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Don J, Schork AJ, Glusman G, Rappaport N, Cummings SR, Duggan D, Raju A, Hellberg KLG, Gunn S, Monti S, Perls T, Lapidus J, Goetz LH, Sebastiani P, Schork NJ. The relationship between 11 different polygenic longevity scores, parental lifespan, and disease diagnosis in the UK Biobank. GeroScience 2024; 46:3911-3927. [PMID: 38451433 PMCID: PMC11226417 DOI: 10.1007/s11357-024-01107-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2023] [Accepted: 02/21/2024] [Indexed: 03/08/2024] Open
Abstract
Large-scale genome-wide association studies (GWAS) strongly suggest that most traits and diseases have a polygenic component. This observation has motivated the development of disease-specific "polygenic scores (PGS)" that are weighted sums of the effects of disease-associated variants identified from GWAS that correlate with an individual's likelihood of expressing a specific phenotype. Although most GWAS have been pursued on disease traits, leading to the creation of refined "Polygenic Risk Scores" (PRS) that quantify risk to diseases, many GWAS have also been pursued on extreme human longevity, general fitness, health span, and other health-positive traits. These GWAS have discovered many genetic variants seemingly protective from disease and are often different from disease-associated variants (i.e., they are not just alternative alleles at disease-associated loci) and suggest that many health-positive traits also have a polygenic basis. This observation has led to an interest in "polygenic longevity scores (PLS)" that quantify the "risk" or genetic predisposition of an individual towards health. We derived 11 different PLS from 4 different available GWAS on lifespan and then investigated the properties of these PLS using data from the UK Biobank (UKB). Tests of association between the PLS and population structure, parental lifespan, and several cancerous and non-cancerous diseases, including death from COVID-19, were performed. Based on the results of our analyses, we argue that PLS are made up of variants not only robustly associated with parental lifespan, but that also contribute to the genetic architecture of disease susceptibility, morbidity, and mortality.
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Affiliation(s)
- Janith Don
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Andrew J Schork
- The Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- GLOBE Institute, Copenhagen University, Copenhagen, Denmark
| | | | | | - Steve R Cummings
- San Francisco Coordinating Center, California Pacific Medical Center Research Institute, San Francisco, CA, USA
| | - David Duggan
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Anish Raju
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
| | - Kajsa-Lotta Georgii Hellberg
- The Institute of Biological Psychiatry, Copenhagen University Hospital, Copenhagen, Denmark
- GLOBE Institute, Copenhagen University, Copenhagen, Denmark
| | - Sophia Gunn
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Stefano Monti
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Thomas Perls
- Department of Medicine, Section of Geriatrics, Boston University, Boston, MA, USA
| | - Jodi Lapidus
- Department of Biostatistics, Oregon Health & Science University, Portland, OR, USA
| | - Laura H Goetz
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA
- Veterans Affairs Loma Linda Health Care, Loma Linda, CA, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, USA
- Tufts University School of Medicine and Data Intensive Study Center, Boston, MA, USA
| | - Nicholas J Schork
- Translational Genomics Research Institute (TGen), Phoenix, AZ, USA.
- The City of Hope National Medical Center, Duarte, CA, USA.
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Félix J, Martínez de Toda I, Díaz-Del Cerro E, González-Sánchez M, De la Fuente M. Frailty and biological age. Which best describes our aging and longevity? Mol Aspects Med 2024; 98:101291. [PMID: 38954948 DOI: 10.1016/j.mam.2024.101291] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Revised: 05/01/2024] [Accepted: 06/26/2024] [Indexed: 07/04/2024]
Abstract
Frailty and Biological Age are two closely related concepts; however, frailty is a multisystem geriatric syndrome that applies to elderly subjects, whereas biological age is a gerontologic way to describe the rate of aging of each individual, which can be used from the beginning of the aging process, in adulthood. If frailty reaches less consensus on the definition, it is a term much more widely used than this of biological age, which shows a clearer definition but is scarcely employed in social and medical fields. In this review, we suggest that this Biological Age is the best to describe how we are aging and determine our longevity, and several examples support our proposal.
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Affiliation(s)
- Judith Félix
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Irene Martínez de Toda
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Estefanía Díaz-Del Cerro
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica González-Sánchez
- Department of Genetics, Physiology, and Microbiology (Unit of Genetics), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
| | - Mónica De la Fuente
- Department of Genetics, Physiology, and Microbiology (Unit of Animal Physiology), Faculty of Biological Sciences, Complutense University of Madrid, 28040 Madrid, Spain; Institute of Investigation Hospital 12 Octubre (imas12), 28041 Madrid, Spain.
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3
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Smulders L, Deelen J. Genetics of human longevity: From variants to genes to pathways. J Intern Med 2024; 295:416-435. [PMID: 37941149 DOI: 10.1111/joim.13740] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/10/2023]
Abstract
The current increase in lifespan without an equivalent increase in healthspan poses a grave challenge to the healthcare system and a severe burden on society. However, some individuals seem to be able to live a long and healthy life without the occurrence of major debilitating chronic diseases, and part of this trait seems to be hidden in their genome. In this review, we discuss the findings from studies on the genetic component of human longevity and the main challenges accompanying these studies. We subsequently focus on results from genetic studies in model organisms and comparative genomic approaches to highlight the most important conserved longevity-associated pathways. By combining the results from studies using these different approaches, we conclude that only five main pathways have been consistently linked to longevity, namely (1) insulin/insulin-like growth factor 1 signalling, (2) DNA-damage response and repair, (3) immune function, (4) cholesterol metabolism and (5) telomere maintenance. As our current approaches to study the relevance of these pathways in humans are limited, we suggest that future studies on the genetics of human longevity should focus on the identification and functional characterization of rare genetic variants in genes involved in these pathways.
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Affiliation(s)
- Larissa Smulders
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
| | - Joris Deelen
- Max Planck Institute for Biology of Ageing, Cologne, Germany
- Cologne Excellence Cluster on Cellular Stress Responses in Ageing-Associated Diseases (CECAD), University of Cologne, Cologne, Germany
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4
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Wu Y, Zhang CY, Liu X, Wang L, Li M, Li Y, Xiao X. Shared genetic architecture and causal relationship between sleep behaviors and lifespan. Transl Psychiatry 2024; 14:108. [PMID: 38388528 PMCID: PMC10883970 DOI: 10.1038/s41398-024-02826-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 02/07/2024] [Accepted: 02/13/2024] [Indexed: 02/24/2024] Open
Abstract
Poor sleep health is associated with a wide array of increased risk for cardiovascular, metabolic and mental health problems as well as all-cause mortality in observational studies, suggesting potential links between sleep health and lifespan. However, it has yet to be determined whether sleep health is genetically or/and causally associated with lifespan. In this study, we firstly studied the genome-wide genetic association between four sleep behaviors (short sleep duration, long sleep duration, insomnia, and sleep chronotype) and lifespan using GWAS summary statistics, and both sleep duration time and insomnia were negatively correlated with lifespan. Then, two-sample Mendelian randomization (MR) and multivariable MR analyses were applied to explore the causal effects between sleep behaviors and lifespan. We found that genetically predicted short sleep duration was causally and negatively associated with lifespan in univariable and multivariable MR analyses, and this effect was partially mediated by coronary artery disease (CAD), type 2 diabetes (T2D) and depression. In contrast, we found that insomnia had no causal effects on lifespan. Our results further confirmed the negative effects of short sleep duration on lifespan and suggested that extension of sleep may benefit the physical health of individuals with sleep loss. Further attention should be given to such public health issues.
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Affiliation(s)
- Yong Wu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China
| | - Chu-Yi Zhang
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Xiaolan Liu
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China
| | - Lu Wang
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Ming Li
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China
| | - Yi Li
- Research Center for Mental Health and Neuroscience, Wuhan Mental Health Center, Wuhan, Hubei, China.
- Affiliated Wuhan Mental Health Center, Jianghan University, Wuhan, Hubei, China.
- Research Center for Psychological and Health Sciences, China University of Geosciences, Wuhan, Hubei, China.
| | - Xiao Xiao
- Yunnan Key Laboratory of Animal Models and Human Disease Mechanisms, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China.
- Kunming College of Life Science, University of Chinese Academy of Sciences, Kunming, Yunnan, China.
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Accardi G, Aiello A, Aprile S, Calabrò A, Caldarella R, Caruso C, Ciaccio M, Dieli F, Ligotti ME, Meraviglia S, Candore G. The Phenotypic Characterization of the Oldest Italian Man from December 28, 2020, to September 23, 2021, A.T., Strengthens the Idea That the Immune System can Play a Key Role in the Attainment of Extreme Longevity. J Clin Med 2023; 12:7591. [PMID: 38137660 PMCID: PMC10744028 DOI: 10.3390/jcm12247591] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2023] [Revised: 11/29/2023] [Accepted: 12/07/2023] [Indexed: 12/24/2023] Open
Abstract
In this paper, we present demographic, clinical, anamnestic, cognitive, and functional data, as well as haematological, haematochemical, immunological, and genetic parameters of an exceptional individual: A.T., a semi-supercentenarian who held the title of the oldest living Italian male centenarian from 28 December 2020, to 23 September 2021. The purpose of this study is to provide fresh insights into extreme phenotypes, with a particular focus on immune-inflammatory parameters. To the best of our knowledge, this study represents the first phenotypic investigation of a semi-supercentenarian, illustrating both INFLA-score, a metric designed to assess the cumulative impact of inflammatory markers and indicators of age-related immune phenotype (ARIP), recognized as significant gauges of biological ageing. The aim of this study was, indeed, to advance our understanding of the role of immune-inflammatory responses in achieving extreme longevity. The results of laboratory tests, as well as clinical history and interview data, when compared to the results of our recent study on Sicilian centenarians, demonstrate an excellent state of health considering his age. Consistent with previous studies, we observed increased IL-6 inflammatory markers and INFLA score in A.T. More interestingly, the semi-supercentenarian showed values of ARIP indicators such as naïve CD4+ cells, CD4+/CD8+ ratio, and CD4+TN/TM ratio in the range of young adult individuals, suggesting that his immune system's biological age was younger than the chronological one. The results support the notion that the immune system can play a role in promoting extreme longevity. However, this does not rule out the involvement of other body systems or organs in achieving extreme longevity.
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Affiliation(s)
- Giulia Accardi
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
| | - Anna Aiello
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
| | - Stefano Aprile
- Unit of Transfusion Medicine, San Giovanni di Dio Hospital, 92100 Agrigento, Italy;
| | - Anna Calabrò
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
| | - Rosalia Caldarella
- Department of Laboratory medicine, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (R.C.); (M.C.)
| | - Calogero Caruso
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
| | - Marcello Ciaccio
- Department of Laboratory medicine, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (R.C.); (M.C.)
- Section of Clinical Biochemistry, Clinical Molecular Medicine and Clinical Laboratory Medicine, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy
| | - Francesco Dieli
- Central Laboratory of Advanced Diagnosis and Biomedical Research, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (F.D.); (S.M.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy
| | - Mattia Emanuela Ligotti
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
| | - Serena Meraviglia
- Central Laboratory of Advanced Diagnosis and Biomedical Research, University Hospital “P. Giaccone”, 90127 Palermo, Italy; (F.D.); (S.M.)
- Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy
| | - Giuseppina Candore
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neurosciences and Advanced Diagnostics, University of Palermo, 90133 Palermo, Italy; (G.A.); (A.A.); (A.C.); (M.E.L.); (G.C.)
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6
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Milman S, Barzilai N. Discovering Biological Mechanisms of Exceptional Human Health Span and Life Span. Cold Spring Harb Perspect Med 2023; 13:a041204. [PMID: 37137499 PMCID: PMC10513160 DOI: 10.1101/cshperspect.a041204] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Humans age at different rates and families with exceptional longevity provide an opportunity to understand why some people age slower than others. Unique features exhibited by centenarians include a family history of extended life span, compression of morbidity with resultant extension of health span, and longevity-associated biomarker profiles. These biomarkers, including low-circulating insulin-like growth factor 1 (IGF-1) and elevated high-density lipoprotein (HDL) cholesterol levels, are associated with functional genotypes that are enriched in centenarians, suggesting that they may be causative for longevity. While not all genetic discoveries from centenarians have been validated, in part due to exceptional life span being a rare phenotype in the general population, the APOE2 and FOXO3a genotypes have been confirmed in a number of populations with exceptional longevity. However, life span is now recognized as a complex trait and genetic research methods to study longevity are rapidly extending beyond classical Mendelian genetics to polygenic inheritance methodologies. Moreover, newer approaches are suggesting that pathways that have been recognized for decades to control life span in animals may also regulate life span in humans. These discoveries led to strategic development of therapeutics that may delay aging and prolong health span.
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Affiliation(s)
- Sofiya Milman
- Institute for Aging Research, Department of Medicine, Divisions of Endocrinology and Geriatrics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York 10461, USA
| | - Nir Barzilai
- Institute for Aging Research, Department of Medicine, Divisions of Endocrinology and Geriatrics, Department of Genetics, Albert Einstein College of Medicine, Bronx, New York 10461, USA
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Caruso C, Puca AA. Special Issue "Centenarians-A Model to Study the Molecular Basis of Lifespan and Healthspan 2.0". Int J Mol Sci 2023; 24:13180. [PMID: 37685989 PMCID: PMC10488218 DOI: 10.3390/ijms241713180] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Accepted: 08/23/2023] [Indexed: 09/10/2023] Open
Abstract
The global population is experiencing an increase in ageing and life expectancy [...].
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Affiliation(s)
- Calogero Caruso
- Laboratory of Immunopathology and Immunosenescence, Department of Biomedicine, Neuroscience and Advanced Diagnostics, University of Palermo, 90134 Palermo, Italy
| | - Annibale Alessandro Puca
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84081 Fisciano, Italy;
- Cardiovascular Research Unit, IRCCS MultiMedica, 20138 Milan, Italy
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8
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Akiyama M, Sakaue S, Takahashi A, Ishigaki K, Hirata M, Matsuda K, Momozawa Y, Okada Y, Ninomiya T, Terao C, Murakami Y, Kubo M, Kamatani Y. Genome-wide association study reveals BET1L associated with survival time in the 137,693 Japanese individuals. Commun Biol 2023; 6:143. [PMID: 36737517 PMCID: PMC9898503 DOI: 10.1038/s42003-023-04491-0] [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: 04/09/2022] [Accepted: 01/17/2023] [Indexed: 02/05/2023] Open
Abstract
Human lifespan is reported to be heritable. Although previous genome-wide association studies (GWASs) have identified several loci, a limited number of studies have assessed the genetic associations with the real survival information on the participants. We conducted a GWAS to identify loci associated with survival time in the Japanese individuals participated in the BioBank Japan Project by carrying out sex-stratified GWASs involving 78,029 males and 59,664 females. Of them, 31,324 (22.7%) died during the mean follow-up period of 7.44 years. We found a novel locus associated with survival (BET1L; P = 5.89 × 10-9). By integrating with eQTL data, we detected a significant overlap with eQTL of BET1L in skeletal muscle. A gene-set enrichment analysis showed that genes related to the BCAR1 protein-protein interaction subnetwork influence survival time (P = 1.54 × 10-7). These findings offer the candidate genes and biological mechanisms associated with human lifespan.
