Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances

We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and...

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Published ineLife Vol. 8
Main Authors Timmers, Paul RHJ, Mounier, Ninon, Lall, Kristi, Fischer, Krista, Ning, Zheng, Feng, Xiao, Bretherick, Andrew D, Clark, David W, Agbessi, M, Ahsan, H, Alves, I, Andiappan, A, Awadalla, P, Battle, A, Bonder, MJ, Boomsma, D, Christiansen, M, Claringbould, A, Deelen, P, van Dongen, J, Esko, T, Favé, M, Franke, L, Frayling, T, Gharib, SA, Gibson, G, Hemani, G, Jansen, R, Kalnapenkis, A, Kasela, S, Kettunen, J, Kim, Y, Kirsten, H, Kovacs, P, Krohn, K, Kronberg-Guzman, J, Kukushkina, V, Kutalik, Z, Kähönen, M, Lee, B, Lehtimäki, T, Loeffler, M, Marigorta, U, Metspalu, A, van Meurs, J, Milani, L, Müller-Nurasyid, M, Nauck, M, Nivard, M, Penninx, B, Perola, M, Pervjakova, N, Pierce, B, Powell, J, Prokisch, H, Psaty, BM, Raitakari, O, Ring, S, Ripatti, S, Rotzschke, O, Ruëger, S, Saha, A, Scholz, M, Schramm, K, Seppälä, I, Stumvoll, M, Sullivan, P, Teumer, A, Thiery, J, Tong, L, Tönjes, A, Verlouw, J, Visscher, PM, Võsa, U, Völker, U, Yaghootkar, H, Yang, J, Zeng, B, Zhang, F, Shen, Xia, Esko, Tõnu, Kutalik, Zoltán, Wilson, James F, Joshi, Peter K
Format Journal Article
LanguageEnglish
Published England eLife Sciences Publications Ltd 15.01.2019
eLife Sciences Publications, Ltd
Subjects
Age Factors
Aged
Bayes Theorem
Cardiovascular diseases
complex trait
Dementia disorders
Disease - genetics
DNA Methylation - genetics
Female
FOXO3 protein
Furin
Genetic diversity
Genetic Loci
Genetics and Genomics
Genome-Wide Association Study
Genomics
Homeostasis
Humans
Insulin-like growth factor II receptors
Life span
lifespan
longevity
Longevity - genetics
Lung cancer
Lung diseases
Male
Middle Aged
Multifactorial Inheritance - genetics
Parents
Polymorphism, Single Nucleotide - genetics
Prefrontal cortex
Research Communication
Risk Factors
Sex Characteristics
Signal Transduction - genetics
Survival Analysis
genomics
longevity
genetics
human
complex trait
lifespan
Online AccessGet full text

