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Chermside-Scabbo CJ, Shuster JT, Erdmann-Gilmore P, Tycksen E, Zhang Q, Townsend RR, Silva MJ. A proteomics approach to study mouse long bones: examining baseline differences and mechanical loading-induced bone formation in young-adult and old mice. Aging (Albany NY) 2024; 16:12726-12768. [PMID: 39400554 PMCID: PMC11501390 DOI: 10.18632/aging.206131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2023] [Accepted: 09/23/2024] [Indexed: 10/15/2024]
Abstract
With aging, bone mass declines and the anabolic effects of skeletal loading diminish. While much research has focused on gene transcription, how bone ages and loses its mechanoresponsiveness at the protein level remains unclear. We developed a novel proteomics approach and performed a paired mass spectrometry and RNA-seq analysis on tibias from young-adult (5-month) and old (22-month) mice. We report the first correlation estimate between the bone proteome and transcriptome (Spearman ρ = 0.40), which is in line with other tissues but indicates that a relatively low amount of variation in protein levels is explained by the variation in transcript levels. Of 71 shared targets that differed with age, eight were associated with bone mineral density in previous GWAS, including understudied targets Asrgl1 and Timp2. We used complementary RNA in situ hybridization to confirm that Asrgl1 and Timp2 had reduced expression in osteoblasts/osteocytes in old bones. We also found evidence for reduced TGF-beta signaling with aging, in particular Tgfb2. Next, we defined proteomic changes following mechanical loading. At the protein level, bone differed more with age than with loading, and aged bone had fewer loading-induced changes. Overall, our findings underscore the need for complementary protein-level assays in skeletal biology research.
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Affiliation(s)
- Christopher J. Chermside-Scabbo
- Department of Orthopaedic Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
- Medical Scientist Training Program, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - John T. Shuster
- Department of Orthopaedic Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Petra Erdmann-Gilmore
- Department of Medicine, Proteomics Core, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Eric Tycksen
- Department of Genetics, McDonnell Genome Institute, Washington University School of Medicine, St. Louis, MO 63108, USA
| | - Qiang Zhang
- Department of Medicine, Proteomics Core, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - R. Reid Townsend
- Department of Medicine, Proteomics Core, Washington University School of Medicine, St. Louis, MO 63110, USA
| | - Matthew J. Silva
- Department of Orthopaedic Surgery, Washington University School of Medicine, St. Louis, MO 63110, USA
- Department of Biomedical Engineering, Washington University, St. Louis, MO 63105, USA
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Xu J, Duan J, Cai Z, Arai C, Di C, Venters CC, Xu J, Jones M, So BR, Dreyfuss G. TOMM40-APOE chimera linking Alzheimer's highest risk genes: a new pathway for mitochondria regulation and APOE4 pathogenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.10.09.617477. [PMID: 39416128 PMCID: PMC11482918 DOI: 10.1101/2024.10.09.617477] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/19/2024]
Abstract
The patho-mechanism of apolipoprotein variant, APOE4, the strongest genetic risk for late-onset Alzheimer's disease (AD) and longevity, remains unclear. APOE's neighboring gene, TOMM40 (mitochondria protein transport channel), is associated with brain trauma outcome and aging-related cognitive decline, however its role in AD APOE4-independently is controversial. We report that TOMM40 is prone to transcription readthrough into APOE that can generate spliced TOMM40-APOE mRNA chimera (termed T9A2) detected in human neurons and other cells and tissues. T9A2 translation tethers APOE (normal APOE3 or APOE4) to near-full-length TOM40 that is targeted to mitochondria. Importantly, T9A2-APOE3 boosts mitochondrial bioenergetic capacity and decreases oxidative stress significantly more than T9A2-APOE4 and APOE3, and lacking in APOE4. We describe detailed interactomes of these actors that may inform about the activities and roles in pathogenesis. T9A2 uncovers a new candidate pathway for mitochondria regulation and oxidative stress-protection that are impaired in APOE4 genotypes and could initiate neurodegeneration.
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Bian Z, Wang L, Fan R, Sun J, Yu L, Xu M, Timmers PRHJ, Shen X, Wilson JF, Theodoratou E, Wu X, Li X. Genetic predisposition, modifiable lifestyles, and their joint effects on human lifespan: evidence from multiple cohort studies. BMJ Evid Based Med 2024; 29:255-263. [PMID: 38684374 DOI: 10.1136/bmjebm-2023-112583] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 03/15/2024] [Indexed: 05/02/2024]
Abstract
OBJECTIVE To investigate the associations across genetic and lifestyle factors with lifespan. DESIGN A longitudinal cohort study. SETTING UK Biobank. PARTICIPANTS 353 742 adults of European ancestry, who were recruited from 2006 to 2010 and were followed up until 2021. EXPOSURES A polygenic risk score for lifespan with long (highest quintile) risk categories and a weighted healthy lifestyle score, including no current smoking, moderate alcohol consumption, regular physical activity, healthy body shape, adequate sleep duration, and a healthy diet, categorised into favourable, intermediate, and unfavourable lifestyles. MAIN OUTCOME MEASURES Lifespan defined as the date of death or the censor date minus the date of birth. RESULTS Of the included 353 742 participants of European ancestry with a median follow-up of 12.86 years, 24 239 death cases were identified. Participants were grouped into three genetically determined lifespan categories including long (20.1%), intermediate (60.1%), and short (19.8%), and into three lifestyle score categories including favourable (23.1%), intermediate (55.6%), and unfavourable (21.3%). The hazard ratio (HR) of death for individuals with a genetic predisposition to a short lifespan was 1.21 (95% CI 1.16 to 1.26) compared to those with a genetic predisposition to a long lifespan. The HR of death for individuals in the unfavourable lifestyle category was 1.78 (95% CI 1.71 to 1.85), compared with those in the favourable lifestyle category. Participants with a genetic predisposition to a short lifespan and an unfavourable lifestyle had 2.04 times (95% CI 1.87 to 2.22) higher rates of death compared with those with a genetic predisposition to a long lifespan and a favourable lifestyle. No multiplicative interaction was detected between the polygenic risk score of lifespan and the weighted healthy lifestyle score (p=0.10). The optimal combination of healthy lifestyles, including never smoking, regular physical activity, adequate sleep duration, and a healthy diet, was derived to decrease risk of premature death (death before 75 years). CONCLUSION Genetic and lifestyle factors were independently associated with lifespan. Adherence to healthy lifestyles could largely attenuate the genetic risk of a shorter lifespan or premature death. The optimal combination of healthy lifestyles could convey better benefits for a longer lifespan, regardless of genetic background.
