scholarly journals Implicating candidate genes at GWAS signals by leveraging topologically associating domains

2016 ◽  
Author(s):  
Gregory P. Way ◽  
Daniel W. Youngstrom ◽  
Kurt D. Hankenson ◽  
Casey S. Greene ◽  
Struan F. A. Grant
Keyword(s):  
Candidate Genes ◽  
Complex Disease ◽  
System Development ◽  
Association Studies ◽  
Three Dimensional ◽  
Computational Method ◽  
Causal Mechanism ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Topologically Associating Domains

AbstractGenome wide association studies (GWAS) have contributed significantly to the understanding of complex disease genetics. However, GWAS only report associated signals and do not necessarily identify culprit genes. As most signals occur in non-coding regions of the genome, it is often challenging to assign genomic variants to the underlying causal mechanism(s). Topologically associating domains (TADs) are primarily cell-type independent genomic regions that define interactome boundaries and can aid in the designation of limits within which an association most likely impacts gene function. We describe and validate a computational method that uses the genic content of TADs to discover candidate genes. Our method, called “TAD_Pathways,” performs a Gene Ontology (GO) analysis over genes that reside within TAD boundaries corresponding to GWAS signals for a given trait or disease. We applied our pipeline to the GWAS catalog entries associated with bone mineral density (BMD), identifying ‘Skeletal System Development’ (Benjamini-Hochberg adjusted p=1.02x10−5) as the top ranked pathway. In many cases, our method implicated a gene other than the nearest gene. Our molecular experiments describe a novel example: ACP2, implicated at the canonical ‘ARHGAP1’ locus. We found ACP2 to be an important regulator of osteoblast metabolism, whereas ARHGAP1 was not supported. Our results via the example of BMD demonstrate how basic principles of three-dimensional genome organization can define biologically informed association windows.

scholarly journals Twelve years of GWAS discoveries for osteoporosis and related traits: advances, challenges and applications

Bone Research ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Xiaowei Zhu ◽  
Weiyang Bai ◽  
Houfeng Zheng
Keyword(s):  
Drug Targets ◽  
Complex Disease ◽  
Association Studies ◽  
Osteoporotic Fractures ◽  
Disease Prediction ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Small Effect Size ◽  
Endocrine Status ◽  
Meta Analyses

AbstractOsteoporosis is a common skeletal disease, affecting ~200 million people around the world. As a complex disease, osteoporosis is influenced by many factors, including diet (e.g. calcium and protein intake), physical activity, endocrine status, coexisting diseases and genetic factors. In this review, we first summarize the discovery from genome-wide association studies (GWASs) in the bone field in the last 12 years. To date, GWASs and meta-analyses have discovered hundreds of loci that are associated with bone mineral density (BMD), osteoporosis, and osteoporotic fractures. However, the GWAS approach has sometimes been criticized because of the small effect size of the discovered variants and the mystery of missing heritability, these two questions could be partially explained by the newly raised conceptual models, such as omnigenic model and natural selection. Finally, we introduce the clinical use of GWAS findings in the bone field, such as the identification of causal clinical risk factors, the development of drug targets and disease prediction. Despite the fruitful GWAS discoveries in the bone field, most of these GWAS participants were of European descent, and more genetic studies should be carried out in other ethnic populations to benefit disease prediction in the corresponding population.

scholarly journals Identification of known and novel long non-coding RNAs potentially responsible for the effects of BMD GWAS loci

2021 ◽  
Author(s):  
Abdullah Abood ◽  
Larry Mesner ◽  
Will Rosenow ◽  
Basel M Al-Barghouthi ◽  
Nina Horwitz ◽  
...  
Keyword(s):  
Complex Disease ◽  
Bone Cells ◽  
Association Studies ◽  
Genetic Regulation ◽  
Tissue Expression ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Common Complex Disease ◽  
Genetics Of Osteoporosis ◽  
Non Coding Rnas

