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Siland JE, Geelhoed B, Roselli C, Wang B, Lin HJ, Weiss S, Trompet S, van den Berg ME, Soliman EZ, Chen LY, Ford I, Jukema JW, Macfarlane PW, Kornej J, Lin H, Lunetta KL, Kavousi M, Kors JA, Ikram MA, Guo X, Yao J, Dörr M, Felix SB, Völker U, Sotoodehnia N, Arking DE, Stricker BH, Heckbert SR, Lubitz SA, Benjamin EJ, Alonso A, Ellinor PT, van der Harst P, Rienstra M. Resting heart rate and incident atrial fibrillation: A stratified Mendelian randomization in the AFGen consortium. PLoS One 2022; 17:e0268768. [PMID: 35594314 PMCID: PMC9122202 DOI: 10.1371/journal.pone.0268768] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 05/06/2022] [Indexed: 12/02/2022] Open
Abstract
Background Both elevated and low resting heart rates are associated with atrial fibrillation (AF), suggesting a U-shaped relationship. However, evidence for a U-shaped causal association between genetically-determined resting heart rate and incident AF is limited. We investigated potential directional changes of the causal association between genetically-determined resting heart rate and incident AF. Method and results Seven cohorts of the AFGen consortium contributed data to this meta-analysis. All participants were of European ancestry with known AF status, genotype information, and a heart rate measurement from a baseline electrocardiogram (ECG). Three strata of instrumental variable-free resting heart rate were used to assess possible non-linear associations between genetically-determined resting heart rate and the logarithm of the incident AF hazard rate: <65; 65–75; and >75 beats per minute (bpm). Mendelian randomization analyses using a weighted resting heart rate polygenic risk score were performed for each stratum. We studied 38,981 individuals (mean age 59±10 years, 54% women) with a mean resting heart rate of 67±11 bpm. During a mean follow-up of 13±5 years, 4,779 (12%) individuals developed AF. A U-shaped association between the resting heart rate and the incident AF-hazard ratio was observed. Genetically-determined resting heart rate was inversely associated with incident AF for instrumental variable-free resting heart rates below 65 bpm (hazard ratio for genetically-determined resting heart rate, 0.96; 95% confidence interval, 0.94–0.99; p = 0.01). Genetically-determined resting heart rate was not associated with incident AF in the other two strata. Conclusions For resting heart rates below 65 bpm, our results support an inverse causal association between genetically-determined resting heart rate and incident AF.
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Affiliation(s)
- J. E. Siland
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - B. Geelhoed
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - C. Roselli
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
| | - B. Wang
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
| | - H. J. Lin
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States of America
| | - S. Weiss
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics; University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
| | - S. Trompet
- Department of Cardiology, Leiden University Medical Center, Leiden, The Netherlands
- Department of Internal Medicine, Section of Gerontology and Geriatrics, Leiden University Medical Center, Leiden, The Netherlands
| | - M. E. van den Berg
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - E. Z. Soliman
- Division of Public Health Sciences and Department of Medicine, Epidemiological Cardiology Research Center, Department of Epidemiology and Prevention, Section on Cardiology, Wake Forest School of Medicine, Winston-Salem, NC, United States of America
| | - L. Y. Chen
- Cardiovascular Division, Department of Medicine, University of Minnesota Medical School, Minneapolis, MN, United States of America
| | - I. Ford
- Robertson Centre for Biostatistics, University of Glasgow, Glasgow, United Kingdom
| | - J. W. Jukema
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Einthoven Laboratory for Experimental Vascular Medicine, LUMC, Leiden, The Netherlands
- Netherlands Heart Institute, Utrecht, The Netherlands
| | - P. W. Macfarlane
- Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
| | - J. Kornej
- National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
| | - H. Lin
- National Heart Lung and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
- Section of Computational Biomedicine, Department of Medicine, Boston University School of Medicine, Boston, MA, Unites States of America
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America
- National Heart, Lung, and Blood Institute’s and Boston University’s Framingham Heart Study, Framingham, MA, United States of America
| | - M. Kavousi
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - J. A. Kors
- Department of Medical Informatics, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - M. A. Ikram
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - X. Guo
- Institute for Translational Genomics and Population Sciences, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
- Department of Pediatrics, David Geffen School of Medicine at UCLA, Los Angeles, CA, United States of America
| | - J. Yao
- Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute at Harbor-UCLA Medical Center, Torrance, CA, United States of America
| | - M. Dörr
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B-Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - S. B. Felix
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
- Department of Internal Medicine B-Cardiology, Pneumology, Infectious Diseases, Intensive Care Medicine, University Medicine Greifswald, Greifswald, Germany
| | - U. Völker
- Interfaculty Institute for Genetics and Functional Genomics; Department of Functional Genomics; University Medicine Greifswald, Greifswald, Germany
- DZHK (German Centre for Cardiovascular Research); partner site Greifswald, Greifswald, Germany
| | - N. Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, Departments of Medicine and Epidemiology, University of Washington, Seattle, WA, Unites States of America
| | - D. E. Arking
- McKusick-Nathans Institute, Department of Genetic Medicine, Johns Hopkins University SOM, Baltimore, MD, Unites States of America
| | - B. H. Stricker
- Department of Epidemiology, Erasmus University Medical Center Rotterdam, Rotterdam, The Netherlands
| | - S. R. Heckbert
- Cardiovascular Health Research Unit and the Department of Epidemiology, University of Washington, Seattle, WA, Unites States of America
| | - S. A. Lubitz
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Unites States of America
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, Unites States of America
| | - E. J. Benjamin
- Institute of Health and Wellbeing, College of Medical, Veterinary and Life Sciences, University of Glasgow, Glasgow, United Kingdom
- Department of Medicine, Boston University School of Medicine, Boston, MA, Unites States of America
- Department of Epidemiology, Boston University School of Public Health, Boston, MA, Unites States of America
| | - A. Alonso
- Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, GA, Unites States of America
| | - P. T. Ellinor
- Cardiovascular Disease Initiative, The Broad Institute of MIT and Harvard, Cambridge, MA, United States of America
- Cardiovascular Research Center, Massachusetts General Hospital, Boston, MA, Unites States of America
- Cardiac Arrhythmia Service, Massachusetts General Hospital, Boston, MA, Unites States of America
| | - P. van der Harst
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- University of Groningen, University Medical Center Groningen, Department of Genetics, Groningen, The Netherlands
- University Medical Center Utrecht, Department of Heart and Lungs, University of Utrecht, Utrecht, The Netherlands
| | - M. Rienstra
- Department of Cardiology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- * E-mail:
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Longchamps RJ, Yang SY, Castellani CA, Shi W, Lane J, Grove ML, Bartz TM, Sarnowski C, Liu C, Burrows K, Guyatt AL, Gaunt TR, Kacprowski T, Yang J, De Jager PL, Yu L, Bergman A, Xia R, Fornage M, Feitosa MF, Wojczynski MK, Kraja AT, Province MA, Amin N, Rivadeneira F, Tiemeier H, Uitterlinden AG, Broer L, Van Meurs JBJ, Van Duijn CM, Raffield LM, Lange L, Rich SS, Lemaitre RN, Goodarzi MO, Sitlani CM, Mak ACY, Bennett DA, Rodriguez S, Murabito JM, Lunetta KL, Sotoodehnia N, Atzmon G, Ye K, Barzilai N, Brody JA, Psaty BM, Taylor KD, Rotter JI, Boerwinkle E, Pankratz N, Arking DE. Genome-wide analysis of mitochondrial DNA copy number reveals loci implicated in nucleotide metabolism, platelet activation, and megakaryocyte proliferation. Hum Genet 2022; 141:127-146. [PMID: 34859289 PMCID: PMC8758627 DOI: 10.1007/s00439-021-02394-w] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Accepted: 10/22/2021] [Indexed: 12/18/2022]
Abstract
Mitochondrial DNA copy number (mtDNA-CN) measured from blood specimens is a minimally invasive marker of mitochondrial function that exhibits both inter-individual and intercellular variation. To identify genes involved in regulating mitochondrial function, we performed a genome-wide association study (GWAS) in 465,809 White individuals from the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium and the UK Biobank (UKB). We identified 133 SNPs with statistically significant, independent effects associated with mtDNA-CN across 100 loci. A combination of fine-mapping, variant annotation, and co-localization analyses was used to prioritize genes within each of the 133 independent sites. Putative causal genes were enriched for known mitochondrial DNA depletion syndromes (p = 3.09 × 10-15) and the gene ontology (GO) terms for mtDNA metabolism (p = 1.43 × 10-8) and mtDNA replication (p = 1.2 × 10-7). A clustering approach leveraged pleiotropy between mtDNA-CN associated SNPs and 41 mtDNA-CN associated phenotypes to identify functional domains, revealing three distinct groups, including platelet activation, megakaryocyte proliferation, and mtDNA metabolism. Finally, using mitochondrial SNPs, we establish causal relationships between mitochondrial function and a variety of blood cell-related traits, kidney function, liver function and overall (p = 0.044) and non-cancer mortality (p = 6.56 × 10-4).
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Affiliation(s)
- R J Longchamps
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - S Y Yang
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - C A Castellani
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
- Department of Pathology and Laboratory Medicine, Western University, London, ON, Canada
| | - W Shi
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA
| | - J Lane
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - M L Grove
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - T M Bartz
- Cardiovascular Health Research Unit, Departments of Medicine and Biostatistics, University of Washington, Seattle, WA, USA
| | - C Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - C Liu
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - K Burrows
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - A L Guyatt
- Department of Health Sciences, University of Leicester, University Road, Leicester, UK
| | - T R Gaunt
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - T Kacprowski
- Department of Functional Genomics, Interfaculty Institute for Genetics and Functional Genomics, University of Greifswald, Greifswald, Germany
- Data Science in Biomedicine, Peter L. Reichertz Institute for Medical Informatics, TU Braunschweig and Hannover Medical School, Brunswick, Germany
| | - J Yang
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - P L De Jager
- Center for Translational and Systems Neuroimmunology, Department of Neurology, Columbia University Medical Center, New York, NY, USA
- Program in Medical and Population Genetics, Broad Institute, Cambridge, MA, USA
| | - L Yu
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - A Bergman
- Department of Systems and Computational Biology, Albert Einstein College of Medicine, Bronx, NY, USA
| | - R Xia
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
| | - M Fornage
- Institute of Molecular Medicine, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, USA
| | - M F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - A T Kraja
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - M A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, USA
| | - N Amin
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - F Rivadeneira
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Social and Behavioral Science, Harvard T.H. School of Public Health, Boston, USA
| | - A G Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L Broer
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - J B J Van Meurs
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - C M Van Duijn
- Department of Epidemiology, Erasmus Medical Center, Rotterdam, The Netherlands
| | - L M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - L Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - S S Rich
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - R N Lemaitre
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - M O Goodarzi
- Division of Endocrinology, Diabetes and Metabolism, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - C M Sitlani
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - A C Y Mak
- Cardiovascular Research Institute and Institute for Human Genetics, University of California, San Francisco, CA, USA
| | - D A Bennett
- Rush Alzheimer's Disease Center and Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - S Rodriguez
- MRC Integrative Epidemiology Unit at the University of Bristol, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Oakfield House, Oakfield Grove, Bristol, UK
| | - J M Murabito
- Boston University School of Medicine, Boston University, Boston, MA, USA
| | - K L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - N Sotoodehnia
- Cardiovascular Health Research Unit, Division of Cardiology, University of Washington, Seattle, WA, USA
| | - G Atzmon
- Department of Natural Science, University of Haifa, Haifa, Israel
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - K Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - N Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - J A Brody
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, USA
| | - B M Psaty
- Cardiovascular Health Research Unit, Departments of Epidemiology, Medicine and Health Services, University of Washington, Seattle, WA, USA
| | - K D Taylor
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - J I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - E Boerwinkle
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, Human Genetics Center, The University of Texas Health Science Center at Houston, Houston, TX, USA
- Baylor College of Medicine, Human Genome Sequencing Center, Houston, TX, USA
| | - N Pankratz
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, Minneapolis, MN, USA
| | - D E Arking
- Department of Genetic Medicine, McKusick-Nathans Institute, Johns Hopkins University School of Medicine, Baltimore, MD, USA.