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Affiliation(s)
- Zilong Bian
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Lijuan Wang
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Rong Fan
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Department of Biostatistics, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Jing Sun
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Lili Yu
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Meihong Xu
- Department of Nutrition and Food Hygiene, School of Public Health, Peking University, Beijing, China
| | - Paul R H J Timmers
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xia Shen
- Department of Biostatistics, School of Public Health and The Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - James F Wilson
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- MRC Human Genetics Unit, MRC Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Evropi Theodoratou
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
- Cancer Research UK Edinburgh Centre, Medical Research Council Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - Xifeng Wu
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- The Key Laboratory of Intelligent Preventive Medicine of Zhejiang Province, Hangzhou, China
| | - Xue Li
- Department of Big Data in Health Science, School of Public Health and Center of Clinical Big Data and Analytics of The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
- Centre for Global Health, Usher Institute, University of Edinburgh, Edinburgh, UK
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Tseng WHS, Chattopadhyay A, Phan NN, Chuang EY, Lee OK. Utilizing multimodal approach to identify candidate pathways and biomarkers and predicting frailty syndrome in individuals from UK Biobank. GeroScience 2024; 46:1211-1228. [PMID: 37523034 PMCID: PMC10828416 DOI: 10.1007/s11357-023-00874-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/05/2023] [Accepted: 07/12/2023] [Indexed: 08/01/2023] Open
Abstract
Frailty, a prevalent clinical syndrome in aging adults, is characterized by poor health outcomes, represented via a standardized frailty-phenotype (FP), and Frailty Index (FI). While the relevance of the syndrome is gaining awareness, much remains unclear about its underlying biology. Further elucidation of the genetic determinants and possible underlying mechanisms may help improve patients' outcomes allowing healthy aging.Genotype, clinical and demographic data of subjects (aged 60-73 years) from UK Biobank were utilized. FP was defined on Fried's criteria. FI was calculated using electronic-health-records. Genome-wide-association-studies (GWAS) were conducted and polygenic-risk-scores (PRS) were calculated for both FP and FI. Functional analysis provided interpretations of underlying biology. Finally, machine-learning (ML) models were trained using clinical, demographic and PRS towards identifying frail from non-frail individuals.Thirty-one loci were significantly associated with FI accounting for 12% heritability. Seventeen of those were known associations for body-mass-index, coronary diseases, cholesterol-levels, and longevity, while the rest were novel. Significant genes CDKN2B and APOE, previously implicated in aging, were reported to be enriched in lipoprotein-particle-remodeling. Linkage-disequilibrium-regression identified specific regulation in limbic-system, associated with long-term memory and cognitive-function. XGboost was established as the best performing ML model with area-under-curve as 85%, sensitivity and specificity as 0.75 and 0.8, respectively.This study provides novel insights into increased vulnerability and risk stratification of frailty syndrome via a multi-modal approach. The findings suggest frailty as a highly polygenic-trait, enriched in cholesterol-remodeling and metabolism and to be genetically associated with cognitive abilities. ML models utilizing FP and FI + PRS were established that identified frailty-syndrome patients with high accuracy.
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Affiliation(s)
- Watson Hua-Sheng Tseng
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan
| | - Amrita Chattopadhyay
- Bioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan.
| | - Nam Nhut Phan
- Bioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan
| | - Eric Y Chuang
- Bioinformatics and Biostatistics Core, Centers of Genomic and Precision Medicine, National Taiwan University, Taipei, Taiwan
- Graduate Institute of Biomedical Electronics and Bioinformatics, Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan
- Biomedical Technology and Device Research Laboratories, Industrial Technology Research Institute, Hsinchu, Taiwan
| | - Oscar K Lee
- Institute of Clinical Medicine, National Yang Ming Chiao Tung University, Taipei, Taiwan.
- Center for Translational Genomics and Regenerative Medicine, China Medical University Hospital, Taichung, Taiwan.
- Stem Cell Research Center, National Yang Ming Chiao Tung University, Taipei, Taiwan.
- Department of Orthopedics, China Medical University Hospital, Taichung, Taiwan.
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5
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Sánchez-Valle J, Valencia A. Molecular bases of comorbidities: present and future perspectives. Trends Genet 2023; 39:773-786. [PMID: 37482451 DOI: 10.1016/j.tig.2023.06.003] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/13/2023] [Revised: 06/12/2023] [Accepted: 06/12/2023] [Indexed: 07/25/2023]
Abstract
Co-occurrence of diseases decreases patient quality of life, complicates treatment choices, and increases mortality. Analyses of electronic health records present a complex scenario of comorbidity relationships that vary by age, sex, and cohort under study. The study of similarities between diseases using 'omics data, such as genes altered in diseases, gene expression, proteome, and microbiome, are fundamental to uncovering the origin of, and potential treatment for, comorbidities. Recent studies have produced a first generation of genetic interpretations for as much as 46% of the comorbidities described in large cohorts. Integrating different sources of molecular information and using artificial intelligence (AI) methods are promising approaches for the study of comorbidities. They may help to improve the treatment of comorbidities, including the potential repositioning of drugs.
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Affiliation(s)
- Jon Sánchez-Valle
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain.
| | - Alfonso Valencia
- Life Sciences Department, Barcelona Supercomputing Center, Barcelona, 08034, Spain; ICREA, Barcelona, 08010, Spain.
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6
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Rosoff DB, Mavromatis LA, Bell AS, Wagner J, Jung J, Marioni RE, Davey Smith G, Horvath S, Lohoff FW. Multivariate genome-wide analysis of aging-related traits identifies novel loci and new drug targets for healthy aging. NATURE AGING 2023; 3:1020-1035. [PMID: 37550455 PMCID: PMC10432278 DOI: 10.1038/s43587-023-00455-5] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 06/07/2023] [Indexed: 08/09/2023]
Abstract
The concept of aging is complex, including many related phenotypes such as healthspan, lifespan, extreme longevity, frailty and epigenetic aging, suggesting shared biological underpinnings; however, aging-related endpoints have been primarily assessed individually. Using data from these traits and multivariate genome-wide association study methods, we modeled their underlying genetic factor ('mvAge'). mvAge (effective n = ~1.9 million participants of European ancestry) identified 52 independent variants in 38 genomic loci. Twenty variants were novel (not reported in input genome-wide association studies). Transcriptomic imputation identified age-relevant genes, including VEGFA and PHB1. Drug-target Mendelian randomization with metformin target genes showed a beneficial impact on mvAge (P value = 8.41 × 10-5). Similarly, genetically proxied thiazolidinediones (P value = 3.50 × 10-10), proprotein convertase subtilisin/kexin 9 inhibition (P value = 1.62 × 10-6), angiopoietin-like protein 4, beta blockers and calcium channel blockers also had beneficial Mendelian randomization estimates. Extending the drug-target Mendelian randomization framework to 3,947 protein-coding genes prioritized 122 targets. Together, these findings will inform future studies aimed at improving healthy aging.
