis using other MR methods. Conclusion Timing of pubertal maturation was associated with adulthood BP independent of childhood BMI, highlighting the role of pubertal maturation timing in midlife BP.

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