Heritability and Covariate Traits in Sardinian and Other

为了确定年龄相关性状中的遗传和流行病学因素，我们正在应用新的统计学方法在大型人口数据集中寻找协变量和隐藏的相关性。一个特别的重点是NIA赞助的对创始人撒丁岛人口的研究，其中人口的相互关联和多代人的稳定环境可以简化分析。这项研究已经对200个二分性特征(吸烟等)进行了评分。数量性状98个(？内表型？或者？量化风险相关的遗传或环境因素？)这可以在连续的范围内得分。数量性状的使用允许研究种群中的全部等位基因变异范围。特别令人感兴趣的特征包括一系列心血管风险因素、人体测量、血液测试值和个性方面。 在目前一份为期5年的合同中，撒丁岛的一个科学家团队从撒丁岛中东部的四个城镇中挑选了6100多名受试者，并测量了每个受试者的所有特征。样本队列中有超过一半的人口年龄在14岁到102岁之间；他们都是土生土长的人，已知至少96%的人祖父母都出生在同一个省。该组包括4933对表型同胞对、4266对表型亲子对、4069对表型表亲对和6459多对表型伯父对。这个样本足够大，表型也足够好，表明即使在这个创始人群体中，个体性状的方差也可以与远交群体中的个体性状的方差相媲美；而且它足够大和相互关联，足以推断出对性状遗传遗传力的高度显著估计。在这项研究的第一批出版物中，我们报告了98个数量性状的遗传力分析，重点是个性和心血管功能的各个方面。我们还总结了所有性状对的双变量分析结果和每个性状的异质性分析结果。我们发现每种性状都有显著的遗传成分。平均而言，遗传效应解释了38项血液测试的40%，5项人体测量指标的51%，20项心血管功能指标的25%，以及35项个性特征的19%。有四个特征显示了X连锁成分的重要证据。双变量分析表明，许多特征的基因决定因素是重叠的，包括多个个性方面和几个与代谢综合征相关的特征；但我们没有发现共同的基因决定因素的证据，这些基因决定因素可能是某些个性特征和心血管风险因素之间报道的关联的基础。考虑到异质性的模型表明，在这个队列中，女性和年轻个体的遗传差异通常更大，但也观察到了有趣的例外情况。例如，在42岁的个体中，血压的狭义遗传率为~26%，但在年轻个体中仅为~8%。尽管效应大小不同，但相同的基因座似乎在年轻人和老年人以及男性和女性之间造成了差异。总之，我们发现了许多医学上重要特征的遗传性的重要证据，包括心血管功能和个性。年龄和性别的异质性证据表明，考虑到这些差异的模型将在绘制数量性状图谱时发挥重要作用。 全基因组扫描(基因分型)应该有能力检测出对某个性状的变异贡献10%量级的基因座。有了这个队列，使用多达500,000个单核苷酸标记的全基因组扫描几乎完成，预计将指向决定每种研究性状变异的很大一部分遗传贡献的基因/变异。此外，已开始对研究队列进行第二次访问，以评估纵向趋势和结果，以及评估与年龄相关的骨密度和脆弱程度的其他表型。 虽然人群的基因组扫描开始搜索涉及特定特征决定的基因，但正在启动有针对性的数据分析，以寻找相关/重叠的遗传和流行病学因素，包括意想不到的相关性，并与其他大型人群队列研究，包括巴尔的摩老龄化纵向研究，比较可能的相关性。

With the goal of determining genetic and epidemiological factors in age-related traits, we are applying new statistical approaches to look for covariates and hidden correlations in large population data sets. A particular focus is the NIA-sponsored study of the founder Sardinian population, where inter-relatedness and stable environment of the population over many generations can simplify the analysis. The study has been scoring >200 dichotomized traits (smoking, etc.) and 98 quantitative traits (?endophenotypes? or ?quantitative risk-related genetic or environmental factors?) that can be scored on a continuous scale. The use of quantitative traits permits the study of the entire range of allelic variation in a population. Traits of special interest include a range of cardiovascular risk factors, anthropometric measurements, blood test values, and facets of personality. In a current 5-year contract, a team of Sardinian scientists has recruited over 6,100 subjects from a selected group of four towns in east-central Sardinia, and has measured all traits for each subject. The sample cohort numbers over half of the population of the region aged 14-102; they are native-born, and at least 96 percent are known to have all grandparents born in the same province. The group include 4933 phenotyped sib pairs, 4266 phenotyped parent-child pairs, >4069 phenotyped cousin pairs, and more than 6459 phenotyped avuncular pairs. This sample is large enough and well enough phenotyped to show that even in this founder population, the variance for individual traits is comparable to that in outbred populations; and it is large enough and interrelated enough to infer highly significant estimates of genetic heritability for traits. In the first publications from the study,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 5 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 determinant 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 ~26% in individuals >42 years old, but only ~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 suggest that models allowing for these differences will be important in mapping quantitative traits. Genome-wide scans (genotyping) should have the power to detect loci that contribute the order of 10 percent of variance for a trait. With this cohort, full-genome scans with batteries of up to 500,000 single-nucleotide markers are almost complete, and are expected to point to genes/variants that determine a significant portion of the genetic contribution to variance for each trait studied. In addition, second visits have been initiated for the study cohort to permit the assessment of longitudinal trends and outcomes, as well as the assessment of additional phenotypes related to bone density and frailty as a function of age. While the genome scans of the population begin to search for genes involved in the determination of particular traits, targeted data analysis is being initiated to look for correlated/overlapping genetic and epidemiological factors, including unexpected correlations, and to compare possible correlations with other large population cohort studies, including the Baltimore Longitudinal Study of Aging.