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Affiliation(s)
- Daniel B Rosoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
- NIH-Oxford-Cambridge Scholars Program; Radcliffe Department of Medicine, University of Oxford, Oxford, UK
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Lucas A Mavromatis
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Andrew S Bell
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Josephin Wagner
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Jeesun Jung
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA
| | - Riccardo E Marioni
- Centre for Genomic and Experimental Medicine, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit at the University of Bristol, Bristol, UK
| | - Steve Horvath
- Department of Biostatistics, Fielding School of Public Health, University of California Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, David Geffen School of Medicine, University of California Los Angeles, Los Angeles, CA, USA
- San Diego Institute of Science, Alto Labs, San Diego, CA, USA
| | - Falk W Lohoff
- Section on Clinical Genomics and Experimental Therapeutics, National Institute on Alcohol Abuse and Alcoholism, National Institutes of Health, Bethesda, MD, USA.
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7
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Salazar J, Durán P, Díaz MP, Chacín M, Santeliz R, Mengual E, Gutiérrez E, León X, Díaz A, Bernal M, Escalona D, Hernández LAP, Bermúdez V. Exploring the Relationship between the Gut Microbiota and Ageing: A Possible Age Modulator. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2023; 20:5845. [PMID: 37239571 PMCID: PMC10218639 DOI: 10.3390/ijerph20105845] [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: 02/19/2023] [Revised: 03/20/2023] [Accepted: 05/08/2023] [Indexed: 05/28/2023]
Abstract
The gut microbiota (GM) has been the subject of intense research in recent years. Therefore, numerous factors affecting its composition have been thoroughly examined, and with them, their function and role in the individual's systems. The gut microbiota's taxonomical composition dramatically impacts older adults' health status. In this regard, it could either extend their life expectancy via the modulation of metabolic processes and the immune system or, in the case of dysbiosis, predispose them to age-related diseases, including bowel inflammatory and musculoskeletal diseases and metabolic and neurological disorders. In general, the microbiome of the elderly tends to present taxonomic and functional changes, which can function as a target to modulate the microbiota and improve the health of this population. The GM of centenarians is unique, with the faculty-promoting metabolic pathways capable of preventing and counteracting the different processes associated with age-related diseases. The molecular mechanisms by which the microbiota can exhibit anti-ageing properties are mainly based on anti-inflammatory and antioxidant actions. This review focuses on analysing the current knowledge of gut microbiota characteristics and modifiers, its relationship with ageing, and the GM-modulating approaches to increase life expectancy.
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Affiliation(s)
- Juan Salazar
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Pablo Durán
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - María P. Díaz
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Maricarmen Chacín
- Centro de Investigaciones en Ciencias de la Vida, Universidad Simón Bolívar, Barranquilla 080002, Colombia
- Sociedad Internacional de Rejuvenecimiento Facial No Quirúrgico (SIRF), Barranquilla 080002, Colombia
| | - Raquel Santeliz
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Edgardo Mengual
- Biological Research Institute “Doctors Orlando Castejon and Haydee V Castejon”, Faculty of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Emma Gutiérrez
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Xavier León
- Instituto Ecuatoriano de Seguridad Social, Cuenca 010101, Ecuador
| | - Andrea Díaz
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | - Marycarlota Bernal
- Facultad de Ingenierias, Universidad Simón Bolívar, Cúcuta 540001, Colombia
| | - Daniel Escalona
- Endocrine and Metabolic Diseases Research Center, School of Medicine, University of Zulia, Maracaibo 4001, Venezuela
| | | | - Valmore Bermúdez
- Centro de Investigaciones en Ciencias de la Vida, Universidad Simón Bolívar, Barranquilla 080002, Colombia
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8
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Elhaik E. Principal Component Analyses (PCA)-based findings in population genetic studies are highly biased and must be reevaluated. Sci Rep 2022; 12:14683. [PMID: 36038559 PMCID: PMC9424212 DOI: 10.1038/s41598-022-14395-4] [Citation(s) in RCA: 30] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2022] [Accepted: 06/06/2022] [Indexed: 12/29/2022] Open
Abstract
Principal Component Analysis (PCA) is a multivariate analysis that reduces the complexity of datasets while preserving data covariance. The outcome can be visualized on colorful scatterplots, ideally with only a minimal loss of information. PCA applications, implemented in well-cited packages like EIGENSOFT and PLINK, are extensively used as the foremost analyses in population genetics and related fields (e.g., animal and plant or medical genetics). PCA outcomes are used to shape study design, identify, and characterize individuals and populations, and draw historical and ethnobiological conclusions on origins, evolution, dispersion, and relatedness. The replicability crisis in science has prompted us to evaluate whether PCA results are reliable, robust, and replicable. We analyzed twelve common test cases using an intuitive color-based model alongside human population data. We demonstrate that PCA results can be artifacts of the data and can be easily manipulated to generate desired outcomes. PCA adjustment also yielded unfavorable outcomes in association studies. PCA results may not be reliable, robust, or replicable as the field assumes. Our findings raise concerns about the validity of results reported in the population genetics literature and related fields that place a disproportionate reliance upon PCA outcomes and the insights derived from them. We conclude that PCA may have a biasing role in genetic investigations and that 32,000-216,000 genetic studies should be reevaluated. An alternative mixed-admixture population genetic model is discussed.
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Affiliation(s)
- Eran Elhaik
- Department of Biology, Lund University, 22362, Lund, Sweden.
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9
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Co-Inheritance of Variation in All-Cause Mortality and Biochemical Risk Factors. Twin Res Hum Genet 2022; 25:107-114. [PMID: 35818962 DOI: 10.1017/thg.2022.25] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
Biomarkers may be useful endophenotypes for genetic studies if they share genetic sources of variation with the outcome, for example, with all-cause mortality. Australian adult study participants who had reported their parental survival information were included in the study: 14,169 participants had polygenic risk scores (PRS) from genotyping and up to 13,365 had biomarker results. We assessed associations between participants' biomarker results and parental survival, and between biomarker results and eight parental survival PRS at varying p-value cut-offs. Survival in parents was associated with participants' serum bilirubin, C-reactive protein, HDL cholesterol, triglycerides and uric acid, and with LDL cholesterol for participants' fathers but not for their mothers. PRS for all-cause mortality were associated with liver function tests (alkaline phosphatase, butyrylcholinesterase, gamma-glutamyl transferase), metabolic tests (LDL and HDL cholesterol, triglycerides, uric acid), and acute-phase reactants (C-reactive protein, globulins). Association between offspring biomarker results and parental survival demonstrates the existence of familial effects common to both, while associations between biomarker results and PRS for mortality favor at least a partial genetic cause of this covariation. Identification of genetic loci affecting mortality-associated biomarkers offers a route to the identification of additional loci affecting mortality.
