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Zhao C, Su KJ, Wu C, Cao X, Sha Q, Li W, Luo Z, Qing T, Qiu C, Zhao LJ, Liu A, Jiang L, Zhang X, Shen H, Zhou W, Deng HW. Multi-scale variational autoencoder for imputation of missing values in untargeted metabolomics using whole-genome sequencing data. Comput Biol Med 2024; 179:108813. [PMID: 38955127 PMCID: PMC11324385 DOI: 10.1016/j.compbiomed.2024.108813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2024] [Revised: 06/18/2024] [Accepted: 06/24/2024] [Indexed: 07/04/2024]
Abstract
BACKGROUND Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in metabolomics studies. METHOD In this study, we propose a novel method that leverages the information from WGS data and reference metabolites to impute unknown metabolites. Our approach utilizes a multi-scale variational autoencoder to jointly model the burden score, polygenetic risk score (PGS), and linkage disequilibrium (LD) pruned single nucleotide polymorphisms (SNPs) for feature extraction and missing metabolomics data imputation. By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information. RESULTS We evaluate the performance of our method on empirical metabolomics datasets with missing values and demonstrate its superiority compared to conventional imputation techniques. Using 35 template metabolites derived burden scores, PGS and LD-pruned SNPs, the proposed methods achieved R2-scores > 0.01 for 71.55 % of metabolites. CONCLUSION The integration of WGS data in metabolomics imputation not only improves data completeness but also enhances downstream analyses, paving the way for more comprehensive and accurate investigations of metabolic pathways and disease associations. Our findings offer valuable insights into the potential benefits of utilizing WGS data for metabolomics data imputation and underscore the importance of leveraging multi-modal data integration in precision medicine research.
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Affiliation(s)
- Chen Zhao
- Department of Computer Science, Kennesaw State University, 680 Arntson Dr, Marietta, GA, 30060, USA
| | - Kuan-Jui Su
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Chong Wu
- Department of Biostatistics, University of Texas MD Anderson, Pickens Academic Tower, 1400 Pressler St., Houston, TX, 77030, USA
| | - Xuewei Cao
- Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA
| | - Qiuying Sha
- Department of Mathematical Sciences, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA
| | - Wu Li
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Zhe Luo
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Tian Qing
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Chuan Qiu
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Lan Juan Zhao
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Anqi Liu
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Lindong Jiang
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Xiao Zhang
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Hui Shen
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
| | - Weihua Zhou
- Department of Applied Computing, Michigan Technological University, 1400 Townsend Dr, Houghton, MI, 49931, USA; Center for Biocomputing and Digital Health, Institute of Computing and Cybersystems, and Health Research Institute, Michigan Technological University, Houghton, MI, 49931, USA.
| | - Hong-Wen Deng
- Division of Biomedical Informatics and Genomics, Tulane Center of Biomedical Informatics and Genomics, Deming Department of Medicine, Tulane University, New Orleans, LA, 70112, USA
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Musfee FI, Jun G, Mitchell LE, Chen H, Guo D, Prakash SK, Adkar SS, Grove ML, Choi RB, Klarin D, Boerwinkle E, Milewicz DM. X-linked genetic associations in sporadic thoracic aortic dissection. Am J Med Genet A 2024; 194:e63644. [PMID: 38688863 PMCID: PMC11315632 DOI: 10.1002/ajmg.a.63644] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/22/2023] [Revised: 03/06/2024] [Accepted: 04/13/2024] [Indexed: 05/02/2024]
Abstract
The male predominance in sporadic thoracic aortic aneurysm and dissection (TAD) suggests that the X chromosome contributes to TAD, but this has not been tested. We investigated whether X-linked variation-common (minor allele frequency [MAF] ≥0.01) and rare (MAF <0.01)-was associated with sporadic TAD in three cohorts of European descent (Discovery: 364 cases, 874 controls; Replication: 516 cases, 440,131 controls, and ARIC [Atherosclerosis Risk in Communities study]: 753 cases, 2247 controls). For analysis of common variants, we applied a sex-stratified logistic regression model followed by a meta-analysis of sex-specific odds ratios. Furthermore, we conducted a meta-analysis of overlapping common variants between the Discovery and Replication cohorts. For analysis of rare variants, we used a sex-stratified optimized sequence kernel association test model. Common variants results showed no statistically significant findings in the Discovery cohort. An intergenic common variant near SPANXN1 was statistically significant in the Replication cohort (p = 1.81 × 10-8). The highest signal from the meta-analysis of the Discovery and Replication cohorts was a ZNF182 intronic common variant (p = 3.5 × 10-6). In rare variants results, RTL9 reached statistical significance (p = 5.15 × 10-5). Although most of our results were statistically insignificant, our analysis is the most comprehensive X-chromosome association analysis of sporadic TAD to date.
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Affiliation(s)
- Fadi I. Musfee
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Department of Epidemiology, Fay W. Boozman College of Public Health, University of Arkansas for Medical Sciences, Little Rock, AR, USA
| | - Goo Jun
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Laura E. Mitchell
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Han Chen
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Center for Precision Health, School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Dongchuan Guo
- Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, TX 77030, USA
| | - Siddharth K. Prakash
- Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, TX 77030, USA
| | - Shaunak Sanjay Adkar
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Megan L. Grove
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
| | - Ryan Bohyun Choi
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
| | - Derek Klarin
- Veterans Affairs Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Surgery, Stanford University School of Medicine, Palo Alto, CA, USA
| | | | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX, USA
| | - Dianna M. Milewicz
- Department of Internal Medicine, McGovern Medical School, The University of Texas Health Science Center at Houston, TX 77030, USA
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3
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Wang H, Chang TS, Dombroski BA, Cheng PL, Patil V, Valiente-Banuet L, Farrell K, Mclean C, Molina-Porcel L, Rajput A, De Deyn PP, Le Bastard N, Gearing M, Kaat LD, Van Swieten JC, Dopper E, Ghetti BF, Newell KL, Troakes C, de Yébenes JG, Rábano-Gutierrez A, Meller T, Oertel WH, Respondek G, Stamelou M, Arzberger T, Roeber S, Müller U, Hopfner F, Pastor P, Brice A, Durr A, Le Ber I, Beach TG, Serrano GE, Hazrati LN, Litvan I, Rademakers R, Ross OA, Galasko D, Boxer AL, Miller BL, Seeley WW, Van Deerlin VM, Lee EB, White CL, Morris H, de Silva R, Crary JF, Goate AM, Friedman JS, Leung YY, Coppola G, Naj AC, Wang LS, Dalgard C, Dickson DW, Höglinger GU, Schellenberg GD, Geschwind DH, Lee WP. Whole-genome sequencing analysis reveals new susceptibility loci and structural variants associated with progressive supranuclear palsy. Mol Neurodegener 2024; 19:61. [PMID: 39152475 PMCID: PMC11330058 DOI: 10.1186/s13024-024-00747-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Accepted: 07/22/2024] [Indexed: 08/19/2024] Open
Abstract
BACKGROUND Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs). METHOD In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed. RESULTS Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73 × 10-3) in PSP. CONCLUSIONS Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy S Chang
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Po-Liang Cheng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vishakha Patil
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Leopoldo Valiente-Banuet
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kurt Farrell
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catriona Mclean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Parkville, VIC, Australia
| | - Laura Molina-Porcel
- Alzheimer's Disease and Other Cognitive Disorders Unit. Neurology Service, Hospital Clínic, Fundació Recerca Clínic Barcelona (FRCB). Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Neurological Tissue Bank of the Biobanc-Hospital Clínic-IDIBAPS, Barcelona, Spain
| | - Alex Rajput
- Movement Disorders Program, Division of Neurology, University of Saskatchewan, Saskatoon, SK, Canada
| | - Peter Paul De Deyn
- Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Unit, University of Antwerp, Wilrijk (Antwerp), Belgium
- Department of Neurology, University Medical Center Groningen, NL-9713 AV, Groningen, Netherlands
| | | | - Marla Gearing
- Department of Pathology and Laboratory Medicine and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | - Laura Donker Kaat
- Netherlands Brain Bank and Erasmus University, Rotterdam, Netherlands
| | | | - Elise Dopper
- Netherlands Brain Bank and Erasmus University, Rotterdam, Netherlands
| | - Bernardino F Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Claire Troakes
- London Neurodegenerative Diseases Brain Bank, King's College London, London, UK
| | | | - Alberto Rábano-Gutierrez
- Fundación CIEN (Centro de Investigación de Enfermedades Neurológicas) - Centro Alzheimer Fundación Reina Sofía, Madrid, Spain
| | - Tina Meller
- Department of Neurology, Philipps-Universität, Marburg, Germany
| | | | - Gesine Respondek
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maria Stamelou
- Parkinson's Disease and Movement Disorders Department, HYGEIA Hospital, Athens, Greece
- European University of Cyprus, Nicosia, Cyprus
| | - Thomas Arzberger
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Ludwig-Maximilians-University Munich, Munich, Germany
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Sigrun Roeber
- German Brain Bank, Neurobiobank Munich, Munich, Germany
| | - Ulrich Müller
- German Brain Bank, Neurobiobank Munich, Munich, Germany
| | - Franziska Hopfner
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Pau Pastor
- Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias I Pujol, Badalona, Barcelona, Spain
- Neurosciences, The Germans Trias I Pujol Research Institute (IGTP) Badalona, Badalona, Spain
| | - Alexis Brice
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | | | | | | | - Irene Litvan
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Antwerp, Belgium
- Department of Neuroscience, Mayo Clinic Jacksonville, Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic Jacksonville, Jacksonville, FL, USA
| | - Douglas Galasko
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Willian W Seeley
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Vivanna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Charles L White
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Huw Morris
- Departmento of Clinical and Movement Neuroscience, University College of London, London, UK
| | - Rohan de Silva
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, UK
| | - John F Crary
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, New York, NY, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | | | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Giovanni Coppola
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Adam C Naj
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Clifton Dalgard
- Department of Anatomy Physiology and Genetics, the American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Dennis W Dickson
- Department of Neuroscience, Mayo Clinic Jacksonville, Jacksonville, FL, USA.
| | - Günter U Höglinger
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
| | - Daniel H Geschwind
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA.
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA.
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
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Mbatchou J, McPeek MS. JASPER: Fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression. Am J Hum Genet 2024; 111:1750-1769. [PMID: 39025064 PMCID: PMC11339629 DOI: 10.1016/j.ajhg.2024.06.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2023] [Revised: 06/19/2024] [Accepted: 06/20/2024] [Indexed: 07/20/2024] Open
Abstract
Joint association analysis of multiple traits with multiple genetic variants can provide insight into genetic architecture and pleiotropy, improve trait prediction, and increase power for detecting association. Furthermore, some traits are naturally high-dimensional, e.g., images, networks, or longitudinally measured traits. Assessing significance for multitrait genetic association can be challenging, especially when the sample has population sub-structure and/or related individuals. Failure to adequately adjust for sample structure can lead to power loss and inflated type 1 error, and commonly used methods for assessing significance can work poorly with a large number of traits or be computationally slow. We developed JASPER, a fast, powerful, robust method for assessing significance of multitrait association with a set of genetic variants, in samples that have population sub-structure, admixture, and/or relatedness. In simulations, JASPER has higher power, better type 1 error control, and faster computation than existing methods, with the power and speed advantage of JASPER increasing with the number of traits. JASPER is potentially applicable to a wide range of association testing applications, including for multiple disease traits, expression traits, image-derived traits, and microbiome abundances. It allows for covariates, ascertainment, and rare variants and is robust to phenotype model misspecification. We apply JASPER to analyze gene expression in the Framingham Heart Study, where, compared to alternative approaches, JASPER finds more significant associations, including several that indicate pleiotropic effects, most of which replicate previous results, while others have not previously been reported. Our results demonstrate the promise of JASPER for powerful multitrait analysis in structured samples.
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Affiliation(s)
- Joelle Mbatchou
- Regeneron Genetics Center, Tarrytown, NY 10591, USA; Department of Statistics, The University of Chicago, Chicago, IL 60637, USA
| | - Mary Sara McPeek
- Department of Statistics, The University of Chicago, Chicago, IL 60637, USA; Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA.
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5
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Senkevich K, Liu L, Alvarado CX, Leonard HL, Nalls MA, Gan-Or Z. Lack of genetic evidence for NLRP3 inflammasome involvement in Parkinson's disease pathogenesis. NPJ Parkinsons Dis 2024; 10:145. [PMID: 39103393 DOI: 10.1038/s41531-024-00744-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Accepted: 06/26/2024] [Indexed: 08/07/2024] Open
Abstract
Activation of the NLRP3 inflammasome has been implicated in Parkinson's disease (PD) based on in vitro and in vivo studies. Clinical trials targeting the NLRP3 inflammasome in PD are ongoing. However, the evidence supporting NLRP3's involvement in PD from human genetics data is limited. We analyzed common and rare variants in NLRP3 inflammasome-related genes in PD cohorts, performed pathway-specific polygenic risk score (PRS) analyses, and studied causal associations using Mendelian randomization (MR) with the NLRP3 components and the cytokines IL-1β and IL-18. Our findings showed no associations of common or rare variants, nor of the pathway PRS with PD. MR suggests that altering the expression of the NLRP3 inflammasome, IL-1β, or IL-18, does not affect PD risk or progression. Therefore, our results do not support a role for the NLRP3 inflammasome in PD pathogenesis or as a target for drug development.
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Affiliation(s)
- Konstantin Senkevich
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada
| | - Lang Liu
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Chelsea X Alvarado
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20814, USA
- Data Tecnica, Washington, DC, 200373, USA
| | - Hampton L Leonard
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20814, USA
- Data Tecnica, Washington, DC, 200373, USA
- DZNE Tübingen, Tübingen, Germany
| | - Mike A Nalls
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD, 20814, USA
- Data Tecnica, Washington, DC, 200373, USA
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, QC, Canada.
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada.
- Department of Human Genetics, McGill University, Montréal, QC, Canada.
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6
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Park J, Peña-Tauber A, Talozzi L, Greicius MD, Guen YL. Genetic associations with human longevity are enriched for oncogenic genes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.07.30.24311226. [PMID: 39132489 PMCID: PMC11312667 DOI: 10.1101/2024.07.30.24311226] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/13/2024]
Abstract
Human lifespan is shaped by both genetic and environmental exposures and their interaction. To enable precision health, it is essential to understand how genetic variants contribute to earlier death or prolonged survival. In this study, we tested the association of common genetic variants and the burden of rare non-synonymous variants in a survival analysis, using age-at-death (N = 35,551, median [min, max] = 72.4 [40.9, 85.2]), and last-known-age (N = 358,282, median [min, max] = 71.9 [52.6, 88.7]), in European ancestry participants of the UK Biobank. The associations we identified seemed predominantly driven by cancer, likely due to the age range of the cohort. Common variant analysis highlighted three longevity-associated loci: APOE, ZSCAN23, and MUC5B. We identified six genes whose burden of loss-of-function variants is significantly associated with reduced lifespan: TET2, ATM, BRCA2, CKMT1B, BRCA1 and ASXL1. Additionally, in eight genes, the burden of pathogenic missense variants was associated with reduced lifespan: DNMT3A, SF3B1, CHL1, TET2, PTEN, SOX21, TP53 and SRSF2. Most of these genes have previously been linked to oncogenic-related pathways and some are linked to and are known to harbor somatic variants that predispose to clonal hematopoiesis. A direction-agnostic (SKAT-O) approach additionally identified significant associations with C1orf52, TERT, IDH2, and RLIM, highlighting a link between telomerase function and longevity as well as identifying additional oncogenic genes. Our results emphasize the importance of understanding genetic factors driving the most prevalent causes of mortality at a population level, highlighting the potential of early genetic testing to identify germline and somatic variants increasing one's susceptibility to cancer and/or early death.
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Affiliation(s)
- Junyoung Park
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Andrés Peña-Tauber
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Lia Talozzi
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Michael D. Greicius
- Department of Neurology and Neurological Sciences, Stanford University, Stanford, CA, 94305, USA
| | - Yann Le Guen
- Quantitative Sciences Unit, Department of Medicine, Stanford University, Stanford, CA, 94304, USA
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7
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Chia R, Ray A, Shah Z, Ding J, Ruffo P, Fujita M, Menon V, Saez-Atienzar S, Reho P, Kaivola K, Walton RL, Reynolds RH, Karra R, Sait S, Akcimen F, Diez-Fairen M, Alvarez I, Fanciulli A, Stefanova N, Seppi K, Duerr S, Leys F, Krismer F, Sidoroff V, Zimprich A, Pirker W, Rascol O, Foubert-Samier A, Meissner WG, Tison F, Pavy-Le Traon A, Pellecchia MT, Barone P, Russillo MC, Marín-Lahoz J, Kulisevsky J, Torres S, Mir P, Periñán MT, Proukakis C, Chelban V, Wu L, Goh YY, Parkkinen L, Hu MT, Kobylecki C, Saxon JA, Rollinson S, Garland E, Biaggioni I, Litvan I, Rubio I, Alcalay RN, Kwei KT, Lubbe SJ, Mao Q, Flanagan ME, Castellani RJ, Khurana V, Ndayisaba A, Calvo A, Mora G, Canosa A, Floris G, Bohannan RC, Moore A, Norcliffe-Kaufmann L, Palma JA, Kaufmann H, Kim C, Iba M, Masliah E, Dawson TM, Rosenthal LS, Pantelyat A, Albert MS, Pletnikova O, Troncoso JC, Infante J, Lage C, Sánchez-Juan P, Serrano GE, Beach TG, Pastor P, Morris HR, Albani D, Clarimon J, Wenning GK, Hardy JA, Ryten M, Topol E, Torkamani A, Chiò A, Bennett DA, De Jager PL, Low PA, Singer W, Cheshire WP, Wszolek ZK, Dickson DW, Traynor BJ, Gibbs JR, Dalgard CL, Ross OA, Houlden H, Scholz SW. Genome sequence analyses identify novel risk loci for multiple system atrophy. Neuron 2024; 112:2142-2156.e5. [PMID: 38701790 PMCID: PMC11223971 DOI: 10.1016/j.neuron.2024.04.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Revised: 02/28/2024] [Accepted: 04/02/2024] [Indexed: 05/05/2024]
Abstract
Multiple system atrophy (MSA) is an adult-onset, sporadic synucleinopathy characterized by parkinsonism, cerebellar ataxia, and dysautonomia. The genetic architecture of MSA is poorly understood, and treatments are limited to supportive measures. Here, we performed a comprehensive analysis of whole genome sequence data from 888 European-ancestry MSA cases and 7,128 controls to systematically investigate the genetic underpinnings of this understudied neurodegenerative disease. We identified four significantly associated risk loci using a genome-wide association study approach. Transcriptome-wide association analyses prioritized USP38-DT, KCTD7, and lnc-KCTD7-2 as novel susceptibility genes for MSA within these loci, and single-nucleus RNA sequence analysis found that the associated variants acted as cis-expression quantitative trait loci for multiple genes across neuronal and glial cell types. In conclusion, this study highlights the role of genetic determinants in the pathogenesis of MSA, and the publicly available data from this study represent a valuable resource for investigating synucleinopathies.