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3
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Sarnowski C, Cousminer DL, Franceschini N, Raffield LM, Jia G, Fernández-Rhodes L, Grant SFA, Hakonarson H, Lange LA, Long J, Sofer T, Tao R, Wallace RB, Wong Q, Zirpoli G, Boerwinkle E, Bradfield JP, Correa A, Kooperberg CL, North KE, Palmer JR, Zemel BS, Zheng W, Murabito JM, Lunetta KL. Large trans-ethnic meta-analysis identifies AKR1C4 as a novel gene associated with age at menarche. Hum Reprod 2021; 36:1999-2010. [PMID: 34021356 PMCID: PMC8213450 DOI: 10.1093/humrep/deab086] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/30/2020] [Revised: 03/12/2021] [Indexed: 12/25/2022] Open
Abstract
STUDY QUESTION Does the expansion of genome-wide association studies (GWAS) to a broader range of ancestries improve the ability to identify and generalise variants associated with age at menarche (AAM) in European populations to a wider range of world populations? SUMMARY ANSWER By including women with diverse and predominantly non-European ancestry in a large-scale meta-analysis of AAM with half of the women being of African ancestry, we identified a new locus associated with AAM in African-ancestry participants, and generalised loci from GWAS of European ancestry individuals. WHAT IS KNOWN ALREADY AAM is a highly polygenic puberty trait associated with various diseases later in life. Both AAM and diseases associated with puberty timing vary by race or ethnicity. The majority of GWAS of AAM have been performed in European ancestry women. STUDY DESIGN, SIZE, DURATION We analysed a total of 38 546 women who did not have predominantly European ancestry backgrounds: 25 149 women from seven studies from the ReproGen Consortium and 13 397 women from the UK Biobank. In addition, we used an independent sample of 5148 African-ancestry women from the Southern Community Cohort Study (SCCS) for replication. PARTICIPANTS/MATERIALS, SETTING, METHODS Each AAM GWAS was performed by study and ancestry or ethnic group using linear regression models adjusted for birth year and study-specific covariates. ReproGen and UK Biobank results were meta-analysed using an inverse variance-weighted average method. A trans-ethnic meta-analysis was also carried out to assess heterogeneity due to different ancestry. MAIN RESULTS AND THE ROLE OF CHANCE We observed consistent direction and effect sizes between our meta-analysis and the largest GWAS conducted in European or Asian ancestry women. We validated four AAM loci (1p31, 6q16, 6q22 and 9q31) with common genetic variants at P < 5 × 10-7. We detected one new association (10p15) at P < 5 × 10-8 with a low-frequency genetic variant lying in AKR1C4, which was replicated in an independent sample. This gene belongs to a family of enzymes that regulate the metabolism of steroid hormones and have been implicated in the pathophysiology of uterine diseases. The genetic variant in the new locus is more frequent in African-ancestry participants, and has a very low frequency in Asian or European-ancestry individuals. LARGE SCALE DATA N/A. LIMITATIONS, REASONS FOR CAUTION Extreme AAM (<9 years or >18 years) were excluded from analysis. Women may not fully recall their AAM as most of the studies were conducted many years later. Further studies in women with diverse and predominantly non-European ancestry are needed to confirm and extend these findings, but the availability of such replication samples is limited. WIDER IMPLICATIONS OF THE FINDINGS Expanding association studies to a broader range of ancestries or ethnicities may improve the identification of new genetic variants associated with complex diseases or traits and the generalisation of variants from European-ancestry studies to a wider range of world populations. STUDY FUNDING/COMPETING INTEREST(S) Funding was provided by CHARGE Consortium grant R01HL105756-07: Gene Discovery For CVD and Aging Phenotypes and by the NIH grant U24AG051129 awarded by the National Institute on Aging (NIA). The authors have no conflict of interest to declare.
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Affiliation(s)
- C Sarnowski
- Boston University School of Public Health, Boston, MA, USA
- Department of Epidemiology, Human Genetics and Environmental Sciences, The University of Texas Health Science Center at Houston School of Public Health, Houston, TX, USA
| | - D L Cousminer
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Genetics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - N Franceschini
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC, USA
| | - L M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - G Jia
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - L Fernández-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, Pennsylvania State University, University Park, PA, USA
| | - S F A Grant
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Endocrinology, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - H Hakonarson
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Pulmonary Medicine, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - L A Lange
- Department of Medicine, University of Colorado Denver, Anschutz Medical Campus, Aurora, CO, USA
| | - J Long
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - T Sofer
- Departments of Medicine and of Biostatistics, Harvard University, Boston, MA, USA
- Division of Sleep and Circadian Disorders, Departments of Medicine and Neurology, Brigham and Women’s Hospital, Boston, MA, USA
| | - R Tao
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, USA
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, USA
| | - R B Wallace
- University of Iowa College of Public Health, Iowa City, IA, USA
| | - Q Wong
- Department of Biostatistics, University of Washington, Seattle, WA, USA
| | - G Zirpoli
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Section of Hematology/Oncology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - E Boerwinkle
- Human Genetic Center and Department of Epidemiology, The University of Texas School of Public Health, Houston, TX, USA
| | - J P Bradfield
- Center for Applied Genomics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Division of Human Genetics, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
- Quantinuum Research, LLC, Wayne, PA, USA
| | - A Correa
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Pediatrics, University of Mississippi Medical Center, Jackson, MS, USA
- Department of Population Health Science, University of Mississippi Medical Center, Jackson, MS, USA
| | - C L Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - K E North
- Department of Epidemiology, University of North Carolina at Chapel Hill Gillings School of Global Public Health, Chapel Hill, NC, USA
- Carolina Center for Genome Sciences, University of North Carolina, Chapel Hill, NC, USA
| | - J R Palmer
- Slone Epidemiology Center at Boston University, Boston, MA, USA
- Section of Hematology/Oncology, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - B S Zemel
- Department of Pediatrics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Division of Gastroenterology, Hepatology and Nutrition, The Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - W Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt-Ingram Cancer Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - J M Murabito
- National Heart Lung and Blood Institute and Boston University’s Framingham Heart Study, Framingham, MA, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - K L Lunetta
- Boston University School of Public Health, Boston, MA, USA
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4
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Demirkan A, Lahti J, Direk N, Viktorin A, Lunetta KL, Terracciano A, Nalls MA, Tanaka T, Hek K, Fornage M, Wellmann J, Cornelis MC, Ollila HM, Yu L, Smith JA, Pilling LC, Isaacs A, Palotie A, Zhuang WV, Zonderman A, Faul JD, Sutin A, Meirelles O, Mulas A, Hofman A, Uitterlinden A, Rivadeneira F, Perola M, Zhao W, Salomaa V, Yaffe K, Luik AI, Liu Y, Ding J, Lichtenstein P, Landén M, Widen E, Weir DR, Llewellyn DJ, Murray A, Kardia SLR, Eriksson JG, Koenen K, Magnusson PKE, Ferrucci L, Mosley TH, Cucca F, Oostra BA, Bennett DA, Paunio T, Berger K, Harris TB, Pedersen NL, Murabito JM, Tiemeier H, van Duijn CM, Räikkönen K. Somatic, positive and negative domains of the Center for Epidemiological Studies Depression (CES-D) scale: a meta-analysis of genome-wide association studies. Psychol Med 2016; 46:1613-1623. [PMID: 26997408 PMCID: PMC5812462 DOI: 10.1017/s0033291715002081] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND Major depressive disorder (MDD) is moderately heritable, however genome-wide association studies (GWAS) for MDD, as well as for related continuous outcomes, have not shown consistent results. Attempts to elucidate the genetic basis of MDD may be hindered by heterogeneity in diagnosis. The Center for Epidemiological Studies Depression (CES-D) scale provides a widely used tool for measuring depressive symptoms clustered in four different domains which can be combined together into a total score but also can be analysed as separate symptom domains. METHOD We performed a meta-analysis of GWAS of the CES-D symptom clusters. We recruited 12 cohorts with the 20- or 10-item CES-D scale (32 528 persons). RESULTS One single nucleotide polymorphism (SNP), rs713224, located near the brain-expressed melatonin receptor (MTNR1A) gene, was associated with the somatic complaints domain of depression symptoms, with borderline genome-wide significance (p discovery = 3.82 × 10-8). The SNP was analysed in an additional five cohorts comprising the replication sample (6813 persons). However, the association was not consistent among the replication sample (p discovery+replication = 1.10 × 10-6) with evidence of heterogeneity. CONCLUSIONS Despite the effort to harmonize the phenotypes across cohorts and participants, our study is still underpowered to detect consistent association for depression, even by means of symptom classification. On the contrary, the SNP-based heritability and co-heritability estimation results suggest that a very minor part of the variation could be captured by GWAS, explaining the reason of sparse findings.