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10
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Nutrient-Response Pathways in Healthspan and Lifespan Regulation. Cells 2022; 11:cells11091568. [PMID: 35563873 PMCID: PMC9102925 DOI: 10.3390/cells11091568] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/02/2022] [Accepted: 05/05/2022] [Indexed: 02/01/2023] Open
Abstract
Cellular, small invertebrate and vertebrate models are a driving force in biogerontology studies. Using various models, such as yeasts, appropriate tissue culture cells, Drosophila, the nematode Caenorhabditis elegans and the mouse, has tremendously increased our knowledge around the relationship between diet, nutrient-response signaling pathways and lifespan regulation. In recent years, combinatorial drug treatments combined with mutagenesis, high-throughput screens, as well as multi-omics approaches, have provided unprecedented insights in cellular metabolism, development, differentiation, and aging. Scientists are, therefore, moving towards characterizing the fine architecture and cross-talks of growth and stress pathways towards identifying possible interventions that could lead to healthy aging and the amelioration of age-related diseases in humans. In this short review, we briefly examine recently uncovered knowledge around nutrient-response pathways, such as the Insulin Growth Factor (IGF) and the mechanistic Target of Rapamycin signaling pathways, as well as specific GWAS and some EWAS studies on lifespan and age-related disease that have enhanced our current understanding within the aging and biogerontology fields. We discuss what is learned from the rich and diverse generated data, as well as challenges and next frontiers in these scientific disciplines.
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11
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Genome-Wide Association Study of Fluorescent Oxidation Products Accounting for Tobacco Smoking Status in Adults from the French EGEA Study. Antioxidants (Basel) 2022; 11:antiox11050802. [PMID: 35624665 PMCID: PMC9137810 DOI: 10.3390/antiox11050802] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/17/2022] [Revised: 04/13/2022] [Accepted: 04/18/2022] [Indexed: 12/14/2022] Open
Abstract
Oxidative stress (OS) is the main pathophysiological mechanism involved in several chronic diseases, including asthma. Fluorescent oxidation products (FlOPs), a global biomarker of damage due to OS, is of growing interest in epidemiological studies. We conducted a genome-wide association study (GWAS) of the FlOPs level in 1216 adults from the case-control and family-based EGEA study (mean age 43 years old, 51% women, and 23% current smokers) to identify genetic variants associated with FlOPs. The GWAS was first conducted in the whole sample and then stratified according to smoking status, the main exogenous source of reactive oxygen species. Among the top genetic variants identified by the three GWAS, those located in BMP6 (p = 3 × 10−6), near BMPER (p = 9 × 10−6), in GABRG3 (p = 4 × 10−7), and near ATG5 (p = 2 × 10−9) are the most relevant because of both their link to biological pathways related to OS and their association with several chronic diseases for which the role of OS in their pathophysiology has been pointed out. BMP6 and BMPER are of particular interest due to their involvement in the same biological pathways related to OS and their functional interaction. To conclude, this study, which is the first GWAS of FlOPs, provides new insights into the pathophysiology of chronic OS-related diseases.
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12
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Liu JZ, Chen CY, Tsai EA, Whelan CD, Sexton D, John S, Runz H. The burden of rare protein-truncating genetic variants on human lifespan. NATURE AGING 2022; 2:289-294. [PMID: 37117740 PMCID: PMC10154195 DOI: 10.1038/s43587-022-00182-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/13/2021] [Accepted: 01/20/2022] [Indexed: 04/30/2023]
Abstract
Genetic predisposition has been shown to contribute substantially to the age at which we die. Genome-wide association studies (GWASs) have linked more than 20 loci to phenotypes related to human lifespan1. However, little is known about how lifespan is impacted by gene loss of function. Through whole-exome sequencing of 352,338 UK Biobank participants of European ancestry, we assessed the relevance of protein-truncating variant (PTV) gene burden on individual and parental survival. We identified four exome-wide significant (P < 4.2 × 10-7) human lifespan genes, BRCA1, BRCA2, ATM and TET2. Gene and gene-set, PTV-burden, phenome-wide association studies support known roles of these genes in cancer to impact lifespan at the population level. The TET2 PTV burden was associated with a lifespan through somatic mutation events presumably due to clonal hematopoiesis. The overlap between PTV burden and common variant-based lifespan GWASs was modest, underscoring the value of exome sequencing in well-powered biobank cohorts to complement GWASs for identifying genes underlying complex traits.
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Affiliation(s)
- Jimmy Z Liu
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA.
| | - Chia-Yen Chen
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA
| | - Ellen A Tsai
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA
| | | | - David Sexton
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA
| | - Sally John
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA
| | - Heiko Runz
- Translational Biology, Research & Development, Biogen Inc., Cambridge, MA, USA.
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13
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Noren Hooten N, Pacheco NL, Smith JT, Evans MK. The accelerated aging phenotype: The role of race and social determinants of health on aging. Ageing Res Rev 2022; 73:101536. [PMID: 34883202 PMCID: PMC10862389 DOI: 10.1016/j.arr.2021.101536] [Citation(s) in RCA: 62] [Impact Index Per Article: 31.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2021] [Revised: 11/12/2021] [Accepted: 12/03/2021] [Indexed: 02/06/2023]
Abstract
The pursuit to discover the fundamental biology and mechanisms of aging within the context of the physical and social environment is critical to designing interventions to prevent and treat its complex phenotypes. Aging research is critically linked to understanding health disparities because these inequities shape minority aging, which may proceed on a different trajectory than the overall population. Health disparities are characteristically seen in commonly occurring age-associated diseases such as cardiovascular and cerebrovascular disease as well as diabetes mellitus and cancer. The early appearance and increased severity of age-associated disease among African American and low socioeconomic status (SES) individuals suggests that the factors contributing to the emergence of health disparities may also induce a phenotype of 'premature aging' or 'accelerated aging' or 'weathering'. In marginalized and low SES populations with high rates of early onset age-associated disease the interaction of biologic, psychosocial, socioeconomic and environmental factors may result in a phenotype of accelerated aging biologically similar to premature aging syndromes with increased susceptibility to oxidative stress, premature accumulation of oxidative DNA damage, defects in DNA repair and higher levels of biomarkers of oxidative stress and inflammation. Health disparities, therefore, may be the end product of this complex interaction in populations at high risk. This review will examine the factors that drive both health disparities and the accelerated aging phenotype that ultimately contributes to premature mortality.
