Showing papers by "Anne E. Justice published in 2021"
University of Bristol1, VU University Amsterdam2, Norwegian University of Science and Technology3, QIMR Berghofer Medical Research Institute4, Queensland University of Technology5, University of Queensland6, University of Helsinki7, University of Oslo8, King's College London9, Karolinska Institutet10, University of Cambridge11, Monash University12, University of Melbourne13, Western General Hospital14, University of Michigan15, University of Southern Denmark16, Odense University Hospital17, University of California, Berkeley18, University of Colorado Boulder19, University of Edinburgh20, University of Oxford21, Aarhus University22, Public Health Research Institute23, Norwegian Institute of Public Health24, University of Texas at Austin25, Peking University26, Stockholm University27, Max Planck Society28, Cancer Council Victoria29, University College London30, University of Wisconsin-Madison31, National Bureau of Economic Research32, University of California, Los Angeles33, University of Southern California34
TL;DR: In this article, the authors combined data on 159,701 siblings from 17 cohorts to generate population and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes.
Abstract: Estimates from genome-wide association studies (GWAS) represent a combination of the effect of inherited genetic variation (direct effects), demography (population stratification, assortative mating) and genetic nurture from relatives (indirect genetic effects). GWAS using family-based designs can control for demography and indirect genetic effects, but large-scale family datasets have been lacking. We combined data on 159,701 siblings from 17 cohorts to generate population (between-family) and within-sibship (within-family) estimates of genome-wide genetic associations for 25 phenotypes. We demonstrate that existing GWAS associations for height, educational attainment, smoking, depressive symptoms, age at first birth and cognitive ability overestimate direct effects. We show that estimates of SNP-heritability, genetic correlations and Mendelian randomization involving these phenotypes substantially differ when calculated using within-sibship estimates. For example, genetic correlations between educational attainment and height largely disappear. In contrast, analyses of most clinical phenotypes (e.g. LDL-cholesterol) were generally consistent between population and within-sibship models. We also report compelling evidence of polygenic adaptation on taller human height using within-sibship data. Large-scale family datasets provide new opportunities to quantify direct effects of genetic variation on human traits and diseases.
61 citations
AstraZeneca1, Biogen Idec2, Bristol-Myers Squibb3, Alnylam Pharmaceuticals4, Takeda Pharmaceutical Company5, AbbVie6, Pfizer7, University of Pennsylvania8, Columbia University9, Western General Hospital10, University of Edinburgh11, Queen Mary University of London12, Great Ormond Street Hospital for Children NHS Foundation Trust13, McGill University14, King's College London15
TL;DR: In this article, the authors used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), a respiratory illness causing hospitalization or death.
Abstract: Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19), a respiratory illness that can result in hospitalization or death. We used exome sequence data to investigate associations between rare genetic variants and seven COVID-19 outcomes in 586,157 individuals, including 20,952 with COVID-19. After accounting for multiple testing, we did not identify any clear associations with rare variants either exome wide or when specifically focusing on (1) 13 interferon pathway genes in which rare deleterious variants have been reported in individuals with severe COVID-19, (2) 281 genes located in susceptibility loci identified by the COVID-19 Host Genetics Initiative, or (3) 32 additional genes of immunologic relevance and/or therapeutic potential. Our analyses indicate there are no significant associations with rare protein-coding variants with detectable effect sizes at our current sample sizes. Analyses will be updated as additional data become available, and results are publicly available through the Regeneron Genetics Center COVID-19 Results Browser.
59 citations
TL;DR: In this paper, the authors investigated the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes.
Abstract: The clinical impact of rare loss-of-function variants has yet to be determined for most genes. Integration of DNA sequencing data with electronic health records (EHRs) could enhance our understanding of the contribution of rare genetic variation to human disease1. By leveraging 10,900 whole-exome sequences linked to EHR data in the Penn Medicine Biobank, we addressed the association of the cumulative effects of rare predicted loss-of-function variants for each individual gene on human disease on an exome-wide scale, as assessed using a set of diverse EHR phenotypes. After discovering 97 genes with exome-by-phenome-wide significant phenotype associations (P < 10−6), we replicated 26 of these in the Penn Medicine Biobank, as well as in three other medical biobanks and the population-based UK Biobank. Of these 26 genes, five had associations that have been previously reported and represented positive controls, whereas 21 had phenotype associations not previously reported, among which were genes implicated in glaucoma, aortic ectasia, diabetes mellitus, muscular dystrophy and hearing loss. These findings show the value of aggregating rare predicted loss-of-function variants into ‘gene burdens’ for identifying new gene–disease associations using EHR phenotypes in a medical biobank. We suggest that application of this approach to even larger numbers of individuals will provide the statistical power required to uncover unexplored relationships between rare genetic variation and disease phenotypes. Analysis of 10,900 whole-exome sequences linked to electronic health care records in the Penn Medicine Biobank enabled an exome-wide study of the phenotypic effects of rare loss-of-function gene variants, identifying new gene–disease associations that replicated across other biobanks.
37 citations
Mayo Clinic1, VA Palo Alto Healthcare System2, Stanford University3, Vanderbilt University4, Kaiser Permanente5, Columbia University6, University of Washington7, Cincinnati Children's Hospital Medical Center8, Vanderbilt University Medical Center9, Marshfield Clinic10, National Institutes of Health11
TL;DR: In this article, Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than individuals of European ancestry (EA) and they examined associations of genetically predicted Lp (a)...
Abstract: Background: Lp(a) (lipoprotein [a]) levels are higher in individuals of African ancestry (AA) than in individuals of European ancestry (EA). We examined associations of genetically predicted Lp(a) ...
14 citations
TL;DR: In this article, a trans-ethnic meta-analysis revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
Abstract: Although many loci have been associated with height in European ancestry populations, very few have been identified in African ancestry individuals. Furthermore, many of the known loci have yet to be generalized to and fine-mapped within a large-scale African ancestry sample. We performed sex-combined and sex-stratified meta-analyses in up to 52,764 individuals with height and genome-wide genotyping data from the African Ancestry Anthropometry Genetics Consortium (AAAGC). We additionally combined our African ancestry meta-analysis results with published European genome-wide association study (GWAS) data. In the African ancestry analyses, we identified three novel loci (SLC4A3, NCOA2, ECD/FAM149B1) in sex-combined results and two loci (CRB1, KLF6) in women only. In the African plus European sex-combined GWAS, we identified an additional three novel loci (RCCD1, G6PC3, CEP95) which were equally driven by AAAGC and European results. Among 39 genome-wide significant signals at known loci, conditioning index SNPs from European studies identified 20 secondary signals. Two of the 20 new secondary signals and none of the 8 novel loci had minor allele frequencies (MAF) < 5%. Of 802 known European height signals, 643 displayed directionally consistent associations with height, of which 205 were nominally significant (p < 0.05) in the African ancestry sex-combined sample. Furthermore, 148 of 241 loci contained ≤20 variants in the credible sets that jointly account for 99% of the posterior probability of driving the associations. In summary, trans-ethnic meta-analyses revealed novel signals and further improved fine-mapping of putative causal variants in loci shared between African and European ancestry populations.
13 citations
Geisinger Health System1, University of North Carolina at Chapel Hill2, University of Washington3, University of Arizona4, Mexican Social Security Institute5, Los Angeles Biomedical Research Institute6, Universidade Federal de Pelotas7, Vanderbilt University Medical Center8, University of California, San Diego9, University of Southern California10, Cedars-Sinai Medical Center11, University of Texas Health Science Center at Houston12, Ohio State University13, University of Toronto14, Columbia University Medical Center15, University of California, Irvine16, Kaiser Permanente17, Rush University Medical Center18, Albert Einstein College of Medicine19
TL;DR: In this paper, the authors identify loci associated with central obesity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP) adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).
Abstract: Author(s): Justice, Anne E; Young, Kristin; Gogarten, Stephanie M; Sofer, Tamar; Graff, Misa; Love, Shelly Ann M; Wang, Yujie; Klimentidis, Yann C; Cruz, Miguel; Guo, Xiuqing; Hartwig, Fernando; Petty, Lauren; Yao, Jie; Allison, Matthew A; Below, Jennifer E; Buchanan, Thomas A; Chen, Yii-Der Ida; Goodarzi, Mark O; Hanis, Craig; Highland, Heather M; Hsueh, Willa A; Ipp, Eli; Parra, Esteban; Palmas, Walter; Raffel, Leslie J; Rotter, Jerome I; Tan, Jingyi; Taylor, Kent D; Valladares, Adan; Xiang, Anny H; Sanchez-Johnsen, Lisa; Isasi, Carmen R; North, Kari E | Abstract: Central obesity is a leading health concern with a great burden carried by ethnic minority populations, especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aimed to identify loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP) adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); determine if differences in associations differ by background group within HCHS/SOL; and determine whether previously reported associations generalize to HCHS/SOL. Our analyses included 7472 women and 5200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban, and Dominican) background residing in the US. We performed genome-wide association analyses stratified and combined across sexes using linear mixed-model regression. We identified 16 variants for WHRadjBMI, 22 for WCadjBMI, and 28 for HIPadjBMI that reached suggestive significance (P l 1x10-6). Many loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in cohorts (N = 34 161) with participants of Hispanic/Latino, African and European descent. We confirmed 4 novel loci (P l 0.05 and consistent direction of effect, and P l 5x10-8 after meta-analysis), including 2 for WHRadjBMI (rs13301996, rs79478137); 1 for WCadjBMI (rs3168072); and 1 for HIPadjBMI (rs28692724). Also, we generalized previously reported associations to HCHS/SOL, (8 for WHRadjBMI; 10 for WCadjBMI; 12 for HIPadjBMI). Our study highlights the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity-susceptibility that may be ancestry-specific.
5 citations
05 May 2021
TL;DR: This research presents a novel and scalable approach to regenerative medicine based on the principles of cell reprograming, which has the potential to improve the quality of life of patients and dramatically reduce the risks of adverse events.
Abstract: Seon-Kyeong Jang, Luke Evans, Allison Fialkowski, Donna K. Arnett, Diane M. Becker, Joshua C. Bis, John Blangero, Eugene R. Bleecker, Jennifer A Brody, L. Adrienne Cupples, Scott M. Damrauer, Sean P. David, Mariza de Andrade, Tasha E. Fingerlin, Sina A. Gharib, David C Glahn, Jeffrey Haessler, Susan R. Heckbert, John E. Hokanson, Shih-Jen Hwang, Matthew C. Hyman, Renae Judy, Anne E. Justice, Robert C Kaplan, Wonji Kim, Charles Kooperberg, Dan Levy, Ruth J.F. Loos, Ani W. Manichaikul, Mark T. Gladwin, Lisa Warsinger Martin, Mehdi Nouraie, Olle Melander, Deborah A. Meyers, Kari E. North, Elizabeth C. Oelsner, Anna L. Peljto, Michael Preuss, Bruce M Psaty, Dandi Qiao, Daniel J. Rader, Robert M. Reed, Alexander P. Reiner, Stephen S. Rich, Jerome I. Rotter, David A. Schwartz, Aladdin H. Shadyab, Edwin K. Silverman, Nicholas L. Smith, J. Gustav Smith, Albert V. Smith, Weihong Tang, Kent D. Taylor, Ramachandran S. Vasan, Victor R. Gordeuk, Zhe Wang, Kerri L. Wiggins, Lisa R. Yanek, Ivana V. Yang, Kendra A. Young, Kristin L. Young, Yingze Zhang, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Dajiang J. Liu, Matthew Keller, Scott Vrieze
4 citations
TL;DR: The United States Department of Health and Human Services (USDHHS) as discussed by the authors is a part of the National Institutes of Health (NIH) and National Cancer Institute (NCI).
Abstract: American Diabetes Association
1-19-PDF-045
American Heart Association
15GRNT25880008
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Cancer Institute (NCI)
U01CA164973
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Heart Lung & Blood Institute (NHLBI)
HHSN268201100001C
HHSN268201100002C
HHSN268201100003C
HHSN268201100004C
HHSN268201100046C
HHSN268201200008I
HHSN271201100004C
K99/R00HL130580
N01-HC65233
N01-HC65234
N01-HC65235
N01-HC65236
N01-HC65237
R01HL088530
R01HL142825
T32 HL007055
T32 HL129982-03
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Human Genome Research Institute (NHGRI)
U01HG007376
U01HG007397
U01HG007419
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD)
R01 HD33487
United States Department of Health & Human Services
National Institutes of Health (NIH) - USA
NIH National Institute on Minority Health & Health Disparities (NIMHD)
U01HG007416
North Carolina Nutrition Research Institute
2 citations
TL;DR: In this article, the authors investigated the genetic determinants of metabolic biomarkers and their associations with CMD risk factors, and found evidence of substantial mediation of these associations by the biomarker levels.
