Heritability of Cardiovascular and Personality Traits in 6,148 Sardinians
In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recru...
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| Vydáno v: | PLoS genetics Ročník 2; číslo 8; s. e132 |
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| Hlavní autoři: | , , , , , , , , , , , , , , , , , , , , , , , , |
| Médium: | Journal Article |
| Jazyk: | angličtina |
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United States
Public Library of Science
01.08.2006
Public Library of Science (PLoS) |
| Témata: | |
| ISSN: | 1553-7404, 1553-7390, 1553-7404 |
| On-line přístup: | Získat plný text |
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| Abstract | In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits. |
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| AbstractList |
In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits. In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits. In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14–102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits. Genetic analysis of complex traits, which are influenced by many different variables, is difficult because different genes and environmental factors can affect each individual. To simplify analysis, the authors turned to Sardinia, one of the rare, relatively isolated populations. They recruited 6,148 participants, aged 14–102 y, from four neighboring towns. Their sample includes many related individuals, including, for example, approximately 5,000 pairs of brothers and sisters. The authors measured 98 traits in each individual, including different aspects of blood composition and several cardiovascular and personality measures. Here, the authors evaluate the overall impact of genes and environment on each trait and show that genes can explain many of the differences and similarities between individuals. Genetic influences were typically larger in females and in younger individuals, but interesting exceptions were observed. For example, genetic factors accounted for approximately 26% of the variation in blood pressure for those more than 42 y old, but only for approximately 8% in younger individuals. Their analysis also showed that the same genetic factor could influence multiple traits, for example by affecting multiple features of personality or of cardiovascular function. DNA analyses of this cohort will eventually allow researchers to identify genes that affect each of the traits studied, including important risk factors for cardiovascular disease. In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits.In family studies, phenotypic similarities between relatives yield information on the overall contribution of genes to trait variation. Large samples are important for these family studies, especially when comparing heritability between subgroups such as young and old, or males and females. We recruited a cohort of 6,148 participants, aged 14-102 y, from four clustered towns in Sardinia. The cohort includes 34,469 relative pairs. To extract genetic information, we implemented software for variance components heritability analysis, designed to handle large pedigrees, analyze multiple traits simultaneously, and model heterogeneity. Here, we report heritability analyses for 98 quantitative traits, focusing on facets of personality and cardiovascular function. We also summarize results of bivariate analyses for all pairs of traits and of heterogeneity analyses for each trait. We found a significant genetic component for every trait. On average, genetic effects explained 40% of the variance for 38 blood tests, 51% for five anthropometric measures, 25% for 20 measures of cardiovascular function, and 19% for 35 personality traits. Four traits showed significant evidence for an X-linked component. Bivariate analyses suggested overlapping genetic determinants for many traits, including multiple personality facets and several traits related to the metabolic syndrome; but we found no evidence for shared genetic determinants that might underlie the reported association of some personality traits and cardiovascular risk factors. Models allowing for heterogeneity suggested that, in this cohort, the genetic variance was typically larger in females and in younger individuals, but interesting exceptions were observed. For example, narrow heritability of blood pressure was approximately 26% in individuals more than 42 y old, but only approximately 8% in younger individuals. Despite the heterogeneity in effect sizes, the same loci appear to contribute to variance in young and old, and in males and females. In summary, we find significant evidence for heritability of many medically important traits, including cardiovascular function and personality. Evidence for heterogeneity by age and sex suggests that models allowing for these differences will be important in mapping quantitative traits. |