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Affiliation(s)
- A. Demirkan
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
| | - J. Lahti
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
| | - N. Direk
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - A. Viktorin
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - A. Terracciano
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
- College of Medicine, Florida State University, Tallahassee, FL, USA
| | - M. A. Nalls
- Laboratory of Neurogenetics, National Institute on Aging, National Institutes of Health, Bethesda, MD, USA
| | - T. Tanaka
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - K. Hek
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Psychiatry, Epidemiological and Social Psychiatric Research Institute, Erasmus MC, Rotterdam, The Netherlands
| | - M. Fornage
- Houston Institute of Molecular Medicine, University of Texas, Houston, TX, USA
| | - J. Wellmann
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - M. C. Cornelis
- Channing Division of Network Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA, USA
| | - H. M. Ollila
- Public Health Genomics Unit and Institute for Molecular Medicine Finland (FIMM), National Institute for Health and Welfare, Helsinki, Finland
| | - L. Yu
- Department of Neurological Sciences, Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - J. A. Smith
- Department of Epidemiology, University of Michigan, Ann Arbor, MI, USA
| | | | - A. Isaacs
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
| | - A. Palotie
- Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Cambridge, UK
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - W. V. Zhuang
- Department of Preventive Medicine and Public Health, School of Medicine, Creighton University, Omaha, NE, USA
| | - A. Zonderman
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - J. D. Faul
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - A. Sutin
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - O. Meirelles
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - A. Mulas
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
| | - A. Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - A. Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Member of Netherlands Consortium for Healthy Aging sponsored by Netherlands Genomics Initiative, Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - F. Rivadeneira
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Member of Netherlands Consortium for Healthy Aging sponsored by Netherlands Genomics Initiative, Leiden, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
| | - M. Perola
- Public Health Genomics Unit and Institute for Molecular Medicine Finland (FIMM), National Institute for Health and Welfare, Helsinki, Finland
| | - W. Zhao
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - V. Salomaa
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - K. Yaffe
- Departments of Psychiatry, University of California, San Francisco, CA, USA
| | - A. I. Luik
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - NABEC
- North American Brain Expression Consortium, USA
| | - UKBEC
- UK Brain Expression Consortium, UK
| | - Y. Liu
- Center for Human Genomics, Department of Epidemiology and Prevention, Division of Public Health Sciences, Wake Forest School of Medicine, Medical Center Boulevard, Winston-Salem, NC, USA
| | - J. Ding
- Geriatrics & Gerontology, Sticht Center on Aging, Wake Forest University, Primate Center, Epidemiology & Prevention, Winston-Salem, NC, USA
| | - P. Lichtenstein
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - M. Landén
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - E. Widen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
| | - D. R. Weir
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | | | - A. Murray
- University of Exeter Medical School, Exeter, UK
| | - S. L. R. Kardia
- Survey Research Center, Institute for Social Research, University of Michigan, Ann Arbor, MI, USA
| | - J. G. Eriksson
- National Institute for Health and Welfare, Helsinki, Finland
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
| | - K. Koenen
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, NY, USA
| | - P. K. E. Magnusson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - L. Ferrucci
- National Institute on Aging, National Institutes of Health, Baltimore, MD, USA
| | - T. H. Mosley
- Department of Medicine, University of Mississippi Medical Center, Jackson, MS, USA
| | - F. Cucca
- Istituto di Ricerca Genetica e Biomedica, CNR, Monserrato, Cagliari, Italy
| | - B. A. Oostra
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Department of Clinical Genetics, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - D. A. Bennett
- Department of Neurological Sciences, Rush Alzheimer’s Disease Center, Rush University Medical Center, Chicago, IL, USA
| | - T. Paunio
- Public Health Genomics Unit and Institute for Molecular Medicine Finland (FIMM), National Institute for Health and Welfare, Helsinki, Finland
| | - K. Berger
- Institute of Epidemiology and Social Medicine, University of Münster, Münster, Germany
| | - T. B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Ageing, National Institutes of Health, Bethesda, MD, USA
| | - N. L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - J. M. Murabito
- Department of Medicine, Section of General Internal Medicine, Boston University School of Medicine, Boston, MA, USA
| | - H. Tiemeier
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
| | - C. M. van Duijn
- Genetic Epidemiology Unit, Departments of Epidemiology and Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
- Member of Netherlands Consortium for Healthy Aging sponsored by Netherlands Genomics Initiative, Leiden, The Netherlands
| | - K. Räikkönen
- Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland
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5
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Travison TG, Zhuang WV, Lunetta KL, Karasik D, Bhasin S, Kiel DP, Coviello AD, Murabito JM. The heritability of circulating testosterone, oestradiol, oestrone and sex hormone binding globulin concentrations in men: the Framingham Heart Study. Clin Endocrinol (Oxf) 2014; 80:277-82. [PMID: 23746309 PMCID: PMC3825765 DOI: 10.1111/cen.12260] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/04/2013] [Revised: 01/29/2013] [Accepted: 06/02/2013] [Indexed: 11/29/2022]
Abstract
OBJECTIVE Circulating testosterone, oestradiol and oestrone concentrations vary considerably between men. Although a substantial proportion of this variation may be attributed to morbidity and behavioural factors, these cannot account for its entirety, suggesting genetic inheritance as a potential additional determinant. The analysis described here was intended to estimate the heritability of male circulating total testosterone (TT), calculated free testosterone (cFT), oestrone (E1), oestradiol (E2) and sex hormone binding globulin (SHBG), along with the genetic correlation between these factors. DESIGN Cross-sectional, observational analysis of data from male members of the Offspring and Generation 3 cohorts of the Framingham Heart Study. Data were collected in the years 1998-2005. PARTICIPANTS A total of 3367 community-dwelling men contributed to the analysis, including 1066 father/son and 1284 brother pairs among other family relationships. MEASUREMENTS Levels of serum sex steroids (TT, E1 and E2) were measured by liquid chromatography-tandem mass spectrometry, SHBG by immunofluorometric assay and cFT by mass action equation. Heritability was obtained using variance components analysis with adjustment for covariates including age, diabetes mellitus, body mass index and smoking status. RESULTS Age-adjusted heritability estimates were 0·19, 0·40, 0·40, 0·30 and 0·41 for cFT, TT, E1, E2 and SHBG, respectively. Adjustment for covariates did not substantially attenuate these estimates; SHBG-adjusted TT results were similar to those obtained for cFT. Genetic correlation coefficients (ρG ) indicated substantial genetic association between TT and cFT (ρG = 0·68), between TT and SHBG (pG = 0·87), between E1 and E2 (ρG = 0·46) and between TT and E2 (ρG = 0·48). CONCLUSION Circulating testosterone, oestradiol and oestrone concentrations exhibit substantial heritability in adult men. Significant genetic association between testosterone and oestrogen levels suggests shared genetic pathways.
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Affiliation(s)
- T G Travison
- Research Program on Men's Health, Aging and Metabolism, Brigham and Women's Hospital, Boston, MA, USA
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6
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Lambert JC, Ibrahim-Verbaas CA, Harold D, Naj AC, Sims R, Bellenguez C, DeStafano AL, Bis JC, Beecham GW, Grenier-Boley B, Russo G, Thorton-Wells TA, Jones N, Smith AV, Chouraki V, Thomas C, Ikram MA, Zelenika D, Vardarajan BN, Kamatani Y, Lin CF, Gerrish A, Schmidt H, Kunkle B, Dunstan ML, Ruiz A, Bihoreau MT, Choi SH, Reitz C, Pasquier F, Cruchaga C, Craig D, Amin N, Berr C, Lopez OL, De Jager PL, Deramecourt V, Johnston JA, Evans D, Lovestone S, Letenneur L, Morón FJ, Rubinsztein DC, Eiriksdottir G, Sleegers K, Goate AM, Fiévet N, Huentelman MW, Gill M, Brown K, Kamboh MI, Keller L, Barberger-Gateau P, McGuiness B, Larson EB, Green R, Myers AJ, Dufouil C, Todd S, Wallon D, Love S, Rogaeva E, Gallacher J, St George-Hyslop P, Clarimon J, Lleo A, Bayer A, Tsuang DW, Yu L, Tsolaki M, Bossù P, Spalletta G, Proitsi P, Collinge J, Sorbi S, Sanchez-Garcia F, Fox NC, Hardy J, Deniz Naranjo MC, Bosco P, Clarke R, Brayne C, Galimberti D, Mancuso M, Matthews F, Moebus S, Mecocci P, Del Zompo M, Maier W, Hampel H, Pilotto A, Bullido M, Panza F, Caffarra P, Nacmias B, Gilbert JR, Mayhaus M, Lannefelt L, Hakonarson H, Pichler S, Carrasquillo MM, Ingelsson M, Beekly D, Alvarez V, Zou F, Valladares O, Younkin SG, Coto E, Hamilton-Nelson KL, Gu W, Razquin C, Pastor P, Mateo I, Owen MJ, Faber KM, Jonsson PV, Combarros O, O'Donovan MC, Cantwell LB, Soininen H, Blacker D, Mead S, Mosley TH, Bennett DA, Harris TB, Fratiglioni L, Holmes C, de Bruijn RF, Passmore P, Montine TJ, Bettens K, Rotter JI, Brice A, Morgan K, Foroud TM, Kukull WA, Hannequin D, Powell JF, Nalls MA, Ritchie K, Lunetta KL, Kauwe JS, Boerwinkle E, Riemenschneider M, Boada M, Hiltuenen M, Martin ER, Schmidt R, Rujescu D, Wang LS, Dartigues JF, Mayeux R, Tzourio C, Hofman A, Nöthen MM, Graff C, Psaty BM, Jones L, Haines JL, Holmans PA, Lathrop M, Pericak-Vance MA, Launer LJ, Farrer LA, van Duijn CM, Van Broeckhoven C, Moskvina V, Seshadri S, Williams J, Schellenberg GD, Amouyel P. Meta-analysis of 74,046 individuals identifies 11 new susceptibility loci for Alzheimer's disease. Nat Genet 2013; 45:1452-8. [PMID: 24162737 PMCID: PMC3896259 DOI: 10.1038/ng.2802] [Citation(s) in RCA: 2947] [Impact Index Per Article: 267.9] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2013] [Accepted: 09/27/2013] [Indexed: 12/12/2022]
Abstract
Eleven susceptibility loci for late-onset Alzheimer's disease (LOAD) were identified by previous studies; however, a large portion of the genetic risk for this disease remains unexplained. We conducted a large, two-stage meta-analysis of genome-wide association studies (GWAS) in individuals of European ancestry. In stage 1, we used genotyped and imputed data (7,055,881 SNPs) to perform meta-analysis on 4 previously published GWAS data sets consisting of 17,008 Alzheimer's disease cases and 37,154 controls. In stage 2, 11,632 SNPs were genotyped and tested for association in an independent set of 8,572 Alzheimer's disease cases and 11,312 controls. In addition to the APOE locus (encoding apolipoprotein E), 19 loci reached genome-wide significance (P < 5 × 10(-8)) in the combined stage 1 and stage 2 analysis, of which 11 are newly associated with Alzheimer's disease.
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7
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Broer L, Demerath EW, Garcia ME, Homuth G, Kaplan RC, Lunetta KL, Tanaka T, Tranah GJ, Walter S, Arnold AM, Atzmon G, Harris TB, Hoffmann W, Karasik D, Kiel DP, Kocher T, Launer LJ, Lohman KK, Rotter JI, Tiemeier H, Uitterlinden AG, Wallaschofski H, Bandinelli S, Dörr M, Ferrucci L, Franceschini N, Gudnason V, Hofman A, Liu Y, Murabito JM, Newman AB, Oostra BA, Psaty BM, Smith AV, van Duijn CM. Association of heat shock proteins with all-cause mortality. Age (Dordr) 2013; 35:1367-1376. [PMID: 22555621 PMCID: PMC3705092 DOI: 10.1007/s11357-012-9417-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/16/2012] [Accepted: 04/17/2012] [Indexed: 05/31/2023]
Abstract
Experimental mild heat shock is widely known as an intervention that results in extended longevity in various models along the evolutionary lineage. Heat shock proteins (HSPs) are highly upregulated immediately after a heat shock. The elevation in HSP levels was shown to inhibit stress-mediated cell death, and recent experiments indicate a highly versatile role for these proteins as inhibitors of programmed cell death. In this study, we examined common genetic variations in 31 genes encoding all members of the HSP70, small HSP, and heat shock factor (HSF) families for their association with all-cause mortality. Our discovery cohort was the Rotterdam study (RS1) containing 5,974 participants aged 55 years and older (3,174 deaths). We assessed 4,430 single nucleotide polymorphisms (SNPs) using the HumanHap550K Genotyping BeadChip from Illumina. After adjusting for multiple testing by permutation analysis, three SNPs showed evidence for association with all-cause mortality in RS1. These findings were followed in eight independent population-based cohorts, leading to a total of 25,007 participants (8,444 deaths). In the replication phase, only HSF2 (rs1416733) remained significantly associated with all-cause mortality. Rs1416733 is a known cis-eQTL for HSF2. Our findings suggest a role of HSF2 in all-cause mortality.
