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Martin SS, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Barone Gibbs B, Beaton AZ, Boehme AK, Commodore-Mensah Y, Currie ME, Elkind MSV, Evenson KR, Generoso G, Heard DG, Hiremath S, Johansen MC, Kalani R, Kazi DS, Ko D, Liu J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Perman SM, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Tsao CW, Urbut SM, Van Spall HGC, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Palaniappan LP. 2024 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association. Circulation 2024; 149:e347-e913. [PMID: 38264914 DOI: 10.1161/cir.0000000000001209] [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] [Indexed: 01/25/2024]
Abstract
BACKGROUND The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2024 AHA Statistical Update is the product of a full year's worth of effort in 2023 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. The AHA strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional global data, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Yasmin, O’Shaughnessy KM. Genetic Markers Regulating Blood Pressure in Extreme Discordant Sib Pairs. Genes (Basel) 2023; 14:1862. [PMID: 37895212 PMCID: PMC10606487 DOI: 10.3390/genes14101862] [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: 07/31/2023] [Revised: 09/19/2023] [Accepted: 09/19/2023] [Indexed: 10/29/2023] Open
Abstract
Genome-wide scans performed in affected sib pairs have revealed small and often inconsistent clues to the loci responsible for the inherited components of hypertension. Since blood pressure is a quantitative trait regulated by many loci, two siblings at opposite extremes of the blood pressure distribution are more likely to have inherited different alleles at any given locus. Hence, we investigated an extreme discordant sib pair strategy to analyse markers from two previous loci of interest: (1) the Gordons syndrome locus that includes the WNK4 gene and (2) the ROMK locus identified in our first genome-wide scan. For this study, 24 sib pairs with strong family histories of essential hypertension were selected from the top and bottom 10% of the blood pressure distribution and genotyped for highly polymorphic microsatellite markers on chromosomes 11 and 17. The mean age of the population was 39.8 ± 7.8 years. A significant inverse correlation was found between the squared difference in pulse pressure and the number of alleles shared by IBD between the siblings for the DS11925 marker (r = -0.44, p = 0.031), systolic pressure and chromosome 17 markers (D17S250: r = -0.42, p = 0.040; D17S799 (r = -0.51, p = 0.011), and this relationship persisted after correcting for age and gender. Markers on chromosome 17 (D17S250, D17S928 and D17S1301) and 11 (D11S1999) also correlated with diastolic pressure. These results illustrate the successful use of discordant sib pair analysis to detect linkage within relatively small numbers of pedigrees with hypertension. Further analysis of this cohort may be valuable in complementing findings from the large genome wide scans in affected sib pairs.
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Affiliation(s)
- Yasmin
- Experimental Medicine & Immunotherapeutics Division, Department of Medicine, University of Cambridge, Cambridge CB2 0QQ, UK
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Tsao CW, Aday AW, Almarzooq ZI, Anderson CAM, Arora P, Avery CL, Baker-Smith CM, Beaton AZ, Boehme AK, Buxton AE, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Fugar S, Generoso G, Heard DG, Hiremath S, Ho JE, Kalani R, Kazi DS, Ko D, Levine DA, Liu J, Ma J, Magnani JW, Michos ED, Mussolino ME, Navaneethan SD, Parikh NI, Poudel R, Rezk-Hanna M, Roth GA, Shah NS, St-Onge MP, Thacker EL, Virani SS, Voeks JH, Wang NY, Wong ND, Wong SS, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2023 Update: A Report From the American Heart Association. Circulation 2023; 147:e93-e621. [PMID: 36695182 DOI: 10.1161/cir.0000000000001123] [Citation(s) in RCA: 1209] [Impact Index Per Article: 1209.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/26/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2023 Statistical Update is the product of a full year's worth of effort in 2022 by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. The American Heart Association strives to further understand and help heal health problems inflicted by structural racism, a public health crisis that can significantly damage physical and mental health and perpetuate disparities in access to health care, education, income, housing, and several other factors vital to healthy lives. This year's edition includes additional COVID-19 (coronavirus disease 2019) publications, as well as data on the monitoring and benefits of cardiovascular health in the population, with an enhanced focus on health equity across several key domains. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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Abstract
Sickle cell disease (SCD) is the most-common monogenic recessive disease in humans, annually affecting almost 300,000 newborns worldwide, 75% of whom live in Africa. Genomics research can accelerate the development of curative therapies for SCD in three ways. First, research should explore the missing heritability of foetal haemoglobin (HbF) - the strongest known modifier of SCD clinical expression - among highly genetically heterogenous and understudied African populations, to provide novel therapeutics targets for HbF induction. Second, SCD research should invest in RNA therapies, either by using microRNA to target the production of HbF proteins by binding to the transcription machinery in a cell, or by directly mediating production of HbF or adult haemoglobin through injection of messenger RNA. Third, investigators should aim to identify currently unknown genetic risk factors for SCD cardiovascular complications, which will address mortality, particularly in adults. Now is the time for global research programs to uncover genomic keys to unlock SCD therapeutics.
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Affiliation(s)
- Ambroise Wonkam
- McKusick-Nathans Institute and Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA
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5
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Kelly TN, Sun X, He KY, Brown MR, Taliun SAG, Hellwege JN, Irvin MR, Mi X, Brody JA, Franceschini N, Guo X, Hwang SJ, de Vries PS, Gao Y, Moscati A, Nadkarni GN, Yanek LR, Elfassy T, Smith JA, Chung RH, Beitelshees AL, Patki A, Aslibekyan S, Blobner BM, Peralta JM, Assimes TL, Palmas WR, Liu C, Bress AP, Huang Z, Becker LC, Hwa CM, O'Connell JR, Carlson JC, Warren HR, Das S, Giri A, Martin LW, Craig Johnson W, Fox ER, Bottinger EP, Razavi AC, Vaidya D, Chuang LM, Chang YPC, Naseri T, Jain D, Kang HM, Hung AM, Srinivasasainagendra V, Snively BM, Gu D, Montasser ME, Reupena MS, Heavner BD, LeFaive J, Hixson JE, Rice KM, Wang FF, Nielsen JB, Huang J, Khan AT, Zhou W, Nierenberg JL, Laurie CC, Armstrong ND, Shi M, Pan Y, Stilp AM, Emery L, Wong Q, Hawley NL, Minster RL, Curran JE, Munroe PB, Weeks DE, North KE, Tracy RP, Kenny EE, Shimbo D, Chakravarti A, Rich SS, Reiner AP, Blangero J, Redline S, Mitchell BD, Rao DC, Ida Chen YD, Kardia SLR, Kaplan RC, Mathias RA, He J, Psaty BM, Fornage M, Loos RJF, Correa A, Boerwinkle E, Rotter JI, Kooperberg C, Edwards TL, Abecasis GR, Zhu X, Levy D, Arnett DK, Morrison AC. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension. Hypertension 2022; 79:1656-1667. [PMID: 35652341 PMCID: PMC9593435 DOI: 10.1161/hypertensionaha.122.19324] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 05/12/2022] [Indexed: 12/30/2022]
Abstract
BACKGROUND The availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure. METHODS We conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants. RESULTS Two blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P<5×10-8). Among them, a rare intergenic variant at novel locus, LOC100506274, was associated with lower systolic blood pressure in stage-1 (beta [SE]=-32.6 [6.0]; P=4.99×10-8) but not stage-2 analysis (P=0.11). Furthermore, a novel common variant at the known INSR locus was suggestively associated with diastolic blood pressure in stage-1 (beta [SE]=-0.36 [0.07]; P=4.18×10-7) and attained genome-wide significance in stage-2 (beta [SE]=-0.29 [0.03]; P=7.28×10-23). Nineteen additional signals suggestively associated with blood pressure in meta-analysis of single and aggregate rare variant findings (P<1×10-6 and P<1×10-4, respectively). DISCUSSION We report one promising but unconfirmed rare variant for blood pressure and, more importantly, contribute insights for future blood pressure sequencing studies. Our findings suggest promise of aggregate analyses to complement single variant analysis strategies and the need for larger, diverse samples, and family studies to enable robust rare variant identification.
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Affiliation(s)
- Tanika N Kelly
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
| | - Xiao Sun
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Karen Y He
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Michael R Brown
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Sarah A Gagliano Taliun
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Jacklyn N Hellwege
- Division of Genetic Medicine, Department of Medicine (J.N.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Marguerite R Irvin
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Xuenan Mi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Jennifer A Brody
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Nora Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill (N.F.)
| | - 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 (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Shih-Jen Hwang
- National Heart, Lung and Blood Institute, Population Sciences Branch, National Institutes of Health, Framingham, MA (S.-J.H.)
| | - Paul S de Vries
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Yan Gao
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
| | - Arden Moscati
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Girish N Nadkarni
- The Charles Bronfman Institute for Personalized Medicine (A.M., G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
- Department of Medicine (G.N.N.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Lisa R Yanek
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Tali Elfassy
- Division of Epidemiology, Department of Public Health Sciences, University of Miami Miller School of Medicine, Miami' FL (T.E.)
| | - Jennifer A Smith
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Ren-Hua Chung
- Institute of Population Sciences, National Health Research Institutes, Taiwan (R.-H.C.)
| | - Amber L Beitelshees
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Amit Patki
- Department of Biostatistics (A.P., V.S.), University of Alabama at Birmingham' AL
| | - Stella Aslibekyan
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Brandon M Blobner
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services (B.M.P.), University of Washington, Seattle' WA
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Juan M Peralta
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Themistocles L Assimes
- Division of Cardiovascular Medicine, Department of Medicine, Stanford University, Stanford' CA (T.L.A.)
- Division of Cardiology Medicine, Palo Alto VA HealthCare System, Palo Alto' CA (T.L.A.)
| | - Walter R Palmas
- Division of General Medicine, Department of Medicine, Columbia University, New York, NY (W.R.P.)
| | - Chunyu Liu
- Department of Biostatistics, Boston University, Boston' MA (C.L.)
| | - Adam P Bress
- Division of Health System Innovation and Research, Department of Population Health Sciences, University of Utah School of Medicine, Salt Lake City' UT (A.P.B.)
| | - Zhijie Huang
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Lewis C Becker
- Division of Cardiology, Department of Medicine (L.C.B.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Chii-Min Hwa
- Taichung Veterans General Hospital, Taichung, Taiwan (C.-M.H.)
| | - Jeffrey R O'Connell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Jenna C Carlson
- Department of Biostatistics, Graduate School of Public Health (J.C.C.), University of Pittsburgh, PA
| | - Helen R Warren
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Sayantan Das
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Ayush Giri
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
- Division of Quantitative Sciences, Department of Obstetrics and Gynecology, Vanderbilt University, Nashville, TN (A.G.)
| | - Lisa W Martin
- Division of Cardiology, Department of Medicine, George Washington University, Washington, DC (L.W.M.)
| | - W Craig Johnson
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Ervin R Fox
- Division of Cardiology, Department of Medicine (E.R.F.), University of Mississippi Medical Center, Jackson' MS
| | - Erwin P Bottinger
- Hasso Plattner Institute for Digital Health at Mount Sinai (E.P.B.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Alexander C Razavi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Dhananjay Vaidya
- Division of General Internal Medicine, Department of Medicine (L.R.Y., D.V.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Lee-Ming Chuang
- Department of Internal Medicine, National Taiwan University Hospital, Taipei' Taiwan (L.-M.C.)
| | - Yen-Pei C Chang
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | - Take Naseri
- Ministry of Health, Government of Samoa, Apia' Samoa (T.N.)
| | - Deepti Jain
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Hyun Min Kang
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Adriana M Hung
- Division of Nephrology and Hypertension, Department of Medicine (A.M.H.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | | | - Beverly M Snively
- Division of Public Health Sciences, Department of Biostatistics and Data Science, Wake Forest School of Medicine, Winston-Salem, NC (B.M.S.)
| | - Dongfeng Gu
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - May E Montasser
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
| | | | - Benjamin D Heavner
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonathon LeFaive
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - James E Hixson
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Kenneth M Rice
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Fei Fei Wang
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Jonas B Nielsen
- Department of Internal Medicine: Cardiology (J.B.N.), University of Michigan, Ann Arbor' MI
- Department of Epidemiology Research, Statens Serum Institut, Copenhagen, Denmark (J.B.N.)
| | - Jianfeng Huang
- Translational Sciences Institute (T.N.K., J.H.), Tulane University, New Orleans, LA
- Department of Epidemiology and Key Laboratory of Cardiovascular Epidemiology, Fuwai Hospital, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China (D.G., J.H.)