Osteoporosis, characterized by low bone mineral density (BMD), is the most common complex disease affecting bone and constitutes a major societal health problem. Genome-wide association studies (GWASs) have identified over 1100 associations influencing BMD. It has been shown that perturbations to long non-coding RNAs (lncRNAs) influence BMD and the activities of bone cells; however, the extent to which lncRNAs are involved in the genetic regulation of BMD is unknown. Here, we combined the analysis of allelic imbalance (AI) in human acetabular bone fragments with a transcriptome-wide association study (TWAS) and expression quantitative trait loci (eQTL) colocalization analysis using data from the Genotype-Tissue Expression (GTEx) project to identify lncRNAs potentially responsible for GWAS associations. We identified 27 lncRNAs in bone that are located in proximity to a BMD GWAS association and harbor SNPs demonstrating AI. Using GTEx data we identified an additional 31 lncRNAs whose expression was associated (FDR correction<0.05) with BMD through TWAS and had a colocalizing eQTL (regional colocalization probability (RCP)>0.1). The 58 lncRNAs are located in 43 BMD associations. To further support a causal role for the identified lncRNAs, we show that 23 of the 58 lncRNAs are differentially expressed as a function of osteoblast differentiation. Our approach identifies lncRNAs that are potentially responsible for BMD GWAS associations and suggest that lncRNAs play a role in the genetics of osteoporosis.

scholarly journals Polymorphisms Associated With Low Bone Mass and High Risk of Atraumatic Fracture

2015 ◽  
pp. 621-631 ◽  
Author(s):  
I. ZOFKOVA ◽  
P. NEMCIKOVA ◽  
M. KUKLIK
Keyword(s):  
Candidate Genes ◽  
Bone Quality ◽  
Association Studies ◽  
High Morbidity ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Practical Utilization ◽  
New Genes ◽  
Serious Disease ◽  
Canonical Wnt

Osteoporosis is a serious disease characterized by high morbidity and mortality due to atraumatic fractures. In the pathogenesis of osteoporosis, except environment and internal factors, such as hormonal imbalance and genetic background, are also in play. In this study candidate genes for osteoporosis were classified according to metabolic or hormonal pathways, which regulate bone mineral density and bone quality (estrogen, RANKL/RANK/OPG axis, mevalonate, the canonical circuit and genes regulating the vitamin D system). COL1A1 and/or COL1A2 genes, which encode formation of the procollagen 1 molecule, were also studied. Mutations in these genes are well-known causes of the inborn disease ‘osteogenesis imperfecta’. In addition to this, polymorphisms in COL1A1 and/or COL1A2 have been found to be associated with parameters of bone quality in adult subjects. The authors discuss the perspectives for the practical utilization of pharmacogenetics (identification of single candidate genes using PCR) and pharmacogenomics (using genome wide association studies (GWAS) to choose optimal treatment for osteoporosis). Potential predictors of antiresorptive therapy efficacy include the following well established genes: ER, FDPS, Cyp19A1, VDR, Col1A1, and Col1A2, as well as the gene for the canonical (Wnt) pathway. Unfortunately, the positive outcomes seen in most association studies have not been confirmed by other researchers. The controversial results could be explained by the use of different methodological approaches in individual studies (different sample size, homogeneity of investigated groups, ethnic differences, or linkage disequilibrium between genes). The key pitfall of association studies is the low variability (7-10 %) of bone phenotypes associated with the investigated genes. Nevertheless, the identification of new genes and the verification of their association with bone density and/or quality (using both PCR and GWAS), remain a great challenge in the optimal prevention and treatment of osteoporosis.

scholarly journals Gene Expression and RNA Splicing Imputation Identifies Novel Candidate Genes Associated with Osteoporosis

2020 ◽  
Vol 105 (12) ◽  
pp. e4742-e4757
Author(s):  
Yong Liu ◽  
Hui Shen ◽  
Jonathan Greenbaum ◽  
Anqi Liu ◽  
Kuan-Jui Su ◽  
...  
Keyword(s):  
Quantitative Trait Loci ◽  
Candidate Genes ◽  
Quantitative Trait ◽  
Mendelian Randomization ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Mendelian Randomization Analysis ◽  
Trait Loci ◽  
Randomization Analysis

