A functional genomics pipeline identifies pleiotropy and cross-tissue effects within obesity-associated GWAS loci

AbstractGenome-wide association studies (GWAS) have identified many disease-associated variants, yet mechanisms underlying these associations remain unclear. To understand obesity-associated variants, we generate gene regulatory annotations in adipocytes and hypothalamic neurons across cellular differentiation stages. We then test variants in 97 obesity-associated loci using a massively parallel reporter assay and identify putatively causal variants that display cell type specific or cross-tissue enhancer-modulating properties. Integrating these variants with gene regulatory information suggests genes that underlie obesity GWAS associations. We also investigate a complex genomic interval on 16p11.2 where two independent loci exhibit megabase-range, cross-locus chromatin interactions. We demonstrate that variants within these two loci regulate a shared gene set. Together, our data support a model where GWAS loci contain variants that alter enhancer activity across tissues, potentially with temporally restricted effects, to impact the expression of multiple genes. This complex model has broad implications for ongoing efforts to understand GWAS.

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Editing GWAS: experimental approaches to dissect and exploit disease-associated genetic variation

Genome Medicine ◽

10.1186/s13073-021-00857-3 ◽

2021 ◽

Vol 13 (1) ◽

Author(s):

Shuquan Rao ◽

Yao Yao ◽

Daniel E. Bauer

Keyword(s):

Genome Editing ◽

Genetic Variants ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Functional Studies ◽

Functional Genetics ◽

Genome Wide ◽

Causal Variants ◽

Experimental Approaches

AbstractGenome-wide association studies (GWAS) have uncovered thousands of genetic variants that influence risk for human diseases and traits. Yet understanding the mechanisms by which these genetic variants, mainly noncoding, have an impact on associated diseases and traits remains a significant hurdle. In this review, we discuss emerging experimental approaches that are being applied for functional studies of causal variants and translational advances from GWAS findings to disease prevention and treatment. We highlight the use of genome editing technologies in GWAS functional studies to modify genomic sequences, with proof-of-principle examples. We discuss the challenges in interrogating causal variants, points for consideration in experimental design and interpretation of GWAS locus mechanisms, and the potential for novel therapeutic opportunities. With the accumulation of knowledge of functional genetics, therapeutic genome editing based on GWAS discoveries will become increasingly feasible.

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CAUSALdb: a database for disease/trait causal variants identified using summary statistics of genome-wide association studies

Nucleic Acids Research ◽

10.1093/nar/gkz1026 ◽

2019 ◽

Cited By ~ 2

Author(s):

Jianhua Wang ◽

Dandan Huang ◽

Yao Zhou ◽

Hongcheng Yao ◽

Huanhuan Liu ◽

...

Keyword(s):

Fine Mapping ◽

Genetic Variants ◽

Association Studies ◽

Complex Trait ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Genome Wide ◽

Credible Sets ◽

Causal Variants

Abstract Genome-wide association studies (GWASs) have revolutionized the field of complex trait genetics over the past decade, yet for most of the significant genotype-phenotype associations the true causal variants remain unknown. Identifying and interpreting how causal genetic variants confer disease susceptibility is still a big challenge. Herein we introduce a new database, CAUSALdb, to integrate the most comprehensive GWAS summary statistics to date and identify credible sets of potential causal variants using uniformly processed fine-mapping. The database has six major features: it (i) curates 3052 high-quality, fine-mappable GWAS summary statistics across five human super-populations and 2629 unique traits; (ii) estimates causal probabilities of all genetic variants in GWAS significant loci using three state-of-the-art fine-mapping tools; (iii) maps the reported traits to a powerful ontology MeSH, making it simple for users to browse studies on the trait tree; (iv) incorporates highly interactive Manhattan and LocusZoom-like plots to allow visualization of credible sets in a single web page more efficiently; (v) enables online comparison of causal relations on variant-, gene- and trait-levels among studies with different sample sizes or populations and (vi) offers comprehensive variant annotations by integrating massive base-wise and allele-specific functional annotations. CAUSALdb is freely available at http://mulinlab.org/causaldb.