| | - Alyna T Khan
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Wei Zhou
- Department of Computational Medicine and Bioinformatics (W.Z.), University of Michigan, Ann Arbor' MI
| | - Jovia L Nierenberg
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Cathy C Laurie
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicole D Armstrong
- Department of Epidemiology (M.R.I., S.A., N.D.A.), University of Alabama at Birmingham' AL
| | - Mengyao Shi
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Yang Pan
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Adrienne M Stilp
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Leslie Emery
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Quenna Wong
- Department of Biostatistics, School of Public Health (W.C.J., D.J., B.D.H., K.M.R., F.F.E., A.T.K., C.C.L., A.M.S., L.E., Q.W.), University of Washington, Seattle' WA
| | - Nicola L Hawley
- Department of Chronic Disease Epidemiology, Yale University, New Haven, CT (N.L.H.)
| | - Ryan L Minster
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
| | - Joanne E Curran
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Patricia B Munroe
- Department of Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
- National Institute for Health Research Barts Cardiovascular Biomedical Research Centre (H.R.W., P.B.M.), Queen Mary University of London, United Kingdom
| | - Daniel E Weeks
- Department of Human Genetics (B.M.B., R.L.M., D.E.W.), University of Pittsburgh, PA
- Department of Biostatistics (D.E.W.), University of Pittsburgh, PA
| | - Kari E North
- Cardiovascular Health Research Unit, Department of Medicine (J.A.B., K.E.N.), University of Washington, Seattle' WA
| | - Russell P Tracy
- Department of Pathology & Laboratory Medicine, Larner College of Medicine, University of Vermont, Burlington' VT (R.P.T.)
| | - Eimear E Kenny
- Department of Physiology and Biophysics (Y.G., E.E.K., R.J.F.L.), University of Mississippi Medical Center, Jackson' MS
- Department of Genetics and Genomics (E.E.K.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Daichi Shimbo
- Division of Cardiology, Department of Medicine, Columbia University Medical Center, New York, NY (D.S.)
| | - Aravinda Chakravarti
- Department of Medicine (A.C.), University of Mississippi Medical Center, Jackson' MS
| | - Stephen S Rich
- Center for Public Health, University of Virginia, Charlottesville' VA (S.S.R.)
| | - Alex P Reiner
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - John Blangero
- Department of Human Genetics and South Texas Diabetes and Obesity Institute, University of Texas Rio Grande Valley, Brownsville' TX (J.M.P., J.E.C., J.B.)
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA (S.R.)
| | - Braxton D Mitchell
- Division of Endocrinology, Diabetes, and Nutrition, Department of Medicine, University of Maryland School of Medicine, Baltimore' MD (A.L.B., J.R.O., Y.-P.C.C., M.E.M., B.D.M.)
- Geriatrics Research and Education Clinical Center, Baltimore Veterans Administration Medical Center, Baltimore' MD (B.D.M.)
| | - Dabeeru C Rao
- Division of Biostatistics, Washington University School of Medicine, St. Louis, MO (D.C.R.)
| | - Yii-Der Ida Chen
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Sharon L R Kardia
- Department of Epidemiology (J.A.S., S.L.R.K.), University of Michigan, Ann Arbor' MI
| | - Robert C Kaplan
- Division of Social Medicine, Albert Einstein College of Medicine, Bronx, NY (R.C.K.)
| | - Rasika A Mathias
- Division of Allergy & Clinical Immunology, Department of Medicine (R.A.M.), Johns Hopkins University School of Medicine, Baltimore, MD
| | - Jiang He
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
| | - Bruce M Psaty
- Department of Epidemiology (T.N.K., X.S., X.M., Z.H., A.C.R., J.L.N., M.S., Y.P., J.H.), Tulane University, New Orleans, LA
- Kaiser Permanente Washington Health Research Institute, Seattle' WA (B.M.P.)
| | - Myriam Fornage
- Brown Foundation Institute of Molecular Medicine (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genetics Center (M.F.), The University of Texas Health Science Center at Houston' Houston' TX
| | - Ruth J F Loos
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
- The Mindich Child Health and Development Institute (R.J.F.L.), The Icahn School of Medicine at Mount Sinai, New York, NY
| | - Adolfo Correa
- Center for Human Genetics and Genomics, New York University Grossman School of Medicine, New York, NY (A.C.)
| | - Eric Boerwinkle
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX (E.B.)
| | - 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 (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA (A.P.R., C.K.)
| | - Todd L Edwards
- Division of Epidemiology, Department of Medicine (T.L.E.), Vanderbilt University Medical Center, Nashville, TN
- Biomedical Laboratory Research and Development, Tennessee Valley Healthcare System (626)/Vanderbilt University, Nashville' TN (J.N.H., A.G., A.M.H., T.L.E.)
| | - Gonçalo R Abecasis
- Department of Biostatistics (S.A.G.T., S.D., H.M.K., J.L., G.R.A.), University of Michigan, Ann Arbor' MI
| | - Xiaofeng Zhu
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH (K.Y.H., X.Z.)
| | - Daniel Levy
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance' CA (X.G., Y.-D.I.C., J.I.R., D.L.)
| | - Donna K Arnett
- College of Public Health, University of Kentucky, Lexington, KY (D.K.A.)
| | - Alanna C Morrison
- Human Genetics Center, Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health (M.R.B., P.D.d.V., J.E.H., E.B., A.C.M.), The University of Texas Health Science Center at Houston' Houston' TX
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6
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Krupenko SA, Cole SA, Hou R, Haack K, Laston S, Mehta NR, Comuzzie AG, Butte NF, Voruganti VS. Genetic variants in ALDH1L1 and GLDC influence the serine-to-glycine ratio in Hispanic children. Am J Clin Nutr 2022; 116:500-510. [PMID: 35460232 PMCID: PMC9348975 DOI: 10.1093/ajcn/nqac091] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2021] [Revised: 02/15/2022] [Accepted: 04/21/2022] [Indexed: 11/14/2022] Open
Abstract
BACKGROUND Glycine is a proteogenic amino acid that is required for numerous metabolic pathways, including purine, creatine, heme, and glutathione biosynthesis. Glycine formation from serine, catalyzed by serine hydroxy methyltransferase, is the major source of this amino acid in humans. Our previous studies in a mouse model have shown a crucial role for the 10-formyltetrahydrofolate dehydrogenase enzyme in serine-to-glycine conversion. OBJECTIVES We sought to determine the genomic influence on the serine-glycine ratio in 803 Hispanic children from 319 families of the Viva La Familia cohort. METHODS We performed a genome-wide association analysis for plasma serine, glycine, and the serine-glycine ratio in Sequential Oligogenic Linkage Analysis Routines while accounting for relationships among family members. RESULTS All 3 parameters were significantly heritable (h2 = 0.22-0.78; P < 0.004). The strongest associations for the serine-glycine ratio were with single nucleotide polymorphisms (SNPs) in aldehyde dehydrogenase 1 family member L1 (ALDH1L1) and glycine decarboxylase (GLDC) and for glycine with GLDC (P < 3.5 × 10-8; effect sizes, 0.03-0.07). No significant associations were found for serine. We also conducted a targeted genetic analysis with ALDH1L1 exonic SNPs and found significant associations between the serine-glycine ratio and rs2886059 (β = 0.68; SE, 0.25; P = 0.006) and rs3796191 (β = 0.25; SE, 0.08; P = 0.003) and between glycine and rs3796191 (β = -0.08; SE, 0.02; P = 0.0004). These exonic SNPs were further associated with metabolic disease risk factors, mainly adiposity measures (P < 0.006). Significant genetic and phenotypic correlations were found for glycine and the serine-glycine ratio with metabolic disease risk factors, including adiposity, insulin sensitivity, and inflammation-related phenotypes [estimate of genetic correlation = -0.37 to 0.35 (P < 0.03); estimate of phenotypic correlation = -0.19 to 0.13 (P < 0.006)]. The significant genetic correlations indicate shared genetic effects among glycine, the serine-glycine ratio, and adiposity and insulin sensitivity phenotypes. CONCLUSIONS Our study suggests that ALDH1L1 and GLDC SNPs influence the serine-to-glycine ratio and metabolic disease risk.
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Affiliation(s)
- Sergey A Krupenko
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Ruixue Hou
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Sandra Laston
- 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
| | - Nitesh R Mehta
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,USDA/ARS Children Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | | | - Nancy F Butte
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA,USDA/ARS Children Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
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7
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In Silico Analysis of Ion Channels and Their Correlation with Epithelial to Mesenchymal Transition in Breast Cancer. Cancers (Basel) 2022; 14:cancers14061444. [PMID: 35326596 PMCID: PMC8946083 DOI: 10.3390/cancers14061444] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 02/09/2022] [Accepted: 02/11/2022] [Indexed: 02/01/2023] Open
Abstract
Simple Summary Breast cancer involves changes in the healthy cells of the breast resulting in rapid and abnormal division of cells that later spread to other parts of the body through the process of metastasis, which involves epithelial mesenchymal transition (EMT). Ion channels play a significant role in the switch from epithelial to mesenchymal transition through their contributions to cellular motility, cell volume regulation and cell cycle progression. Comprehensive computational analyses were performed to understand the role of ion channels in tumor/metastatic samples of breast cancer and their correlation with EMT. Abstract Uncontrolled growth of breast cells due to altered gene expression is a key feature of breast cancer. Alterations in the expression of ion channels lead to variations in cellular activities, thus contributing to attributes of cancer hallmarks. Changes in the expression levels of ion channels were observed as a consequence of EMT. Additionally, ion channels were reported in the activation of EMT and maintenance of a mesenchymal phenotype. Here, to identify altered ion channels in breast cancer patients, differential gene expression and weighted gene co-expression network analyses were performed using transcriptomic data. Protein–protein interactions network analysis was carried out to determine the ion channels interacting with hub EMT-related genes in breast cancer. Thirty-two ion channels were found interacting with twenty-six hub EMT-related genes. The identified ion channels were further correlated with EMT scores, indicating mesenchymal phenotype. Further, the pathway map was generated to represent a snapshot of deregulated cellular processes by altered ion channels and EMT-related genes. Kaplan–Meier five-year survival analysis and Cox regressions indicated the expression of CACNA1B, ANO6, TRPV3, VDAC1 and VDAC2 to be potentially associated with poor survival. Deregulated ion channels correlate with EMT-related genes and have a crucial role in breast cancer-associated tumorigenesis. Most likely, they are potential candidates for the determination of prognosis in patients with breast cancer.
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8
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Zifarelli G, Pusch M, Fong P. Altered voltage-dependence of slowly activating chloride-proton antiport by late endosomal ClC-6 explains distinct neurological disorders. J Physiol 2022; 600:2147-2164. [PMID: 35262198 DOI: 10.1113/jp282737] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/14/2021] [Accepted: 03/01/2022] [Indexed: 11/08/2022] Open
Abstract
KEY POINTS Ionic composition and pH within intracellular compartments, such as endo-lysosomes, rely on the activity of chloride/proton transporters including ClC-6. Distinct CLCN6 mutations previously were found in individuals with neurodegenerative disease, and also putatively associated with neuronal ceroidal lipofuscinosis. Limited knowledge of wild-type ClC-6 transport function impedes understanding of mechanisms underlying these conditions. We resolved transient and transport currents that permit measurement of voltage- and pH- dependences, as well as kinetics, for wild-type and disease-associated mutant ClC-6s. These findings define wild-type ClC-6 function robustly, and reveal how alterations of the slow activation gating of the transporter cause different kinds of neurological diseases. ABSTRACT ClC-6 is an intracellularly localized member of the CLC family of chloride transport proteins. It presumably functions in the endo-lysosomal compartment as a chloride-proton antiporter, despite a paucity of biophysical studies in direct support. Observations of lysosomal storage disease, as well as neurodegenerative disorders, emerge with its disruption by knockout or mutation, respectively. An incomplete understanding of wild type ClC-6 function obscures clear mechanistic insight into disease etiology. Here, high-resolution recording protocols that incorporate extreme voltage pulses permit detailed biophysical measurement and analysis of transient capacitive, as well as ionic transport currents. This approach reveals that wild type ClC-6 activation and transport require depolarization to voltages beyond 140 mV. Mutant Y553C associated with early-onset neurodegeneration exerts gain-of-function by shifting the half-maximal voltage for activation to less depolarized voltages. Moreover, we show that the E267A proton glutamate mutant conserves transport currents, albeit reduced. Lastly, the positive shift in activation voltage shown by V580M, a mutant identified in a patient with late- onset lysosomal storage disease, can explain loss-of-function leading to disease. Abstract figure legend CLC transport proteins comprise both channels and transporters. Vesicular CLC transporters function to regulate compartmental ionic homeostasis and acidification. ClC-6 is a vesicular CLC that localizes to the endo-lysosomal compartment. Functional plasma membrane overexpression of GFP-tagged ClC-6 in HEK293 cells surmounted spatial inaccessibility, and rapid whole cell patch recording protocols enabling resolution of fast capacitive transients, as well as ionic transport currents, provided details of wild-type ClC-6 biophysical properties including voltage-dependence, pH-dependence, and kinetics. Clearly defined wild-type ClC-6 function permitted subsequent comparative analysis of mutants, including but not limited to those pertinent to disease. These range from one causing severe, early-onset neurodegeneration, to two variants previously identified in Kufs disease, a late-onset lysosomal storage disease characterized by neuronal ceroid lipofuscinosis. These findings further inform models whereby disruption of ClC-6 biophysical properties set the stage for dysregulated compartmental homeostasis and hence, disease. This article is protected by copyright. All rights reserved.
