Malika Kumar Freund, Kathryn S

Slides:



Advertisements
Similar presentations
Functional Analysis of the Neurofibromatosis Type 2 Protein by Means of Disease- Causing Point Mutations Renee P. Stokowski, David R. Cox The American.
Advertisements

Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders  Ariel Feiglin, Bryce K. Allen,
Michael Dannemann, Janet Kelso  The American Journal of Human Genetics 
Comprehensively Evaluating cis-Regulatory Variation in the Human Prostate Transcriptome by Using Gene-Level Allele-Specific Expression  Nicholas B. Larson,
Colocalization of GWAS and eQTL Signals Detects Target Genes
Genetic-Variation-Driven Gene-Expression Changes Highlight Genes with Important Functions for Kidney Disease  Yi-An Ko, Huiguang Yi, Chengxiang Qiu, Shizheng.
Disentangling the Effects of Colocalizing Genomic Annotations to Functionally Prioritize Non-coding Variants within Complex-Trait Loci  Gosia Trynka,
Volume 18, Issue 9, Pages (February 2017)
Integrating Gene Expression with Summary Association Statistics to Identify Genes Associated with 30 Complex Traits  Nicholas Mancuso, Huwenbo Shi, Pagé.
High-Resolution Genetic Maps Identify Multiple Type 2 Diabetes Loci at Regulatory Hotspots in African Americans and Europeans  Winston Lau, Toby Andrew,
Huwenbo Shi, Nicholas Mancuso, Sarah Spendlove, Bogdan Pasaniuc 
Haplotype Estimation Using Sequencing Reads
Genome-wide Analysis of Body Proportion Classifies Height-Associated Variants by Mechanism of Action and Implicates Genes Important for Skeletal Development 
Genome-wide Transcriptome Profiling Reveals the Functional Impact of Rare De Novo and Recurrent CNVs in Autism Spectrum Disorders  Rui Luo, Stephan J.
Volume 26, Issue 22, Pages (November 2016)
The Post-GWAS Era: From Association to Function
Improved Heritability Estimation from Genome-wide SNPs
PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger  Anurag Verma,
Rounak Dey, Ellen M. Schmidt, Goncalo R. Abecasis, Seunggeun Lee 
Weight Loss after Gastric Bypass Is Associated with a Variant at 15q26
Parisa Shooshtari, Hailiang Huang, Chris Cotsapas 
Revisiting the Thrifty Gene Hypothesis via 65 Loci Associated with Susceptibility to Type 2 Diabetes  Qasim Ayub, Loukas Moutsianas, Yuan Chen, Kalliope.
Relationship between Deleterious Variation, Genomic Autozygosity, and Disease Risk: Insights from The 1000 Genomes Project  Trevor J. Pemberton, Zachary.
Volume 11, Issue 5, Pages (May 2015)
Long-Range Modulation of PAG1 Expression by 8q21 Allergy Risk Variants
Michael Dannemann, Janet Kelso  The American Journal of Human Genetics 
HYST: A Hybrid Set-Based Test for Genome-wide Association Studies, with Application to Protein-Protein Interaction-Based Association Analysis  Miao-Xin.
Gene Expression in Skin and Lymphoblastoid Cells: Refined Statistical Method Reveals Extensive Overlap in cis-eQTL Signals  Jun Ding, Johann E. Gudjonsson,
Genomic Signatures of Selective Pressures and Introgression from Archaic Hominins at Human Innate Immunity Genes  Matthieu Deschamps, Guillaume Laval,
A Flexible Bayesian Framework for Modeling Haplotype Association with Disease, Allowing for Dominance Effects of the Underlying Causative Variants  Andrew.
Kristina Allen-Brady, Peggy A. Norton, James M
Towfique Raj, Manik Kuchroo, Joseph M
Enhancer Connectome Nominates Target Genes of Inherited Risk Variants from Inflammatory Skin Disorders  Mark Y. Jeng, Maxwell R. Mumbach, Jeffrey M. Granja,