Abstract: BACKGROUND Metabolic regulation plays a significant role in energy homeostasis, and adolescence is a crucial life stage for the development of cardiometabolic disease (CMD). This study aims to investigate the genetic determinants of metabolic biomarkers-adiponectin, leptin, ghrelin, and orexin-and their associations with CMD risk factors. METHODS We characterized the genetic determinants of the biomarkers among Hispanic/Latino adolescents of the Santiago Longitudinal Study (SLS) and identified the cumulative effects of genetic variants on adiponectin and leptin using biomarker polygenic risk scores (PRS). We further investigated the direct and indirect effect of the biomarker PRS on downstream body fat percent (BF%) and glycemic traits using structural equation modeling. RESULTS We identified putatively novel genetic variants associated with the metabolic biomarkers. A substantial amount of biomarker variance was explained by SLS-specific PRS, and the prediction was improved by including the putatively novel loci. Fasting blood insulin and insulin resistance were associated with PRS for adiponectin, leptin, and ghrelin, and BF% was associated with PRS for adiponectin and leptin. We found evidence of substantial mediation of these associations by the biomarker levels. CONCLUSIONS The genetic underpinnings of metabolic biomarkers can affect the early development of CMD, partly mediated by the biomarkers. IMPACT This study characterized the genetic underpinnings of four metabolic hormones and investigated their potential influence on adiposity and insulin biology among Hispanic/Latino adolescents. Fasting blood insulin and insulin resistance were associated with polygenic risk score (PRS) for adiponectin, leptin, and ghrelin, with evidence of some degree of mediation by the biomarker levels. Body fat percent (BF%) was also associated with PRS for adiponectin and leptin. This provides important insight on biological mechanisms underlying early metabolic dysfunction and reveals candidates for prevention efforts. Our findings also highlight the importance of ancestrally diverse populations to facilitate valid studies of the genetic architecture of metabolic biomarker levels.
University of North Carolina at Chapel Hill1, Geisinger Health System2, University of Washington3, University of Arizona4, Los Angeles Biomedical Research Institute5, Universidade Federal de Pelotas6, Vanderbilt University Medical Center7, University of California, San Diego8, University of Southern California9, Cedars-Sinai Medical Center10, University of Texas Health Science Center at Houston11, Ohio State University12, University of Toronto13, Columbia University Medical Center14, University of California, Berkeley15, Kaiser Permanente16, Rush University Medical Center17, Albert Einstein College of Medicine18
TL;DR: In this paper, the authors identify novel loci associated with central obesity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP), all adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL).
Abstract: Central obesity is a leading health concern with a great burden carried by ethnic minority populations, and especially Hispanics/Latinos. Genetic factors contribute to the obesity burden overall and to inter-population differences. We aim to: 1) identify novel loci associated with central adiposity measured as waist-to-hip ratio (WHR), waist circumference (WC), and hip circumference (HIP), all adjusted for body mass index (adjBMI), using the Hispanic Community Health Study/Study of Latinos (HCHS/SOL); 2) determine if differences in genetic associations differ by background group within HCHS/SOL; 3) determine whether previously reported association regions generalize to HCHS/SOL. Our analyses included 7,472 women and 5,200 men of mainland (Mexican, Central and South American) and Caribbean (Puerto Rican, Cuban, and Dominican) background residing in the US, with genome-wide array data imputed to the 1000 genomes Phase I multiethnic reference panel. We analyzed associations stratified by sex in addition to sexes combined using linear mixed-model regression. We identified 16 variants for WHRadjBMI, 22 for WCadjBMI, and 28 for HIPadjBMI that reached suggestive significance (P<1x10-6). Many of the loci exhibited differences in strength of associations by ethnic background and sex. We brought a total of 66 variants forward for validation in nine cohort studies (N=34,161) with participants of Hispanic/Latino, African and European descent. We confirmed four novel loci (ancestry-specific P<0.05 in replication, consistent direction of effect with HCHS/SOL, and P<5x10-8 after meta-analysis with HCHS/SOL), including rs13301996 in the sexes-combined analysis, and rs79478137 for women-only for WHRadjBMI; rs28692724 in women-only for HIPadjBMI; and rs3168072 in the sexes combined analysis for WCadjBMI. Also, a total of eight previously reported WHRadjBMI association regions, 12 for HIPadjBMI, and 10 for WCadjBMI generalized to HCHS/SOL. Our study findings highlight the importance of large-scale genomic studies in ancestrally diverse Hispanic/Latino populations for identifying and characterizing central obesity-susceptibility that may be ancestry-specific.
