Reanalysis of CVD Risk Factors Via Likelihood Methods

Cardiovascular Diseases Clinical Trial

Clinical Trial Details — Status: Completed

Administrative data

• NCT number: NCT00005408
• Other study ID #: 4326
• Secondary ID: R03HL046674
• Status: Completed
• Phase: N/A
• First received: May 25, 2000
• Last updated: March 15, 2016
• Start date: July 1992
• