Single-cell genomics improves the discovery of risk variants and genes of atrial fibrillation DOI Creative Commons

Alan Selewa,

Kaixuan Luo, Michael Wasney

et al.

Nature Communications, Journal Year: 2023, Volume and Issue: 14(1)

Published: Aug. 17, 2023

Genome-wide association studies (GWAS) have linked hundreds of loci to cardiac diseases. However, in most the causal variants and their target genes remain unknown. We developed a combined experimental analytical approach that integrates single cell epigenomics with GWAS prioritize risk genes. profiled accessible chromatin cells obtained from human hearts leveraged data study genetics Atrial Fibrillation (AF), common arrhythmia. Enrichment analysis AF using cell-type-resolved open regions (OCRs) implicated cardiomyocytes as main mediator risk. then performed statistical fine-mapping, leveraging information OCRs, identified putative 122 AF-associated loci. Taking advantage fine-mapping results, our novel procedure for gene discovery prioritized 46 high-confidence genes, highlighting transcription factors signal transduction pathways important heart development. In summary, provides comprehensive map general framework integrate single-cell genomics genetic complex traits.

Language: Английский

Fine-mapping across diverse ancestries drives the discovery of putative causal variants underlying human complex traits and diseases DOI Creative Commons
Kai Yuan, Ryan J. Longchamps, Antonio F. Pardiñas

et al.

medRxiv (Cold Spring Harbor Laboratory), Journal Year: 2023, Volume and Issue: unknown

Published: Jan. 9, 2023

Abstract Genome-wide association studies (GWAS) of human complex traits or diseases often implicate genetic loci that span hundreds thousands variants, many which have similar statistical significance. While fine-mapping in individuals European ancestries has made important discoveries, cross-population the potential to improve power and resolution by capitalizing on genomic diversity across ancestries. Here we present SuSiEx, an accurate computationally efficient method for fine-mapping, builds single-population framework, Sum Single Effects (SuSiE). SuSiEx integrates data from arbitrary number ancestries, explicitly models population-specific allele frequencies LD patterns, accounts multiple causal variants a region, can be applied GWAS summary statistics. We comprehensively evaluated using simulations, range quantitative measured both UK Biobank Taiwan Biobank, schizophrenia East Asian In all evaluations, fine-mapped more signals, produced smaller credible sets higher posterior inclusion probability (PIP) putative captured variants.

Language: Английский

Citations

24
Cross-ancestry genome-wide association meta-analyses of hippocampal and subfield volumes DOI
Nana Liu, Long Jiang Zhang, Tian Tian

et al.

Nature Genetics, Journal Year: 2023, Volume and Issue: 55(7), P. 1126 - 1137

Published: June 19, 2023

Language: Английский

Citations

24
Polygenic prediction across populations is influenced by ancestry, genetic architecture, and methodology DOI Creative Commons
Ying Wang, Masahiro Kanai,

Taotao Tan

et al.

Cell Genomics, Journal Year: 2023, Volume and Issue: 3(10), P. 100408 - 100408

Published: Sept. 15, 2023

Polygenic risk scores (PRSs) developed from multi-ancestry genome-wide association studies (GWASs), PRSmulti, hold promise for improving PRS accuracy and generalizability across populations. To establish best practices leveraging the increasing diversity of genomic studies, we investigated how various factors affect performance PRSmulti compared with PRSs constructed single-ancestry GWASs (PRSsingle). Through extensive simulations empirical analyses, showed that overall outperformed PRSsingle in understudied populations, except when population represented a small proportion GWAS. Furthermore, integrating based on local ancestry-informed large-scale, European-based improved predictive African especially less polygenic traits large-effect ancestry-enriched variants. Our work highlights importance diversifying to achieve equitable ancestral populations provides guidance developing multiple studies.

Language: Английский

Citations

24
A genome-wide association analysis reveals new pathogenic pathways in gout* DOI
Tanya J. Major, Riku Takei, Hirotaka Matsuo

et al.