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Abstract MP208: A Shared Fog2 / Tbx5-dependent Gene Regulatory Network Identified By Transcription Factor-dependent Non-coding RNA Profiling Modulates Cardiac Rhythm

Circulation Research ◽

10.1161/res.129.suppl_1.mp208 ◽

2021 ◽

Vol 129 (Suppl_1) ◽

Author(s):

Linsin A Smith ◽

Carlos Perez-Cervantes ◽

Michael Broman ◽

Rangarajan Nadadur ◽

Jeff Steimle ◽

...

Keyword(s):

Gene Regulatory Network ◽

Regulatory Network ◽

Cardiac Rhythm ◽

Association Studies ◽

Genome Wide Association ◽

Calcium Handling ◽

Genome Wide Association Studies ◽

Genome Wide ◽

Gene Regulatory ◽

Atrial Rhythm

Atrial fibrillation (AF) is the most common cardiac arrhythmia, affecting over 33 million individuals throughout the world. AF is highly heritable and recent genome-wide association studies (GWAS) have cumulatively identified over 100 loci associated with AF risk. Genome-wide association studies (GWAS) often identify transcription factor (TF) loci in association with complex human diseases, implying that a significant transcriptional component underlies human disease risk and etiology. The transcription factors ZFPM2 (FOG2), GATA4, and TBX5 have all been implicated in human AF risk by genetic studies. We hypothesized that FOG2, GATA4, and TBX5 functionally interact to regulate a gene regulatory network essential for atrial rhythm control. We generated a novel mouse model of spontaneous AF based on FOG2 overexpression. FOG2 ChIP-seq identified FOG2 genomic localization at loci co-occupied by GATA4, a known FOG2 binding partner. However, we found that FOG2 OE caused gene expression alterations that correlated more highly with TBX5-dependent rather than GATA4-dependent gene expression, including a module of calcium handling genes required for atrial rhythm homeostasis. We applied TF-dependent non-coding transcriptional profiling to examine the FOG2 dependent atrial GRN, which identified 805 candidate regulatory regions with accessible chromatin and FOG2 dependent ncRNAs. TBX5 removal and FOG2 OE caused highly correlated dysregulation of ncRNA expression at open chromatin regions genome-wide, suggesting a functional interaction between TBX5 and FOG2. Furthermore, FOG2 OE only affected enhancer activity by altered ncRNA abundance at locations of TBX5 co-binding. The shared TBX5/FOG2 genomic interaction predicted a potential genetic interaction, and we found that cardiac rhythm abnormalities caused by Tbx5 haploinsufficiency were rescued by Fog2 haploinsufficiency. Taken together, TF-dependent ncRNA-profiling revealed an interconnected cardiac rhythm gene regulatory network (GRN) between FOG2, TBX5 and GATA4. These data nominate a specific model in which FOG2 is recruited by GATA4 to modulate a co-bound TBX5-dependent atrial gene regulatory network for calcium handling and atrial rhythm homeostasis.

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Partitioning heritability by functional category using GWAS summary statistics

10.1101/014241 ◽

2015 ◽

Cited By ~ 9

Author(s):

Hilary Kiyo Finucane ◽

Brendan Bulik-Sullivan ◽

Alexander Gusev ◽

Gosia Trynka ◽

Yakir Reshef ◽

...

Keyword(s):

Association Studies ◽

Smoking Behavior ◽

Complex Diseases ◽

New Method ◽

Age At Menarche ◽

Genome Wide Association Studies ◽

Summary Statistics ◽

Cell Type ◽

Genome Wide ◽

Cell Type Specific

Recent work has demonstrated that some functional categories of the genome contribute disproportionately to the heritability of complex diseases. Here, we analyze a broad set of functional elements, including cell-type-specific elements, to estimate their polygenic contributions to heritability in genome-wide association studies (GWAS) of 17 complex diseases and traits spanning a total of 1.3 million phenotype measurements. To enable this analysis, we introduce a new method for partitioning heritability from GWAS summary statistics while controlling for linked markers. This new method is computationally tractable at very large sample sizes, and leverages genome-wide information. Our results include a large enrichment of heritability in conserved regions across many traits; a very large immunological disease-specific enrichment of heritability in FANTOM5 enhancers; and many cell-type-specific enrichments including significant enrichment of central nervous system cell types in body mass index, age at menarche, educational attainment, and smoking behavior. These results demonstrate that GWAS can aid in understanding the biological basis of disease and provide direction for functional follow-up.