Genetic Regulatory Mechanisms of Smooth Muscle Cells Map to Coronary Artery Disease Risk Loci  Boxiang Liu, Milos Pjanic, Ting Wang, Trieu Nguyen, Michael.
One SNP at a Time: Moving beyond GWAS in Psoriasis
Genetic Investigations of Kidney Disease: Core Curriculum 2013
Xin Li, Alexis Battle, Konrad J. Karczewski, Zach Zappala, David A
Sherlock: Detecting Gene-Disease Associations by Matching Patterns of Expression QTL and GWAS  Xin He, Chris K. Fuller, Yi Song, Qingying Meng, Bin Zhang,
Structural Architecture of SNP Effects on Complex Traits
Mendelian Randomization Analysis Identifies CpG Sites as Putative Mediators for Genetic Influences on Cardiovascular Disease Risk  Tom G. Richardson,
Integrating Autoimmune Risk Loci with Gene-Expression Data Identifies Specific Pathogenic Immune Cell Subsets  Xinli Hu, Hyun Kim, Eli Stahl, Robert Plenge,
A systems view of genetics in chronic kidney disease
GeMes, Clusters of DNA Methylation under Genetic Control, Can Inform Genetic and Epigenetic Analysis of Disease  Yun Liu, Xin Li, Martin J. Aryee, Tomas J.
A Variant in LIN28B Is Associated with 2D:4D Finger-Length Ratio, a Putative Retrospective Biomarker of Prenatal Testosterone Exposure  Sarah E. Medland,
Five Years of GWAS Discovery
Diego Calderon, Anand Bhaskar, David A
Figure 2 Functionally significant genes
Comprehensive Analysis of Tissue-wide Gene Expression and Phenotype Data Reveals Tissues Affected in Rare Genetic Disorders  Ariel Feiglin, Bryce K. Allen,
Volume 4, Issue 3, Pages e3 (March 2017)
An Expanded View of Complex Traits: From Polygenic to Omnigenic
Varying Intolerance of Gene Pathways to Mutational Classes Explain Genetic Convergence across Neuropsychiatric Disorders  Shahar Shohat, Eyal Ben-David,
Volume 122, Issue 6, Pages (September 2005)
Huwenbo Shi, Gleb Kichaev, Bogdan Pasaniuc 
Chen Yao, Roby Joehanes, Andrew D
Gene Density, Transcription, and Insulators Contribute to the Partition of the Drosophila Genome into Physical Domains  Chunhui Hou, Li Li, Zhaohui S.
Wei Pan, Il-Youp Kwak, Peng Wei  The American Journal of Human Genetics 
Joseph K. Pickrell  The American Journal of Human Genetics 
Widespread Allelic Heterogeneity in Complex Traits
The American Journal of Human Genetics
Colocalization of GWAS and eQTL Signals Detects Target Genes
Genetic and Epigenetic Regulation of Human lincRNA Gene Expression
Genome-wide Characterization of Shared and Distinct Genetic Components that Influence Blood Lipid Levels in Ethnically Diverse Human Populations  Marc A.
Sarah E. Medland, Dale R. Nyholt, Jodie N. Painter, Brian P
IMPACT: Genomic Annotation of Cell-State-Specific Regulatory Elements Inferred from the Epigenome of Bound Transcription Factors  Tiffany Amariuta, Yang.
Functional Architectures of Local and Distal Regulation of Gene Expression in Multiple Human Tissues  Xuanyao Liu, Hilary K. Finucane, Alexander Gusev,
Harold A. Nieuwboer, René Pool, Conor V. Dolan, Dorret I
Leveraging Multi-ethnic Evidence for Mapping Complex Traits in Minority Populations: An Empirical Bayes Approach  Marc A. Coram, Sophie I. Candille, Qing.
Zuoheng Wang, Mary Sara McPeek  The American Journal of Human Genetics 
Adiposity-Dependent Regulatory Effects on Multi-tissue Transcriptomes
Beyond GWASs: Illuminating the Dark Road from Association to Function
Presentation transcript:

Phenotype-Specific Enrichment of Mendelian Disorder Genes near GWAS Regions across 62 Complex Traits  Malika Kumar Freund, Kathryn S. Burch, Huwenbo Shi, Nicholas Mancuso, Gleb Kichaev, Kristina M. Garske, David Z. Pan, Zong Miao, Karen L. Mohlke, Markku Laakso, Päivi Pajukanta, Bogdan Pasaniuc, Valerie A. Arboleda  The American Journal of Human Genetics  Volume 103, Issue 4, Pages 535-552 (October 2018) DOI: 10.1016/j.ajhg.2018.08.017 Copyright © 2018 American Society of Human Genetics Terms and Conditions

Figure 1 GWAS Gene Sets and Phenotype-Specific Mendelian Disorder Gene Sets For each complex trait (e.g., height), we first identified matched Mendelian phenotypes (e.g., undergrowth and short stature; Table S2). Using publicly available GWAS data, we defined the “GWAS genes” for a given complex trait to be the closest upstream and closest downstream protein-coding genes for every genome-wide-significant variant in the GWAS. We selected phenotype-matched Mendelian disorder genes by first identifying Mendelian disorders expressing any of the matched Mendelian phenotypes and then identifying all genes linked to any of those disorders. The American Journal of Human Genetics 2018 103, 535-552DOI: (10.1016/j.ajhg.2018.08.017) Copyright © 2018 American Society of Human Genetics Terms and Conditions

Figure 2 Overlap between GWAS Genes and Mendelian Disorder Genes Demonstrates Trait Specificity Significant overlaps from phenotypically matched pairs of complex traits and Mendelian disorders (blue) and pairs with unrelated phenotypes (gray) are shown. Phenotypically matched pairs are subdivided into pairs with perfectly matched phenotypes (light blue) and pairs with related phenotypes (dark blue). Complex traits and Mendelian disorders with no significant overlaps are excluded here; results from all traits are presented in Figure S2. We assessed significance by controlling for FDR < 5% at p < 0.00310. The American Journal of Human Genetics 2018 103, 535-552DOI: (10.1016/j.ajhg.2018.08.017) Copyright © 2018 American Society of Human Genetics Terms and Conditions

Figure 3 Effect Sizes for SNPs on Complex Traits from GWASs Are Higher for LoF-Intolerant Genes and for Phenotypically Relevant Mendelian Disorder Genes The increase in average SNP effect size per gene across gene categories, as compared with all protein-coding genes (dashed line), is shown. We averaged effect size (Z2) across all SNPs falling within 50 kb of a gene to obtain an average SNP effect size per gene and averaged across all genes in each category (all protein-coding genes, all Mendelian disorder genes, all LoF-intolerant genes, and all phenotypically relevant Mendelian disorder genes for each trait). We normalized these averages to the average SNP effect per gene for any protein-coding genes. The boxplots represent the distribution of increases in average effect size per gene across all traits, and notches designate the confidence intervals (CIs). From left to right, CIs read (0.07, 1.24), (1.47, 3.54), and (5.88, 12.19). The American Journal of Human Genetics 2018 103, 535-552DOI: (10.1016/j.ajhg.2018.08.017) Copyright © 2018 American Society of Human Genetics Terms and Conditions

Figure 4 Candidate Regulatory SNPs Fall at TSSs and Long-Range Promoters of Phenotypically Relevant Mendelian Disorder Genes (A and B) Shown here are two examples of putative causal SNPs localizing at a TSS of a phenotypically relevant Mendelian disorder gene. (A) Putative causal SNP rs1332327, associated with coronary artery disease (Z = 6.80), lies at the TSS of LIPA. (B) Putative causal SNP rs1010222, associated with red blood cell count (Z = −5.97), lies at the TSS of CALR. (C and D) Shown here are two representations of chromatin interactions in white adipose tissue. (C) A cluster of SNPs from the credible set of variants associated with BMI (Z score plotted in orange and blue) physically interacts with the promoter of a particular isoform of CYP19A1. (D) A single SNP (rs758747) from the credible set, associated with BMI (Z = 6.08), physically interacts with the promoter of a distant gene, CREBBP. The American Journal of Human Genetics 2018 103, 535-552DOI: (10.1016/j.ajhg.2018.08.017) Copyright © 2018 American Society of Human Genetics Terms and Conditions