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Affiliation(s)
- Nicole Noren Hooten
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD 21224, USA
| | - Natasha L Pacheco
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD 21224, USA
| | - Jessica T Smith
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD 21224, USA
| | - Michele K Evans
- Laboratory of Epidemiology and Population Science, National Institute on Aging, National Institutes of Health, 251 Bayview Boulevard, Baltimore, MD 21224, USA.
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14
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Khorrami MS, Sadabadi F, Pasdar A, Safarian-Bana H, Amerizadeh F, Esmaeily H, Moohebati M, Heidari-Bakavoli A, Ferns G, Ghayour-Mobarhan M, Avan A. A Genetic Variant in Proline and Serine Rich Coiled-Coil 1 Gene Is Associated with the Risk of Cardiovascular Disease. Rep Biochem Mol Biol 2022; 10:653-663. [PMID: 35291603 PMCID: PMC8903358 DOI: 10.52547/rbmb.10.4.653] [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: 07/28/2021] [Accepted: 09/06/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Cardiovascular disease is one of the most common causes of morbidity and mortality worldwide. The Proline and Serine Rich Coiled-Coil 1 gene in 1p13.3 locus has been reported to be associated with low density lipoprotein cholesterol (LDL-C) and coronary artery disease (CAD). The objective of this study was to investigate the association between the rs599839 polymorphism of the Proline and Serine Rich Coiled-Coil 1 (PSRC1) gene with CVD outcomes in a population sample recruited as part of the Mashhad-Stroke and Heart-Atherosclerotic-Disorders (MASHAD) cohort. METHODS Five hundred and nine individuals who had an average follow-up period of 10 years were enrolled as part of the MASHAD cohort. DNA was extracted and genotyped using the TaqMan-real-time-PCR based method. RESULTS The study found individuals with GA/GG genotypes were at a higher risk of CVDs (OR= 4.7; 95% CI, 2.5-8.7; p< 0.001) in comparison to those with AA genotype; however, the result was not significant for GG genotype data. CONCLUSION The results suggest that the GA/GG genotypes of the PSRC1gene locus were at increased risk of CVD in a representative population-based cohort, demonstrating further functional analysis to discover the value of emerging marker as a risk stratification biomarker to recognize high risk cases.
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Affiliation(s)
- Mohammad Sadegh Khorrami
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Fatemeh Sadabadi
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Alireza Pasdar
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Hamide Safarian-Bana
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Forouzan Amerizadeh
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Habibollah Esmaeily
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
- Department of Epidemiology and Biostatistics, School of Health, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Mohsen Moohebati
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
| | | | - Gordon Ferns
- Brighton & Sussex Medical School, Division of Medical Education, Falmer, Brighton, Sussex, UK.
| | - Majid Ghayour-Mobarhan
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
| | - Amir Avan
- Department of Medical Genetics and Molecular Medicine, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
- Metabolic Syndrome Research center, Mashhad University of Medical Sciences, Mashhad, Iran.
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15
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Kondratyev NV, Alfimova MV, Golov AK, Golimbet VE. Bench Research Informed by GWAS Results. Cells 2021; 10:3184. [PMID: 34831407 PMCID: PMC8623533 DOI: 10.3390/cells10113184] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2021] [Revised: 11/11/2021] [Accepted: 11/11/2021] [Indexed: 12/15/2022] Open
Abstract
Scientifically interesting as well as practically important phenotypes often belong to the realm of complex traits. To the extent that these traits are hereditary, they are usually 'highly polygenic'. The study of such traits presents a challenge for researchers, as the complex genetic architecture of such traits makes it nearly impossible to utilise many of the usual methods of reverse genetics, which often focus on specific genes. In recent years, thousands of genome-wide association studies (GWAS) were undertaken to explore the relationships between complex traits and a large number of genetic factors, most of which are characterised by tiny effects. In this review, we aim to familiarise 'wet biologists' with approaches for the interpretation of GWAS results, to clarify some issues that may seem counterintuitive and to assess the possibility of using GWAS results in experiments on various complex traits.
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Affiliation(s)
| | | | - Arkadiy K. Golov
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
- Institute of Gene Biology, Russian Academy of Sciences, 119334 Moscow, Russia
| | - Vera E. Golimbet
- Mental Health Research Center, 115522 Moscow, Russia; (M.V.A.); (A.K.G.); (V.E.G.)
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16
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Raj Kolora SR, Owens GL, Vazquez JM, Stubbs A, Chatla K, Jainese C, Seeto K, McCrea M, Sandel MW, Vianna JA, Maslenikov K, Bachtrog D, Orr JW, Love M, Sudmant PH. Origins and evolution of extreme life span in Pacific Ocean rockfishes. Science 2021; 374:842-847. [PMID: 34762458 PMCID: PMC8923369 DOI: 10.1126/science.abg5332] [Citation(s) in RCA: 45] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
Abstract
Pacific Ocean rockfishes (genus Sebastes) exhibit extreme variation in life span, with some species being among the most long-lived extant vertebrates. We de novo assembled the genomes of 88 rockfish species and from these identified repeated signatures of positive selection in DNA repair pathways in long-lived taxa and 137 longevity-associated genes with direct effects on life span through insulin signaling and with pleiotropic effects through size and environmental adaptations. A genome-wide screen of structural variation reveals copy number expansions in the immune modulatory butyrophilin gene family in long-lived species. The evolution of different rockfish life histories is coupled to genetic diversity and reshapes the mutational spectrum driving segregating CpG→TpG variants in long-lived species. These analyses highlight the genetic innovations that underlie life history trait adaptations and, in turn, how they shape genomic diversity.