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Affiliation(s)
- Masato Akiyama
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.177174.30000 0001 2242 4849Department of Ocular Pathology and Imaging Science, Graduate School of Medical Sciences, Kyushu University, Fukuoka, 812-8582 Japan
| | - Saori Sakaue
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.136593.b0000 0004 0373 3971Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871 Japan
| | - Atsushi Takahashi
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.410796.d0000 0004 0378 8307Department of Genomic Medicine, Research Institute, National Cerebral and Cardiovascular Center, Osaka, 564-8565 Japan
| | - Kazuyoshi Ishigaki
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Makoto Hirata
- grid.26999.3d0000 0001 2151 536XLaboratory of Genome Technology, Human Genome Center, Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Koichi Matsuda
- grid.26999.3d0000 0001 2151 536XLaboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate school of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Yukihide Momozawa
- grid.509459.40000 0004 0472 0267Laboratory for Genotyping Development, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yukinori Okada
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.136593.b0000 0004 0373 3971Department of Statistical Genetics, Osaka University Graduate School of Medicine, Suita, 565-0871 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Systems Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Toshiharu Ninomiya
- grid.177174.30000 0001 2242 4849Department of Epidemiology and Public Health, Graduate School of Medical Sciences, Fukuoka, 812-8582 Japan
| | | | - Chikashi Terao
- grid.509459.40000 0004 0472 0267Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan ,grid.509459.40000 0004 0472 0267Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yoshinori Murakami
- grid.26999.3d0000 0001 2151 536XDivision of Molecular Pathology, The Institute of Medical Science, The University of Tokyo, Tokyo, 108-8639 Japan
| | - Michiaki Kubo
- grid.509459.40000 0004 0472 0267RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045 Japan
| | - Yoichiro Kamatani
- Laboratory for Statistical Analysis, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory for Statistical and Translational Genetics, RIKEN Center for Integrative Medical Sciences, Yokohama, 230-0045, Japan. .,Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, 108-8639, Japan.
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Olivieri F, Prattichizzo F, Lattanzio F, Bonfigli AR, Spazzafumo L. Antifragility and antiinflammaging: Can they play a role for a healthy longevity? Ageing Res Rev 2023; 84:101836. [PMID: 36574863 DOI: 10.1016/j.arr.2022.101836] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2022] [Revised: 12/14/2022] [Accepted: 12/21/2022] [Indexed: 12/25/2022]
Abstract
One of the most exciting challenges of the research on aging is to explain how the environmental factors interact with the genetic background to modulate the chances to reach the extreme limit of human life in healthy conditions. The complex epigenetic mechanisms can explain both the interaction between DNA and environmental factors, and the long-distance persistence of lifestyle effects, due to the so called "epigenetic memory". One of the most extensively investigated theories on aging focuses on the inflammatory responses, suggesting that the age-related progression of low-grade and therefore for long time subclinical, chronic, systemic, inflammatory process, named "inflammaging", could be the most relevant risk factor for the development and progression of the most common age-related diseases and ultimately of death. The results of many studies on long-lived people, especially on centenarians, suggested that healthy old people can cope with inflammaging upregulating the antiinflammaging responses. Overall, a genetic make-up coding for a strong antiinflammaging response and an age-related ability to remodel key metabolic pathways to cope with a plethora of antigens and stressors seem to be the best ways for reach the extreme limit of human lifespan in health status. In this scenario, we wondered if the antifragility concept, recently developed in the framework of business and risk analysis, could add some information to disentangle the heterogeneous nature of the aging process in human. The antifragility is the property of the complex systems to increase their performances because of high stress. Based on this theory we were wondering if some subjects could be able to modulate faster than others their epigenome to cope with a plethora of stressors during life, probably modulating the inflammatory and anti-inflammatory responses. In this framework, antifragility could share some common mechanisms with anti-inflammaging, modulating the ability to restrain the inflammatory responses, so that antifragility and antiinflammaging could be viewed as different pieces of the same puzzle, both impinging upon the chances to travel along the healthy aging trajectory.
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Affiliation(s)
- Fabiola Olivieri
- Department of Clinical and Molecular Sciences, DISCLIMO, Università Politecnica Delle Marche, Ancona, Italy; Clinica di Medicina di Laboratorio e di Precisione, IRCCS INRCA, Ancona, Italy.
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10
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Revelas M, Thalamuthu A, Zettergren A, Oldmeadow C, Najar J, Seidu NM, Armstrong NJ, Riveros C, Kwok JB, Schofield PR, Trollor JN, Waern M, Wright MJ, Zetterberg H, Ames D, Belnnow K, Brodaty H, Scott RJ, Skoog I, Attia JR, Sachdev PS, Mather KA. High polygenic risk score for exceptional longevity is associated with a healthy metabolic profile. GeroScience 2023; 45:399-413. [PMID: 35972662 PMCID: PMC9886704 DOI: 10.1007/s11357-022-00643-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2022] [Accepted: 08/08/2022] [Indexed: 02/03/2023] Open
Abstract
Healthy metabolic measures in humans are associated with longevity. Dysregulation leads to metabolic syndrome (MetS) and negative health outcomes. Recent exceptional longevity (EL) genome wide association studies have facilitated estimation of an individual's polygenic risk score (PRS) for EL. We tested the hypothesis that individuals with high ELPRS have a low prevalence of MetS. Participants were from five cohorts of middle-aged to older adults. The primary analyses were performed in the UK Biobank (UKBB) (n = 407,800, 40-69 years). Replication analyses were undertaken using three Australian studies: Hunter Community Study (n = 2122, 55-85 years), Older Australian Twins Study (n = 539, 65-90 years) and Sydney Memory and Ageing Study (n = 925, 70-90 years), as well as the Swedish Gothenburg H70 Birth Cohort Studies (n = 2273, 70-93 years). MetS was defined using established criteria. Regressions and meta-analyses were performed with the ELPRS and MetS and its components. Generally, MetS prevalence (22-30%) was higher in the older cohorts. In the UKBB, high EL polygenic risk was associated with lower MetS prevalence (OR = 0.94, p = 1.84 × 10-42) and its components (p < 2.30 × 10-8). Meta-analyses of the replication cohorts showed nominal associations with MetS (p = 0.028) and 3 MetS components (p < 0.05). This work suggests individuals with a high polygenic risk for EL have a healthy metabolic profile promoting longevity.
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Affiliation(s)
- Mary Revelas
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia.
- Neuroscience Research Australia, Sydney, NSW, Australia.
| | - Anbupalam Thalamuthu
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
| | - Anna Zettergren
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | | | - Jenna Najar
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - Nazib M Seidu
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
| | - Nicola J Armstrong
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Mathematics and Statistics, Curtin University, Perth, Australia
| | - Carlos Riveros
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
| | - John B Kwok
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Medical Sciences, UNSW, Sydney, Australia
| | - Peter R Schofield
- Neuroscience Research Australia, Sydney, NSW, Australia
- School of Medical Sciences, UNSW, Sydney, Australia
| | - Julian N Trollor
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Department of Developmental Disability Neuropsychiatry, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
| | - Margda Waern
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychosis Clinic, Gothenburg, Sweden
| | - Margaret J Wright
- Queensland Brain Institute, University of Queensland, Brisbane, Australia
- Centre for Advanced Imaging, University of Queensland, Brisbane, Australia
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, UCL Institute of Neurology, London, UK
- UK Dementia Research Institute at UCL, London, UK
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Hong Kong Centre for Neurodegenerative Diseases, Hong Kong, China
| | - David Ames
- University of Melbourne Academic Unit for Psychiatry of Old Age, St George's Hospital, Kew, VIC, Australia
- National Ageing Research Institute, Parkville Victoria, Australia
| | - Kaj Belnnow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Henry Brodaty
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Dementia Centre for Research Collaboration, UNSW, Sydney, Australia
| | - Rodney J Scott
- Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia
- Pathology North, John Hunter Hospital, Newcastle, NSW, Australia
| | - Ingmar Skoog
- Neuropsychiatric Epidemiology Unit, Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, the Sahlgrenska Academy, Centre for Ageing and Health (AGECAP) at the University of Gothenburg, Gothenburg, Sweden
- Region Västra Götaland, Sahlgrenska University Hospital, Psychiatry, Cognition and Old Age Psychiatry Clinic, Gothenburg, Sweden
| | - John R Attia
- Hunter Medical Research Institute, Newcastle, NSW, Australia
- Faculty of Health and Medicine, University of Newcastle, Callaghan, NSW, Australia
- Pathology North, John Hunter Hospital, Newcastle, NSW, Australia
| | - Perminder S Sachdev
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Neuropsychiatric Institute, Prince of Wales Hospital, Randwick, NSW, Australia
| | - Karen A Mather
- Centre for Healthy Brain Ageing, School of Psychiatry, UNSW Medicine & Health, UNSW, Sydney, Australia
- Neuroscience Research Australia, Sydney, NSW, Australia
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11
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Kunizheva SS, Volobaev VP, Plotnikova MY, Kupriyanova DA, Kuznetsova IL, Tyazhelova TV, Rogaev EI. Current Trends and Approaches to the Search for Genetic Determinants of Aging and Longevity. RUSS J GENET+ 2022; 58:1427-1443. [PMID: 36590179 PMCID: PMC9794410 DOI: 10.1134/s1022795422120067] [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: 01/20/2022] [Revised: 07/06/2022] [Accepted: 07/07/2022] [Indexed: 12/29/2022]
Abstract
Aging is a natural process of extinction of the body and the main aspect that determines the life expectancy for individuals who have survived to the post-reproductive period. The process of aging is accompanied by certain physiological, immune, and metabolic changes in the body, as well as the development of age-related diseases. The contribution of genetic factors to human life expectancy is estimated at about 25-30%. Despite the success in identifying genes and metabolic pathways that may be involved in the life extension process in model organisms, the key question remains to what extent these data can be extrapolated to humans, for example, because of the complexity of its biological and sociocultural systems, as well as possible species differences in life expectancy and causes of mortality. New molecular genetic methods have significantly expanded the possibilities for searching for genetic factors of human life expectancy and identifying metabolic pathways of aging, the interaction of genes and transcription factors, the regulation of gene expression at the level of transcription, and epigenetic modifications. The review presents the latest research and current strategies for studying the genetic basis of human aging and longevity: the study of individual candidate genes in genetic population studies, variations identified by the GWAS method, immunogenetic differences in aging, and genomic studies to identify factors of "healthy aging." Understanding the mechanisms of the interaction between factors affecting the life expectancy and the possibility of their regulation can become the basis for developing comprehensive measures to achieve healthy longevity. Supplementary Information The online version contains supplementary material available at 10.1134/S1022795422120067.
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Affiliation(s)
- S. S. Kunizheva
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - V. P. Volobaev
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - M. Yu. Plotnikova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
| | - D. A. Kupriyanova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
| | - I. L. Kuznetsova
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - T. V. Tyazhelova
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
| | - E. I. Rogaev
- Center for Genetics and Life Sciences, Sirius University of Science and Technology, 354340 Sochi, Russia
- Moscow State University, 119234 Moscow, Russia
- Vavilov Institute of General Genetics, Russian Academy of Sciences, 119991 Moscow, Russia
- University of Massachusetts Chan Medical School, 01545 Shrewsbury, MA United States
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12
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Bae H, Gurinovich A, Karagiannis TT, Song Z, Leshchyk A, Li M, Andersen SL, Arbeev K, Yashin A, Zmuda J, An P, Feitosa M, Giuliani C, Franceschi C, Garagnani P, Mengel-From J, Atzmon G, Barzilai N, Puca A, Schork NJ, Perls TT, Sebastiani P. A Genome-Wide Association Study of 2304 Extreme Longevity Cases Identifies Novel Longevity Variants. Int J Mol Sci 2022; 24:ijms24010116. [PMID: 36613555 PMCID: PMC9820206 DOI: 10.3390/ijms24010116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2022] [Revised: 12/08/2022] [Accepted: 12/15/2022] [Indexed: 12/24/2022] Open
Abstract
We performed a genome-wide association study (GWAS) of human extreme longevity (EL), defined as surviving past the 99th survival percentile, by aggregating data from four centenarian studies. The combined data included 2304 EL cases and 5879 controls. The analysis identified a locus in CDKN2B-AS1 (rs6475609, p = 7.13 × 10-8) that almost reached genome-wide significance and four additional loci that were suggestively significant. Among these, a novel rare variant (rs145265196) on chromosome 11 had much higher longevity allele frequencies in cases of Ashkenazi Jewish and Southern Italian ancestry compared to cases of other European ancestries. We also correlated EL-associated SNPs with serum proteins to link our findings to potential biological mechanisms that may be related to EL and are under genetic regulation. The findings from the proteomic analyses suggested that longevity-promoting alleles of significant genetic variants either provided EL cases with more youthful molecular profiles compared to controls or provided some form of protection from other illnesses, such as Alzheimer's disease, and disease progressions.
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Affiliation(s)
- Harold Bae
- Biostatistics Program, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR 97331, USA
- Correspondence:
| | - Anastasia Gurinovich
- Center for Quantitative Methods and Data Science, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA 02111, USA
| | - Tanya T. Karagiannis
- Center for Quantitative Methods and Data Science, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA 02111, USA
| | - Zeyuan Song
- Department of Biostatistics, Boston University School of Public Health, Boston, MA 02118, USA
| | - Anastasia Leshchyk
- Division of Computational Biomedicine, Boston University, Boston, MA 02215, USA
| | - Mengze Li
- Division of Computational Biomedicine, Boston University, Boston, MA 02215, USA
| | - Stacy L. Andersen
- Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02215, USA
| | - Konstantin Arbeev
- Social Science Research Institute, Duke University, Durham, NC 27708, USA
| | - Anatoliy Yashin
- Social Science Research Institute, Duke University, Durham, NC 27708, USA
| | - Joseph Zmuda
- School of Public Health, University of Pittsburgh, Pittsburgh, PA 15260, USA
| | - Ping An
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Mary Feitosa
- Department of Genetics, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Cristina Giuliani
- Department of Biological, Geological and Environmental Sciences, University of Bologna, 40126 Bologna, Italy
| | - Claudio Franceschi
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40126 Bologna, Italy
- Department of Applied Mathematics and Laboratory of Systems Medicine of Aging, Lobachevsky University, 603950 Nizhny Novgorod, Russia
| | - Paolo Garagnani
- Department of Experimental, Diagnostic and Specialty Medicine, University of Bologna, 40126 Bologna, Italy
| | - Jonas Mengel-From
- Department of Public Health, University of Southern Denmark, 5230 Odense, Denmark
| | - Gil Atzmon
- Faculty of Natural Sciences, University of Haifa, Haifa 3498838, Israel
- Department of Genetics and Medicine, Albert Einstein College of Medicine, Bronx, NY 10451, USA
| | - Nir Barzilai
- Department of Genetics and Medicine, Albert Einstein College of Medicine, Bronx, NY 10451, USA
| | - Annibale Puca
- Department of Medicine, Surgery and Dentistry “Scuola Medica Salernitana”, University of Salerno, 84084 Fisciano, Italy
- Cardiovascular Research Unit, IRCCS MultiMedica, 20099 Milan, Italy
| | - Nicholas J. Schork
- Quantitative Medicine & Systems Biology Division, Translational Genomics Research Institute, Phoenix, AZ 85004, USA
| | - Thomas T. Perls
- Chobanian & Avedisian School of Medicine, Boston University, Boston, MA 02215, USA
| | - Paola Sebastiani
- Center for Quantitative Methods and Data Science, Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA 02111, USA
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13
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Gurinovich A, Li M, Leshchyk A, Bae H, Song Z, Arbeev KG, Nygaard M, Feitosa MF, Perls TT, Sebastiani P. Evaluation of GENESIS, SAIGE, REGENIE and fastGWA-GLMM for genome-wide association studies of binary traits in correlated data. Front Genet 2022; 13:897210. [PMID: 36212134 PMCID: PMC9544087 DOI: 10.3389/fgene.2022.897210] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2022] [Accepted: 08/08/2022] [Indexed: 11/28/2022] Open
Abstract
Performing a genome-wide association study (GWAS) with a binary phenotype using family data is a challenging task. Using linear mixed effects models is typically unsuitable for binary traits, and numerical approximations of the likelihood function may not work well with rare genetic variants with small counts. Additionally, imbalance in the case-control ratios poses challenges as traditional statistical methods such as the Score test or Wald test perform poorly in this setting. In the last couple of years, several methods have been proposed to better approximate the likelihood function of a mixed effects logistic regression model that uses Saddle Point Approximation (SPA). SPA adjustment has recently been implemented in multiple software, including GENESIS, SAIGE, REGENIE and fastGWA-GLMM: four increasingly popular tools to perform GWAS of binary traits. We compare Score and SPA tests using real family data to evaluate computational efficiency and the agreement of the results. Additionally, we compare various ways to adjust for family relatedness, such as sparse and full genetic relationship matrices (GRM) and polygenic effect estimates. We use the New England Centenarian Study imputed genotype data and the Long Life Family Study whole-genome sequencing data and the binary phenotype of human extreme longevity to compare the agreement of the results and tools’ computational performance. The evaluation suggests that REGENIE might not be a good choice when analyzing correlated data of a small size. fastGWA-GLMM is the most computationally efficient compared to the other three tools, but it appears to be overly conservative when applied to family-based data. GENESIS, SAIGE and fastGWA-GLMM produced similar, although not identical, results, with SPA adjustment performing better than Score tests. Our evaluation also demonstrates the importance of adjusting by full GRM in highly correlated datasets when using GENESIS or SAIGE.
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Affiliation(s)
- Anastasia Gurinovich
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States
- *Correspondence: Anastasia Gurinovich,
| | - Mengze Li
- Bioinformatics Program, Boston University, Boston, MA, United States
| | | | - Harold Bae
- Biostatistics Program, College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, United States
| | - Zeyuan Song
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States
| | - Konstantin G. Arbeev
- Biodemography of Aging Research Unit, Social Science Research Institute, Duke University, Durham, NC, United States
| | - Marianne Nygaard
- Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
| | - Mary F Feitosa
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St Louis, MO, United States
| | - Thomas T Perls
- Department of Medicine, Geriatrics Section, Boston University School of Medicine, Boston, MA, United States
| | - Paola Sebastiani
- Institute for Clinical Research and Health Policy Studies, Tufts Medical Center, Boston, MA, United States
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14
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Hu D, Li Y, Zhang D, Ding J, Song Z, Min J, Zeng Y, Nie C. Genetic trade-offs between complex diseases and longevity. Aging Cell 2022; 21:e13654. [PMID: 35754110 PMCID: PMC9282840 DOI: 10.1111/acel.13654] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2021] [Revised: 02/28/2022] [Accepted: 05/26/2022] [Indexed: 11/30/2022] Open
Abstract
Longevity was influenced by many complex diseases and traits. However, the relationships between human longevity and genetic risks of complex diseases were not broadly studied. Here, we constructed polygenic risk scores (PRSs) for 225 complex diseases/traits and evaluated their relationships with human longevity in a cohort with 2178 centenarians and 2299 middle‐aged individuals. Lower genetic risks of stroke and hypotension were observed in centenarians, while higher genetic risks of schizophrenia (SCZ) and type 2 diabetes (T2D) were detected in long‐lived individuals. We further stratified PRSs into cell‐type groups and significance‐level groups. The results showed that the immune component of SCZ genetic risk was positively linked to longevity, and the renal component of T2D genetic risk was the most deleterious. Additionally, SNPs with very small p‐values (p ≤ 1x10‐5) for SCZ and T2D were negatively correlated with longevity. While for the less significant SNPs (1x10‐5 < p ≤ 0.05), their effects on disease and longevity were positively correlated. Overall, we identified genetically informed positive and negative factors for human longevity, gained more insights on the accumulation of disease risk alleles during evolution, and provided evidence for the theory of genetic trade‐offs between complex diseases and longevity.
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Affiliation(s)
- Dingxue Hu
- College of Life Sciences, University of Chinese Academy of Sciences, Beijing, China.,BGI-Shenzhen, Shenzhen, China
| | - Yan Li
- BGI-Shenzhen, Shenzhen, China
| | | | | | - Zijun Song
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Junxia Min
- The First Affiliated Hospital, Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, China
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development, Peking University, Beijing, China.,Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, North Carolina, USA
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15
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How Important Are Genes to Achieve Longevity? Int J Mol Sci 2022; 23:ijms23105635. [PMID: 35628444 PMCID: PMC9145989 DOI: 10.3390/ijms23105635] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2022] [Revised: 05/13/2022] [Accepted: 05/16/2022] [Indexed: 01/25/2023] Open
Abstract
Several studies on the genetics of longevity have been reviewed in this paper. The results show that, despite efforts and new technologies, only two genes, APOE and FOXO3A, involved in the protection of cardiovascular diseases, have been shown to be associated with longevity in nearly all studies. This happens because the genetic determinants of longevity are dynamic and depend on the environmental history of a given population. In fact, population-specific genes are thought to play a greater role in the attainment of longevity than those shared between different populations. Hence, it is not surprising that GWAS replicated associations of common variants with longevity have been few, if any, as these studies pool together different populations. An alternative way might be the study of long-life families. This type of approach is proving to be an ideal resource for uncovering protective alleles and associated biological signatures for healthy aging phenotypes and exceptional longevity.
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16
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Intermediate alleles of HTT: A new pathway in longevity. J Neurol Sci 2022; 438:120274. [DOI: 10.1016/j.jns.2022.120274] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2022] [Revised: 04/22/2022] [Accepted: 04/30/2022] [Indexed: 11/29/2022]
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17
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Cable J, Weber-Ban E, Clausen T, Walters KJ, Sharon M, Finley DJ, Gu Y, Hanna J, Feng Y, Martens S, Simonsen A, Hansen M, Zhang H, Goodwin JM, Reggio A, Chang C, Ge L, Schulman BA, Deshaies RJ, Dikic I, Harper JW, Wertz IE, Thomä NH, Słabicki M, Frydman J, Jakob U, David DC, Bennett EJ, Bertozzi CR, Sardana R, Eapen VV, Carra S. Targeted protein degradation: from small molecules to complex organelles-a Keystone Symposia report. Ann N Y Acad Sci 2022; 1510:79-99. [PMID: 35000205 DOI: 10.1111/nyas.14745] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2021] [Accepted: 12/10/2021] [Indexed: 12/15/2022]
Abstract
Targeted protein degradation is critical for proper cellular function and development. Protein degradation pathways, such as the ubiquitin proteasomes system, autophagy, and endosome-lysosome pathway, must be tightly regulated to ensure proper elimination of misfolded and aggregated proteins and regulate changing protein levels during cellular differentiation, while ensuring that normal proteins remain unscathed. Protein degradation pathways have also garnered interest as a means to selectively eliminate target proteins that may be difficult to inhibit via other mechanisms. On June 7 and 8, 2021, several experts in protein degradation pathways met virtually for the Keystone eSymposium "Targeting protein degradation: from small molecules to complex organelles." The event brought together researchers working in different protein degradation pathways in an effort to begin to develop a holistic, integrated vision of protein degradation that incorporates all the major pathways to understand how changes in them can lead to disease pathology and, alternatively, how they can be leveraged for novel therapeutics.
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Affiliation(s)
| | - Eilika Weber-Ban
- Institute of Molecular Biology and Biophysics, ETH Zurich, Zurich, Switzerland
| | - Tim Clausen
- Research Institute of Molecular Pathology (IMP), Vienna BioCenter and Medical University of Vienna, Vienna, Austria
| | - Kylie J Walters
- Protein Processing Section, Center for Structural Biology, Center for Cancer Research, National Cancer Institute, National Institutes of Health, Frederick, Maryland
| | - Michal Sharon
- Department of Bimolecular Sciences, Weizmann Institute of Science, Rehovot, Israel
| | - Daniel J Finley
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts
| | - Yangnan Gu
- Department of Plant and Microbial Biology and Innovative Genomics Institute, University of California, Berkeley, California
| | - John Hanna
- Department of Pathology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts
| | - Yue Feng
- Princess Margaret Cancer Centre, University Health Network and Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Sascha Martens
- Max Perutz Labs, University of Vienna, Vienna BioCenter (VBC), Vienna, Austria
| | - Anne Simonsen
- Department of Molecular Medicine, Institute of Basic Medical Sciences and Centre for Cancer Cell Reprogramming, Institute of Clinical Medicine, University of Oslo, Oslo, Norway
- Department of Molecular Cell Biology, Institute for Cancer Research, Oslo University Hospital, Oslo, Norway
| | - Malene Hansen
- Sanford Burnham Prebys Medical Discovery Institute, Program of Development, Aging, and Regeneration, La Jolla, California
| | - Hong Zhang
- National Laboratory of Biomacromolecules, CAS Center for Excellence in Biomacromolecules, Institute of Biophysics, Chinese Academy of Sciences and College of Life Sciences, University of Chinese Academy of Sciences, Beijing, People's Republic of China
| | | | - Alessio Reggio
- Telethon Institute of Genetics and Medicine (TIGEM), Pozzuoli, Italy
| | - Chunmei Chang
- Molecular and Cell Biology, University of California, Berkeley, Berkeley, California
| | - Liang Ge
- State Key Laboratory of Membrane Biology, Tsinghua University-Peking University Joint Center for Life Sciences, School of Life Sciences, Tsinghua University, Beijing, China
| | - Brenda A Schulman
- Department of Molecular Machines and Signaling, Max Planck Institute of Biochemistry, Martinsried, Germany
| | | | - Ivan Dikic
- Institute of Biochemistry II, School of Medicine and Buchmann Institute for Molecular Life Sciences, Goethe University, Frankfurt, Germany
| | - J Wade Harper
- Department of Cell Biology, Blavatnik Institute, Harvard Medical School, Boston, Massachusetts
| | - Ingrid E Wertz
- Departments of Molecular Oncology and Early Discovery Biochemistry, Genentech, Inc., South San Francisco, California
- Bristol Myers Squibb, Brisbane, California
| | - Nicolas H Thomä
- Friedrich Miescher Institute for Biomedical Research, Basel, Switzerland
| | - Mikołaj Słabicki
- Broad Institute of MIT and Harvard, Cambridge, Massachusetts
- Department of Medical Oncology, Dana-Farber Cancer Institute, Boston, Massachusetts
- Division of Translational Medical Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Judith Frydman
- Biophysics Graduate Program, Department of Biology and Department of Genetics, Stanford University, Stanford, California
- Biohub, San Francisco, California
- Division of CryoEM and Bioimaging, SSRL, SLAC National Accelerator Laboratory, Menlo Park, California
| | - Ursula Jakob
- Department of Molecular, Cellular and Developmental Biology, College of Literature, Science, and the Arts, University of Michigan, Ann Arbor, Michigan
| | - Della C David
- German Center for Neurodegenerative Diseases (DZNE), and Interfaculty Institute of Biochemistry, University of Tübingen, Tübingen, Germany
| | - Eric J Bennett
- Section of Cell and Developmental Biology, Division of Biological Sciences, University of California, San Diego, La Jolla, California
| | - Carolyn R Bertozzi
- Department of Chemistry and Stanford ChEM-H, Stanford University and Howard Hughes Medical Institute, Stanford, California
| | - Richa Sardana
- Weill Institute of Cell and Molecular Biology and Department of Molecular Biology and Genetics, Cornell University, Ithaca, New York
| | - Vinay V Eapen
- Department of Cell Biology, Harvard Medical School, Boston, Massachusetts
| | - Serena Carra
- Department of Biomedical, Metabolic and Neural Sciences, University of Modena and Reggio Emilia, Modena, Italy
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18
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Vega T, Hilario F, Pérez-Caro M, Núñez-Torres R, Pinto RM, González-Neira A. Genetic, environmental and life-style factors associated with longevity. Protocol and response of the LONGECYL Study. GACETA SANITARIA 2022; 36:260-264. [PMID: 35339311 DOI: 10.1016/j.gaceta.2022.01.005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/26/2021] [Revised: 01/03/2022] [Accepted: 01/03/2022] [Indexed: 11/18/2022]
Abstract
OBJECTIVE To describe the objectives, the methodological approach, the response rate of the Genetic, Environmental and Life-style Factors Study in Castilla y León (Spain). METHOD The Health Sentinel Network studied a sample of long-lived individuals aged 95 or more (LLI). The study included biological samples processed with the Global Screening Array v3.0 that contains a total of 730,059 markers. Written consent was obtained before the examination. CONCLUSIONS The LLI contacted were 944, and 760 were completed studied. The 87.4% of LLI were born in Castile and Leon and only 1% were non-native of Spain. Severe cognitive impairment was declared in 8.1% of men and 19.2% of women. Genotyping was performed in 739 LLI, the 78.3% of the contacted sample. Family doctors and nurses achieve high participation in population-based studies. DNA samples were taken from 94% of fully studied LLI, and 100% of these samples where successfully genotyped.