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Abstract We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (<xref ref-type="decision-letter" rid="SA1">see decision letter ). Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.
AbstractList We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (<xref ref-type="decision-letter" rid="SA1">see decision letter ). Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.
We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near , , , , , and 13q21.31, and identify and replicate novel findings near , , and . We also validate previous findings near 5q33.3/ and , whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer - but not other cancers - explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles.Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer - but not other cancers - explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles.We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1, ATXN2/BRAP, FURIN/FES, ZW10, PSORS1C3, and 13q21.31, and identify and replicate novel findings near ABO, ZC3HC1, and IGF2R. We also validate previous findings near 5q33.3/EBF1 and FOXO3, whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer - but not other cancers - explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles.This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).Editorial noteThis article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed (see decision letter).
We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated findings near CDKN2B-AS1 , ATXN2/BRAP , FURIN/FES , ZW10 , PSORS1C3 , and 13q21.31, and identify and replicate novel findings near ABO , ZC3HC1 , and IGF2R . We also validate previous findings near 5q33.3/ EBF1 and FOXO3 , whilst finding contradictory evidence at other loci. Gene set and cell-specific analyses show that expression in foetal brain cells and adult dorsolateral prefrontal cortex is enriched for lifespan variation, as are gene pathways involving lipid proteins and homeostasis, vesicle-mediated transport, and synaptic function. Individual genetic variants that increase dementia, cardiovascular disease, and lung cancer – but not other cancers – explain the most variance. Resulting polygenic scores show a mean lifespan difference of around five years of life across the deciles. Editorial note: This article has been through an editorial process in which the authors decide how to respond to the issues raised during peer review. The Reviewing Editor's assessment is that all the issues have been addressed ( see decision letter ). Ageing happens to us all, and as the cabaret singer Maurice Chevalier pointed out, "old age is not that bad when you consider the alternative". Yet, the growing ageing population of most developed countries presents challenges to healthcare systems and government finances. For many older people, long periods of ill health are part of the end of life, and so a better understanding of ageing could offer the opportunity to prolong healthy living into old age. Ageing is complex and takes a long time to study – a lifetime in fact. This makes it difficult to discern its causes, among the countless possibilities based on an individual’s genes, behaviour or environment. While thousands of regions in an individual’s genetic makeup are known to influence their risk of different diseases, those that affect how long they will live have proved harder to disentangle. Timmers et al. sought to pinpoint such regions, and then use this information to predict, based on their DNA, whether someone had a better or worse chance of living longer than average. The DNA of over 500,000 people was read to reveal the specific ‘genetic fingerprints’ of each participant. Then, after asking each of the participants how long both of their parents had lived, Timmers et al. pinpointed 12 DNA regions that affect lifespan. Five of these regions were new and had not been linked to lifespan before. Across the twelve as a whole several were known to be involved in Alzheimer’s disease, smoking-related cancer or heart disease. Looking at the entire genome, Timmers et al. could then predict a lifespan score for each individual, and when they sorted participants into ten groups based on these scores they found that top group lived five years longer than the bottom, on average. Many factors beside genetics influence how long a person will live and our lifespan cannot be read from our DNA alone. Nevertheless, Timmers et al. had hoped to narrow down their search and discover specific genes that directly influence how quickly people age, beyond diseases. If such genes exist, their effects were too small to be detected in this study. The next step will be to expand the study to include more participants, which will hopefully pinpoint further genomic regions and help disentangle the biology of ageing and disease.
Author Agbessi, M
Ahsan, H
Ripatti, S
Christiansen, M
Hemani, G
Stumvoll, M
Kronberg-Guzman, J
Esko, T
Lee, B
Nauck, M
Zeng, B
Schramm, K
Seppälä, I
Psaty, BM
Scholz, M
Marigorta, U
Saha, A
Kalnapenkis, A
Fischer, Krista
Yang, J
Kutalik, Z
Krohn, K
Frayling, T
Kim, Y
Gibson, G
Ring, S
Ning, Zheng
Favé, M
Sullivan, P
Battle, A
Tönjes, A
Mounier, Ninon
Nivard, M
Lehtimäki, T
Visscher, PM
Feng, Xiao
Esko, Tõnu
Võsa, U
Perola, M
Loeffler, M
Wilson, James F
Jansen, R
Kasela, S
Lall, Kristi
Timmers, Paul RHJ
Andiappan, A
Claringbould, A
Penninx, B
Franke, L
van Dongen, J
Ruëger, S
Verlouw, J
Thiery, J
Kähönen, M
Völker, U
Powell, J
Alves, I
Kutalik, Zoltán
Yaghootkar, H
Boomsma, D
Pierce, B
Awadalla, P
Joshi, Peter K
Kukushkina, V
Raitakari, O
Bonder, MJ
Kovacs, P
Prokisch, H
Rotzschke, O
Gharib, SA
Metspalu, A
Pervjakova, N
Kirsten, H
Deelen, P
van Meurs, J
Kettunen, J
Shen, Xia
Zhang, F
Clark, David W
Tong, L
Milani, L
Müller-Nurasyid, M
Bretherick, Andrew D
Teumer, A
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  organization: University of Helsinki, Helsinki, Finland
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  organization: Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom, Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou, China
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  givenname: James F
  orcidid: 0000-0001-5751-9178
  surname: Wilson
  fullname: Wilson, James F
  organization: Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom, MRC Human Genetics Unit, Institute of Genetics and Molecular Medicine, University of Edinburgh, Edinburgh, United Kingdom
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  organization: Centre for Global Health Research, Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, United Kingdom, Institute of Social and Preventive Medicine, University Hospital of Lausanne, Lausanne, Switzerland
BackLink https://www.ncbi.nlm.nih.gov/pubmed/30642433$$D View this record in MEDLINE/PubMed
http://kipublications.ki.se/Default.aspx?queryparsed=id:139995293$$DView record from Swedish Publication Index
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ContentType Journal Article
Contributor Agbessi, M
Ahsan, H
Visscher, P M
Ripatti, S
Christiansen, M
Hemani, G
Stumvoll, M
Gharib, S A
Kronberg-Guzman, J
Esko, T
Lee, B
Nauck, M
Zeng, B
Schramm, K
Seppälä, I
Scholz, M
Marigorta, U
Saha, A
Kalnapenkis, A
Yang, J
Kutalik, Z
Krohn, K
Frayling, T
Kim, Y
Gibson, G
Ring, S
Favé, M
Sullivan, P
Battle, A
Tönjes, A
Nivard, M
Lehtimäki, T
Võsa, U
Perola, M
Loeffler, M
Jansen, R
Kasela, S
Andiappan, A
Claringbould, A
Penninx, B
Franke, L
van Dongen, J
Ruëger, S
Verlouw, J
Thiery, J
Kähönen, M
Völker, U
Powell, J
Alves, I
Yaghootkar, H
Boomsma, D
Pierce, B
Awadalla, P
Kukushkina, V
Raitakari, O
Kovacs, P
Prokisch, H
Rotzschke, O
Metspalu, A
Pervjakova, N
Kirsten, H
Deelen, P
van Meurs, J
Kettunen, J
Zhang, F
Psaty, B M
Tong, L
Bonder, M J
Milani, L
Müller-Nurasyid, M
Teumer, A
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Keywords genomics
longevity
genetics
human
complex trait
lifespan
Language English
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2019, Timmers et al.
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
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Snippet We use a genome-wide association of 1 million parental lifespans of genotyped subjects and data on mortality risk factors to validate previously unreplicated...
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SubjectTerms Age Factors
Aged
Bayes Theorem
Cardiovascular diseases
complex trait
Dementia disorders
Disease - genetics
DNA Methylation - genetics
Female
FOXO3 protein
Furin
Genetic diversity
Genetic Loci
Genetics and Genomics
Genome-Wide Association Study
Genomics
Homeostasis
Humans
Insulin-like growth factor II receptors
Life span
lifespan
longevity
Longevity - genetics
Lung cancer
Lung diseases
Male
Middle Aged
Multifactorial Inheritance - genetics
Parents
Polymorphism, Single Nucleotide - genetics
Prefrontal cortex
Research Communication
Risk Factors
Sex Characteristics
Signal Transduction - genetics
Survival Analysis
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Title Genomics of 1 million parent lifespans implicates novel pathways and common diseases and distinguishes survival chances
URI https://www.ncbi.nlm.nih.gov/pubmed/30642433
https://www.proquest.com/docview/2289414326
https://www.proquest.com/docview/2179348905
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Volume 8
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