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Song Z, Gunn S, Monti S, Peloso GM, Liu CT, Lunetta K, Sebastiani P. Learning Gaussian Graphical Models from Correlated Data. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.04.03.587948. [PMID: 38617340 PMCID: PMC11014549 DOI: 10.1101/2024.04.03.587948] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/16/2024]
Abstract
Gaussian Graphical Models (GGM) have been widely used in biomedical research to explore complex relationships between many variables. There are well established procedures to build GGMs from a sample of independent and identical distributed observations. However, many studies include clustered and longitudinal data that result in correlated observations and ignoring this correlation among observations can lead to inflated Type I error. In this paper, we propose a Bootstrap algorithm to infer GGM from correlated data. We use extensive simulations of correlated data from family-based studies to show that the Bootstrap method does not inflate the Type I error while retaining statistical power compared to alternative solutions. We apply our method to learn the GGM that represents complex relations between 47 Polygenic Risk Scores generated using genome-wide genotype data from a family-based study known as the Long Life Family Study. By comparing it to the conventional methods that ignore within-cluster correlation, we show that our method controls the Type I error well in this real example.
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Liang S, Wang N, Wang Y, Wang M, Zhao X, Yang M, Yi H, Zhu M, Wang C, Hang D, Jiang Y, Dai J. Polygenic risk for termination of the 'healthspan' and its interactions with lifestyle factors: A prospective cohort study based on 288,359 participants. Maturitas 2023; 175:107786. [PMID: 37354644 DOI: 10.1016/j.maturitas.2023.107786] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 05/24/2023] [Accepted: 06/09/2023] [Indexed: 06/26/2023]
Abstract
OBJECTIVES To investigate whether a polygenic risk score (PRS) and its interactions with lifestyle factors are associated with termination of the 'healthspan' (the number of years living without serious diseases or degeneration). DESIGN, EXPOSURES AND PARTICIPANTS Death or the incidence of any of seven independent morbidities (cancer, congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, and diabetes) strongly associated with aging were considered to define the termination of the healthspan. A total of 288,359 healthy participants from the UK Biobank were included in this prospective cohort study to evaluate the associations between PRS, lifestyle, and healthspan. The PRS was generated by weighting 12 healthspan-related genetic loci, which and scores were then categorized into three groups in Cox regression models. A lifestyle index was developed that incorporated body mass index (BMI), alcohol consumption, diet, smoking, and physical activity, and these scores were also categorized into three groups. The risk of termination of the healthspan was calculated across the different PRS and lifestyle index groups using Cox regression models. Interactions were estimated with the marginal effect of lifestyle on the risk of termination of healthspan across values of the moderator PRS using kernel estimation. RESULTS During an average follow-up of 9.83 years, 68,903 healthspan-termination events occurred. It was calculated that people with high polygenic risk could reduce their risk of healthspan termination by 40 % if they maintain a favorable lifestyle. The marginal effect of lifestyle on the risk of healthspan termination increased with growing genetic risk. Smoking and diet showed monotonic changes in opposite directions, while BMI, physical activity, and alcohol had a U-shaped interaction with genetic risk. CONCLUSIONS Favorable lifestyle can attenuate the risk of termination of the healthspan, especially for people with high genetic risk. The improvement afforded by ideal lifestyle behaviors varies for each individual.
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Affiliation(s)
- Shuang Liang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Nanxi Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Yifan Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Mei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Xiaoyu Zhao
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Meiqi Yang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Honggang Yi
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing 211166, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing 211166, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, China
| | - Cheng Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing 211166, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, China
| | - Dong Hang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing 211166, China
| | - Yue Jiang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing 211166, China
| | - Juncheng Dai
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, China; Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Gusu School, Nanjing Medical University, Nanjing 211166, China; Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, China.
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Wojczynski MK, Lin SJ, Sebastiani P, Perls TT, Lee J, Kulminski A, Newman A, Zmuda JM, Christensen K, Province MA. NIA Long Life Family Study: Objectives, Design, and Heritability of Cross Sectional and Longitudinal Phenotypes. J Gerontol A Biol Sci Med Sci 2021; 77:717-727. [PMID: 34739053 PMCID: PMC8974329 DOI: 10.1093/gerona/glab333] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2021] [Indexed: 12/02/2022] Open
Abstract
The NIA Long Life Family Study (LLFS) is a longitudinal, multicenter, multinational, population-based multigenerational family study of the genetic and nongenetic determinants of exceptional longevity and healthy aging. The Visit 1 in-person evaluation (2006–2009) recruited 4 953 individuals from 539 two-generation families, selected from the upper 1% tail of the Family Longevity Selection Score (FLoSS, which quantifies the degree of familial clustering of longevity). Demographic, anthropometric, cognitive, activities of daily living, ankle-brachial index, blood pressure, physical performance, and pulmonary function, along with serum, plasma, lymphocytes, red cells, and DNA, were collected. A Genome Wide Association Scan (GWAS) (Ilumina Omni 2.5M chip) followed by imputation was conducted. Visit 2 (2014–2017) repeated all Visit 1 protocols and added carotid ultrasonography of atherosclerotic plaque and wall thickness, additional cognitive testing, and perceived fatigability. On average, LLFS families show healthier aging profiles than reference populations, such as the Framingham Heart Study, at all age/sex groups, for many critical healthy aging phenotypes. However, participants are not uniformly protected. There is considerable heterogeneity among the pedigrees, with some showing exceptional cognition, others showing exceptional grip strength, others exceptional pulmonary function, etc. with little overlap in these families. There is strong heritability for key healthy aging phenotypes, both cross-sectionally and longitudinally, suggesting that at least some of this protection may be genetic. Little of the variance in these heritable phenotypes is explained by the common genome (GWAS + Imputation), which may indicate that rare protective variants for specific phenotypes may be running in selected families.
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Affiliation(s)
- Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Shiow Jiuan Lin
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Thomas T Perls
- Department of Medicine, Geriatrics Section, Boston Medical Center, Boston University School of Medicine, MA, USA
| | - Joseph Lee
- Taub Institute for Research on Alzheimer's Disease and the Aging Brain, Department of Neurology, Columbia University Medical Center, New York, NY, USA
| | - Alexander Kulminski
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, USA
| | - Anne Newman
- Departments of Epidemiology and Human Genetics, Graduate School of Public Health, University of Pittsburgh, PA, USA
| | - Joe M Zmuda
- Departments of Epidemiology and Human Genetics, Graduate School of Public Health, University of Pittsburgh, PA, USA
| | - Kaare Christensen
- Unit of Epidemiology, Biostatistics and Biodemography, Department of Public Health, Southern Denmark University, Odense, Denmark
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, USA
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Vital personality scores and healthy aging: Life-course associations and familial transmission. Soc Sci Med 2021; 285:114283. [PMID: 34450386 PMCID: PMC8482063 DOI: 10.1016/j.socscimed.2021.114283] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 07/16/2021] [Accepted: 07/28/2021] [Indexed: 11/21/2022]
Abstract
OBJECTIVES Personality traits are linked with healthy aging, but it is not clear how these associations come to manifest across the life-course and across generations. To study this question, we tested a series of hypotheses about (a) personality-trait prediction of markers of healthy aging across the life-course, (b) developmental origins, stability and change of links between personality and healthy aging across time, and (c) intergenerational transmission of links between personality and healthy aging. For our analyses we used a measure that aggregates the contributions of Big 5 personality traits to healthy aging: a "vital personality" score. METHODS Data came from two population-based longitudinal cohort studies, one based in New Zealand and the other in the UK, comprising over 6000 study members across two generations, and spanning an age range from birth to late life. RESULTS Our analyses revealed three main findings: first, individuals with higher vital personality scores engaged in fewer health-risk behaviors, aged slower, and lived longer. Second, individuals' vital personality scores were preceded by differences in early-life temperament and were relatively stable across adulthood, but also increased from young adulthood to midlife. Third, individuals with higher vital personality scores had children with similarly vital partners, promoted healthier behaviors in their children, and had children who grew up to have more vital personality scores themselves, for genetic and environmental reasons. CONCLUSION Our study shows how the health benefits associated with personality accrue throughout the life-course and across generations.
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Zwir I, Del-Val C, Arnedo J, Pulkki-Råback L, Konte B, Yang SS, Romero-Zaliz R, Hintsanen M, Cloninger KM, Garcia D, Svrakic DM, Lester N, Rozsa S, Mesa A, Lyytikäinen LP, Giegling I, Kähönen M, Martinez M, Seppälä I, Raitoharju E, de Erausquin GA, Mamah D, Raitakari O, Rujescu D, Postolache TT, Gu CC, Sung J, Lehtimäki T, Keltikangas-Järvinen L, Cloninger CR. Three genetic-environmental networks for human personality. Mol Psychiatry 2021; 26:3858-3875. [PMID: 31748689 PMCID: PMC8550959 DOI: 10.1038/s41380-019-0579-x] [Citation(s) in RCA: 39] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Revised: 09/26/2019] [Accepted: 10/24/2019] [Indexed: 02/07/2023]
Abstract
Phylogenetic, developmental, and brain-imaging studies suggest that human personality is the integrated expression of three major systems of learning and memory that regulate (1) associative conditioning, (2) intentionality, and (3) self-awareness. We have uncovered largely disjoint sets of genes regulating these dissociable learning processes in different clusters of people with (1) unregulated temperament profiles (i.e., associatively conditioned habits and emotional reactivity), (2) organized character profiles (i.e., intentional self-control of emotional conflicts and goals), and (3) creative character profiles (i.e., self-aware appraisal of values and theories), respectively. However, little is known about how these temperament and character components of personality are jointly organized and develop in an integrated manner. In three large independent genome-wide association studies from Finland, Germany, and Korea, we used a data-driven machine learning method to uncover joint phenotypic networks of temperament and character and also the genetic networks with which they are associated. We found three clusters of similar numbers of people with distinct combinations of temperament and character profiles. Their associated genetic and environmental networks were largely disjoint, and differentially related to distinct forms of learning and memory. Of the 972 genes that mapped to the three phenotypic networks, 72% were unique to a single network. The findings in the Finnish discovery sample were blindly and independently replicated in samples of Germans and Koreans. We conclude that temperament and character are integrated within three disjoint networks that regulate healthy longevity and dissociable systems of learning and memory by nearly disjoint sets of genetic and environmental influences.
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Grants
- Spanish Ministry of Science and Technology TIN2012-38805 and DPI2015-69585-R
- The Young Finns Study has been financially supported by the Academy of Finland: grants 286284, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), 41071 (Skidi), and 308676; the Social Insurance Institution of Finland; Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals (grant X51001); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation for Cardiovascular Research ; Finnish Cultural Foundation; Tampere Tuberculosis Foundation; Emil Aaltonen Foundation; Yrjö Jahnsson Foundation; Signe and Ane Gyllenberg Foundation; Diabetes Research Foundation of Finnish Diabetes Association: and EU Horizon 2020 (grant 755320 for TAXINOMISIS).
- American Federation for Suicide Prevention
- Healthy Twin Family Register of Korea
- Anthropedia Foundation
- The Young Finns Study has been financially supported by the Academy of Finland: grants 286284, 322098, 134309 (Eye), 126925, 121584, 124282, 129378 (Salve), 117787 (Gendi), 41071 (Skidi), and 308676; the Social Insurance Institution of Finland; Competitive State Research Financing of the Expert Responsibility area of Kuopio, Tampere and Turku University Hospitals (grant X51001); Juho Vainio Foundation; Paavo Nurmi Foundation; Finnish Foundation for Cardiovascular Research ; Finnish Cultural Foundation; Tampere Tuberculosis Foundation; Emil Aaltonen Foundation; Yrjö Jahnsson Foundation; Signe and Ane Gyllenberg Foundation; Diabetes Research Foundation of Finnish Diabetes Association: and EU Horizon 2020 (grant 755320 for TAXINOMISIS); and Tampere University Hospital Supporting Foundation.
- American Society for Suicide Prevention
- American Foundation for Suicide Prevention
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Affiliation(s)
- Igor Zwir
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Department of Computer Science, University of Granada, Granada, Spain
| | - Coral Del-Val
- Department of Computer Science, University of Granada, Granada, Spain
| | - Javier Arnedo
- Department of Computer Science, University of Granada, Granada, Spain
| | - Laura Pulkki-Råback
- Department of Psychology and Logopedics, University of Helsinki, Helsinki, Finland
| | - Bettina Konte
- Department of Psychiatry, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Sarah S Yang
- Department of Epidemiology, and Institute of Health and Environment, School of Public Health, Seoul National University, Seoul, Korea
| | | | - Mirka Hintsanen
- Unit of Psychology, Faculty of Education, University of Oulu, Oulu, Finland
| | | | - Danilo Garcia
- Department of Psychology, University of Gothenburg, Gothenburg, Sweden
- Blekinge Centre of Competence, Blekinge County Council, Karlskrona, Sweden
| | - Dragan M Svrakic
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Nigel Lester
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Sandor Rozsa
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Alberto Mesa
- Department of Computer Science, University of Granada, Granada, Spain
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Ina Giegling
- Department of Psychiatry, Martin-Luther-University Halle-Wittenberg, Halle, Germany
- University Clinic, Ludwig-Maximilian University, Munich, Germany
| | - Mika Kähönen
- Department of Clinical Physiology Tampere University Hospital, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Maribel Martinez
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Emma Raitoharju
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Gabriel A de Erausquin
- The Glenn Biggs Institute of Alzheimer's and Neurodegenerative Disorders, Long School of Medicine, University of Texas Heath San Antonio, San Antonio, TX, USA
| | - Daniel Mamah
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
| | - Olli Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland
- Centre for Population Health Research, Turku University Hospital, University of Turku Hospital, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
| | - Dan Rujescu
- Department of Psychiatry, Martin-Luther-University Halle-Wittenberg, Halle, Germany
| | - Teodor T Postolache
- Department of Psychiatry, School of Medicine, University of Maryland, Baltimore, MD, USA
- Rocky Mountain Mental Illness, Research, Education, and Clinical Center for Veteran Suicide Prevention, Denver, CO, USA
| | - C Charles Gu
- Division of Biostatistics, School of Medicine, Washington University, St. Louis, MO, USA
| | - Joohon Sung
- Department of Epidemiology, and Institute of Health and Environment, School of Public Health, Seoul National University, Seoul, Korea
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories, and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | | | - C Robert Cloninger
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA.
- Department of Psychological and Brain Sciences, and School of Medicine, Department of Genetics, School of Arts and Sciences, Washington University, St. Louis, MO, USA.
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Liu X, Song Z, Li Y, Yao Y, Fang M, Bai C, An P, Chen H, Chen Z, Tang B, Shen J, Gao X, Zhang M, Chen P, Zhang T, Jia H, Liu X, Hou Y, Yang H, Wang J, Wang F, Xu X, Min J, Nie C, Zeng Y. Integrated genetic analyses revealed novel human longevity loci and reduced risks of multiple diseases in a cohort study of 15,651 Chinese individuals. Aging Cell 2021; 20:e13323. [PMID: 33657282 PMCID: PMC7963337 DOI: 10.1111/acel.13323] [Citation(s) in RCA: 25] [Impact Index Per Article: 8.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2020] [Revised: 01/16/2021] [Accepted: 01/23/2021] [Indexed: 12/14/2022] Open
Abstract
There is growing interest in studying the genetic contributions to longevity, but limited relevant genes have been identified. In this study, we performed a genetic association study of longevity in a total of 15,651 Chinese individuals. Novel longevity loci, BMPER (rs17169634; p = 7.91 × 10-15 ) and TMEM43/XPC (rs1043943; p = 3.59 × 10-8 ), were identified in a case-control analysis of 11,045 individuals. BRAF (rs1267601; p = 8.33 × 10-15 ) and BMPER (rs17169634; p = 1.45 × 10-10 ) were significantly associated with life expectancy in 12,664 individuals who had survival status records. Additional sex-stratified analyses identified sex-specific longevity genes. Notably, sex-differential associations were identified in two linkage disequilibrium blocks in the TOMM40/APOE region, indicating potential differences during meiosis between males and females. Moreover, polygenic risk scores and Mendelian randomization analyses revealed that longevity was genetically causally correlated with reduced risks of multiple diseases, such as type 2 diabetes, cardiovascular diseases, and arthritis. Finally, we incorporated genetic markers, disease status, and lifestyles to classify longevity or not-longevity groups and predict life span. Our predictive models showed good performance (AUC = 0.86 for longevity classification and explained 19.8% variance of life span) and presented a greater predictive efficiency in females than in males. Taken together, our findings not only shed light on the genetic contributions to longevity but also elucidate correlations between diseases and longevity.
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Affiliation(s)
- Xiaomin Liu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
- BGI Education Center University of Chinese Academy of Sciences Shenzhen China
| | - Zijun Song
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Yan Li
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yao Yao
- Center for the Study of Aging and Human Development Medical School of Duke University Durham USA
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
| | - Mingyan Fang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Chen Bai
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
- School of Labor and Human Resources Renmin University Beijing China
| | - Peng An
- Beijing Advanced Innovation Center for Food Nutrition and Human Health China Agricultural University Beijing China
| | - Huashuai Chen
- Business School of Xiangtan University Xiangtan China
| | - Zhihua Chen
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Biyao Tang
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Juan Shen
- BGI Genomics BGI‐Shenzhen Shenzhen China
| | - Xiaotong Gao
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | | | - Pengyu Chen
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Tao Zhang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Huijue Jia
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Xiao Liu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yong Hou
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Huanming Yang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Jian Wang
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Fudi Wang
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
- Beijing Advanced Innovation Center for Food Nutrition and Human Health China Agricultural University Beijing China
| | - Xun Xu
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
- Guangdong Provincial Key Laboratory of Genome Read and Write Shenzhen China
| | - Junxia Min
- The First Affiliated Hospital Institute of Translational Medicine School of Medicine, Zhejiang University Hangzhou China
| | - Chao Nie
- BGI‐Shenzhen Shenzhen China
- China National Genebank Shenzhen China
| | - Yi Zeng
- Center for the Study of Aging and Human Development Medical School of Duke University Durham USA
- Center for Healthy Aging and Development Studies National School of Development, Raissun Institute for Advanced Studies, Peking University Beijing China
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7
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Zmorzyński S, Styk W, Klinkosz W, Iskra J, Filip AA. Personality traits and polymorphisms of genes coding neurotransmitter receptors or transporters: review of single gene and genome-wide association studies. Ann Gen Psychiatry 2021; 20:7. [PMID: 33482861 PMCID: PMC7825153 DOI: 10.1186/s12991-021-00328-4] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/04/2019] [Accepted: 01/10/2021] [Indexed: 01/11/2023] Open
Abstract
BACKGROUND The most popular tool used for measuring personality traits is the Five-Factor Model (FFM). It includes neuroticism, extraversion, openness, agreeableness and conscientiousness. Many studies indicated the association of genes encoding neurotransmitter receptors/transporters with personality traits. The relationship connecting polymorphic DNA sequences and FFM features has been described in the case of genes encoding receptors of cannabinoid and dopaminergic systems. Moreover, dopaminergic system receives inputs from other neurotransmitters, like GABAergic or serotoninergic systems. METHODS We searched PubMed Central (PMC), Science Direct, Scopus, Cochrane Library, Web of Science and EBSCO databases from their inception to November 19, 2020, to identify original studies, as well as peer-reviewed studies examining the FFM and its association with gene polymorphisms affecting the neurotransmitter functions in central nervous system. RESULTS Serotonin neurons modulate dopamine function. In gene encoding serotonin transporter protein, SLC6A4, was found polymorphism, which was correlated with openness to experience (in Sweden population), and high scores of neuroticism and low levels of agreeableness (in Caucasian population). The genome-wide association studies (GWASs) found an association of 5q34-q35, 3p24, 3q13 regions with higher scores of neuroticism, extraversion and agreeableness. However, the results for chromosome 3 regions are inconsistent, which was shown in our review paper. CONCLUSIONS GWASs on polymorphisms are being continued in order to determine and further understand the relationship between the changes in DNA and personality traits.
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Affiliation(s)
- Szymon Zmorzyński
- Department of Cancer Genetics With Cytogenetic Laboratory, Medical University of Lublin, Lublin, Poland
| | - Wojciech Styk
- Institute of Psychology, The John Paul II Catholic University of Lublin, Lublin, Poland.
| | - Waldemar Klinkosz
- Institute of Psychology, Cardinal Stefan Wyszynski University, Warsaw, Poland
| | - Justyna Iskra
- Institute of Psychology, The John Paul II Catholic University of Lublin, Lublin, Poland
| | - Agata Anna Filip
- Department of Cancer Genetics With Cytogenetic Laboratory, Medical University of Lublin, Lublin, Poland
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8
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Sebastiani P, Andersen SL, Sweigart B, Du M, Cosentino S, Thyagarajan B, Christensen K, Schupf N, Perls TT. Patterns of multi-domain cognitive aging in participants of the Long Life Family Study. GeroScience 2020; 42:1335-1350. [PMID: 32514870 PMCID: PMC7525612 DOI: 10.1007/s11357-020-00202-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2020] [Accepted: 05/08/2020] [Indexed: 12/16/2022] Open
Abstract
Maintaining good cognitive function at older age is important, but our knowledge of patterns and predictors of cognitive aging is still limited. We used Bayesian model-based clustering to group 5064 participants of the Long Life Family Study (ages 49-110 years) into clusters characterized by distinct trajectories of cognitive change in the domains of episodic memory, attention, processing speed, and verbal fluency. For each domain, we identified 4 or 5 large clusters with representative patterns of change ranging from rapid decline to exceptionally slow change. We annotated the clusters by their correlation with genetic and molecular biomarkers, non-genetic risk factors, medical history, and other markers of aging to discover correlates of cognitive changes and neuroprotection. The annotation analysis discovered both predictors of multi-domain cognitive change such as gait speed and predictors of domain-specific cognitive change such as IL6 and NTproBNP that correlate only with change of processing speed or APOE genotypes that correlate only with change of processing speed and logical memory. These patterns also suggest that cognitive decline starts at young age and that maintaining good physical function correlates with slower cognitive decline. To better understand the agreement of cognitive changes across multiple domains, we summarized the results of the cluster analysis into a score of cognitive function change. This score showed that extreme patterns of change affecting multiple cognitive domains simultaneously are rare in this study and that specific signatures of biomarkers of inflammation and metabolic disease predict severity of cognitive changes. The substantial heterogeneity of change patterns within and between cognitive domains and the net of correlations between patterns of cognitive aging and other aging traits emphasizes the importance of measuring a wide range of cognitive functions and the need for studying cognitive aging in concert with other aging traits.