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Affiliation(s)
| | - Gregory L. Owens
- University of California Berkeley Department of Integrative Biology
- University of Victoria Department of Biology
| | | | - Alexander Stubbs
- University of California Berkeley Department of Integrative Biology
| | - Kamalakar Chatla
- University of California Berkeley Department of Integrative Biology
| | - Conner Jainese
- University of California Santa Barbara Marine Sciences Institute
| | - Katelin Seeto
- University of California Santa Barbara Marine Sciences Institute
| | - Merit McCrea
- University of California Santa Barbara Marine Sciences Institute
| | | | - Juliana A. Vianna
- Pontificia Universidad Católica de Chile, Departamento de Ecosistemas y Medio Ambiente
| | - Katherine Maslenikov
- University of Washington, School of Aquatic and Fishery Sciences and Burke Museum of Natural History and Culture
| | - Doris Bachtrog
- University of California Berkeley Department of Integrative Biology
| | - James W. Orr
- University of Washington, School of Aquatic and Fishery Sciences and Burke Museum of Natural History and Culture
| | - Milton Love
- University of California Santa Barbara Marine Sciences Institute
| | - Peter H. Sudmant
- University of California Berkeley Department of Integrative Biology
- University of California Berkeley Center for Computational Biology
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17
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Kaya A, Phua CZJ, Lee M, Wang L, Tyshkovskiy A, Ma S, Barre B, Liu W, Harrison BR, Zhao X, Zhou X, Wasko BM, Bammler TK, Promislow DEL, Kaeberlein M, Gladyshev VN. Evolution of natural lifespan variation and molecular strategies of extended lifespan in yeast. eLife 2021; 10:e64860. [PMID: 34751131 PMCID: PMC8612763 DOI: 10.7554/elife.64860] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2020] [Accepted: 11/04/2021] [Indexed: 01/29/2023] Open
Abstract
To understand the genetic basis and selective forces acting on longevity, it is useful to examine lifespan variation among closely related species, or ecologically diverse isolates of the same species, within a controlled environment. In particular, this approach may lead to understanding mechanisms underlying natural variation in lifespan. Here, we analyzed 76 ecologically diverse wild yeast isolates and discovered a wide diversity of replicative lifespan (RLS). Phylogenetic analyses pointed to genes and environmental factors that strongly interact to modulate the observed aging patterns. We then identified genetic networks causally associated with natural variation in RLS across wild yeast isolates, as well as genes, metabolites, and pathways, many of which have never been associated with yeast lifespan in laboratory settings. In addition, a combined analysis of lifespan-associated metabolic and transcriptomic changes revealed unique adaptations to interconnected amino acid biosynthesis, glutamate metabolism, and mitochondrial function in long-lived strains. Overall, our multiomic and lifespan analyses across diverse isolates of the same species shows how gene-environment interactions shape cellular processes involved in phenotypic variation such as lifespan.
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Affiliation(s)
- Alaattin Kaya
- Department of Biology, Virginia Commonwealth UniversityRichmondUnited States
| | - Cheryl Zi Jin Phua
- Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
| | - Mitchell Lee
- Department of Laboratory Medicine and Pathology, University of WashingtonSeattleUnited States
| | - Lu Wang
- Department of Environmental and Occupational Health Sciences, University of WashingtonSeattleUnited States
| | - Alexander Tyshkovskiy
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical SchoolBostonUnited States
- Belozersky Institute of Physico-Chemical Biology, Moscow State UniversityMoscowRussian Federation
| | - Siming Ma
- Genetics, Genome Institute of Singapore, Agency for Science, Technology and Research (A*STAR)SingaporeSingapore
| | - Benjamin Barre
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical SchoolBostonUnited States
| | - Weiqiang Liu
- Key Laboratory of Animal Ecology and Conservation Biology, Chinese Academy of Sciences, Institute of ZoologyBeijingChina
| | - Benjamin R Harrison
- Department of Laboratory Medicine and Pathology, University of WashingtonSeattleUnited States
| | - Xiaqing Zhao
- Department of Laboratory Medicine and Pathology, University of WashingtonSeattleUnited States
| | - Xuming Zhou
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical SchoolBostonUnited States
| | - Brian M Wasko
- Department of Biology, University of Houston - Clear LakeHoustonUnited States
| | - Theo K Bammler
- Department of Environmental and Occupational Health Sciences, University of WashingtonSeattleUnited States
| | - Daniel EL Promislow
- Department of Laboratory Medicine and Pathology, University of WashingtonSeattleUnited States
- Department of Biology, University of WashingtonSeattleUnited States
| | - Matt Kaeberlein
- Department of Laboratory Medicine and Pathology, University of WashingtonSeattleUnited States
| | - Vadim N Gladyshev
- Division of Genetics, Department of Medicine, Brigham and Women's Hospital, Harvard Medical SchoolBostonUnited States
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18
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Atkins JL, Jylhävä J, Pedersen NL, Magnusson PK, Lu Y, Wang Y, Hägg S, Melzer D, Williams DM, Pilling LC. A genome-wide association study of the frailty index highlights brain pathways in ageing. Aging Cell 2021; 20:e13459. [PMID: 34431594 PMCID: PMC8441299 DOI: 10.1111/acel.13459] [Citation(s) in RCA: 114] [Impact Index Per Article: 38.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2019] [Revised: 07/14/2021] [Accepted: 08/06/2021] [Indexed: 12/16/2022] Open
Abstract
Frailty is a common geriatric syndrome and strongly associated with disability, mortality and hospitalization. Frailty is commonly measured using the frailty index (FI), based on the accumulation of a number of health deficits during the life course. The mechanisms underlying FI are multifactorial and not well understood, but a genetic basis has been suggested with heritability estimates between 30 and 45%. Understanding the genetic determinants and biological mechanisms underpinning FI may help to delay or even prevent frailty. We performed a genome-wide association study (GWAS) meta-analysis of a frailty index in European descent UK Biobank participants (n = 164,610, 60-70 years) and Swedish TwinGene participants (n = 10,616, 41-87 years). FI calculation was based on 49 or 44 self-reported items on symptoms, disabilities and diagnosed diseases for UK Biobank and TwinGene, respectively. 14 loci were associated with the FI (p < 5*10-8 ). Many FI-associated loci have established associations with traits such as body mass index, cardiovascular disease, smoking, HLA proteins, depression and neuroticism; however, one appears to be novel. The estimated single nucleotide polymorphism (SNP) heritability of the FI was 11% (0.11, SE 0.005). In enrichment analysis, genes expressed in the frontal cortex and hippocampus were significantly downregulated (adjusted p < 0.05). We also used Mendelian randomization to identify modifiable traits and exposures that may affect frailty risk, with a higher educational attainment genetic risk score being associated with a lower degree of frailty. Risk of frailty is influenced by many genetic factors, including well-known disease risk factors and mental health, with particular emphasis on pathways in the brain.
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Affiliation(s)
- Janice L. Atkins
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
| | - Juulia Jylhävä
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- Department of PsychologyUniversity of Southern CaliforniaLos AngelesCAUSA
| | - Patrik K. Magnusson
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yi Lu
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Yunzhang Wang
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - Sara Hägg
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
| | - David Melzer
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
- Center on AgingUniversity of ConnecticutFarmingtonCTUSA
| | - Dylan M. Williams
- Department of Medical Epidemiology and BiostatisticsKarolinska InstitutetStockholmSweden
- MRC Unit for Lifelong Health and Ageing at UCLUniversity College LondonLondonUK
| | - Luke C. Pilling
- Epidemiology and Public Health GroupUniversity of Exeter Medical SchoolExeterUK
- Center on AgingUniversity of ConnecticutFarmingtonCTUSA
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19
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Vitiello D, Dakhovnik A, Statzer C, Ewald CY. Lifespan-Associated Gene Expression Signatures of Recombinant BXD Mice Implicates Coro7 and Set in Longevity. Front Genet 2021; 12:694033. [PMID: 34306034 PMCID: PMC8299419 DOI: 10.3389/fgene.2021.694033] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Accepted: 06/01/2021] [Indexed: 11/13/2022] Open
Abstract
Although genetic approaches have identified key genes and pathways that promote longevity, systems-level approaches are less utilized. Here, we took advantage of the wealth of omics data characterizing the BXD family of mice. We associated transcript and peptide levels across five tissues from both female and male BXD isogenic lines with their median lifespan. We identified over 5000 genes that showed a longevity correlation in a given tissue. Surprisingly, we found less than 1% overlap among longevity-correlating genes across tissues and sex. These 1% shared genes consist of 51 genes, of which 13 have been shown to alter lifespan. Only two genes -Coro7 and Set- showed a longevity correlation in all tissues and in both sexes. While differential regulation of aging across tissues and sex has been reported, our systems-level analysis reveals two unique genes that may promote healthy aging in unique sex- and tissue-agnostic manner.
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Affiliation(s)
| | | | | | - Collin Y. Ewald
- Laboratory of Extracellular Matrix Regeneration, Department of Health Sciences and Technology, Institute of Translational Medicine, ETH Zürich, Schwerzenbach, Switzerland
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20
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Treaster S, Karasik D, Harris MP. Footprints in the Sand: Deep Taxonomic Comparisons in Vertebrate Genomics to Unveil the Genetic Programs of Human Longevity. Front Genet 2021; 12:678073. [PMID: 34163529 PMCID: PMC8215702 DOI: 10.3389/fgene.2021.678073] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2021] [Accepted: 05/12/2021] [Indexed: 01/09/2023] Open
Abstract
With the modern quality, quantity, and availability of genomic sequencing across species, as well as across the expanse of human populations, we can screen for shared signatures underlying longevity and lifespan. Knowledge of these mechanisms would be medically invaluable in combating aging and age-related diseases. The diversity of longevities across vertebrates is an opportunity to look for patterns of genetic variation that may signal how this life history property is regulated, and ultimately how it can be modulated. Variation in human longevity provides a unique window to look for cases of extreme lifespan within a population, as well as associations across populations for factors that influence capacity to live longer. Current large cohort studies support the use of population level analyses to identify key factors associating with human lifespan. These studies are powerful in concept, but have demonstrated limited ability to resolve signals from background variation. In parallel, the expanding catalog of sequencing and annotation from diverse species, some of which have evolved longevities well past a human lifespan, provides independent cases to look at the genomic signatures of longevity. Recent comparative genomic work has shown promise in finding shared mechanisms associating with longevity among distantly related vertebrate groups. Given the genetic constraints between vertebrates, we posit that a combination of approaches, of parallel meta-analysis of human longevity along with refined analysis of other vertebrate clades having exceptional longevity, will aid in resolving key regulators of enhanced lifespan that have proven to be elusive when analyzed in isolation.
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Affiliation(s)
- Stephen Treaster
- Department of Orthopaedics, Boston Children's Hospital, Boston, MA, United States.,Department of Genetics, Harvard Medical School, Boston, MA, United States
| | - David Karasik
- Azrieli Faculty of Medicine, Bar-Ilan University, Ramat Gan, Israel.,Marcus Institute for Aging Research, Hebrew SeniorLife, Boston, MA, United States
| | - Matthew P Harris
- Department of Orthopaedics, Boston Children's Hospital, Boston, MA, United States.,Department of Genetics, Harvard Medical School, Boston, MA, United States
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21
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Johnston KJA, Ward J, Ray PR, Adams MJ, McIntosh AM, Smith BH, Strawbridge RJ, Price TJ, Smith DJ, Nicholl BI, Bailey MES. Sex-stratified genome-wide association study of multisite chronic pain in UK Biobank. PLoS Genet 2021; 17:e1009428. [PMID: 33830993 PMCID: PMC8031124 DOI: 10.1371/journal.pgen.1009428] [Citation(s) in RCA: 38] [Impact Index Per Article: 12.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2020] [Accepted: 02/16/2021] [Indexed: 12/30/2022] Open
Abstract
Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene, DCC, associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an rg of significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception.