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Affiliation(s)
- Giovanni Zifarelli
- Institute of Biophysics, CNR, Genoa, Italy.,Present address: Centogene GmbH, Rostock, Germany
| | | | - Peying Fong
- Department of Anatomy and Physiology, Kansas State University College of Veterinary Medicine, Manhattan, KS, USA
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9
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Tsao CW, Aday AW, Almarzooq ZI, Alonso A, Beaton AZ, Bittencourt MS, Boehme AK, Buxton AE, Carson AP, Commodore-Mensah Y, Elkind MSV, Evenson KR, Eze-Nliam C, Ferguson JF, Generoso G, Ho JE, Kalani R, Khan SS, Kissela BM, Knutson KL, Levine DA, Lewis TT, Liu J, Loop MS, Ma J, Mussolino ME, Navaneethan SD, Perak AM, Poudel R, Rezk-Hanna M, Roth GA, Schroeder EB, Shah SH, Thacker EL, VanWagner LB, Virani SS, Voecks JH, Wang NY, Yaffe K, Martin SS. Heart Disease and Stroke Statistics-2022 Update: A Report From the American Heart Association. Circulation 2022; 145:e153-e639. [PMID: 35078371 DOI: 10.1161/cir.0000000000001052] [Citation(s) in RCA: 2433] [Impact Index Per Article: 1216.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2022 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population and an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, and the global burden of cardiovascular disease and healthy life expectancy. RESULTS Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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10
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Virani SS, Alonso A, Aparicio HJ, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Cheng S, Delling FN, Elkind MSV, Evenson KR, Ferguson JF, Gupta DK, Khan SS, Kissela BM, Knutson KL, Lee CD, Lewis TT, Liu J, Loop MS, Lutsey PL, Ma J, Mackey J, Martin SS, Matchar DB, Mussolino ME, Navaneethan SD, Perak AM, Roth GA, Samad Z, Satou GM, Schroeder EB, Shah SH, Shay CM, Stokes A, VanWagner LB, Wang NY, Tsao CW. Heart Disease and Stroke Statistics-2021 Update: A Report From the American Heart Association. Circulation 2021; 143:e254-e743. [PMID: 33501848 DOI: 10.1161/cir.0000000000000950] [Citation(s) in RCA: 3052] [Impact Index Per Article: 1017.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2021 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, an enhanced focus on social determinants of health, adverse pregnancy outcomes, vascular contributions to brain health, the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors related to cardiovascular disease. RESULTS Each of the 27 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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11
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He H, Cao X, Yin F, Wu T, Stauber T, Peng J. West Syndrome Caused By a Chloride/Proton Exchange-Uncoupling CLCN6 Mutation Related to Autophagic-Lysosomal Dysfunction. Mol Neurobiol 2021; 58:2990-2999. [PMID: 33590434 DOI: 10.1007/s12035-021-02291-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Accepted: 01/12/2021] [Indexed: 12/25/2022]
Abstract
Vesicular chloride/proton exchangers of the CLC family are critically involved in the function of the endosomal-lysosomal pathway. Their dysfunction leads to severe disorders including intellectual disability and epilepsy for ClC-4, Dent's disease for ClC-5, and lysosomal storage disease and osteopetrosis for ClC-7. Here, we report a de novo variant p.Glu200Ala (p.E200A; c.599A>C) of the late endosomal ClC-6, encoded by CLCN6, in a patient with West syndrome (WS), severe developmental delay, autism, movement disorder, microcephaly, facial dysmorphism, and visual impairment. Mutation of this conserved glutamate uncouples chloride transport from proton antiport by ClC-6. This affects organellar ion homeostasis and was shown to be deleterious for other CLCs. In this study, we found that upon heterologous expression, the ClC-6 E200A variant caused autophagosome accumulation and impaired the clearance of autophagosomes by blocking autophagosome-lysosome fusion. Our study provides clinical and functional support for an association between CLCN6 variants and WS. Our findings also provide novel insights into the molecular mechanisms underlying the pathogenesis of WS, suggesting an involvement of autophagic-lysosomal dysfunction.
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Affiliation(s)
- Hailan He
- Department of Pediatrics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China
| | - Xiaoshuang Cao
- Department of Pediatrics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China
| | - Fei Yin
- Department of Pediatrics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China.,Hunan Intellectual and Developmental Disabilities Research Center, Xiangya Road 87, Changsha, 410008, Hunan, China
| | - Tenghui Wu
- Department of Pediatrics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China
| | - Tobias Stauber
- Institute of Chemistry and Biochemistry, Freie Universität Berlin, Thielallee 63, 14195, Berlin, Germany.,Institute for Molecular Medicine and Department of Human Medicine, MSH Medical School Hamburg, Am Kaiserkai 1, 20457, Hamburg, Germany
| | - Jing Peng
- Department of Pediatrics, Xiangya Hospital, Central South University, Xiangya Road 87, Changsha, 410008, Hunan, China. .,Hunan Intellectual and Developmental Disabilities Research Center, Xiangya Road 87, Changsha, 410008, Hunan, China.
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12
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Coronary computed tomography angiography before on-pump cardiac surgery does not reduce the risk of postoperative acute kidney injury compared to coronary angiography. Gen Thorac Cardiovasc Surg 2021; 69:1445-1452. [PMID: 33550545 DOI: 10.1007/s11748-021-01602-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2020] [Accepted: 01/26/2021] [Indexed: 10/22/2022]
Abstract
OBJECTIVES Cardiac surgery and contrast media are both related to acute kidney injury. We investigated whether undergoing coronary computed tomography angiography, which uses less contrast medium, before on-pump cardiac surgery could reduce the risk of postoperative acute kidney injury compared to coronary angiography. METHODS In this retrospective study, 745 and 171 patients underwent coronary angiography and coronary computed tomography angiography, respectively, within 30 days before on-pump cardiac surgery. Postoperative acute kidney injury was defined according to Kidney Disease Improving Global Outcomes Definition and Staging criteria. RESULTS Age, hypertension, cardiopulmonary bypass time, and performing cardiac surgery within 24 h of preoperative angiography (odds ratio: 1.507, 95% confidence interval: 1.111‒2.045, P = 0.008) independently predicted postoperative acute kidney injury on multivariable analysis. After propensity score matching, the acute kidney injury incidence in coronary angiography and computed tomography angiography groups was 43% and 46%, respectively (P = 0.65), and the groups had similar intensive care unit stay (2 days vs. 2 days, P = 0.209), postoperative hospital stay (11 days vs. 12 days, P = 0.084), postoperative continuous renal replacement therapy use (0.6% vs 1.9%, P = 0.314), and in-hospital mortality (0 vs. 1.3%, P = 0.156). In-hospital outcomes were similar among patients who underwent preoperative coronary angiography or computed tomography angiography within 24 h before cardiac surgery. CONCLUSION Although coronary computed tomography angiography uses less contrast medium, it does not reduce the risk of postoperative acute kidney injury or improve in-hospital outcomes compared to coronary angiography.
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13
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Klemens CA, Chulkov EG, Wu J, Hye Khan MA, Levchenko V, Flister MJ, Imig JD, Kriegel AJ, Palygin O, Staruschenko A. Loss of Chloride Channel 6 (CLC-6) Affects Vascular Smooth Muscle Contractility and Arterial Stiffness via Alterations to Golgi Calcium Stores. Hypertension 2021; 77:582-593. [PMID: 33390052 DOI: 10.1161/hypertensionaha.120.16589] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/26/2022]
Abstract
Genome-wide association studies have found a number of potential genes involved in blood pressure regulation; however, the functional role of many of these candidates has yet to be established. One such candidate gene is CLCN6, which encodes the transmembrane protein, chloride channel 6 (ClC-6). Although the CLCN6 locus has been widely associated with human blood pressure regulation, the mechanistic role of ClC-6 in blood pressure homeostasis at the molecular, cellular, and physiological levels is completely unknown. In this study, we demonstrate that rats with a functional knockout of ClC-6 on the Dahl Salt-Sensitive rat background (SS-Clcn6) have lower diastolic but not systolic blood pressures. The effect of diastolic blood pressure attenuation was independent of dietary salt exposure in knockout animals. Moreover, SS-Clcn6 rats are protected from hypertension-induced cardiac hypertrophy and arterial stiffening; however, they have impaired vasodilation and dysregulated intracellular calcium handling. ClC-6 is highly expressed in vascular smooth muscle cells where it is targeted to the Golgi apparatus. Using bilayer electrophysiology, we provide evidence that recombinant human ClC-6 protein can function as a channel. Last, we demonstrate that loss of ClC-6 function reduces Golgi calcium stores, which may play a previously unidentified role in vascular contraction and relaxation signaling in vascular smooth muscle cells. Collectively, these data indicate that ClC-6 may modulate blood pressure by regulating Golgi calcium reserves, which in turn contribute to vascular smooth muscle function.
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Affiliation(s)
- Christine A Klemens
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin.,Cardiovascular Center (C.A.K., J.W., J.D.I., O.P., A.S.), Medical College of Wisconsin
| | - Evgeny G Chulkov
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin.,Department of Cell Biology, Neurobiology and Anatomy (E.G.C.), Medical College of Wisconsin
| | - Jing Wu
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin.,Cardiovascular Center (C.A.K., J.W., J.D.I., O.P., A.S.), Medical College of Wisconsin
| | - Md Abdul Hye Khan
- Department of Pharmacology (M.A.H.K., J.D.I.), Medical College of Wisconsin
| | - Vladislav Levchenko
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin
| | - Michael J Flister
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin
| | - John D Imig
- Department of Pharmacology (M.A.H.K., J.D.I.), Medical College of Wisconsin.,Cardiovascular Center (C.A.K., J.W., J.D.I., O.P., A.S.), Medical College of Wisconsin
| | - Alison J Kriegel
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin
| | - Oleg Palygin
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin.,Cardiovascular Center (C.A.K., J.W., J.D.I., O.P., A.S.), Medical College of Wisconsin
| | - Alexander Staruschenko
- From the Department of Physiology (C.A.K., E.G.C., J.W., V.L., M.J.F., A.J.K., O.P., A.S.), Medical College of Wisconsin.,Cardiovascular Center (C.A.K., J.W., J.D.I., O.P., A.S.), Medical College of Wisconsin.,Clement J. Zablocki VA Medical Center, Milwaukee (A.S.)
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14
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Genetic loci associated with prevalent and incident myocardial infarction and coronary heart disease in the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium. PLoS One 2020; 15:e0230035. [PMID: 33186364 PMCID: PMC7665790 DOI: 10.1371/journal.pone.0230035] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2020] [Accepted: 10/26/2020] [Indexed: 12/31/2022] Open
Abstract
BACKGROUND Genome-wide association studies have identified multiple genomic loci associated with coronary artery disease, but most are common variants in non-coding regions that provide limited information on causal genes and etiology of the disease. To overcome the limited scope that common variants provide, we focused our investigation on low-frequency and rare sequence variations primarily residing in coding regions of the genome. METHODS AND RESULTS Using samples of individuals of European ancestry from ten cohorts within the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium, both cross-sectional and prospective analyses were conducted to examine associations between genetic variants and myocardial infarction (MI), coronary heart disease (CHD), and all-cause mortality following these events. For prevalent events, a total of 27,349 participants of European ancestry, including 1831 prevalent MI cases and 2518 prevalent CHD cases were used. For incident cases, a total of 55,736 participants of European ancestry were included (3,031 incident MI cases and 5,425 incident CHD cases). There were 1,860 all-cause deaths among the 3,751 MI and CHD cases from six cohorts that contributed to the analysis of all-cause mortality. Single variant and gene-based analyses were performed separately in each cohort and then meta-analyzed for each outcome. A low-frequency intronic variant (rs988583) in PLCL1 was significantly associated with prevalent MI (OR = 1.80, 95% confidence interval: 1.43, 2.27; P = 7.12 × 10-7). We conducted gene-based burden tests for genes with a cumulative minor allele count (cMAC) ≥ 5 and variants with minor allele frequency (MAF) < 5%. TMPRSS5 and LDLRAD1 were significantly associated with prevalent MI and CHD, respectively, and RC3H2 and ANGPTL4 were significantly associated with incident MI and CHD, respectively. No loci were significantly associated with all-cause mortality following a MI or CHD event. CONCLUSION This study identified one known locus (ANGPTL4) and four new loci (PLCL1, RC3H2, TMPRSS5, and LDLRAD1) associated with cardiovascular disease risk that warrant further investigation.