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Affiliation(s)
- L. Broer
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
| | - E. W. Demerath
- Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN USA
| | - M. E. Garcia
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - G. Homuth
- Interfaculty Institute for Genetics and Functional Genomics, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - R. C. Kaplan
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY USA
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public Health, 715 Albany Street, Talbot Building, Boston, MA 02118 USA
- NHLBI’s Framingham Heart Study, Framingham, USA
| | - T. Tanaka
- Clinical Research Branch, National Institute on Aging, Baltimore, MD USA
| | - G. J. Tranah
- California Pacific Medical Center, San Francisco, CA USA
| | - S. Walter
- Department of Society, Human Development, and Health, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115 USA
| | - A. M. Arnold
- Department of Biostatistics, University of Washington, Seattle, WA USA
| | - G. Atzmon
- Institute for Aging Research and the Diabetes Research Center, Albert Einstein College of Medicine, Bronx, NY USA
- Department of Medicine, Albert Einstein College of Medicine, Bronx, NY USA
- Department of Genetics, Albert Einstein College of Medicine, Bronx, NY USA
| | - T. B. Harris
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - W. Hoffmann
- Institute of Community Medicine, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - D. Karasik
- NHLBI’s Framingham Heart Study, Framingham, USA
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA USA
| | - D. P. Kiel
- NHLBI’s Framingham Heart Study, Framingham, USA
- Hebrew Senior Life Institute for Aging Research and Harvard Medical School, Boston, MA USA
| | - T. Kocher
- Dental School, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - L. J. Launer
- Laboratory of Epidemiology, Demography, and Biometry, National Institute on Aging, National Institutes of Health, Bethesda, MD USA
| | - K. K. Lohman
- Sticht Center on Aging, Wake Forest University School of Medicine, Winston-Salem, NC USA
| | - J. I. Rotter
- Medical Genetics Institute, Cedars-Sinai Medical Center, Los Angeles, CA USA
| | - H. Tiemeier
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
- Department of Psychiatry, Erasmus Medical Center, Rotterdam, The Netherlands
| | - A. G. Uitterlinden
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus Medical Center, Rotterdam, The Netherlands
| | - H. Wallaschofski
- Institute of Clinical Chemistry and Laboratory Medicine, University Medicine Greifswald, Ernst-Moritz-Arndt-University Greifswald, Greifswald, Germany
| | - S. Bandinelli
- Geriatric Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy
| | - M. Dörr
- Department of Internal Medicine B, University Medicine Greifswald, Greifswald, Germany
| | - L. Ferrucci
- Clinical Research Branch, National Institute on Aging, Baltimore, MD USA
| | - N. Franceschini
- Department of Epidemiology, University of North Carolina, Chapel Hill, NC USA
| | - V. Gudnason
- Icelandic Heart Association, Kópavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - A. Hofman
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
| | - Y. Liu
- Department of Biostatistical Sciences, Wake Forest University School of Medicine, Winston-Salem, NC USA
| | - J. M. Murabito
- NHLBI’s Framingham Heart Study, Framingham, USA
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, 72 E. Concord Street, Boston, MA 02118 USA
| | - A. B. Newman
- Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA USA
| | - B. A. Oostra
- Department of Clinical Genetics, Erasmus Medical Center, Rotterdam, The Netherlands
| | - B. M. Psaty
- Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology, and Health Services, University of Washington, Seattle, WA USA
- Group Health Research Unit, Group Health Cooperative, Seattle, WA USA
| | - A. V. Smith
- Icelandic Heart Association, Kópavogur, Iceland
- University of Iceland, Reykjavik, Iceland
| | - C. M. van Duijn
- Department of Epidemiology, Erasmus Medical Center, Dr. Molewaterplein 50, PO-Box 2040, 3000 CA Rotterdam, The Netherlands
- Netherlands Consortium of Healthy Aging, Rotterdam, The Netherlands
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8
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Liu CT, Ng MCY, Rybin D, Adeyemo A, Bielinski SJ, Boerwinkle E, Borecki I, Cade B, Chen YDI, Djousse L, Fornage M, Goodarzi MO, Grant SFA, Guo X, Harris T, Kabagambe E, Kizer JR, Liu Y, Lunetta KL, Mukamal K, Nettleton JA, Pankow JS, Patel SR, Ramos E, Rasmussen-Torvik L, Rich SS, Rotimi CN, Sarpong D, Shriner D, Sims M, Zmuda JM, Redline S, Kao WH, Siscovick D, Florez JC, Rotter JI, Dupuis J, Wilson JG, Bowden DW, Meigs JB. Transferability and fine-mapping of glucose and insulin quantitative trait loci across populations: CARe, the Candidate Gene Association Resource. Diabetologia 2012; 55:2970-84. [PMID: 22893027 PMCID: PMC3804308 DOI: 10.1007/s00125-012-2656-4] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/20/2012] [Accepted: 06/14/2012] [Indexed: 01/22/2023]
Abstract
AIMS/HYPOTHESIS Hyperglycaemia disproportionately affects African-Americans (AfAs). We tested the transferability of 18 single-nucleotide polymorphisms (SNPs) associated with glycaemic traits identified in European ancestry (EuA) populations in 5,984 non-diabetic AfAs. METHODS We meta-analysed SNP associations with fasting glucose (FG) or insulin (FI) in AfAs from five cohorts in the Candidate Gene Association Resource. We: (1) calculated allele frequency differences, variations in linkage disequilibrium (LD), fixation indices (F(st)s) and integrated haplotype scores (iHSs); (2) tested EuA SNPs in AfAs; and (3) interrogated within ± 250 kb around each EuA SNP in AfAs. RESULTS Allele frequency differences ranged from 0.6% to 54%. F(st) exceeded 0.15 at 6/16 loci, indicating modest population differentiation. All iHSs were <2, suggesting no recent positive selection. For 18 SNPs, all directions of effect were the same and 95% CIs of association overlapped when comparing EuA with AfA. For 17 of 18 loci, at least one SNP was nominally associated with FG in AfAs. Four loci were significantly associated with FG (GCK, p = 5.8 × 10(-8); MTNR1B, p = 8.5 × 10(-9); and FADS1, p = 2.2 × 10(-4)) or FI (GCKR, p = 5.9 × 10(-4)). At GCK and MTNR1B the EuA and AfA SNPs represented the same signal, while at FADS1, and GCKR, the EuA and best AfA SNPs were weakly correlated (r(2) <0.2), suggesting allelic heterogeneity for association with FG at these loci. CONCLUSIONS/INTERPRETATION Few glycaemic SNPs showed strict evidence of transferability from EuA to AfAs. Four loci were significantly associated in both AfAs and those with EuA after accounting for varying LD across ancestral groups, with new signals emerging to aid fine-mapping.
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Affiliation(s)
- C.-T. Liu
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA
| | - M. C. Y. Ng
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA
| | - D. Rybin
- Boston University Data Coordinating Center, Boston, MA, USA
| | - A. Adeyemo
- National Human Genome Research Institute, Bethesda, MD, USA
| | | | - E. Boerwinkle
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | - I. Borecki
- Washington University, St Louis, MO, USA
| | - B. Cade
- Brigham and Women's Hospital, Boston, MA, USA
| | | | - L. Djousse
- Brigham and Women's Hospital, Boston, MA, USA; Department
of Medicine, Harvard Medical School, Boston, MA, USA; Boston VA Healthcare
System, Boston, MA, USA
| | - M. Fornage
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | | | - S. F. A. Grant
- Children's Hospital of Philadelphia, Philadelphia, PA,
USA
| | - X. Guo
- Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - T. Harris
- National Institute on Aging, Bethesda, MD, USA
| | | | | | - Y. Liu
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA; Department of Epidemiology and Prevention, Wake Forest University,
Winston-Salem, North Carolina, USA
| | - K. L. Lunetta
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA; National Heart, Lung, and Blood Institute'
Framingham Heart Study, Framingham, MA, USA
| | - K. Mukamal
- Department of Medicine, Harvard Medical School, Boston, MA,
USA
| | - J. A. Nettleton
- University of Texas Health Science Center at Houston, Houston, TX,
USA
| | | | - S. R. Patel
- Brigham and Women's Hospital, Boston, MA, USA
| | - E. Ramos
- National Human Genome Research Institute, Bethesda, MD, USA
| | | | - S. S. Rich
- University of Virginia, Charlottesville, VA, USA
| | - C. N. Rotimi
- National Human Genome Research Institute, Bethesda, MD, USA
| | - D. Sarpong
- Jackson State University, Jackson, MS, USA
| | - D. Shriner
- National Human Genome Research Institute, Bethesda, MD, USA
| | - M. Sims
- University of Mississippi Medical Center, Jackson, MS, USA
| | - J. M. Zmuda
- University of Pittsburgh, Graduate School of Public Health,
Pittsburgh, PA, USA
| | - S. Redline
- Brigham and Women's Hospital, Boston, MA, USA
| | - W. H. Kao
- Johns Hopkins University, Baltimore, MD, USA
| | | | - J. C. Florez
- Department of Medicine, Harvard Medical School, Boston, MA, USA;
Diabetes Unit and Center for Human Genetic Research, Massachusetts General
Hospital, Boston, MA, USA; Program in Medical and Population Genetics, Broad
Institute, Cambridge, MA, USA
| | - J. I. Rotter
- Cedars Sinai Medical Center, Los Angeles, CA, USA
| | - J. Dupuis
- Department of Biostatistics, Boston University School of Public
Health, Boston, MA, USA; National Heart, Lung, and Blood Institute's
Framingham Heart Study, Framingham, MA, USA
| | - J. G. Wilson
- University of Mississippi Medical Center, Jackson, MS, USA
| | - D. W. Bowden
- Center for Genomics and Personalized Medicine Research, Center for
Diabetes Research, Wake Forest University School of Medicine, Winston-Salem,
NC, USA; Departments of Biochemistry and Internal Medicine, Wake Forest
University School of Medicine, Winston-Salem, NC, USA
| | - J. B. Meigs
- Department of Medicine, Harvard Medical School, Boston, MA, USA;
General Medicine Division, Massachusetts General Hospital, 50 Staniford
Street, 9th Flr, Boston, MA, USA
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9
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Coviello AD, Zhuang WV, Lunetta KL, Bhasin S, Ulloor J, Zhang A, Karasik D, Kiel DP, Vasan RS, Murabito JM. Circulating testosterone and SHBG concentrations are heritable in women: the Framingham Heart Study. J Clin Endocrinol Metab 2011; 96:E1491-5. [PMID: 21752884 PMCID: PMC3167671 DOI: 10.1210/jc.2011-0050] [Citation(s) in RCA: 18] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
CONTEXT Many factors influence the concentration of circulating testosterone and its primary binding protein, SHBG. However, little is known about the genetic contribution to their circulating concentrations in women, and their heritability in women is not well established. OBJECTIVE Our objective was to estimate the heritability of circulating total testosterone (TT), free testosterone (FT), and SHBG in women in families from the Framingham Heart Study. METHODS Women in the Framingham Heart Study who were not pregnant, had not undergone bilateral oophorectomy, and were not using exogenous hormones were eligible for this investigation. TT was measured using liquid chromatography tandem mass spectrometry and SHBG using an immunofluorometric assay (Delfia-Wallac), and FT was calculated. Heritability estimates were calculated using variance-components methods in Sequential Oligogenic Linkage Analysis Routines (SOLAR) and were adjusted for age, age(2), body mass index (BMI), BMI(2), diabetes, smoking, and menopausal status. Bivariate analyses were done to assess genetic correlation between TT, FT, and SHBG. RESULTS A total of 2685 women were studied including 868 sister pairs and 688 mother-daughter pairs. Multivariable adjusted heritability estimates were 0.26 ± 0.05 for FT, 0.26 ± 0.05 for TT, and 0.56 ± 0.05 for SHBG (P < 1.0 × 10(-7) for all). TT was genetically correlated with SHBG [genetic correlation coefficient (ρG) = 0.31 ± 0.10] and FT (ρG = 0.54 ± 0.09), whereas SHBG was inversely correlated with FT (ρG = -0.60 ± 0.08). CONCLUSION Circulating TT, FT, and SHBG concentrations in women are significantly heritable, underscoring the importance of further work to identify the specific genes that contribute significantly to variation in sex steroid concentrations in women. The strong shared genetic component among pairs of TT, FT, and SHBG concentrations suggests potential pleiotropic effects for some of the underlying genes.
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Affiliation(s)
- A D Coviello
- Sections of Preventive Medicine and Epidemiology, Department of Medicine, Boston University School of Medicine, Boston University School of Public Health, Boston, Massachusetts 02118, USA.
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10
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Perneczky R, Wagenpfeil S, Lunetta KL, Cupples LA, Green RC, Decarli C, Farrer LA, Kurz A. Head circumference, atrophy, and cognition: implications for brain reserve in Alzheimer disease. Neurology 2010; 75:137-42. [PMID: 20625166 DOI: 10.1212/wnl.0b013e3181e7ca97] [Citation(s) in RCA: 65] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND Clinical and epidemiologic studies suggest that patients with Alzheimer disease (AD) with larger head circumference have better cognitive performance at the same level of brain pathology than subjects with smaller head circumference. METHODS A total of 270 patients with AD participating in the Multi-Institutional Research in Alzheimer's Genetic Epidemiology (MIRAGE) study underwent cognitive testing, APOE genotyping, and MRI of the brain in a cross-sectional study. Linear regression analysis was used to examine the association between cerebral atrophy, as a proxy for AD pathology, and level of cognitive function, adjusting for age, duration of AD symptoms, gender, head circumference, APOE genotype, diabetes mellitus, hypertension, major depression, and ethnicity. An interaction term between atrophy and head circumference was introduced to explore if head circumference modified the association between cerebral atrophy and cognition. RESULTS There was a significant inverse association between atrophy and cognitive function, and a significant interaction between atrophy and head circumference. With greater levels of atrophy, cognition was higher for individuals with greater head circumference. CONCLUSION This study suggests that larger head circumference is associated with less cognitive impairment in the face of cerebral atrophy. This finding supports the notion that head circumference (and presumably brain size) offers protection against AD symptoms through enhanced brain reserve.
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Affiliation(s)
- R Perneczky
- Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany.
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11
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Lee DS, Larson MG, Lunetta KL, Dupuis J, Rong J, Keaney JF, Lipinska I, Baldwin CT, Vasan RS, Benjamin EJ. Clinical and genetic correlates of soluble P-selectin in the community. J Thromb Haemost 2008; 6:20-31. [PMID: 17944986 DOI: 10.1111/j.1538-7836.2007.02805.x] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
BACKGROUND P-selectin is a cell adhesion molecule that is involved in atherogenesis, and soluble concentrations of this biomarker reflect cardiovascular risk. However, the clinical correlates and genetic characterization of soluble P-selectin have not been clearly elucidated. OBJECTIVE To describe clinical and genetic correlates of circulating P-selectin in the community. METHODS In Framingham Heart Study Offspring (European descent) and Omni (ethnic/racial minority) participants, we examined the association of cardiovascular risk factors with soluble P-selectin concentrations. In Offspring participants, we evaluated heritability, linkage and association of 29 SELP single-nucleotide polymorphisms (SNPs) with adjusted P-selectin concentrations. RESULTS In multivariable analysis of 3,690 participants (54% women, mean age 60 +/- 10 years), higher log-transformed P-selectin concentrations were inversely associated with female sex and hormone replacement therapy, and positively associated with age, ethnic/racial minority status, cigarette smoking, waist circumference, systolic blood pressure, fasting glucose, and total/high-density lipoprotein cholesterol and triglyceride concentrations. Clinical factors explained 10.4% of the interindividual variability in P-selectin concentrations. In 571 extended pedigrees (n = 1,841) with >or= 2 phenotyped members per family, multivariable-adjusted heritability was 45.4 +/- 5.8%. Among the SELP SNPs examined, a non-synonymous SNP (rs6136) encoding a threonine-to-proline substitution at position 715 was highly significantly associated with decreased P-selectin concentrations (P = 5.2 x 10(-39)), explaining 9.7% of variation after adjustment for clinical factors. CONCLUSIONS Multiple clinical factors and an SNP in the SELP gene were significantly associated with circulating P-selectin concentrations. One SNP in SELP explained significant variation in circulating P-selectin concentrations, even after accounting for known clinical correlates.
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Affiliation(s)
- D S Lee
- Institute for Clinical Evaluative Sciences and University Health Network, University of Toronto, Toronto, ON, Canada
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12
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Akomolafe A, Lunetta KL, Erlich PM, Cupples LA, Baldwin CT, Huyck M, Green RC, Farrer LA. Genetic association between endothelial nitric oxide synthase and Alzheimer disease. Clin Genet 2006; 70:49-56. [PMID: 16813604 DOI: 10.1111/j.1399-0004.2006.00638.x] [Citation(s) in RCA: 24] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Evidence suggests that vascular and inflammatory factors may be important in the etiology of Alzheimer disease (AD). The Glu/Glu genotype at the Glu298Asp variant of the endothelial nitric oxide synthase (NOS3) gene has been tested for association with AD in several Caucasian and Asian populations, with conflicting results. We tested the Glu298Asp variant for association in African American and Caucasian AD patients, unaffected siblings, and unrelated controls from the MIRAGE Study. To explore whether the inconsistent results in previous studies might be due to linkage disequilibrium with a polymorphism or haplotype not previously tested, we genotyped 10 additional NOS3 single nucleotide polymorphisms (SNPs) spanning 25.3 kb. Finally, we compiled results of previous studies of Glu298Asp using meta-analysis, to determine whether the aggregate studies support an association between Glu298Asp and AD. We found that the Glu298 allele was associated with higher risk of AD in the MIRAGE African American (p = 0.002) but not Caucasian (p = 0.9) groups. None of the additional SNPs were associated with AD in the Caucasians, whereas two showed evidence for association in the African Americans. The meta-analysis showed a small effect of the Glu298Asp GG genotype on AD risk across all studies (summary odds ratio = 1.15, 95% confidence interval: 0.97-1.35) and significant heterogeneity of this association among studies (p = 0.02).
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Affiliation(s)
- A Akomolafe
- Department of Medicine, Morehouse School of Medicine, Atlanta, GA, USA
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13
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Abstract
Comorbidity, the association of two disorders, occurs commonly with complex diseases. In this paper, we investigate the effects of both true (within-family) comorbidity and spurious comorbidity due to ascertainment bias on the validity of both the parental and sibling control transmission/disequilibrium test. Specifically, we consider settings in which a candidate gene is unlinked to the target phenotype but is in linkage disequilibrium with a comorbid phenotype. We derive conditions under which the presence of true and/or spurious comorbidity will result in an artificial correlation between the target phenotype and the candidate gene.
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Affiliation(s)
- J M Robins
- Department of Epidemiology and Biostatistics, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
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14
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Krop IE, Sgroi D, Porter DA, Lunetta KL, LeVangie R, Seth P, Kaelin CM, Rhei E, Bosenberg M, Schnitt S, Marks JR, Pagon Z, Belina D, Razumovic J, Polyak K. HIN-1, a putative cytokine highly expressed in normal but not cancerous mammary epithelial cells. Proc Natl Acad Sci U S A 2001; 98:9796-801. [PMID: 11481438 PMCID: PMC55532 DOI: 10.1073/pnas.171138398] [Citation(s) in RCA: 106] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023] Open
Abstract
To identify molecular alterations implicated in the initiating steps of breast tumorogenesis, we compared the gene expression profiles of normal and ductal carcinoma in situ (DCIS) mammary epithelial cells by using serial analysis of gene expression (SAGE). Through the pair-wise comparison of normal and DCIS SAGE libraries, we identified several differentially expressed genes. Here, we report the characterization of one of these genes, HIN-1 (high in normal-1). HIN-1 expression is significantly down regulated in 94% of human breast carcinomas and in 95% of preinvasive lesions, such as ductal and lobular carcinoma in situ. This decrease in HIN-1 expression is accompanied by hypermethylation of its promoter in the majority of breast cancer cell lines (>90%) and primary tumors (74%). HIN-1 is a putative cytokine with no significant homology to known proteins. Reintroduction of HIN-1 into breast cancer cells inhibits cell growth. These results indicate that HIN-1 is a candidate tumor suppressor gene that is inactivated at high frequency in the earliest stages of breast tumorogenesis.
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MESH Headings
- Amino Acid Sequence
- Animals
- Blotting, Northern
- Blotting, Western
- Breast/cytology
- Breast/metabolism
- Breast Neoplasms/genetics
- Breast Neoplasms/metabolism
- Breast Neoplasms/pathology
- CHO Cells
- COS Cells
- Carcinoma, Ductal, Breast/genetics
- Carcinoma, Ductal, Breast/metabolism
- Carcinoma, Ductal, Breast/pathology
- Carcinoma, Intraductal, Noninfiltrating/genetics
- Carcinoma, Intraductal, Noninfiltrating/metabolism
- Carcinoma, Intraductal, Noninfiltrating/pathology
- Carcinoma, Lobular/genetics
- Carcinoma, Lobular/metabolism
- Carcinoma, Lobular/pathology
- Cell Division
- Cells, Cultured/metabolism
- Chlorocebus aethiops
- Cricetinae
- Cricetulus
- Cytokines/biosynthesis
- Cytokines/genetics
- Cytokines/isolation & purification
- Cytokines/physiology
- DNA Methylation
- Epithelial Cells/metabolism
- Female
- Gene Expression Profiling
- Gene Expression Regulation, Neoplastic
- Gene Library
- Gene Silencing
- Genes, Tumor Suppressor
- Growth Inhibitors/genetics
- Growth Inhibitors/physiology
- Humans
- Molecular Sequence Data
- Neoplasm Proteins/biosynthesis
- Neoplasm Proteins/genetics
- Neoplasm Proteins/isolation & purification
- Promoter Regions, Genetic
- RNA, Messenger/biosynthesis
- RNA, Neoplasm/biosynthesis
- Recombinant Fusion Proteins/physiology
- Sequence Alignment
- Sequence Homology, Amino Acid
- Transfection
- Tumor Cells, Cultured/metabolism
- Tumor Suppressor Proteins
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Affiliation(s)
- I E Krop
- Department of Adult Oncology, Dana-Farber Cancer Institute, Boston, MA 02115, USA
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15
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Abstract
BACKGROUND The importance of the bone marrow microenvironment in multiple myeloma is receiving increasing attention. Recent studies have suggested the importance of cytokine production and cell-cell contact by bone marrow stromal cells in the survival of myeloma cells. METHODS In the current study, the authors examined bone marrow mesenchymal progenitor cell (MPC) cultures derived from eight multiple myeloma patients (mean age, 58 years) and nine normal donors (mean age, 61 years), with emphasis on cell surface antigens, cytokine, and growth factor expression. RESULTS The authors have found, based on analysis of cellular receptors, growth factors, and cytokine expression, that myeloma MPCs are phenotypically and functionally distinguishable from normal donor MPCs. Immunofluorescence analysis of MPC monolayers shows that myeloma MPC cultures expressed reduced cell surface vascular cell adhesion molecule-1 and fibronectin, in contrast with the strong expression found on normal donor MPCs. Furthermore, a subset of myeloma MPCs strongly express intracellular receptor for hyaluronan-mediated motility, whereas normal MPCs do not. Cytokine expression in bone marrow MPC cultures was examined by reverse transcription-polymerase chain reaction and enzyme linked immunosorbent assay. Bone marrow MPCs constitutively express interleukin (IL)-1beta, IL-6, granulocyte colony-stimulating factor (G-CSF), granulocyte macrophage (GM)-CSF, stem cell factor (SCF), and tumor necrosis factor (TNF)-alpha. In comparison to normal MPCs, multiple myeloma MPCs express increased basal levels of IL-1beta and TNF-alpha. In vitro exposure of MPC cultures to dexamethasone resulted in the down-regulation of IL-6, G-CSF, and GM-CSF in both normal and myeloma MPC cultures. However, dexamethasone treatment significantly increased expression of SCF-1 in myeloma MPCs. CONCLUSIONS In myeloma, bone marrow stromal cells provide paracrine factors, through cytokine production and cell-cell contact, which play a role in plasma cell growth and survival. The authors' data indicate differences in bone marrow MPCs, which may be biologically relevant to the growth and survival of myeloma plasma cells.