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Affiliation(s)
- Ruth Chia
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Anindita Ray
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Zalak Shah
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Jinhui Ding
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Paola Ruffo
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA; Medical Genetics Laboratory, Department of Pharmacy, Health and Nutritional Sciences, University of Calabria, Rende, Italy
| | - Masashi Fujita
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Vilas Menon
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Sara Saez-Atienzar
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Paolo Reho
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Karri Kaivola
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Ronald L Walton
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA
| | - Regina H Reynolds
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK; Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, UK; Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Ramita Karra
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Shaimaa Sait
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Fulya Akcimen
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Monica Diez-Fairen
- Memory and Movement Disorders Units, Department of Neurology, University Hospital Mutua de Terrassa, Barcelona, Spain
| | - Ignacio Alvarez
- Memory and Movement Disorders Units, Department of Neurology, University Hospital Mutua de Terrassa, Barcelona, Spain
| | | | - Nadia Stefanova
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Klaus Seppi
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Susanne Duerr
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Fabian Leys
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Florian Krismer
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - Victoria Sidoroff
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | | | - Walter Pirker
- Department of Neurology, Klinik Ottakring - Wilhelminenspital, Vienna, Austria
| | - Olivier Rascol
- MSA French Reference Center and CIC-1436, Department of Clinical Pharmacology and Neurosciences, University of Toulouse, Toulouse, France
| | - Alexandra Foubert-Samier
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France
| | - Wassilios G Meissner
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France; University of Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, France; Department of Medicine, University of Otago, and the New Zealand Brain Research Institute, Christchurch, New Zealand
| | - François Tison
- Service de Neurologie des Maladies Neurodégénératives, French Reference Center for MSA, NS-Park/FCRIN Network, CHU Bordeaux, Bordeaux, France; University of Bordeaux, CNRS, IMN, UMR 5293, Bordeaux, France
| | - Anne Pavy-Le Traon
- French Reference Center for MSA, Department of Neurosciences, Centre d'Investigation Clinique de Toulouse CIC1436, UMR 1048, Institute of Cardiovascular and Metabolic Diseases (I2MC), University Hospital of Toulouse, INSERM, Toulouse, France
| | - Maria Teresa Pellecchia
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Paolo Barone
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Maria Claudia Russillo
- Neuroscience Section, Department of Medicine, Surgery and Dentistry "Scuola Medica Salernitana", University of Salerno, Salerno, Italy
| | - Juan Marín-Lahoz
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain; Servicio de Neurología, Hospital Universitario Miguel Servet, Zaragoza, Spain
| | - Jaime Kulisevsky
- Movement Disorders Unit, Neurology Department, Hospital de la Santa Creu i Sant Pau, Barcelona, Spain; Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Soraya Torres
- Institut d'Investigacions Biomèdiques Sant Pau (IIB-Sant Pau), Centro de Investigación en Red Enfermedades Neurodegenerativas (CIBERNED), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Pablo Mir
- Unidad de Trastornos del Movimiento Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain; Centro de Investigación Biomédica en Red sobre Enfermedades Neurodegenerativas, Madrid, Spain; Departamento de Medicina Facultad de Medicina, Universidad de Sevilla, Seville, Spain
| | - Maria Teresa Periñán
- Unidad de Trastornos del Movimiento Servicio de Neurología y Neurofisiología Clínica, Instituto de Biomedicina de Sevilla Hospital Universitario Virgen del Rocío, Universidad de Sevilla, Seville, Spain; Centre for Preventive Neurology, Wolfson Institute of Population Health, Queen Mary University, London, UK
| | - Christos Proukakis
- Department of Clinical and Movement Neurosciences, University College London Queen Square Institute of Neurology, London, UK
| | - Viorica Chelban
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Lesley Wu
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK
| | - Yee Y Goh
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK
| | - Laura Parkkinen
- Nuffield Department of Clinical Neurosciences, Oxford Parkinson's Disease Centre, University of Oxford, Oxford, UK
| | - Michele T Hu
- Nuffield Department of Clinical Neurosciences, John Radcliffe Hospital, University of Oxford, Oxford, UK
| | - Christopher Kobylecki
- Department of Neurology, Northern Care Alliance NHS Foundation Trust, Manchester Academic Health Sciences Centre, The University of Manchester, Manchester, UK
| | - Jennifer A Saxon
- Cerebral Function Unit, Manchester Centre for Clinical Neurosciences, Salfort, UK; Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Sara Rollinson
- Division of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester, UK
| | - Emily Garland
- Autonomic Dysfunction Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Italo Biaggioni
- Autonomic Dysfunction Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Irene Litvan
- Department of Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Ileana Rubio
- Department of Neurosciences, University of California, San Diego, San Diego, CA, USA
| | - Roy N Alcalay
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA; Neurological Institute, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Kimberly T Kwei
- Department of Neurology, Columbia University Irving Medical Center, New York, NY, USA
| | - Steven J Lubbe
- Ken and Ruth Davee Department of Neurology and Simpson Querrey Center for Neurogenetics, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Qinwen Mao
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Department of Pathology, University of Utah School of Medicine, Salt Lake City, UT, USA
| | - Margaret E Flanagan
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA; Glenn Biggs Institute for Alzheimer's and Neurodegenerative Diseases, UT Health San Antonio, San Antonio, TX, USA; Department of Pathology, UT Health San Antonio, San Antonio, TX, USA
| | - Rudolph J Castellani
- Mesulam Center for Cognitive Neurology and Alzheimer's Disease, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Vikram Khurana
- Ann Romney Center for Neurologic Disease, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Broad Institute of MIT and Harvard, Cambridge, MA, USA; Harvard Stem Cell Institute, Cambridge, MA, USA
| | - Alain Ndayisaba
- Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria; Ann Romney Center for Neurologic Disease, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Andrea Calvo
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Gabriele Mora
- Istituti Clinici Scientifici Maugeri, IRCCS, Milan, Italy
| | - Antonio Canosa
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy
| | - Gianluca Floris
- Department of Neurology, University Hospital of Cagliari, Cagliari, Italy
| | - Ryan C Bohannan
- Department of Neurobiology and Behavior, University of California, Irvine, Irvine, CA, USA
| | - Anni Moore
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | | | - Jose-Alberto Palma
- Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Horacio Kaufmann
- Department of Neurology, New York University School of Medicine, New York, NY, USA
| | - Changyoun Kim
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Michiyo Iba
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Eliezer Masliah
- Molecular Neuropathology Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Ted M Dawson
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA; Neuroregeneration and Stem Cell Programs, Institute of Cell Engineering, Johns Hopkins University Medical Center, Baltimore, MD, USA; Department of Pharmacology and Molecular Science, Johns Hopkins University Medical Center, Baltimore, MD, USA; Solomon H. Snyder Department of Neuroscience, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Liana S Rosenthal
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Alexander Pantelyat
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Marilyn S Albert
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Olga Pletnikova
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA; Department of Pathology and Anatomical Sciences, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA
| | - Juan C Troncoso
- Department of Pathology (Neuropathology), Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Jon Infante
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain
| | - Carmen Lage
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain
| | - Pascual Sánchez-Juan
- Neurology Service, University Hospital Marqués de Valdecilla-IDIVAL-UC-CIBERNED, Santander, Spain; Alzheimer's Centre Reina Sofia-CIEN Foundation-ISCIII, Madrid, Spain
| | - Geidy E Serrano
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Thomas G Beach
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ, USA
| | - Pau Pastor
- Genomics and Transcriptomics of Synucleinopathies, Neurosciences, The Germans Trias i Pujol Research Institute (IGTP), Badalona, Barcelona, Spain; Unit of Neurodegenerative Diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
| | - Huw R Morris
- Department of Clinical and Movement Neuroscience, UCL Queen Square Institute of Neurology, University College London, London, UK
| | - Diego Albani
- Department of Neuroscience, Istituto di Ricerche Farmacologiche Mario Negri IRCCS, Milan, Italy
| | - Jordi Clarimon
- Sant Pau Biomedical Research Institute, Hospital de la Santa Creu i Sant Pau, Universitat Autònoma de Barcelona, Barcelona, Spain; The Network Center for Biomedical Research in Neurodegenerative Diseases (CIBERNED), Madrid, Spain
| | - Gregor K Wenning
- Autonomic Unit - Division of Neurobiology, Department of Neurology, Medical University of Innsbruck, Innsbruck, Austria
| | - John A Hardy
- Department of Neurodegenerative Disease, UCL Queen Square Institute of Neurology, University College London, London, UK; UK Dementia Research Institute of UCL, UCL Institute of Neurology, University College London, London, UK; Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, University College London, London, UK; UCL Movement Disorders Centre, University College London, London, UK; Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | - Mina Ryten
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK; Great Ormond Street Institute of Child Health, Genetics and Genomic Medicine, University College London, London, UK
| | - Eric Topol
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Ali Torkamani
- Scripps Research Translational Institute, Scripps Research, La Jolla, CA, USA
| | - Adriano Chiò
- "Rita Levi Montalcini" Department of Neuroscience, University of Turin, Turin, Italy; Institute of Cognitive Sciences and Technologies, C.N.R., Rome, Italy; Azienda Ospedaliero Universitaria Città della Salute e della Scienza, Turin, Italy
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - Philip L De Jager
- Center for Translational & Computational Neuroimmunology, Department of Neurology, Columbia University Irving Medical Center and the Taub Institute for Research on Alzheimer's Disease and the Aging Brain, New York, NY, USA
| | - Philip A Low
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | | | | | | | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA; RNA Therapeutics Laboratory, Therapeutics Development Branch, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - J Raphael Gibbs
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Clifton L Dalgard
- Department of Anatomy, Physiology and Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic, Jacksonville, FL, USA; Department of Clinical Genomics, Mayo Clinic, Jacksonville, FL, USA
| | - Henry Houlden
- Department of Neuromuscular Diseases, University College London Queen Square Institute of Neurology, London, UK; The National Hospital for Neurology and Neurosurgery, London, UK
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA; Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA.
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8
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Kizilkaya HS, Sørensen KV, Madsen JS, Lindquist P, Douros JD, Bork-Jensen J, Berghella A, Gerlach PA, Gasbjerg LS, Mokrosiński J, Mowery SA, Knerr PJ, Finan B, Campbell JE, D'Alessio DA, Perez-Tilve D, Faas F, Mathiasen S, Rungby J, Sørensen HT, Vaag A, Nielsen JS, Holm JC, Lauenborg J, Damm P, Pedersen O, Linneberg A, Hartmann B, Holst JJ, Hansen T, Wright SC, Lauschke VM, Grarup N, Hauser AS, Rosenkilde MM. Characterization of genetic variants of GIPR reveals a contribution of β-arrestin to metabolic phenotypes. Nat Metab 2024; 6:1268-1281. [PMID: 38871982 PMCID: PMC11272584 DOI: 10.1038/s42255-024-01061-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/18/2023] [Accepted: 05/02/2024] [Indexed: 06/15/2024]
Abstract
Incretin-based therapies are highly successful in combatting obesity and type 2 diabetes1. Yet both activation and inhibition of the glucose-dependent insulinotropic polypeptide (GIP) receptor (GIPR) in combination with glucagon-like peptide-1 (GLP-1) receptor (GLP-1R) activation have resulted in similar clinical outcomes, as demonstrated by the GIPR-GLP-1R co-agonist tirzepatide2 and AMG-133 (ref. 3) combining GIPR antagonism with GLP-1R agonism. This underlines the importance of a better understanding of the GIP system. Here we show the necessity of β-arrestin recruitment for GIPR function, by combining in vitro pharmacological characterization of 47 GIPR variants with burden testing of clinical phenotypes and in vivo studies. Burden testing of variants with distinct ligand-binding capacity, Gs activation (cyclic adenosine monophosphate production) and β-arrestin 2 recruitment and internalization shows that unlike variants solely impaired in Gs signalling, variants impaired in both Gs and β-arrestin 2 recruitment contribute to lower adiposity-related traits. Endosomal Gs-mediated signalling of the variants shows a β-arrestin dependency and genetic ablation of β-arrestin 2 impairs cyclic adenosine monophosphate production and decreases GIP efficacy on glucose control in male mice. This study highlights a crucial impact of β-arrestins in regulating GIPR signalling and overall preservation of biological activity that may facilitate new developments in therapeutic targeting of the GIPR system.
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Affiliation(s)
- Hüsün S Kizilkaya
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Kimmie V Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jakob S Madsen
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
| | - Peter Lindquist
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jonathan D Douros
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA
- Indiana Biosciences Research Institute Indianapolis, Indianapolis, IN, USA
| | - Jette Bork-Jensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Alessandro Berghella
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark
- Department of Bioscience and Agro-Food and Environmental Technology, University of Teramo, Teramo, Italy
| | - Peter A Gerlach
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Lærke S Gasbjerg
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | | | - Stephanie A Mowery
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA
- Indiana Biosciences Research Institute Indianapolis, Indianapolis, IN, USA
| | - Patrick J Knerr
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA
- Indiana Biosciences Research Institute Indianapolis, Indianapolis, IN, USA
| | - Brian Finan
- Novo Nordisk Research Center Indianapolis, Indianapolis, IN, USA
- Eli Lilly and Company, Indianapolis, IN, USA
| | - Jonathan E Campbell
- Duke Molecular Physiology Institute, Duke University Durham, Durham, NC, USA
| | - David A D'Alessio
- Duke Molecular Physiology Institute, Duke University Durham, Durham, NC, USA
| | - Diego Perez-Tilve
- Department of Pharmacology and Systems Physiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA
| | - Felix Faas
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Signe Mathiasen
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jørgen Rungby
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Steno Diabetes Center Copenhagen, Herlev, Denmark
| | - Henrik T Sørensen
- Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark
- Department of Epidemiology, Boston University, Boston, MA, USA
| | - Allan Vaag
- Steno Diabetes Center Copenhagen, Herlev, Denmark
- Department of Clinical Sciences, Lund University Diabetes Center, Lund University, Malmö, Sweden
| | - Jens S Nielsen
- Steno Diabetes Center Odense, Odense University Hospital, Odense, Denmark
- Department of Clinical Research, University of Southern Denmark, Odense, Denmark
| | - Jens-Christian Holm
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- The Children's Obesity Clinic, accredited European Centre for Obesity Management, Department of Pediatrics, Holbæk Hospital, Holbæk, Denmark
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jeannet Lauenborg
- Department of Obstetrics and Gynecology, Copenhagen University Hospital Herlev, Herlev, Denmark
| | - Peter Damm
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Pregnant Women with Diabetes, Rigshospitalet, Copenhagen, Denmark
- Department of Obstetrics, Rigshospitalet, Copenhagen, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Metabolic Research, Department of Medicine, Gentofte Hospital, Copenhagen, Denmark
| | - Allan Linneberg
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Research and Prevention, Copenhagen University Hospital - Bispebjerg and Frederiksberg, Copenhagen, Denmark
| | - Bolette Hartmann
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Jens J Holst
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Torben Hansen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Shane C Wright
- Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
| | - Volker M Lauschke
- Department of Physiology & Pharmacology, Karolinska Institutet, Stockholm, Sweden
- Dr Margarete Fischer-Bosch Institute of Clinical Pharmacology, Stuttgart, Germany
- University of Tübingen, Tübingen, Germany
| | - Niels Grarup
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
| | - Alexander S Hauser
- Department of Drug Design and Pharmacology, University of Copenhagen, Copenhagen, Denmark.
| | - Mette M Rosenkilde
- Department of Biomedical Sciences, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark.
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Marriott H, Spargo TP, Al Khleifat A, Andersen PM, Başak NA, Cooper‐Knock J, Corcia P, Couratier P, de Carvalho M, Drory V, Gotkine M, Landers JE, McLaughlin R, Pardina JSM, Morrison KE, Pinto S, Shaw CE, Shaw PJ, Silani V, Ticozzi N, van Damme P, van den Berg LH, Vourc'h P, Weber M, Veldink JH, Dobson RJ, Schwab P, Al‐Chalabi A, Iacoangeli A. Mutations in the tail and rod domains of the neurofilament heavy-chain gene increase the risk of ALS. Ann Clin Transl Neurol 2024; 11:1775-1786. [PMID: 38775181 PMCID: PMC11251467 DOI: 10.1002/acn3.52083] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2024] [Revised: 04/23/2024] [Accepted: 04/24/2024] [Indexed: 07/17/2024] Open
Abstract
OBJECTIVE Neurofilament heavy-chain gene (NEFH) variants are associated with multiple neurodegenerative diseases, however, their relationship with ALS has not been robustly explored. Still, NEFH is commonly included in genetic screening panels worldwide. We therefore aimed to determine if NEFH variants modify ALS risk. METHODS Genetic data of 11,130 people with ALS and 7,416 controls from the literature and Project MinE were analysed. We performed meta-analyses of published case-control studies reporting NEFH variants, and variant analysis of NEFH in Project MinE whole-genome sequencing data. RESULTS Fixed-effects meta-analysis found that rare (MAF <1%) missense variants in the tail domain of NEFH increase ALS risk (OR 4.55, 95% CI 2.13-9.71, p < 0.0001). In Project MinE, ultrarare NEFH variants increased ALS risk (OR 1.37 95% CI 1.14-1.63, p = 0.0007), with rod domain variants (mostly intronic) appearing to drive the association (OR 1.45 95% CI 1.18-1.77, pMadsen-Browning = 0.0007, pSKAT-O = 0.003). While in the tail domain, ultrarare (MAF <0.1%) pathogenic missense variants were also associated with higher risk of ALS (OR 1.94, 95% CI 0.86-4.37, pMadsen-Browning = 0.039), supporting the meta-analysis results. Finally, several tail in-frame deletions were also found to affect disease risk, however, both protective and pathogenic deletions were found in this domain, highlighting an intricate architecture that requires further investigation. INTERPRETATION We showed that NEFH tail missense and in-frame deletion variants, and intronic rod variants are risk factors for ALS. However, they are not variants of large effect, and their functional impact needs to be clarified in further studies. Therefore, their inclusion in routine genetic screening panels should be reconsidered.
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Affiliation(s)
- Heather Marriott
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
| | - Thomas P. Spargo
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
| | - Ahmad Al Khleifat
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
| | - Peter M Andersen
- Department of Clinical ScienceUmeå UniversityUmeåSE‐901 85Sweden
| | - Nazli A. Başak
- Translational Medicine Research Center, NDAL, School of MedicineKoc UniversityIstanbul34450Turkey
| | - Johnathan Cooper‐Knock
- Sheffield Institute for Translational Neuroscience (SITraN)University of SheffieldSheffieldS10 2HQUK
| | - Philippe Corcia
- UMR 1253, Université de Tours, InsermTours37044France
- Centre de référence sur la SLA, CHU de ToursTours37044France
| | - Philippe Couratier
- Centre de référence sur la SLA, CHRU de LimogesLimogesFrance
- UMR 1094, Université de Limoges, InsermLimoges87025France
| | - Mamede de Carvalho
- Instituto de Fisiologia, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de MedicinaUniversidade de LisboaLisbon1649‐028Portugal
| | - Vivian Drory
- Department of NeurologyTel‐Aviv Sourasky Medical CentreTel‐Aviv64239Israel
- Sackler Faculty of MedicineTel‐Aviv UniversityTel‐Aviv6997801Israel
| | - Marc Gotkine
- Faculty of MedicineHebrew University of JerusalemJerusalem91904Israel
- Agnes Ginges Center for Human Neurogenetics, Department of NeurologyHadassah Medical CenterJerusalem91120Israel
| | - John E. Landers
- Department of NeurologyUniversity of Massachusetts Medical SchoolWorcesterMassachusetts01655USA
| | - Russell McLaughlin
- Complex Trait Genomics LaboratorySmurfit Institute of Genetics, Trinity College DublinDublinD02 PN40Ireland
| | | | - Karen E. Morrison
- School of Medicine, Dentistry and Biomedical SciencesQueen's University BelfastBelfastBT9 7BLUK
| | - Susana Pinto
- Instituto de Fisiologia, Instituto de Medicina Molecular João Lobo Antunes, Faculdade de MedicinaUniversidade de LisboaLisbon1649‐028Portugal
| | - Christopher E. Shaw
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
| | - Pamela J. Shaw
- Sheffield Institute for Translational Neuroscience (SITraN)University of SheffieldSheffieldS10 2HQUK
| | - Vincenzo Silani
- Department of Neurology‐Stroke Unit and Laboratory of NeuroscienceIstituto Auxologico Italiano, IRCCSMilan20149Italy
- Department of Pathophysiology and Transplantation, “Dino Ferrari” CenterUniversità degli Studi di MilanoMilan20122Italy
| | - Nicola Ticozzi
- Department of Neurology‐Stroke Unit and Laboratory of NeuroscienceIstituto Auxologico Italiano, IRCCSMilan20149Italy
- Department of Pathophysiology and Transplantation, “Dino Ferrari” CenterUniversità degli Studi di MilanoMilan20122Italy
| | - Philip van Damme
- Experimental Neurology and Leuven Brain Institute (LBI)Leuven3000Belgium
- VIB, Center for Brain and Disease ResearchLeuven3000Belgium
- Department of NeurologyUniversity Hospitals LeuvenLeuven3000Belgium
| | - Leonard H. van den Berg
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical CenterUtrecht3584 CXNetherlands
| | - Patrick Vourc'h
- UMR 1253, Université de Tours, InsermTours37044France
- Service de Biochimie et Biologie molécularie, CHU de ToursTours37044France
| | - Markus Weber
- Neuromuscular Diseases Unit/ALS ClinicKantonsspital St. GallenSt. Gallen9007Switzerland
| | - Jan H. Veldink
- Department of Neurology, UMC Utrecht Brain CenterUniversity Medical CenterUtrecht3584 CXNetherlands
| | - Richard J. Dobson
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College LondonLondonUK
- Institute of Health Informatics, University College LondonLondonNW1 2DAUK
- NIHR Biomedical Research Centre at University College London Hospitals NHS Foundation TrustLondonUK
| | - Patrick Schwab
- GlaxoSmithKline, Artificial Intelligence and Machine LearningLondonUK
| | - Ammar Al‐Chalabi
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- King's College HospitalLondonSE5 9RSUK
| | - Alfredo Iacoangeli
- Department of Basic and Clinical NeuroscienceMaurice Wohl Clinical Neuroscience Institute, Institute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- Department of Biostatistics and Health InformaticsInstitute of Psychiatry, Psychology and Neuroscience, King's College LondonLondonSE5 8AFUK
- NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College LondonLondonUK
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10
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Senkevich K, Parlar SC, Chantereault C, Yu E, Ahmad J, Ruskey JA, Asayesh F, Spiegelman D, Waters C, Monchi O, Dauvilliers Y, Dupré N, Miliukhina I, Timofeeva A, Emelyanov A, Pchelina S, Greenbaum L, Hassin-Baer S, Alcalay RN, Gan-Or Z. Are rare heterozygous SYNJ1 variants associated with Parkinson's disease? MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.29.24307986. [PMID: 38853950 PMCID: PMC11160829 DOI: 10.1101/2024.05.29.24307986] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2024]
Abstract
Previous studies have suggested that rare biallelic SYNJ1 mutations may cause autosomal recessive parkinsonism and Parkinson's disease (PD). Our study explored the impact of rare SYNJ1 variants in non-familial settings, including 8,165 PD cases, 818 early-onset PD (EOPD, <50 years) and 70,363 controls. Burden meta-analysis using optimized sequence Kernel association test (SKAT-O) revealed an association between rare nonsynonymous variants in the Sac1 SYNJ1 domain and PD (Pfdr=0.040). Additionally, a meta-analysis focusing on patients with EOPD demonstrated an association between all rare SYNJ1 variants and PD (Pfdr=0.029). Rare SYNJ1 variants may be associated with sporadic PD, and more specifically with EOPD.