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15
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Hou R, Cole SA, Graff M, Haack K, Laston S, Comuzzie AG, Mehta NR, Ryan K, Cousminer DL, Zemel BS, Grant SFA, Mitchell BD, Shypailo RJ, Gourlay ML, North KE, Butte NF, Voruganti VS. Genetic variants affecting bone mineral density and bone mineral content at multiple skeletal sites in Hispanic children. Bone 2020; 132:115175. [PMID: 31790847 PMCID: PMC7120871 DOI: 10.1016/j.bone.2019.115175] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/27/2019] [Revised: 11/22/2019] [Accepted: 11/22/2019] [Indexed: 12/24/2022]
Abstract
CONTEXT Osteoporosis is a major public health burden with significant economic costs. However, the correlates of bone health in Hispanic children are understudied. OBJECTIVE We aimed to identify genetic variants associated with bone mineral density (BMD) and bone mineral content (BMC) at multiple skeletal sites in Hispanic children. METHODS We conducted a cross-sectional genome-wide linkage analysis, genome-wide and exome-wide association analysis of BMD and BMC. The Viva La Familia Study is a family-based cohort with a total of 1030 Hispanic children (4-19 years old at baseline) conducted in Houston, TX. BMD and BMC were measured by Dual-energy X-ray absorptiometry. RESULTS Significant heritability were observed for BMC and BMD at multiple skeletal sites ranging between 44 and 68% (P < 2.8 × 10-9). Significant evidence for linkage was found for BMD of pelvis and left leg on chromosome 7p14, lumbar spine on 20q13 and left rib on 6p21, and BMC of pelvis on chromosome 20q12 and total body on 14q22-23 (logarithm of odds score > 3). We found genome-wide significant association between BMC of right arm and rs762920 at PVALB (P = 4.6 × 10-8), and between pelvis BMD and rs7000615 at PTK2B (P = 7.4 × 10-8). Exome-wide association analysis revealed novel association of variants at MEGF10 and ABRAXAS2 with left arm and lumber spine BMC, respectively (P < 9 × 10-7). CONCLUSIONS We identified novel loci associated with BMC and BMD in Hispanic children, with strongest evidence for PTK2B. These findings provide better understanding of bone genetics and shed light on biological mechanisms underlying BMD and BMC variation.
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Affiliation(s)
- Ruixue Hou
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA
| | - Shelley A Cole
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Mariaelisa Graff
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Karin Haack
- Population Health Program, Texas Biomedical Research Institute, San Antonio, TX, USA
| | - Sandra Laston
- South Texas Diabetes and Obesity Institute and Department of Human Genetics, University of Texas the Rio Grande Valley, Brownsville, TX, USA
| | | | - Nitesh R Mehta
- Department of Pediatrics and USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Kathleen Ryan
- 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
| | - Diana L Cousminer
- Division of Human Genetics, Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, USA; Department of Genetics, University of Pennsylvania, USA
| | - Babette S Zemel
- Division of GI, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, USA; Department of Pediatrics, University of Pennsylvania, Philadelphia, USA
| | - Struan F A Grant
- Division of Human Genetics, Center for Spatial and Functional Genomics, Children's Hospital of Philadelphia, Philadelphia, USA; Department of Pediatrics, University of Pennsylvania, Philadelphia, USA; Department of Genetics, University of Pennsylvania, USA; Institute for Diabetes, Obesity and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA; Division of Endocrinology and Diabetes, Children's Hospital of Philadelphia, Philadelphia, PA, 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
| | - Roman J Shypailo
- Department of Pediatrics and USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - Margaret L Gourlay
- Department of Family Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Nancy F Butte
- Department of Pediatrics and USDA/ARS Children's Nutrition Research Center, Baylor College of Medicine, Houston, TX, USA
| | - V Saroja Voruganti
- Department of Nutrition and Nutrition Research Institute, University of North Carolina at Chapel Hill, Kannapolis, NC, USA.
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16
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Tang W, Stimson MR, Basu S, Heckbert SR, Cushman M, Pankow JS, Folsom AR, Pankratz N. Burden of rare exome sequence variants in PROC gene is associated with venous thromboembolism: a population-based study. J Thromb Haemost 2020; 18:445-453. [PMID: 31680443 PMCID: PMC7787541 DOI: 10.1111/jth.14676] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 10/13/2019] [Accepted: 10/30/2019] [Indexed: 12/15/2022]
Abstract
BACKGROUND Rare coding mutations underlying deficiencies of antithrombin and proteins C and S contribute to familial venous thromboembolism (VTE). It is uncertain whether rare variants play a role in the etiology of VTE in the general population. OBJECTIVES We conducted a deep whole-exome sequencing (WES) study to investigate the associations between rare coding variants and the risk of VTE in two population-based prospective cohorts. PATIENTS/METHODS Whole-exome sequencing was performed in the Longitudinal Investigation of Thromboembolism Etiology (LITE), which combines the Atherosclerosis Risk in Communities (ARIC) study (316 incident VTE events among 3159 African Americans [AAs] and 458 incident VTEs among 7772 European Americans [EAs]) and the Cardiovascular Healthy Study (CHS; 60 incident VTEs among 1751 EAs). We performed gene-based tests of rare variants (allele frequency < 1%, exome-wide significance P < 1.47 × 10-6 ) separately in each study and ancestry group, and meta-analyzed the results for the EAs in ARIC and CHS. RESULTS In the meta-analysis of EAs, we identified one gene, PROC, in which the burden of rare, coding variants was significantly associated with increased risk of VTE (HR = 5.42 [3.11, 9.42] for carriers versus non-carriers, P = 2.27 × 10-9 ). In ARIC EAs, carriers of the PROC rare variants had on average 0.75 standard deviation (SD) lower concentrations of plasma protein C and 0.28 SD higher D-dimer (P < .05) than non-carriers. Adjustment for low protein C status did not eliminate the association of PROC burden with VTE. In AAs, rare coding PROC variants were not associated with VTE. CONCLUSIONS Rare coding variants in PROC contribute to increased VTE risk in EAs in this general population sample.
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Affiliation(s)
- Weihong Tang
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Mary Rachel Stimson
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, United States
| | - Saonli Basu
- Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Susan R. Heckbert
- Department of Epidemiology, University of Washington, Seattle, Washington, United States
| | - Mary Cushman
- Department of Pathology, University of Vermont, Burlington, Vermont, United States
| | - James S. Pankow
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Aaron R. Folsom
- Division of Epidemiology & Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota, United States
| | - Nathan Pankratz
- Department of Laboratory Medicine and Pathology, School of Medicine, University of Minnesota, Minneapolis, Minnesota, United States
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Virani SS, Alonso A, Benjamin EJ, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Shay CM, Spartano NL, Stokes A, Tirschwell DL, VanWagner LB, Tsao CW. Heart Disease and Stroke Statistics-2020 Update: A Report From the American Heart Association. Circulation 2020; 141:e139-e596. [PMID: 31992061 DOI: 10.1161/cir.0000000000000757] [Citation(s) in RCA: 4802] [Impact Index Per Article: 1200.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
BACKGROUND The American Heart Association, in conjunction with the National Institutes of Health, annually reports on the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, diet, and weight) and health factors (cholesterol, blood pressure, and glucose control) that contribute to cardiovascular health. The Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, congenital heart disease, rhythm disorders, subclinical atherosclerosis, coronary heart disease, heart failure, valvular disease, venous disease, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs). METHODS The American Heart Association, through its Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States to provide the most current information available in the annual Statistical Update. The 2020 Statistical Update is the product of a full year's worth of effort by dedicated volunteer clinicians and scientists, committed government professionals, and American Heart Association staff members. This year's edition includes data on the monitoring and benefits of cardiovascular health in the population, metrics to assess and monitor healthy diets, an enhanced focus on social determinants of health, a focus on the global burden of cardiovascular disease, and further evidence-based approaches to changing behaviors, implementation strategies, and implications of the American Heart Association's 2020 Impact Goals. RESULTS Each of the 26 chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics. CONCLUSIONS The Statistical Update represents a critical resource for the lay public, policy makers, media professionals, clinicians, healthcare administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.
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18
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Benjamin EJ, Muntner P, Alonso A, Bittencourt MS, Callaway CW, Carson AP, Chamberlain AM, Chang AR, Cheng S, Das SR, Delling FN, Djousse L, Elkind MSV, Ferguson JF, Fornage M, Jordan LC, Khan SS, Kissela BM, Knutson KL, Kwan TW, Lackland DT, Lewis TT, Lichtman JH, Longenecker CT, Loop MS, Lutsey PL, Martin SS, Matsushita K, Moran AE, Mussolino ME, O'Flaherty M, Pandey A, Perak AM, Rosamond WD, Roth GA, Sampson UKA, Satou GM, Schroeder EB, Shah SH, Spartano NL, Stokes A, Tirschwell DL, Tsao CW, Turakhia MP, VanWagner LB, Wilkins JT, Wong SS, Virani SS. Heart Disease and Stroke Statistics-2019 Update: A Report From the American Heart Association. Circulation 2019; 139:e56-e528. [PMID: 30700139 DOI: 10.1161/cir.0000000000000659] [Citation(s) in RCA: 5292] [Impact Index Per Article: 1058.4] [Reference Citation Analysis] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
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19
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Examination of the associations between m6A-associated single-nucleotide polymorphisms and blood pressure. Hypertens Res 2019; 42:1582-1589. [DOI: 10.1038/s41440-019-0277-8] [Citation(s) in RCA: 29] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2018] [Revised: 04/25/2019] [Accepted: 05/06/2019] [Indexed: 01/10/2023]
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20
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Flannick J, Mercader JM, Fuchsberger C, Udler MS, Mahajan A, Wessel J, Teslovich TM, Caulkins L, Koesterer R, Barajas-Olmos F, Blackwell TW, Boerwinkle E, Brody JA, Centeno-Cruz F, Chen L, Chen S, Contreras-Cubas C, Córdova E, Correa A, Cortes M, DeFronzo RA, Dolan L, Drews KL, Elliott A, Floyd JS, Gabriel S, Garay-Sevilla ME, García-Ortiz H, Gross M, Han S, Heard-Costa NL, Jackson AU, Jørgensen ME, Kang HM, Kelsey M, Kim BJ, Koistinen HA, Kuusisto J, Leader JB, Linneberg A, Liu CT, Liu J, Lyssenko V, Manning AK, Marcketta A, Malacara-Hernandez JM, Martínez-Hernández A, Matsuo K, Mayer-Davis E, Mendoza-Caamal E, Mohlke KL, Morrison AC, Ndungu A, Ng MCY, O'Dushlaine C, Payne AJ, Pihoker C, Post WS, Preuss M, Psaty BM, Vasan RS, Rayner NW, Reiner AP, Revilla-Monsalve C, Robertson NR, Santoro N, Schurmann C, So WY, Soberón X, Stringham HM, Strom TM, Tam CHT, Thameem F, Tomlinson B, Torres JM, Tracy RP, van Dam RM, Vujkovic M, Wang S, Welch RP, Witte DR, Wong TY, Atzmon G, Barzilai N, Blangero J, Bonnycastle LL, Bowden DW, Chambers JC, Chan E, Cheng CY, Cho YS, Collins FS, de Vries PS, Duggirala R, Glaser B, Gonzalez C, Gonzalez ME, Groop L, Kooner JS, Kwak SH, Laakso M, Lehman DM, Nilsson P, Spector TD, Tai ES, Tuomi T, Tuomilehto J, Wilson JG, Aguilar-Salinas CA, Bottinger E, Burke B, Carey DJ, Chan JCN, Dupuis J, Frossard P, Heckbert SR, Hwang MY, Kim YJ, Kirchner HL, Lee JY, Lee J, Loos RJF, Ma RCW, Morris AD, O'Donnell CJ, Palmer CNA, Pankow J, Park KS, Rasheed A, Saleheen D, Sim X, Small KS, Teo YY, Haiman C, Hanis CL, Henderson BE, Orozco L, Tusié-Luna T, Dewey FE, Baras A, Gieger C, Meitinger T, Strauch K, Lange L, Grarup N, Hansen T, Pedersen O, Zeitler P, Dabelea D, Abecasis G, Bell GI, Cox NJ, Seielstad M, Sladek R, Meigs JB, Rich SS, Rotter JI, Altshuler D, Burtt NP, Scott LJ, Morris AP, Florez JC, McCarthy MI, Boehnke M. Exome sequencing of 20,791 cases of type 2 diabetes and 24,440 controls. Nature 2019; 570:71-76. [PMID: 31118516 PMCID: PMC6699738 DOI: 10.1038/s41586-019-1231-2] [Citation(s) in RCA: 190] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Accepted: 04/23/2019] [Indexed: 02/08/2023]
Abstract
Protein-coding genetic variants that strongly affect disease risk can yield relevant clues to disease pathogenesis. Here we report exome-sequencing analyses of 20,791 individuals with type 2 diabetes (T2D) and 24,440 non-diabetic control participants from 5 ancestries. We identify gene-level associations of rare variants (with minor allele frequencies of less than 0.5%) in 4 genes at exome-wide significance, including a series of more than 30 SLC30A8 alleles that conveys protection against T2D, and in 12 gene sets, including those corresponding to T2D drug targets (P = 6.1 × 10-3) and candidate genes from knockout mice (P = 5.2 × 10-3). Within our study, the strongest T2D gene-level signals for rare variants explain at most 25% of the heritability of the strongest common single-variant signals, and the gene-level effect sizes of the rare variants that we observed in established T2D drug targets will require 75,000-185,000 sequenced cases to achieve exome-wide significance. We propose a method to interpret these modest rare-variant associations and to incorporate these associations into future target or gene prioritization efforts.