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Affiliation(s)
- Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118 USA
| | - Stacy L. Andersen
- Department of Medicine, Geriatrics Section, Boston University School of Medicine, Robinson 2400, 72 E Concord St, Boston, MA 02118 USA
| | - Benjamin Sweigart
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118 USA
| | - Mengtian Du
- Department of Biostatistics, Boston University School of Public Health, 801 Massachusetts Avenue, Boston, MA 02118 USA
| | - Stephanie Cosentino
- Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, and the Gertrude H. Sergievsky Center, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032 USA
| | - Bharat Thyagarajan
- Department of Laboratory Medicine and Pathology, University of Minnesota Medical School, MMC 609 Mayo, 420 Delaware, Minneapolis, MN 55455 USA
| | - Kaare Christensen
- Department of Public Health, The Danish Aging Research Center and The Danish Twin Registry, Epidemiology, Biostatistics and Biodemography, University of Southern Denmark, 5000 Odense, Denmark
| | - Nicole Schupf
- Department of Neurology, Taub Institute for Research on Alzheimer’s Disease and the Aging Brain, and the Gertrude H. Sergievsky Center, Columbia University Medical Center, 630 West 168th Street, New York, NY 10032 USA
- Department of Epidemiology, Sergievsky Center, Columbia University Mailman School of Public Health, 630 West 168th Street, New York, NY 10032 USA
| | - Thomas T Perls
- Department of Medicine, Geriatrics Section, Boston University School of Medicine, Robinson 2400, 72 E Concord St, Boston, MA 02118 USA
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9
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Chen C, Wei Y, Wei L, Chen J, Chen X, Dong X, He J, Lin L, Zhu Y, Huang H, You D, Lai L, Shen S, Duan W, Su L, Shafer A, Fleischer T, Bjaanæs MM, Karlsson A, Planck M, Wang R, Staaf J, Helland Å, Esteller M, Zhang R, Chen F, Christiani DC. Epigenome-wide gene-age interaction analysis reveals reversed effects of PRODH DNA methylation on survival between young and elderly early-stage NSCLC patients. Aging (Albany NY) 2020; 12:10642-10662. [PMID: 32511103 PMCID: PMC7346054 DOI: 10.18632/aging.103284] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2019] [Accepted: 04/27/2020] [Indexed: 12/29/2022]
Abstract
DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation–age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts. A Cox proportional hazards model was used to investigate lung adenocarcinoma and squamous cell carcinoma patients for methylation–age interactions, which were further confirmed in a validation phase. We identified one adenocarcinoma-specific CpG probe, cg14326354PRODH, with effects significantly modified by age (HRinteraction = 0.989; 95% CI: 0.986–0.994; P = 9.18×10–7). The effect of low methylation was reversed for young and elderly patients categorized by the boundary of 95% CI standard (HRyoung = 2.44; 95% CI: 1.26–4.72; P = 8.34×10-3; HRelderly = 0.58; 95% CI: 0.42–0.82; P = 1.67×10-3). Moreover, there was an antagonistic interaction between low cg14326354PRODH methylation and elderly age (HRinteraction = 0.21; 95% CI: 0.11–0.40; P = 2.20×10−6). In summary, low methylation of cg14326354PRODH might benefit survival of elderly lung adenocarcinoma patients, providing new insight to age-specific prediction and potential drug targeting.
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Affiliation(s)
- Chao Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Yongyue Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Liangmin Wei
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Jiajin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Xin Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Xuesi Dong
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Epidemiology and Biostatistics, School of Public Health, Southeast University, Nanjing 210009, Jiangsu, China
| | - Jieyu He
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Lijuan Lin
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Ying Zhu
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Hui Huang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Dongfang You
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Linjing Lai
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Sipeng Shen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Weiwei Duan
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Bioinformatics, School of Biomedical Engineering and Informatics, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - Li Su
- China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Andrea Shafer
- Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Thomas Fleischer
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo 0424, Norway
| | - Maria Moksnes Bjaanæs
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo 0424, Norway
| | - Anna Karlsson
- Division of Oncology and Pathology, Department of Clinical Sciences Lund and CREATE Health Strategic Center for Translational Cancer Research, Lund University, Lund 22381, Sweden
| | - Maria Planck
- Division of Oncology and Pathology, Department of Clinical Sciences Lund and CREATE Health Strategic Center for Translational Cancer Research, Lund University, Lund 22381, Sweden
| | - Rui Wang
- Department of Medical Oncology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing 210002, Jiangsu China
| | - Johan Staaf
- Division of Oncology and Pathology, Department of Clinical Sciences Lund and CREATE Health Strategic Center for Translational Cancer Research, Lund University, Lund 22381, Sweden
| | - Åslaug Helland
- Department of Cancer Genetics, Institute for Cancer Research, Oslo University Hospital, Oslo 0424, Norway.,Institute of Clinical Medicine, University of Oslo, Oslo 0424, Norway
| | - Manel Esteller
- Josep Carreras Leukaemia Research Institute, Badalona, Barcelona, 08021, Catalonia, Spain.,Centro de Investigacion Biomedica en Red Cancer, Madrid 28029, Spain.,Institucio Catalana de Recerca i Estudis Avançats, Barcelona 08010, Catalonia, Spain.,Physiological Sciences Department, School of Medicine and Health Sciences, University of Barcelona, Barcelona 08007, Catalonia, Spain
| | - Ruyang Zhang
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.,Department of Medical Oncology, Jinling Hospital, School of Medicine, Nanjing University, Nanjing 210002, Jiangsu China
| | - Feng Chen
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,State Key Laboratory of Reproductive Medicine, Nanjing Medical University, Nanjing 211166, Jiangsu, China.,Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Cancer Center, Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing 211166, Jiangsu, China
| | - David C Christiani
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA.,Pulmonary and Critical Care Division, Department of Medicine, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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10
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Bae H, Lunetta KL, Murabito JM, Andersen SL, Schupf N, Perls T, Sebastiani P. Genetic associations with age of menopause in familial longevity. Menopause 2019; 26:1204-1212. [PMID: 31188284 PMCID: PMC7008937 DOI: 10.1097/gme.0000000000001367] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
OBJECTIVE We hypothesize that mechanisms associated with extended reproductive age may overlap with mechanisms for the selection of genetic variants that slow aging and decrease risk for age-related diseases. Therefore, the goal of this analysis is to search for genetic variants associated with delayed age of menopause (AOM) among women in a study of familial longevity. METHODS We performed a meta-analysis of genome-wide association studies for AOM in 1,286 women in the Long Life Family Study (LLFS) and 3,151 women in the Health and Retirement Study, and then sought replication in the Framingham Heart Study (FHS). We used Cox proportional hazard regression of AOM to account for censoring, with a robust variance estimator to adjust for within familial relations. RESULTS In the meta-analysis, a single nucleotide polymorphism (SNP) previously associated with AOM reached genome-wide significance (rs16991615; HR = 0.74, P = 6.99 × 10). A total of 35 variants reached >10 level of significance and replicated in the FHS and in a 2015 large meta-analysis (ReproGen Consortium). We also identified several novel SNPs associated with AOM including rs3094005: MICB, rs13196892: TXNDC5 | MUTED, rs72774935: SSBP2 | ATG10, rs9447453: COL12A1, rs114298934: FHL2 | NCK2, rs6467223: TNPO3, rs9666274 and rs10766593: NAV2, and rs7281846: HSPA13. CONCLUSIONS This work indicates novel associations and replicates known associations between genetic variants and AOM. A number of these associations make sense for their roles in aging. VIDEO SUMMARY Supplemental Digital Content 1, http://links.lww.com/MENO/A420.
