Genetics of systemic sclerosis

2020 ◽  
Vol 5 (3) ◽  
pp. 192-201 ◽  
Author(s):  
Yuki Ishikawa ◽  
Chikashi Terao
Keyword(s):  
Systemic Sclerosis ◽  
Disease Risk ◽  
Association Studies ◽  
Human Leukocyte ◽  
Premature Death ◽  
Microvascular Dysfunction ◽  
Candidate Gene Approach ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genetic Components

Systemic sclerosis is an autoimmune disease characterized by generalized fibrosis in connective tissues and internal organs as consequences of microvascular dysfunction and immune dysfunctions, which leads to premature death in affected individuals. The etiology of systemic sclerosis is complex and poorly understood, but as with most autoimmune diseases, it is widely accepted that both environmental and genetic factors contribute to disease risk. During the last decade, the number of genetic markers convincingly associated with systemic sclerosis has exponentially increased. In this article, we briefly mention the genetic components of systemic sclerosis. Then, we review the classical and novel genetic associations with systemic sclerosis, analyzing the firmest and replicated signals within non–human leukocyte antigen genes, identified by both candidate gene approach and genome-wide association studies. We also provide an insight into the future perspectives that will shed more light into the complex genetic background of the disease. Despite the remarkable advance of systemic sclerosis genetics during the last decade, the use of the new genetic technologies such as next-generation sequencing, as well as the deep phenotyping of the study cohorts, to fully characterize the genetic component of this disease is imperative to identify causal variants, which leads to more targeted and effective treatment of systemic sclerosis.

scholarly journals Challenges and progress in interpretation of non-coding genetic variants associated with human disease

2017 ◽  
Vol 242 (13) ◽  
pp. 1325-1334 ◽  
Author(s):  
Yizhou Zhu ◽  
Cagdas Tazearslan ◽  
Yousin Suh
Keyword(s):  
Molecular Mechanisms ◽  
Target Genes ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Functional Interpretation ◽  
Genome Wide ◽  
Coding Variants

Genome-wide association studies have shown that the far majority of disease-associated variants reside in the non-coding regions of the genome, suggesting that gene regulatory changes contribute to disease risk. To identify truly causal non-coding variants and their affected target genes remains challenging but is a critical step to translate the genetic associations to molecular mechanisms and ultimately clinical applications. Here we review genomic/epigenomic resources and in silico tools that can be used to identify causal non-coding variants and experimental strategies to validate their functionalities. Impact statement Most signals from genome-wide association studies (GWASs) map to the non-coding genome, and functional interpretation of these associations remained challenging. We reviewed recent progress in methodologies of studying the non-coding genome and argued that no single approach allows one to effectively identify the causal regulatory variants from GWAS results. By illustrating the advantages and limitations of each method, our review potentially provided a guideline for taking a combinatorial approach to accurately predict, prioritize, and eventually experimentally validate the causal variants.

scholarly journals XWAS: a software toolset for genetic data analysis and association studies of the X chromosome

2014 ◽  
Author(s):  
Feng Gao ◽  
Diana Chang ◽  
Arjun Biddanda ◽  
Li Ma ◽  
Yingjie Guo ◽  
...  
Keyword(s):  
X Chromosome ◽  
Disease Risk ◽  
Association Studies ◽  
Statistical Tests ◽  
Standard Test ◽  
Sexually Dimorphic ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Tests Of Association ◽  
Artery Disease

XWAS is a new software suite for the analysis of the X chromosome in association studies and similar studies. The X chromosome plays an important role in human disease, especially those with sexually dimorphic characteristics. Special attention needs to be given to its analysis due to the unique inheritance pattern, which leads to analytical complications that have resulted in the majority of genome-wide association studies (GWAS) either not considering X or mishandling it with toolsets that had been designed for non-sex chromosomes. We hence developed XWAS to fill the need for tools that are specially designed for analysis of X. Following extensive, stringent, and X-specific quality control, XWAS offers an array of statistical tests of association, including: (1) the standard test between a SNP (single nucleotide polymorphism) and disease risk, including after first stratifying individuals by sex, (2) a test for a differential effect of a SNP on disease between males and females, (3) motivated by X-inactivation, a test for higher variance of a trait in heterozygous females as compared to homozygous females, and (4) for all tests, a version that allows for combining evidence from all SNPs across a gene. We applied the toolset analysis pipeline to 16 GWAS datasets of immune-related disorders and 7 risk factors of coronary artery disease, and discovered several new X-linked genetic associations. XWAS will provide the tools and incentive for others to incorporate the X chromosome into GWAS, hence enabling discoveries of novel loci implicated in many diseases and in their sexual dimorphism.

scholarly journals A global atlas of genetic associations of 220 deep phenotypes

2020 ◽  
Author(s):  
Saori Sakaue ◽  
Masahiro Kanai ◽  
Yosuke Tanigawa ◽  
Juha Karjalainen ◽  
Mitja Kurki ◽  
...  
Keyword(s):  
Association Studies ◽  
East Asian ◽  
Allergic Diseases ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Endemic Diseases ◽  
Genetic Components ◽  
Mhc Locus ◽  
The Uk ◽  
Meta Analyses

AbstractThe current genome-wide association studies (GWASs) do not yet capture sufficient diversity in terms of populations and scope of phenotypes. To address an essential need to expand an atlas of genetic associations in non-European populations, we conducted 220 deep-phenotype GWASs (disease endpoints, biomarkers, and medication usage) in BioBank Japan (n = 179,000), by incorporating past medical history and text-mining results of electronic medical records. Meta-analyses with the harmonized phenotypes in the UK Biobank and FinnGen (ntotal = 628,000) identified over 4,000 novel loci, which substantially deepened the resolution of the genomic map of human traits, benefited from East Asian endemic diseases and East Asian specific variants. This atlas elucidated the globally shared landscape of pleiotropy as represented by the MHC locus, where we conducted fine-mapping by HLA imputation. Finally, to intensify the value of deep-phenotype GWASs, we performed statistical decomposition of matrices of phenome-wide summary statistics, and identified the latent genetic components, which pinpointed the responsible variants and shared biological mechanisms underlying current disease classifications across populations. The decomposed components enabled genetically informed subtyping of similar diseases (e.g., allergic diseases). Our study suggests a potential avenue for hypothesis-free re-investigation of human disease classifications through genetics.

Genetic Risk and the Development of Autoimmune Liver Disease

2015 ◽  
Vol 33 (Suppl. 2) ◽  
pp. 13-24 ◽  
Author(s):  
Tom H. Karlsen ◽  
Brian K. Chung
Keyword(s):  
Genetic Risk ◽  
Liver Diseases ◽  
Disease Risk ◽  
Association Studies ◽  
Strong Association ◽  
Human Leukocyte ◽  
Biliary Cirrhosis ◽  
Genome Wide Association Studies ◽  
Autoimmune Liver Diseases ◽  
Study Designs

Primary biliary cirrhosis (PBC), primary sclerosing cholangitis (PSC) and autoimmune hepatitis (AIH) have collectively been recognized as autoimmune liver diseases. They have all been subjected to genome-wide association studies (GWAS) and several dozens susceptibility loci have been determined. The predominant feature of the genetic findings is that of a strong association with the human leukocyte antigen (HLA) and numerous weak associations scattered throughout the remainder of the genome. The non-HLA associations show some degree of overlap, not only between PBC, PSC and AIH, but also with other autoimmune and immune-mediated diseases. Mathematical modelling shows that the main fraction of autoimmune disease risk (including that of autoimmune liver diseases) is not explained by GWAS, proposing a major role of environmental factors. The HLA associations and autoantibodies observed in these conditions may hold clues as to the nature of such factors, which are exceedingly difficult to map by means of epidemiological study designs. The present review article explores the potential relationship between genetic risk as determined by GWAS and environmental risk in autoimmune liver diseases, and proposes a model for relevant thinking on the susceptibility genes in PBC, PSC and AIH.

scholarly journals Sex differences in the genetic predictors of Alzheimer’s pathology

Brain ◽  
2019 ◽  
Vol 142 (9) ◽  
pp. 2581-2589 ◽  
Author(s):  
Logan Dumitrescu ◽  
Lisa L Barnes ◽  
Madhav Thambisetty ◽  
Gary Beecham ◽  
Brian Kunkle ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Sex Differences ◽  
Disease Risk ◽  
Association Studies ◽  
Age At Onset ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Data Repositories ◽  
Genome Wide