| Audience | Academic |
| Author | Deiana, Manila Costa, Paul Lai, Sandra Dei, Mariano Lakatta, Edward Schlessinger, David Loi, Paola Masala, Marco Olla, Nazario Albai, Giuseppe Sharov, Alexei Cao, Antonio Zonderman, Alan B Scuteri, Angelo Chen, Wei-Min Terracciano, Antonio Pilia, Giuseppe Usala, Gianluca Orrú, Marco Najjar, Samer S Nedorezov, Timur Mameli, Cinzia Vacca, Loredana Lai, Monica Abecasis, Gonçalo R |
| AuthorAffiliation | 1 Istituto di Neurogenetica e Neurofarmacologia, Consiglio Nazionale delle Ricerche, Ospedale Microcitemico, Cagliari, Italy 2 Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America 3 Unità Operativa Geriatria, Istituto Nazionale Riposo e Cura Anziani, Rome, Italy 5 Unità Operativa Semplice Cardiologia, Divisione di Medicina, Presidio Ospedaliero Santa Barbara, Iglesias, Italy The Jackson Laboratory, United States of America 4 Gerontology Research Center, National Institute on Aging, Baltimore, Maryland, United States of America |
| AuthorAffiliation_xml | – name: 5 Unità Operativa Semplice Cardiologia, Divisione di Medicina, Presidio Ospedaliero Santa Barbara, Iglesias, Italy – name: 2 Center for Statistical Genetics, Department of Biostatistics, University of Michigan, Ann Arbor, Michigan, United States of America – name: 3 Unità Operativa Geriatria, Istituto Nazionale Riposo e Cura Anziani, Rome, Italy – name: 1 Istituto di Neurogenetica e Neurofarmacologia, Consiglio Nazionale delle Ricerche, Ospedale Microcitemico, Cagliari, Italy – name: 4 Gerontology Research Center, National Institute on Aging, Baltimore, Maryland, United States of America – name: The Jackson Laboratory, United States of America |
| Author_xml | – sequence: 1 givenname: Giuseppe surname: Pilia fullname: Pilia, Giuseppe – sequence: 2 givenname: Wei-Min surname: Chen fullname: Chen, Wei-Min – sequence: 3 givenname: Angelo surname: Scuteri fullname: Scuteri, Angelo – sequence: 4 givenname: Marco surname: Orrú fullname: Orrú, Marco – sequence: 5 givenname: Giuseppe surname: Albai fullname: Albai, Giuseppe – sequence: 6 givenname: Mariano surname: Dei fullname: Dei, Mariano – sequence: 7 givenname: Sandra surname: Lai fullname: Lai, Sandra – sequence: 8 givenname: Gianluca surname: Usala fullname: Usala, Gianluca – sequence: 9 givenname: Monica surname: Lai fullname: Lai, Monica – sequence: 10 givenname: Paola surname: Loi fullname: Loi, Paola – sequence: 11 givenname: Cinzia surname: Mameli fullname: Mameli, Cinzia – sequence: 12 givenname: Loredana surname: Vacca fullname: Vacca, Loredana – sequence: 13 givenname: Manila surname: Deiana fullname: Deiana, Manila – sequence: 14 givenname: Nazario surname: Olla fullname: Olla, Nazario – sequence: 15 givenname: Marco surname: Masala fullname: Masala, Marco – sequence: 16 givenname: Antonio surname: Cao fullname: Cao, Antonio – sequence: 17 givenname: Samer S surname: Najjar fullname: Najjar, Samer S – sequence: 18 givenname: Antonio surname: Terracciano fullname: Terracciano, Antonio – sequence: 19 givenname: Timur surname: Nedorezov fullname: Nedorezov, Timur – sequence: 20 givenname: Alexei surname: Sharov fullname: Sharov, Alexei – sequence: 21 givenname: Alan B surname: Zonderman fullname: Zonderman, Alan B – sequence: 22 givenname: Gonçalo R surname: Abecasis fullname: Abecasis, Gonçalo R – sequence: 23 givenname: Paul surname: Costa fullname: Costa, Paul – sequence: 24 givenname: Edward surname: Lakatta fullname: Lakatta, Edward – sequence: 25 givenname: David surname: Schlessinger fullname: Schlessinger, David |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/16934002$$D View this record in MEDLINE/PubMed |
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| SubjectTerms | Adolescent Adult Aged Aged, 80 and over Aging Analysis of Variance Blood pressure Cardiology - Cardiac Surgery Cardiovascular Diseases - genetics Cardiovascular Physiological Phenomena Chromosomes, Human, X - genetics Cohort Studies Dominance (Genetics) Female Genes, Mitochondrial Genetic aspects Genetics Genetics/Complex Traits Genetics/Disease Models Genetics/Population Genetics Homo (Human) Humans Italy Male Mental Health Middle Aged Models, Genetic Multifactorial Inheritance Personality - genetics Physiological aspects Population Psychology Quantitative Trait, Heritable Sardinians Sex Characteristics Siblings Studies |
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| Title | Heritability of Cardiovascular and Personality Traits in 6,148 Sardinians |
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