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Affiliation(s)
- Harold Bae
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
| | - Joanne M Murabito
- Section of General Internal Medicine, Department of Medicine, and the Framingham Heart Study, Boston University School of Medicine, Boston, MA
| | - Stacy L Andersen
- Geriatrics Section, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA
| | - Nicole Schupf
- Department of Epidemiology, Mailman School of Public Health, Columbia University, NY
| | - Thomas Perls
- Geriatrics Section, Department of Medicine, Boston Medical Center and Boston University School of Medicine, Boston, MA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA
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11
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Sallis H, Davey Smith G, Munafò MR. Genetics of biologically based psychological differences. Philos Trans R Soc Lond B Biol Sci 2019; 373:rstb.2017.0162. [PMID: 29483347 PMCID: PMC5832687 DOI: 10.1098/rstb.2017.0162] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 11/22/2017] [Indexed: 01/21/2023] Open
Abstract
In recent years, substantial effort has gone into disentangling the genetic contribution to individual differences in behaviour (such as personality and temperament traits). Heritability estimates from twin and family studies, and more recently using whole genome approaches, suggest a substantial genetic component to these traits. However, efforts to identify the genes that influence these traits have had relatively little success. Here, we review current work investigating the heritability of individual differences in behavioural traits and provide an overview of the results from genome-wide association analyses of these traits to date. In addition, we discuss the implications of these findings for the potential applications of Mendelian randomization.This article is part of the theme issue 'Diverse perspectives on diversity: multi-disciplinary approaches to taxonomies of individual differences'.
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Affiliation(s)
- Hannah Sallis
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK .,UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK.,Centre for Academic Mental Health, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | | | - Marcus R Munafò
- MRC Integrative Epidemiology Unit, University of Bristol, Bristol, UK.,UK Centre for Tobacco and Alcohol Studies, School of Experimental Psychology, University of Bristol, Bristol, UK
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12
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Bae H, Gurinovich A, Malovini A, Atzmon G, Andersen SL, Villa F, Barzilai N, Puca A, Perls TT, Sebastiani P. Effects of FOXO3 Polymorphisms on Survival to Extreme Longevity in Four Centenarian Studies. J Gerontol A Biol Sci Med Sci 2018; 73:1439-1447. [PMID: 28977569 PMCID: PMC6175020 DOI: 10.1093/gerona/glx124] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2016] [Indexed: 02/04/2023] Open
Abstract
Previous studies note specific FOXO3 single-nucleotide polymorphisms (SNPs) associated with human longevity. However, it is not clear if these SNPs influence mortality risk beyond the oldest 1 percentile of survival. Using data from four longevity studies (total n = 8,266, age range 96-119 years for cases), we tested gene-wide association between 107 SNPs and survival to at least the oldest 1 percentile of survival for the 1900 birth cohort (≥96, white males; ≥100 white females). This analysis replicated 17 previously published variants, several of which are significant expression quantitative trait loci of FOXO3; rs6911407 and rs2253310 have the most significant effect on FOXO3 expressions in brain tissue. We then performed a survival analysis to determine if any of these 107 SNPs impact upon mortality risk beyond the oldest 1 percentile. While none of the 17 published variants was significantly associated with mortality risk beyond this extreme age, an uncommon homozygote genotype of rs9384680 exhibited the strongest association with mortality risk (p = 2.68E-04) in only 11 females, a heretofore unreported association. These analyses replicate the previous association of common variants of FOXO3 with older age but these common variants do not modify risk for mortality at ages beyond the oldest 1 percentile age of survival.
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Affiliation(s)
- Harold Bae
- College of Public Health and Human Sciences, Oregon State University, Corvallis,Address correspondence to: Harold Bae, College of Public Health and Human Sciences, Oregon State University, 151 Milam Hall, Corvallis, OR 97331. E-mail:
| | | | - Alberto Malovini
- Laboratory of Informatics and Systems Engineering for Clinical Research, IRCCS Fondazione Salvatore Maugeri, Pavia Pavia, Italy
| | - Gil Atzmon
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, New York,Faculty of Natural Science, University of Haifa, Israel
| | - Stacy L Andersen
- Geriatrics Section, Department of Medicine, Boston University School of Medicine & Boston Medical Center, Massachusetts
| | - Francesco Villa
- IRCCS Multimedica, Laboratory of Cardiovascular Research, Milan, Italy
| | - Nir Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, New York
| | - Annibale Puca
- IRCCS MultiMedica, Milan, Italy and Department of Medicine and Surgery, University of Salerno, Baronissi, Italy
| | - Thomas T Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine & Boston Medical Center, Massachusetts
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
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13
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Genomic Approach to Understand the Association of DNA Repair with Longevity and Healthy Aging Using Genomic Databases of Oldest-Old Population. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2018; 2018:2984730. [PMID: 29854078 PMCID: PMC5960555 DOI: 10.1155/2018/2984730] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/27/2018] [Accepted: 04/03/2018] [Indexed: 12/16/2022]
Abstract
Aged population is increasing worldwide due to the aging process that is inevitable. Accordingly, longevity and healthy aging have been spotlighted to promote social contribution of aged population. Many studies in the past few decades have reported the process of aging and longevity, emphasizing the importance of maintaining genomic stability in exceptionally long-lived population. Underlying reason of longevity remains unclear due to its complexity involving multiple factors. With advances in sequencing technology and human genome-associated approaches, studies based on population-based genomic studies are increasing. In this review, we summarize recent longevity and healthy aging studies of human population focusing on DNA repair as a major factor in maintaining genome integrity. To keep pace with recent growth in genomic research, aging- and longevity-associated genomic databases are also briefly introduced. To suggest novel approaches to investigate longevity-associated genetic variants related to DNA repair using genomic databases, gene set analysis was conducted, focusing on DNA repair- and longevity-associated genes. Their biological networks were additionally analyzed to grasp major factors containing genetic variants of human longevity and healthy aging in DNA repair mechanisms. In summary, this review emphasizes DNA repair activity in human longevity and suggests approach to conduct DNA repair-associated genomic study on human healthy aging.
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14
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Melas PA, Guban P, Rahman MS, Lavebratt C, Forsell Y. Neuropeptide Y, stressful life events and personality trait conscientiousness: Preliminary associations from a Swedish longitudinal study. Psychiatry Res 2018; 263:48-53. [PMID: 29494882 DOI: 10.1016/j.psychres.2018.02.041] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/22/2017] [Revised: 11/23/2017] [Accepted: 02/18/2018] [Indexed: 11/20/2022]
Abstract
The heritability of the Five-Factor Model (FFM) of human personality is high, but few genes have been identified to underlie FFM traits. Neuropeptide Y (NPY) is a pleiotropic gene implicated in stress resilience that contains two well-studied functional SNPs: (1) rs16147, which lies in the NPY promoter and affects expression levels, and (2) rs16139, which lies in the coding sequence of NPY's precursor peptide, pre-pro NPY, and affects precursor processing. In the present study we examined whether these two polymorphisms are associated with FFM traits, using a Swedish cohort (rs16147, N = 2113; and rs16139, N = 1971), and found a significant association with rs16139. Specifically, the minor G-allele of the SNP, which encodes proline instead of leucine and leads to higher processing of pre-pro NPY into mature NPY, was associated with higher levels of conscientiousness. Next, we looked at exposure to life adversities, both in childhood and adulthood, and found that stressful life events were significantly associated with reduced levels of conscientiousness. These data provide insights into the neurobiology of human personality. However, given the difficulty in replicating genetic and environmental associations with behaviorally complex traits, these findings should be considered preliminary and warrant replication in additional cohorts.
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Affiliation(s)
- Philippe A Melas
- Department of Clinical Neuroscience, Karolinska Institutet, CMM L8:00, Karolinska University Hospital, 17176 Stockholm, Sweden; Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden.
| | - Peter Guban
- Center for Epidemiology and Community Medicine, Stockholm County Council, Stockholm, Sweden
| | - Md Shafiqur Rahman
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
| | - Catharina Lavebratt
- Center for Molecular Medicine, Karolinska University Hospital, Stockholm, Sweden; Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Yvonne Forsell
- Department of Public Health Sciences, Karolinska Institutet, Stockholm, Sweden
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15
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Sanchez-Roige S, Gray JC, MacKillop JK, Chen CH, Palmer AA. The genetics of human personality. GENES, BRAIN, AND BEHAVIOR 2018; 17:e12439. [PMID: 29152902 PMCID: PMC7012279 DOI: 10.1111/gbb.12439] [Citation(s) in RCA: 63] [Impact Index Per Article: 10.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/30/2017] [Revised: 10/12/2017] [Accepted: 11/07/2017] [Indexed: 12/13/2022]
Abstract
Personality traits are the relatively enduring patterns of thoughts, feelings and behaviors that reflect the tendency to respond in certain ways under certain circumstances. Twin and family studies have showed that personality traits are moderately heritable, and can predict various lifetime outcomes, including psychopathology. The Research Domain Criteria characterizes psychiatric diseases as extremes of normal tendencies, including specific personality traits. This implies that heritable variation in personality traits, such as neuroticism, would share a common genetic basis with psychiatric diseases, such as major depressive disorder. Despite considerable efforts over the past several decades, the genetic variants that influence personality are only beginning to be identified. We review these recent and increasingly rapid developments, which focus on the assessment of personality via several commonly used personality questionnaires in healthy human subjects. Study designs covered include twin, linkage, candidate gene association studies, genome-wide association studies and polygenic analyses. Findings from genetic studies of personality have furthered our understanding about the genetic etiology of personality, which, like neuropsychiatric diseases themselves, is highly polygenic. Polygenic analyses have showed genetic correlations between personality and psychopathology, confirming that genetic studies of personality can help to elucidate the etiology of several neuropsychiatric diseases.
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Affiliation(s)
- Sandra Sanchez-Roige
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
| | - Joshua C Gray
- Center for Deployment Psychology, Uniformed Services University, Bethesda, MD, 20814
| | - James K MacKillop
- Peter Boris Centre for Addictions Research, McMaster University/St. Joseph’s Healthcare Hamilton, Hamilton, ON L8N 3K7, Canada; Homewood Research Institute, Guelph, ON N1E 6K9, Canada
| | - Chi-Hua Chen
- Department of Radiology, University of California San Diego, La Jolla, CA, 92093, USA
| | - Abraham A Palmer
- Department of Psychiatry, University of California San Diego, La Jolla, CA, 92093, USA
- Institute for Genomic Medicine, University of California San Diego, La Jolla, CA, USA
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16
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Sebastiani P, Gurinovich A, Bae H, Andersen SL, Perls TT. Assortative Mating by Ethnicity in Longevous Families. Front Genet 2017; 8:186. [PMID: 29209360 PMCID: PMC5702482 DOI: 10.3389/fgene.2017.00186] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2017] [Accepted: 11/07/2017] [Indexed: 12/01/2022] Open
Abstract
Recent work shows strong evidence of ancestry-based assortative mating in spouse pairs of the older generation of the Framingham Heart Study. Here, we extend this analysis to two studies of human longevity: the Long Life Family Study (LLFS), and the New England Centenarian Study (NECS). In the LLFS, we identified 890 spouse pairs spanning two generations, while in the NECS we used data from 102 spouse pairs including offspring of centenarians. We used principal components of genome-wide genotype data to demonstrate strong evidence of ancestry-based assortative mating in spouse pairs of the older generation and also confirm the decreasing trend of endogamy in more recent generations. These findings in studies of human longevity suggest that spouses marrying into longevous families may not be powerful controls for genetic association studies, and that there may be important ethnicity-specific, genetic influences and/or gene–environment interactions that influence extreme survival in old generations. In addition, the decreasing trend of genetic similarity of more recent generations might have ramifications for the incidence of homozygous rare variants necessary for survival to the most extreme ages.
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Affiliation(s)
- Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | | | - Harold Bae
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States
| | - Stacy L Andersen
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA, United States
| | - Thomas T Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA, United States
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17
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Heckerman D, Traynor BJ, Picca A, Calvani R, Marzetti E, Hernandez D, Nalls M, Arepali S, Ferrucci L, Landi F. Genetic variants associated with physical performance and anthropometry in old age: a genome-wide association study in the ilSIRENTE cohort. Sci Rep 2017; 7:15879. [PMID: 29158487 PMCID: PMC5696534 DOI: 10.1038/s41598-017-13475-0] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2017] [Accepted: 09/25/2017] [Indexed: 11/09/2022] Open
Abstract
Unraveling the complexity of aging is crucial for understanding its mechanisms and its role as a risk factor for most chronic conditions. Advancements marked by genome-wide association studies (GWASs) have sparked interest in gene cataloguing in the context of aging and age-related conditions. Here, we used GWAS to explore whether single nucleotide polymorphisms (SNPs) were associated with functional and anthropometric parameters in a cohort of old community-dwellers enrolled in the ilSIRENTE study. Analyses were carried out in men and women aged 80+ years enrolled in the ilSIRENTE study (n = 286) and replicated in the inCHIANTI study (n = 1055). Genotyping was accomplished on Infinium Human610-QUAD version 1. In the ilSIRENTE population, genetic variants in ZNF295 and C2CD2 (rs928874 and rs1788355) on chromosome 21q22.3, were significantly associated with the 4-meter gait speed (rs928874, p = 5.61 × 10−8; rs1788355, p = 5.73 × 10−8). This association was not replicated in the inCHIANTI population. Our findings suggest that specific SNPs may be associated with a key measure of physical performance in older adults. GWASs using larger samples are needed to confirm these preliminary results to enhance our comprehension of complex age-associated phenomena.
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Affiliation(s)
| | - Bryan J Traynor
- Neuromuscular Diseases Research Section, Laboratory of Neurogenetics, National Institute on Aging, 35 Convent Drive, Room 1A-1000, Bethesda, MD, 20892, USA
| | - Anna Picca
- Center for Geriatric Medicine (CEMI), Department of Geriatrics, Neurosciences and Orthopedics, Catholic University of Sacred Heart, Rome, 00168, Italy
| | - Riccardo Calvani
- Center for Geriatric Medicine (CEMI), Department of Geriatrics, Neurosciences and Orthopedics, Catholic University of Sacred Heart, Rome, 00168, Italy
| | - Emanuele Marzetti
- Center for Geriatric Medicine (CEMI), Department of Geriatrics, Neurosciences and Orthopedics, Catholic University of Sacred Heart, Rome, 00168, Italy
| | - Dena Hernandez
- Genomics Technology Group, Laboratory of Neurogenetics, National Institute on Aging, 35 Convent Drive, Room 1A-1000, Bethesda, MD, 20892, USA
| | - Michael Nalls
- Molecular Genetics Unit, Laboratory of Neurogenetics, National Institute on Aging, 35 Convent Drive, Room 1A-1000, Bethesda, MD, 20892, USA
| | - Sampath Arepali
- Genomics Technology Group, Laboratory of Neurogenetics, National Institute on Aging, 35 Convent Drive, Room 1A-1000, Bethesda, MD, 20892, USA
| | - Luigi Ferrucci
- Longitudinal Studies Section, Clinical Research Branch, National Institute on Aging, 251 Bayview Blvd., Room BRC/04C225, Baltimore, MD, 21224, USA
| | - Francesco Landi
- Center for Geriatric Medicine (CEMI), Department of Geriatrics, Neurosciences and Orthopedics, Catholic University of Sacred Heart, Rome, 00168, Italy.