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Affiliation(s)
- S R Wallace
- Virginia Piper Cancer Institute, Abbott Northwestern Hospital, Minneapolis, Minnesota, USA
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16
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Abstract
BACKGROUND The importance of the bone marrow microenvironment in multiple myeloma is receiving increasing attention. Recent studies have suggested the importance of cytokine production and cell-cell contact by bone marrow stromal cells in the survival of myeloma cells. METHODS In the current study, the authors examined bone marrow mesenchymal progenitor cell (MPC) cultures derived from eight multiple myeloma patients (mean age, 58 years) and nine normal donors (mean age, 61 years), with emphasis on cell surface antigens, cytokine, and growth factor expression. RESULTS The authors have found, based on analysis of cellular receptors, growth factors, and cytokine expression, that myeloma MPCs are phenotypically and functionally distinguishable from normal donor MPCs. Immunofluorescence analysis of MPC monolayers shows that myeloma MPC cultures expressed reduced cell surface vascular cell adhesion molecule-1 and fibronectin, in contrast with the strong expression found on normal donor MPCs. Furthermore, a subset of myeloma MPCs strongly express intracellular receptor for hyaluronan-mediated motility, whereas normal MPCs do not. Cytokine expression in bone marrow MPC cultures was examined by reverse transcription-polymerase chain reaction and enzyme linked immunosorbent assay. Bone marrow MPCs constitutively express interleukin (IL)-1beta, IL-6, granulocyte colony-stimulating factor (G-CSF), granulocyte macrophage (GM)-CSF, stem cell factor (SCF), and tumor necrosis factor (TNF)-alpha. In comparison to normal MPCs, multiple myeloma MPCs express increased basal levels of IL-1beta and TNF-alpha. In vitro exposure of MPC cultures to dexamethasone resulted in the down-regulation of IL-6, G-CSF, and GM-CSF in both normal and myeloma MPC cultures. However, dexamethasone treatment significantly increased expression of SCF-1 in myeloma MPCs. CONCLUSIONS In myeloma, bone marrow stromal cells provide paracrine factors, through cytokine production and cell-cell contact, which play a role in plasma cell growth and survival. The authors' data indicate differences in bone marrow MPCs, which may be biologically relevant to the growth and survival of myeloma plasma cells.
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Affiliation(s)
- S R Wallace
- Virginia Piper Cancer Institute, Abbott Northwestern Hospital, Minneapolis, Minnesota, USA
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17
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Seth P, Lunetta KL, Bell DW, Gray H, Nasser SM, Rhei E, Kaelin CM, Iglehart DJ, Marks JR, Garber JE, Haber DA, Polyak K. Phenol sulfotransferases: hormonal regulation, polymorphism, and age of onset of breast cancer. Cancer Res 2000; 60:6859-63. [PMID: 11156380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
In recent years, significant effort has been made to identify genes that influence breast cancer risk. Because the high-penetrance breast cancer susceptibility genes BRCA1 and 2 play a role only in a small fraction of breast cancer cases, understanding the genetic risk of the majority of breast cancers will require the identification and analysis of several lower penetrance genes. The estrogen-signaling pathway plays a crucial role in the pathophysiology of breast cancer; therefore, polymorphism in genes involved in this pathway is likely to influence breast cancer risk. Our detailed analysis of gene expression profiles of estrogen- and 4-OH-tamoxifen-treated ZR75-1 breast cancer cells identified members of the sulfotransferase 1A (SULT1A) phenol sulfotransferase family as downstream targets of tamoxifen. On the basis of the induction of SULT1A by 4-OH-tamoxifen and the known inherited variability in SULT1A enzymatic activity, we hypothesized that polymorphism in sulfotransferase genes might influence the risk of breast cancer. Using an RFLP that distinguishes an arginine to histidine change in exon 7 of the SULT1A1 gene, we characterized SULT1A1 genotypes in relation to breast cancer risk. An analysis of 444 breast cancer patients and 227 controls revealed no effect of SULT1A1 genotype on the risk of breast cancer (P = 0.69); however, it did appear to influence the age of onset among early-onset affected patients (P = 0.04). Moreover, individuals with the higher activity SULT1A1*1 allele were more likely to have other tumors in addition to breast cancer (P = 0.004; odds ratio, 3.02; 95% confidence interval, 1.32, 8.09). The large number of environmental mutagens and carcinogens activated by sulfotransferases and the high frequency of the SULT1A1*1 allele in human populations warrants additional studies to address the role of SULT genes in human cancer.
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Affiliation(s)
- P Seth
- Departent of Adult Oncology, Dana Farher Cancer Institute, Boston, Massachasetts 02115, USA
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18
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Abstract
Comorbidity, the co-occurrence of disorders, is frequently observed to occur at higher rates in clinically ascertained samples than in population-based samples. An explanation for this finding is that subjects suffering from multiple illnesses are more likely to seek medical care and receive a diagnostic evaluation. We refer to the component of the comorbidity between illnesses due to such ascertainment bias as "spurious comorbidity." When spurious comorbidity is present, an apparent association between a candidate locus and the phenotype of interest may actually be attributable to an association between the locus and a comorbid phenotype. This phenomenon, which we call "spurious comorbidity bias," could thus produce misleading association findings. In this article, we describe this phenomenon and demonstrate that it may produce marked bias in the conclusions of family-based association studies. Because of the extremely high rates of comorbidity among psychiatric disorders in clinical samples, this problem may be particularly salient for genetic studies of neuropsychiatric disorders. We conclude that ascertainment bias may contribute to the frequent difficulty in replicating candidate gene study findings in psychiatry. Am. J. Med. Genet. (Neuropsychiatr. Genet.) 96:817-822, 2000.
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Affiliation(s)
- J W Smoller
- Harvard School of Public Health, Boston, Massachusetts, USA.
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19
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Abstract
We introduce a novel application for linkage analysis: using bone marrow donor-recipient sib pairs to search for genes influential in graft-versus-host disease (GVHD), a major cause of morbidity and mortality following allogeneic bone marrow transplantation. In particular, we show that transplant sib pairs in which the recipient developed severe GVHD can be used to map genes in the same way as traditional discordant (affected/unaffected) sib pairs (DSPs). For a plausible GVHD model, we demonstrate that the transplant/discordant sib pair analog of the "possible triangle test" [Holmans (1993) Am J Hum Genet 52:362-374] has similar power to that of the simpler "restricted test" proposed by Risch [(1990b) Am J Hum Genet 46:229-241; (1992) Am J Hum Genet 51:673-675]. Moreover, we show that the restricted test has superior power in much of the DSP possible triangle and significantly inferior power in only a small region. Thus, we conclude that the restricted test is preferable for localizing genes with transplant/discordant sib pairs. Finally, we examine the effects of heterogeneity on the power to detect GVHD loci and demonstrate the gain in efficiency by dividing the sample into genetically more homogeneous subgroups.
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Affiliation(s)
- K L Lunetta
- Department of Biostatistical Science, Dana Farber Cancer Institute, Harvard School of Public Health, Boston, Massachusetts 02115, USA.
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20
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Yeh JJ, Lunetta KL, van Orsouw NJ, Moore FD, Mutter GL, Vijg J, Dahia PL, Eng C. Somatic mitochondrial DNA (mtDNA) mutations in papillary thyroid carcinomas and differential mtDNA sequence variants in cases with thyroid tumours. Oncogene 2000; 19:2060-6. [PMID: 10803467 DOI: 10.1038/sj.onc.1203537] [Citation(s) in RCA: 136] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Somatic mutations in mtDNA have recently been identified in colorectal tumours. Studies of oncocytic tumours have led to hypotheses which propose that defects in oxidative phosphorylation may result in a compensatory increase in mitochondrial replication and/or gene expression. Mutational analysis of mtDNA in thyroid neoplasia, which is characterised by increased numbers of mitochondria and is also one of the most common sites of oncocytic tumours. has been limited to date. Using the recently developed technique of two-dimensional gene scanning, we have successfully examined 21 cases of thyroid tumours, six cases of non-neoplastic thyroid pathology, 30 population controls, nine foetal thyroid tissues and nine foetal tissues of non-thyroid origin, either kidney or liver. We have identified three different somatic mutations (23%) in papillary thyroid carcinomas. In addition, we have found significant differential distributions of mtDNA sequence variants between thyroid carcinomas and controls. Interestingly, these variants appear to be more frequent in the genes which encode complex I of the mitochondrial electron transport chain compared to normal population controls. These findings suggest first, that somatic mtDNA mutations may be involved in thyroid tumorigenesis and second, that the accumulation of certain non-somatic variants may be related to tumour progression in the thyroid.
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Affiliation(s)
- J J Yeh
- Clinical Cancer Genetics Program, Ohio State University Comprehensive Cancer Center, Columbus 43210, USA
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21
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Lunetta KL, Faraone SV, Biederman J, Laird NM. Family-based tests of association and linkage that use unaffected sibs, covariates, and interactions. Am J Hum Genet 2000; 66:605-14. [PMID: 10677320 PMCID: PMC1288113 DOI: 10.1086/302782] [Citation(s) in RCA: 131] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/24/1999] [Accepted: 11/29/1999] [Indexed: 11/04/2022] Open
Abstract
We extend the methodology for family-based tests of association and linkage to allow for both variation in the phenotypes of subjects and incorporation of covariates into general-score tests of association. We use standard association models for a phenotype and any number of predictors. We then construct a score statistic, using likelihoods for the distribution of phenotype, given genotype. The distribution of the score is computed as a function of offspring genotypes, conditional on parental genotypes and trait values for offspring and parents. This approach provides a natural extension of the transmission/disequilibrium test to any phenotype and to multiple genes or environmental factors and allows the study of gene-gene and gene-environment interaction. When the trait varies among subjects or when covariates are included in the association model, the score statistic depends on one or more nuisance parameters. We suggest two approaches for obtaining parameter estimates: (1) choosing the estimate that minimizes the variance of the test statistic and (2) maximizing the statistic over a nuisance parameter and using a corrected P value. We apply our methods to a sample of families with attention-deficit/hyperactivity disorder and provide examples of how covariates and gene-environment and gene-gene interactions can be incorporated.