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Affiliation(s)
- Tomás Vega
- Dirección General de Salud Pública, Consejería de Sanidad, Valladolid, Spain.
| | - Fernando Hilario
- Dirección General de Salud Pública, Consejería de Sanidad, Valladolid, Spain
| | - María Pérez-Caro
- Banco Nacional de ADN, Universidad de Salamanca, Salamanca, Spain
| | - Rocío Núñez-Torres
- Unidad de Genotipado Humano-CEGEN, Centro Nacional de Investigaciones Oncológicas, Madrid, Spain
| | - Rosa M Pinto
- Banco Nacional de ADN, Universidad de Salamanca, Salamanca, Spain
| | - Anna González-Neira
- Unidad de Genotipado Humano-CEGEN, Centro Nacional de Investigaciones Oncológicas, Madrid, Spain
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19
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Cahill S, Chandola T, Hager R. Genetic Variants Associated With Resilience in Human and Animal Studies. Front Psychiatry 2022; 13:840120. [PMID: 35669264 PMCID: PMC9163442 DOI: 10.3389/fpsyt.2022.840120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/20/2021] [Accepted: 04/19/2022] [Indexed: 11/15/2022] Open
Abstract
Resilience is broadly defined as the ability to maintain or regain functioning in the face of adversity and is influenced by both environmental and genetic factors. The identification of specific genetic factors and their biological pathways underpinning resilient functioning can help in the identification of common key factors, but heterogeneities in the operationalisation of resilience have hampered advances. We conducted a systematic review of genetic variants associated with resilience to enable the identification of general resilience mechanisms. We adopted broad inclusion criteria for the definition of resilience to capture both human and animal model studies, which use a wide range of resilience definitions and measure very different outcomes. Analyzing 158 studies, we found 71 candidate genes associated with resilience. OPRM1 (Opioid receptor mu 1), NPY (neuropeptide Y), CACNA1C (calcium voltage-gated channel subunit alpha1 C), DCC (deleted in colorectal carcinoma), and FKBP5 (FKBP prolyl isomerase 5) had both animal and human variants associated with resilience, supporting the idea of shared biological pathways. Further, for OPRM1, OXTR (oxytocin receptor), CRHR1 (corticotropin-releasing hormone receptor 1), COMT (catechol-O-methyltransferase), BDNF (brain-derived neurotrophic factor), APOE (apolipoprotein E), and SLC6A4 (solute carrier family 6 member 4), the same allele was associated with resilience across divergent resilience definitions, which suggests these genes may therefore provide a starting point for further research examining commonality in resilience pathways.
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Affiliation(s)
- Stephanie Cahill
- Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom.,Faculty of Humanities, Cathie Marsh Institute for Social Research, The University of Manchester, Manchester, United Kingdom
| | - Tarani Chandola
- Faculty of Humanities, Cathie Marsh Institute for Social Research, The University of Manchester, Manchester, United Kingdom.,Methods Hub, Department of Sociology, Faculty of Social Sciences, The University of Hong Kong, Hong Kong, Hong Kong SAR, China
| | - Reinmar Hager
- Evolution, Infection and Genomics, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, The University of Manchester, Manchester, United Kingdom
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20
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Tesi N, van der Lee SJ, Hulsman M, Jansen IE, Stringa N, van Schoor NM, Scheltens P, van der Flier WM, Huisman M, Reinders MJT, Holstege H. Polygenic Risk Score of Longevity Predicts Longer Survival Across an Age Continuum. J Gerontol A Biol Sci Med Sci 2021; 76:750-759. [PMID: 33216869 PMCID: PMC8087277 DOI: 10.1093/gerona/glaa289] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2020] [Indexed: 12/17/2022] Open
Abstract
Studying the genome of centenarians may give insights into the molecular mechanisms underlying extreme human longevity and the escape of age-related diseases. Here, we set out to construct polygenic risk scores (PRSs) for longevity and to investigate the functions of longevity-associated variants. Using a cohort of centenarians with maintained cognitive health (N = 343), a population-matched cohort of older adults from 5 cohorts (N = 2905), and summary statistics data from genome-wide association studies on parental longevity, we constructed a PRS including 330 variants that significantly discriminated between centenarians and older adults. This PRS was also associated with longer survival in an independent sample of younger individuals (p = .02), leading up to a 4-year difference in survival based on common genetic factors only. We show that this PRS was, in part, able to compensate for the deleterious effect of the APOE-ε4 allele. Using an integrative framework, we annotated the 330 variants included in this PRS by the genes they associate with. We find that they are enriched with genes associated with cellular differentiation, developmental processes, and cellular response to stress. Together, our results indicate that an extended human life span is, in part, the result of a constellation of variants each exerting small advantageous effects on aging-related biological mechanisms that maintain overall health and decrease the risk of age-related diseases.
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Affiliation(s)
- Niccolo' Tesi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands.,Delft Bioinformatics Lab, Delft University of Technology, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands.,Department of Clinical Genetics, Amsterdam UMC, The Netherlands
| | - Marc Hulsman
- Delft Bioinformatics Lab, Delft University of Technology, The Netherlands.,Department of Clinical Genetics, Amsterdam UMC, The Netherlands
| | - Iris E Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands.,Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Najada Stringa
- Department of Epidemiology and Biostatistics, Amsterdam UMC, The Netherlands.,Amsterdam Public Health Research Institute, The Netherlands
| | - Natasja M van Schoor
- Department of Epidemiology and Biostatistics, Amsterdam UMC, The Netherlands.,Amsterdam Public Health Research Institute, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands.,Department of Epidemiology and Biostatistics, Amsterdam UMC, The Netherlands
| | - Martijn Huisman
- Department of Epidemiology and Biostatistics, Amsterdam UMC, The Netherlands.,Amsterdam Public Health Research Institute, The Netherlands
| | | | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, The Netherlands.,Department of Clinical Genetics, Amsterdam UMC, The Netherlands
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21
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Effect of longevity genetic variants on the molecular aging rate. GeroScience 2021; 43:1237-1251. [PMID: 33948810 DOI: 10.1007/s11357-021-00376-4] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2021] [Accepted: 04/20/2021] [Indexed: 12/18/2022] Open
Abstract
We conducted a genome-wide association study of 1320 centenarians from the New England Centenarian Study (median age = 104 years) and 2899 unrelated controls using >9 M genetic variants imputed to the HRC panel of ~65,000 haplotypes. The genetic variants with the most significant associations were correlated to 4131 proteins that were profiled in the serum of a subset of 224 study participants using a SOMAscan array. The genetic associations were replicated in a genome-wide association study of 480 centenarians and ~800 controls of Ashkenazi Jewish descent. The proteomic associations were replicated in a proteomic scan of approximately 1000 Ashkenazi Jewish participants from a third cohort. The analysis replicated a protein signature associated with APOE genotypes and confirmed strong overexpression of BIRC2 (p < 5E-16) and under-expression of APOB in carriers of the APOE2 allele (p < 0.05). The analysis also discovered and replicated associations between longevity variants and slower changes of protein biomarkers of aging, including a novel protein signature of rs2184061 (CDKN2A/CDKN2B in chromosome 9) that suggests a genetic regulation of GDF15. The analyses showed that longevity variants correlate with proteome signatures that could be manipulated to discover healthy-aging targets.
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22
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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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23
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Sebastiani P, Federico A, Morris M, Gurinovich A, Tanaka T, Chandler KB, Andersen SL, Denis G, Costello CE, Ferrucci L, Jennings L, Glass DJ, Monti S, Perls TT. Protein signatures of centenarians and their offspring suggest centenarians age slower than other humans. Aging Cell 2021; 20:e13290. [PMID: 33512769 PMCID: PMC7884029 DOI: 10.1111/acel.13290] [Citation(s) in RCA: 36] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2020] [Revised: 10/23/2020] [Accepted: 11/14/2020] [Indexed: 12/18/2022] Open
Abstract
Using samples from the New England Centenarian Study (NECS), we sought to characterize the serum proteome of 77 centenarians, 82 centenarians' offspring, and 65 age-matched controls of the offspring (mean ages: 105, 80, and 79 years). We identified 1312 proteins that significantly differ between centenarians and their offspring and controls (FDR < 1%), and two different protein signatures that predict longer survival in centenarians and in younger people. By comparing the centenarian signature with 2 independent proteomic studies of aging, we replicated the association of 484 proteins of aging and we identified two serum protein signatures that are specific of extreme old age. The data suggest that centenarians acquire similar aging signatures as seen in younger cohorts that have short survival periods, suggesting that they do not escape normal aging markers, but rather acquire them much later than usual. For example, centenarian signatures are significantly enriched for senescence-associated secretory phenotypes, consistent with those seen with younger aged individuals, and from this finding, we provide a new list of serum proteins that can be used to measure cellular senescence. Protein co-expression network analysis suggests that a small number of biological drivers may regulate aging and extreme longevity, and that changes in gene regulation may be important to reach extreme old age. This centenarian study thus provides additional signatures that can be used to measure aging and provides specific circulating biomarkers of healthy aging and longevity, suggesting potential mechanisms that could help prolong health and support longevity.
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Affiliation(s)
- Paola Sebastiani
- Institute for Clinical Research and Health Policy StudiesTufts Medical CenterBostonMAUSA
| | - Anthony Federico
- Bioinformatics ProgramBoston UniversityBostonMAUSA
- Division of Computational BiomedicineDepartment of MedicineBoston University School of MedicineBostonMAUSA
| | - Melody Morris
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | | | - Toshiko Tanaka
- Translational Gerontology BranchNational Institute on AgingBaltimoreMDUSA
| | - Kevin B. Chandler
- Translational Glycobiology InstituteDepartment of Translational MedicineFlorida International UniversityHerbert Wertheim College of MedicineMiamiFLUSA
| | - Stacy L. Andersen
- Geriatric SectionDepartment of MedicineBoston University School of Medicine and Boston Medical CenterBostonMAUSA
| | - Gerald Denis
- Department of MedicineBU‐BMC Cancer CenterBoston University School of MedicineBostonMAUSA
| | - Catherine E. Costello
- Department of BiochemistryCenter for Biomedical Mass SpectrometryBoston University School of MedicineBostonMAUSA
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on AgingBaltimoreMDUSA
| | - Lori Jennings
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
| | - David J. Glass
- Novartis Institutes for Biomedical ResearchCambridgeMAUSA
- Regeneron PharmaceuticalsTarrytownNYUSA
| | - Stefano Monti
- Bioinformatics ProgramBoston UniversityBostonMAUSA
- Division of Computational BiomedicineDepartment of MedicineBoston University School of MedicineBostonMAUSA
| | - Thomas T. Perls
- Geriatric SectionDepartment of MedicineBoston University School of Medicine and Boston Medical CenterBostonMAUSA
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24
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Rodríguez-Girondo M, van den Berg N, Hof MH, Beekman M, Slagboom E. Improved selection of participants in genetic longevity studies: family scores revisited. BMC Med Res Methodol 2021; 21:7. [PMID: 33407157 PMCID: PMC7789146 DOI: 10.1186/s12874-020-01193-7] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2020] [Accepted: 12/14/2020] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND Although human longevity tends to cluster within families, genetic studies on longevity have had limited success in identifying longevity loci. One of the main causes of this limited success is the selection of participants. Studies generally include sporadically long-lived individuals, i.e. individuals with the longevity phenotype but without a genetic predisposition for longevity. The inclusion of these individuals causes phenotype heterogeneity which results in power reduction and bias. A way to avoid sporadically long-lived individuals and reduce sample heterogeneity is to include family history of longevity as selection criterion using a longevity family score. A main challenge when developing family scores are the large differences in family size, because of real differences in sibship sizes or because of missing data. METHODS We discussed the statistical properties of two existing longevity family scores: the Family Longevity Selection Score (FLoSS) and the Longevity Relatives Count (LRC) score and we evaluated their performance dealing with differential family size. We proposed a new longevity family score, the mLRC score, an extension of the LRC based on random effects modeling, which is robust for family size and missing values. The performance of the new mLRC as selection tool was evaluated in an intensive simulation study and illustrated in a large real dataset, the Historical Sample of the Netherlands (HSN). RESULTS Empirical scores such as the FLOSS and LRC cannot properly deal with differential family size and missing data. Our simulation study showed that mLRC is not affected by family size and provides more accurate selections of long-lived families. The analysis of 1105 sibships of the Historical Sample of the Netherlands showed that the selection of long-lived individuals based on the mLRC score predicts excess survival in the validation set better than the selection based on the LRC score . CONCLUSIONS Model-based score systems such as the mLRC score help to reduce heterogeneity in the selection of long-lived families. The power of future studies into the genetics of longevity can likely be improved and their bias reduced, by selecting long-lived cases using the mLRC.
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Affiliation(s)
- Mar Rodríguez-Girondo
- Department of Biomedical Data Sciences, section of Medical Statistics, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands.
| | - Niels van den Berg
- Department of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands
| | - Michel H Hof
- Department of Clinical Epidemiology, Biostatistics, and Bioinformatics, Amsterdam UMC, University of Amsterdam, Meibergdreef 9, 1105, AZ, Amsterdam, the Netherlands
| | - Marian Beekman
- Department of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands
| | - Eline Slagboom
- Department of Biomedical Data Sciences, Section of Molecular Epidemiology, Leiden University Medical Center, Albinusdreef 2, 2333, ZA, Leiden, the Netherlands
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25
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Miller JB, Ward E, Staley LA, Stevens J, Teerlink CC, Tavana JP, Cloward M, Page M, Dayton L, Cannon-Albright LA, Kauwe JSK. Identification and genomic analysis of pedigrees with exceptional longevity identifies candidate rare variants. Neurobiol Dis 2020; 143:104972. [PMID: 32574725 PMCID: PMC7461696 DOI: 10.1016/j.nbd.2020.104972] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2020] [Revised: 05/05/2020] [Accepted: 06/12/2020] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND Longevity as a phenotype entails living longer than average and typically includes living without chronic age-related diseases. Recently, several common genetic components to longevity have been identified. This study aims to identify additional genetic variants associated with longevity using unique and powerful analyses of pedigrees with a statistical excess of healthy elderly individuals identified in the Utah Population Database (UPDB). METHODS From an existing biorepository of Utah pedigrees, six independent cousin pairs were selected from four extended pedigrees that exhibited an excess of healthy elderly individuals; whole exome sequencing (WES) was performed on two elderly individuals from each pedigree who were either first cousins or first cousins once removed. Rare (<.01 population frequency) variants shared by at least one elderly cousin pair in a region likely to be identical by descent were identified as candidates. Ingenuity Variant Analysis was used to prioritize putative causal variants based on quality control, frequency, and gain or loss of function. The variant frequency was compared in healthy cohorts and in an Alzheimer's disease cohort. Remaining variants were filtered based on their presence in genes reported to have an effect on the aging process, aging of cells, or the longevity process. Validation of these candidate variants included tests of segregation on other elderly relatives. RESULTS Fifteen rare candidate genetic variants spanning 17 genes shared within cousins were identified as having passed prioritization criteria. Of those variants, six were present in genes that are known or predicted to affect the aging process: rs78408340 (PAM), rs112892337 (ZFAT), rs61737629 (ESPL1), rs141903485 (CEBPE), rs144369314 (UTP4), and rs61753103 (NUP88 and RABEP1). ESPL1 rs61737629 and CEBPE rs141903485 show additional evidence of segregation with longevity in expanded pedigree analyses (p-values = .001 and .0001, respectively). DISCUSSION This unique pedigree analysis efficiently identified several novel rare candidate variants that may affect the aging process and added support to seven genes that likely contribute to longevity. Further analyses showed evidence for segregation for two rare variants, ESPL1 rs61737629 and CEBPE rs141903485, in the original longevity pedigrees in which they were initially observed. These candidate genes and variants warrant further investigation.
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Affiliation(s)
- Justin B Miller
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Elizabeth Ward
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Lyndsay A Staley
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Jeffrey Stevens
- Genetic Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - Craig C Teerlink
- Genetic Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - Justina P Tavana
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Matthew Cloward
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Madeline Page
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Louisa Dayton
- Department of Biology, Brigham Young University, Provo, UT 84602, USA
| | - Lisa A Cannon-Albright
- Genetic Epidemiology, Department of Internal Medicine, University of Utah, Salt Lake City, UT 84132, USA
| | - John S K Kauwe
- Department of Biology, Brigham Young University, Provo, UT 84602, USA.
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26
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Impact on Longevity of Genetic Cardiovascular Risk and Lifestyle including Red Meat Consumption. OXIDATIVE MEDICINE AND CELLULAR LONGEVITY 2020; 2020:1305413. [PMID: 32714484 PMCID: PMC7354649 DOI: 10.1155/2020/1305413] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/17/2020] [Accepted: 06/02/2020] [Indexed: 12/25/2022]
Abstract
Background Cardiovascular risk (CVR) underlies aging process and longevity. Previous work points to genetic and environmental factors associated with this risk. Objectives The aim of this research is to look for any CVR gene-gene and gene-multifactorial/lifestyle interactions that may impact health and disease and underlie exceptional longevity. Methods A case-control study involving 521 both gender individuals, 253 centenarians (100.26 ± 1.98 years), and 268 controls (67.51 ± 3.25 years), low (LCR, n = 107) and high (HCR, n = 161) CVR. Hypertension, diabetes, obesity (BMI, kg·m−2), and impaired kidney function were defined according to standard criteria. CVR was calculated using Q risk®. DNA was genotyping (ACE-rs4646994, AGT-rs4762, AGR1-rs5182, GRK4-rs2960306, GRK4-rs1024323, NOS3-rs1799983, and SLC12A3-rs13306673) through iPlex-MassARRAY®, read by MALDI-TOF mass spectrometry, and analyzed by EARTDECODE®. Results Antilongevity factors consisted (OR 95% CI, p < 0.05) BMI 1.558 (1.445-1.680), hypertension 2.358 (1.565-3.553), smoking habits 4.528 (2.579-7.949), diabetes 5.553 (2.889-10.675), hypercholesterolemia 1.016 (1.010-1.022), and regular consumption of red meat 22.363 (13.987-35.755). Genetic aspects particularly for HCR individuals ACE II (OR: 3.96 (1.83-8.56), p < 0.0001) and NOS3 TT (OR: 3.11 (1.70-5.70), p < 0.0001) genotypes were also risk associate. Obesity, smoking, hypercholesterolemia, and frequent consumption of red meat have an additive action to hypertension in the longevity process. There was a synergistic interaction between the endothelial NOS3 genotypes and the severity of arterial hypertension. An epistatic interaction between functional genetic variants of GRK4 and angiotensinogen was also observed. Conclusions Cardiovascular risk-related genetic and multifactorial or predominantly lifestyle aspects and its interactions might influence the aging process and contribute to exceptional longevity in Portuguese centenarians. Besides lifestyle, the activity of nitrite oxide synthase may be one of the main physiologic regulators of cardiovascular protection in the path of longevity.
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27
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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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Gurinovich A, Andersen SL, Puca A, Atzmon G, Barzilai N, Sebastiani P. Varying Effects of APOE Alleles on Extreme Longevity in European Ethnicities. J Gerontol A Biol Sci Med Sci 2020; 74:S45-S51. [PMID: 31724059 DOI: 10.1093/gerona/glz179] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Indexed: 12/19/2022] Open
Abstract
APOE is a well-studied gene with multiple effects on aging and longevity. The gene has three alleles: e2, e3, and e4, whose frequencies vary by ethnicity. While the e2 is associated with healthy cognitive aging, the e4 allele is associated with Alzheimer's disease and early mortality and therefore its prevalence among people with extreme longevity (EL) is low. Using the PopCluster algorithm, we identified several ethnically different clusters in which the effect of the e2 and e4 alleles on EL changed substantially. For example, PopCluster discovered a large group of 1,309 subjects enriched of Southern Italian genetic ancestry with weaker protective effect of e2 (odds ratio [OR] = 1.27, p = .14) and weaker damaging effect of e4 (OR = 0.82, p = .31) on the phenotype of EL compared to other European ethnicities. Further analysis of this cluster suggests that the odds for EL in carriers of the e4 allele with Southern Italian genetic ancestry differ depending on whether they live in the United States (OR = 0.29, p = .009) or Italy (OR = 1.21, p = .38). PopCluster also found clusters enriched of subjects with Danish ancestry with varying effect of e2 on EL. The country of residence (Denmark or United States) appears to change the odds for EL in the e2 carriers.
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Affiliation(s)
- Anastasia Gurinovich
- Bioinformatics Program, Boston University, Massachusetts.,Department of Biostatistics, Boston University School of Public Health, Massachusetts
| | | | - Annibale Puca
- Department of Medicine and Surgery, University of Salerno, Fisciano, SA, Italy.,Cardiovascular Research Unit, IRCCS MultiMedica, Sesto San Giovanni, MI, Italy
| | - Gil Atzmon
- Faculty of Natural Science, University of Haifa, Israel.,Albert Einstein College of Medicine, Bronx, New York
| | - Nir Barzilai
- Albert Einstein College of Medicine, Bronx, New York
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Massachusetts
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29
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Abstract
The majority of research to understand the pathogenesis of and contributors to Alzheimer’s disease (AD) pathology, dementia, and disease progression has focused on studying individuals who have the disease or are at increased risk of having the disease. Yet there may be much to learn from individuals who have a paradoxical decreased risk of AD suggesting underlying protective factors. Centenarians demonstrate exceptional longevity that for a subset of the cohort is associated with an increased health span characterized by the delay or escape of age-related diseases including dementia. Here, I give evidence of the association of exceptional longevity with resistance and resilience to AD and describe how cohorts of centenarians and their offspring may serve as models of neuroprotection from AD. Discoveries of novel genetic, environmental, and behavioral factors that are associated with a decreased risk of AD may inform the development of interventions to slow or prevent AD in the general population. Centenarian cohorts may also be instrumental in serving as controls to individuals with AD to identify additional risk factors.
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30
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Sathyan S, Verghese J. Genetics of frailty: A longevity perspective. Transl Res 2020; 221:83-96. [PMID: 32289255 PMCID: PMC7729977 DOI: 10.1016/j.trsl.2020.03.005] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/02/2020] [Revised: 02/18/2020] [Accepted: 03/09/2020] [Indexed: 12/31/2022]
Abstract
Frailty is a complex late life phenotype characterized by cumulative declines in multiple physiological systems that increases the risk for disability and mortality. The biological changes associated with aging are risk factors for frailty as well as for complex diseases; whereas longevity is assumed to be an outcome of protective biological mechanisms. Understanding the interplay between biological alterations associated with aging and protective mechanisms associated with longevity in the context of frailty may help guide development of interventions to increase healthspan and promote successful aging. The complexity of these phenotypes and relatively low heritability in studies are the main roadblocks in deciphering genetic mechanisms of these age associated conditions. We review genetic research related to frailty, and discuss the possible intertwined biology of frailty and longevity.
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Affiliation(s)
- Sanish Sathyan
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York
| | - Joe Verghese
- Department of Neurology, Albert Einstein College of Medicine, Bronx, New York; Department of Medicine, Albert Einstein College of Medicine, Bronx, New York.
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31
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Nygaard HB, Erson-Omay EZ, Wu X, Kent BA, Bernales CQ, Evans DM, Farrer MJ, Vilariño-Güell C, Strittmatter SM. Whole-Exome Sequencing of an Exceptional Longevity Cohort. J Gerontol A Biol Sci Med Sci 2020; 74:1386-1390. [PMID: 29750252 DOI: 10.1093/gerona/gly098] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2018] [Accepted: 04/26/2018] [Indexed: 12/22/2022] Open
Abstract
Centenarians represent a unique cohort to study the genetic basis for longevity and factors determining the risk of neurodegenerative disorders, including Alzheimer's disease (AD). The estimated genetic contribution to longevity is highest in centenarians and super-cententenarians, but few genetic variants have been shown to clearly impact this phenotype. While the genetic risk for AD and other dementias is now well understood, the frequency of known dementia risk variants in centenarians is not fully characterized. To address these questions, we performed whole-exome sequencing on 100 individuals of 98-108 years age in search of genes with large effect sizes towards the exceptional aging phenotype. Overall, we were unable to identify a rare protein-altering variant or individual genes with an increased burden of rare variants associated with exceptional longevity. Gene burden analysis revealed three genes of nominal statistical significance associated with extreme aging, including LYST, MDN1, and RBMXL1. Several genes with variants conferring an increased risk for AD and other dementias were identified, including TREM2, EPHA1, ABCA7, PLD3, MAPT, and NOTCH3. Larger centenarian studies will be required to further elucidate the genetic basis for longevity, and factors conferring protection against age-dependent neurodegenerative syndromes.
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Affiliation(s)
- Haakon B Nygaard
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - E Zeynep Erson-Omay
- Department of Neurosurgery, Yale University School of Medicine, New Haven, Connecticut
| | - Xiujuan Wu
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Brianne A Kent
- Division of Neurology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Cecily Q Bernales
- Department of Medical Genetics, Centre for Applied Neurogenetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Daniel M Evans
- Department of Medical Genetics, Centre for Applied Neurogenetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Matthew J Farrer
- Department of Medical Genetics, Centre for Applied Neurogenetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Carles Vilariño-Güell
- Department of Medical Genetics, Centre for Applied Neurogenetics, University of British Columbia, Vancouver, British Columbia, Canada
| | - Stephen M Strittmatter
- Program in Cellular Neuroscience, Neurodegeneration and Repair (CNNR), Yale University School of Medicine, New Haven, Connecticut
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32
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Kuo CL, Pilling LC, Atkins JL, Kuchel GA, Melzer D. ApoE e2 and aging-related outcomes in 379,000 UK Biobank participants. Aging (Albany NY) 2020; 12:12222-12233. [PMID: 32511104 PMCID: PMC7343499 DOI: 10.18632/aging.103405] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2020] [Accepted: 05/25/2020] [Indexed: 01/07/2023]
Abstract
The Apolipoprotein E (APOE) e4 allele is associated with reduced longevity and increased Coronary Artery Disease (CAD) and Alzheimer’s disease, with e4e4 having markedly larger effect sizes than e3e4. The e2 longevity promoting variant is less studied. We conducted a phenome-wide association study of ApoE e2e3 and e2e2 with aging phenotypes, to assess their potential as targets for anti-aging interventions. Data were from 379,000 UK Biobank participants, aged 40 to 70 years. e2e3 (n=46,535) had mostly lower lipid-related biomarker levels including reduced total and LDL-cholesterol, and lower risks of CAD (Odds Ratio=0.87, 95% CI: 0.83 to 0.90, p=4.92×10-14) and hypertension (OR=0.94, 95% CI: 0.92 to 0.97, p=7.28×10-7) versus e3e3. However, lipid changes in e2e2 (n=2,398) were more extreme, including a marked increase in triglyceride levels (0.41 Standard Deviations, 95% CI: 0.37 to 0.45, p=5.42×10-92), with no associated changes in CAD risks. There were no associations with biomarkers of kidney function. The effects of both e2e2 and e2e3 were minimal on falls, muscle mass, grip strength or frailty. In conclusion, e2e3 has protective effects on some health outcomes, but the effects of e2e2 are not similar, complicating the potential usefulness of e2 as a target for anti-aging intervention.
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Affiliation(s)
- Chia-Ling Kuo
- Department of Public Health Sciences, University of Connecticut Health, Farmington, CT 06032, USA.,Connecticut Convergence Institute for Translation in Regenerative Engineering, University of Connecticut Health, Farmington, CT 06032, USA.,Center on Aging, School of Medicine, University of Connecticut Health, Farmington, CT 06030, USA
| | - Luke C Pilling
- Center on Aging, School of Medicine, University of Connecticut Health, Farmington, CT 06030, USA.,College of Medicine and Health, University of Exeter, Exeter, Devon, UK
| | - Janice L Atkins
- College of Medicine and Health, University of Exeter, Exeter, Devon, UK
| | - George A Kuchel
- Center on Aging, School of Medicine, University of Connecticut Health, Farmington, CT 06030, USA
| | - David Melzer
- Center on Aging, School of Medicine, University of Connecticut Health, Farmington, CT 06030, USA.,College of Medicine and Health, University of Exeter, Exeter, Devon, UK
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33
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Berg N, Rodríguez‐Girondo M, Mandemakers K, Janssens AAPO, Beekman M, Slagboom PE. Longevity Relatives Count score identifies heritable longevity carriers and suggests case improvement in genetic studies. Aging Cell 2020; 19:e13139. [PMID: 32352215 PMCID: PMC7294789 DOI: 10.1111/acel.13139] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/24/2019] [Revised: 01/24/2020] [Accepted: 02/23/2020] [Indexed: 12/23/2022] Open
Abstract
Loci associated with longevity are likely to harbor genes coding for key players of molecular pathways involved in a lifelong decreased mortality and decreased/compressed morbidity. However, identifying such loci is challenging. One of the most plausible reasons is the uncertainty in defining long‐lived cases with the heritable longevity trait among long‐living phenocopies. To avoid phenocopies, family selection scores have been constructed, but these have not yet been adopted as state of the art in longevity research. Here, we aim to identify individuals with the heritable longevity trait by using current insights and a novel family score based on these insights. We use a unique dataset connecting living study participants to their deceased ancestors covering 37,825 persons from 1,326 five‐generational families, living between 1788 and 2019. Our main finding suggests that longevity is transmitted for at least two subsequent generations only when at least 20% of all relatives are long‐lived. This proves the importance of family data to avoid phenocopies in genetic studies.
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Affiliation(s)
- Niels Berg
- Section of Molecular Epidemiology Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
- Radboud Group for Historical Demography and Family History Radboud University Nijmegen The Netherlands
| | - Mar Rodríguez‐Girondo
- Section of Medical Statistics Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
| | - Kees Mandemakers
- International Institute of Social History Amsterdam The Netherlands
| | | | - Marian Beekman
- Section of Molecular Epidemiology Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
| | - P. Eline Slagboom
- Section of Molecular Epidemiology Department of Biomedical Data Sciences Leiden University Medical Center Leiden The Netherlands
- Max Planck Institute for Biology of Ageing Cologne Germany
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34
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Huang W, Campbell T, Carbone MA, Jones WE, Unselt D, Anholt RRH, Mackay TFC. Context-dependent genetic architecture of Drosophila life span. PLoS Biol 2020; 18:e3000645. [PMID: 32134916 PMCID: PMC7077879 DOI: 10.1371/journal.pbio.3000645] [Citation(s) in RCA: 38] [Impact Index Per Article: 9.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2019] [Revised: 03/17/2020] [Accepted: 02/14/2020] [Indexed: 12/13/2022] Open
Abstract
Understanding the genetic basis of variation in life span is a major challenge that is difficult to address in human populations. Evolutionary theory predicts that alleles affecting natural variation in life span will have properties that enable them to persist in populations at intermediate frequencies, such as late-life-specific deleterious effects, antagonistic pleiotropic effects on early and late-age fitness components, and/or sex- and environment-specific or antagonistic effects. Here, we quantified variation in life span in males and females reared in 3 thermal environments for the sequenced, inbred lines of the Drosophila melanogaster Genetic Reference Panel (DGRP) and an advanced intercross outbred population derived from a subset of DGRP lines. Quantitative genetic analyses of life span and the micro-environmental variance of life span in the DGRP revealed significant genetic variance for both traits within each sex and environment, as well as significant genotype-by-sex interaction (GSI) and genotype-by-environment interaction (GEI). Genome-wide association (GWA) mapping in both populations implicates over 2,000 candidate genes with sex- and environment-specific or antagonistic pleiotropic allelic effects. Over 1,000 of these genes are associated with variation in life span in other D. melanogaster populations. We functionally assessed the effects of 15 candidate genes using RNA interference (RNAi): all affected life span and/or micro-environmental variance of life span in at least one sex and environment and exhibited sex-and environment-specific effects. Our results implicate novel candidate genes affecting life span and suggest that variation for life span may be maintained by variable allelic effects in heterogeneous environments.
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Affiliation(s)
- Wen Huang
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Terry Campbell
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Mary Anna Carbone
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - W. Elizabeth Jones
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Desiree Unselt
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Robert R. H. Anholt
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
| | - Trudy F. C. Mackay
- Program in Genetics, W. M. Keck Center for Behavioral Biology and Department of Biological Sciences, North Carolina State University, Raleigh, North Carolina, United States of America
- * E-mail:
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35
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Abstract
The past two centuries have witnessed an unprecedented rise in human life expectancy. Sustaining longer lives with reduced periods of disability will require an understanding of the underlying mechanisms of ageing, and genetics is a powerful tool for identifying these mechanisms. Large-scale genome-wide association studies have recently identified many loci that influence key human ageing traits, including lifespan. Multi-trait loci have been linked with several age-related diseases, suggesting shared ageing influences. Mutations that drive accelerated ageing in prototypical progeria syndromes in humans point to an important role for genome maintenance and stability. Together, these different strands of genetic research are highlighting pathways for the discovery of anti-ageing interventions that may be applicable in humans.
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36
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Xu R, Gong CX, Duan CM, Huang JC, Yang GQ, Yuan JJ, Zhang Q, Xiong XY, Yang QW. Age-Dependent Changes in the Plasma Proteome of Healthy Adults. J Nutr Health Aging 2020; 24:846-856. [PMID: 33009535 DOI: 10.1007/s12603-020-1392-6] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/24/2022]
Abstract
OBJECTIVE Human blood plasma is a complex that communicates with most parts of the body and reflects the changes in the state of an organism. Identifying age-related biomarkers can help predict and monitor age-related physiological decline and diseases and identify new treatments for diseases. METHODS AND PARTICIPANTS In this study, TMT-LC-MS/MS was utilized to screen differentially expressed plasma proteins in 118 healthy adults of different ages. Participants were divided into three groups: 21-30 years of age (Young), 41-50 years of age (Middle) and ≥60 years of age (Old). RESULTS The number of differentially expressed proteins in the comparisons of Young vs Middle, Middle vs Old and Young vs Old were 82, 22 and 99, respectively. These proteins were involved in numerous physiological processes, such as "negative regulation of smooth muscle cell proliferation" and "blood coagulation". Moreover, when Young was compared with Middle or Old, "complement and coagulation cascades" was the top enriched pathway by KEGG pathway enrichment analysis. Functional phenotyping of the proteome demonstrated that the plasma proteomic profiles of young adults were strikingly dissimilar to those of the middle-aged or older adults. CONCLUSIONS The results of this study mapped the variation in the expression of plasma proteins and provided information about possible biomarkers/treatments for different age-related functional disorders.
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Affiliation(s)
- R Xu
- Xiaoyi Xiong and Qingwu Yang, No.183, Xinqiaozheng Street, Shapingba District, Chongqing 400037, China, Fax number: +86 23 6877 4413, (Xiaoyi Xiong) and (Qingwu Yang)
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37
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Sebastiani P, Monti S, Morris M, Gurinovich A, Toshiko T, Andersen SL, Sweigart B, Ferrucci L, Jennings LL, Glass DJ, Perls TT. A serum protein signature of APOE genotypes in centenarians. Aging Cell 2019; 18:e13023. [PMID: 31385390 PMCID: PMC6826130 DOI: 10.1111/acel.13023] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 04/07/2019] [Accepted: 07/07/2019] [Indexed: 12/30/2022] Open
Abstract
The discovery of treatments to prevent or delay dementia and Alzheimer's disease is a priority. The gene APOE is associated with cognitive change and late-onset Alzheimer's disease, and epidemiological studies have provided strong evidence that the e2 allele of APOE has a neuroprotective effect, it is associated with increased longevity and an extended healthy lifespan in centenarians. In this study, we correlated APOE genotype data of 222 participants of the New England Centenarian Study, including 75 centenarians, 82 centenarian offspring, and 65 controls, comprising 55 carriers of APOE e2 , with aptamer-based serum proteomics (SomaLogic technology) of 4,785 human proteins corresponding to 4,137 genes. We discovered a signature of 16 proteins that associated with different APOE genotypes and replicated the signature in three independent studies. We also show that the protein signature tracks with gene expression profiles in brains of late-onset Alzheimer's disease versus healthy controls. Finally, we show that seven of these proteins correlate with cognitive function patterns in longitudinally collected data. This analysis in particular suggests that Baculoviral IAP repeat containing two (BIRC2) is a novel biomarker of neuroprotection that associates with the neuroprotective allele of APOE. Therefore, targeting APOE e2 molecularly may preserve cognitive function.
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Affiliation(s)
- Paola Sebastiani
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusetts
| | - Stefano Monti
- Bioinformatics ProgramBoston UniversityBostonMassachusetts
- Division of Computational Biomedicine, Department of MedicineBoston University School of MedicineBostonMassachusetts
| | - Melody Morris
- Novartis Institutes for Biomedical ResearchCambridgeMassachusetts
| | - Anastasia Gurinovich
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusetts
- Bioinformatics ProgramBoston UniversityBostonMassachusetts
| | - Tanaka Toshiko
- Translational Gerontology BranchNational Institute on AgingBaltimoreMaryland
| | - Stacy L. Andersen
- Geriatrics Section, Department of Medicine, School of Medicine and Boston Medical CenterBoston UniversityBostonMA
| | - Benjamin Sweigart
- Department of BiostatisticsBoston University School of Public HealthBostonMassachusetts
| | - Luigi Ferrucci
- Translational Gerontology BranchNational Institute on AgingBaltimoreMaryland
| | - Lori L. Jennings
- Novartis Institutes for Biomedical ResearchCambridgeMassachusetts
| | - David J. Glass
- Novartis Institutes for Biomedical ResearchCambridgeMassachusetts
| | - Thomas T. Perls
- Geriatrics Section, Department of Medicine, School of Medicine and Boston Medical CenterBoston UniversityBostonMA
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38
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Kuo C, Pilling LC, Kuchel GA, Ferrucci L, Melzer D. Telomere length and aging-related outcomes in humans: A Mendelian randomization study in 261,000 older participants. Aging Cell 2019; 18:e13017. [PMID: 31444995 PMCID: PMC6826144 DOI: 10.1111/acel.13017] [Citation(s) in RCA: 61] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2018] [Revised: 07/04/2019] [Accepted: 07/06/2019] [Indexed: 12/29/2022] Open
Abstract
Inherited genetic variation influencing leukocyte telomere length provides a natural experiment for testing associations with health outcomes, more robust to confounding and reverse causation than observational studies. We tested associations between genetically determined telomere length and aging‐related health outcomes in a large European ancestry older cohort. Data were from n = 379,758 UK Biobank participants aged 40–70, followed up for mean of 7.5 years (n = 261,837 participants aged 60 and older by end of follow‐up). Thirteen variants strongly associated with longer telomere length in peripheral white blood cells were analyzed using Mendelian randomization methods with Egger plots to assess pleiotropy. Variants in TERC, TERT, NAF1, OBFC1, and RTEL1 were included, and estimates were per 250 base pairs increase in telomere length, approximately equivalent to the average change over a decade in the general white population. We highlighted associations with false discovery rate‐adjusted p‐values smaller than .05. Genetically determined longer telomere length was associated with lowered risk of coronary heart disease (CHD; OR = 0.95, 95% CI: 0.92–0.98) but raised risk of cancer (OR = 1.11, 95% CI: 1.06–1.16). Little evidence for associations were found with parental lifespan, centenarian status of parents, cognitive function, grip strength, sarcopenia, or falls. The results for those aged 60 and older were similar in younger or all participants. Genetically determined telomere length was associated with increased risk of cancer and reduced risk of CHD but little change in other age‐related health outcomes. Telomere lengthening may offer little gain in later‐life health status and face increasing cancer risks.
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Affiliation(s)
- Chia‐Ling Kuo
- Department of Community Medicine and Health Care, Connecticut Convergence Institute for Translation in Regenerative Engineering, Institute for Systems Genomics University of Connecticut Health Farmington CT USA
| | - Luke C. Pilling
- Epidemiology and Public Health Group, University of Exeter Medical School, RILD Level 3 Royal Devon & Exeter Hospital Exeter UK
| | - George A. Kuchel
- Center on Aging, School of Medicine University of Connecticut Farmington CT USA
| | | | - David Melzer
- Epidemiology and Public Health Group, University of Exeter Medical School, RILD Level 3 Royal Devon & Exeter Hospital Exeter UK
- Center on Aging, School of Medicine University of Connecticut Farmington CT USA
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McCorrison J, Girke T, Goetz LH, Miller RA, Schork NJ. Genetic Support for Longevity-Enhancing Drug Targets: Issues, Preliminary Data, and Future Directions. J Gerontol A Biol Sci Med Sci 2019; 74:S61-S71. [PMID: 31724058 PMCID: PMC7330475 DOI: 10.1093/gerona/glz206] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2019] [Indexed: 12/16/2022] Open
Abstract
Interventions meant to promote longevity and healthy aging have often been designed or observed to modulate very specific gene or protein targets. If there are naturally occurring genetic variants in such a target that affect longevity as well as the molecular function of that target (eg, the variants influence the expression of the target, acting as "expression quantitative trait loci" or "eQTLs"), this could support a causal relationship between the pharmacologic modulation of the target and longevity and thereby validate the target at some level. We considered the gene targets of many pharmacologic interventions hypothesized to enhance human longevity and explored how many variants there are in those targets that affect gene function (eg, as expression quantitative trait loci). We also determined whether variants in genes associated with longevity-related phenotypes affect gene function or are in linkage disequilibrium with variants that do, and whether pharmacologic studies point to compounds exhibiting activity against those genes. Our results are somewhat ambiguous, suggesting that integrating genetic association study results with functional genomic and pharmacologic studies is necessary to shed light on genetically mediated targets for longevity-enhancing drugs. Such integration will require more sophisticated data sets, phenotypic definitions, and bioinformatics approaches to be useful.
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Affiliation(s)
- Jamison McCorrison
- Graduate Program in Bioinformatics and Systems Biology, University of California–San Diego, Phoenix, Arizona
| | - Thomas Girke
- Institute for Integrative Genome Biology, University of California, Riverside, Phoenix, Arizona
| | - Laura H Goetz
- Department of Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute (TGen), Phoenix, Arizona
- Department of Medical Oncology, City of Hope National Medical Center, Duarte, California
| | - Richard A Miller
- Department of Pathology, Ann Arbor
- Glenn Center for the Biology of Aging, University of Michigan, Ann Arbor
| | - Nicholas J Schork
- Department of Quantitative Medicine and Systems Biology, The Translational Genomics Research Institute (TGen), Phoenix, Arizona
- Department of Population Sciences, City of Hope National Medical Center, Duarte, California
- Department of Psychiatry, University of California–San Diego
- Department of Family Medicine and Public Health, University of California–San Diego
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40
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O'Connell KMS, Ouellette AR, Neuner SM, Dunn AR, Kaczorowski CC. Genetic background modifies CNS-mediated sensorimotor decline in the AD-BXD mouse model of genetic diversity in Alzheimer's disease. GENES, BRAIN, AND BEHAVIOR 2019; 18:e12603. [PMID: 31381246 PMCID: PMC6899779 DOI: 10.1111/gbb.12603] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 07/17/2019] [Accepted: 07/31/2019] [Indexed: 12/14/2022]
Abstract
Many patients with Alzheimer's dementia (AD) also exhibit noncognitive symptoms such as sensorimotor deficits, which can precede the hallmark cognitive deficits and significantly impact daily activities and an individual's ability to live independently. However, the mechanisms underlying sensorimotor dysfunction in AD and their relationship with cognitive decline remains poorly understood, due in part to a lack of translationally relevant animal models. To address this, we recently developed a novel model of genetic diversity in Alzheimer's disease, the AD-BXD genetic reference panel. In this study, we investigated sensorimotor deficits in the AD-BXDs and the relationship to cognitive decline in these mice. We found that age- and AD-related declines in coordination, balance and vestibular function vary significantly across the panel, indicating genetic background strongly influences the expressivity of the familial AD mutations used in the AD-BXD panel and their impact on motor function. Although young males and females perform comparably regardless of genotype on narrow beam and inclined screen tasks, there were significant sex differences in aging- and AD-related decline, with females exhibiting worse decline than males of the same age and transgene status. Finally, we found that AD motor decline is not correlated with cognitive decline, suggesting that sensorimotor deficits in AD may occur through distinct mechanisms. Overall, our results suggest that AD-related sensorimotor decline is strongly dependent on background genetics and is independent of dementia and cognitive deficits, suggesting that effective therapeutics for the entire spectrum of AD symptoms will likely require interventions targeting each distinct domain involved in the disease.
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Affiliation(s)
| | | | - Sarah M. Neuner
- The Jackson LaboratoryBar HarborMaine
- Department of Anatomy and NeurobiologyThe University of Tennessee Health Science CenterMemphisTennessee
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Andersen SL, Sweigart B, Sebastiani P, Drury J, Sidlowski S, Perls TT. Reduced Prevalence and Incidence of Cognitive Impairment Among Centenarian Offspring. J Gerontol A Biol Sci Med Sci 2019; 74:108-113. [PMID: 29931286 DOI: 10.1093/gerona/gly141] [Citation(s) in RCA: 17] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/05/2017] [Accepted: 06/18/2018] [Indexed: 01/20/2023] Open
Abstract
Background Centenarian offspring have better health and lower mortality in comparison to referent cohorts, however it is unknown whether they have preserved cognition at older ages. Methods This prospective study of 491 centenarian offspring and 270 referent participants without familial longevity (mean baseline age 75.5 years) from the New England Centenarian Study analyzed longitudinal cognitive assessments performed using the Telephone Interview for Cognitive Status. Logistic regression was used for cognitive impairment at baseline and Cox proportional hazards regression for risk of incident cognitive impairment. Results After adjustment for age, sex, education, stroke, and diabetes, offspring were 46% less likely to have baseline cognitive impairment (adjusted odds ratio 0.54, 95% CI 0.35-0.82) and were 27% less likely to become cognitively impaired over a median follow-up of 7.8 years (adjusted hazard ratio 0.73, 95% CI 0.53-0.99). Female gender was also independently associated with lower odds of baseline cognitive impairment and lower risk of incident cognitive impairment. Conclusions Familial longevity may confer exposure to genetic and environmental factors that predispose centenarian offspring to preservation of cognitive function at older ages. Centenarian offspring cohorts may provide an opportunity to study cognitive resilience associated with familial longevity.