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18
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Nationwide Genomic Study in Denmark Reveals Remarkable Population Homogeneity. Genetics 2016; 204:711-722. [PMID: 27535931 DOI: 10.1534/genetics.116.189241] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2016] [Accepted: 07/30/2016] [Indexed: 02/07/2023] Open
Abstract
Denmark has played a substantial role in the history of Northern Europe. Through a nationwide scientific outreach initiative, we collected genetic and anthropometrical data from ∼800 high school students and used them to elucidate the genetic makeup of the Danish population, as well as to assess polygenic predictions of phenotypic traits in adolescents. We observed remarkable homogeneity across different geographic regions, although we could still detect weak signals of genetic structure reflecting the history of the country. Denmark presented genomic affinity with primarily neighboring countries with overall resemblance of decreasing weight from Britain, Sweden, Norway, Germany, and France. A Polish admixture signal was detected in Zealand and Funen, and our date estimates coincided with historical evidence of Wend settlements in the south of Denmark. We also observed considerably diverse demographic histories among Scandinavian countries, with Denmark having the smallest current effective population size compared to Norway and Sweden. Finally, we found that polygenic prediction of self-reported adolescent height in the population was remarkably accurate (R2 = 0.639 ± 0.015). The high homogeneity of the Danish population could render population structure a lesser concern for the upcoming large-scale gene-mapping studies in the country.
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19
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Stevenson M, Bae H, Schupf N, Andersen S, Zhang Q, Perls T, Sebastiani P. Burden of disease variants in participants of the Long Life Family Study. Aging (Albany NY) 2015; 7:123-32. [PMID: 25664523 PMCID: PMC4359694 DOI: 10.18632/aging.100724] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
Case control studies of nonagenarians and centenarians provide evidence that long-lived individuals do not differ in the rate of disease associated variants compared to population controls. These results suggest that an enrichment of novel protective variants, rather than a lack of disease associated variants, determine the genetic predisposition to exceptionally long lives. Using data from the Long Life Family Study (LLFS), we sought to replicate these findings and extend them to include a larger number of disease-specific risk alleles. To accomplish this goal, we built a genetic risk score for each of four age-related disease groups: Alzheimer's disease, cardiovascular disease and stroke, type 2 diabetes, and various cancers and compared the distribution of these scores between older participants of the LLFS, their offspring and their spouses. The analyses showed no significant differences in distribution of the genetic risk scores for cardiovascular disease and stroke, type 2 diabetes, or cancer between the groups, while participants of the LLFS appeared to carry an average 1% fewer risk alleles for Alzheimer's disease compared to spousal controls and, while the difference may not be clinically relevant, it was statistically significant. However, the statistical significance between familial longevity and the Alzheimer's disease genetic risk score was lost when a more stringent linkage disequilibrium threshold was imposed to select independent genetic variants.
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Affiliation(s)
- Meredith Stevenson
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Harold Bae
- College of Public Health and Human Sciences, Oregon State University, OR 97331, USA
| | - Nicole Schupf
- Department of Neurology, Columbia UNiversity, New York City, NY 10027, USA
| | - Stacy Andersen
- Section of Geriatrics, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA 02118, USA
| | - Qunyuan Zhang
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Thomas Perls
- Section of Geriatrics, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, MA 02118, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
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20
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Power RA, Pluess M. Heritability estimates of the Big Five personality traits based on common genetic variants. Transl Psychiatry 2015; 5:e604. [PMID: 26171985 PMCID: PMC5068715 DOI: 10.1038/tp.2015.96] [Citation(s) in RCA: 88] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/28/2015] [Accepted: 06/01/2015] [Indexed: 12/16/2022] Open
Abstract
According to twin studies, the Big Five personality traits have substantial heritable components explaining 40-60% of the variance, but identification of associated genetic variants has remained elusive. Consequently, knowledge regarding the molecular genetic architecture of personality and to what extent it is shared across the different personality traits is limited. Using genomic-relatedness-matrix residual maximum likelihood analysis (GREML), we here estimated the heritability of the Big Five personality factors (extraversion, agreeableness, conscientiousness, neuroticism and openness for experience) in a sample of 5011 European adults from 527,469 single-nucleotide polymorphisms across the genome. We tested for the heritability of each personality trait, as well as for the genetic overlap between the personality factors. We found significant and substantial heritability estimates for neuroticism (15%, s.e. = 0.08, P = 0.04) and openness (21%, s.e. = 0.08, P < 0.01), but not for extraversion, agreeableness and conscientiousness. The bivariate analyses showed that the variance explained by common variants entirely overlapped between neuroticism and openness (rG = 1.00, P < 0.001), despite low phenotypic correlation (r = - 0.09, P < 0.001), suggesting that the remaining unique heritability may be determined by rare or structural variants. As far as we are aware of, this is the first study estimating the shared and unique heritability of all Big Five personality traits using the GREML approach. Findings should be considered exploratory and suggest that detectable heritability estimates based on common variants is shared between neuroticism and openness to experiences.
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Affiliation(s)
- R A Power
- MRC Social Genetic & Developmental Psychiatry Centre, Institute of Psychiatry, Psychology & Neuroscience, King's College London, London, UK
| | - M Pluess
- Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, London, UK,Department of Biological and Experimental Psychology, School of Biological and Chemical Sciences, Queen Mary University of London, Mile End Road, London E1 4NS, UK. E-mail:
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21
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Bae H, Perls T, Steinberg M, Sebastiani P. Bayesian Polynomial Regression Models to Fit Multiple Genetic Models for Quantitative Traits. BAYESIAN ANALYSIS 2015; 10:53-74. [PMID: 26029316 PMCID: PMC4446790 DOI: 10.1214/14-ba880] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
We present a coherent Bayesian framework for selection of the most likely model from the five genetic models (genotypic, additive, dominant, co-dominant, and recessive) commonly used in genetic association studies. The approach uses a polynomial parameterization of genetic data to simultaneously fit the five models and save computations. We provide a closed-form expression of the marginal likelihood for normally distributed data, and evaluate the performance of the proposed method and existing method through simulated and real genome-wide data sets.
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Affiliation(s)
- Harold Bae
- Department of Biostatistics, Boston University School of Public Health
| | - Thomas Perls
- New England Centenarian Study, Section of Geriatrics, Department of Medicine, Boston University School of Medicine
| | - Martin Steinberg
- Center of Excellence in Sickle Cell Disease Boston Medical Center, Pediatrics, Pathology and Laboratory Medicine
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health
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22
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Kerner B. Psychiatric genetics, neurogenetics, and neurodegeneration. Front Genet 2015; 5:467. [PMID: 25642241 PMCID: PMC4294215 DOI: 10.3389/fgene.2014.00467] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2014] [Accepted: 12/18/2014] [Indexed: 12/13/2022] Open
Affiliation(s)
- Berit Kerner
- Semel Institute for Neuroscience and Human Behavior, University of California, Los Angeles Los Angeles, CA, USA
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23
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Zhu B, Chen C, Moyzis RK, Dong Q, Lin C. Educational attainment-related loci identified by GWAS are associated with select personality traits and mathematics and language abilities. PERSONALITY AND INDIVIDUAL DIFFERENCES 2015. [DOI: 10.1016/j.paid.2014.08.028] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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24
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Watkins SE, Meyer RE, Strauss RP, Aylsworth AS. Classification, epidemiology, and genetics of orofacial clefts. Clin Plast Surg 2014; 41:149-63. [PMID: 24607185 DOI: 10.1016/j.cps.2013.12.003] [Citation(s) in RCA: 146] [Impact Index Per Article: 14.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/07/2023]
Abstract
Orofacial clefts (OFCs) include a broad range of facial conditions that differ in cause and disease burden. In the published literature, there is substantial ambiguity in both terminology and classification of OFCs. This article discusses the terminology and classification of OFCs and the epidemiology of OFCs. Demographic, environmental, and genetic risk factors for OFCs are described, including suggestions for family counseling. This article enables clinicians to counsel families regarding the occurrence and recurrence of OFCs. Although much of the information is detailed, it is intended to be accessible to all health professionals for use in their clinical practices.
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Affiliation(s)
- Stephanie E Watkins
- Center for Health Promotion and Disease Prevention, University of North Carolina at Chapel Hill, 1700 Martin Luther King Jr Boulevard, Chapel Hill, NC, USA.
| | - Robert E Meyer
- Birth Defects Monitoring Program, Division of Public Health, North Carolina Department of Health and Human Services, State Center for Health Statistics, 222 North Dawson Street, Cotton Building, Raleigh, NC 27603, USA
| | - Ronald P Strauss
- UNC Center for AIDS Research, UNC School of Dentistry, UNC School of Medicine, University of North Carolina at Chapel Hill, 104 South Building, CB# 3000, Chapel Hill, NC 27599-3000, USA
| | - Arthur S Aylsworth
- Departments of Pediatrics and Genetics, University of North Carolina at Chapel Hill, CB# 7487, UNC Campus, Chapel Hill, NC 27599-7487, USA
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25
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Tian XL, Li Y. Endothelial cell senescence and age-related vascular diseases. J Genet Genomics 2014; 41:485-95. [PMID: 25269674 DOI: 10.1016/j.jgg.2014.08.001] [Citation(s) in RCA: 69] [Impact Index Per Article: 6.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2014] [Revised: 07/31/2014] [Accepted: 08/06/2014] [Indexed: 10/24/2022]
Abstract
Advanced age is an independent risk factor for ageing-related complex diseases, such as coronary artery disease, stroke, and hypertension, which are common but life threatening and related to the ageing-associated vascular dysfunction. On the other hand, patients with progeria syndromes suffer from serious atherosclerosis, suggesting that the impaired vascular functions may be critical to organismal ageing, or vice versa. However, it remains largely unknown how vascular cells, particularly endothelial cell, become senescent and how the senescence impairs the vascular functions and contributes to the age-related vascular diseases over time. Here, we review the recent progress on the characteristics of vascular ageing and endothelial cell senescence in vitro and in vivo, evaluate how genetic and environmental factors as well as autophagy and stem cell influence endothelial cell senescence and how the senescence contributes to the age-related vascular phenotypes, such as atherosclerosis and increased vascular stiffness, and explore the possibility whether we can delay the age-related vascular diseases through the control of vascular ageing.
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Affiliation(s)
- Xiao-Li Tian
- Department of Human Population Genetics and Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine (IMM), Peking University, Beijing 100871, China.
| | - Yang Li
- Department of Human Population Genetics and Beijing Key Laboratory of Cardiometabolic Molecular Medicine, Institute of Molecular Medicine (IMM), Peking University, Beijing 100871, China
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26
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Sebastiani P, Bae H, Sun FX, Andersen SL, Daw EW, Malovini A, Kojima T, Hirose N, Schupf N, Puca A, Perls TT. Meta‐analysis of genetic variants associated with human exceptional longevity. Aging (Albany NY) 2014; 5:653-61. [PMID: 24244950 PMCID: PMC3808698 DOI: 10.18632/aging.100594] [Citation(s) in RCA: 71] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
Abstract
Despite evidence from family studies that there is a strong genetic influence upon exceptional longevity, relatively few genetic variants have been associated with this trait. One reason could be that many genes individually have such weak effects that they cannot meet standard thresholds of genome wide significance, but as a group in specific combinations of genetic variations, they can have a strong influence. Previously we reported that such genetic signatures of 281 genetic markers associated with about 130 genes can do a relatively good job of differentiating centenarians from non-centenarians particularly if the centenarians are 106 years and older. This would support our hypothesis that the genetic influence upon exceptional longevity increases with older and older (and rarer) ages. We investigated this list of markers using similar genetic data from 5 studies of centenarians from the USA, Europe and Japan. The results from the meta-analysis show that many of these variants are associated with survival to these extreme ages in other studies. Since many centenarians compress morbidity and disability towards the end of their lives, these results could point to biological pathways and therefore new therapeutics to increase years of healthy lives in the general population.
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27
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Brooks-Wilson AR. Genetics of healthy aging and longevity. Hum Genet 2013; 132:1323-38. [PMID: 23925498 PMCID: PMC3898394 DOI: 10.1007/s00439-013-1342-z] [Citation(s) in RCA: 185] [Impact Index Per Article: 16.8] [Reference Citation Analysis] [Abstract] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2012] [Accepted: 07/15/2013] [Indexed: 12/17/2022]
Abstract
Longevity and healthy aging are among the most complex phenotypes studied to date. The heritability of age at death in adulthood is approximately 25 %. Studies of exceptionally long-lived individuals show that heritability is greatest at the oldest ages. Linkage studies of exceptionally long-lived families now support a longevity locus on chromosome 3; other putative longevity loci differ between studies. Candidate gene studies have identified variants at APOE and FOXO3A associated with longevity; other genes show inconsistent results. Genome-wide association scans (GWAS) of centenarians vs. younger controls reveal only APOE as achieving genome-wide significance (GWS); however, analyses of combinations of SNPs or genes represented among associations that do not reach GWS have identified pathways and signatures that converge upon genes and biological processes related to aging. The impact of these SNPs, which may exert joint effects, may be obscured by gene-environment interactions or inter-ethnic differences. GWAS and whole genome sequencing data both show that the risk alleles defined by GWAS of common complex diseases are, perhaps surprisingly, found in long-lived individuals, who may tolerate them by means of protective genetic factors. Such protective factors may ‘buffer’ the effects of specific risk alleles. Rare alleles are also likely to contribute to healthy aging and longevity. Epigenetics is quickly emerging as a critical aspect of aging and longevity. Centenarians delay age-related methylation changes, and they can pass this methylation preservation ability on to their offspring. Non-genetic factors, particularly lifestyle, clearly affect the development of age-related diseases and affect health and lifespan in the general population. To fully understand the desirable phenotypes of healthy aging and longevity, it will be necessary to examine whole genome data from large numbers of healthy long-lived individuals to look simultaneously at both common and rare alleles, with impeccable control for population stratification and consideration of non-genetic factors such as environment.
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Affiliation(s)
- Angela R Brooks-Wilson
- Canada's Michael Smith Genome Sciences Centre, BC Cancer Agency, 675 West 10th Avenue, Vancouver, BC, V5Z 1L3, Canada,
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