Nature Genetics, Journal Year: 2024, Volume and Issue: 56(11), P. 2392 - 2406

Published: Oct. 15, 2024

Language: Английский

Citations

12
Functional dissection of complex and molecular trait variants at single nucleotide resolution DOI Creative Commons
Layla Siraj, Rodrigo Castro,

Hannah B. Dewey

et al.

bioRxiv (Cold Spring Harbor Laboratory), Journal Year: 2024, Volume and Issue: unknown

Published: May 6, 2024

Identifying the causal variants and mechanisms that drive complex traits diseases remains a core problem in human genetics. The majority of these have individually weak effects lie non-coding gene-regulatory elements where we lack complete understanding how single nucleotide alterations modulate transcriptional processes to affect phenotypes. To address this, measured activity 221,412 trait-associated had been statistically fine-mapped using Massively Parallel Reporter Assay (MPRA) 5 diverse cell-types. We show MPRA is able discriminate between likely controls, identifying 12,025 regulatory with high precision. Although largely agree orthogonal measures function, only 69% can plausibly be explained by disruption known transcription factor (TF) binding motif. dissect 136 saturation mutagenesis assign impacted TFs for 91% without clear canonical mechanism. Finally, provide evidence epistasis prevalent close proximity identify multiple functional on same haplotype at small, but important, subset loci. Overall, our study provides systematic characterization common underlying molecular traits, enabling new insights into grammar disease risk.

Language: Английский

Citations

11
Using omics data and genome editing methods to decipher GWAS loci associated with coronary artery disease DOI Creative Commons

Arnaud Chignon,

Guillaume Lettre

Atherosclerosis, Journal Year: 2025, Volume and Issue: 401, P. 118621 - 118621

Published: Feb. 1, 2025

Coronary artery disease (CAD) is due to atherosclerosis, a pathophysiological process that involves several cell-types and results in the accumulation of lipid-rich plaque disrupt normal blood flow through coronary arteries heart. Genome-wide association studies have identified 1000s genetic variants robustly associated with CAD or its traditional risk factors (e.g. pressure, lipids, type 2 diabetes, smoking). However, gaining biological insights from these discoveries remain challenging because linkage disequilibrium difficulty interpret functions non-coding regulatory elements human genome. In this review, we present different statistical methods Mendelian randomization) molecular datasets expression protein quantitative trait loci) helped connect CAD-associated genes, pathways, tissues. We emphasize various strategies make predictions, which need be validated orthologous systems. discuss specific examples where integration omics data GWAS has prioritized causal genes. Finally, review how targeted genome-wide genome editing experiments using CRISPR/Cas9 toolbox been used characterize new genes cells. Researchers now bioinformatic methods, datasets, experimental tools dissect comprehensively loci contribute humans.

Language: Английский

Citations

1
A large-scale genome-wide association study on female genital tract polyps highlights role of DNA repair, cell proliferation, and cell growth DOI
Amruta D. S. Pathare, Jelisaveta Džigurski, Natàlia Pujol‐Gualdo

et al.