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Affiliation(s)
- K L Lunetta
- Department of Biostatistical Science, Dana-Farber Cancer Institute, 44 Binney Street, Boston, MA 02115, USA.
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22
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Wilcox MA, Smoller JW, Lunetta KL, Neuberg D. Using recursive partitioning for exploration and follow-up of linkage and association analyses. Genet Epidemiol 1999; 17 Suppl 1:S391-6. [PMID: 10597468 DOI: 10.1002/gepi.1370170766] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
We first conducted a genome-wide screen for association with discordant sibships using the multi allelic and diallelic SDT. Markers at D4S1628, D8S1109, D9S66 and D7S1797 showed multi-allelic association. Deleterious diallelic association was found for markers at D1S1613, D1S534, D3S2459, D7S1817, and D9S131. Protective association was found at markers D8S1109, D8S1136, and D9S66. We then incorporated these findings with previous linkage findings in the exploration of oligogenes and epistasis using recursive partitioning. We conclude that recursive partitioning can be a useful adjunct to traditional linkage and association analyses in the exploration of these effects.
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Affiliation(s)
- M A Wilcox
- Department of Epidemiology, Harvard School of Public Health, Boston, Massachusetts, USA
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Lunetta KL, Wilcox M, Smoller J, Neuberg D. Exploring linkage for alcoholism using affection status and quantitative event related potential phenotypes. Genet Epidemiol 1999; 17 Suppl 1:S241-6. [PMID: 10597443 DOI: 10.1002/gepi.1370170741] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
Using genome-scan data from the Collaborative Study on the Genetics of Alcoholism (COGA), we compared results of linkage analyses using a qualitative alcoholism phenotype to results of linkage analyses using event related potential (ERP) quantitative phenotypes, and compared our results to the results of Reich et al. [1998] and Begleiter et al. [1998]. We describe a general and simple strategy for identifying regions of the genome which may harbor genes involved in alcohol dependence which takes into consideration the results of both the affection status and ERP linkage analyses.
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Affiliation(s)
- K L Lunetta
- Department of Biostatistics, Harvard School of Public Health, Boston, Massachusetts, USA
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24
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Larson GP, Zhang G, Ding S, Foldenauer K, Udar N, Gatti RA, Neuberg D, Lunetta KL, Ruckdeschel JC, Longmate J, Flanagan S, Krontiris TG. An allelic variant at the ATM locus is implicated in breast cancer susceptibility. Genet Test 1999; 1:165-70. [PMID: 10464642 DOI: 10.1089/gte.1997.1.165] [Citation(s) in RCA: 32] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/13/2022]
Abstract
We have tested a simple procedure, disease association by locus stratification, for identifying breast cancer patients with pathogenetic allelic variants at several candidate loci. The strategy was based on the assumption of epistatic interactions of the candidates. We analyzed 66 independent cases from sib pairs affected with breast cancer that had previously been collected during an investigation of pathogenetic-allele-sharing at the HRAS1 mini-satellite locus. An exon 24 polymorphism of ATM, substituting arginine for proline was associated with breast cancer in these cases with an overall odds ratio of 4.5 (95% confidence interval, 1.2-20.5, nominal p = 0.02, 2-tail Fisher exact test). In the presence of a rare HRAS1 allele, the odds ratio increased to 6.9 (95% CI, 1.2-38.3, p = 0.03). Thus, our procedure identified at least one allelic variant of ATM associated with breast cancer, and indicated that the ATM locus may interact with HRAS1.
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Affiliation(s)
- G P Larson
- Division of Molecular Medicine, Beckman Research Institute, City of Hope National Medical Center, Duarte, CA 91010, USA
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25
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Marsh DJ, Kum JB, Lunetta KL, Bennett MJ, Gorlin RJ, Ahmed SF, Bodurtha J, Crowe C, Curtis MA, Dasouki M, Dunn T, Feit H, Geraghty MT, Graham JM, Hodgson SV, Hunter A, Korf BR, Manchester D, Miesfeldt S, Murday VA, Nathanson KL, Parisi M, Pober B, Romano C, Eng C. PTEN mutation spectrum and genotype-phenotype correlations in Bannayan-Riley-Ruvalcaba syndrome suggest a single entity with Cowden syndrome. Hum Mol Genet 1999; 8:1461-72. [PMID: 10400993 DOI: 10.1093/hmg/8.8.1461] [Citation(s) in RCA: 358] [Impact Index Per Article: 14.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023] Open
Abstract
Germline mutations in the tumour suppressor gene PTEN have been implicated in two hamartoma syndromes that exhibit some clinical overlap, Cowden syndrome (CS) and Bannayan-Riley-Ruvalcaba syndrome (BRR). PTEN maps to 10q23 and encodes a dual specificity phosphatase, a substrate of which is phosphatidylinositol 3,4,5-triphosphate, a phospholipid in the phosphatidylinositol 3-kinase pathway. CS is characterized by multiple hamartomas and an increased risk of benign and malignant disease of the breast, thyroid and central nervous system, whilst the presence of cancer has not been formally documented in BRR. The partial clinical overlap in these two syndromes is exemplified by the hallmark features of BRR: macrocephaly and multiple lipomas, the latter of which occur in a minority of individuals with CS. Additional features observed in BRR, which may also occur in a minority of CS patients, include Hashimoto's thyroiditis, vascular malformations and mental retardation. Pigmented macules of the glans penis, delayed motor development and neonatal or infant onset are noted only in BRR. In this study, constitutive DNA samples from 43 BRR individuals comprising 16 sporadic and 27 familial cases, 11 of which were families with both CS and BRR, were screened for PTEN mutations. Mutations were identified in 26 of 43 (60%) BRR cases. Genotype-phenotype analyses within the BRR group suggested a number of correlations, including the association of PTEN mutation and cancer or breast fibroadenoma in any given CS, BRR or BRR/CS overlap family ( P = 0.014), and, in particular, truncating mutations were associated with the presence of cancer and breast fibroadenoma in a given family ( P = 0.024). Additionally, the presence of lipomas was correlated with the presence of PTEN mutation in BRR patients ( P = 0.028). In contrast to a prior report, no significant difference in mutation status was found in familial versus sporadic cases of BRR ( P = 0.113). Comparisons between BRR and a previously studied group of 37 CS families suggested an increased likelihood of identifying a germline PTEN mutation in families with either CS alone or both CS and BRR when compared with BRR alone ( P = 0.002). Among CS, BRR and BRR/CS overlap families that are PTEN mutation positive, the mutation spectra appear similar. Thus, PTEN mutation-positive CS and BRR may be different presentations of a single syndrome and, hence, both should receive equal attention with respect to cancer surveillance.
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Affiliation(s)
- D J Marsh
- Clinical Cancer Genetics and Human Cancer Genetics Programs, Ohio State University Comprehensive Cancer Center, 690C Medical Research Facility, 420 West 12th Avenue, Columbus, OH 43210, USA
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26
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Marsh DJ, Coulon V, Lunetta KL, Rocca-Serra P, Dahia PL, Zheng Z, Liaw D, Caron S, Duboué B, Lin AY, Richardson AL, Bonnetblanc JM, Bressieux JM, Cabarrot-Moreau A, Chompret A, Demange L, Eeles RA, Yahanda AM, Fearon ER, Fricker JP, Gorlin RJ, Hodgson SV, Huson S, Lacombe D, Eng C. Mutation spectrum and genotype-phenotype analyses in Cowden disease and Bannayan-Zonana syndrome, two hamartoma syndromes with germline PTEN mutation. Hum Mol Genet 1998; 7:507-15. [PMID: 9467011 DOI: 10.1093/hmg/7.3.507] [Citation(s) in RCA: 426] [Impact Index Per Article: 16.4] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
The tumour suppressor gene PTEN , which maps to 10q23.3 and encodes a 403 amino acid dual specificity phosphatase (protein tyrosine phosphatase; PTPase), was shown recently to play a broad role in human malignancy. Somatic PTEN deletions and mutations were observed in sporadic breast, brain, prostate and kidney cancer cell lines and in several primary tumours such as endometrial carcinomas, malignant melanoma and thyroid tumours. In addition, PTEN was identified as the susceptibility gene for two hamartoma syndromes: Cowden disease (CD; MIM 158350) and Bannayan-Zonana (BZS) or Ruvalcaba-Riley-Smith syndrome (MIM 153480). Constitutive DNA from 37 CD families and seven BZS families was screened for germline PTEN mutations. PTEN mutations were identified in 30 of 37 (81%) CD families, including missense and nonsense point mutations, deletions, insertions, a deletion/insertion and splice site mutations. These mutations were scattered over the entire length of PTEN , with the exception of the first, fourth and last exons. A 'hot spot' for PTEN mutation in CD was identified in exon 5 that contains the PTPase core motif, with 13 of 30 (43%) CD mutations identified in this exon. Seven of 30 (23%) were within the core motif, the majority (five of seven) of which were missense mutations, possibly pointing to the functional significance of this region. Germline PTEN mutations were identified in four of seven (57%) BZS families studied. Interestingly, none of these mutations was observed in the PTPase core motif. It is also worthy of note that a single nonsense point mutation, R233X, was observed in the germline DNA from two unrelated CD families and one BZS family. Genotype-phenotype studies were not performed on this small group of BZS families. However, genotype-phenotype analysis inthe group of CD families revealed two possible associations worthy of follow-up in independent analyses. The first was an association noted in the group of CD families with breast disease. A correlation was observed between the presence/absence of a PTEN mutation and the type of breast involvement (unaffected versus benign versus malignant). Specifically and more directly, an association was also observed between the presence of a PTEN mutation and malignant breast disease. Secondly, there appeared to be an interdependent association between mutations upstream and within the PTPase core motif, the core motif containing the majority of missense mutations, and the involvement of all major organ systems (central nervous system, thyroid, breast, skin and gastrointestinal tract). However, these observations would need to be confirmed by studying a larger number of CD families.
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Affiliation(s)
- D J Marsh
- Department of Adult Oncology and Charles A. Dana Human Cancer Genetics Unit, Dana-Farber Cancer Institute, Boston, MA 02115-6084, USA. Molecular Oncology Laboratory, Institut Bergo
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27
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Marsh DJ, Roth S, Lunetta KL, Hemminki A, Dahia PL, Sistonen P, Zheng Z, Caron S, van Orsouw NJ, Bodmer WF, Cottrell SE, Dunlop MG, Eccles D, Hodgson SV, Järvinen H, Kellokumpu I, Markie D, Neale K, Phillips R, Rozen P, Syngal S, Vijg J, Tomlinson IP, Aaltonen LA, Eng C. Exclusion of PTEN and 10q22-24 as the susceptibility locus for juvenile polyposis syndrome. Cancer Res 1997; 57:5017-21. [PMID: 9371495] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Juvenile polyposis syndrome (JPS; MIM 174900) is an autosomal dominant condition with incomplete penetrance characterized by hamartomatous polyps of the gastrointestinal tract and a risk of gastrointestinal cancer. Gastrointestinal hamartomatous polyps are also present in Cowden syndrome (CS; MIM 158350) and Bannayan-Zonana syndrome (BZS; also called Ruvalcaba-Myhre-Smith syndrome; MIM 153480). The susceptibility locus for both CS and BZS has recently been identified as the novel tumor suppressor gene PTEN, encoding a dual specificity phosphatase, located at 10q23.3. A putative JPS locus, JP1, which most likely functions as a tumor suppressor, had previously been mapped to 10q22-24 in both familial and sporadic juvenile polyps. Given the shared clinical features of gastrointestinal hamartomatous polyps among the three syndromes and the coincident mapping of JP1 to the region of PTEN, we sought to determine whether JPS was allelic to CS and BZS by mutation analysis of PTEN and linkage approaches. Microsatellite markers spanning the CS/BZS locus (D10S219, D10S551, D10S579, and D10S541) were used to compute multipoint lod scores in eight informative families with JPS. Lod scores of < -2.0 were generated for the entire region, thus excluding PTEN and any genes within the flanking 20-cM interval as candidate loci for familial JPS under our statistical models. In addition, analysis of PTEN using a combination of denaturing gradient gel electrophoresis and direct sequencing was unable to identify a germline mutation in 14 families with JPS and 11 sporadic cases. Therefore, at least a proportion of JPS cases are not caused by germline PTEN alteration or by an alternative locus at 10q22-24.
