Author
Qin Qin Huang
Other affiliations: University of Melbourne, Baker IDI Heart and Diabetes Institute
Bio: Qin Qin Huang is an academic researcher from Wellcome Trust Sanger Institute. The author has contributed to research in topics: Genome-wide association study & Population. The author has an hindex of 7, co-authored 16 publications receiving 278 citations. Previous affiliations of Qin Qin Huang include University of Melbourne & Baker IDI Heart and Diabetes Institute.
Papers
More filters
••
26 Aug 2021
TL;DR: This Primer provides an introduction to genome-wide association studies (GWAS), techniques for deriving functional inferences from the results and applications of GWAS in understanding disease risk and trait architecture, and discusses important ethical considerations when considering GWAS populations and data.
Abstract: Genome-wide association studies (GWAS) test hundreds of thousands of genetic variants across many genomes to find those statistically associated with a specific trait or disease. This methodology has generated a myriad of robust associations for a range of traits and diseases, and the number of associated variants is expected to grow steadily as GWAS sample sizes increase. GWAS results have a range of applications, such as gaining insight into a phenotype’s underlying biology, estimating its heritability, calculating genetic correlations, making clinical risk predictions, informing drug development programmes and inferring potential causal relationships between risk factors and health outcomes. In this Primer, we provide the reader with an introduction to GWAS, explaining their statistical basis and how they are conducted, describe state-of-the art approaches and discuss limitations and challenges, concluding with an overview of the current and future applications for GWAS results. Uffelmann et al. describe the key considerations and best practices for conducting genome-wide association studies (GWAS), techniques for deriving functional inferences from the results and applications of GWAS in understanding disease risk and trait architecture. The Primer also provides information on the best practices for data sharing and discusses important ethical considerations when considering GWAS populations and data.
299 citations
••
University of North Carolina at Chapel Hill1, Montreal Heart Institute2, Osaka University3, VA Boston Healthcare System4, Icahn School of Medicine at Mount Sinai5, Queen Mary University of London6, University of Cambridge7, National Institute for Health Research8, Wellcome Trust Sanger Institute9, Harvard University10, Vanderbilt University11, University of Wisconsin–Milwaukee12, Université de Montréal13, University of Southern California14, Kyushu University15, University of Washington16, University of Bristol17, University of Copenhagen18, Erasmus University Medical Center19, National Institutes of Health20, Brigham and Women's Hospital21, Kaiser Permanente22, University of Mississippi Medical Center23, International Agency for Research on Cancer24, Wake Forest University25, Imperial College London26, Broad Institute27, University of Pennsylvania28, Greifswald University Hospital29, Fred Hutchinson Cancer Research Center30, Chinese National Human Genome Center31, Technische Universität München32, University of Tampere33, University of Tokyo34, University of Ioannina35, University of Colorado Denver36, Duke University37, University of Virginia38, NHS Blood and Transplant39, University of Minnesota40, Turku University Hospital41, Los Angeles Biomedical Research Institute42, Stanford University43, King's College London44, Mashhad University of Medical Sciences45, Veterans Health Administration46
TL;DR: The clinical significance and predictive value of trans-ethnic variants in multiple populations are explored, genetic architecture and the effect of natural selection on these blood phenotypes between populations are compared and the value of a more global representation of populations in genetic studies is highlighted.
233 citations
••
TL;DR: A bootstrap method was developed (BootstrapQTL) that led to more accurate effect size estimation in eQTL study design and the performance of various analysis strategies, and provide a foundation for future eZTL studies, especially those with sampling constraints and subtly different conditions.
Abstract: Investigation of the genetic architecture of gene expression traits has aided interpretation of disease and trait-associated genetic variants; however, key aspects of expression quantitative trait loci (eQTL) study design and analysis remain understudied. We used extensive, empirically driven simulations to explore eQTL study design and the performance of various analysis strategies. Across multiple testing correction methods, false discoveries of genes with eQTLs (eGenes) were substantially inflated when false discovery rate (FDR) control was applied to all tests and only appropriately controlled using hierarchical procedures. All multiple testing correction procedures had low power and inflated FDR for eGenes whose causal SNPs had small allele frequencies using small sample sizes (e.g. frequency 25%). Overestimation of eQTL effect sizes, so-called 'Winner's Curse', was common in low and moderate power settings. To address this, we developed a bootstrap method (BootstrapQTL) that led to more accurate effect size estimation. These insights provide a foundation for future eQTL studies, especially those with sampling constraints and subtly different conditions.
84 citations
••
TL;DR: A genome-wide association study meta-analysis of up to 125,584 cases and over 2.5 million control individuals across 60 studies from 25 countries reveals compelling insights regarding disease susceptibility and severity.
50 citations
••
TL;DR: It is found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductiveSuccess is antagonistic, and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.
Abstract: Traditional genome-wide scans for positive selection have mainly uncovered selective sweeps associated with monogenic traits. While selection on quantitative traits is much more common, very few signals have been detected because of their polygenic nature. We searched for positive selection signals underlying coronary artery disease (CAD) in worldwide populations, using novel approaches to quantify relationships between polygenic selection signals and CAD genetic risk. We identified new candidate adaptive loci that appear to have been directly modified by disease pressures given their significant associations with CAD genetic risk. These candidates were all uniquely and consistently associated with many different male and female reproductive traits suggesting selection may have also targeted these because of their direct effects on fitness. We found that CAD loci are significantly enriched for lifetime reproductive success relative to the rest of the human genome, with evidence that the relationship between CAD and lifetime reproductive success is antagonistic. This supports the presence of antagonistic-pleiotropic tradeoffs on CAD loci and provides a novel explanation for the maintenance and high prevalence of CAD in modern humans. Lastly, we found that positive selection more often targeted CAD gene regulatory variants using HapMap3 lymphoblastoid cell lines, which further highlights the unique biological significance of candidate adaptive loci underlying CAD. Our study provides a novel approach for detecting selection on polygenic traits and evidence that modern human genomes have evolved in response to CAD-induced selection pressures and other early-life traits sharing pleiotropic links with CAD.