Abstract Context Though genome-wide association studies (GWASs) have identified hundreds of genetic variants associated with osteoporosis related traits, such as bone mineral density (BMD) and fracture, it remains a challenge to interpret their biological functions and underlying biological mechanisms. Objective Integrate diverse expression quantitative trait loci and splicing quantitative trait loci data with several powerful GWAS datasets to identify novel candidate genes associated with osteoporosis. Design, Setting, and Participants Here, we conducted a transcriptome-wide association study (TWAS) for total body BMD (TB-BMD) (n = 66 628 for discovery and 7697 for validation) and fracture (53 184 fracture cases and 373 611 controls for discovery and 37 857 cases and 227 116 controls for validation), respectively. We also conducted multi-SNP-based summarized mendelian randomization analysis to further validate our findings. Results In total, we detected 88 genes significantly associated with TB-BMD or fracture through expression or ribonucleic acid splicing. Summarized mendelian randomization analysis revealed that 78 of the significant genes may have potential causal effects on TB-BMD or fracture in at least 1 specific tissue. Among them, 64 genes have been reported in previous GWASs or TWASs for osteoporosis, such as ING3, CPED1, and WNT16, as well as 14 novel genes, such as DBF4B, GRN, TMUB2, and UNC93B1. Conclusions Overall, our findings provide novel insights into the pathogenesis mechanisms of osteoporosis and highlight the power of a TWAS to identify and prioritize potential causal genes.

scholarly journals Genome-Wide Association Studies Based on Equine Joint Angle Measurements Reveal New QTL Affecting the Conformation of Horses

Genes ◽  
2019 ◽  
Vol 10 (5) ◽  
pp. 370 ◽  
Author(s):  
Annik Imogen Gmel ◽  
Thomas Druml ◽  
Rudolf von Niederhäusern ◽  
Tosso Leeb ◽  
Markus Neuditschko
Keyword(s):  
Joint Angle ◽  
Association Studies ◽  
Genome Wide Association ◽  
Cranial Morphology ◽  
Genome Wide Association Studies ◽  
Joint Angles ◽  
Mineral Density ◽  
Mixed Effect ◽  
Stifle Joint ◽  
Genome Wide

The evaluation of conformation traits is an important part of selection for breeding stallions and mares. Some of these judged conformation traits involve joint angles that are associated with performance, health, and longevity. To improve our understanding of the genetic background of joint angles in horses, we have objectively measured the angles of the poll, elbow, carpal, fetlock (front and hind), hip, stifle, and hock joints based on one photograph of each of the 300 Franches-Montagnes (FM) and 224 Lipizzan (LIP) horses. After quality control, genome-wide association studies (GWASs) for these traits were performed on 495 horses, using 374,070 genome-wide single nucleotide polymorphisms (SNPs) in a mixed-effect model. We identified two significant quantitative trait loci (QTL) for the poll angle on ECA28 (p = 1.36 × 10−7), 50 kb downstream of the ALX1 gene, involved in cranial morphology, and for the elbow joint on ECA29 (p = 1.69 × 10−7), 49 kb downstream of the RSU1 gene, and 75 kb upstream of the PTER gene. Both genes are associated with bone mineral density in humans. Furthermore, we identified other suggestive QTL associated with the stifle joint on ECA8 (p = 3.10 × 10−7); the poll on ECA1 (p = 6.83 × 10−7); the fetlock joint of the hind limb on ECA27 (p = 5.42 × 10−7); and the carpal joint angle on ECA3 (p = 6.24 × 10−7), ECA4 (p = 6.07 × 10−7), and ECA7 (p = 8.83 × 10−7). The application of angular measurements in genetic studies may increase our understanding of the underlying genetic effects of important traits in equine breeding.

scholarly journals A meta-analysis of genome-wide association studies for average daily gain and lean meat percentage in two Duroc pig populations

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shenping Zhou ◽  
Rongrong Ding ◽  
Fanming Meng ◽  
Xingwang Wang ◽  
Zhanwei Zhuang ◽  
...  
Keyword(s):  
Candidate Genes ◽  
Growth And Development ◽  
Genetic Architecture ◽  
Association Studies ◽  
Meta Analysis ◽  
Average Daily Gain ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Daily Gain