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Affiliation(s)
- D J Marsh
- Department of Adult Oncology and Human Cancer Genetics Unit, Dana-Farber Cancer Institute, Boston, Massachusetts 02115, USA
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28
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Nichols WC, Antin JH, Lunetta KL, Terry VH, Hertel CE, Wheatley MA, Arnold ND, Siemieniak DR, Boehnke M, Ginsburg D. Polymorphism of adhesion molecule CD31 is not a significant risk factor for graft-versus-host disease. Blood 1996; 88:4429-34. [PMID: 8977234] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/03/2023] Open
Abstract
Mismatch between bone marrow transplant (BMT) patient and donor for an amino acid polymorphism within the adhesion molecule CD31 has recently been reported to increase risk for the development of graft-versus-host disease (GVHD). We further examined this association in a larger series of 301 BMT patients (227 with grade III/IV GVHD and 74 with grade 0 GVHD) and their HLA-identical sibling donors. CD31 genotypes were determined by polymerase chain reaction and restriction endonuclease digestion. The role of mismatch at the CD31 locus in the development of GVHD was assessed by analyzing the extent of CD31 identity and CD31 compatibility among the grade 0 GVHD and grade III/IV GVHD sibling pairs. No significant association between CD31 mismatch and the development of severe GVHD was detected in our overall patient population. Sixty-three percent of grade III/IV GVHD sibling pairs and 69% of grade 0 GVHD sibling pairs had CD31 genotypes that were identical (P = .36, odds ratio = 1.30). In addition, neither the grade 0 GVHD group (P = .10) nor the grade III/IV GVHD group (P = .27) differed significantly from the expected probability of identity between sibling pairs. Mismatch at the CD31 polymorphism between recipients and donors showed no consistent association with the development of GVHD. Current evidence does not support the value of CD31 mismatch in the selection of BMT donors.
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Affiliation(s)
- W C Nichols
- Department of Internal Medicine, University of Michigan Medical Center, Ann Arbor 48109-0650, USA
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29
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Lunetta KL, Boehnke M, Lange K, Cox DR. Selected locus and multiple panel models for radiation hybrid mapping. Am J Hum Genet 1996; 59:717-25. [PMID: 8751873 PMCID: PMC1914929] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
We develop two new types of models for whole-genome radiation hybrid mapping using the general multipoint framework. The first, selected locus models, are appropriate for mapping markers in the region of a selectable locus that was used in creation of the hybrids. The models allow for strong retention of the selectable locus, with retention rates decreasing with increasing distance from the selectable locus in both directions. We illustrate the application of these models with 10 chromosome 17 sequence-tagged site (STS) markers and the thymidine kinase (TK) locus typed on a whole-genome hybrid panel in which TK was used in the selection process. The second set of models are appropriate when loci typed on two or more independent panels are to be used to build maps. Maps can be built assuming interlocus distances are independent or proportional between the panels, and the hypothesis of proportional distances can be tested. We illustrate the application of these models by using 27 chromosome 21 STS markers typed on two hybrid panels created with radiation doses of approximately 10,000 and approximately 50,000 Rads.
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Affiliation(s)
- K L Lunetta
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor 48109-2029, USA
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30
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Hou YC, Richards JE, Bingham EL, Pawar H, Scott K, Segal M, Lunetta KL, Boehnke M, Sieving PA. Linkage study of Best's vitelliform macular dystrophy (VMD2) in a large North American family. Hum Hered 1996; 46:211-20. [PMID: 8807324 DOI: 10.1159/000154356] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Best's vitelliform macular dystrophy (VMD2) is an autosomal dominant retinal dystrophy for which the underlying biochemical cause is unknown. We used 11 genetic markers in the vicinity of the VMD2 gene in our study of a large North American family in which macular dystrophy characteristics overlap the broad definition of Best's disease. Significant evidence for linkage was found for markers D11S956 (Z = 5.88, theta = 0.04) and FCER1B (Z = 4.31, theta = 0.00). Recombination events localized the disease gene to the 5-cM interval D11S956-UGB, a genetic inclusion interval that substantially overlaps the VMD2 inclusion interval defined by recombinants at FCER1B and UGB observed by other research groups. The resulting exclusion of ROM1 from the genetic inclusion interval eliminates ROM1 defects as a possible cause of the disease in this family. Linkage studies of many families, including those that share most but not all features with classical Best's disease, will be needed to properly evaluate genetic heterogeneity and the range of phenotypic variation that can result from VMD2 defects.
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Affiliation(s)
- Y C Hou
- Department of Ophthalmology, University of Michigan, Ann Arbor, USA
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31
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Abstract
In this paper we consider issues of experimental design and error detection and correction for polyploid radiation hybrid mapping. Using analytic methods and computer simulation, we first consider the combinations of fragment retention rate, ploidy, and marker spacing that provide the best chance to order markers. We find that in general, combinations of ploidy and chromosome-specific retention rates that lead to a per-hybrid retention rate of approximately 50% result in the greatest power to order markers. We also find that analyzing polyploid radiation hybrids as if they were haploid does not compromise the ability to order markers but does result in less accurate intermarker distance estimates. Second, we examine the effect of typing errors on two-locus information, ability to order multiple loci, and estimation of intermarker distances and total map length. Even low levels of error result in large losses of information about breakage probabilities, markedly reduce ability to order loci, and inflate estimates of intermarker distances and total map length. We compare the ordering accuracy that results from duplicate typing of hybrids to that of single typing twice as many hybrids and find that duplicate typing results in a higher probability of identifying the true order as one of the best orders, but that single typing of twice as many hybrids results in stronger support for the true order. For low error rates, framework maps constructed from the larger single-typed panels are only slightly less likely to be correct and include substantially more markers than the smaller double-typed panels. Third, we develop a method to calculate the distribution of the number of obligate chromosome breaks for a polyploid radiation hybrid under a given locus order and discuss how this method may be used to identify hybrids with suspiciously large numbers of chromosome breaks.
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Affiliation(s)
- K L Lunetta
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor 48109, USA
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32
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Abstract
Radiation hybrid mapping is a somatic cell technique for ordering genetic loci along a chromosome and estimating physical distances between adjacent loci. This paper presents a model of fragment generation and retention for data involving two or more copies of the chromosome of interest per clone. Such polyploid data can be generated by initially irradiating normal diploid cells or by pooling haploid or diploid clones. The current model assumes that fragments are generated in the ancestral cell of a clone according to an independent Poisson breakage process along each chromosome. Once generated, fragments are independently retained in the clone with a common retention probability. On the basis of this and less restrictive retention models, statistical criteria such as minimum obligate breaks, maximum likelihood ratios, and Bayesian posterior probabilities can be used to decide locus order. Distances can be estimated by maximum likelihood. Likelihood computation is particularly challenging, and computing techniques from the theory of hidden Markov chains prove crucial. Within this context it is possible to incorporate typing errors. The statistical tools discussed here are applied to 14 loci on the short arm of human chromosome 4.
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Affiliation(s)
- K Lange
- Department of Biostatistics, School of Public Health, University of Michigan, Ann Arbor 48109, USA
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Abstract
Juvenile X-linked retinoschisis (RS) is an eye disease that causes acuity reduction and peripheral visual field loss typically beginning early in life. In further work towards positional cloning of the RS gene, we restudied our previously reported seven large American families and one additional new family, with a total of 63 affected males. RS linkage analysis using microsatellite repeat markers gave the following results: DXS207 (Z = 24.89, theta = 0.01), DXS987 (Z = 24.04, theta 0.01) and DXS999 (Z = 14.70, theta = 0.00). Recombination events in four individuals were studied further with additional markers (AFM291wf5, DXS443, DXS1052, DXS274 and DXS1226), and a flanking interval was obtained (DXS43, DXS207, DXS987)-RS-(AFM291wf5, DXS443). This study moves the RS centromeric boundary to (AFM291wf5, DXS443), about 5.5 cM closer than the previously reported boundary at DXS274 and narrows the RS inclusion interval to about 3.7 cM (using distances from CEPH family data).
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Affiliation(s)
- H Pawar
- Department of Ophthalmology, University of Michigan, Ann Arbor, USA
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34
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Abstract
There are several statistical methods available for analyzing radiation hybrid (RH) data, but little is known about the ordering accuracy we can expect under common study conditions. Using analytic methods and computer simulation, we compared the ordering accuracy of three multipoint statistical methods: minimum breaks (MB), maximum likelihood (ML), and maximum posterior probability (PP). For 8, 12, and 16 markers and all combinations of numbers of hybrids, retention patterns, and marker spacings considered, the probabilities that the true order is identified as the best order were considerably higher with the ML and PP methods than with the MB method. ML and PP performed similarly, but PP tended to give slightly greater support for the best order than did ML. Our results can be used as guidelines for determining sample size requirements and optimal marker spacing for future RH mapping experiments. For equally spaced markers, intermarker spacing of 30 to 50 cR gave the highest probability of correctly ordering all the markers. For randomly spaced markers, 10-20 cR average intermarker spacing resulted in the highest proportion of markers being placed in a 1000:1 framework map. Assuming equal retention in the analysis when a centromeric model would be more appropriate did not affect the ability of the ML method to accurately order the markers, but did influence the distance estimates obtained.
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Affiliation(s)
- K L Lunetta
- Department of Biostatics, University of Michigan School of Public Health, Ann Arbor 48109
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35
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Abstract
Although the structural gene for human dopamine-beta-hydroxylase (DBH) has been cloned, the mechanism by which DBH physical properties and activity are regulated is not well understood. Previous reports have suggested that three-allele or two-locus models may account for the genetic regulation of these traits in human blood. It is an interesting challenge to determine the extent to which quantitative analyses will complement or guide molecular genetic studies. In this study we analyzed data on the physical property of DBH thermal stability and DBH activity in 230 individuals in 53 families in an attempt to clarify genetic mechanisms for the inheritance of these traits. Commingling and segregation analyses of the thermal stability data provided the first clear evidence of a major gene polymorphism for DBH thermal stability analyzed as a quantitative trait. Major gene transmission was supported within a mixed model (chi 2[3] = 13.39, P less than .004). In keeping with earlier findings, similar analyses of DBH activity provided strong evidence of genetic transmission. However, in our data support for a major gene polymorphism was equivocal (chi 2(2) = 2.99, P = .22).
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Affiliation(s)
- J P Vuchetich
- Department of Psychology, School of Arts and Sciences, University of Pennsylvania, Philadelphia
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