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Affiliation(s)
- Jason Flannick
- Program in Metabolism, Broad Institute, Cambridge, MA, USA.
- Division of Genetics and Genomics, Boston Children's Hospital, Boston, MA, USA.
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA.
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA.
| | - Josep M Mercader
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Christian Fuchsberger
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Institute for Biomedicine, Eurac Research, Bolzano, Italy
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Miriam S Udler
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Anubha Mahajan
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Jennifer Wessel
- Department of Epidemiology, Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA
- Department of Medicine, School of Medicine, Indiana University, Indianapolis, IN, USA
- Diabetes Translational Research Center, Indiana University, Indianapolis, IN, USA
| | - Tanya M Teslovich
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Lizz Caulkins
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Ryan Koesterer
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
| | | | - Thomas W Blackwell
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, 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
| | - Jennifer A Brody
- Cardiovascular Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | | | - Ling Chen
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Siying Chen
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | - Emilio Córdova
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Adolfo Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - Maria Cortes
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Ralph A DeFronzo
- Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Lawrence Dolan
- Cincinnati Children's Hospital Medical Center, Cincinnati, OH, USA
| | - Kimberly L Drews
- Biostatistics Center, George Washington University, Rockville, MD, USA
| | - Amanda Elliott
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - James S Floyd
- Department of Medicine and Epidemiology, University of Washington, Seattle, WA, USA
| | | | - Maria Eugenia Garay-Sevilla
- Department of Medicine, The University of Chicago, Chicago, IL, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | | | - Myron Gross
- Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA
| | - Sohee Han
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea
| | - Nancy L Heard-Costa
- Department of Neurology, Boston University School of Medicine, Boston, MA, USA
- National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
| | - Anne U Jackson
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Marit E Jørgensen
- Steno Diabetes Center Copenhagen, Gentofte, Denmark
- National Institute of Public Health, University of Southern Denmark, Copenhagen, Denmark
- Greenland Centre for Health Research, University of Greenland, Nuuk, Greenland
| | - Hyun Min Kang
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Megan Kelsey
- Biostatistics Center, George Washington University, Rockville, MD, USA
| | - Bong-Jo Kim
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea
| | - Heikki A Koistinen
- Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland
- University of Helsinki and Department of Medicine, Helsinki University Central Hospital, Helsinki, Finland
- Minerva Foundation Institute for Medical Research, Helsinki, Finland
| | - Johanna Kuusisto
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicin, Kuopio University Hospital, Kuopio, Finland
| | | | - Allan Linneberg
- Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
- Center for Clinical Research and Prevention, Bispebjerg and Frederiksberg Hospital, Copenhagen, Denmark
- Department of Clinical Experimental Research, Rigshospitalet, Copenhagen, Denmark
| | - Ching-Ti Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Jianjun Liu
- Genome Institute of Singapore, Agency for Science Technology and Research, Singapore, Singapore
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Valeriya Lyssenko
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Department of Clinical Science, University of Bergen, Bergen, Norway
| | - Alisa K Manning
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital, Harvard University, Boston, MA, USA
| | - Anthony Marcketta
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Juan Manuel Malacara-Hernandez
- Department of Medicine, The University of Chicago, Chicago, IL, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | | | - Karen Matsuo
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | | | | | - Karen L Mohlke
- Department of Genetics, University of North Carolina Chapel Hill, Chapel Hill, NC, 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
| | - Anne Ndungu
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Maggie C Y Ng
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Colm O'Dushlaine
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Anthony J Payne
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | | | - Wendy S Post
- Division of Cardiology, Department of Medicine, Johns Hopkins University, Baltimore, MD, USA
| | - Michael Preuss
- Charles R. Bronfman Institute of Personalized Medicine, Mount Sinai School of Medicine, New York, NY, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, USA
- 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
| | - Ramachandran S Vasan
- National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Preventive Medicine & Epidemiology, Medicine, Boston University School of Medicine, Boston, MA, USA
| | - N William Rayner
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Department of Human Genetics, Wellcome Trust Sanger Institute, Hinxton, UK
| | | | | | - Neil R Robertson
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
| | - Nicola Santoro
- Department of Pediatrics, Yale University, New Haven, CT, USA
| | - Claudia Schurmann
- Charles R. Bronfman Institute of Personalized Medicine, Mount Sinai School of Medicine, New York, NY, USA
| | - Wing Yee So
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Xavier Soberón
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Heather M Stringham
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Tim M Strom
- Institute of Human Genetics, Technische Universität München, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
| | - Claudia H T Tam
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Farook Thameem
- Health Science Center, Department of Biochemistry, Faculty of Medicine, Kuwait University, Safat, Kuwait
| | - Brian Tomlinson
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
| | - Jason M Torres
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
| | - Russell P Tracy
- Department of Pathology and Laboratory Medicine, The Robert Larner M.D. College of Medicine, University of Vermont, Burlington, VT, USA
- Department of Biochemistry, The Robert Larner M.D. College of Medicine, University of Vermont, Burlington, VT, USA
| | - Rob M van Dam
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Department of Nutrition, Harvard School of Public Health, Boston, MA, USA
| | - Marijana Vujkovic
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
| | - Shuai Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Ryan P Welch
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Daniel R Witte
- Department of Public Health, Aarhus University, Aarhus, Denmark
- Danish Diabetes Academy, Odense, Denmark
| | - Tien-Yin Wong
- Singapore Eye Research Institute, Singapore National Eye Centre, Singapore, Singapore
- Duke-NUS Medical School Singapore, Singapore, Singapore
- Department of Ophthalmology, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
| | - Gil Atzmon
- Department of Medicine, Albert Einstein College of Medicine, New York, NY, USA
- Faculty of Natural Science, University of Haifa, Haifa, Israel
- Department of Genetics, Albert Einstein College of Medicine, New York, NY, USA
| | - Nir Barzilai
- Department of Medicine, Albert Einstein College of Medicine, New York, NY, USA
- Department of Genetics, Albert Einstein College of Medicine, New York, NY, USA
| | - John Blangero
- Department of Human Genetics, University of Texas Rio Grande Valley, Edinburg, TX, USA
- South Texas Diabetes and Obesity Institute, Brownsville, TX, USA
| | - Lori L Bonnycastle
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - Donald W Bowden
- Center for Diabetes Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Center for Genomics and Personalized Medicine Research, Wake Forest School of Medicine, Winston-Salem, NC, USA
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - John C Chambers
- Department of Epidemiology and Biostatistics, Imperial College London, London, UK
- Department of Cardiology, Ealing Hospital NHS Trust, Southall, UK
- Imperial College Healthcare NHS Trust, Imperial College London, London, UK
| | - Edmund Chan
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
| | - Ching-Yu Cheng
- Ophthalmology & Visual Sciences Academic Clinical Program (Eye ACP), Duke-NUS Medical School, Singapore, Singapore
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon, South Korea
| | - Francis S Collins
- Medical Genomics and Metabolic Genetics Branch, National Human Genome Research Institute, National Institutes of Health, Bethesda, MD, USA
| | - 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
| | - Ravindranath Duggirala
- Department of Human Genetics, University of Texas Rio Grande Valley, Edinburg, TX, USA
- South Texas Diabetes and Obesity Institute, Brownsville, TX, USA
| | - Benjamin Glaser
- Endocrinology and Metabolism Service, Hadassah-Hebrew University Medical Center, Jerusalem, Israel
| | - Clicerio Gonzalez
- Unidad de Diabetes y Riesgo Cardiovascular, Instituto Nacional de Salud Pública, Cuernavaca, Mexico
| | | | - Leif Groop
- Department of Clinical Sciences, Diabetes and Endocrinology, Lund University Diabetes Centre, Malmö, Sweden
- Institute for Molecular Genetics Finland, University of Helsinki, Helsinki, Finland
| | - Jaspal Singh Kooner
- National Heart and Lung Institute, Cardiovascular Sciences, Imperial College London, London, UK
| | - Soo Heon Kwak
- Department of Internal Medicine, Seoul National University Hospital, Seoul, South Korea
| | - Markku Laakso
- Institute of Clinical Medicine, Internal Medicine, University of Eastern Finland, Kuopio, Finland
- Department of Medicin, Kuopio University Hospital, Kuopio, Finland
| | - Donna M Lehman
- Department of Medicine, University of Texas Health Science Center, San Antonio, TX, USA
| | - Peter Nilsson
- Department of Clinical Sciences, Medicine, Lund University, Malmö, Sweden
| | - Timothy D Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - E Shyong Tai
- Department of Medicine, Yong Loo Lin School of Medicine, National University of Singapore, National University Health System, Singapore, Singapore
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Duke-NUS Medical School Singapore, Singapore, Singapore
| | - Tiinamaija Tuomi
- Institute for Molecular Genetics Finland, University of Helsinki, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
- Department of Endocrinology, Abdominal Centre, Helsinki University Hospital, Helsinki, Finland
- Research Programs Unit, Diabetes and Obesity, University of Helsinki, Helsinki, Finland
| | - Jaakko Tuomilehto
- Diabetes Prevention Unit, National Institute for Health and Welfare, Helsinki, Finland
- Center for Vascular Prevention, Danube University Krems, Krems, Austria
- Diabetes Research Group, King Abdulaziz University, Jeddah, Saudi Arabia
- Instituto de Investigacion Sanitaria del Hospital Universario LaPaz (IdiPAZ), University Hospital LaPaz, Autonomous University of Madrid, Madrid, Spain
| | - James G Wilson
- Department of Physiology and Biophysics, University of Mississippi Medical Center, Jackson, MS, USA
| | | | - Erwin Bottinger
- Charles R. Bronfman Institute of Personalized Medicine, Mount Sinai School of Medicine, New York, NY, USA
| | - Brian Burke
- Biostatistics Center, George Washington University, Rockville, MD, USA
| | | | - Juliana C N Chan
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Josée Dupuis
- National Heart Lung and Blood Institute's Framingham Heart Study, Framingham, MA, USA
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | | | - Susan R Heckbert
- Cardiovascular Health Research Unit, University of Washington, Seattle, WA, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Mi Yeong Hwang
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea
| | - Young Jin Kim
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea
| | | | - Jong-Young Lee
- Department of Business Data Convergence, Chungbuk National University, Gyeonggi-do, South Korea
| | - Juyoung Lee
- Division of Genome Research, Center for Genome Science, National Institute of Health, Chungcheongbuk-do, South Korea
| | - Ruth J F Loos
- Charles R. Bronfman Institute of Personalized Medicine, Mount Sinai School of Medicine, New York, NY, USA
- The Mindich Child Health and Development Insititute, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Ronald C W Ma
- Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Hong Kong, China
- Li Ka Shing Institute of Health Sciences, The Chinese University of Hong Kong, Hong Kong, China
- Hong Kong Institute of Diabetes and Obesity, The Chinese University of Hong Kong, Hong Kong, China
| | - Andrew D Morris
- Clinical Research Centre, Centre for Molecular Medicine, Ninewells Hospital and Medical School, Dundee, UK
| | - Christopher J O'Donnell
- Department of Pediatrics, Harvard Medical School, Boston, MA, USA
- Section of Cardiology, Department of Medicine, VA Boston Healthcare, Boston, MA, USA
- Brigham and Women's Hospital, Boston, MA, USA
- Intramural Administration Management Branch, National Heart Lung and Blood Institute, NIH, Framingham, MA, USA
| | - Colin N A Palmer
- Pat Macpherson Centre for Pharmacogenetics and Pharmacogenomics, Medical Research Institute, Ninewells Hospital and Medical School, Dundee, UK
| | - James Pankow
- Division of Epidemiology and Community Health, University of Minnesota, Minneapolis, MN, USA
| | - Kyong Soo Park
- National Heart and Lung Institute, Cardiovascular Sciences, Imperial College London, London, UK
- Department of Molecular Medicine and Biopharmaceutical Sciences, Graduate School of Convergence Science and Technology, Seoul National University, Seoul, South Korea
- Department of Internal Medicine, Seoul National University College of Medicine, Seoul, South Korea
| | - Asif Rasheed
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Danish Saleheen
- Department of Biostatistics and Epidemiology, University of Pennsylvania, Philadelphia, PA, USA
- Center for Non-Communicable Diseases, Karachi, Pakistan