50 citations
Cited by
More filters
•
TL;DR: For the next few weeks the course is going to be exploring a field that’s actually older than classical population genetics, although the approach it’ll be taking to it involves the use of population genetic machinery.
Abstract: So far in this course we have dealt entirely with the evolution of characters that are controlled by simple Mendelian inheritance at a single locus. There are notes on the course website about gametic disequilibrium and how allele frequencies change at two loci simultaneously, but we didn’t discuss them. In every example we’ve considered we’ve imagined that we could understand something about evolution by examining the evolution of a single gene. That’s the domain of classical population genetics. For the next few weeks we’re going to be exploring a field that’s actually older than classical population genetics, although the approach we’ll be taking to it involves the use of population genetic machinery. If you know a little about the history of evolutionary biology, you may know that after the rediscovery of Mendel’s work in 1900 there was a heated debate between the “biometricians” (e.g., Galton and Pearson) and the “Mendelians” (e.g., de Vries, Correns, Bateson, and Morgan). Biometricians asserted that the really important variation in evolution didn’t follow Mendelian rules. Height, weight, skin color, and similar traits seemed to
9,847 citations
29 Jan 2015
TL;DR: The current state of the genetic dissection of complex traits is summarized in this paper, which describes the methods, limitations, and recent applications to biological problems, including linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses.
Abstract: Medical genetics was revolutionized during the 1980s by the application of genetic mapping to locate the genes responsible for simple Mendelian diseases. Most diseases and traits, however, do not follow simple inheritance patterns. Geneticists have thus begun taking up the even greater challenge of the genetic dissection of complex traits. Four major approaches have been developed: linkage analysis, allele-sharing methods, association studies, and polygenic analysis of experimental crosses. This article synthesizes the current state of the genetic dissection of complex traits—describing the methods, limitations, and recent applications to biological problems.
1,805 citations
01 Dec 2016
TL;DR: Insight is provided into how the three sensors of ER homeostasis monitor distinct types of stress and the ability of Perturb-seq to dissect complex cellular responses are highlighted.
Abstract: Functional genomics efforts face tradeoffs between number of perturbations examined and complexity of phenotypes measured. We bridge this gap with Perturb-seq, which combines droplet-based single-cell RNA-seq with a strategy for barcoding CRISPR-mediated perturbations, allowing many perturbations to be profiled in pooled format. We applied Perturb-seq to dissect the mammalian unfolded protein response (UPR) using single and combinatorial CRISPR perturbations. Two genome-scale CRISPR interference (CRISPRi) screens identified genes whose repression perturbs ER homeostasis. Subjecting ∼100 hits to Perturb-seq enabled high-precision functional clustering of genes. Single-cell analyses decoupled the three UPR branches, revealed bifurcated UPR branch activation among cells subject to the same perturbation, and uncovered differential activation of the branches across hits, including an isolated feedback loop between the translocon and IRE1α. These studies provide insight into how the three sensors of ER homeostasis monitor distinct types of stress and highlight the ability of Perturb-seq to dissect complex cellular responses.
593 citations
01 Dec 2016
TL;DR: Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions, and posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation.
Abstract: Genetic screens help infer gene function in mammalian cells, but it has remained difficult to assay complex phenotypes-such as transcriptional profiles-at scale. Here, we develop Perturb-seq, combining single-cell RNA sequencing (RNA-seq) and clustered regularly interspaced short palindromic repeats (CRISPR)-based perturbations to perform many such assays in a pool. We demonstrate Perturb-seq by analyzing 200,000 cells in immune cells and cell lines, focusing on transcription factors regulating the response of dendritic cells to lipopolysaccharide (LPS). Perturb-seq accurately identifies individual gene targets, gene signatures, and cell states affected by individual perturbations and their genetic interactions. We posit new functions for regulators of differentiation, the anti-viral response, and mitochondrial function during immune activation. By decomposing many high content measurements into the effects of perturbations, their interactions, and diverse cell metadata, Perturb-seq dramatically increases the scope of pooled genomic assays.
539 citations
01 Jan 2012
TL;DR: A meta-analysis of genome-wide association studies and independent data sets genotyped on the Immunochip identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals, and identified five independent signals within previously known loci.
Abstract: To gain further insight into the genetic architecture of psoriasis, we conducted a meta-analysis of 3 genome-wide association studies (GWAS) and 2 independent data sets genotyped on the Immunochip, including 10,588 cases and 22,806 controls. We identified 15 new susceptibility loci, increasing to 36 the number associated with psoriasis in European individuals. We also identified, using conditional analyses, five independent signals within previously known loci. The newly identified loci shared with other autoimmune diseases include candidate genes with roles in regulating T-cell function (such as RUNX3, TAGAP and STAT3). Notably, they included candidate genes whose products are involved in innate host defense, including interferon-mediated antiviral responses (DDX58), macrophage activation (ZC3H12C) and nuclear factor (NF)-κB signaling (CARD14 and CARM1). These results portend a better understanding of shared and distinctive genetic determinants of immune-mediated inflammatory disorders and emphasize the importance of the skin in innate and acquired host defense. © 2012 Nature America, Inc. All rights reserved.
464 citations