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Affiliation(s)
- Konstantin Senkevich
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Sitki Cem Parlar
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Cloe Chantereault
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Eric Yu
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Jamil Ahmad
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
| | - Jennifer A. Ruskey
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
| | - Farnaz Asayesh
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
| | - Dan Spiegelman
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
| | - Cheryl Waters
- Department of Neurology, College of Physicians and Surgeons, Columbia University Medical Center, NY, USA
| | - Oury Monchi
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
- Département de radiologie, radio-oncologie et médecine nucléaire, Université de Montréal, Montréal, QC, Canada
- Centre de recherche de l’Institut universitaire de gériatrie de Montréal, Montréal, QC, Canada
| | - Yves Dauvilliers
- National Reference Center for Narcolepsy, Sleep Unit, Department of Neurology, Guide-Chauliac Hospital, CHU Montpellier, University of Montpellier, Montpellier, France
| | - Nicolas Dupré
- Neuroscience axis, CHU de Québec-Université Laval, Québec, QC, Canada
- Department of Medicine, Faculty of Medicine, Université Laval, Quebec City, QC, Canada
| | | | - Alla Timofeeva
- First Pavlov State Medical University of St. Petersburg, Saint-Petersburg, Russia
| | - Anton Emelyanov
- First Pavlov State Medical University of St. Petersburg, Saint-Petersburg, Russia
| | - Sofya Pchelina
- First Pavlov State Medical University of St. Petersburg, Saint-Petersburg, Russia
| | - Lior Greenbaum
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Danek Gertner Institute of Human Genetics, Sheba Medical Center, Tel Hashomer, Israel
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
| | - Sharon Hassin-Baer
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- The Joseph Sagol Neuroscience Center, Sheba Medical Center, Tel Hashomer, Israel
- The Movement Disorders Institute, Department of Neurology, Sheba Medical Center, Tel Hashomer, Israel
| | - Roy N. Alcalay
- Department of Neurology, College of Physicians and Surgeons, Columbia University Medical Center, NY, USA
- Faculty of Medicine, Tel Aviv University, Tel Aviv, Israel
- Division of Movement Disorders, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel
| | - Ziv Gan-Or
- The Neuro (Montreal Neurological Institute-Hospital), McGill University, Montreal, Quebec, Canada
- Department of Neurology and neurosurgery, McGill University, Montréal, QC, Canada, Canada
- Department of Human Genetics, McGill University, Montréal, QC, Canada
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11
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Chen A, Zhao X, Wen J, Zhao X, Wang G, Zhang X, Ren X, Zhang Y, Cheng X, Yu X, Mei X, Wang H, Guo M, Jiang X, Wei G, Wang X, Jiang R, Guo X, Ning Z, Qu L. Genetic parameter estimation and molecular foundation of chicken beak shape. Poult Sci 2024; 103:103666. [PMID: 38703454 PMCID: PMC11087718 DOI: 10.1016/j.psj.2024.103666] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2024] [Revised: 03/02/2024] [Accepted: 03/12/2024] [Indexed: 05/06/2024] Open
Abstract
The bird beak is mainly functioned as feeding and attacking, and its shape has extremely important significance for survival and reproduction. In chickens, since beak shape could lead to some disadvantages including pecking and waste of feed, it is important to understand the inheritance of chicken beak shape. In the present study, we firstly established 4 indicators to describe the chicken beak shapes, including upper beak length (UL), lower beak length (LL), distance between upper and lower beak tips (DB) and upper beak curvature (BC). And then, we measured the 4 beak shape indicators as well as some production traits including body weight (BW), shank length (SL), egg weight (EW), eggshell strength (ES) of a layer breed, Rhode Island Red (RIR), in order to estimate genetic parameters of chicken beak shape. The heritabilities of UL and LL were 0.41 and 0.37, and the heritabilities of DB and BC were 0.22 and 0.21, indicating that beak shape was a highly or mediumly heritable. There were significant positive genetic and phenotypic correlations among UL, LL, and DB. And UL was positively correlated with body weight (BW18) and shank length (SL18) at 18 weeks of age in genetics, and DB was positively correlated with BC in terms of genetics and phenotype. We also found that layers of chicken cages played a role on beak shape, which could be attributed to the difference of lightness in different cage layers. By a genome-wide association study (GWAS) for the chicken UL, we identified 9 significant candidate genes associated with UL in RIR. For the variants with low minor allele frequencies (MAF <0.01) and outside of high linkage disequilibrium (LD) regions, we also conducted rare variant association studies (RVA) and GWAS to find the association between genotype and phenotype. We also analyzed transcriptomic data from multiple tissues of chicken embryos and revealed that all of the 9 genes were highly expressed in beak of chicken embryos, indicating their potential function for beak development. Our results provided the genetic foundation of chicken beak shape, which could help chicken breeding on beak related traits.
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Affiliation(s)
- Anqi Chen
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Zhao
- Xingrui Agricultural Stock Breeding, Baoding 072550, Hebei Province, China
| | - Junhui Wen
- Institute of Animal Husbandry and Veterinary Medicine, Beijing Academy of Agricultural and Forestry Sciences, Beijing 100097, China
| | - Xiurong Zhao
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Gang Wang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xinye Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xufang Ren
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Yalan Zhang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xue Cheng
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaofan Yu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaohan Mei
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Huie Wang
- Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China
| | - Menghan Guo
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Xiaoyu Jiang
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Guozhen Wei
- Qingliu Animal Husbandry, Veterinary and Aquatic Products Center, Sanming, China
| | - Xue Wang
- VVBK Animal Medical Diagnostic Technology (Beijing) Co., Ltd, Beijing, China
| | - Runshen Jiang
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Xing Guo
- College of Animal Science and Technology, Anhui Agricultural University, Hefei 230036, China
| | - Zhonghua Ning
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China
| | - Lujiang Qu
- National Engineering Laboratory for Animal Breeding, College of Animal Science and Technology, China Agricultural University, Beijing 100193, China; Xinjiang Production and Construction Corps, Key Laboratory of Protection and Utilization of Biological Resources in Tarim Basin, Tarim University, Alar 843300, China.
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12
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Senkevich K, Liu L, Alvarado CX, Leonard HL, Nalls MA, Gan-Or Z. Lack of genetic evidence for NLRP3-inflammasome involvement in Parkinson's disease pathogenesis. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.09.20.23295790. [PMID: 37886468 PMCID: PMC10602039 DOI: 10.1101/2023.09.20.23295790] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/28/2023]
Abstract
Activation of the NLRP3-inflammasome has been implicated in Parkinson's disease based on in vitro and in vivo studies. Clinical trials targeting the NLRP3-inflammasome in Parkinson's disease are ongoing. However, the evidence supporting NLRP3's involvement in Parkinson's disease from human genetics data is limited. In this study, we conducted analyses of common and rare variants in NLRP3-inflammasome related genes in Parkinson's disease cohorts. We performed pathway-specific analyses using polygenic risk scores and studied potential causal associations using Mendelian randomization with the NLRP3 components and the cytokines IL-1β and IL-18. Our findings showed no associations of common or rare variants, nor of the pathway polygenic risk score with Parkinson's disease. Mendelian randomization suggests that altering the expression of the NLRP3-inflammasome, IL-1β or IL-18, does not affect Parkinson's disease risk or progression. Therefore, our results do not support a role for the NLRP3-inflammasome in Parkinson's disease pathogenesis or as a target for drug development.
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13
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Pérez-Gutiérrez AM, Carmona R, Loucera C, Cervilla JA, Gutiérrez B, Molina E, Lopez-Lopez D, Pérez-Florido J, Zarza-Rebollo JA, López-Isac E, Dopazo J, Martínez-González LJ, Rivera M. Mutational landscape of risk variants in comorbid depression and obesity: a next-generation sequencing approach. Mol Psychiatry 2024:10.1038/s41380-024-02609-2. [PMID: 38806690 DOI: 10.1038/s41380-024-02609-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 05/03/2024] [Accepted: 05/13/2024] [Indexed: 05/30/2024]
Abstract
Major depression (MD) and obesity are complex genetic disorders that are frequently comorbid. However, the study of both diseases concurrently remains poorly addressed and therefore the underlying genetic mechanisms involved in this comorbidity remain largely unknown. Here we examine the contribution of common and rare variants to this comorbidity through a next-generation sequencing (NGS) approach. Specific genomic regions of interest in MD and obesity were sequenced in a group of 654 individuals from the PISMA-ep epidemiological study. We obtained variants across the entire frequency spectrum and assessed their association with comorbid MD and obesity, both at variant and gene levels. We identified 55 independent common variants and a burden of rare variants in 4 genes (PARK2, FGF21, HIST1H3D and RSRC1) associated with the comorbid phenotype. Follow-up analyses revealed significantly enriched gene-sets associated with biological processes and pathways involved in metabolic dysregulation, hormone signaling and cell cycle regulation. Our results suggest that, while risk variants specific to the comorbid phenotype have been identified, the genes functionally impacted by the risk variants share cell biological processes and signaling pathways with MD and obesity phenotypes separately. To the best of our knowledge, this is the first study involving a targeted sequencing approach toward the study of the comorbid MD and obesity. The framework presented here allowed a deep characterization of the genetics of the co-occurring MD and obesity, revealing insights into the mutational and functional profile that underlies this comorbidity and contributing to a better understanding of the relationship between these two disabling disorders.
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Affiliation(s)
- Ana M Pérez-Gutiérrez
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
| | - Rosario Carmona
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U715, Seville, Spain
| | - Carlos Loucera
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
| | - Jorge A Cervilla
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
- Department of Psychiatry, Faculty of Medicine, University of Granada, Granada, Spain
| | - Blanca Gutiérrez
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
- Department of Psychiatry, Faculty of Medicine, University of Granada, Granada, Spain
| | - Esther Molina
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
- Department of Nursing, Faculty of Health Sciences, University of Granada, Granada, Spain
| | - Daniel Lopez-Lopez
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
| | - Javier Pérez-Florido
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U715, Seville, Spain
| | - Juan Antonio Zarza-Rebollo
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
| | - Elena López-Isac
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain
| | - Joaquín Dopazo
- Platform for Computational Medicine, Andalusian Public Foundation Progress and Health-FPS, Seville, Spain
- Computational Systems Medicine, Institute of Biomedicine of Seville (IBIS), Hospital Virgen del Rocío, Seville, Spain
- Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER-ISCIII), U715, Seville, Spain
| | - Luis Javier Martínez-González
- Genomics Unit, Pfizer-University of Granada-Junta de Andalucía Centre for Genomics and Oncological Research (GENYO), Granada, Spain
| | - Margarita Rivera
- Department of Biochemistry and Molecular Biology II, Faculty of Pharmacy, University of Granada, Granada, Spain.
- Institute of Neurosciences "Federico Olóriz", Biomedical Research Center (CIBM), University of Granada, Granada, Spain.
- Instituto de Investigación Biosanitaria, Ibs Granada, Granada, Spain.
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14
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Ali A, Milman S, Weiss EF, Gao T, Napolioni V, Barzilai N, Zhang ZD, Lin JR. Rare genetic coding variants associated with age-related episodic memory decline implicate distinct memory pathologies in the hippocampus. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.05.21.24307692. [PMID: 38826255 PMCID: PMC11142267 DOI: 10.1101/2024.05.21.24307692] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Background Approximately 40% of people aged 65 or older experience memory loss, particularly in episodic memory. Identifying the genetic basis of episodic memory decline is crucial for uncovering its underlying causes. Methods We investigated common and rare genetic variants associated with episodic memory decline in 742 (632 for rare variants) Ashkenazi Jewish individuals (mean age 75) from the LonGenity study. All-atom MD simulations were performed to uncover mechanistic insights underlying rare variants associated with episodic memory decline. Results In addition to the common polygenic risk of Alzheimer's Disease (AD), we identified and replicated rare variant association in ITSN1 and CRHR2 . Structural analyses revealed distinct memory pathologies mediated by interfacial rare coding variants such as impaired receptor activation of corticotropin releasing hormone and dysregulated L-serine synthesis. Discussion Our study uncovers novel risk loci for episodic memory decline. The identified underlying mechanisms point toward heterogeneous memory pathologies mediated by rare coding variants.
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15
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Kars ME, Wu Y, Stenson PD, Cooper DN, Burisch J, Peter I, Itan Y. The landscape of rare genetic variation associated with inflammatory bowel disease and Parkinson's disease comorbidity. Genome Med 2024; 16:66. [PMID: 38741190 PMCID: PMC11092054 DOI: 10.1186/s13073-024-01335-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2024] [Accepted: 04/16/2024] [Indexed: 05/16/2024] Open
Abstract
BACKGROUND Inflammatory bowel disease (IBD) and Parkinson's disease (PD) are chronic disorders that have been suggested to share common pathophysiological processes. LRRK2 has been implicated as playing a role in both diseases. Exploring the genetic basis of the IBD-PD comorbidity through studying high-impact rare genetic variants can facilitate the identification of the novel shared genetic factors underlying this comorbidity. METHODS We analyzed whole exomes from the BioMe BioBank and UK Biobank, and whole genomes from a cohort of 67 European patients diagnosed with both IBD and PD to examine the effects of LRRK2 missense variants on IBD, PD and their co-occurrence (IBD-PD). We performed optimized sequence kernel association test (SKAT-O) and network-based heterogeneity clustering (NHC) analyses using high-impact rare variants in the IBD-PD cohort to identify novel candidate genes, which we further prioritized by biological relatedness approaches. We conducted phenome-wide association studies (PheWAS) employing BioMe BioBank and UK Biobank whole exomes to estimate the genetic relevance of the 14 prioritized genes to IBD-PD. RESULTS The analysis of LRRK2 missense variants revealed significant associations of the G2019S and N2081D variants with IBD-PD in addition to several other variants as potential contributors to increased or decreased IBD-PD risk. SKAT-O identified two significant genes, LRRK2 and IL10RA, and NHC identified 6 significant gene clusters that are biologically relevant to IBD-PD. We observed prominent overlaps between the enriched pathways in the known IBD, PD, and candidate IBD-PD gene sets. Additionally, we detected significantly enriched pathways unique to the IBD-PD, including MAPK signaling, LPS/IL-1 mediated inhibition of RXR function, and NAD signaling. Fourteen final candidate IBD-PD genes were prioritized by biological relatedness methods. The biological importance scores estimated by protein-protein interaction networks and pathway and ontology enrichment analyses indicated the involvement of genes related to immunity, inflammation, and autophagy in IBD-PD. Additionally, PheWAS provided support for the associations of candidate genes with IBD and PD. CONCLUSIONS Our study confirms and uncovers new LRRK2 associations in IBD-PD. The identification of novel inflammation and autophagy-related genes supports and expands previous findings related to IBD-PD pathogenesis, and underscores the significance of therapeutic interventions for reducing systemic inflammation.
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Affiliation(s)
- Meltem Ece Kars
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
| | - Yiming Wu
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA
- College of Life Science, China West Normal University, Nan Chong, Si Chuan, 637009, China
| | - Peter D Stenson
- Institute of Medical Genetics, Cardiff University, Cardiff, CF14 4XN, UK
| | - David N Cooper
- Institute of Medical Genetics, Cardiff University, Cardiff, CF14 4XN, UK
| | - Johan Burisch
- Gastrounit, Medical Division, Copenhagen University Hospital - Amager and Hvidovre, Kettegård Alle 30, Hvidovre, Copenhagen, 2650, Denmark
- Copenhagen Center for Inflammatory Bowel Disease in Children, Adolescents and Adults, Copenhagen University Hospital - Amager and Hvidovre, Kettegård Alle 30, Hvidovre, Copenhagen, 2650, Denmark
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Blegdamsvej 3B, Copenhagen, 2200, Denmark
| | - Inga Peter
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
| | - Yuval Itan
- The Charles Bronfman Institute for Personalized Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
- Mindich Child Health and Development Institute, Icahn School of Medicine at Mount Sinai, New York, NY, 10029, USA.
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16
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Guo H, Urban AE, Wong WH. Prioritizing disease-related rare variants by integrating gene expression data. RESEARCH SQUARE 2024:rs.3.rs-4355589. [PMID: 38766095 PMCID: PMC11100897 DOI: 10.21203/rs.3.rs-4355589/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/22/2024]
Abstract
Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. We also found strong excess of rare variants among the top prioritized genes in diseased patients compared to that in healthy individuals. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.
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17
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Muranishi Y, Kobori Y, Katoh-Fukui Y, Tamaoka S, Hattori A, Osaka A, Okada H, Nakabayashi K, Hata K, Kawai T, Ogata-Kawata H, Iwahata T, Saito K, Kon M, Shinohara N, Fukami M. Systematic molecular analyses for 115 karyotypically normal men with isolated non-obstructive azoospermia. Hum Reprod 2024; 39:1131-1140. [PMID: 38511217 DOI: 10.1093/humrep/deae057] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 02/21/2024] [Indexed: 03/22/2024] Open
Abstract
STUDY QUESTION Do copy-number variations (CNVs) in the azoospermia factor (AZF) regions and monogenic mutations play a major role in the development of isolated (non-syndromic) non-obstructive azoospermia (NOA) in Japanese men with a normal 46, XY karyotype? SUMMARY ANSWER Deleterious CNVs in the AZF regions and damaging sequence variants in eight genes likely constitute at least 8% and approximately 8% of the genetic causes, respectively, while variants in other genes play only a minor role. WHAT IS KNOWN ALREADY Sex chromosomal abnormalities, AZF-linked microdeletions, and monogenic mutations have been implicated in isolated NOA. More than 160 genes have been reported as causative/susceptibility/candidate genes for NOA. STUDY DESIGN, SIZE, DURATION Systematic molecular analyses were conducted for 115 patients with isolated NOA and a normal 46, XY karyotype, who visited our hospital between 2017 and 2021. PARTICIPANTS/MATERIALS, SETTING, METHODS We studied 115 unrelated Japanese patients. AZF-linked CNVs were examined using sequence-tagged PCR and multiplex ligation-dependent probe amplification, and nucleotide variants were screened using whole exome sequencing (WES). An optimized sequence kernel association test (SKAT-O), a gene-based association study using WES data, was performed to identify novel disease-associated genes in the genome. The results were compared to those of previous studies and our in-house control data. MAIN RESULTS AND THE ROLE OF CHANCE Thirteen types of AZF-linked CNVs, including the hitherto unreported gr/gr triplication and partial AZFb deletion, were identified in 63 (54.8%) cases. When the gr/gr deletion, a common polymorphism in Japan, was excluded from data analyses, the total frequency of CNVs was 23/75 (30.7%). This frequency is higher than that of the reference data in Japan and China (11.1% and 14.7%, respectively). Known NOA-causative AZF-linked CNVs were found in nine (7.8%) cases. Rare damaging variants in known causative genes (DMRT1, PLK4, SYCP2, TEX11, and USP26) and hemizygous/multiple-heterozygous damaging variants in known spermatogenesis-associated genes (TAF7L, DNAH2, and DNAH17) were identified in nine cases (7.8% in total). Some patients carried rare damaging variants in multiple genes. SKAT-O detected no genes whose rare damaging variants were significantly accumulated in the patient group. LIMITATIONS, REASONS FOR CAUTION The number of participants was relatively small, and the clinical information of each patient was fragmentary. Moreover, the pathogenicity of identified variants was assessed only by in silico analyses. WIDER IMPLICATIONS OF THE FINDINGS This study showed that various AZF-linked CNVs are present in more than half of Japanese NOA patients. These results broadened the structural variations of AZF-linked CNVs, which should be considered for the molecular diagnosis of spermatogenic failure. Furthermore, the results of this study highlight the etiological heterogeneity and possible oligogenicity of isolated NOA. STUDY FUNDING/COMPETING INTEREST(S) This study was supported by Grants from the Japan Society for the Promotion of Science (21K19283 and 21H0246), the Japan Agency for Medical Research and Development (22ek0109464h0003), the National Center for Child Health and Development, the Canon Foundation, the Japan Endocrine Society, and the Takeda Science Foundation. The results of this study were based on samples and patient data obtained from the International Center for Reproductive Medicine, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan. The authors have no conflicts of interest to disclose. TRIAL REGISTRATION NUMBER N/A.
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Affiliation(s)
- Yuki Muranishi
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
- Department of Renal and Genitourinary Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Yoshitomo Kobori
- International Center for Reproductive Medicine, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Yuko Katoh-Fukui
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Satoshi Tamaoka
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Atsushi Hattori
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Akiyoshi Osaka
- International Center for Reproductive Medicine, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Hiroshi Okada
- International Center for Reproductive Medicine, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Kazuhiko Nakabayashi
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Kenichiro Hata
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Tomoko Kawai
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Hiroko Ogata-Kawata
- Department of Maternal-Fetal Biology, National Research Institute for Child Health and Development, Tokyo, Japan
| | - Toshiyuki Iwahata
- International Center for Reproductive Medicine, Dokkyo Medical University Saitama Medical Center, Koshigaya, Japan
| | - Kazuki Saito
- Department of Comprehensive Reproductive Medicine, Graduate School, Tokyo Medical and Dental University, Tokyo, Japan
| | - Masafumi Kon
- Department of Renal and Genitourinary Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Nobuo Shinohara
- Department of Renal and Genitourinary Surgery, Hokkaido University Graduate School of Medicine, Sapporo, Japan
| | - Maki Fukami
- Department of Molecular Endocrinology, National Research Institute for Child Health and Development, Tokyo, Japan
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18
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Kronzer VL, Sparks JA, Raychaudhuri S, Cerhan JR. Low-frequency and rare genetic variants associated with rheumatoid arthritis risk. Nat Rev Rheumatol 2024; 20:290-300. [PMID: 38538758 DOI: 10.1038/s41584-024-01096-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 02/20/2024] [Indexed: 04/28/2024]
Abstract
Rheumatoid arthritis (RA) has an estimated heritability of nearly 50%, which is particularly high in seropositive RA. HLA alleles account for a large proportion of this heritability, in addition to many common single-nucleotide polymorphisms with smaller individual effects. Low-frequency and rare variants, such as those captured by next-generation sequencing, can also have a large role in heritability in some individuals. Rare variant discovery has informed the development of drugs such as inhibitors of PCSK9 and Janus kinases. Some 34 low-frequency and rare variants are currently associated with RA risk. One variant (19:10352442G>C in TYK2) was identified in five separate studies, and might therefore represent a promising therapeutic target. Following a set of best practices in future studies, including studying diverse populations, using large sample sizes, validating RA and serostatus, replicating findings, adjusting for other variants and performing functional assessment, could help to ensure the relevance of identified variants. Exciting opportunities are now on the horizon for genetics in RA, including larger datasets and consortia, whole-genome sequencing and direct applications of findings in the management, and especially treatment, of RA.