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Identification of Novel Genome-Wide Associations for Oral Inflammatory Traits

10.21203/rs.3.rs-104530/v1 ◽

2020 ◽

Author(s):

Yanjiao Jin ◽

Jie Yang ◽

Shuyue Zhang ◽

Jin Li ◽

Songlin Wang

Keyword(s):

Candidate Genes ◽

Immune Regulation ◽

Functional Annotation ◽

Inflammatory Diseases ◽

Association Studies ◽

Genome Wide Association ◽

Genome Wide Association Studies ◽

Protein Protein Interaction ◽

Genome Wide ◽

Causal Variants

Abstract Background: Oral diseases impact the majority of the world’s population. The following traits are common in oral inflammatory diseases: mouth ulcers, painful gums, bleeding gums, loose teeth, and toothache. Despite the prevalence of genome-wide association studies, the associations between these traits and common genomic variants, and whether pleiotropic loci are shared by some of these traits remain poorly understood. Methods: In this work, we conducted multi-trait joint analyses based on the summary statistics of genome-wide association studies of these five oral inflammatory traits from the UK Biobank, each of which is comprised of over 10,000 cases and over 300,000 controls. We estimated the genetic correlations between the five traits. We conducted fine-mapping and functional annotation based on multi-omics data to better understand the biological functions of the potential causal variants at each locus. To identify the pathways in which the candidate genes were mainly involved, we applied gene-set enrichment analysis, and further performed protein-protein interaction (PPI) analyses.Results: We identified 39 association signals that surpassed genome-wide significance, including three that were shared between two or more oral inflammatory traits, consistent with a strong correlation. Among these genome-wide significant loci, two were novel for both painful gums and toothache. We performed fine-mapping and identified causal variants at each novel locus. Further functional annotation based on multi-omics data suggested IL10 and IL12A/TRIM59 as potential candidate genes at the novel pleiotropic loci, respectively. Subsequent analyses of pathway enrichment and protein-protein interaction networks suggested the involvement of candidate genes at genome-wide significant loci in immune regulation.Conclusions: Our results highlighted the importance of immune regulation in the pathogenesis of oral inflammatory diseases. Some common immune-related pleiotropic loci or genetic variants are shared by multiple oral inflammatory traits. These findings will be beneficial for risk prediction, prevention, and therapy of oral inflammatory diseases.

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Genetic overlap between idiopathic pulmonary fibrosis and COVID−19

10.1101/2021.12.08.21267459 ◽

2021 ◽

Author(s):

Richard J Allen ◽

Beatriz Guillen-Guio ◽

Emma Croot ◽

Luke M Kraven ◽

Samuel Moss ◽

...

Keyword(s):

Idiopathic Pulmonary Fibrosis ◽

Pulmonary Fibrosis ◽

Association Studies ◽

Genome Wide Association Studies ◽

Biological Processes ◽

Genetic Loci ◽

Genome Wide ◽

Genetic Overlap ◽

Causal Variants ◽

Shared Genetic

AbstractGenome-wide association studies (GWAS) of coronavirus disease 2019 (COVID-19) and idiopathic pulmonary fibrosis (IPF) have identified genetic loci associated with both traits, suggesting possible shared biological mechanisms. Using updated GWAS of COVID-19 and IPF, we evaluated the genetic overlap between these two diseases and identified four genetic loci (including one novel) with likely shared causal variants between severe COVID-19 and IPF. Although there was a positive genetic correlation between COVID-19 and IPF, two of these four shared genetic loci had an opposite direction of effect. IPF-associated genetic variants related to telomere dysfunction and spindle assembly showed no association with COVID-19 phenotypes. Together, these results suggest there are both shared and distinct biological processes driving IPF and severe COVID-19 phenotypes.

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Genomic characterization of the adolescent idiopathic scoliosis associated transcriptome and regulome

10.1101/2020.03.02.973735 ◽

2020 ◽

Author(s):

Nadja Makki ◽

Jingjing Zhao ◽

Zhaoyang Liu ◽

Walter L. Eckalbar ◽

Aki Ushiki ◽

...