Human Reproduction, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 5, 2025

Abstract STUDY QUESTION Can a large-scale genome-wide association study (GWAS) meta-analysis identify genomic risk loci and likely involved genes for female genital tract (FGT) polyps, provide insights into the biological mechanism underlying their development, inform of potential overlap with other traits, including endometrial cancer? SUMMARY ANSWER GWAS FGT polyps highlights potentially shared mechanisms between polyp development cancerous processes. WHAT IS KNOWN ALREADY Small-scale candidate gene studies have focused on processes such as oestrogen stimulation inflammation to clarify biology behind polyps. However, exact is still elusive. At same time, approach, which has become gold standard in complex disease genetics, never been used uncover genetics DESIGN, SIZE, DURATION We performed total 36 984 women (International Classification Diseases (ICD-10) diagnosis code N84) 420 993 controls (without N84 code) European ancestry from FinnGen (11 092 cases 94 394 controls), Estonian Biobank (EstBB, 14 008 112 799 Pan-UKBB 884 213 800 controls). PARTICIPANTS/MATERIALS, SETTING, METHODS functional annotation signals were genetic prioritize associated loci. To explore associations we look-up variants across multiple traits health conditions, correlation analysis, phenome-wide (PheWAS) ICD-10 codes. MAIN RESULTS AND THE ROLE OF CHANCE Our revealed 16 significant (P < 5 × 10−8) Based exonic signals, prioritized EEFSEC, ODF3, PRIM1, PLCE1, LRRC34/MYNN, EXO1, CHEK2 are DNA repair, cell proliferation, growth. Several identified previously linked cancer and/or uterine fibroids, highlighting tissue overgrowth Genetic analysis positive body mass index reproductive that can be classified symptoms or factors (EPs), whereas negative was observed both menopause (genetic estimate (rg) = −0.29, SE 0.08, P 8.8×10−4) sex hormone-binding globulin (SHBG) (rg −0.22, 0.04, 2.4×10−8). On phenotypic level, strongest endometriosis, excessive, frequent, irregular menstruation. LARGE SCALE DATA The complete summary statistics will made available after publication through Catalog (https://www.ebi.ac.uk/gwas/). LIMITATIONS, REASONS FOR CAUTION In this study, broadly did not differentiate subtypes. Considering prevalence subtypes, assumed most included had EPs. Further research expression profile could complement substantiate importance variants. WIDER IMPLICATIONS FINDINGS findings significantly enhance our understanding involved, paving way future follow-up, turn improve diagnosis, assessment, targeted treatment options, since surgery only line diagnosed FUNDING/COMPETING INTEREST(S) This funded by Union Regional Development Fund Project No. 2014-2020.4.01.15-0012 GENTRANSMED. Computations High-Performance Computing Center University Tartu. also supported Research Council (grant no. PRG1076 MOBJD1056) Horizon 2020 innovation grant (ERIN, EU952516). All authors declared no conflict interest.

Language: Английский

Citations

1
Secure and federated genome-wide association studies for biobank-scale datasets DOI Creative Commons
Hyunghoon Cho, David Froelicher, Jeffrey Chen

et al.

Nature Genetics, Journal Year: 2025, Volume and Issue: unknown

Published: Feb. 24, 2025

Sharing data across institutions for genome-wide association studies (GWAS) would enhance the discovery of genetic variation linked to health and disease1,2. However, existing data-sharing regulations limit scope such collaborations3. Although cryptographic tools secure computation promise enable collaborative analysis with formal privacy guarantees, approaches either are computationally impractical or do not implement current state-of-the-art methods4–6. We introduce federated (SF-GWAS), a combination frameworks distributed algorithms that empowers efficient accurate GWAS on private held by multiple entities while ensuring confidentiality. SF-GWAS supports widely used pipelines based principal-component linear mixed models. demonstrate accuracy practical runtimes five datasets, including UK Biobank cohort 410,000 individuals, showcasing an order-of-magnitude improvement in runtime compared previous methods. Our work enables genomic at unprecedented scale. is workflow secure, studies, implementing accurate, privacy-preserving analysis, linear/logistic regression model methods biobank-scale multisite analyses.

Language: Английский

Citations

1
Extremely sparse models of linkage disequilibrium in ancestrally diverse association studies DOI
Pouria Salehi Nowbandegani, Anthony Wilder Wohns,

Jenna L. Ballard

et al.

Nature Genetics, Journal Year: 2023, Volume and Issue: 55(9), P. 1494 - 1502

Published: Aug. 28, 2023

Language: Английский

Citations

21
Improving fine-mapping by modeling infinitesimal effects DOI
Ran Cui, Roy Elzur, Masahiro Kanai

et al.

Nature Genetics, Journal Year: 2023, Volume and Issue: 56(1), P. 162 - 169

Published: Nov. 30, 2023

Language: Английский

Citations

20