Abstract Background Average daily gain (ADG) and lean meat percentage (LMP) are the main production performance indicators of pigs. Nevertheless, the genetic architecture of ADG and LMP is still elusive. Here, we conducted genome-wide association studies (GWAS) and meta-analysis for ADG and LMP in 3770 American and 2090 Canadian Duroc pigs. Results In the American Duroc pigs, one novel pleiotropic quantitative trait locus (QTL) on Sus scrofa chromosome 1 (SSC1) was identified to be associated with ADG and LMP, which spans 2.53 Mb (from 159.66 to 162.19 Mb). In the Canadian Duroc pigs, two novel QTLs on SSC1 were detected for LMP, which were situated in 3.86 Mb (from 157.99 to 161.85 Mb) and 555 kb (from 37.63 to 38.19 Mb) regions. The meta-analysis identified ten and 20 additional SNPs for ADG and LMP, respectively. Finally, four genes (PHLPP1, STC1, DYRK1B, and PIK3C2A) were detected to be associated with ADG and/or LMP. Further bioinformatics analysis showed that the candidate genes for ADG are mainly involved in bone growth and development, whereas the candidate genes for LMP mainly participated in adipose tissue and muscle tissue growth and development. Conclusions We performed GWAS and meta-analysis for ADG and LMP based on a large sample size consisting of two Duroc pig populations. One pleiotropic QTL that shared a 2.19 Mb haplotype block from 159.66 to 161.85 Mb on SSC1 was found to affect ADG and LMP in the two Duroc pig populations. Furthermore, the combination of single-population and meta-analysis of GWAS improved the efficiency of detecting additional SNPs for the analyzed traits. Our results provide new insights into the genetic architecture of ADG and LMP traits in pigs. Moreover, some significant SNPs associated with ADG and/or LMP in this study may be useful for marker-assisted selection in pig breeding.

scholarly journals A gene co-association network regulating gut microbial communities in a Duroc pig population

Microbiome ◽  
2021 ◽  
Vol 9 (1) ◽  
Author(s):  
Antonio Reverter ◽  
Maria Ballester ◽  
Pamela A. Alexandre ◽  
Emilio Mármol-Sánchez ◽  
Antoni Dalmau ◽  
...  
Keyword(s):  
Microbial Communities ◽  
Candidate Genes ◽  
Relative Abundance ◽  
Association Studies ◽  
Single Gene ◽  
Host Genome ◽  
Genome Wide Association Studies ◽  
Vaccine Response ◽  
Microbiome Composition ◽  
Host Genetic

Abstract Background Analyses of gut microbiome composition in livestock species have shown its potential to contribute to the regulation of complex phenotypes. However, little is known about the host genetic control over the gut microbial communities. In pigs, previous studies are based on classical “single-gene-single-trait” approaches and have evaluated the role of host genome controlling gut prokaryote and eukaryote communities separately. Results In order to determine the ability of the host genome to control the diversity and composition of microbial communities in healthy pigs, we undertook genome-wide association studies (GWAS) for 39 microbial phenotypes that included 2 diversity indexes, and the relative abundance of 31 bacterial and six commensal protist genera in 390 pigs genotyped for 70 K SNPs. The GWAS results were processed through a 3-step analytical pipeline comprised of (1) association weight matrix; (2) regulatory impact factor; and (3) partial correlation and information theory. The inferred gene regulatory network comprised 3561 genes (within a 5 kb distance from a relevant SNP–P < 0.05) and 738,913 connections (SNP-to-SNP co-associations). Our findings highlight the complexity and polygenic nature of the pig gut microbial ecosystem. Prominent within the network were 5 regulators, PRDM15, STAT1, ssc-mir-371, SOX9 and RUNX2 which gathered 942, 607, 588, 284 and 273 connections, respectively. PRDM15 modulates the transcription of upstream regulators of WNT and MAPK-ERK signaling to safeguard naive pluripotency and regulates the production of Th1- and Th2-type immune response. The signal transducer STAT1 has long been associated with immune processes and was recently identified as a potential regulator of vaccine response to porcine reproductive and respiratory syndrome. The list of regulators was enriched for immune-related pathways, and the list of predicted targets includes candidate genes previously reported as associated with microbiota profile in pigs, mice and human, such as SLIT3, SLC39A8, NOS1, IL1R2, DAB1, TOX3, SPP1, THSD7B, ELF2, PIANP, A2ML1, and IFNAR1. Moreover, we show the existence of host-genetic variants jointly associated with the relative abundance of butyrate producer bacteria and host performance. Conclusions Taken together, our results identified regulators, candidate genes, and mechanisms linked with microbiome modulation by the host. They further highlight the value of the proposed analytical pipeline to exploit pleiotropy and the crosstalk between bacteria and protists as significant contributors to host-microbiome interactions and identify genetic markers and candidate genes that can be incorporated in breeding program to improve host-performance and microbial traits.

scholarly journals Systems genetics in diversity outbred mice inform BMD GWAS and identify determinants of bone strength

