REANALYSIS OF CVD RISK FACTORS VIA LIKELIHOOD METHODS

通过似然法重新分析 CVD 危险因素

• 批准号: 3426814
• 负责人: CHRISTOPHER WILLIAMS
• 金额: $ 4.75万
• 依托单位: INDIANA UNIV-PURDUE UNIV AT INDIANAPOLIS
• 依托单位国家: 美国
• 财政年份: 1991
• 资助国家: 美国
• 起止时间: 1991-05-01 至 1993-04-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/3426814
• 关键词: aging; cardiovascular disorder epidemiology; cholesterol; disease /disorder proneness /risk; genetic models; high density lipoproteins; human population genetics; human subject; longitudinal human study; monozygotic twins; patient /disease registry; statistics /biometry

We will reanalyze data on risk factors for cardiovascular disease (CVD) including total cholesterol and HDL cholesterol for the subjects of the NHLBI twin study for examinations 1, 2, and 3 of the study. The analyses will utilize maximum likelihood estimators of genetic variance which are asymptotically more efficient than the method-of-moments estimators used in previous analyses. The models used will incorporate terms to partition the variance in a trait from twin data into either i) additive genetic variance and unshared environmental variance (the AE model), ii) additive genetic variance, dominance genetic variance, and unshared environmental variance (the ADE model), or iii) additive genetic variance, shared environmental variance, and unshared environmental variance (the ACE model). The AE, ADE, and ACE models can be fitted separately to data from each of the three exams to obtain a cross-sectional analysis. We shall also extend these models for use with longitudinal data by incorporating terms to represent the covariance of variance components from different exams. The results of these longitudinal analyses will yield new insights on genetic effects affecting CVD risk factors during the aging process. Two important additional objectives of this proposal are i) to introduce resistant estimation techniques in twin modeling, which trim the effect of outlier data points smoothly, and ii) to carefully study the performance of maximum likelihood and method-of-moments estimators when assumptions of the twin model are violated. The results of these parts of the proposal will yield a more complete understanding of the relative merits and limitations of twin modeling procedures.

我们将重新分析心血管疾病（CVD）风险因素的数据 包括受试者的总胆固醇和HDL胆固醇。 研究检查1、2和3的NHLBI双胞胎研究。 的 分析将利用遗传方差的最大似然估计 它比矩量法更有效 在以前的分析中使用的估计。 使用的模型将包含 将来自双胞胎数据的性状方差划分为i） 加性遗传方差和非共享环境方差（AE ii）加性遗传方差，显性遗传方差，以及 非共享环境方差（ADE模型），或iii）加性 遗传方差、共享环境方差和非共享环境方差 环境变量（ACE模型）。 AE、ADE和ACE模型可以 分别拟合三次检查的数据，以获得 横截面分析 我们还将扩展这些模型， 纵向数据通过合并术语来表示 不同检查的方差分量的协方差。 的结果 这些纵向分析将对遗传效应产生新的认识， 在衰老过程中影响心血管疾病的危险因素。 本提案的两个重要附加目标是：i）引入 双胞胎建模中的抗性估计技术， 离群数据点顺利，和ii）仔细研究 最大似然法和矩估计法的性能 这违反了孪生模型的假设。 这些部分的结果 的建议将产生一个更完整的了解相对 双胞胎建模程序的优点和局限性。