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Affiliation(s)
| | - Jeffrey A Sparks
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Soumya Raychaudhuri
- Division of Rheumatology, Inflammation, and Immunity, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Center for Data Sciences, Brigham and Women's Hospital, Boston, MA, USA
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - James R Cerhan
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
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19
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Fitzsimmons L, Beaulieu-Jones B, Kobren SN. Phenotypic overlap between rare disease patients and variant carriers in a large population cohort informs biological mechanisms. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.04.18.24305861. [PMID: 38699301 PMCID: PMC11064998 DOI: 10.1101/2024.04.18.24305861] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/05/2024]
Abstract
The biological mechanisms giving rise to the extreme symptoms exhibited by rare disease patients are complex, heterogenous, and difficult to discern. Understanding these mechanisms is critical for developing treatments that address the underlying causes of diseases rather than merely the presenting symptoms. Moreover, the same dysfunctional biological mechanisms implicated in rare recessive diseases may also lead to milder and potentially preventable symptoms in carriers in the general population. Seizures are a common, extreme phenotype that can result from diverse and often elusive biological pathways in patients with ultrarare or undiagnosed disorders. In this pilot study, we present an approach to understand the biological pathways leading to seizures in patients from the Undiagnosed Diseases Network (UDN) by analyzing aggregated genotype and phenotype data from the UK Biobank (UKB). Specifically, we look for enriched phenotypes across UKB participants who harbor rare variants in the same gene known or suspected to be causally implicated in a UDN patient's recessively manifesting disorder. Analyzing these milder but related associated phenotypes in UKB participants can provide insight into the disease-causing molecular mechanisms at play in the rare disease UDN patient. We present six vignettes of undiagnosed patients experiencing seizures as part of their recessive genetic condition, and we discuss the potential mechanisms underlying the spectrum of symptoms associated with UKB participants to the severe presentations exhibited by UDN patients. We find that in our set of rare disease patients, seizures may result from diverse, multi-step pathways that involve multiple body systems. Analyses of large-scale population cohorts such as the UKB can be a critical tool to further our understanding of rare diseases in general.
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20
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Luo L, Mehrotra DV, Shen J, Tang ZZ. Multi-trait analysis of gene-by-environment interactions in large-scale genetic studies. Biostatistics 2024; 25:504-520. [PMID: 36897773 DOI: 10.1093/biostatistics/kxad004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2022] [Revised: 02/15/2023] [Accepted: 02/22/2023] [Indexed: 03/11/2023] Open
Abstract
Identifying genotype-by-environment interaction (GEI) is challenging because the GEI analysis generally has low power. Large-scale consortium-based studies are ultimately needed to achieve adequate power for identifying GEI. We introduce Multi-Trait Analysis of Gene-Environment Interactions (MTAGEI), a powerful, robust, and computationally efficient framework to test gene-environment interactions on multiple traits in large data sets, such as the UK Biobank (UKB). To facilitate the meta-analysis of GEI studies in a consortium, MTAGEI efficiently generates summary statistics of genetic associations for multiple traits under different environmental conditions and integrates the summary statistics for GEI analysis. MTAGEI enhances the power of GEI analysis by aggregating GEI signals across multiple traits and variants that would otherwise be difficult to detect individually. MTAGEI achieves robustness by combining complementary tests under a wide spectrum of genetic architectures. We demonstrate the advantages of MTAGEI over existing single-trait-based GEI tests through extensive simulation studies and the analysis of the whole exome sequencing data from the UKB.
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Affiliation(s)
- Lan Luo
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ 07065, USA
| | - Devan V Mehrotra
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., North Wales, PA 19454, USA
| | - Judong Shen
- Biostatistics and Research Decision Sciences, Merck & Co., Inc., Rahway, NJ 07065, USA
| | - Zheng-Zheng Tang
- Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, 330 N Orchard St, Madison, WI 53715, USA
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21
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Zhang S, Moll T, Rubin-Sigler J, Tu S, Li S, Yuan E, Liu M, Butt A, Harvey C, Gornall S, Alhalthli E, Shaw A, Souza CDS, Ferraiuolo L, Hornstein E, Shelkovnikova T, van Dijk CH, Timpanaro IS, Kenna KP, Zeng J, Tsao PS, Shaw PJ, Ichida JK, Cooper-Knock J, Snyder MP. Deep learning modeling of rare noncoding genetic variants in human motor neurons defines CCDC146 as a therapeutic target for ALS. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.03.30.24305115. [PMID: 38633814 PMCID: PMC11023684 DOI: 10.1101/2024.03.30.24305115] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/19/2024]
Abstract
Amyotrophic lateral sclerosis (ALS) is a fatal and incurable neurodegenerative disease caused by the selective and progressive death of motor neurons (MNs). Understanding the genetic and molecular factors influencing ALS survival is crucial for disease management and therapeutics. In this study, we introduce a deep learning-powered genetic analysis framework to link rare noncoding genetic variants to ALS survival. Using data from human induced pluripotent stem cell (iPSC)-derived MNs, this method prioritizes functional noncoding variants using deep learning, links cis-regulatory elements (CREs) to target genes using epigenomics data, and integrates these data through gene-level burden tests to identify survival-modifying variants, CREs, and genes. We apply this approach to analyze 6,715 ALS genomes, and pinpoint four novel rare noncoding variants associated with survival, including chr7:76,009,472:C>T linked to CCDC146. CRISPR-Cas9 editing of this variant increases CCDC146 expression in iPSC-derived MNs and exacerbates ALS-specific phenotypes, including TDP-43 mislocalization. Suppressing CCDC146 with an antisense oligonucleotide (ASO), showing no toxicity, completely rescues ALS-associated survival defects in neurons derived from sporadic ALS patients and from carriers of the ALS-associated G4C2-repeat expansion within C9ORF72. ASO targeting of CCDC146 may be a broadly effective therapeutic approach for ALS. Our framework provides a generic and powerful approach for studying noncoding genetics of complex human diseases.
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Affiliation(s)
- Sai Zhang
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
- J. Crayton Pruitt Family Department of Biomedical Engineering, Genetics Institute, McKnight Brain Institute, University of Florida, Gainesville, FL, USA
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
- These authors contributed equally: Sai Zhang, Tobias Moll, and Jasper Rubin-Sigler
| | - Tobias Moll
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
- These authors contributed equally: Sai Zhang, Tobias Moll, and Jasper Rubin-Sigler
| | - Jasper Rubin-Sigler
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California, Los Angeles, CA, USA
- These authors contributed equally: Sai Zhang, Tobias Moll, and Jasper Rubin-Sigler
| | - Sharon Tu
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California, Los Angeles, CA, USA
| | - Shuya Li
- School of Engineering, Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Enming Yuan
- Institute for Interdisciplinary Information Sciences, Tsinghua University, Beijing, China
| | - Menghui Liu
- Department of Epidemiology, University of Florida, Gainesville, FL, USA
| | - Afreen Butt
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Calum Harvey
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Sarah Gornall
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Elham Alhalthli
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Allan Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Cleide Dos Santos Souza
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Laura Ferraiuolo
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Eran Hornstein
- Department of Molecular Genetics and Department of Molecular Neuroscience, Weizmann Institute of Science, Rehovot, Israel
| | - Tatyana Shelkovnikova
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Charlotte H. van Dijk
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Ilia S. Timpanaro
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Kevin P. Kenna
- Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, The Netherlands
| | - Jianyang Zeng
- School of Engineering, Research Center for Industries of the Future, Westlake University, Hangzhou, Zhejiang, China
| | - Philip S. Tsao
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
| | - Pamela J. Shaw
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Justin K. Ichida
- Department of Stem Cell Biology and Regenerative Medicine, Eli and Edythe Broad Center for Regenerative Medicine and Stem Cell Research, University of Southern California, Los Angeles, CA, USA
| | - Johnathan Cooper-Knock
- Sheffield Institute for Translational Neuroscience (SITraN), University of Sheffield, Sheffield, UK
| | - Michael P. Snyder
- Department of Genetics, Center for Genomics and Personalized Medicine, Stanford University School of Medicine, Stanford, CA, USA
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22
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Peng Q, Gilder DA, Bernert RA, Karriker-Jaffe KJ, Ehlers CL. Genetic factors associated with suicidal behaviors and alcohol use disorders in an American Indian population. Mol Psychiatry 2024; 29:902-913. [PMID: 38177348 PMCID: PMC11176067 DOI: 10.1038/s41380-023-02379-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/18/2023] [Revised: 12/12/2023] [Accepted: 12/13/2023] [Indexed: 01/06/2024]
Abstract
American Indians (AI) demonstrate the highest rates of both suicidal behaviors (SB) and alcohol use disorders (AUD) among all ethnic groups in the US. Rates of suicide and AUD vary substantially between tribal groups and across different geographical regions, underscoring a need to delineate more specific risk and resilience factors. Using data from over 740 AI living within eight contiguous reservations, we assessed genetic risk factors for SB by investigating: (1) possible genetic overlap with AUD, and (2) impacts of rare and low-frequency genomic variants. Suicidal behaviors included lifetime history of suicidal thoughts and acts, including verified suicide deaths, scored using a ranking variable for the SB phenotype (range 0-4). We identified five loci significantly associated with SB and AUD, two of which are intergenic and three intronic on genes AACSP1, ANK1, and FBXO11. Nonsynonymous rare and low-frequency mutations in four genes including SERPINF1 (PEDF), ZNF30, CD34, and SLC5A9, and non-intronic rare and low-frequency mutations in genes OPRD1, HSD17B3 and one lincRNA were significantly associated with SB. One identified pathway related to hypoxia-inducible factor (HIF) regulation, whose 83 nonsynonymous rare and low-frequency variants on 10 genes were significantly linked to SB as well. Four additional genes, and two pathways related to vasopressin-regulated water metabolism and cellular hexose transport, also were strongly associated with SB. This study represents the first investigation of genetic factors for SB in an American Indian population that has high risk for suicide. Our study suggests that bivariate association analysis between comorbid disorders can increase statistical power; and rare and low-frequency variant analysis in a high-risk population enabled by whole-genome sequencing has the potential to identify novel genetic factors. Although such findings may be population specific, rare functional mutations relating to PEDF and HIF regulation align with past reports and suggest a biological mechanism for suicide risk and a potential therapeutic target for intervention.
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Affiliation(s)
- Qian Peng
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA.
| | - David A Gilder
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA
| | - Rebecca A Bernert
- Department of Psychiatry and Behavioral Sciences, Stanford University, Stanford, CA, USA
| | | | - Cindy L Ehlers
- Department of Neuroscience, The Scripps Research Institute, La Jolla, CA, USA
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23
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Guo H, Urban AE, Wong WH. Prioritizing disease-related rare variants by integrating gene expression data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.19.585836. [PMID: 38562756 PMCID: PMC10983955 DOI: 10.1101/2024.03.19.585836] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Abstract
Rare variants, comprising a vast majority of human genetic variations, are likely to have more deleterious impact on human diseases compared to common variants. Here we present carrier statistic, a statistical framework to prioritize disease-related rare variants by integrating gene expression data. By quantifying the impact of rare variants on gene expression, carrier statistic can prioritize those rare variants that have large functional consequence in the diseased patients. Through simulation studies and analyzing real multi-omics dataset, we demonstrated that carrier statistic is applicable in studies with limited sample size (a few hundreds) and achieves substantially higher sensitivity than existing rare variants association methods. Application to Alzheimer's disease reveals 16 rare variants within 15 genes with extreme carrier statistics. The carrier statistic method can be applied to various rare variant types and is adaptable to other omics data modalities, offering a powerful tool for investigating the molecular mechanisms underlying complex diseases.
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Affiliation(s)
- Hanmin Guo
- Department of Statistics, Stanford University, Stanford, California 94305, USA
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Alexander Eckehart Urban
- Department of Psychiatry and Behavioral Sciences, Stanford University School of Medicine, Stanford, California 94305, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California 94305, USA
| | - Wing Hung Wong
- Department of Statistics, Stanford University, Stanford, California 94305, USA
- Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, California 94305, USA
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24
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Zhao C, Su KJ, Wu C, Cao X, Sha Q, Li W, Luo Z, Qin T, Qiu C, Zhao LJ, Liu A, Jiang L, Zhang X, Shen H, Zhou W, Deng HW. Multi-View Variational Autoencoder for Missing Value Imputation in Untargeted Metabolomics. ARXIV 2024:arXiv:2310.07990v2. [PMID: 37873011 PMCID: PMC10593076] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
BACKGROUND Missing data is a common challenge in mass spectrometry-based metabolomics, which can lead to biased and incomplete analyses. The integration of whole-genome sequencing (WGS) data with metabolomics data has emerged as a promising approach to enhance the accuracy of data imputation in metabolomics studies. METHOD In this study, we propose a novel method that leverages the information from WGS data and reference metabolites to impute unknown metabolites. Our approach utilizes a multi-view variational autoencoder to jointly model the burden score, polygenetic risk score (PGS), and linkage disequilibrium (LD) pruned single nucleotide polymorphisms (SNPs) for feature extraction and missing metabolomics data imputation. By learning the latent representations of both omics data, our method can effectively impute missing metabolomics values based on genomic information. RESULTS We evaluate the performance of our method on empirical metabolomics datasets with missing values and demonstrate its superiority compared to conventional imputation techniques. Using 35 template metabolites derived burden scores, PGS and LD-pruned SNPs, the proposed methods achieved R^2-scores > 0.01 for 71.55% of metabolites. CONCLUSION The integration of WGS data in metabolomics imputation not only improves data completeness but also enhances downstream analyses, paving the way for more comprehensive and accurate investigations of metabolic pathways and disease associations. Our findings offer valuable insights into the potential benefits of utilizing WGS data for metabolomics data imputation and underscore the importance of leveraging multi-modal data integration in precision medicine research.
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Koo HJ, Pan W. Are trait-associated genes clustered together in a gene network? Genet Epidemiol 2024. [PMID: 38472164 DOI: 10.1002/gepi.22557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2023] [Revised: 01/25/2024] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
Genome-wide association studies (GWAS) have provided an abundance of information about the genetic variants and their loci that are associated to complex traits and diseases. However, due to linkage disequilibrium (LD) and noncoding regions of loci, it remains a challenge to pinpoint the causal genes. Gene network-based approaches, paired with network diffusion methods, have been proposed to prioritize causal genes and to boost statistical power in GWAS based on the assumption that trait-associated genes are clustered in a gene network. Due to the difficulty in mapping trait-associated variants to genes in GWAS, this assumption has never been directly or rigorously tested empirically. On the other hand, whole exome sequencing (WES) data focuses on the protein-coding regions, directly identifying trait-associated genes. In this study, we tested the assumption by leveraging the recently available exome-based association statistics from the UK Biobank WES data along with two types of networks. We found that almost all trait-associated genes were significantly more proximal to each other than randomly selected genes within both networks. These results support the assumption that trait-associated genes are clustered in gene networks, which can be further leveraged to boost the power of GWAS such as by introducing less stringent p value thresholds.
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Affiliation(s)
- Hyun Jung Koo
- School of Statistics, University of Minnesota, Minneapolis, Minnesota, USA
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
| | - Wei Pan
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, USA
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26
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Oh EY, Han KM, Kim A, Kang Y, Tae WS, Han MR, Ham BJ. Integration of whole-exome sequencing and structural neuroimaging analysis in major depressive disorder: a joint study. Transl Psychiatry 2024; 14:141. [PMID: 38461185 PMCID: PMC10924915 DOI: 10.1038/s41398-024-02849-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 02/07/2024] [Accepted: 02/22/2024] [Indexed: 03/11/2024] Open
Abstract
Major depressive disorder (MDD) is a common mental illness worldwide and is triggered by an intricate interplay between environmental and genetic factors. Although there are several studies on common variants in MDD, studies on rare variants are relatively limited. In addition, few studies have examined the genetic contributions to neurostructural alterations in MDD using whole-exome sequencing (WES). We performed WES in 367 patients with MDD and 161 healthy controls (HCs) to detect germline and copy number variations in the Korean population. Gene-based rare variants were analyzed to investigate the association between the genes and individuals, followed by neuroimaging-genetic analysis to explore the neural mechanisms underlying the genetic impact in 234 patients with MDD and 135 HCs using diffusion tensor imaging data. We identified 40 MDD-related genes and observed 95 recurrent regions of copy number variations. We also discovered a novel gene, FRMPD3, carrying rare variants that influence MDD. In addition, the single nucleotide polymorphism rs771995197 in the MUC6 gene was significantly associated with the integrity of widespread white matter tracts. Moreover, we identified 918 rare exonic missense variants in genes associated with MDD susceptibility. We postulate that rare variants of FRMPD3 may contribute significantly to MDD, with a mild penetration effect.
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Affiliation(s)
- Eun-Young Oh
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea
| | - Kyu-Man Han
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Aram Kim
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Youbin Kang
- Department of Biomedical Sciences, Korea University College of Medicine, Seoul, Republic of Korea
| | - Woo-Suk Tae
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea
| | - Mi-Ryung Han
- Division of Life Sciences, College of Life Sciences and Bioengineering, Incheon National University, Incheon, Republic of Korea.
| | - Byung-Joo Ham
- Department of Psychiatry, Korea University Anam Hospital, Korea University College of Medicine, Seoul, Republic of Korea.
- Brain Convergence Research Center, Korea University College of Medicine, Seoul, Republic of Korea.
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27
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Nazeen S, Wang X, Zielinski D, Lam I, Hallacli E, Xu P, Ethier E, Strom R, Zanella CA, Nithianandam V, Ritter D, Henderson A, Saurat N, Afroz J, Nutter-Upham A, Benyamini H, Copty J, Ravishankar S, Morrow A, Mitchel J, Neavin D, Gupta R, Farbehi N, Grundman J, Myers RH, Scherzer CR, Trojanowski JQ, Van Deerlin VM, Cooper AA, Lee EB, Erlich Y, Lindquist S, Peng J, Geschwind DH, Powell J, Studer L, Feany MB, Sunyaev SR, Khurana V. Deep sequencing of proteotoxicity modifier genes uncovers a Presenilin-2/beta-amyloid-actin genetic risk module shared among alpha-synucleinopathies. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.03.03.583145. [PMID: 38496508 PMCID: PMC10942362 DOI: 10.1101/2024.03.03.583145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/19/2024]
Abstract
Whether neurodegenerative diseases linked to misfolding of the same protein share genetic risk drivers or whether different protein-aggregation pathologies in neurodegeneration are mechanistically related remains uncertain. Conventional genetic analyses are underpowered to address these questions. Through careful selection of patients based on protein aggregation phenotype (rather than clinical diagnosis) we can increase statistical power to detect associated variants in a targeted set of genes that modify proteotoxicities. Genetic modifiers of alpha-synuclein (ɑS) and beta-amyloid (Aβ) cytotoxicity in yeast are enriched in risk factors for Parkinson's disease (PD) and Alzheimer's disease (AD), respectively. Here, along with known AD/PD risk genes, we deeply sequenced exomes of 430 ɑS/Aβ modifier genes in patients across alpha-synucleinopathies (PD, Lewy body dementia and multiple system atrophy). Beyond known PD genes GBA1 and LRRK2, rare variants AD genes (CD33, CR1 and PSEN2) and Aβ toxicity modifiers involved in RhoA/actin cytoskeleton regulation (ARGHEF1, ARHGEF28, MICAL3, PASK, PKN2, PSEN2) were shared risk factors across synucleinopathies. Actin pathology occurred in iPSC synucleinopathy models and RhoA downregulation exacerbated ɑS pathology. Even in sporadic PD, the expression of these genes was altered across CNS cell types. Genome-wide CRISPR screens revealed the essentiality of PSEN2 in both human cortical and dopaminergic neurons, and PSEN2 mutation carriers exhibited diffuse brainstem and cortical synucleinopathy independent of AD pathology. PSEN2 contributes to a common-risk signal in PD GWAS and regulates ɑS expression in neurons. Our results identify convergent mechanisms across synucleinopathies, some shared with AD.