University of North Carolina at Chapel Hill1, Pennsylvania State University2, University of Florida3, University of Washington4, University of California, Los Angeles5, Stanford University6, University of Minnesota7, University of Texas Health Science Center at Houston8, Emory University9, Northwestern University10, Columbia University11
TL;DR: In this article, the authors found that among racially/ethnically and environmentally diverse U.S. populations, sub-chronic exposures to coarser particulates may not exert appreciable, epigenetically mediated effects on cardiac autonomic function or ventricular repolarization.
Pennsylvania State University1, University of North Carolina at Chapel Hill2, University of California, Los Angeles3, Vanderbilt University Medical Center4, Open University5, Wake Forest University6, Children's Hospital of Philadelphia7, University of São Paulo8, University of Southern California9, Vertex Pharmaceuticals10, University of Copenhagen11, Icahn School of Medicine at Mount Sinai12, Hasso Plattner Institute13, University of Antioquia14, Universidade Federal do Rio Grande do Sul15, National Autonomous University of Mexico16, Cayetano Heredia University17, University of Tarapacá18, Case Western Reserve University19, University of Washington20, Albert Einstein College of Medicine21, National Institutes of Health22, University of Michigan23, Ohio State University24, University of California, Berkeley25, Los Angeles Biomedical Research Institute26, Cedars-Sinai Medical Center27, The Ohio State University Wexner Medical Center28, Beckman Research Institute29, New York Medical College30, Kaiser Permanente31, Mexican Social Security Institute32, Universidade Federal de Pelotas33, University of Texas at Austin34, University of California, Davis35, Stanford University36, Massachusetts Institute of Technology37, Harvard University38, University of California, San Diego39, University of Texas Health Science Center at Houston40, United States Department of Agriculture41, Baylor College of Medicine42, Texas Biomedical Research Institute43, Obesity Society44, Brigham and Women's Hospital45, University of Toronto46
TL;DR: In this article, the authors analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults, to identify and fine-map common genetic variants associated with body mass index (BMI), height, and BMI adjusted waist-to-hip ratio (WHRadjBMI).
Abstract: Hispanic/Latinos have been underrepresented in genome-wide association studies (GWAS) for anthropometric traits despite notable anthropometric variability with ancestry proportions, and a high burden of growth stunting and overweight/obesity in Hispanic/Latino populations. This address this knowledge gap, we analyzed densely-imputed genetic data in a sample of Hispanic/Latino adults, to identify and fine-map common genetic variants associated with body mass index (BMI), height, and BMI-adjusted waist-to-hip ratio (WHRadjBMI). We conducted a GWAS of 18 studies/consortia as part of the Hispanic/Latino Anthropometry (HISLA) Consortium (Stage 1, n=59,769) and validated our findings in 9 additional studies (HISLA Stage 2, n=9,336). We conducted a trans-ethnic GWAS with summary statistics from HISLA Stage 1 and existing consortia of European and African ancestries. In our HISLA Stage 1+2 analyses, we discovered one novel BMI locus, as well two novel BMI signals and another novel height signal, each within established anthropometric loci. In our trans-ethnic meta- analysis, we identified three additional novel BMI loci, one novel height locus, and one novel WHRadjBMI locus. We also identified three secondary signals for BMI, 28 for height, and two for WHRadjBMI. We replicated >60 established anthropometric loci in Hispanic/Latino populations at genome-wide significance—representing up to 30% of previously-reported index SNP anthropometric associations. Trans-ethnic meta-analysis of the three ancestries showed a small-to-moderate impact of uncorrected population stratification on the resulting effect size estimates. Our novel findings demonstrate that future studies may also benefit from leveraging differences in linkage disequilibrium patterns to discover novel loci and additional signals with less residual population stratification.