Keyword(s):

Adolescent Idiopathic Scoliosis ◽

Connective Tissue ◽

Idiopathic Scoliosis ◽

Association Studies ◽

Regulatory Elements ◽

Intervertebral Discs ◽

Genome Wide Association Studies ◽

Specific Expression ◽

Enhancer Activity ◽

Genome Wide

AbstractAdolescent idiopathic scoliosis (AIS), a sideways curvature of the spine, is the most common pediatric musculoskeletal disorder, affecting ∼3% of the population worldwide. However, its genetic bases and tissues of origin remain largely unknown. Several genome-wide association studies (GWAS) have implicated nucleotide variants in noncoding sequences that control genes with important roles in cartilage, muscle, bone, connective tissue and intervertebral discs (IVDs) as drivers of AIS susceptibility. Here, we set out to define the expression of AIS-associated genes and active regulatory elements by performing RNA-seq and ChIP-seq against H3K27ac in these tissues in mouse and human. Our study highlights genetic pathways involving AIS-associated loci that regulate chondrogenesis, IVD development and connective tissue maintenance and homeostasis. In addition, we identify thousands of putative AIS-associated regulatory elements which may orchestrate tissue-specific expression in musculoskeletal tissues of the spine. Quantification of enhancer activity of several candidate regulatory elements from our study identifies three functional enhancers carrying AIS-associated GWAS SNPs at the ADGRG6 and BNC2 loci. Our findings provide a novel genome-wide catalog of AIS-relevant genes and regulatory elements and aid in the identification of novel targets for AIS causality and treatment.

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Abstract 18374: Targeted Sequencing and Massively Parallel Reporter Assay Identify the Functional Variation Underlying the 4q25 Locus for Atrial Fibrillation

Circulation ◽

10.1161/circ.132.suppl_3.18374 ◽

2015 ◽

Vol 132 (suppl_3) ◽

Author(s):

Nathan R Tucker ◽

Jiangchuan Ye ◽

Honghuang Lin ◽

Michael A McLellan ◽

Emelia J Benjamin ◽

...

Keyword(s):

Atrial Fibrillation ◽

Association Studies ◽

Targeted Sequencing ◽

Massively Parallel ◽

Genome Wide Association Studies ◽

Sequencing Analysis ◽

Reporter Assay ◽

Enhancer Activity ◽

Functional Variants ◽

Massively Parallel Reporter Assay

Introduction: Genome-wide association studies have identified 14 independent loci for atrial fibrillation (AF). The 4q25 locus upstream of the left-right asymmetry gene PITX2 is, by far, the strongest association signal for AF. However, as with most GWAS loci, the functional variants are noncoding, presumed to be regulatory, and remain unknown. We therefore sought to rapidly identify the functional variants at an AF locus by combining high throughput sequencing and massively parallel reporter assays. Methods and Results: We sequenced a ~750kb region encompassing the PITX2 locus in 462 individuals with early-onset AF from the MGH AF Study and 464 referents from the Framingham Heart Study. The SNP most significantly associated with AF in our sequenced sample was rs2129983, which is 140kb from PITX2 (OR=2.43, P =8.9X10 -16 ). rs2129983 is approximately 1.7kb from the most significantly associated SNP in a prior AF GWAS, rs6817105 (r 2 =0.52). From the targeted sequencing analysis, we identified 262 SNVs with a MAF >0.5% within a genomic region bounded by SNPs with an r2 greater than 0.4 with the top variant. To identify functional variants, we then utilized a massively parallel reporter assay (MPRA) in order to measure enhancer activity at each SNP across the entire AF locus. In both HL-1 and C2C12 myoblasts, MPRA identified many distinct SNP regions with differential enhancer activity. Using AF-association status as a standard, we were able to identify a series of variants that have both differential activity in either cell line tested and also a high level of association (rs17042076, rs4469143). Mechanistically, these functional SNPs are predicted to alter transcription factor binding. Conclusions: We have comprehensively identified the AF-associated variation at 4q25 and determined which of these variants are functional through differential enhancer activity. Here, in addition to identifying the causative variation for AF at 4q25, we provide a generalizable pathway for translating this work to other loci, a method that could expedite the identification of causative genetic variants at other disease loci.