| | - Xueling Sim
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
| | - Kerrin S Small
- Department of Twin Research and Genetic Epidemiology, King's College London, London, UK
| | - Yik Ying Teo
- Saw Swee Hock School of Public Health, National University of Singapore, Singapore, Singapore
- Life Sciences Institute, National University of Singapore, Singapore, Singapore
- Department of Statistics and Applied Probability, National University of Singapore, Singapore, Singapore
| | - Christopher Haiman
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Craig L Hanis
- Human Genetics Center, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - Brian E Henderson
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Lorena Orozco
- Instituto Nacional de Medicina Genómica, Mexico City, Mexico
| | - Teresa Tusié-Luna
- Instituto Nacional de Ciencias Medicas y Nutricion, Mexico City, Mexico
- Instituto de Investigaciones Biomédicas, Departamento de Medicina Genómica y Toxicología, Universidad Nacional Autónoma de México, Mexico City, Mexico
| | - Frederick E Dewey
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Aris Baras
- Regeneron Genetics Center, Regeneron Pharmaceuticals, Tarrytown, NY, USA
| | - Christian Gieger
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- German Center for Diabetes Research (DZD e.V.), Neuherberg, Germany
| | - Thomas Meitinger
- Institute of Human Genetics, Technische Universität München, Munich, Germany
- Institute of Human Genetics, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Deutsches Forschungszentrum für Herz-Kreislauferkrankungen (DZHK), Partner Site Munich Heart Alliance, Munich, Germany
| | - Konstantin Strauch
- Research Unit of Molecular Epidemiology, Institute of Epidemiology, Helmholtz Zentrum München, German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Genetic Epidemiology, Ludwig-Maximilians-Universität, Neuherberg, Germany
| | - Leslie Lange
- Department of Medicine, University of Colorado Denver, Aurora, CO, USA
| | - Niels Grarup
- 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
- Faculty of Health Sciences, University of Southern Denmark, Odense, Denmark
| | - Oluf Pedersen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark
| | - Philip Zeitler
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA
| | - Dana Dabelea
- Department of Epidemiology, Colorado School of Public Health, Aurora, CO, USA
| | - Goncalo Abecasis
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Graeme I Bell
- Department of Medicine, The University of Chicago, Chicago, IL, USA
- Department of Human Genetics, The University of Chicago, Chicago, IL, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University, Nashville, TN, USA
| | - Mark Seielstad
- Department of Laboratory Medicine & Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
- Blood Systems Research Institute, San Francisco, CA, USA
| | - Rob Sladek
- Department of Human Genetics, McGill University, Montreal, Quebec, Canada
- Division of Endocrinology and Metabolism, Department of Medicine, McGill University, Montreal, Quebec, Canada
- McGill University and Génome Québec Innovation Centre, Montreal, Quebec, Canada
| | - James B Meigs
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Division of General Internal Medicine, Massachusetts General Hospital, Boston, MA, USA
| | - Steve S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Jerome I Rotter
- Department of Pediatrics, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Department of Medicine, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
- Institute for Translational Genomics and Population Sciences, Los Angeles BioMedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - David Altshuler
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Genetics, Harvard Medical School, Boston, MA, USA
- Department of Biology, Massachusetts Institute of Technology, Cambridge, MA, USA
- Department of Molecular Biology, Massachusetts General Hospital, Boston, MA, USA
| | - Noël P Burtt
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
| | - Laura J Scott
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
| | - Andrew P Morris
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Department of Biostatistics, University of Liverpool, Liverpool, UK
| | - Jose C Florez
- Program in Metabolism, Broad Institute, Cambridge, MA, USA
- Program in Medical & Population Genetics, Broad Institute, Cambridge, MA, USA
- Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Diabetes Research Center (Diabetes Unit), Massachusetts General Hospital, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
| | - Mark I McCarthy
- Wellcome Centre for Human Genetics, Nuffield Department of Medicine, University of Oxford, Oxford, UK
- Oxford Centre for Diabetes, Endocrinology and Metabolism, Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- Oxford NIHR Biomedical Research Centre, Oxford University Hospitals Trust, Oxford, UK
| | - Michael Boehnke
- Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA
- Center for Statistical Genetics, University of Michigan, Ann Arbor, MI, USA
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Association of FMO3 Variants with Blood Pressure in the Atherosclerosis Risk in Communities Study. Int J Hypertens 2019; 2019:2137629. [PMID: 30906589 PMCID: PMC6397986 DOI: 10.1155/2019/2137629] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/01/2018] [Revised: 01/23/2019] [Accepted: 02/03/2019] [Indexed: 12/03/2022] Open
Abstract
Flavin containing monooxygenase 3 [FMO3] encodes dimethylaniline monooxygenase [N-oxide-forming] 3, which breaks down nitrogen-containing compounds, and has been implicated in blood pressure regulation. Studies have reported conflicting results of the association of a common nonsynonymous variant, E158K (rs2266782), with hypertension. We examined the associations of E158K, along with rare and low frequency exonic variants (minor allele frequency [MAF]<5%) in FMO3 with hypertension, systolic blood pressure (SBP), and diastolic blood pressure (DBP). We included 7,350 European Americans and 2,814 African Americans in the Atherosclerosis Risk in Communities (ARIC) study with exome sequencing of FMO3. The association of FMO3 variants with SBP and DBP was tested using single variant and gene-based tests followed by the replication or interrogation of significant variants in ancestry-specific cohorts based on Bonferroni corrected thresholds. E158K had significant association with higher SBP in African Americans in ARIC (p=0.03), and two low frequency variants had significant association with higher SBP in African Americans (rs200985584, MAF 0.1%, p=0.0003) and European Americans (rs75904274, MAF 1.7%, p=0.006). These associations were not significant with additional samples: E158K in a meta-analysis of SBP of African ancestry (N=30,841, p=0.43) that included ARIC participants and the two low frequency variants in an independent ancestry-specific exome sequencing study of blood pressure (rs200985584, p=0.94; rs75904274, p=0.81). Our study does not support the association of E158K and low frequency variants in FMO3 with blood pressure and demonstrates the importance of replication in genetic studies.
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Detection of Putative Functional Single Nucleotide Polymorphisms in Blood Pressure Loci and Validation of Association Between Single Nucleotide Polymorphism in WBP1L and Hypertension in the Chinese Han Population. J Cardiovasc Pharmacol 2018; 73:48-55. [PMID: 30422892 DOI: 10.1097/fjc.0000000000000633] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
We have performed a gene-based association study and detected several important blood pressure (BP)-associated genes. In this study, we explored functional variants in these genes by bioinformatics analysis and validated the associations between the functional single nucleotide polymorphisms (SNPs) and hypertension with public data and our in-house data of 857 cases and 927 controls. We found various functional variants in the BP-associated genes, including missense mutations and phosphorylation-related SNPs. Most of these SNPs were associated with expressions of the local genes. Some of these SNPs were associated with coronary artery disease or ischemic stroke. The associations between 12 functional SNPs in 7 genes and BP were validated (P < 5 × 10). The intronic SNP rs176185, which may influence promoter histone, enhancer histone, DNase and regulatory motifs and showed cis-eQTL effect on WBP1L, was associated with hypertension in the Chinese Han population (P = 0.0119). Our study detected plenty of potential functional SNPs in the BP-associated genes and demonstrated that rs176185 may be associated with hypertension in the Chinese Han population.
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Nandakumar P, Morrison AC, Grove ML, Boerwinkle E, Chakravarti A. Contributions of rare coding variants in hypotension syndrome genes to population blood pressure variation. Medicine (Baltimore) 2018; 97:e11865. [PMID: 30113482 PMCID: PMC6113003 DOI: 10.1097/md.0000000000011865] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/21/2022] Open
Abstract
Rare variants, in particular renal salt handling genes, contribute to monogenic forms of hypertension and hypotension syndromes with electrolyte abnormalities. A study by Ji et al (2008) demonstrated this effect for rare loss-of-function coding variants in SLC12A3 (NCCT), SLC12A1 (NKCC2), and KCNJ1 (ROMK) that led to reduction of ∼6 mm Hg for SBP and ∼3 mm Hg for DBP among carriers in 2492 European ancestry Framingham Heart Study (FHS) subjects. These findings support a potentially large role for these variants in interindividual variation in systolic and diastolic blood pressure (SBP, DBP) in the population. The present study focuses on replicating the analyses completed by Ji et al to identify effects of rare variants in the population-based Atherosclerosis Risk in Communities (ARIC) study.We attempted to replicate the findings by Ji et al by applying their criteria to identify putative loss-of-function variants with allele frequency <0.001 and complete conservation across a set of orthologs, to exome sequencing data from 7444 European ancestry participants of the ARIC study.Although we failed to replicate the previous findings when applying their methods to the ARIC study data, we observed a similar effect when we restricted analyses to the subset of variants they observed.These results simultaneously support the utility of exome sequencing data for studying extremely rare coding variants in hypertension and underscore the need for improved filtering methods for identifying functional variants in human sequences.
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Affiliation(s)
- Priyanka Nandakumar
- Center for Complex Disease Genomics Predoctoral Training Program in Human Genetics and Molecular Biology, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD Human Genome Sequencing Center, Baylor College of Medicine 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. Center for Human Genetics and Genomics, NYU School of Medicine, New York, NY
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Abstract
PURPOSE OF REVIEW Evidence that artificial intelligence (AI) is useful for predicting risk factors for hypertension and its management is emerging. However, we are far from harnessing the innovative AI tools to predict these risk factors for hypertension and applying them to personalized management. This review summarizes recent advances in the computer science and medical field, illustrating the innovative AI approach for potential prediction of early stages of hypertension. Additionally, we review ongoing research and future implications of AI in hypertension management and clinical trials, with an eye towards personalized medicine. RECENT FINDINGS Although recent studies demonstrate that AI in hypertension research is feasible and possibly useful, AI-informed care has yet to transform blood pressure (BP) control. This is due, in part, to lack of data on AI's consistency, accuracy, and reliability in the BP sphere. However, many factors contribute to poorly controlled BP, including biological, environmental, and lifestyle issues. AI allows insight into extrapolating data analytics to inform prescribers and patients about specific factors that may impact their BP control. To date, AI has been mainly used to investigate risk factors for hypertension, but has not yet been utilized for hypertension management due to the limitations of study design and of physician's engagement in computer science literature. The future of AI with more robust architecture using multi-omics approaches and wearable technology will likely be an important tool allowing to incorporate biological, lifestyle, and environmental factors into decision-making of appropriate drug use for BP control.
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Jentsch TJ, Pusch M. CLC Chloride Channels and Transporters: Structure, Function, Physiology, and Disease. Physiol Rev 2018; 98:1493-1590. [DOI: 10.1152/physrev.00047.2017] [Citation(s) in RCA: 214] [Impact Index Per Article: 35.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
CLC anion transporters are found in all phyla and form a gene family of eight members in mammals. Two CLC proteins, each of which completely contains an ion translocation parthway, assemble to homo- or heteromeric dimers that sometimes require accessory β-subunits for function. CLC proteins come in two flavors: anion channels and anion/proton exchangers. Structures of these two CLC protein classes are surprisingly similar. Extensive structure-function analysis identified residues involved in ion permeation, anion-proton coupling and gating and led to attractive biophysical models. In mammals, ClC-1, -2, -Ka/-Kb are plasma membrane Cl−channels, whereas ClC-3 through ClC-7 are 2Cl−/H+-exchangers in endolysosomal membranes. Biological roles of CLCs were mostly studied in mammals, but also in plants and model organisms like yeast and Caenorhabditis elegans. CLC Cl−channels have roles in the control of electrical excitability, extra- and intracellular ion homeostasis, and transepithelial transport, whereas anion/proton exchangers influence vesicular ion composition and impinge on endocytosis and lysosomal function. The surprisingly diverse roles of CLCs are highlighted by human and mouse disorders elicited by mutations in their genes. These pathologies include neurodegeneration, leukodystrophy, mental retardation, deafness, blindness, myotonia, hyperaldosteronism, renal salt loss, proteinuria, kidney stones, male infertility, and osteopetrosis. In this review, emphasis is laid on biophysical structure-function analysis and on the cell biological and organismal roles of mammalian CLCs and their role in disease.