Abstract Autopsy measures of Alzheimer’s disease neuropathology have been leveraged as endophenotypes in previous genome-wide association studies (GWAS). However, despite evidence of sex differences in Alzheimer’s disease risk, sex-stratified models have not been incorporated into previous GWAS analyses. We looked for sex-specific genetic associations with Alzheimer’s disease endophenotypes from six brain bank data repositories. The pooled dataset included 2701 males and 3275 females, the majority of whom were diagnosed with Alzheimer’s disease at autopsy (70%). Sex-stratified GWAS were performed within each dataset and then meta-analysed. Loci that reached genome-wide significance (P < 5 × 10−8) in stratified models were further assessed for sex interactions. Additional analyses were performed in independent datasets leveraging cognitive, neuroimaging and CSF endophenotypes, along with age-at-onset data. Outside of the APOE region, one locus on chromosome 7 (rs34331204) showed a sex-specific association with neurofibrillary tangles among males (P = 2.5 × 10−8) but not females (P = 0.85, sex-interaction P = 2.9 × 10−4). In follow-up analyses, rs34331204 was also associated with hippocampal volume, executive function, and age-at-onset only among males. These results implicate a novel locus that confers male-specific protection from tau pathology and highlight the value of assessing genetic associations in a sex-specific manner.

scholarly journals Loss-of-function of MFGE8 and protection against coronary atherosclerosis

2021 ◽  
Author(s):  
Sanni E Ruotsalainen ◽  
Ida Surakka ◽  
Nina Mars ◽  
Juha Karjalainen ◽  
Mitja Kurki ◽  
...  
Keyword(s):  
Cardiovascular Diseases ◽  
Coronary Atherosclerosis ◽  
Association Studies ◽  
Meta Analysis ◽  
Significant Risk ◽  
Premature Death ◽  
Population History ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Loss Of Function

Cardiovascular diseases are the leading cause of premature death and disability worldwide, with both genetic and environmental determinants. While genome-wide association studies have identified multiple genetic loci associated with cardiovascular diseases, exact genes driving these associations remain mostly uncovered. Due to Finland's population history, many deleterious and high-impact variants are enriched in the Finnish population giving a possibility to find genetic associations for protein-truncating variants that likely tie the association to a gene and that would not be detected elsewhere. In FinnGen, a large Finnish biobank study, we identified an inframe insertion rs534125149 in MFGE8 to have protective effect against coronary atherosclerosis (OR = 0.75, p = 2.63E-16) and related endpoints. This variant is highly enriched in Finland (70-fold compared to Non-Finnish Europeans) with allele frequency of 3% in Finland. The protective association was replicated in meta-analysis of biobanks of Japan and Estonian (OR = 0.75, p = 5.41E-7). Additionally, we identified a splice acceptor variant rs201988637 in MFGE8, independent of the rs534125149 and similarly protective in relation to coronary atherosclerosis (OR = 0.72, p = 7.94E-06) and related endpoints, with no significant risk-increasing associations. The protein-truncating variant was also associated with lower pulse pressure, pointing towards a function of MFGE8 in arterial stiffness and aging also in humans in addition to previous evidence in mice. In conclusion, our results show that inhibiting the production of lactadherin could lower the risk for coronary heart disease substantially.

scholarly journals Alzheimer's disease variant portal (ADVP): a catalog of genetic findings for Alzheimer's disease

2020 ◽  
Author(s):  
Pavel P Kuksa ◽  
Chia-Lun Lui ◽  
Wei Fu ◽  
Liming Qu ◽  
Yi Zhao ◽  
...  
Keyword(s):  
Alzheimer’S Disease ◽  
Alzheimer's Disease ◽  
Functional Genomics ◽  
Genetic Variants ◽  
Disease Risk ◽  
Association Studies ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genome Wide ◽  
Disease Variant

Background: Alzheimer's disease (AD) genetic findings span progressively larger genome-wide association studies (GWASs) for various outcomes and populations. These genetic findings are obtained from a single GWAS, joint- or meta- analyses of multiple GWAS datasets. However, no single resource provides harmonized and searchable information on all AD genetic associations obtained from these analyses, nor linking the identified genetic variants and reported genes with other supporting functional genomic evidence. Methods: We created the Alzheimer's Disease Variant Portal (ADVP), which provides unified access to a uniquely extensive collection of high-quality GWAS association results for AD. Records in ADVP are curated from the genome-wide significant and suggestive loci reported in AD genetics literature. ADVP contains curated results from all AD GWAS publications by Alzheimer's Disease Genetics Consortium (ADGC) since 2009 and AD GWAS publications identified from other public catalogs (GWAS catalog). Genetic association information was systematically extracted from these publications, harmonized, and organized into three types of tables. These tables included structured publication, variant, and association categories to ensure consistent representation of all AD genetic findings. All extracted AD genetic associations were further annotated and integrated with NIAGADS Genomics DB in order to provide extensive biological and functional genomics annotations. Results: Currently, ADVP contains 6,990 AD-association records curated from >200 AD GWAS publications corresponding to >900 unique genomic loci and >1,800 unique genetic variants. The ADVP collection contains genetic findings from >80 cohorts and across various populations, including Caucasians, Hispanics, African-Americans, and Asians. Of all the association records, 46% are disease-risk, 13% are related to expression quantitative trait analyses, and 27% are related to AD endophenotypes and neuropathology. ADVP web interface allows accessing AD association records by individual variants, genes, publications, genomic regions of interest, and genome-wide interactive variant views. ADVP is integrated with the NIAGADS Alzheimer's Genomics Database. Researchers can explore additional biological annotations at the genetic variant or gene level and view cross-reference functional genomics evidence provided by other public resources. Conclusions: ADVP is the largest, most up-to-date, and comprehensive literature-derived collection of AD genetic associations. All records have been systematically curated, harmonized, and comprehensively annotated. ADVP is freely accessible at https://advp.niagads.org/.