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Basel M. Al-Barghouthi ◽  
Larry D. Mesner ◽  
Gina M. Calabrese ◽  
Daniel Brooks ◽  
Steven M. Tommasini ◽  
...  
Keyword(s):  
Cortical Bone ◽  
Bone Strength ◽  
Human Genetics ◽  
Association Studies ◽  
Systems Genetics ◽  
Genome Wide Association Studies ◽  
Mineral Density ◽  
Diversity Outbred ◽  
Wide Range ◽  
Genetics Of Osteoporosis

AbstractGenome-wide association studies (GWASs) for osteoporotic traits have identified over 1000 associations; however, their impact has been limited by the difficulties of causal gene identification and a strict focus on bone mineral density (BMD). Here, we use Diversity Outbred (DO) mice to directly address these limitations by performing a systems genetics analysis of 55 complex skeletal phenotypes. We apply a network approach to cortical bone RNA-seq data to discover 66 genes likely to be causal for human BMD GWAS associations, including the genes SERTAD4 and GLT8D2. We also perform GWAS in the DO for a wide-range of bone traits and identify Qsox1 as a gene influencing cortical bone accrual and bone strength. In this work, we advance our understanding of the genetics of osteoporosis and highlight the ability of the mouse to inform human genetics.

scholarly journals Host Genetics and Gut Microbiome: Perspectives for Multiple Sclerosis

Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1181
Author(s):  
Alessandro Maglione ◽  
Miriam Zuccalà ◽  
Martina Tosi ◽  
Marinella Clerico ◽  
Simona Rolla
Keyword(s):  
Multiple Sclerosis ◽  
Environmental Factors ◽  
Lupus Erythematosus ◽  
Gut Microbiome ◽  
Complex Disease ◽  
Current Knowledge ◽  
Association Studies ◽  
Future Research ◽  
Genome Wide Association Studies ◽  
Host Genetics

As a complex disease, Multiple Sclerosis (MS)’s etiology is determined by both genetic and environmental factors. In the last decade, the gut microbiome has emerged as an important environmental factor, but its interaction with host genetics is still unknown. In this review, we focus on these dual aspects of MS pathogenesis: we describe the current knowledge on genetic factors related to MS, based on genome-wide association studies, and then illustrate the interactions between the immune system, gut microbiome and central nervous system in MS, summarizing the evidence available from Experimental Autoimmune Encephalomyelitis mouse models and studies in patients. Finally, as the understanding of influence of host genetics on the gut microbiome composition in MS is in its infancy, we explore this issue based on the evidence currently available from other autoimmune diseases that share with MS the interplay of genetic with environmental factors (Inflammatory Bowel Disease, Rheumatoid Arthritis and Systemic Lupus Erythematosus), and discuss avenues for future research.

scholarly journals Genetic and Epigenetic Modifiers of Alcoholic Liver Disease

2018 ◽  
Vol 19 (12) ◽  
pp. 3857 ◽  
Author(s):  
Marica Meroni ◽  
Miriam Longo ◽  
Raffaela Rametta ◽  
Paola Dongiovanni
Keyword(s):  
Liver Disease ◽  
Alcohol Consumption ◽  
Alcoholic Liver Disease ◽  
Complex Disease ◽  
Wide Spectrum ◽  
Association Studies ◽  
Phenotypic Variability ◽  
Genome Wide Association Studies ◽  
Epigenetic Factors ◽  
Excessive Alcohol Consumption

Alcoholic liver disease (ALD), a disorder caused by excessive alcohol consumption is a global health issue. More than two billion people consume alcohol in the world and about 75 million are classified as having alcohol disorders. ALD embraces a wide spectrum of hepatic lesions including steatosis, alcoholic steatohepatitis (ASH), fibrosis, cirrhosis, and hepatocellular carcinoma (HCC). ALD is a complex disease where environmental, genetic, and epigenetic factors contribute to its pathogenesis and progression. The severity of alcohol-induced liver disease depends on the amount, method of usage and duration of alcohol consumption as well as on age, gender, presence of obesity, and genetic susceptibility. Genome-wide association studies and candidate gene studies have identified genetic modifiers of ALD that can be exploited as non-invasive biomarkers, but which do not completely explain the phenotypic variability. Indeed, ALD development and progression is also modulated by epigenetic factors. The premise of this review is to discuss the role of genetic variants and epigenetic modifications, with particular attention being paid to microRNAs, as pathogenic markers, risk predictors, and therapeutic targets in ALD.

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