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Affiliation(s)
- Sumaiya Nazeen
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Xinyuan Wang
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Dina Zielinski
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Whitehead Institute of Biomedical Research, Cambridge, MA, USA
| | - Isabel Lam
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Erinc Hallacli
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ping Xu
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Elizabeth Ethier
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Ronya Strom
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Camila A Zanella
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Vanitha Nithianandam
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Dylan Ritter
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Alexander Henderson
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Nathalie Saurat
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | - Jalwa Afroz
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
| | | | - Hadar Benyamini
- Whitehead Institute of Biomedical Research, Cambridge, MA, USA
| | - Joseph Copty
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | | | - Autumn Morrow
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
| | - Jonathan Mitchel
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Program in Health Sciences & Technology, Harvard Medical School & Massachusetts Institute of Technology, Boston, MA
| | - Drew Neavin
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Renuka Gupta
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Nona Farbehi
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Jennifer Grundman
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Richard H Myers
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
| | - Clemens R Scherzer
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - John Q Trojanowski
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Vivianna M Van Deerlin
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Antony A Cooper
- Garvan Institute of Medical Research, Sydney, NSW, Australia
| | - Edward B Lee
- Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA, USA
| | - Yaniv Erlich
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Susan Lindquist
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Jian Peng
- Department of Computer Science, University of Illinois Urbana-Champaign, Champaign, IL, USA
| | - Daniel H Geschwind
- Center for Autism Research and Treatment, Semel Institute, Program in Neurogenetics, Department of Neurology and Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Joseph Powell
- Garvan Institute of Medical Research, Sydney, NSW, Australia
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Lorenz Studer
- The Center for Stem Cell Biology, Sloan-Kettering Institute for Cancer Research, New York, NY, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Mel B Feany
- Department of Pathology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
| | - Shamil R Sunyaev
- Division of Genetics, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biomedical Informatics, Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Vikram Khurana
- Division of Movement Disorders, Department of Neurology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Harvard Stem Cell Institute, Cambridge, MA, USA
- Aligning Science Across Parkinson's (ASAP) Collaborative Research Network, Chevy Chase, MD, USA
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28
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Garg E, Arguello-Pascualli P, Vishnyakova O, Halevy AR, Yoo S, Brooks JD, Bull SB, Gagnon F, Greenwood CMT, Hung RJ, Lawless JF, Lerner-Ellis J, Dennis JK, Abraham RJS, Garant JM, Thiruvahindrapuram B, Jones SJM, Strug LJ, Paterson AD, Sun L, Elliott LT. Canadian COVID-19 host genetics cohort replicates known severity associations. PLoS Genet 2024; 20:e1011192. [PMID: 38517939 PMCID: PMC10990181 DOI: 10.1371/journal.pgen.1011192] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2023] [Revised: 04/03/2024] [Accepted: 02/22/2024] [Indexed: 03/24/2024] Open
Abstract
The HostSeq initiative recruited 10,059 Canadians infected with SARS-CoV-2 between March 2020 and March 2023, obtained clinical information on their disease experience and whole genome sequenced (WGS) their DNA. We analyzed the WGS data for genetic contributors to severe COVID-19 (considering 3,499 hospitalized cases and 4,975 non-hospitalized after quality control). We investigated the evidence for replication of loci reported by the International Host Genetics Initiative (HGI); analyzed the X chromosome; conducted rare variant gene-based analysis and polygenic risk score testing. Population stratification was adjusted for using meta-analysis across ancestry groups. We replicated two loci identified by the HGI for COVID-19 severity: the LZTFL1/SLC6A20 locus on chromosome 3 and the FOXP4 locus on chromosome 6 (the latter with a variant significant at P < 5E-8). We found novel significant associations with MRAS and WDR89 in gene-based analyses, and constructed a polygenic risk score that explained 1.01% of the variance in severe COVID-19. This study provides independent evidence confirming the robustness of previously identified COVID-19 severity loci by the HGI and identifies novel genes for further investigation.
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Affiliation(s)
- Elika Garg
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Paola Arguello-Pascualli
- BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Olga Vishnyakova
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Anat R. Halevy
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
| | - Samantha Yoo
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- School of Epidemiology and Public Health, University of Ottawa, Ottawa, Ontario, Canada
| | - Jennifer D. Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Shelley B. Bull
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - France Gagnon
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Celia M. T. Greenwood
- Gerald Bronfman Department of Oncology, Department of Epidemiology, Biostatistics and Occupational Health, Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Lady Davis Institute for Medical Research, Jewish General Hospital, Montreal, Quebec, Canada
| | - Rayjean J. Hung
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
| | - Jerald F. Lawless
- Department of Statistics and Actuarial Science, University of Waterloo, Waterloo, Ontario, Canada
| | - Jordan Lerner-Ellis
- Lunenfeld-Tanenbaum Research Institute, Sinai Health, Toronto, Ontario, Canada
- Mount Sinai Hospital, Toronto, Ontario, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Ontario, Canada
| | - Jessica K. Dennis
- BC Children’s Hospital Research Institute, Vancouver, British Columbia, Canada
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Rohan J. S. Abraham
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada
| | - Jean-Michel Garant
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | - Steven J. M. Jones
- Department of Medical Genetics, University of British Columbia, Vancouver, British Columbia, Canada
- Canada’s Michael Smith Genome Sciences Centre, BC Cancer Agency, Vancouver, British Columbia, Canada
| | | | - Lisa J. Strug
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Andrew D. Paterson
- Genetics and Genome Biology Program, The Hospital for Sick Children, Toronto, Ontario, Canada
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Lei Sun
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Department of Statistical Sciences, University of Toronto, Toronto, Ontario, Canada
| | - Lloyd T. Elliott
- Department of Statistics and Actuarial Science, Simon Fraser University, Vancouver, British Columbia, Canada
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29
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Yoon JG, Jang DG, Cho SG, Lee C, Noh SH, Seo SK, Yu JW, Chung HW, Han K, Kwon SS, Han DH, Oh J, Jang IJ, Kim SH, Jee YK, Lee H, Park DW, Sohn JW, Yoon HJ, Kim CH, Lee JM, Kim SH, Lee MG. Synergistic toxicity with copper contributes to NAT2-associated isoniazid toxicity. Exp Mol Med 2024; 56:570-582. [PMID: 38424191 PMCID: PMC10984958 DOI: 10.1038/s12276-024-01172-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/21/2023] [Revised: 12/12/2023] [Accepted: 12/15/2023] [Indexed: 03/02/2024] Open
Abstract
Anti-tuberculosis (AT) medications, including isoniazid (INH), can cause drug-induced liver injury (DILI), but the underlying mechanism remains unclear. In this study, we aimed to identify genetic factors that may increase the susceptibility of individuals to AT-DILI and to examine genetic interactions that may lead to isoniazid (INH)-induced hepatotoxicity. We performed a targeted sequencing analysis of 380 pharmacogenes in a discovery cohort of 112 patients (35 AT-DILI patients and 77 controls) receiving AT treatment for active tuberculosis. Pharmacogenome-wide association analysis was also conducted using 1048 population controls (Korea1K). NAT2 and ATP7B genotypes were analyzed in a replication cohort of 165 patients (37 AT-DILI patients and 128 controls) to validate the effects of both risk genotypes. NAT2 ultraslow acetylators (UAs) were found to have a greater risk of AT-DILI than other genotypes (odds ratio [OR] 5.6 [95% confidence interval; 2.5-13.2], P = 7.2 × 10-6). The presence of ATP7B gene 832R/R homozygosity (rs1061472) was found to co-occur with NAT2 UA in AT-DILI patients (P = 0.017) and to amplify the risk in NAT2 UA (OR 32.5 [4.5-1423], P = 7.5 × 10-6). In vitro experiments using human liver-derived cell lines (HepG2 and SNU387 cells) revealed toxic synergism between INH and Cu, which were strongly augmented in cells with defective NAT2 and ATP7B activity, leading to increased mitochondrial reactive oxygen species generation, mitochondrial dysfunction, DNA damage, and apoptosis. These findings link the co-occurrence of ATP7B and NAT2 genotypes to the risk of INH-induced hepatotoxicity, providing novel mechanistic insight into individual AT-DILI susceptibility. Yoon et al. showed that individuals who carry NAT2 UAs and ATP7B 832R/R genotypes are at increased risk of developing isoniazid hepatotoxicity, primarily due to the increased synergistic toxicity between isoniazid and copper, which exacerbates mitochondrial dysfunction-related apoptosis.
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Affiliation(s)
- Jihoon G Yoon
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Genomic Medicine, Seoul National University Hospital, Seoul, Republic of Korea
| | - Dong Geon Jang
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Sung-Gyu Cho
- Department of Microbiology and Immunology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Chaeyoung Lee
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Shin Hye Noh
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
- Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Soo Kyung Seo
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jung Woo Yu
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Hyeon Woo Chung
- Department of Microbiology and Immunology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - KyeoRe Han
- Department of Microbiology and Immunology, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Soon Sung Kwon
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
- Department of Laboratory Medicine, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Dai Hoon Han
- Division of Hepatobiliary and Pancreatic Surgery, Department of Surgery, Yonsei University College of Medicine, Seoul, Korea
| | - Jaeseong Oh
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
| | - In-Jin Jang
- Department of Clinical Pharmacology and Therapeutics, Seoul National University College of Medicine and Hospital, Seoul, Republic of Korea
| | - Sang-Hoon Kim
- Department of Internal Medicine, Eulji University School of Medicine, Seoul, Republic of Korea
| | - Young-Koo Jee
- Department of Internal Medicine, Dankook University College of Medicine, Cheonan, Republic of Korea
| | - Hyun Lee
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Dong Won Park
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Jang Won Sohn
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Ho Joo Yoon
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Chul Hoon Kim
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea
| | - Jae Myun Lee
- Department of Microbiology and Immunology, Yonsei University College of Medicine, Seoul, Republic of Korea.
| | - Sang-Heon Kim
- Department of Internal Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea.
| | - Min Goo Lee
- Department of Pharmacology, BK21 Project of Yonsei Advanced Medical Science, Woo Choo Lee Institute for Precision Drug Development, Yonsei University College of Medicine, Seoul, Republic of Korea.
- Severance Biomedical Science Institute, Yonsei University College of Medicine, Seoul, Republic of Korea.
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30
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Ås J, Bertulyte I, Norgren N, Johansson A, Eriksson N, Green H, Wadelius M, Hallberg P. Whole genome case-control study of central nervous system toxicity due to antimicrobial drugs. PLoS One 2024; 19:e0299075. [PMID: 38422004 PMCID: PMC10903854 DOI: 10.1371/journal.pone.0299075] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2023] [Accepted: 02/03/2024] [Indexed: 03/02/2024] Open
Abstract
A genetic predisposition to central nervous system (CNS) toxicity induced by antimicrobial drugs (antibiotics, antivirals, antifungals, and antiparasitic drugs) has been suspected. Whole genome sequencing of 66 cases and 833 controls was performed to investigate whether antimicrobial drug-induced CNS toxicity was associated with genetic variation. The primary objective was to test whether antimicrobial-induced CNS toxicity was associated with seventeen efflux transporters at the blood-brain barrier. In this study, variants or structural elements in efflux transporters were not significantly associated with CNS toxicity. Secondary objectives were to test whether antimicrobial-induced CNS toxicity was associated with genes over the whole genome, with HLA, or with structural genetic variation. Uncommon variants in and close to three genes were significantly associated with CNS toxicity according to a sequence kernel association test combined with an optimal unified test (SKAT-O). These genes were LCP1 (q = 0.013), RETSAT (q = 0.013) and SFMBT2 (q = 0.035). Two variants were driving the LCP1 association: rs6561297 (p = 1.15x10-6, OR: 4.60 [95% CI: 2.51-8.46]) and the regulatory variant rs10492451 (p = 1.15x10-6, OR: 4.60 [95% CI: 2.51-8.46]). No common genetic variant, HLA-type or structural variation was associated with CNS toxicity. In conclusion, CNS toxicity due to antimicrobial drugs was associated with uncommon variants in LCP1, RETSAT and SFMBT2.
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Affiliation(s)
- Joel Ås
- Department of Medical Sciences, Clinical Pharmacogenomics and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Ilma Bertulyte
- Department of Medical Sciences, Clinical Pharmacogenomics and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Nina Norgren
- Department of Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Umeå University, Umeå, Sweden
| | - Anna Johansson
- Dept of Cell and Molecular Biology, National Bioinformatics Infrastructure Sweden, Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Niclas Eriksson
- Department of Medical Sciences, Clinical Pharmacogenomics and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
- Uppsala Clinical Research Center, Uppsala, Sweden
| | - Henrik Green
- Division of Clinical Chemistry and Pharmacology, Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden
- Department of Forensic Genetics and Forensic Toxicology, National Board of Forensic Medicine, Linköping, Sweden
| | - Mia Wadelius
- Department of Medical Sciences, Clinical Pharmacogenomics and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
| | - Pär Hallberg
- Department of Medical Sciences, Clinical Pharmacogenomics and Science for Life Laboratory, Uppsala University, Uppsala, Sweden
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Bayram E, Reho P, Litvan I, Ding J, Gibbs JR, Dalgard CL, Traynor BJ, Scholz SW, Chia R. Genetic analysis of the X chromosome in people with Lewy body dementia nominates new risk loci. NPJ Parkinsons Dis 2024; 10:39. [PMID: 38378815 PMCID: PMC10879525 DOI: 10.1038/s41531-024-00649-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/25/2023] [Accepted: 02/01/2024] [Indexed: 02/22/2024] Open
Abstract
Sex influences the prevalence and symptoms of Lewy body dementia (LBD). However, genome-wide association studies typically focus on autosomal variants and exclude sex-specific risk factors. We addressed this gap by performing an X chromosome-wide association study using whole-genome sequence data from 2591 LBD cases and 4391 controls. We identified a significant risk locus within intron 1 of MAP3K15 (rs141773145, odds ratio = 2.42, 95% confidence interval = 1.65-3.56, p-value = 7.0 × 10-6) in female LBD cases conditioned for APOE ε4 dosage. The locus includes an enhancer region that regulates MAP3K15 expression in ganglionic eminence cells derived from primary cultured neurospheres. Rare variant burden testing showed differential enrichment of missense mutations in TEX13A in female LBD cases, that did not reach significance (p-value = 1.34 × 10-4). These findings support the sex-specific effects of genetic factors and a potential role of Alzheimer's-related risk for females with LBD.
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Affiliation(s)
- Ece Bayram
- Department of Neurosciences, Parkinson and Other Movement Disorders Center, University of California San Diego, La Jolla, CA, USA
| | - Paolo Reho
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
| | - Irene Litvan
- Department of Neurosciences, Parkinson and Other Movement Disorders Center, University of California San Diego, La Jolla, CA, USA
| | - Jinhui Ding
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - J Raphael Gibbs
- Computational Biology Group, Laboratory of Neurogenetics, National Institute on Aging, Bethesda, MD, USA
| | - Clifton L Dalgard
- Department of Anatomy, Physiology & Genetics, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
- The American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD, USA
| | - Bryan J Traynor
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
- Neuromuscular Diseases Research Section, National Institute on Aging, Bethesda, MD, USA
- Therapeutics Development Laboratory, National Center for Advancing Translational Sciences, Rockville, MD, USA
| | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD, USA
| | - Ruth Chia
- Neuromuscular Diseases Research Section, National Institute on Aging, Bethesda, MD, USA.
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32
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He J, Li Q, Zhang Q. rvTWAS: identifying gene-trait association using sequences by utilizing transcriptome-directed feature selection. Genetics 2024; 226:iyad204. [PMID: 38001381 DOI: 10.1093/genetics/iyad204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/20/2023] [Revised: 11/14/2023] [Accepted: 11/16/2023] [Indexed: 11/26/2023] Open
Abstract
Toward the identification of genetic basis of complex traits, transcriptome-wide association study (TWAS) is successful in integrating transcriptome data. However, TWAS is only applicable for common variants, excluding rare variants in exome or whole-genome sequences. This is partly because of the inherent limitation of TWAS protocols that rely on predicting gene expressions. Our previous research has revealed the insight into TWAS: the 2 steps in TWAS, building and applying the expression prediction models, are essentially genetic feature selection and aggregations that do not have to involve predictions. Based on this insight disentangling TWAS, rare variants' inability of predicting expression traits is no longer an obstacle. Herein, we developed "rare variant TWAS," or rvTWAS, that first uses a Bayesian model to conduct expression-directed feature selection and then uses a kernel machine to carry out feature aggregation, forming a model leveraging expressions for association mapping including rare variants. We demonstrated the performance of rvTWAS by thorough simulations and real data analysis in 3 psychiatric disorders, namely schizophrenia, bipolar disorder, and autism spectrum disorder. We confirmed that rvTWAS outperforms existing TWAS protocols and revealed additional genes underlying psychiatric disorders. Particularly, we formed a hypothetical mechanism in which zinc finger genes impact all 3 disorders through transcriptional regulations. rvTWAS will open a door for sequence-based association mappings integrating gene expressions.
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Affiliation(s)
- Jingni He
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary T2N 1N4, Canada
| | - Qing Li
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary T2N 1N4, Canada
| | - Qingrun Zhang
- Department of Biochemistry and Molecular Biology, University of Calgary, Calgary T2N 1N4, Canada
- Department of Mathematics and Statistics, University of Calgary, Calgary T2N 1N4, Canada
- Alberta Children's Hospital Research Institute, University of Calgary, Calgary T2N 1N4, Canada
- Arnie Charbonneau Cancer Institute, University of Calgary, Calgary T2N 1N4, Canada
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33
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Petrykey K, Lippé S, Sultan S, Robaey P, Drouin S, Affret-Bertout L, Beaulieu P, St-Onge P, Baedke JL, Yasui Y, Hudson MM, Laverdière C, Sinnett D, Krajinovic M. Genetic Factors and Long-term Treatment-Related Neurocognitive Deficits, Anxiety, and Depression in Childhood Leukemia Survivors: An Exome-Wide Association Study. Cancer Epidemiol Biomarkers Prev 2024; 33:234-243. [PMID: 38051303 PMCID: PMC10903523 DOI: 10.1158/1055-9965.epi-23-0634] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/13/2023] [Revised: 09/23/2023] [Accepted: 11/30/2023] [Indexed: 12/07/2023] Open
Abstract
BACKGROUND An increased risk of neurocognitive deficits, anxiety, and depression has been reported in childhood cancer survivors. METHODS We analyzed associations of neurocognitive deficits, as well as anxiety and depression, with common and rare genetic variants derived from whole-exome sequencing data of acute lymphoblastic leukemia (ALL) survivors from the PETALE cohort. In addition, significant associations were assessed using stratified and multivariable analyses. Next, top-ranking common associations were analyzed in an independent SJLIFE replication cohort of ALL survivors. RESULTS Significant associations were identified in the entire discovery cohort (N = 229) between the AK8 gene and changes in neurocognitive function, whereas PTPRZ1, MUC16, TNRC6C-AS1 were associated with anxiety. Following stratification according to sex, the ZNF382 gene was linked to a neurocognitive deficit in males, whereas APOL2 and C6orf165 were associated with anxiety and EXO5 with depression. Following stratification according to prognostic risk groups, the modulatory effect of rare variants on depression was additionally found in the CYP2W1 and PCMTD1 genes. In the replication SJLIFE cohort (N = 688), the male-specific association in the ZNF382 gene was not significant; however, a P value<0.05 was observed when the entire SJLIFE cohort was analyzed. ZNF382 was significant in males in the combined cohorts as shown by meta-analyses as well as the depression-associated gene EXO5. CONCLUSIONS Further research is needed to confirm whether the current findings, along with other known risk factors, may be valuable in identifying patients at increased risk of these long-term complications. IMPACT Our results suggest that specific genes may be related to increased neuropsychological consequences.
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Affiliation(s)
- Kateryna Petrykey
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pharmacology and Physiology, Université de Montréal (Quebec), Canada
| | - Sarah Lippé
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Psychology, Université de Montréal (Quebec), Canada
| | - Serge Sultan
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Psychology, Université de Montréal (Quebec), Canada
| | - Philippe Robaey
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Children’s Hospital of Eastern Ontario, Ottawa (Ontario), Canada
- Department of Psychiatry, Université de Montréal (Quebec), Canada
- Department of Psychiatry, University of Ottawa (Ontario), Canada
| | - Simon Drouin
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | | | - Patrick Beaulieu
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | - Pascal St-Onge
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
| | - Jessica L. Baedke
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Yutaka Yasui
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Melissa M. Hudson
- Department of Epidemiology and Cancer Control, St. Jude Children’s Research Hospital, Memphis (TN), USA
- Department of Oncology, St. Jude Children’s Research Hospital, Memphis (TN), USA
| | - Caroline Laverdière
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
| | - Daniel Sinnett
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
| | - Maja Krajinovic
- Sainte-Justine University Health Center (SJUHC), Montreal (Quebec), Canada
- Department of Pharmacology and Physiology, Université de Montréal (Quebec), Canada
- Department of Pediatrics, Université de Montréal (Quebec), Canada
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34
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Hamzic E, Spahic L, Pistoljevic N, Dzanko E, Pasic S, Kadric L, Serdarevic F, Hajdarpasic A. Exploratory genetic analysis in children with autism spectrum disorder and other developmental disorders using whole exome sequencing. BIOMOLECULES & BIOMEDICINE 2024; 24:888-896. [PMID: 38421723 PMCID: PMC11293238 DOI: 10.17305/bb.2024.10221] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/29/2023] [Revised: 02/02/2024] [Accepted: 02/06/2024] [Indexed: 03/02/2024]
Abstract
Developmental disorders (DDs), such as autism spectrum disorder (ASD), incorporate various conditions; once identified, further diagnostics are necessary to specify their type and severity. The aim of this exploratory study was to identify genetic variants that can help differentiate ASD early from other DDs. We selected 36 children (mean age 60.1 months) with DDs using Developmental Behavioral Scales (DBS) through "EDUS-Education for All", an organization providing services for children with developmental disorders in Bosnia and Herzegovina. We further rated children's autistic traits with the preschool version of the Childhood Autism Rating Scale, second edition (CARS-II). We defined ASD if scores were >25.5 and other DDs if scores were <25.5. Diagnosis of ASD and DD were independently confirmed by child psychiatrists. Whole exome sequencing (WES) was performed by Veritas Genetics, USA, using Illumina NovaSeq 6000 (Illumina Inc., San Diego, CA, USA) next-generation sequencing (NGS) apparatus. We tested genetic association by applying SKAT-O, which optimally combines the standard Sequence Kernel Association Test (SKAT) and burden tests to identify rare variants associated with complex traits in samples of limited power. The analysis yielded seven genes (DSE, COL10A1, DLK2, CSMD1, FAM47E, PPIA, PYDC2) to potentially differentiate observed phenotypic characteristics between our cohort participants with ASD and other DDs. Our exploratory study in a small sample of participants with ASD and other DDs contributed to gene discovery in differentiating ASD from DDs. A replication study is needed in a larger sample to confirm our results.