scholarly journals Association of genetic variants with prostate cancer in Africa: a concise review

2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Emmanuel Acheampong ◽  
Evans Asamoah Adu ◽  
Christian Obirikorang ◽  
George Amoah ◽  
Osei Owusu Afriyie ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Genetic Variants ◽  
Association Studies ◽  
African Ancestry ◽  
Candidate Gene Approach ◽  
Main Body ◽  
Genome Wide Association Studies ◽  
Genetic Associations ◽  
Genetic Studies ◽  
Genome Wide

Abstract Background Prostate cancer (PCa) has one of the highest heritability of all major cancers, where the genetic contribution has been documented, and knowledge about the molecular genetics of the disease is increasing. However, the extent and aspects to which genetic variants explain PCa heritability in Africa are limited. Main body In this review, we summarize studies that highlight how identified genetic variants explain differences in PCa incidence and presentation across ethnic groups. We also present the knowledge gaps in PCa genetics in Africa and why Africa represents an untapped potential ground for genetic studies on PCa. A significant number of genome-wide association studies, linkage, and fine-mapping analyses have been conducted globally, and that explains 30–33% of PCa heritability. The African ancestry has a significant mention in PCa incidence and presentation. To date, the candidate gene approach has replicated 23 polymorphisms including dinucleotide and trinucleotide repeats in 16 genes. CYP17-rs743572, CYP3A4-rs2740574, CYP3A5-rs776746, CYP3A43-rs501275, and haplotype blocks, containing these variants, are significantly associated with PCa among some population groups but not others. With the few existing studies, the extent of genetic diversity in Africa suggests that genetic associations of PCa to African ancestry go beyond nucleotide sequence polymorphisms, to a level of environmental adaptation, which may interpret genetic risk profiles. Also, the shreds of evidence suggest that evolutionary history contributes to the high rates of PCa relative to African ancestry, and genetic associations do not always replicate across populations. Conclusion The genetic architecture of PCa in Africa provides important contributions to the global understanding of PCa specifically the African-ancestry hypothesis. There is a need for more prostate cancer consortiums to justify the heritable certainties of PCa among Africans, and emphasis should be placed on the genetic epidemiological model of PCa in Africa.

scholarly journals MR-Base: a platform for systematic causal inference across the phenome using billions of genetic associations

2016 ◽  
Author(s):  
Gibran Hemani ◽  
Jie Zheng ◽  
Kaitlin H Wade ◽  
Charles Laurin ◽  
Benjamin Elsworth ◽  
...  
Keyword(s):  
Complex Traits ◽  
Disease Risk ◽  
Drug Repositioning ◽  
Association Studies ◽  
Sensitivity Analyses ◽  
Lipid Lowering ◽  
Genome Wide Association Studies ◽  
Causal Relationships ◽  
Genetic Associations ◽  
The Impact

AbstractPublished genetic associations can be used to infer causal relationships between phenotypes, bypassing the need for individual-level genotype or phenotype data. We have curated complete summary data from 1094 genome-wide association studies (GWAS) on diseases and other complex traits into a centralised database, and developed an analytical platform that uses these data to perform Mendelian randomization (MR) tests and sensitivity analyses (MR-Base, http://www.mrbase.org). Combined with curated data of published GWAS hits for phenomic measures, the MR-Base platform enables millions of potential causal relationships to be evaluated. We use the platform to predict the impact of lipid lowering on human health. While our analysis provides evidence that reducing LDL-cholesterol, lipoprotein(a) or triglyceride levels reduce coronary disease risk, it also suggests causal effects on a number of other non-vascular outcomes, indicating potential for adverse-effects or drug repositioning of lipid-lowering therapies.

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.

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