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Affiliation(s)
- Thomas J. Jentsch
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP) and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, Germany; and Istituto di Biofisica, Consiglio Nazionale delle Ricerche, Genova, Italy
| | - Michael Pusch
- Leibniz-Forschungsinstitut für Molekulare Pharmakologie (FMP) and Max-Delbrück-Centrum für Molekulare Medizin (MDC), Berlin, Germany; and Istituto di Biofisica, Consiglio Nazionale delle Ricerche, Genova, Italy
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Affiliation(s)
- Donna K. Arnett
- From the College of Public Health, University of Kentucky, Lexington
| | - Steven A. Claas
- From the College of Public Health, University of Kentucky, Lexington
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Gulati A, Somlo S. Whole exome sequencing: a state-of-the-art approach for defining (and exploring!) genetic landscapes in pediatric nephrology. Pediatr Nephrol 2018; 33:745-761. [PMID: 28660367 DOI: 10.1007/s00467-017-3698-0] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/06/2017] [Revised: 05/04/2017] [Accepted: 05/09/2017] [Indexed: 12/30/2022]
Abstract
The genesis of whole exome sequencing as a powerful tool for detailing the protein coding sequence of the human genome was conceptualized based on the availability of next-generation sequencing technology and knowledge of the human reference genome. The field of pediatric nephrology enriched with molecularly unsolved phenotypes is allowing the clinical and research application of whole exome sequencing to enable novel gene discovery and provide amendment of phenotypic misclassification. Recent studies in the field have informed us that newer high-throughput sequencing techniques are likely to be of high yield when applied in conjunction with conventional genomic approaches such as linkage analysis and other strategies used to focus subsequent analysis. They have also emphasized the need for the validation of novel genetic findings in large collaborative cohorts and the production of robust corroborative biological data. The well-structured application of comprehensive genomic testing in clinical and research arenas will hopefully continue to advance patient care and precision medicine, but does call for attention to be paid to its integrated challenges.
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Affiliation(s)
- Ashima Gulati
- Division of Nephrology, Department of Pediatrics, Yale University School of Medicine, New Haven, CT, USA.
| | - Stefan Somlo
- Departments of Internal Medicine and Genetics, Yale University School of Medicine, New Haven, CT, USA
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Benjamin EJ, Virani SS, Callaway CW, Chamberlain AM, Chang AR, Cheng S, Chiuve SE, Cushman M, Delling FN, Deo R, de Ferranti SD, Ferguson JF, Fornage M, Gillespie C, Isasi CR, Jiménez MC, Jordan LC, Judd SE, Lackland D, Lichtman JH, Lisabeth L, Liu S, Longenecker CT, Lutsey PL, Mackey JS, Matchar DB, Matsushita K, Mussolino ME, Nasir K, O'Flaherty M, Palaniappan LP, Pandey A, Pandey DK, Reeves MJ, Ritchey MD, Rodriguez CJ, Roth GA, Rosamond WD, Sampson UKA, Satou GM, Shah SH, Spartano NL, Tirschwell DL, Tsao CW, Voeks JH, Willey JZ, Wilkins JT, Wu JH, Alger HM, Wong SS, Muntner P. Heart Disease and Stroke Statistics-2018 Update: A Report From the American Heart Association. Circulation 2018; 137:e67-e492. [PMID: 29386200 DOI: 10.1161/cir.0000000000000558] [Citation(s) in RCA: 4489] [Impact Index Per Article: 748.2] [Reference Citation Analysis] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
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Joshu CE, Barber JR, Coresh J, Couper DJ, Mosley TH, Vitolins MZ, Butler KR, Nelson HH, Prizment AE, Selvin E, Tooze JA, Visvanathan K, Folsom AR, Platz EA. Enhancing the Infrastructure of the Atherosclerosis Risk in Communities (ARIC) Study for Cancer Epidemiology Research: ARIC Cancer. Cancer Epidemiol Biomarkers Prev 2018; 27:295-305. [PMID: 29263187 PMCID: PMC5835193 DOI: 10.1158/1055-9965.epi-17-0696] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2017] [Revised: 10/05/2017] [Accepted: 12/19/2017] [Indexed: 01/03/2023] Open
Abstract
Background: We describe the expansion of the Atherosclerosis Risk in Communities (ARIC) Study into a cancer cohort. In 1987 to 1989, ARIC recruited 15,792 participants 45 to 64 years old to be sex (55% female), race (27% black), and geographically diverse. ARIC has exceptional data collected during 6 clinical visits and calls every 6 months, repeated biospecimens, and linkage to Medicare claims data.Methods: We established a Cancer Coordinating Center to implement infrastructure activities, convened a Working Group for data use, leveraged ARIC staff and procedures, and developed protocols. We initiated a cancer-specific participant contact, added questions to existing contacts, obtained permission to collect medical records and tissue, abstracted records, linked with state cancer registries, and adjudicated cases and characterizing data.Results: Through 2012, we ascertained and characterized 4,743 incident invasive, first, and subsequent primary cancers among 4,107 participants and 1,660 cancer-related deaths. We generated a total cancer incidence and mortality analytic case file, and analytic case files for bladder, breast, colorectal, liver, lung, pancreas, and prostate cancer incidence, mortality, and case fatality. Adjudication of multiple data sources improved case records and identified cancers not identified via registries. From 2013 onward, we ascertain cases from self-report coupled with medical records. Additional cancer registry linkages are planned.Conclusions: Compared with starting a new cohort, expanding a cardiovascular cohort into ARIC Cancer was an efficient strategy. Our efforts yielded enhanced case files with 25 years of follow-up.Impact: Now that the cancer infrastructure is established, ARIC is contributing its unique features to modern cancer epidemiology research. Cancer Epidemiol Biomarkers Prev; 27(3); 295-305. ©2017 AACR.
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Affiliation(s)
- Corinne E Joshu
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland
| | - John R Barber
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - David J Couper
- Department of Biostatistics, University of North Carolina at Chapel Hill School of Global Public Health, Chapel Hill, North Carolina
| | - Thomas H Mosley
- Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
- Division of Neurology, University of Mississippi Medical Center, Jackson, Mississippi
| | - Mara Z Vitolins
- Department of Epidemiology and Prevention, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Kenneth R Butler
- Division of Geriatrics, University of Mississippi Medical Center, Jackson, Mississippi
| | - Heather H Nelson
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Anna E Prizment
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Elizabeth Selvin
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Welch Center for Prevention, Epidemiology and Clinical Research, Johns Hopkins University, Baltimore, Maryland
| | - Janet A Tooze
- Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston-Salem, North Carolina
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, Maryland
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland
| | - Aaron R Folsom
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, Minnesota
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland
- Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, Maryland
- James Buchanan Brady Urological Institute, Johns Hopkins University School of Medicine, Baltimore, Maryland
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Russo A, Di Gaetano C, Cugliari G, Matullo G. Advances in the Genetics of Hypertension: The Effect of Rare Variants. Int J Mol Sci 2018; 19:E688. [PMID: 29495593 PMCID: PMC5877549 DOI: 10.3390/ijms19030688] [Citation(s) in RCA: 34] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Revised: 02/19/2018] [Accepted: 02/26/2018] [Indexed: 12/22/2022] Open
Abstract
Worldwide, hypertension still represents a serious health burden with nine million people dying as a consequence of hypertension-related complications. Essential hypertension is a complex trait supported by multifactorial genetic inheritance together with environmental factors. The heritability of blood pressure (BP) is estimated to be 30-50%. A great effort was made to find genetic variants affecting BP levels through Genome-Wide Association Studies (GWAS). This approach relies on the "common disease-common variant" hypothesis and led to the identification of multiple genetic variants which explain, in aggregate, only 2-3% of the genetic variance of hypertension. Part of the missing genetic information could be caused by variants too rare to be detected by GWAS. The use of exome chips and Next-Generation Sequencing facilitated the discovery of causative variants. Here, we report the advances in the detection of novel rare variants, genes, and/or pathways through the most promising approaches, and the recent statistical tests that have emerged to handle rare variants. We also discuss the need to further support rare novel variants with replication studies within larger consortia and with deeper functional studies to better understand how new genes might improve patient care and the stratification of the response to antihypertensive treatments.
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Affiliation(s)
- Alessia Russo
- Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
- Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy.
| | - Cornelia Di Gaetano
- Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
- Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy.
| | - Giovanni Cugliari
- Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
- Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy.
| | - Giuseppe Matullo
- Department of Medical Sciences, University of Turin, 10126 Turin, Italy.
- Italian Institute for Genomic Medicine (IIGM, Formerly HuGeF), 10126 Turin, Italy.
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31
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Yuan Y, You Y, Wen Y, Liu J, Li H, Zhang Y, Wu N, Liu S, Zhang S, Chen J, Ai J, Zhang W, Zhang Y. Identification of novel genetic loci GAL3ST4 and CHGB involved in susceptibility to leprosy. Sci Rep 2017; 7:16352. [PMID: 29180661 PMCID: PMC5703986 DOI: 10.1038/s41598-017-16422-1] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 10/30/2017] [Indexed: 01/26/2023] Open
Abstract
Leprosy has long been thought to have a strong genetic component, and so far, only positional cloning and genomewide association studies have been used to study the genetic susceptibility to leprosy,while whole exome sequencing (WES) approach has not yet been applied. In this study, we used WES approach on four leprosy patients and four healthy control relatives from two leprosy families. We found three new susceptible loci of leprosy, one in GAL3ST4 and two in CHGB. We went on to validate the findings of WES using 151 leprosy cases and 226 healthy controls by Sanger sequencing. Stratified by gender, GAL3ST4 was found to be the susceptible gene only for the female population, and CHGB48 and CHGB23 were susceptibile to leprosy for the male population, respectively). Moreover, the gene expression levels of the three susceptible loci were measured by real-time PCR after the stimulation by M. leprae antigens in the PBMC (peripheral blood mononuclear cells) of 69 healthy people. The results showed that the female subjects with high frequent genotype in GAL3ST4 had a fivefold elevated expression. We suggest the polymorphisms in GAL3ST4 in different population are associated with increased risk of leprosy.
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Affiliation(s)
- Youhua Yuan
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China.,Department of Clinical laboratory, Henan Provincial People's Hospital, Zhengzhou, China
| | - Yuangang You
- Beijing Tropical Medicine Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, China.
| | - Yan Wen
- Beijing Tropical Medicine Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Jian Liu
- Beijing Tropical Medicine Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Huanying Li
- Beijing Tropical Medicine Research Institute, Beijing Friendship Hospital, Capital Medical University, Beijing, China
| | - Yumeng Zhang
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Nan Wu
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shuang Liu
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Shanshan Zhang
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jiazhen Chen
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Jingwen Ai
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Wenhong Zhang
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China
| | - Ying Zhang
- Key Laboratory of Medical Virology, Department of Infectious Diseases, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, China. .,Department of Molecular Microbiology and Immunology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, Maryland, USA.
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Abstract
The erythrocyte contains a network of pathways that regulate salt and water content in the face of extracellular and intracellular osmotic perturbations. This allows the erythrocyte to maintain a narrow range of cell hemoglobin concentration, a process critical for normal red blood cell function and survival. Primary disorders that perturb volume homeostasis jeopardize the erythrocyte and may lead to its premature destruction. These disorders are marked by clinical, laboratory, and physiologic heterogeneity. Recent studies have revealed that these disorders are also marked by genetic heterogeneity. They have implicated roles for several proteins, PIEZO1, a mammalian mechanosensory protein; GLUT1, the glucose transporter; SLC4A1, the anion transporter; RhAG, the Rh-associated glycoprotein; KCNN4, the Gardos channel; and ABCB6, an adenosine triphosphate-binding cassette family member, in the maintenance of erythrocyte volume homeostasis. Secondary disorders of erythrocyte hydration include sickle cell disease, thalassemia, hemoglobin CC, and hereditary spherocytosis, where cellular dehydration may be a significant contributor to disease pathology and clinical complications. Understanding the pathways regulating erythrocyte water and solute content may reveal innovative strategies to maintain normal volume in disorders associated with primary or secondary cellular dehydration. These mechanisms will serve as a paradigm for other cells and may reveal new therapeutic targets for disease prevention and treatment beyond the erythrocyte.