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Affiliation(s)
- Edin Hamzic
- Biocomputix, Sarajevo, Bosnia and Herzegovina
- BioCertica, Paarl, South Africa
| | - Lemana Spahic
- International Burch University, Sarajevo, Bosnia and Herzegovina
| | | | - Eldin Dzanko
- Education for All (EDUS), Sarajevo, Bosnia and Herzegovina
| | - Sanela Pasic
- Department of Economics and Business, Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina
| | - Lejla Kadric
- Department of Medical Biology and Genetics, Sarajevo Medical School, Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina
| | - Fadila Serdarevic
- Department of Epidemiology, Sarajevo Medical School, Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina
- Department of Child and Adolescent Psychiatry, Erasmus MC, Rotterdam, The Netherlands
| | - Aida Hajdarpasic
- Department of Medical Biology and Genetics, Sarajevo Medical School, Sarajevo School of Science and Technology, Sarajevo, Bosnia and Herzegovina
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35
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Li X, Pura J, Allen A, Owzar K, Lu J, Harms M, Xie J. DYNATE: Localizing rare-variant association regions via multiple testing embedded in an aggregation tree. Genet Epidemiol 2024; 48:42-55. [PMID: 38014869 PMCID: PMC10842871 DOI: 10.1002/gepi.22542] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 10/09/2023] [Accepted: 10/26/2023] [Indexed: 11/29/2023]
Abstract
Rare-variants (RVs) genetic association studies enable researchers to uncover the variation in phenotypic traits left unexplained by common variation. Traditional single-variant analysis lacks power; thus, researchers have developed various methods to aggregate the effects of RVs across genomic regions to study their collective impact. Some existing methods utilize a static delineation of genomic regions, often resulting in suboptimal effect aggregation, as neutral subregions within the test region will result in an attenuation of signal. Other methods use varying windows to search for signals but often result in long regions containing many neutral RVs. To pinpoint short genomic regions enriched for disease-associated RVs, we developed a novel method, DYNamic Aggregation TEsting (DYNATE). DYNATE dynamically and hierarchically aggregates smaller genomic regions into larger ones and performs multiple testing for disease associations with a controlled weighted false discovery rate. DYNATE's main advantage lies in its strong ability to identify short genomic regions highly enriched for disease-associated RVs. Extensive numerical simulations demonstrate the superior performance of DYNATE under various scenarios compared with existing methods. We applied DYNATE to an amyotrophic lateral sclerosis study and identified a new gene, EPG5, harboring possibly pathogenic mutations.
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Affiliation(s)
- Xuechan Li
- Novartis Pharmaceuticals Corporation, Basel, Switzerland
| | | | - Andrew Allen
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Kouros Owzar
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
| | - Jianfeng Lu
- Department of Mathematics, Duke University, Durham, North Carolina, USA
| | - Matthew Harms
- Department of Neurology, Columbia University, Broadway, New York, USA
| | - Jichun Xie
- Department of Biostatistics and Bioinformatics, Duke University, Durham, North Carolina, USA
- Department of Mathematics, Duke University, Durham, North Carolina, USA
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36
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Kwong A, Zawistowski M, Fritsche LG, Zhan X, Bragg-Gresham J, Branham KE, Advani J, Othman M, Ratnapriya R, Teslovich TM, Stambolian D, Chew EY, Abecasis GR, Swaroop A. Whole genome sequencing of 4,787 individuals identifies gene-based rare variants in age-related macular degeneration. Hum Mol Genet 2024; 33:374-385. [PMID: 37934784 PMCID: PMC10840384 DOI: 10.1093/hmg/ddad189] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2023] [Revised: 10/12/2023] [Accepted: 10/31/2023] [Indexed: 11/09/2023] Open
Abstract
Genome-wide association studies have contributed extensively to the discovery of disease-associated common variants. However, the genetic contribution to complex traits is still largely difficult to interpret. We report a genome-wide association study of 2394 cases and 2393 controls for age-related macular degeneration (AMD) via whole-genome sequencing, with 46.9 million genetic variants. Our study reveals significant single-variant association signals at four loci and independent gene-based signals in CFH, C2, C3, and NRTN. Using data from the Exome Aggregation Consortium (ExAC) for a gene-based test, we demonstrate an enrichment of predicted rare loss-of-function variants in CFH, CFI, and an as-yet unreported gene in AMD, ORMDL2. Our method of using a large variant list without individual-level genotypes as an external reference provides a flexible and convenient approach to leverage the publicly available variant datasets to augment the search for rare variant associations, which can explain additional disease risk in AMD.
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Affiliation(s)
- Alan Kwong
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Matthew Zawistowski
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Lars G Fritsche
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Xiaowei Zhan
- Southwestern Medical Center, University of Texas, 5323 Harry Hines Blvd, Dallas, TX 75390, United States
| | - Jennifer Bragg-Gresham
- Kidney Epidemiology and Cost Center, Department of Internal Medicine-Nephrology, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
| | - Kari E Branham
- Department of Ophthalmology and Visual Sciences, University of Michigan Kellogg Eye Center, 1000 Wall St, Ann Arbor, MI 48105, United States
| | - Jayshree Advani
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC 0610, Bethesda, MD 20892, United States
| | - Mohammad Othman
- Department of Ophthalmology and Visual Sciences, University of Michigan Kellogg Eye Center, 1000 Wall St, Ann Arbor, MI 48105, United States
| | - Rinki Ratnapriya
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC 0610, Bethesda, MD 20892, United States
| | - Tanya M Teslovich
- Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Rd, Tarrytown, NY 10591, United States
| | - Dwight Stambolian
- Department of Ophthalmology, Perelman School of Medicine, University of Pennsylvania Medical School, 51 N. 39th Street, Philadelphia, PA 19104, United States
| | - Emily Y Chew
- Division of Epidemiology and Clinical Application, National Eye Institute, National Institutes of Health, 10 Center Drive Building 10-CRC, Bethesda, MD 20892, United States
| | - Gonçalo R Abecasis
- Department of Biostatistics and Center for Statistical Genetics, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109, United States
- Regeneron Pharmaceuticals Inc., 777 Old Saw Mill River Rd, Tarrytown, NY 10591, United States
| | - Anand Swaroop
- Neurobiology-Neurodegeneration and Repair Laboratory, National Eye Institute, National Institutes of Health, 6 Center Drive, MSC 0610, Bethesda, MD 20892, United States
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37
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Wang H, Chang TS, Dombroski BA, Cheng PL, Patil V, Valiente-Banuet L, Farrell K, Mclean C, Molina-Porcel L, Rajput A, De Deyn PP, Bastard NL, Gearing M, Kaat LD, Swieten JCV, Dopper E, Ghetti BF, Newell KL, Troakes C, de Yébenes JG, Rábano-Gutierrez A, Meller T, Oertel WH, Respondek G, Stamelou M, Arzberger T, Roeber S, Müller U, Hopfner F, Pastor P, Brice A, Durr A, Ber IL, Beach TG, Serrano GE, Hazrati LN, Litvan I, Rademakers R, Ross OA, Galasko D, Boxer AL, Miller BL, Seeley WW, Deerlin VMV, Lee EB, White CL, Morris H, de Silva R, Crary JF, Goate AM, Friedman JS, Leung YY, Coppola G, Naj AC, Wang LS, Dickson DW, Höglinger GU, Schellenberg GD, Geschwind DH, Lee WP. Whole-Genome Sequencing Analysis Reveals New Susceptibility Loci and Structural Variants Associated with Progressive Supranuclear Palsy. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.12.28.23300612. [PMID: 38234807 PMCID: PMC10793533 DOI: 10.1101/2023.12.28.23300612] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/19/2024]
Abstract
Background Progressive supranuclear palsy (PSP) is a rare neurodegenerative disease characterized by the accumulation of aggregated tau proteins in astrocytes, neurons, and oligodendrocytes. Previous genome-wide association studies for PSP were based on genotype array, therefore, were inadequate for the analysis of rare variants as well as larger mutations, such as small insertions/deletions (indels) and structural variants (SVs). Method In this study, we performed whole genome sequencing (WGS) and conducted association analysis for single nucleotide variants (SNVs), indels, and SVs, in a cohort of 1,718 cases and 2,944 controls of European ancestry. Of the 1,718 PSP individuals, 1,441 were autopsy-confirmed and 277 were clinically diagnosed. Results Our analysis of common SNVs and indels confirmed known genetic loci at MAPT, MOBP, STX6, SLCO1A2, DUSP10, and SP1, and further uncovered novel signals in APOE, FCHO1/MAP1S, KIF13A, TRIM24, TNXB, and ELOVL1. Notably, in contrast to Alzheimer's disease (AD), we observed the APOE ε2 allele to be the risk allele in PSP. Analysis of rare SNVs and indels identified significant association in ZNF592 and further gene network analysis identified a module of neuronal genes dysregulated in PSP. Moreover, seven common SVs associated with PSP were observed in the H1/H2 haplotype region (17q21.31) and other loci, including IGH, PCMT1, CYP2A13, and SMCP. In the H1/H2 haplotype region, there is a burden of rare deletions and duplications (P = 6.73×10-3) in PSP. Conclusions Through WGS, we significantly enhanced our understanding of the genetic basis of PSP, providing new targets for exploring disease mechanisms and therapeutic interventions.
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Affiliation(s)
- Hui Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Timothy S Chang
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Beth A Dombroski
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Po-Liang Cheng
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Vishakha Patil
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Leopoldo Valiente-Banuet
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Kurt Farrell
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Catriona Mclean
- Victorian Brain Bank, The Florey Institute of Neuroscience and Mental Health, Parkville, Victoria, Australia
| | - Laura Molina-Porcel
- Alzheimer's disease and other cognitive disorders unit. Neurology Service, Hospital Clínic, Fundació Recerca Clínic Barcelona (FRCB). Institut d'Investigacions Biomediques August Pi I Sunyer (IDIBAPS), University of Barcelona, Barcelona, Spain
- Neurological Tissue Bank of the Biobanc-Hospital Clínic-IDIBAPS, Barcelona, Spain
| | - Alex Rajput
- Movement Disorders Program, Division of Neurology, University of Saskatchewan, Saskatoon, Saskatchewan, Canada
| | - Peter Paul De Deyn
- Laboratory of Neurochemistry and Behavior, Experimental Neurobiology Unit, University of Antwerp, Wilrijk (Antwerp), Belgium
- Department of Neurology, University Medical Center Groningen, NL-9713 AV Groningen, Netherlands
| | | | - Marla Gearing
- Department of Pathology and Laboratory Medicine and Department of Neurology, Emory University School of Medicine, Atlanta, GA, USA
| | | | | | - Elise Dopper
- Netherlands Brain Bank and Erasmus University, Netherlands
| | - Bernardino F Ghetti
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Kathy L Newell
- Department of Pathology and Laboratory Medicine, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Claire Troakes
- London Neurodegenerative Diseases Brain Bank, King's College London, London, UK
| | | | - Alberto Rábano-Gutierrez
- Fundación CIEN (Centro de Investigación de Enfermedades Neurológicas) - Centro Alzheimer Fundación Reina Sofía, Madrid, Spain
| | - Tina Meller
- Department of Neurology, Philipps-Universität, Marburg, Germany
| | | | - Gesine Respondek
- German Center for Neurodegenerative Diseases (DZNE), Munich, Germany
| | - Maria Stamelou
- Parkinson's disease and Movement Disorders Department, HYGEIA Hospital, Athens, Greece
- European University of Cyprus, Nicosia, Cyprus
| | - Thomas Arzberger
- Department of Psychiatry and Psychotherapy, University Hospital Munich, Ludwig-Maximilians-University Munich, Germany
- Center for Neuropathology and Prion Research, Ludwig-Maximilians-University Munich, Germany
| | | | | | - Franziska Hopfner
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Pau Pastor
- Unit of Neurodegenerative diseases, Department of Neurology, University Hospital Germans Trias i Pujol, Badalona, Barcelona, Spain
- Neurosciences, The Germans Trias i Pujol Research Institute (IGTP) Badalona, Badalona, Spain
| | - Alexis Brice
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Alexandra Durr
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | - Isabelle Le Ber
- Sorbonne Université, Paris Brain Institute - Institut du Cerveau - ICM, Inserm U1127, CNRS UMR 7225, APHP - Hôpital Pitié-Salpêtrière, Paris, France
| | | | | | | | - Irene Litvan
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Rosa Rademakers
- VIB Center for Molecular Neurology, University of Antwerp, Belgium
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Owen A Ross
- Department of Neuroscience, Mayo Clinic Jacksonville, FL, USA
| | - Douglas Galasko
- Department of Neuroscience, University of California, San Diego, CA, USA
| | - Adam L Boxer
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Bruce L Miller
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Willian W Seeley
- Memory and Aging Center, University of California, San Francisco, CA, USA
| | - Vivanna M Van Deerlin
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Center for Neurodegenerative Disease Research, University of Pennsylvania School of Medicine, Philadelphia, PA, USA
| | - Charles L White
- University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Huw Morris
- Departmento of Clinical and Movement Neuroscience, University College of London, London, UK
| | - Rohan de Silva
- Reta Lila Weston Institute, UCL Queen Square Institute of Neurology, London, UK
| | - John F Crary
- Department of Pathology, Department of Artificial Intelligence & Human Health, Nash Family, Department of Neuroscience, Ronald M. Loeb Center for Alzheimer's Disease, Friedman Brain, Institute, Neuropathology Brain Bank & Research CoRE, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Alison M Goate
- Department of Genetics and Genomic Sciences, New York, NY, USA; Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Jeffrey S Friedman
- Friedman Bioventure, Inc., Del Mar, CA, USA; Department of Genetics and Genomic Sciences, New York, NY, USA
| | - Yuk Yee Leung
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Giovanni Coppola
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Psychiatry, Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles, CA, USA
| | - Adam C Naj
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Biostatistics, Epidemiology, and Informatics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Li-San Wang
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | | | - Günter U Höglinger
- Department of Neurology, LMU University Hospital, Ludwig-Maximilians-Universität (LMU) München; German Center for Neurodegenerative Diseases (DZNE), Munich, Germany; and Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Gerard D Schellenberg
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Daniel H Geschwind
- Movement Disorders Programs, Department of Neurology, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California, Los Angeles, Los Angeles, CA, USA
- Institute of Precision Health, University of California, Los Angeles, Los Angeles, CA, USA
| | - Wan-Ping Lee
- Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Neurodegeneration Genomics Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
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Jacob S, Kosaka Y, Bhatlekar S, Denorme F, Benzon H, Moody A, Moody V, Tugolukova E, Hull G, Kishimoto N, Manne BK, Guo L, Souvenir R, Seliger BJ, Eustes AS, Hoerger K, Tolley ND, Fatahian AN, Boudina S, Christiani DC, Wei Y, Ju C, Campbell RA, Rondina MT, Abel ED, Bray PF, Weyrich AS, Rowley JW. Mitofusin-2 Regulates Platelet Mitochondria and Function. Circ Res 2024; 134:143-161. [PMID: 38156445 PMCID: PMC10872864 DOI: 10.1161/circresaha.123.322914] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 12/13/2023] [Indexed: 12/30/2023]
Abstract
BACKGROUND Single-nucleotide polymorphisms linked with the rs1474868 T allele (MFN2 [mitofusin-2] T/T) in the human mitochondrial fusion protein MFN2 gene are associated with reduced platelet MFN2 RNA expression and platelet counts. This study investigates the impact of MFN2 on megakaryocyte and platelet biology. METHODS Mice with megakaryocyte/platelet deletion of Mfn2 (Mfn2-/- [Mfn2 conditional knockout]) were generated using Pf4-Cre crossed with floxed Mfn2 mice. Human megakaryocytes were generated from cord blood and platelets isolated from healthy subjects genotyped for rs1474868. Ex vivo approaches assessed mitochondrial morphology, function, and platelet activation responses. In vivo measurements included endogenous/transfused platelet life span, tail bleed time, transient middle cerebral artery occlusion, and pulmonary vascular permeability/hemorrhage following lipopolysaccharide-induced acute lung injury. RESULTS Mitochondria was more fragmented in megakaryocytes derived from Mfn2-/- mice and from human cord blood with MFN2 T/T genotype compared with control megakaryocytes. Human resting platelets of MFN2 T/T genotype had reduced MFN2 protein, diminished mitochondrial membrane potential, and an increased rate of phosphatidylserine exposure during ex vivo culture. Platelet counts and platelet life span were reduced in Mfn2-/- mice accompanied by an increased rate of phosphatidylserine exposure in resting platelets, especially aged platelets, during ex vivo culture. Mfn2-/- also decreased platelet mitochondrial membrane potential (basal) and activated mitochondrial oxygen consumption rate, reactive oxygen species generation, calcium flux, platelet-neutrophil aggregate formation, and phosphatidylserine exposure following dual agonist activation. Ultimately, Mfn2-/- mice showed prolonged tail bleed times, decreased ischemic stroke infarct size after cerebral ischemia-reperfusion, and exacerbated pulmonary inflammatory hemorrhage following lipopolysaccharide-induced acute lung injury. Analysis of MFN2 SNPs in the iSPAAR study (Identification of SNPs Predisposing to Altered ALI Risk) identified a significant association between MFN2 and 28-day mortality in patients with acute respiratory distress syndrome. CONCLUSIONS Mfn2 preserves mitochondrial phenotypes in megakaryocytes and platelets and influences platelet life span, function, and outcomes of stroke and lung injury.
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Affiliation(s)
- Shancy Jacob
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Yasuhiro Kosaka
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Seema Bhatlekar
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Frederik Denorme
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Haley Benzon
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Alexandra Moody
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Victoria Moody
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | | | - Grayson Hull
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Nina Kishimoto
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Bhanu K. Manne
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Li Guo
- Bloodworks Northwest Research Institute, Seattle, WA
- Division of Hematology and Oncology, University of Utah, Seattle, WA
| | - Rhonda Souvenir
- David Geffen School of Medicine and University of California, Los Angeles (UCLA), Health, Los Angeles, CA
| | | | | | - Kelly Hoerger
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Neal D. Tolley
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
| | - Amir N. Fatahian
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT
| | - Sihem Boudina
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Department of Nutrition and Integrative Physiology, University of Utah, Salt Lake City, UT
| | - David C. Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, 02115, USA
- Department of Medicine, Massachusetts General Hospital/Harvard Medical School, Boston, MA, 02115, USA
| | - Yongyue Wei
- Peking University Center for Public Health and Epidemic Preparedness and Response, Beijing, 100191, China
- Key Laboratory of Epidemiology of Major Diseases (Peking University), Ministry of Education, Beijing, 100191, China
| | - Can Ju
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, China
| | - Robert A. Campbell
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
- Department of Pathology, University of Utah Heath, Salt Lake City, UT
| | - Matthew T. Rondina
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
- Department of Pathology, University of Utah Heath, Salt Lake City, UT
- Department of Internal Medicine and the GRECC, George E. Wahlen VAMC, Salt Lake City, UT
| | - E. Dale Abel
- David Geffen School of Medicine and University of California, Los Angeles (UCLA), Health, Los Angeles, CA
| | - Paul F. Bray
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Division of Hematology and Hematologic Malignancies, Department of Internal Medicine, University of Utah, Salt Lake City, UT
| | - Andrew S. Weyrich
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Oklahoma Medical Research Foundation (OMRF), Oklahoma City, OK
| | - Jesse W. Rowley
- Molecular Medicine Program, University of Utah, Salt Lake City, UT
- Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT
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Cao C, Shao M, Zuo C, Kwok D, Liu L, Ge Y, Zhang Z, Cui F, Chen M, Fan R, Ding Y, Jiang H, Wang G, Zou Q. RAVAR: a curated repository for rare variant-trait associations. Nucleic Acids Res 2024; 52:D990-D997. [PMID: 37831073 PMCID: PMC10767942 DOI: 10.1093/nar/gkad876] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2023] [Revised: 09/20/2023] [Accepted: 09/28/2023] [Indexed: 10/14/2023] Open
Abstract
Rare variants contribute significantly to the genetic causes of complex traits, as they can have much larger effects than common variants and account for much of the missing heritability in genome-wide association studies. The emergence of UK Biobank scale datasets and accurate gene-level rare variant-trait association testing methods have dramatically increased the number of rare variant associations that have been detected. However, no systematic collection of these associations has been carried out to date, especially at the gene level. To address the issue, we present the Rare Variant Association Repository (RAVAR), a comprehensive collection of rare variant associations. RAVAR includes 95 047 high-quality rare variant associations (76186 gene-level and 18 861 variant-level associations) for 4429 reported traits which are manually curated from 245 publications. RAVAR is the first resource to collect and curate published rare variant associations in an interactive web interface with integrated visualization, search, and download features. Detailed gene and SNP information are provided for each association, and users can conveniently search for related studies by exploring the EFO tree structure and interactive Manhattan plots. RAVAR could vastly improve the accessibility of rare variant studies. RAVAR is freely available for all users without login requirement at http://www.ravar.bio.
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Affiliation(s)
- Chen Cao
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Mengting Shao
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Chunman Zuo
- Institute of Artificial Intelligence, Donghua University, Shanghai, China
| | - Devin Kwok
- School of Computer Science, McGill University, Montreal, Canada
| | - Lin Liu
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Yuli Ge
- Key Laboratory for Bio-Electromagnetic Environment and Advanced Medical Theranostics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing, China
| | - Zilong Zhang
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
| | - Feifei Cui
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
| | - Mingshuai Chen
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
| | - Rui Fan
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
| | - Yijie Ding
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
| | - Hangjin Jiang
- Center for Data Science, Zhejiang University, Hangzhou, China
| | - Guishen Wang
- College of Computer Science and Engineering, Changchun University of Technology, Changchun, China
| | - Quan Zou
- Institute of Fundamental and Frontier Sciences, University of Electronic Science and Technology of China, Chengdu, China
- Yangtze Delta Region Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou, China
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40
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He J, Antonyan L, Zhu H, Ardila K, Li Q, Enoma D, Zhang W, Liu A, Chekouo T, Cao B, MacDonald ME, Arnold PD, Long Q. A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders. Am J Hum Genet 2024; 111:48-69. [PMID: 38118447 PMCID: PMC10806749 DOI: 10.1016/j.ajhg.2023.11.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2023] [Revised: 11/04/2023] [Accepted: 11/16/2023] [Indexed: 12/22/2023] Open
Abstract
Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.