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Identification of ST3AGL4, MFHAS1, CSNK2A2 and CD226 as loci associated with systemic lupus erythematosus (SLE) and evaluation of SLE genetics in drug repositioning

Annals of the Rheumatic Diseases ◽

10.1136/annrheumdis-2018-213093 ◽

2018 ◽

Vol 77 (7) ◽

pp. 1078-1084 ◽

Cited By ~ 10

Author(s):

Yong-Fei Wang ◽

Yan Zhang ◽

Zhengwei Zhu ◽

Ting-You Wang ◽

David L Morris ◽

...

Keyword(s):

Systemic Lupus Erythematosus ◽

Fine Mapping ◽

Lupus Erythematosus ◽

Drug Repositioning ◽

Association Studies ◽

Genome Wide Association Studies ◽

Systemic Lupus ◽

Genome Wide ◽

Causal Variants

ObjectivesSystemic lupus erythematosus (SLE) is a prototype autoimmune disease with a strong genetic component in its pathogenesis. Through genome-wide association studies (GWAS), we recently identified 10 novel loci associated with SLE and uncovered a number of suggestive loci requiring further validation. This study aimed to validate those loci in independent cohorts and evaluate the role of SLE genetics in drug repositioning.MethodsWe conducted GWAS and replication studies involving 12 280 SLE cases and 18 828 controls, and performed fine-mapping analyses to identify likely causal variants within the newly identified loci. We further scanned drug target databases to evaluate the role of SLE genetics in drug repositioning.ResultsWe identified three novel loci that surpassed genome-wide significance, including ST3AGL4 (rs13238909, pmeta=4.40E-08), MFHAS1 (rs2428, pmeta=1.17E-08) and CSNK2A2 (rs2731783, pmeta=1.08E-09). We also confirmed the association of CD226 locus with SLE (rs763361, pmeta=2.45E-08). Fine-mapping and functional analyses indicated that the putative causal variants in CSNK2A2 locus reside in an enhancer and are associated with expression of CSNK2A2 in B-lymphocytes, suggesting a potential mechanism of association. In addition, we demonstrated that SLE risk genes were more likely to be interacting proteins with targets of approved SLE drugs (OR=2.41, p=1.50E-03) which supports the role of genetic studies to repurpose drugs approved for other diseases for the treatment of SLE.ConclusionThis study identified three novel loci associated with SLE and demonstrated the role of SLE GWAS findings in drug repositioning.

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Phenotype-specific differences in polygenicity and effect size distribution across functional annotation categories revealed by AI-MiXeR

Bioinformatics ◽

10.1093/bioinformatics/btaa568 ◽

2020 ◽

Vol 36 (18) ◽

pp. 4749-4756 ◽

Cited By ~ 2

Author(s):

Alexey A Shadrin ◽

Oleksandr Frei ◽

Olav B Smeland ◽

Francesco Bettella ◽

Kevin S O'Connell ◽

...

Keyword(s):

Functional Annotation ◽

Association Studies ◽

Effect Sizes ◽

Supplementary Information ◽

Genome Wide Association Studies ◽

Protein Coding ◽

Genome Wide ◽

Whole Exome ◽

Causal Variants ◽

Complex Human Traits

Abstract Motivation Determining the relative contributions of functional genetic categories is fundamental to understanding the genetic etiology of complex human traits and diseases. Here, we present Annotation Informed-MiXeR, a likelihood-based method for estimating the number of variants influencing a phenotype and their effect sizes across different functional annotation categories of the genome using summary statistics from genome-wide association studies. Results Extensive simulations demonstrate that the model is valid for a broad range of genetic architectures. The model suggests that complex human phenotypes substantially differ in the number of causal variants, their localization in the genome and their effect sizes. Specifically, the exons of protein-coding genes harbor more than 90% of variants influencing type 2 diabetes and inflammatory bowel disease, making them good candidates for whole-exome studies. In contrast, <10% of the causal variants for schizophrenia, bipolar disorder and attention-deficit/hyperactivity disorder are located in protein-coding exons, indicating a more substantial role of regulatory mechanisms in the pathogenesis of these disorders. Availability and implementation The software is available at: https://github.com/precimed/mixer. Supplementary information Supplementary data are available at Bioinformatics online.

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