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33
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Seidel E, Scholl UI. Genetic mechanisms of human hypertension and their implications for blood pressure physiology. Physiol Genomics 2017; 49:630-652. [PMID: 28887369 DOI: 10.1152/physiolgenomics.00032.2017] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023] Open
Abstract
Hypertension, or elevated blood pressure, constitutes a major public health burden that affects more than 1 billion people worldwide and contributes to ~9 million deaths annually. Hereditary factors are thought to contribute to up to 50% of interindividual blood pressure variability. Blood pressure in the general population approximately shows a normal distribution and is thought to be a polygenic trait. In rare cases, early-onset hypertension or hypotension are inherited as Mendelian traits. The identification of the underlying Mendelian genes and variants has contributed to our understanding of the physiology of blood pressure regulation, emphasizing renal salt handling and the renin angiotensin aldosterone system as players in the determination of blood pressure. Genome-wide association studies (GWAS) have revealed more than 100 variants that are associated with blood pressure, typically with small effect sizes, which cumulatively explain ~3.5% of blood pressure trait variability. Several GWAS associations point to a role of the vasculature in the pathogenesis of hypertension. Despite these advances, the majority of the genetic contributors to blood pressure regulation are currently unknown; whether large-scale exome or genome sequencing studies will unravel these factors remains to be determined.
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Affiliation(s)
- Eric Seidel
- Department of Nephrology, Medical School, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
| | - Ute I Scholl
- Department of Nephrology, Medical School, Heinrich Heine University Düsseldorf, Düsseldorf, Germany
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34
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Li M, Kroetz DL. Bevacizumab-induced hypertension: Clinical presentation and molecular understanding. Pharmacol Ther 2017; 182:152-160. [PMID: 28882537 DOI: 10.1016/j.pharmthera.2017.08.012] [Citation(s) in RCA: 81] [Impact Index Per Article: 11.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Bevacizumab is a vascular endothelial growth factor-A-specific angiogenesis inhibitor indicated as an adjunct to chemotherapy for the treatment of several types of cancer. Hypertension is commonly observed during bevacizumab treatment, and high-grade toxicity can limit therapy and lead to other cardiovascular complications. The factors that contribute to interindividual variability in blood pressure response to bevacizumab treatment are not well understood. In this review, we outline research efforts to understand the mechanisms and pathophysiology of hypertension resulting from bevacizumab treatment. Moreover, we highlight current knowledge of the pharmacogenetics of bevacizumab-induced hypertension, which may be used to develop strategies to prevent or minimize this toxicity.
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Affiliation(s)
- Megan Li
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States
| | - Deanna L Kroetz
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, United States.
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35
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Sabo A, Mishra P, Dugan-Perez S, Voruganti VS, Kent JW, Kalra D, Cole SA, Comuzzie AG, Muzny DM, Gibbs RA, Butte NF. Exome sequencing reveals novel genetic loci influencing obesity-related traits in Hispanic children. Obesity (Silver Spring) 2017; 25:1270-1276. [PMID: 28508493 PMCID: PMC5687071 DOI: 10.1002/oby.21869] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/02/2017] [Revised: 03/28/2017] [Accepted: 03/30/2017] [Indexed: 01/01/2023]
Abstract
OBJECTIVE To perform whole exome sequencing in 928 Hispanic children and identify variants and genes associated with childhood obesity. METHODS Single-nucleotide variants (SNVs) were identified from Illumina whole exome sequencing data using integrated read mapping, variant calling, and an annotation pipeline (Mercury). Association analyses of 74 obesity-related traits and exonic variants were performed using SeqMeta software. Rare autosomal variants were analyzed using gene-based association analyses, and common autosomal variants were analyzed at the SNV level. RESULTS (1) Rare exonic variants in 10 genes and 16 common SNVs in 11 genes that were associated with obesity traits in a cohort of Hispanic children were identified, (2) novel rare variants in peroxisome biogenesis factor 1 (PEX1) associated with several obesity traits (weight, weight z score, BMI, BMI z score, waist circumference, fat mass, trunk fat mass) were discovered, and (3) previously reported SNVs associated with childhood obesity were replicated. CONCLUSIONS Convergence of whole exome sequencing, a family-based design, and extensive phenotyping discovered novel rare and common variants associated with childhood obesity. Linking PEX1 to obesity phenotypes poses a novel mechanism of peroxisomal biogenesis and metabolism underlying the development of childhood obesity.
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Affiliation(s)
- Aniko Sabo
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Pamela Mishra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | | | - V. Saroja Voruganti
- Department of Nutrition and UNC Nutrition Research Institute, University of North Carolina, Chapel Hill, NC, USA
| | - Jack W. Kent
- Department of Genetics, Texas Biomedical Research institute, San Antonio, TX, USA
| | - Divya Kalra
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Shelley A. Cole
- Department of Genetics, Texas Biomedical Research institute, San Antonio, TX, USA
| | - Anthony G. Comuzzie
- Department of Genetics, Texas Biomedical Research institute, San Antonio, TX, USA
| | - Donna M. Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Richard A. Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX
| | - Nancy F. Butte
- USDA/ARS Children’s Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX
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36
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Morrison AC, Huang Z, Yu B, Metcalf G, Liu X, Ballantyne C, Coresh J, Yu F, Muzny D, Feofanova E, Rustagi N, Gibbs R, Boerwinkle E. Practical Approaches for Whole-Genome Sequence Analysis of Heart- and Blood-Related Traits. Am J Hum Genet 2017; 100:205-215. [PMID: 28089252 DOI: 10.1016/j.ajhg.2016.12.009] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2016] [Accepted: 12/14/2016] [Indexed: 01/11/2023] Open
Abstract
Whole-genome sequencing (WGS) allows for a comprehensive view of the sequence of the human genome. We present and apply integrated methodologic steps for interrogating WGS data to characterize the genetic architecture of 10 heart- and blood-related traits in a sample of 1,860 African Americans. In order to evaluate the contribution of regulatory and non-protein coding regions of the genome, we conducted aggregate tests of rare variation across the entire genomic landscape using a sliding window, complemented by an annotation-based assessment of the genome using predefined regulatory elements and within the first intron of all genes. These tests were performed treating all variants equally as well as with individual variants weighted by a measure of predicted functional consequence. Significant findings were assessed in 1,705 individuals of European ancestry. After these steps, we identified and replicated components of the genomic landscape significantly associated with heart- and blood-related traits. For two traits, lipoprotein(a) levels and neutrophil count, aggregate tests of low-frequency and rare variation were significantly associated across multiple motifs. For a third trait, cardiac troponin T, investigation of regulatory domains identified a locus on chromosome 9. These practical approaches for WGS analysis led to the identification of informative genomic regions and also showed that defined non-coding regions, such as first introns of genes and regulatory domains, are associated with important risk factor phenotypes. This study illustrates the tractable nature of WGS data and outlines an approach for characterizing the genetic architecture of complex traits.
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Affiliation(s)
- Alanna C Morrison
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA.
| | - Zhuoyi Huang
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Bing Yu
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Ginger Metcalf
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Xiaoming Liu
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Christie Ballantyne
- Section of Cardiovascular Research, Baylor College of Medicine, Houston, TX 77030, USA; Houston Methodist Debakey Heart and Vascular Center, Houston, TX 77030, USA
| | - Josef Coresh
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21287, USA
| | - Fuli Yu
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Donna Muzny
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Elena Feofanova
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA
| | - Navin Rustagi
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Richard Gibbs
- Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA
| | - Eric Boerwinkle
- Human Genetics Center, University of Texas School of Public Health, Houston, TX 77030, USA; Human Genome Sequencing Center, Baylor College of Medicine, Houston, TX 77030, USA.
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Mensah GA, Galis ZS, Fine LJ, Garcia ME, Levy DF, Gibbons GH. Building on a Legacy of Hypertension Research: Charting Our Future Together. Hypertension 2017; 69:5-10. [PMID: 27849567 PMCID: PMC5145749 DOI: 10.1161/hypertensionaha.116.06582] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/11/2023]
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38
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Bimber BN, Raboin MJ, Letaw J, Nevonen KA, Spindel JE, McCouch SR, Cervera-Juanes R, Spindel E, Carbone L, Ferguson B, Vinson A. Whole-genome characterization in pedigreed non-human primates using genotyping-by-sequencing (GBS) and imputation. BMC Genomics 2016; 17:676. [PMID: 27558348 PMCID: PMC4997765 DOI: 10.1186/s12864-016-2966-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/01/2016] [Accepted: 07/22/2016] [Indexed: 01/29/2023] Open
Abstract
BACKGROUND Rhesus macaques are widely used in biomedical research, but the application of genomic information in this species to better understand human disease is still in its infancy. Whole-genome sequence (WGS) data in large pedigreed macaque colonies could provide substantial experimental power for genetic discovery, but the collection of WGS data in large cohorts remains a formidable expense. Here, we describe a cost-effective approach that selects the most informative macaques in a pedigree for 30X WGS, followed by low-cost genotyping-by-sequencing (GBS) at 30X on the remaining macaques in order to generate sparse genotype data at high accuracy. Dense variants from the selected macaques with WGS data are then imputed into macaques having only sparse GBS data, resulting in dense genome-wide genotypes throughout the pedigree. RESULTS We developed GBS for the macaque genome using a digestion with PstI, followed by sequencing of size-selected fragments at 30X coverage. From GBS sequence data collected on all individuals in a 16-member pedigree, we characterized high-confidence genotypes at 22,455 single nucleotide variant (SNV) sites that were suitable for guiding imputation of dense sequence data from WGS. To characterize dense markers for imputation, we performed WGS at 30X coverage on nine of the 16 individuals, yielding 10,193,425 high-confidence SNVs. To validate the use of GBS data for facilitating imputation, we initially focused on chromosome 19 as a test case, using an optimized panel of 833 sparse, evenly-spaced markers from GBS and 5,010 dense markers from WGS. Using the method of "Genotype Imputation Given Inheritance" (GIGI), we evaluated the effects on imputation accuracy of 3 different strategies for selecting individuals for WGS, including 1) using "GIGI-Pick" to select the most informative individuals, 2) using the most recent generation, or 3) using founders only. We also evaluated the effects on imputation accuracy of using a range of from 1 to 9 WGS individuals for imputation. We found that the GIGI-Pick algorithm for selection of WGS individuals outperformed common heuristic approaches, and that genotype numbers and accuracy improved very little when using >5 WGS individuals for imputation. Informed by our findings, we used 4 macaques with WGS data to impute variants at up to 7,655,491 sites spanning all 20 autosomes in the 12 remaining macaques, based on their GBS genotypes at only 17,158 loci. Using a strict confidence threshold, we imputed an average of 3,680,238 variants per individual at >99 % accuracy, or an average 4,458,883 variants per individual at a more relaxed threshold, yielding >97 % accuracy. CONCLUSIONS We conclude that an optimal tradeoff between genotype accuracy, number of imputed genotypes, and overall cost exists at the ratio of one individual selected for WGS using the GIGI-Pick algorithm, per 3-5 relatives selected for GBS. This approach makes feasible the collection of accurate, dense genome-wide sequence data in large pedigreed macaque cohorts without the need for more expensive WGS data on all individuals.
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Affiliation(s)
- Benjamin N Bimber
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Michael J Raboin
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - John Letaw
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Kimberly A Nevonen
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Jennifer E Spindel
- Section of Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, USA
| | - Susan R McCouch
- Section of Plant Breeding and Genetics, School of Integrative Plant Sciences, Cornell University, Ithaca, NY, USA
| | - Rita Cervera-Juanes
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Eliot Spindel
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Lucia Carbone
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Betsy Ferguson
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA.,Oregon Health & Science University, Portland, OR, USA
| | - Amanda Vinson
- Primate Genetics Section, Oregon National Primate Research Center, Beaverton, OR, USA. .,Oregon Health & Science University, Portland, OR, USA.
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Niiranen TJ, Vasan RS. Epidemiology of cardiovascular disease: recent novel outlooks on risk factors and clinical approaches. Expert Rev Cardiovasc Ther 2016; 14:855-69. [PMID: 27057779 DOI: 10.1080/14779072.2016.1176528] [Citation(s) in RCA: 22] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/28/2023]
Abstract
INTRODUCTION Cardiovascular (CVD) risk assessment with traditional risk factors (age, sex, blood pressure, lipids, smoking and diabetes) has remained relatively invariant over the past decades despite some inaccuracies associated with this approach. However, the search for novel, robust and cost-effective risk markers of CVD risk is ongoing. AREAS COVERED A large share of the major developments in CVD risk prediction during the past five years has been made in large-scale biomarker discovery and the so called 'omics' - the rapidly growing fields of genomics, transcriptomics, epigenetics and metabolomics. This review focuses on how these new technologies are helping drive primary CVD risk estimation forward in recent years, and speculates on how they could be utilized more effectively for discovering novel risk factors in the future. Expert commentary: The search for new CVD risk factors is currently undergoing a significant revolution as the simple relationship between single risk factors and disease will have to be replaced by models that strive to integrate the whole field of omics into medicine.
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Affiliation(s)
- Teemu J Niiranen
- a National Heart, Blood and Lung Institute's and Boston University's Framingham Heart Study , Framingham , MA , USA
| | - Ramachandran S Vasan
- a National Heart, Blood and Lung Institute's and Boston University's Framingham Heart Study , Framingham , MA , USA
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