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Affiliation(s)
- Jingni He
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Lilit Antonyan
- Department of Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Harold Zhu
- Department of Biological Sciences, Faculty of Science, University of Calgary, Calgary, AB, Canada
| | - Karen Ardila
- Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada
| | - Qing Li
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - David Enoma
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | | | - Andy Liu
- Sir Winston Churchill High School, Calgary, AB, Canada; College of Letters and Science, University of California, Los Angeles, Los Angeles, CA, USA
| | - Thierry Chekouo
- Department of Mathematics and Statistics, Faculty of Science, University of Calgary, Calgary, AB, Canada; Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN, USA
| | - Bo Cao
- Department of Psychiatry, Faculty of Medicine & Dentistry, University of Alberta, Edmonton, AB, Canada
| | - M Ethan MacDonald
- The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Biomedical Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada; Department of Electrical and Software Engineering, Schulich School of Engineering, University of Calgary, Calgary, AB, Canada; Department of Radiology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - Paul D Arnold
- Department of Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Psychiatry, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.
| | - Quan Long
- Department of Biochemistry and Molecular Biology, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; The Mathison Centre for Mental Health Research & Education, Hotchkiss Brain Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Alberta Children's Hospital Research Institute, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada; Department of Mathematics and Statistics, Faculty of Science, University of Calgary, Calgary, AB, Canada.
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41
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Mbatchou J, McPeek MS. JASPER: fast, powerful, multitrait association testing in structured samples gives insight on pleiotropy in gene expression. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.12.18.571948. [PMID: 38187553 PMCID: PMC10769254 DOI: 10.1101/2023.12.18.571948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Joint association analysis of multiple traits with multiple genetic variants can provide insight into genetic architecture and pleiotropy, improve trait prediction and increase power for detecting association. Furthermore, some traits are naturally high-dimensional, e.g., images, networks or longitudinally measured traits. Assessing significance for multitrait genetic association can be challenging, especially when the sample has population sub-structure and/or related individuals. Failure to adequately adjust for sample structure can lead to power loss and inflated type 1 error, and commonly used methods for assessing significance can work poorly with a large number of traits or be computationally slow. We developed JASPER, a fast, powerful, robust method for assessing significance of multitrait association with a set of genetic variants, in samples that have population sub-structure, admixture and/or relatedness. In simulations, JASPER has higher power, better type 1 error control, and faster computation than existing methods, with the power and speed advantage of JASPER increasing with the number of traits. JASPER is potentially applicable to a wide range of association testing applications, including for multiple disease traits, expression traits, image-derived traits and microbiome abundances. It allows for covariates, ascertainment and rare variants and is robust to phenotype model misspecification. We apply JASPER to analyze gene expression in the Framingham Heart Study, where, compared to alternative approaches, JASPER finds more significant associations, including several that indicate pleiotropic effects, some of which replicate previous results, while others have not previously been reported. Our results demonstrate the promise of JASPER for powerful multitrait analysis in structured samples.
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Affiliation(s)
- Joelle Mbatchou
- Regeneron Genetics Center, Tarrytown, NY 10591, USA
- Department of Statistics, The University of Chicago, Chicago, IL 60637, USA
| | - Mary Sara McPeek
- Department of Statistics, The University of Chicago, Chicago, IL 60637, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL 60637, USA
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42
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Soh PXY, Mmekwa N, Petersen DC, Gheybi K, van Zyl S, Jiang J, Patrick SM, Campbell R, Jaratlerdseri W, Mutambirwa SBA, Bornman MSR, Hayes VM. Prostate cancer genetic risk and associated aggressive disease in men of African ancestry. Nat Commun 2023; 14:8037. [PMID: 38052806 PMCID: PMC10697980 DOI: 10.1038/s41467-023-43726-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2023] [Accepted: 11/17/2023] [Indexed: 12/07/2023] Open
Abstract
African ancestry is a significant risk factor for prostate cancer and advanced disease. Yet, genetic studies have largely been conducted outside the context of Sub-Saharan Africa, identifying 278 common risk variants contributing to a multiethnic polygenic risk score, with rare variants focused on a panel of roughly 20 pathogenic genes. Based on this knowledge, we are unable to determine polygenic risk or differentiate prostate cancer status interrogating whole genome data for 113 Black South African men. To further assess for potentially functional common and rare variant associations, here we interrogate 247,780 exomic variants for 798 Black South African men using a case versus control or aggressive versus non-aggressive study design. Notable genes of interest include HCP5, RFX6 and H3C1 for risk, and MKI67 and KLF5 for aggressive disease. Our study highlights the need for further inclusion across the African diaspora to establish African-relevant risk models aimed at reducing prostate cancer health disparities.
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Affiliation(s)
- Pamela X Y Soh
- Ancestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Naledi Mmekwa
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Desiree C Petersen
- South African Medical Research Council Centre for Tuberculosis Research, Division of Molecular Biology and Human Genetics, Faculty of Medicine and Health Sciences, Stellenbosch University, Cape Town, South Africa
| | - Kazzem Gheybi
- Ancestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Smit van Zyl
- Faculty of Health Sciences, University of Limpopo, Turfloop Campus, South Africa
| | - Jue Jiang
- Ancestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Sean M Patrick
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | | | - Weerachai Jaratlerdseri
- Ancestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia
| | - Shingai B A Mutambirwa
- Department of Urology, Sefako Makgatho Health Science University, Dr George Mukhari Academic Hospital, Medunsa, South Africa
| | - M S Riana Bornman
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa
| | - Vanessa M Hayes
- Ancestry and Health Genomics Laboratory, Charles Perkins Centre, School of Medical Sciences, Faculty of Medicine and Health, University of Sydney, Camperdown, NSW, 2006, Australia.
- School of Health Systems and Public Health, University of Pretoria, Pretoria, South Africa.
- Faculty of Health Sciences, University of Limpopo, Turfloop Campus, South Africa.
- Manchester Cancer Research Centre, University of Manchester, Manchester, M20 4GJ, UK.
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43
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Stacey SN, Zink F, Halldorsson GH, Stefansdottir L, Gudjonsson SA, Einarsson G, Hjörleifsson G, Eiriksdottir T, Helgadottir A, Björnsdottir G, Thorgeirsson TE, Olafsdottir TA, Jonsdottir I, Gretarsdottir S, Tragante V, Magnusson MK, Jonsson H, Gudmundsson J, Olafsson S, Holm H, Gudbjartsson DF, Sulem P, Helgason A, Thorsteinsdottir U, Tryggvadottir L, Rafnar T, Melsted P, Ulfarsson MÖ, Vidarsson B, Thorleifsson G, Stefansson K. Genetics and epidemiology of mutational barcode-defined clonal hematopoiesis. Nat Genet 2023; 55:2149-2159. [PMID: 37932435 PMCID: PMC10703693 DOI: 10.1038/s41588-023-01555-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Accepted: 09/28/2023] [Indexed: 11/08/2023]
Abstract
Clonal hematopoiesis (CH) arises when a substantial proportion of mature blood cells is derived from a single hematopoietic stem cell lineage. Using whole-genome sequencing of 45,510 Icelandic and 130,709 UK Biobank participants combined with a mutational barcode method, we identified 16,306 people with CH. Prevalence approaches 50% in elderly participants. Smoking demonstrates a dosage-dependent impact on risk of CH. CH associates with several smoking-related diseases. Contrary to published claims, we find no evidence that CH is associated with cardiovascular disease. We provide evidence that CH is driven by genes that are commonly mutated in myeloid neoplasia and implicate several new driver genes. The presence and nature of a driver mutation alters the risk profile for hematological disorders. Nevertheless, most CH cases have no known driver mutations. A CH genome-wide association study identified 25 loci, including 19 not implicated previously in CH. Splicing, protein and expression quantitative trait loci were identified for CD164 and TCL1A.
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Affiliation(s)
| | | | - Gisli H Halldorsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | | | | | | | | | | | - Thorunn A Olafsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | - Ingileif Jonsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Immunology, Landspitali University Hospital, Reykjavik, Iceland
| | | | | | - Magnus K Magnusson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | | | - Hilma Holm
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
| | - Daniel F Gudbjartsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | | | - Agnar Helgason
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Department of Anthropology, University of Iceland, Reykjavik, Iceland
| | - Unnur Thorsteinsdottir
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
| | | | | | - Pall Melsted
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Magnus Ö Ulfarsson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland
- School of Engineering and Natural Sciences, University of Iceland, Reykjavik, Iceland
| | - Brynjar Vidarsson
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland
- Department of Hematology, Landspitali University Hospital, Reykjavik, Iceland
| | | | - Kari Stefansson
- deCODE genetics/Amgen Inc., Reykjavik, Iceland.
- Faculty of Medicine, School of Health Sciences, University of Iceland, Reykjavik, Iceland.
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44
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Martino J, Liu Q, Vukojevic K, Ke J, Lim TY, Khan A, Gupta Y, Perez A, Yan Z, Milo Rasouly H, Vena N, Lippa N, Giordano JL, Saraga M, Saraga-Babic M, Westland R, Bodria M, Piaggio G, Bendapudi PK, Iglesias AD, Wapner RJ, Tasic V, Wang F, Ionita-Laza I, Ghiggeri GM, Kiryluk K, Sampogna RV, Mendelsohn CL, D'Agati VD, Gharavi AG, Sanna-Cherchi S. Mouse and human studies support DSTYK loss of function as a low-penetrance and variable expressivity risk factor for congenital urinary tract anomalies. Genet Med 2023; 25:100983. [PMID: 37746849 DOI: 10.1016/j.gim.2023.100983] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/11/2023] [Revised: 09/14/2023] [Accepted: 09/17/2023] [Indexed: 09/26/2023] Open
Abstract
PURPOSE Previous work identified rare variants in DSTYK associated with human congenital anomalies of the kidney and urinary tract (CAKUT). Here, we present a series of mouse and human studies to clarify the association, penetrance, and expressivity of DSTYK variants. METHODS We phenotypically characterized Dstyk knockout mice of 3 separate inbred backgrounds and re-analyzed the original family segregating the DSTYK c.654+1G>A splice-site variant (referred to as "SSV" below). DSTYK loss of function (LOF) and SSVs were annotated in individuals with CAKUT, epilepsy, or amyotrophic lateral sclerosis vs controls. A phenome-wide association study analysis was also performed using United Kingdom Biobank (UKBB) data. RESULTS Results demonstrate ∼20% to 25% penetrance of obstructive uropathy, at least, in C57BL/6J and FVB/NJ Dstyk-/- mice. Phenotypic penetrance increased to ∼40% in C3H/HeJ mutants, with mild-to-moderate severity. Re-analysis of the original family segregating the rare SSV showed low penetrance (43.8%) and no alternative genetic causes for CAKUT. LOF DSTYK variants burden showed significant excess for CAKUT and epilepsy vs controls and an exploratory phenome-wide association study supported association with neurological disorders. CONCLUSION These data support causality for DSTYK LOF variants and highlights the need for large-scale sequencing studies (here >200,000 cases) to accurately assess causality for genes and variants to lowly penetrant traits with common population prevalence.
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Affiliation(s)
- Jeremiah Martino
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Qingxue Liu
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Katarina Vukojevic
- Department of Medicine, Columbia University Irving Medical Center, New York, NY; Department of Anatomy, Histology and Embryology, University of Split School of Medicine, Split, Croatia
| | - Juntao Ke
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Tze Y Lim
- Department of Medicine, Columbia University Irving Medical Center, New York, NY; Unit of Genomic Variability and Complex Diseases, Department of Medical Sciences, University of Turin, Turin, Italy
| | - Atlas Khan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Yask Gupta
- Department of Medicine, Columbia University Irving Medical Center, New York, NY; Institute for Inflammation Medicine, University of Lubeck, Germany
| | - Alejandra Perez
- Department of Medicine, Columbia University Irving Medical Center, New York, NY; Department of Urology, Mount Sinai Medical Center, Miami, FL
| | - Zonghai Yan
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Hila Milo Rasouly
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Natalie Vena
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Natalie Lippa
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Jessica L Giordano
- Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY
| | - Marijan Saraga
- Department of Pediatrics, University Hospital of Split, Split, Croatia; School of Medicine, University of Split, Split, Croatia
| | - Mirna Saraga-Babic
- Department of Anatomy, Histology and Embryology, University of Split School of Medicine, Split, Croatia
| | - Rik Westland
- Department of Pediatric Nephrology, Emma Children's Hospital, University of Amsterdam, Meibergdreef 9, Amsterdam, The Netherlands
| | - Monica Bodria
- Division of Nephrology and Renal Transplantation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Laboratory on Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Giorgio Piaggio
- Division of Nephrology and Renal Transplantation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Laboratory on Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Pavan K Bendapudi
- Division of Hematology and Blood Transfusion Service, Massachusetts General Hospital, Boston, MA; Division of Hemostasis and Thrombosis, Beth Israel Deaconess Medical Center, Boston, MA; Harvard Medical School, Boston, MA
| | - Alejandro D Iglesias
- Department of Pediatrics, Columbia University Vagelos College of Physicians and Surgeons, New York, NY
| | - Ronald J Wapner
- Obstetrics and Gynecology, Columbia University Irving Medical Center, New York, NY
| | - Velibor Tasic
- Medical Faculty of Skopje, University Children's Hospital, Skopje, Macedonia
| | - Fan Wang
- Department of Biostatistics, Columbia University, New York, NY
| | | | - Gian Marco Ghiggeri
- Division of Nephrology and Renal Transplantation, IRCCS Istituto Giannina Gaslini, Genoa, Italy; Laboratory on Molecular Nephrology, IRCCS Istituto Giannina Gaslini, Genoa, Italy
| | - Krzysztof Kiryluk
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Rosemary V Sampogna
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Cathy L Mendelsohn
- Department of Urology, Columbia University Irving Medical Center, New York, NY; Department of Pathology and Cell Biology, Columbia University Irving Medical Center, New York, NY; Department of Genetics and Development, Columbia University Irving Medical Center, New York, NY; Columbia Stem Cell Initiative, Columbia University Irving Medical Center, New York, NY
| | - Vivette D D'Agati
- The Renal Pathology Laboratory of the Department of Pathology and Cell Biology, Columbia University, New York, NY
| | - Ali G Gharavi
- Department of Medicine, Columbia University Irving Medical Center, New York, NY
| | - Simone Sanna-Cherchi
- Department of Medicine, Columbia University Irving Medical Center, New York, NY.
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de Vries PS, Conomos MP, Singh K, Nicholson CJ, Jain D, Hasbani NR, Jiang W, Lee S, Lino Cardenas CL, Lutz SM, Wong D, Guo X, Yao J, Young EP, Tcheandjieu C, Hilliard AT, Bis JC, Bielak LF, Brown MR, Musharoff S, Clarke SL, Terry JG, Palmer ND, Yanek LR, Xu H, Heard-Costa N, Wessel J, Selvaraj MS, Li RH, Sun X, Turner AW, Stilp AM, Khan A, Newman AB, Rasheed A, Freedman BI, Kral BG, McHugh CP, Hodonsky C, Saleheen D, Herrington DM, Jacobs DR, Nickerson DA, Boerwinkle E, Wang FF, Heiss G, Jun G, Kinney GL, Sigurslid HH, Doddapaneni H, Hall IM, Bensenor IM, Broome J, Crapo JD, Wilson JG, Smith JA, Blangero J, Vargas JD, Mosquera JV, Smith JD, Viaud-Martinez KA, Ryan KA, Young KA, Taylor KD, Lange LA, Emery LS, Bittencourt MS, Budoff MJ, Montasser ME, Yu M, Mahaney MC, Mahamdeh MS, Fornage M, Franceschini N, Lotufo PA, Natarajan P, Wong Q, Mathias RA, Gibbs RA, Do R, Mehran R, Tracy RP, Kim RW, Nelson SC, Damrauer SM, Kardia SL, Rich SS, Fuster V, Napolioni V, Zhao W, Tian W, Yin X, Min YI, Manning AK, Peloso G, Kelly TN, O’Donnell CJ, Morrison AC, Curran JE, Zapol WM, Bowden DW, Becker LC, Correa A, Mitchell BD, Psaty BM, Carr JJ, Pereira AC, Assimes TL, Stitziel NO, Hokanson JE, Laurie CA, Rotter JI, Vasan RS, Post WS, Peyser PA, Miller CL, Malhotra R. Whole-genome sequencing uncovers two loci for coronary artery calcification and identifies ARSE as a regulator of vascular calcification. NATURE CARDIOVASCULAR RESEARCH 2023; 2:1159-1172. [PMID: 38817323 PMCID: PMC11138106 DOI: 10.1038/s44161-023-00375-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/13/2022] [Accepted: 10/25/2023] [Indexed: 06/01/2024]
Abstract
Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.