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Affiliation(s)
- Keira J. A. Johnston
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
- Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland, United Kingdom
- School of Life Sciences, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Joey Ward
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Pradipta R. Ray
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, Texas, United States of America
| | - Mark J. Adams
- Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Andrew M. McIntosh
- Division of Psychiatry, University of Edinburgh, Edinburgh, Scotland, United Kingdom
| | - Blair H. Smith
- Division of Population Health Sciences, University of Dundee, Ninewells Hospital and Medical School, Dundee, Scotland, United Kingdom
| | - Rona J. Strawbridge
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
- Department of Medicine Solna, Karolinska Institute, Stockholm, Sweden
| | - Theodore J. Price
- School of Behavioral and Brain Sciences, The University of Texas at Dallas, Richardson, Texas, United States of America
| | - Daniel J. Smith
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Barbara I. Nicholl
- Institute of Health and Wellbeing, University of Glasgow, Glasgow, Scotland, United Kingdom
| | - Mark E. S. Bailey
- School of Life Sciences, College of Medical, Veterinary & Life Sciences, University of Glasgow, Glasgow, Scotland, United Kingdom
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22
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Sienski G, Narayan P, Bonner JM, Kory N, Boland S, Arczewska AA, Ralvenius WT, Akay L, Lockshin E, He L, Milo B, Graziosi A, Baru V, Lewis CA, Kellis M, Sabatini DM, Tsai LH, Lindquist S. APOE4 disrupts intracellular lipid homeostasis in human iPSC-derived glia. Sci Transl Med 2021; 13:eaaz4564. [PMID: 33658354 PMCID: PMC8218593 DOI: 10.1126/scitranslmed.aaz4564] [Citation(s) in RCA: 146] [Impact Index Per Article: 48.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2019] [Revised: 05/27/2020] [Accepted: 11/05/2020] [Indexed: 12/11/2022]
Abstract
The E4 allele of the apolipoprotein E gene (APOE) has been established as a genetic risk factor for many diseases including cardiovascular diseases and Alzheimer's disease (AD), yet its mechanism of action remains poorly understood. APOE is a lipid transport protein, and the dysregulation of lipids has recently emerged as a key feature of several neurodegenerative diseases including AD. However, it is unclear how APOE4 perturbs the intracellular lipid state. Here, we report that APOE4, but not APOE3, disrupted the cellular lipidomes of human induced pluripotent stem cell (iPSC)-derived astrocytes generated from fibroblasts of APOE4 or APOE3 carriers, and of yeast expressing human APOE isoforms. We combined lipidomics and unbiased genome-wide screens in yeast with functional and genetic characterization to demonstrate that human APOE4 induced altered lipid homeostasis. These changes resulted in increased unsaturation of fatty acids and accumulation of intracellular lipid droplets both in yeast and in APOE4-expressing human iPSC-derived astrocytes. We then identified genetic and chemical modulators of this lipid disruption. We showed that supplementation of the culture medium with choline (a soluble phospholipid precursor) restored the cellular lipidome to its basal state in APOE4-expressing human iPSC-derived astrocytes and in yeast expressing human APOE4 Our study illuminates key molecular disruptions in lipid metabolism that may contribute to the disease risk linked to the APOE4 genotype. Our study suggests that manipulating lipid metabolism could be a therapeutic approach to help alleviate the consequences of carrying the APOE4 allele.
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Affiliation(s)
- Grzegorz Sienski
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Priyanka Narayan
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
- Genetics and Biochemistry Branch, NIDDK, National Institutes of Health, Bethesda, MD 20814, USA
| | - Julia Maeve Bonner
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Nora Kory
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Sebastian Boland
- Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA
| | - Aleksandra A Arczewska
- Department of Stem Cell and Regenerative Biology, Harvard University, Cambridge, MA 02138, USA
| | - William T Ralvenius
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Leyla Akay
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Elana Lockshin
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Liang He
- Duke University, Durham, NC 27708, USA
| | - Blerta Milo
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Agnese Graziosi
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA
| | - Valeriya Baru
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Caroline A Lewis
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
| | - Manolis Kellis
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
| | - David M Sabatini
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA
- Koch Institute for Integrative Cancer Research and Massachusetts Institute of Technology, Department of Biology, Cambridge, MA 02139, USA
| | - Li-Huei Tsai
- Picower Institute for Learning and Memory, Department of Brain and Cognitive Sciences, MIT, Cambridge, MA 02139, USA.
- Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
| | - Susan Lindquist
- Whitehead Institute for Biomedical Research, Cambridge, MA 02142, USA
- Massachusetts Institute of Technology, Cambridge, MA 02142, USA
- Howard Hughes Medical Institute, Cambridge, MA 02139, USA
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23
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Meisner A, Kundu P, Zhang YD, Lan LV, Kim S, Ghandwani D, Pal Choudhury P, Berndt SI, Freedman ND, Garcia-Closas M, Chatterjee N. Combined Utility of 25 Disease and Risk Factor Polygenic Risk Scores for Stratifying Risk of All-Cause Mortality. Am J Hum Genet 2020; 107:418-431. [PMID: 32758451 DOI: 10.1016/j.ajhg.2020.07.002] [Citation(s) in RCA: 39] [Impact Index Per Article: 9.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2020] [Accepted: 07/01/2020] [Indexed: 12/13/2022] Open
Abstract
While genome-wide association studies have identified susceptibility variants for numerous traits, their combined utility for predicting broad measures of health, such as mortality, remains poorly understood. We used data from the UK Biobank to combine polygenic risk scores (PRS) for 13 diseases and 12 mortality risk factors into sex-specific composite PRS (cPRS). These cPRS were moderately associated with all-cause mortality in independent data within the UK Biobank: the estimated hazard ratios per standard deviation were 1.10 (95% confidence interval: 1.05, 1.16) and 1.15 (1.10, 1.19) for women and men, respectively. Differences in life expectancy between the top and bottom 5% of the cPRS were estimated to be 4.79 (1.76, 7.81) years and 6.75 (4.16, 9.35) years for women and men, respectively. These associations were substantially attenuated after adjusting for non-genetic mortality risk factors measured at study entry (i.e., middle age for most participants). The cPRS may be useful in counseling younger individuals at higher genetic risk of mortality on modification of non-genetic factors.
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Affiliation(s)
- Allison Meisner
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Prosenjit Kundu
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Yan Dora Zhang
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Department of Statistics, University of Hong Kong, 999077, Hong Kong
| | - Lauren V Lan
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Sungwon Kim
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA
| | - Disha Ghandwani
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Indian Statistical Institute, Kolkata, West Bengal 700108, India
| | - Parichoy Pal Choudhury
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Neal D Freedman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Montserrat Garcia-Closas
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Bethesda, MD 20892, USA
| | - Nilanjan Chatterjee
- Department of Biostatistics, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD 21205, USA; Department of Oncology, Johns Hopkins University School of Medicine, Baltimore, MD 21205, USA.
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24
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Kudryashova KS, Burka K, Kulaga AY, Vorobyeva NS, Kennedy BK. Aging Biomarkers: From Functional Tests to Multi‐Omics Approaches. Proteomics 2020; 20:e1900408. [DOI: 10.1002/pmic.201900408] [Citation(s) in RCA: 20] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/17/2019] [Revised: 02/07/2020] [Indexed: 12/15/2022]
Affiliation(s)
| | - Ksenia Burka
- Centaura AG Bleicherweg 10 Zurich 8002 Switzerland
| | - Anton Y. Kulaga
- Centaura AG Bleicherweg 10 Zurich 8002 Switzerland
- Systems Biology of Aging GroupInstitute of Biochemistry of the Romanian Academy Splaiul Independentei 296 Bucharest 060031 Romania
| | | | - Brian K. Kennedy
- Departments of Biochemistry and Physiology Yong Loo Lin School of MedicineNational University of Singapore 8 Medical Drive, MD7, 117596 Singapore
- Singapore Institute for Clinical Sciences (SICS)Agency for Science and Technology (A*STAR)Brenner Centre for Molecular Medicine 30 Medical Drive Singapore 117609 Singapore
- Buck Institute for Research on Aging 8001 Redwood Blvd. Novato CA 94945‐1400 USA
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25
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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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