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Affiliation(s)
- Stacy L Andersen
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Massachusetts
| | - Benjamin Sweigart
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, Massachusetts
| | - Julia Drury
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Massachusetts
| | - Sara Sidlowski
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Massachusetts
| | - Thomas T Perls
- Geriatrics Section, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Massachusetts
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A Prospective Analysis of Genetic Variants Associated with Human Lifespan. G3-GENES GENOMES GENETICS 2019; 9:2863-2878. [PMID: 31484785 PMCID: PMC6723124 DOI: 10.1534/g3.119.400448] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 02/08/2023]
Abstract
We present a massive investigation into the genetic basis of human lifespan. Beginning with a genome-wide association (GWA) study using a de-identified snapshot of the unique AncestryDNA database – more than 300,000 genotyped individuals linked to pedigrees of over 400,000,000 people – we mapped six genome-wide significant loci associated with parental lifespan. We compared these results to a GWA analysis of the traditional lifespan proxy trait, age, and found only one locus, APOE, to be associated with both age and lifespan. By combining the AncestryDNA results with those of an independent UK Biobank dataset, we conducted a meta-analysis of more than 650,000 individuals and identified fifteen parental lifespan-associated loci. Beyond just those significant loci, our genome-wide set of polymorphisms accounts for up to 8% of the variance in human lifespan; this value represents a large fraction of the heritability estimated from phenotypic correlations between relatives.
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Gurinovich A, Bae H, Farrell JJ, Andersen SL, Monti S, Puca A, Atzmon G, Barzilai N, Perls TT, Sebastiani P. PopCluster: an algorithm to identify genetic variants with ethnicity-dependent effects. Bioinformatics 2019; 35:3046-3054. [PMID: 30624692 DOI: 10.1093/bioinformatics/btz017] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2018] [Revised: 11/01/2018] [Accepted: 01/04/2019] [Indexed: 12/13/2022] Open
Abstract
MOTIVATION Over the last decade, more diverse populations have been included in genome-wide association studies. If a genetic variant has a varying effect on a phenotype in different populations, genome-wide association studies applied to a dataset as a whole may not pinpoint such differences. It is especially important to be able to identify population-specific effects of genetic variants in studies that would eventually lead to development of diagnostic tests or drug discovery. RESULTS In this paper, we propose PopCluster: an algorithm to automatically discover subsets of individuals in which the genetic effects of a variant are statistically different. PopCluster provides a simple framework to directly analyze genotype data without prior knowledge of subjects' ethnicities. PopCluster combines logistic regression modeling, principal component analysis, hierarchical clustering and a recursive bottom-up tree parsing procedure. The evaluation of PopCluster suggests that the algorithm has a stable low false positive rate (∼4%) and high true positive rate (>80%) in simulations with large differences in allele frequencies between cases and controls. Application of PopCluster to data from genetic studies of longevity discovers ethnicity-dependent heterogeneity in the association of rs3764814 (USP42) with the phenotype. AVAILABILITY AND IMPLEMENTATION PopCluster was implemented using the R programming language, PLINK and Eigensoft software, and can be found at the following GitHub repository: https://github.com/gurinovich/PopCluster with instructions on its installation and usage. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
| | - Harold Bae
- College of Public Health and Human Sciences, Oregon State University, Corvallis, OR, USA
| | - John J Farrell
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Stacy L Andersen
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Stefano Monti
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Annibale Puca
- Department of Medicine and Surgery, University of Salerno, Fisciano, Italy.,Cardiovascular Research Unit, IRCCS MultiMedica, Sesto San Giovanni, Italy
| | - Gil Atzmon
- Department of Medicine and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Nir Barzilai
- Department of Medicine and Department of Genetics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Thomas T Perls
- Department of Medicine, Boston University School of Medicine, Boston, MA, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, USA
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Deelen J, Evans DS, Arking DE, Tesi N, Nygaard M, Liu X, Wojczynski MK, Biggs ML, van der Spek A, Atzmon G, Ware EB, Sarnowski C, Smith AV, Seppälä I, Cordell HJ, Dose J, Amin N, Arnold AM, Ayers KL, Barzilai N, Becker EJ, Beekman M, Blanché H, Christensen K, Christiansen L, Collerton JC, Cubaynes S, Cummings SR, Davies K, Debrabant B, Deleuze JF, Duncan R, Faul JD, Franceschi C, Galan P, Gudnason V, Harris TB, Huisman M, Hurme MA, Jagger C, Jansen I, Jylhä M, Kähönen M, Karasik D, Kardia SLR, Kingston A, Kirkwood TBL, Launer LJ, Lehtimäki T, Lieb W, Lyytikäinen LP, Martin-Ruiz C, Min J, Nebel A, Newman AB, Nie C, Nohr EA, Orwoll ES, Perls TT, Province MA, Psaty BM, Raitakari OT, Reinders MJT, Robine JM, Rotter JI, Sebastiani P, Smith J, Sørensen TIA, Taylor KD, Uitterlinden AG, van der Flier W, van der Lee SJ, van Duijn CM, van Heemst D, Vaupel JW, Weir D, Ye K, Zeng Y, Zheng W, Holstege H, Kiel DP, Lunetta KL, Slagboom PE, Murabito JM. A meta-analysis of genome-wide association studies identifies multiple longevity genes. Nat Commun 2019; 10:3669. [PMID: 31413261 PMCID: PMC6694136 DOI: 10.1038/s41467-019-11558-2] [Citation(s) in RCA: 168] [Impact Index Per Article: 33.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/31/2018] [Accepted: 07/17/2019] [Indexed: 12/16/2022] Open
Abstract
Human longevity is heritable, but genome-wide association (GWA) studies have had limited success. Here, we perform two meta-analyses of GWA studies of a rigorous longevity phenotype definition including 11,262/3484 cases surviving at or beyond the age corresponding to the 90th/99th survival percentile, respectively, and 25,483 controls whose age at death or at last contact was at or below the age corresponding to the 60th survival percentile. Consistent with previous reports, rs429358 (apolipoprotein E (ApoE) ε4) is associated with lower odds of surviving to the 90th and 99th percentile age, while rs7412 (ApoE ε2) shows the opposite. Moreover, rs7676745, located near GPR78, associates with lower odds of surviving to the 90th percentile age. Gene-level association analysis reveals a role for tissue-specific expression of multiple genes in longevity. Finally, genetic correlation of the longevity GWA results with that of several disease-related phenotypes points to a shared genetic architecture between health and longevity.
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Affiliation(s)
- Joris Deelen
- Max Planck Institute for Biology of Ageing, 50866, Cologne, Germany.
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands.
| | - Daniel S Evans
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA.
| | - Dan E Arking
- McKusick-Nathans Institute of Genetic Medicine, Department of Genetic Medicine, Johns Hopkins University School of Medicine, Baltimore, MD, 21287, USA
| | - Niccolò Tesi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Marianne Nygaard
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
| | - Xiaomin Liu
- BGI-Shenzhen, Shenzhen, 518083, China
- China National Genebank, BGI-Shenzhen, Shenzhen, 518120, China
| | - Mary K Wojczynski
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Mary L Biggs
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, USA
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
| | | | - Gil Atzmon
- Department of Biology, Faculty of Natural Science, University of Haifa, Haifa, 3498838, Israel
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Erin B Ware
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Chloé Sarnowski
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Albert V Smith
- School of Public Health, Department of Biostatistics, University of Michigan, Ann Arbor, MI, 48109, USA
- Icelandic Heart Association, 201, Kópavogur, Iceland
| | - Ilkka Seppälä
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Heather J Cordell
- Institute of Genetic Medicine, Newcastle University, Newcastle upon Tyne, NE1 3BZ, UK
| | - Janina Dose
- Institute of Clinical Molecular Biology, Kiel University, 24105, Kiel, Germany
| | - Najaf Amin
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
| | - Alice M Arnold
- Department of Biostatistics, University of Washington, Seattle, WA, 98115, USA
| | | | - Nir Barzilai
- Departments of Medicine and Genetics, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | | | - Marian Beekman
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | | | - Kaare Christensen
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Clinical Biochemistry and Pharmacology, Odense University Hospital, 5000, Odense C, Denmark
- Department of Clinical Genetics, Odense University Hospital, 5000, Odense C, Denmark
| | - Lene Christiansen
- The Danish Aging Research Center, Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
- Department of Clinical Immunology, Copenhagen University Hospital, Rigshospitalet, 2100, Copenhagen, Denmark
| | - Joanna C Collerton
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Sarah Cubaynes
- MMDN, Univ. Montpellier, EPHE, Unité Inserm 1198, PSL Research University, 34095, Montpellier, France
| | - Steven R Cummings
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA
| | - Karen Davies
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Birgit Debrabant
- Department of Public Health, University of Southern Denmark, 5000, Odense C, Denmark
| | - Jean-François Deleuze
- Fondation Jean Dausset-CEPH, 75010, Paris, France
- Centre National de Recherche en Génomique Humaine, CEA-Institut de Biologie François Jacob, 91000, Evry, France
| | - Rachel Duncan
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Jessica D Faul
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Claudio Franceschi
- Department of Applied Mathematics and Centre of Bioinformatics, Lobachevsky State University of Nizhny Novgorod, Nizhny Novgorod, 603022, Russia
- IRCCS Institute of Neurological Sciences of Bologna (ISNB), 40124, Bologna, Italy
| | - Pilar Galan
- EREN, UMR U1153 Inserm/U1125 Inra/Cnam/Paris 13, Université Paris 13, CRESS, 93017, Bobigny, France
| | - Vilmundur Gudnason
- Icelandic Heart Association, 201, Kópavogur, Iceland
- Faculty of Medicine, University of Iceland, 101, Reykjavik, Iceland
| | - Tamara B Harris
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Bethesda, MD, 20892, USA
| | - Martijn Huisman
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, 1007 MB, Amsterdam, The Netherlands
| | - Mikko A Hurme
- Department of Microbiology and Immunology, Faculty of Medicine and Health Technology, Tampere University, 33014, Tampere, Finland
| | - Carol Jagger
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Iris Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, Vrije Universiteit Amsterdam, 1081 HV, Amsterdam, The Netherlands
| | - Marja Jylhä
- Faculty of Social Sciences (Health Sciences) and Gerontology Research Center (GEREC), Tampere University, 33104, Tampere, Finland
| | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33521, Tampere, Finland
| | - David Karasik
- Azrieli Faculty of Medicine, Bar Ilan University, Safed, 13010, Israel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA
| | - Sharon L R Kardia
- School of Public Health, Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Andrew Kingston
- Institute of Health & Society, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Thomas B L Kirkwood
- Newcastle University Institute for Ageing, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Lenore J Launer
- Laboratory of Epidemiology and Population Sciences, National Institute on Aging, NIH, Bethesda, MD, 20892, USA
| | - Terho Lehtimäki
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Wolfgang Lieb
- Institute of Epidemiology and Biobank PopGen, Kiel University, 24105, Kiel, Germany
| | - Leo-Pekka Lyytikäinen
- Department of Clinical Chemistry, Fimlab Laboratories and Finnish Cardiovascular Research Center-Tampere, Faculty of Medicine and Health Technology, Tampere University, 33520, Tampere, Finland
| | - Carmen Martin-Ruiz
- Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, NE4 5PL, UK
| | - Junxia Min
- Institute of Translational Medicine, School of Medicine, Zhejiang University, Hangzhou, 311058, China
| | - Almut Nebel
- Institute of Clinical Molecular Biology, Kiel University, 24105, Kiel, Germany
| | - Anne B Newman
- Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, 15261, USA
| | - Chao Nie
- BGI-Shenzhen, Shenzhen, 518083, China
| | - Ellen A Nohr
- Research Unit of Gynecology and Obstetrics, Department of Clinical Research, University of Southern Denmark, 5000, Odense C, Denmark
| | - Eric S Orwoll
- Bone and Mineral Unit, Oregon Health Sciences University, Portland, OR, 97239, USA
| | - Thomas T Perls
- Department of Medicine, Geriatrics Section, Boston Medical Center, Boston University School of Medicine, Boston, MA, 02118, USA
| | - Michael A Province
- Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, Saint Louis, MO, 63110, USA
| | - Bruce M Psaty
- Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA, 98101, USA
- Department of Epidemiology, University of Washington, Seattle, WA, 98101, USA
- Department of Health Services, University of Washington, Seattle, WA, 98101, USA
- Kaiser Permanente Washington Health Research Institute, Seattle, WA, 98101, USA
| | - Olli T Raitakari
- Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, 20521, Turku, Finland
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, 20014, Turku, Finland
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Jean-Marie Robine
- MMDN, Univ. Montpellier, EPHE, Unité Inserm 1198, PSL Research University, 34095, Montpellier, France
- CERMES3, UMR CNRS 8211-Unité Inserm 988-EHESS-Université Paris Descartes, 94801, Paris, France
| | - Jerome I Rotter
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Division of Genetic Outcomes, Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - Paola Sebastiani
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - Jennifer Smith
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
- School of Public Health, Epidemiology, University of Michigan, Ann Arbor, MI, 48109, USA
| | - Thorkild I A Sørensen
- Novo Nordisk Foundation Center for Basic Metabolic Research, Section of Metabolic Genetics, and Department of Public Health, Section of Epidemiology, Faculty of Health and Medical Sciences, University of Copenhagen, 2200, Copenhagen N, Denmark
- MRC Integrative Epidemiology Unit, Bristol University, BS8 2BN, Bristol, UK
| | - Kent D Taylor
- Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
- Department of Pediatrics, Harbor-UCLA Medical Center, Torrance, CA, 90502, USA
| | - André G Uitterlinden
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
| | - Wiesje van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
| | - Cornelia M van Duijn
- Department of Epidemiology, Erasmus MC, 3000 CA, Rotterdam, The Netherlands
- Nuffield Department of Population Health, University of Oxford, Oxford, OX3 7LF, UK
| | - Diana van Heemst
- Department of Gerontology and Geriatrics, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands
| | - James W Vaupel
- Max Planck Institute for Demographic Research, 18057, Rostock, Germany
| | - David Weir
- Institute for Social Research, Survey Research Center, University of Michigan, Ann Arbor, MI, 48104, USA
| | - Kenny Ye
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, 10461, USA
| | - Yi Zeng
- Center for Healthy Aging and Development Studies, National School of Development and Raissun Institute for Advanced Studies, Peking University, 100871, Beijing, China
- Center for the Study of Aging and Human Development and Geriatrics Division, Medical School of Duke University, Durham, NC, 27710, USA
| | - Wanlin Zheng
- California Pacific Medical Center Research Institute, San Francisco, CA, 94158, USA
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, 1007 MB, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, 2600 GA, Delft, The Netherlands
| | - Douglas P Kiel
- Hinda and Arthur Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, 02131, USA
- Department of Medicine, Beth Israel Deaconess Medical Center and Harvard Medical School, Boston, MA, 02215, USA
- Broad Institute of MIT & Harvard, Cambridge, MA, 02142, USA
| | - Kathryn L Lunetta
- Department of Biostatistics, Boston University School of Public Health, Boston, MA, 02118, USA
| | - P Eline Slagboom
- Molecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, 2300 RC, Leiden, The Netherlands.
| | - Joanne M Murabito
- NHLBI's and Boston University's Framingham Heart Study, Framingham, MA, 01702, USA.
- Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine, Boston, MA, 02118, USA.
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Moore JH, Raghavachari N. Artificial Intelligence Based Approaches to Identify Molecular Determinants of Exceptional Health and Life Span-An Interdisciplinary Workshop at the National Institute on Aging. Front Artif Intell 2019; 2:12. [PMID: 33733101 PMCID: PMC7861312 DOI: 10.3389/frai.2019.00012] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 07/08/2019] [Indexed: 01/01/2023] Open
Abstract
Artificial intelligence (AI) has emerged as a powerful approach for integrated analysis of the rapidly growing volume of multi-omics data, including many research and clinical tasks such as prediction of disease risk and identification of potential therapeutic targets. However, the potential for AI to facilitate the identification of factors contributing to human exceptional health and life span and their translation into novel interventions for enhancing health and life span has not yet been realized. As researchers on aging acquire large scale data both in human cohorts and model organisms, emerging opportunities exist for the application of AI approaches to untangle the complex physiologic process(es) that modulate health and life span. It is expected that efficient and novel data mining tools that could unravel molecular mechanisms and causal pathways associated with exceptional health and life span could accelerate the discovery of novel therapeutics for healthy aging. Keeping this in mind, the National Institute on Aging (NIA) convened an interdisciplinary workshop titled “Contributions of Artificial Intelligence to Research on Determinants and Modulation of Health Span and Life Span” in August 2018. The workshop involved experts in the fields of aging, comparative biology, cardiology, cancer, and computational science/AI who brainstormed ideas on how AI can be leveraged for the analyses of large-scale data sets from human epidemiological studies and animal/model organisms to close the current knowledge gaps in processes that drive exceptional life and health span. This report summarizes the discussions and recommendations from the workshop on future application of AI approaches to advance our understanding of human health and life span.
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Affiliation(s)
- Jason H Moore
- University of Pennsylvania, Philadelphia, PA, United States
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Morris BJ, Willcox BJ, Donlon TA. Genetic and epigenetic regulation of human aging and longevity. Biochim Biophys Acta Mol Basis Dis 2019; 1865:1718-1744. [PMID: 31109447 PMCID: PMC7295568 DOI: 10.1016/j.bbadis.2018.08.039] [Citation(s) in RCA: 71] [Impact Index Per Article: 14.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2018] [Revised: 08/02/2018] [Accepted: 08/28/2018] [Indexed: 02/06/2023]
Abstract
Here we summarize the latest data on genetic and epigenetic contributions to human aging and longevity. Whereas environmental and lifestyle factors are important at younger ages, the contribution of genetics appears more important in reaching extreme old age. Genome-wide studies have implicated ~57 gene loci in lifespan. Epigenomic changes during aging profoundly affect cellular function and stress resistance. Dysregulation of transcriptional and chromatin networks is likely a crucial component of aging. Large-scale bioinformatic analyses have revealed involvement of numerous interaction networks. As the young well-differentiated cell replicates into eventual senescence there is drift in the highly regulated chromatin marks towards an entropic middle-ground between repressed and active, such that genes that were previously inactive "leak". There is a breakdown in chromatin connectivity such that topologically associated domains and their insulators weaken, and well-defined blocks of constitutive heterochromatin give way to generalized, senescence-associated heterochromatin, foci. Together, these phenomena contribute to aging.
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Affiliation(s)
- Brian J Morris
- Basic & Clinical Genomics Laboratory, School of Medical Sciences and Bosch Institute, University of Sydney, New South Wales 2006, Australia; Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Bradley J Willcox
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Department of Geriatric Medicine, John A. Burns School of Medicine, University of Hawaii, Kuakini Medical Center Campus, Honolulu, HI 96813, United States.
| | - Timothy A Donlon
- Honolulu Heart Program (HHP)/Honolulu-Asia Aging Study (HAAS), Department of Research, Kuakini Medical Center, Honolulu, HI 96817, United States; Departments of Cell & Molecular Biology and Pathology, John A. Burns School of Medicine, University of Hawaii, Honolulu, HI 96813, United States.
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Ye S, Ma L, Zhang R, Liu F, Jiang P, Xu J, Cao H, Du X, Lin F, Cheng L, Zhou X, Shi Z, Liu Y, Huang Y, Wang Z, Li C. Plasma proteomic and autoantibody profiles reveal the proteomic characteristics involved in longevity families in Bama, China. Clin Proteomics 2019; 16:22. [PMID: 31139026 PMCID: PMC6526601 DOI: 10.1186/s12014-019-9242-4] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2018] [Accepted: 05/15/2019] [Indexed: 12/23/2022] Open
Abstract
BACKGROUND Chinese Bama Yao Autonomous County is a well-known longevity region in the world. In the past 30 years, population and genome studies were undertaken to investigate the secret of longevity and showed that longevity is the result of a combination of multiple factors, such as genetic, environmental and other causes. In this study, characteristics of the blood plasma proteomic and autoantibody profiles of people from Bama longevity family were investigated. METHODS Sixty-six plasma donors from Chinese Bama longevity area were recruited in this study. Thirty-three offsprings of longevous families were selected as case studies (Longevous group) and 33 ABO (blood type), age, and gender-matched subjects from non-longevous families were selected as controls (Normal group). Each group contains 3 biological replicates. Tandem mass tag-based proteomic technique was used to investigate the differentially expressed plasma proteins between the two groups. The auto-reactive IgG antibody profiles of the 3 pooled samples in each group were revealed by human proteome microarrays with 17,000 recombinant human proteins. RESULTS Firstly, 525 plasma proteins were quantified and 12 proteins were discovered differentially expressed between the two groups. Secondly, more than 500 proteins were recognized by plasma antibodies, 14 proteins ware differentially reacted with the autoantibodies in the two groups. Bioinformatics analysis showed some of the differential proteins and targeted autoantigens were involved in cancer, cardiovascular disease and immunity. CONCLUSIONS Proteomic and autoantibody profiles varied between the offspring of longevous and normal families which are from the same area and shared the same environmental factors. The identified differences were reported to be involved in several physiological and pathological pathways. The identified proteins will contribute to a better understanding of the proteomic characteristics of people from Bama longevous area and a revelation of the molecular mechanisms of longevity.
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Affiliation(s)
- Shengliang Ye
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Li Ma
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Rong Zhang
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Fengjuan Liu
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Peng Jiang
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Jun Xu
- Shanghai RAAS Blood Products Co. Ltd, Shanghai, 201401 China
| | - Haijun Cao
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Xi Du
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Fangzhao Lin
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Lu Cheng
- Shanghai RAAS Blood Products Co. Ltd, Shanghai, 201401 China
| | - Xuefeng Zhou
- Shanghai RAAS Blood Products Co. Ltd, Shanghai, 201401 China
| | - Zhihui Shi
- Shanghai RAAS Blood Products Co. Ltd, Shanghai, 201401 China
| | - Yeheng Liu
- Shanghai RAAS Blood Products Co. Ltd, Shanghai, 201401 China
| | | | - Zongkui Wang
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
| | - Changqing Li
- Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610052 China
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Singh PP, Demmitt BA, Nath RD, Brunet A. The Genetics of Aging: A Vertebrate Perspective. Cell 2019; 177:200-220. [PMID: 30901541 PMCID: PMC7592626 DOI: 10.1016/j.cell.2019.02.038] [Citation(s) in RCA: 145] [Impact Index Per Article: 29.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/26/2018] [Revised: 02/21/2019] [Accepted: 02/22/2019] [Indexed: 02/07/2023]
Abstract
Aging negatively impacts vitality and health. Many genetic pathways that regulate aging were discovered in invertebrates. However, the genetics of aging is more complex in vertebrates because of their specialized systems. This Review discusses advances in the genetic regulation of aging in vertebrates from work in mice, humans, and organisms with exceptional lifespans. We highlight challenges for the future, including sex-dependent differences in lifespan and the interplay between genes and environment. We also discuss how the identification of reliable biomarkers of age and development of new vertebrate models can be leveraged for personalized interventions to counter aging and age-related diseases.
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Affiliation(s)
- Param Priya Singh
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | | | - Ravi D Nath
- Department of Genetics, Stanford University, Stanford, CA 94305, USA
| | - Anne Brunet
- Department of Genetics, Stanford University, Stanford, CA 94305, USA; Glenn Laboratories for the Biology of Aging, Stanford, CA 94305, USA.
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49
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Tesi N, van der Lee SJ, Hulsman M, Jansen IE, Stringa N, van Schoor N, Meijers-Heijboer H, Huisman M, Scheltens P, Reinders MJT, van der Flier WM, Holstege H. Centenarian controls increase variant effect sizes by an average twofold in an extreme case-extreme control analysis of Alzheimer's disease. Eur J Hum Genet 2019; 27:244-253. [PMID: 30258121 PMCID: PMC6336855 DOI: 10.1038/s41431-018-0273-5] [Citation(s) in RCA: 35] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2018] [Revised: 07/13/2018] [Accepted: 08/09/2018] [Indexed: 12/12/2022] Open
Abstract
The detection of genetic loci associated with Alzheimer's disease (AD) requires large numbers of cases and controls because variant effect sizes are mostly small. We hypothesized that variant effect sizes should increase when individuals who represent the extreme ends of a disease spectrum are considered, as their genomes are assumed to be maximally enriched or depleted with disease-associated genetic variants. We used 1,073 extensively phenotyped AD cases with relatively young age at onset as extreme cases (66.3 ± 7.9 years), 1,664 age-matched controls (66.0 ± 6.5 years) and 255 cognitively healthy centenarians as extreme controls (101.4 ± 1.3 years). We estimated the effect size of 29 variants that were previously associated with AD in genome-wide association studies. Comparing extreme AD cases with centenarian controls increased the variant effect size relative to published effect sizes by on average 1.90-fold (SE = 0.29, p = 9.0 × 10-4). The effect size increase was largest for the rare high-impact TREM2 (R74H) variant (6.5-fold), and significant for variants in/near ECHDC3 (4.6-fold), SLC24A4-RIN3 (4.5-fold), NME8 (3.8-fold), PLCG2 (3.3-fold), APOE-ε2 (2.2-fold), and APOE-ε4 (twofold). Comparing extreme phenotypes enabled us to replicate the AD association for 10 variants (p < 0.05) in relatively small samples. The increase in effect sizes depended mainly on using centenarians as extreme controls: the average variant effect size was not increased in a comparison of extreme AD cases and age-matched controls (0.94-fold, p = 6.8 × 10-1), suggesting that on average the tested genetic variants did not explain the extremity of the AD cases. Concluding, using centenarians as extreme controls in AD case-control studies boosts the variant effect size by on average twofold, allowing the replication of disease-association in relatively small samples.
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Affiliation(s)
- Niccolò Tesi
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands
| | - Sven J van der Lee
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marc Hulsman
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands
- Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands
| | - Iris E Jansen
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Complex Trait Genetics, Center for Neurogenomics and Cognitive Research, VU, Amsterdam, The Netherlands
| | - Najada Stringa
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Natasja van Schoor
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | | | - Martijn Huisman
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands
- Amsterdam Public Health Research Institute, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
| | - Marcel J T Reinders
- Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands
- Department of Epidemiology and Biostatistics, Amsterdam UMC, Amsterdam, The Netherlands
| | - Henne Holstege
- Alzheimer Center Amsterdam, Department of Neurology, Amsterdam Neuroscience, Vrije Universiteit Amsterdam, Amsterdam UMC, Amsterdam, The Netherlands.
- Department of Clinical Genetics, Amsterdam UMC, Amsterdam, The Netherlands.
- Delft Bioinformatics Lab, Delft University of Technology, Delft, The Netherlands.
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50
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Ferri E, Gussago C, Casati M, Mari D, Rossi PD, Ciccone S, Cesari M, Arosio B. Apolipoprotein E gene in physiological and pathological aging. Mech Ageing Dev 2019; 178:41-45. [PMID: 30658061 DOI: 10.1016/j.mad.2019.01.005] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/30/2018] [Revised: 01/02/2019] [Accepted: 01/15/2019] [Indexed: 01/03/2023]
Abstract
INTRODUCTION The genetic background plays a role on longevity. The distribution of the apolipoprotein E gene (APOE) variants (ε2, ε3, ε4) may differ across age groups, especially in the oldest old and despite geographical and ethnic specificities. Since the ε4 variant is associated with Alzheimer's disease (AD), it might represent an opportunity for exploring the relationship of APOE with physiological and pathological aging. AIM To explore the role played by APOE genotype/alleles on physiological and pathological brain aging. MATERIALS AND METHODS The study was conducted in a cohort of centenarians (n = 106), and two cohorts of octogenarians (without cognitive decline, n = 351 controls; and with AD, n = 294). RESULTS No significant differences in genotype/allele distributions were observed comparing controls to centenarians. The prevalence of ε2/ε3, ε3/ε3, ε3/ε4 and ε4/ε4 genotypes were significantly different in centenarians compared to AD. The prevalence of ε2 and ε3 alleles were significantly higher in centenarians, whereas the ε4 was less frequent. The ε4 allele was positively associated with AD, whereas a negative association was found for ε2 and ε3 alleles. CONCLUSIONS Our study indicates that ε4 allele is strongly associated with AD. APOE significantly affects AD risk, but apparently not longevity.
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Affiliation(s)
- E Ferri
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy.
| | - C Gussago
- Department of Clinical Sciences and Community Health, University of Milan, Via Pace 9, 20122 Milan, Italy.
| | - M Casati
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy.
| | - D Mari
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Via Pace 9, 20122 Milan, Italy.
| | - P D Rossi
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy.
| | - S Ciccone
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy.
| | - M Cesari
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Via Pace 9, 20122 Milan, Italy.
| | - B Arosio
- Geriatric Unit, Fondazione IRCCS Ca' Granda Ospedale Maggiore Policlinico, Via Pace 9, 20122 Milan, Italy; Department of Clinical Sciences and Community Health, University of Milan, Via Pace 9, 20122 Milan, Italy.
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