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Affiliation(s)
- Paul S. de Vries
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Matthew P. Conomos
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Kuldeep Singh
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Christopher J. Nicholson
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Deepti Jain
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Natalie R. Hasbani
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Wanlin Jiang
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Sujin Lee
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Christian L Lino Cardenas
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Sharon M. Lutz
- PRecisiOn Medicine Translational Research (PROMoTeR)
Center, Department of Population Medicine, Harvard Medical School and Harvard
Pilgrim Health Care Institute, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of
Public Health, Boston, MA, USA
| | - Doris Wong
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Xiuqing Guo
- The Institute for Translational Genomics and Population
Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Jie Yao
- The Institute for Translational Genomics and Population
Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Erica P. Young
- Cardiovascular Division, Department of Internal Medicine,
Washington University School of Medicine, St. Louis, MO, USA
| | - Catherine Tcheandjieu
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - Austin T. Hilliard
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Palo Alto Veterans Institute for Research, Palo Alto, CA,
USA
| | - Joshua C. Bis
- Cardiovascular Health Research Unit, Department of
Medicine, University of Washington, Seattle, WA, USA
| | - Lawrence F. Bielak
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Michael R. Brown
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Shaila Musharoff
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Genetics, Stanford University School of
Medicine, Stanford, CA, USA
| | - Shoa L. Clarke
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - James G. Terry
- Department of Radiology, Vanderbilt Translational and
Clinical Cardiovascular Research Center, Vanderbilt University Medical Center,
Nashville, TN, USA
| | - Nicholette D. Palmer
- Department of Biochemistry, Wake Forest School of
Medicine, Winston-Salem, NC, USA
| | - Lisa R. Yanek
- Division of General Internal Medicine, Department of
Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Huichun Xu
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Nancy Heard-Costa
- Boston University School of Medicine, Boston, MA,
USA
- Boston University and National Heart, Lung, and Blood
Institute’s Framingham Heart Study, Framingham, MA, USA
| | - Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public
Health, Indiana University, Indianapolis, IN, USA
- Diabetes Translational Research Center, Indiana
University, Indianapolis, IN, USA
| | - Margaret Sunitha Selvaraj
- Cardiovascular Research Center and Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad
Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston,
MA, USA
| | - Rebecca H. Li
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Xiao Sun
- School of Public Health and Tropical Medicine, Department
of Epidemiology, Tulane University, New Orleans, LA, USA
- College of Medicine, Department of Medicine, Division of
Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Adam W. Turner
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Adrienne M. Stilp
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Alyna Khan
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Anne B. Newman
- Department of Epidemiology, Graduate School of Public
Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Asif Rasheed
- Center For Non-Communicable Diseases, Karachi,
Pakistan
| | - Barry I Freedman
- Section on Nephrology, Department of Internal Medicine,
Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Brian G. Kral
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Caitlin P. McHugh
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Chani Hodonsky
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Danish Saleheen
- Center For Non-Communicable Diseases, Karachi,
Pakistan
- Department of Medicine, Columbia University Irving
Medical Center, New York, NY, USA
- Department of Cardiology, Columbia University Irving
Medical Center, New York, NY, USA
| | - David M. Herrington
- Department of Internal Medicine, Section of
Cardiovascular Medicine, Wake Forest School of Medicine, Winston-Salem, NC,
USA
| | - David R. Jacobs
- Division of Epidemiology and Community Health, University
of Minnesota School of Public Health, Minneapolis, MN, USA
| | - Deborah A. Nickerson
- Department of Genome Sciences, University of Washington,
Seattle, WA, USA
- Northwest Genomics Center, University of Washington,
Seattle, WA, USA
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
- Human Genome Sequencing Center, Baylor College of
Medicine, Houston, TX, USA
| | - Fei Fei Wang
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Gerardo Heiss
- Department of Epidemiology, Gillings School of Global
Public Health, University of North Carolina, Chapel Hill, NC, USA
| | - Goo Jun
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Greg L. Kinney
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Haakon H. Sigurslid
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | | | - Ira M. Hall
- Yale Center for Genomic Health, Yale School of Medicine,
New Haven, CT, USA
| | - Isabela M. Bensenor
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Jai Broome
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - James D. Crapo
- Department of Medicine, National Jewish Health, Denver,
CO, USA
| | - James G. Wilson
- Division of Cardiology, Beth Israel Deaconess Medical
Center, Boston, MA, USA
| | - Jennifer A. Smith
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
- Survey Research Center, Institute for Social Research,
University of Michigan, Ann Arbor, MI, USA
| | - John Blangero
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Jose D. Vargas
- Medstar Heart and Vascular Institute, Medstar Georgetown
University Hospital, Washington, DC, USA
| | - Jose Verdezoto Mosquera
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Joshua D. Smith
- Department of Genome Sciences, University of Washington,
Seattle, WA, USA
- Northwest Genomics Center, University of Washington,
Seattle, WA, USA
| | | | - Kathleen A. Ryan
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Kendra A. Young
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Kent D. Taylor
- The Institute for Translational Genomics and Population
Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Leslie A. Lange
- Department of Medicine, University of Colorado Denver,
Anschutz Medical Campus, Aurora, CO, USA
| | - Leslie S. Emery
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Marcio S. Bittencourt
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Matthew J. Budoff
- Department of Medicine, The Lundquist Institute for
Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - May E. Montasser
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
| | - Miao Yu
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Michael C. Mahaney
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Mohammed S Mahamdeh
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Myriam Fornage
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
- Institute of Molecular Medicine, McGovern Medical School,
The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Nora Franceschini
- Department of Epidemiology, Gillings School of Global
Public health, University of North Carolina, Chapel Hill, NC, USA
| | - Paulo A. Lotufo
- Center for Clinical and Epidemiological Research,
University Hospital, University of Sao Paulo Medical School, São Paulo, Brazil
| | - Pradeep Natarajan
- Cardiovascular Research Center and Center for Genomic
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Program in Medical and Population Genetics, Broad
Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston,
MA, USA
| | - Quenna Wong
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Rasika A. Mathias
- Division of General Internal Medicine, Department of
Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Division of Allergy and Clinical Immunology, Department
of Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of
Medicine, Houston, TX, USA
- Department of Molecular and Human Genetics, Baylor
College of Medicine, Houston, TX, USA
| | - Ron Do
- The Charles Bronfman Institute for Personalized Medicine,
Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School
of Medicine at Mount Sinai, New York, NY, USA
| | - Roxana Mehran
- Icahn School of Medicine at Mount Sinai, New York, NY,
USA
| | - Russell P. Tracy
- Department of Pathology and Laboratory Medicine, Robert
Larner, M.D. College of Medicine, University of Vermont, Burlington, VT, USA
| | | | - Sarah C. Nelson
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Scott M. Damrauer
- Corporal Michael J. Crescenz VA Medical Center,
Philadelphia, PA, USA
- Department of Surgery, Perelman School of Medicine,
University of Pennsylvania, Philadelphia, PA, USA
| | - Sharon L.R. Kardia
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Stephen S. Rich
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Valentin Fuster
- Centro Nacional de Investigaciones Cardiovasculares
Carlos III, Madrid, Spain
- Mount Sinai Heart Center, New York, NY, USA
| | - Valerio Napolioni
- Genomic And Molecular Epidemiology (GAME) Lab, School of
Biosciences and Veterinary Medicine, University of Camerino, Camerino, Italy
| | - Wei Zhao
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Wenjie Tian
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
| | - Xianyong Yin
- Department of Biostatistics and Center for Statistical
Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Yuan-I Min
- Jackson Heart Study, Department of Medicine, University
of Mississippi Medical Center, Jackson, MS, USA
| | - Alisa K. Manning
- Clinical and Translation Epidemiology Unit, Department of
Medicine, Massachusetts General Hospital, Boston, MA, USA
- Programs in Metabolism and Medical and Population
Genetics, Broad Institute, Cambridge, MA, USA
| | - Gina Peloso
- Department of Biostatistics, Boston University School of
Public Health, Boston, MA, USA
| | - Tanika N. Kelly
- College of Medicine, Department of Medicine, Division of
Nephrology, University of Illinois Chicago, Chicago, IL, USA
| | - Christopher J. O’Donnell
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital,
Boston, MA, USA
| | - Alanna C. Morrison
- Human Genetics Center, Department of Epidemiology, Human
Genetics, and Environmental Sciences, School of Public Health, The University of
Texas Health Science Center at Houston, Houston, TX, USA
| | - Joanne E. Curran
- Department of Human Genetics, University of Texas Rio
Grande Valley School of Medicine, Brownsville, TX, USA
- South Texas Diabetes and Obesity Institute, University of
Texas Rio Grande Valley School of Medicine, Brownsville, TX, USA
| | - Warren M. Zapol
- Department of Anesthesia, Critical Care and Pain Medicine
at Massachusetts General Hospital, Boston, MA, USA
| | - Donald W. Bowden
- Department of Biochemistry, Wake Forest School of
Medicine, Winston-Salem, NC, USA
| | - Lewis C. Becker
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Adolfo Correa
- Jackson Heart Study, Department of Medicine, University
of Mississippi Medical Center, Jackson, MS, USA
- Department of Population Health Science, University of
Mississippi Medical Center, Jackson, MS, USA
| | - Braxton D. Mitchell
- Division of Endocrinology, Diabetes and Nutrition,
Department of Medicine, University of Maryland School of Medicine, Baltimore, MD,
USA
- Geriatrics Research and Education Clinical Center,
Baltimore Veterans Administration Medical Center, Baltimore, MD, USA
| | - Bruce M. Psaty
- Cardiovascular Health Research Unit, Department of
Medicine, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington,
Seattle, WA, USA
- Department of Health Services, University of Washington,
Seattle, WA, USA
| | - John Jeffrey Carr
- Department of Radiology, Vanderbilt Translational and
Clinical Cardiovascular Research Center, Vanderbilt University Medical Center,
Nashville, TN, USA
| | - Alexandre C. Pereira
- Department of Genetics, Harvard Medical School, Boston,
MA, USA
- Laboratory of Genetics and Molecular Cardiology, Heart
Institute, University of São Paulo, São Paulo, Brazil
| | - Themistocles L. Assimes
- VA Palo Alto Healthcare System, Palo Alto, CA, USA
- Department of Medicine, Stanford University School of
Medicine, Stanford, CA, USA
| | - Nathan O. Stitziel
- Cardiovascular Division, Department of Internal Medicine,
Washington University School of Medicine, St. Louis, MO, USA
- Department of Genetics, Washington University School of
Medicine, St. Louis, MO, USA
- McDonnell Genome Institute, Washington University School
of Medicine, St. Louis, MO, USA
| | - John E. Hokanson
- Department of Epidemiology, Colorado School of Public
Health, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Cecelia A. Laurie
- Genetic Analysis Center, Department of Biostatistics,
School of Public Health, University of Washington, Seattle, WA, USA
| | - Jerome I. Rotter
- The Institute for Translational Genomics and Population
Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical
Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Ramachandran S. Vasan
- Boston University and National Heart, Lung, and Blood
Institute’s Framingham Heart Study, Framingham, MA, USA
- Department of Medicine, Boston University School of
Medicine, Boston, MA, USA
- Department of Epidemiology, Boston University School of
Public Health, Boston, MA, USA
| | - Wendy S. Post
- Division of Cardiology, Department of Medicine, Johns
Hopkins University School of Medicine, Baltimore, MD, USA
| | - Patricia A. Peyser
- School of Public Health, Department of Epidemiology,
University of Michigan, Ann Arbor, MI, USA
| | - Clint L. Miller
- Center for Public Health Genomics, University of Virginia
School of Medicine, Charlottesville, VA, USA
| | - Rajeev Malhotra
- Cardiovascular Research Center, Division of Cardiology,
Department of Medicine, Massachusetts General Hospital, Harvard Medical School,
Boston, MA, USA
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Lopera-Maya EA, Li S, de Brouwer R, Nolte IM, van Breen J, Jongbloed JDH, Swertz MA, Snieder H, Franke L, Wijmenga C, de Boer RA, Deelen P, van der Zwaag PA, Sanna S. Phenotypic and Genetic Factors Associated with Absence of Cardiomyopathy Symptoms in PLN:c.40_42delAGA Carriers. J Cardiovasc Transl Res 2023; 16:1251-1266. [PMID: 36622581 PMCID: PMC10721704 DOI: 10.1007/s12265-022-10347-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Accepted: 12/14/2022] [Indexed: 01/10/2023]
Abstract
The c.40_42delAGA variant in the phospholamban gene (PLN) has been associated with dilated and arrhythmogenic cardiomyopathy, with up to 70% of carriers experiencing a major cardiac event by age 70. However, there are carriers who remain asymptomatic at older ages. To understand the mechanisms behind this incomplete penetrance, we evaluated potential phenotypic and genetic modifiers in 74 PLN:c.40_42delAGA carriers identified in 36,339 participants of the Lifelines population cohort. Asymptomatic carriers (N = 48) showed shorter QRS duration (- 5.73 ms, q value = 0.001) compared to asymptomatic non-carriers, an effect we could replicate in two different independent cohorts. Furthermore, symptomatic carriers showed a higher correlation (rPearson = 0.17) between polygenic predisposition to higher QRS (PGSQRS) and QRS (p value = 1.98 × 10-8), suggesting that the effect of the genetic variation on cardiac rhythm might be increased in symptomatic carriers. Our results allow for improved clinical interpretation for asymptomatic carriers, while our approach could guide future studies on genetic diseases with incomplete penetrance.
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Affiliation(s)
- Esteban A Lopera-Maya
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Shuang Li
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Remco de Brouwer
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Ilja M Nolte
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Justin van Breen
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Jan D H Jongbloed
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Morris A Swertz
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Genomics Coordination Center, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Harold Snieder
- Department of Epidemiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Lude Franke
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Rudolf A de Boer
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
| | - Patrick Deelen
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands
- Oncode Institute, Utrecht, Netherlands
| | - Paul A van der Zwaag
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
| | - Serena Sanna
- Department of Genetics, University Medical Center Groningen, University of Groningen, Groningen, Netherlands.
- Institute for Genetic and Biomedical Research (IRGB), National Research Council (CNR), Cagliari, Italy.
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Liu Z, Xu J, Tan J, Li X, Zhang F, Ouyang W, Wang S, Huang Y, Li S, Pan X. Genetic overlap for ten cardiovascular diseases: A comprehensive gene-centric pleiotropic association analysis and Mendelian randomization study. iScience 2023; 26:108150. [PMID: 37908310 PMCID: PMC10613921 DOI: 10.1016/j.isci.2023.108150] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Revised: 08/13/2023] [Accepted: 10/02/2023] [Indexed: 11/02/2023] Open
Abstract
Recent studies suggest that pleiotropic effects may explain the genetic architecture of cardiovascular diseases (CVDs). We conducted a comprehensive gene-centric pleiotropic association analysis for ten CVDs using genome-wide association study (GWAS) summary statistics to identify pleiotropic genes and pathways that may underlie multiple CVDs. We found shared genetic mechanisms underlying the pathophysiology of CVDs, with over two-thirds of the diseases exhibiting common genes and single-nucleotide polymorphisms (SNPs). Significant positive genetic correlations were observed in more than half of paired CVDs. Additionally, we investigated the pleiotropic genes shared between different CVDs, as well as their functional pathways and distribution in different tissues. Moreover, six hub genes, including ALDH2, XPO1, HSPA1L, ESR2, WDR12, and RAB1A, as well as 26 targeted potential drugs, were identified. Our study provides further evidence for the pleiotropic effects of genetic variants on CVDs and highlights the importance of considering pleiotropy in genetic association studies.
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Affiliation(s)
- Zeye Liu
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Jing Xu
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Jiangshan Tan
- Key Laboratory of Pulmonary Vascular Medicine, National Clinical Research Center of Cardiovascular Diseases, State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - Xiaofei Li
- Department of Cardiology, Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing, China
| | - Fengwen Zhang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Wenbin Ouyang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Shouzheng Wang
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
| | - Yuan Huang
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Pediatric Cardiac Surgery Center, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Shoujun Li
- State Key Laboratory of Cardiovascular Disease, Fuwai Hospital, National Center for Cardiovascular Diseases, Pediatric Cardiac Surgery Center, Fuwai Hospital, Chinese Academy of Medical Sciences, and Peking Union Medical College, Beijing, China
| | - Xiangbin Pan
- Department of Structural Heart Disease, National Center for Cardiovascular Disease, China & Fuwai Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Beijing 100037, China
- National Health Commission Key Laboratory of Cardiovascular Regeneration Medicine, Beijing 100037, China
- Key Laboratory of Innovative Cardiovascular Devices, Chinese Academy of Medical Sciences, Beijing 100037, China
- National Clinical Research Center for Cardiovascular Diseases, Fuwai Hospital, Chinese Academy of Medical Sciences, Beijing 100037, China
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48
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Dichgans M, Malik R, Beaufort N, Tanaka K, Georgakis M, He Y, Koido M, Terao C, Anderson C, Kamatani Y. Genetically proxied HTRA1 protease activity and circulating levels independently predict risk of ischemic stroke and coronary artery disease. RESEARCH SQUARE 2023:rs.3.rs-3523612. [PMID: 37986915 PMCID: PMC10659557 DOI: 10.21203/rs.3.rs-3523612/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/22/2023]
Abstract
HTRA1 has emerged as a major risk gene for stroke and cerebral small vessel disease with both rare and common variants contributing to disease risk. However, the precise mechanisms mediating this risk remain largely unknown as does the full spectrum of phenotypes associated with genetic variation in HTRA1 in the general population. Using a family-history informed approach, we first show that rare variants in HTRA1 are linked to ischemic stroke in 425,338 European individuals from the UK Biobank with replication in 143,149 individuals from the Biobank Japan. Integrating data from biochemical experiments on 76 mutations occurring in the UK Biobank, we next show that rare variants causing loss of protease function in vitro associate with ischemic stroke, coronary artery disease, and skeletal traits. In addition, a common causal variant (rs2672592) modulating circulating HTRA1 mRNA and protein levels enhances the risk of ischemic stroke, small vessel stroke, and coronary artery disease while lowering the risk of migraine and age-related macular dystrophy in GWAS and UK Biobank data from > 2,000,000 individuals. There was no evidence of an interaction between genetically proxied HTRA1 activity and levels. Our findings demonstrate a central role of HTRA1 for human disease including stroke and coronary artery disease and identify two independent mechanisms that might qualify as targets for future therapeutic interventions.
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Affiliation(s)
| | | | | | | | | | | | - Masaru Koido
- Institute of Medical Science, The University of Tokyo
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49
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Makarious MB, Lake J, Pitz V, Ye Fu A, Guidubaldi JL, Solsberg CW, Bandres-Ciga S, Leonard HL, Kim JJ, Billingsley KJ, Grenn FP, Jerez PA, Alvarado CX, Iwaki H, Ta M, Vitale D, Hernandez D, Torkamani A, Ryten M, Hardy J, Scholz SW, Traynor BJ, Dalgard CL, Ehrlich DJ, Tanaka T, Ferrucci L, Beach TG, Serrano GE, Real R, Morris HR, Ding J, Gibbs JR, Singleton AB, Nalls MA, Bhangale T, Blauwendraat C. Large-scale rare variant burden testing in Parkinson's disease. Brain 2023; 146:4622-4632. [PMID: 37348876 PMCID: PMC10629770 DOI: 10.1093/brain/awad214] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2022] [Revised: 05/01/2023] [Accepted: 05/30/2023] [Indexed: 06/24/2023] Open
Abstract
Parkinson's disease has a large heritable component and genome-wide association studies have identified over 90 variants with disease-associated common variants, providing deeper insights into the disease biology. However, there have not been large-scale rare variant analyses for Parkinson's disease. To address this gap, we investigated the rare genetic component of Parkinson's disease at minor allele frequencies <1%, using whole genome and whole exome sequencing data from 7184 Parkinson's disease cases, 6701 proxy cases and 51 650 healthy controls from the Accelerating Medicines Partnership Parkinson's disease (AMP-PD) initiative, the National Institutes of Health, the UK Biobank and Genentech. We performed burden tests meta-analyses on small indels and single nucleotide protein-altering variants, prioritized based on their predicted functional impact. Our work identified several genes reaching exome-wide significance. Two of these genes, GBA1 and LRRK2, have variants that have been previously implicated as risk factors for Parkinson's disease, with some variants in LRRK2 resulting in monogenic forms of the disease. We identify potential novel risk associations for variants in B3GNT3, AUNIP, ADH5, TUBA1B, OR1G1, CAPN10 and TREML1 but were unable to replicate the observed associations across independent datasets. Of these, B3GNT3 and TREML1 could provide new evidence for the role of neuroinflammation in Parkinson's disease. To date, this is the largest analysis of rare genetic variants in Parkinson's disease.
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Affiliation(s)
- Mary B Makarious
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Julie Lake
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Vanessa Pitz
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Allen Ye Fu
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Department of Cell Biology and Neuroscience, Rutgers University, Piscataway, NJ 08854, USA
| | - Joseph L Guidubaldi
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Caroline Warly Solsberg
- Memory and Aging Center, Department of Neurology, University of California San Francisco, San Francisco, CA 94158, USA
- Pharmaceutical Sciences and Pharmacogenomics, University of California San Francisco, San Francisco, CA 94143, USA
| | - Sara Bandres-Ciga
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Hampton L Leonard
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Jonggeol Jeffrey Kim
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Preventive Neurology Unit, Wolfson Institute of Preventive Medicine, Queen Mary University of London, London EC1M 6BQ, UK
| | - Kimberley J Billingsley
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Francis P Grenn
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Pilar Alvarez Jerez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Chelsea X Alvarado
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Hirotaka Iwaki
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Michael Ta
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Dan Vitale
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Dena Hernandez
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Ali Torkamani
- Department of Integrative Structural and Computational Biology, Scripps Research Institute, La Jolla, CA 92037, USA
| | - Mina Ryten
- NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London WC1N 1EH, UK
- Department of Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1N 1EH, UK
| | - John Hardy
- UK Dementia Research Institute and Department of Neurodegenerative Disease and Reta Lila Weston Institute, UCL Queen Square Institute of Neurology and UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
- Institute for Advanced Study, The Hong Kong University of Science and Technology, Hong Kong SAR, China
| | | | - Sonja W Scholz
- Neurodegenerative Diseases Research Unit, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20814, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD 21287, USA
| | - Bryan J Traynor
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Department of Neurology, Johns Hopkins University Medical Center, Baltimore, MD 21287, USA
| | - Clifton L Dalgard
- The American Genome Center, Uniformed Services University of the Health Sciences, Bethesda, MD 20814, USA
| | - Debra J Ehrlich
- Parkinson’s Disease Clinic, Office of the Clinical Director, National Institute of Neurological Disorders and Stroke, Bethesda, MD 20814, USA
| | - Toshiko Tanaka
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Luigi Ferrucci
- Translational Gerontology Branch, National Institute on Aging, NIH, Baltimore, MD 21224, USA
| | - Thomas G Beach
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Geidy E Serrano
- Civin Laboratory for Neuropathology, Banner Sun Health Research Institute, Sun City, AZ 85351, USA
| | - Raquel Real
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Huw R Morris
- Department of Clinical and Movement Neurosciences, UCL Queen Square Institute of Neurology, London WC1N 3BG, UK
- UCL Movement Disorders Centre, University College London, London WC1N 3BG, UK
| | - Jinhui Ding
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - J Raphael Gibbs
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
| | - Andrew B Singleton
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
| | - Mike A Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
- Data Tecnica International, Washington, DC 20812, USA
| | - Tushar Bhangale
- Department of Human Genetics, Genentech, Inc., South San Francisco, CA 94080, USA
| | - Cornelis Blauwendraat
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Integrative Neurogenomics Unit, Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD 20814, USA
- Center for Alzheimer's and Related Dementias (CARD), National Institute on Aging and National Institute of Neurological Disorders and Stroke, National Institutes of Health, Bethesda, MD 20814, USA
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50
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Choi YH, Lim Y, Jang DK, Ahn DW, Ryu JK, Paik WH, Kim YT, Kim JH, Lee SH. Genetic susceptibility to post-endoscopic retrograde cholangiopancreatography pancreatitis identified in propensity score-matched analysis. Korean J Intern Med 2023; 38:854-864. [PMID: 37867141 PMCID: PMC10636551 DOI: 10.3904/kjim.2022.404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/23/2022] [Revised: 05/02/2023] [Accepted: 06/16/2023] [Indexed: 10/24/2023] Open
Abstract
BACKGROUND/AIMS A previous history of post-endoscopic retrograde cholangiopancreatography (ERCP) pancreatitis (PEP) is a risk factor for PEP, suggesting that there may be a genetic predisposition to PEP. However, nothing is known about this yet. The aim of this study was to identify genetic variations associated with PEP. METHODS A cohort of high-risk PEP patients was queried from December 2016 to January 2019. For each PEP case, two propensity score-matched controls were selected. Whole exome sequencing was performed using blood samples. Genetic variants reported to be related to pancreatitis were identified. To discover genetic variants that predispose to PEP, a logistic regression analysis with clinical adjustment was performed. Gene-wise analyses were also conducted. RESULTS Totals of 25 PEP patients and 50 matched controls were enrolled. Among the genetic variants reported to be associated with pancreatitis, only CASR rs1042636 was identified, and it showed no significant difference between the case and control groups. A total of 54,269 non-synonymous variants from 14,313 genes was identified. Logistic regression analysis of these variants showed that the IRF2BP1 rs60158447 GC genotype was significantly associated with the occurrence of PEP (odds ratio 2.248, FDR q value = 0.005). Gene-wise analyses did not show any significant results. CONCLUSION This study found that the IRF2BP1 gene variant was significantly associated with PEP. This genetic variant is a highly targeted PEP risk factor candidate and can be used for screening high-risk PEP groups before ERCP through future validation. (ClinicalTrials.gov no. NCT02928718).
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Affiliation(s)
- Young Hoon Choi
- Department of Internal Medicine, College of Medicine, The Catholic University of Korea, Seoul,
Korea
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul,
Korea
| | - Younggyun Lim
- Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul,
Korea
| | - Dong Kee Jang
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul,
Korea
- Department of Internal Medicine, Dongguk University Ilsan Hospital, Dongguk University College of Medicine, Goyang,
Korea
| | - Dong-Won Ahn
- Department of Internal Medicine, Seoul Metropolitan Government Seoul National University Boramae Medical Center, Seoul National University College of Medicine, Seoul,
Korea
| | - Ji Kon Ryu
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul,
Korea
| | - Woo Hyun Paik
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul,
Korea
| | - Yong-Tae Kim
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul,
Korea
| | - Ju Han Kim
- Seoul National University Biomedical Informatics (SNUBI), Division of Biomedical Informatics, Seoul National University College of Medicine, Seoul,
Korea
| | - Sang Hyub Lee
- Department of Internal Medicine and Liver Research Institute, Seoul National University Hospital, Seoul National University College of Medicine, Seoul,
Korea
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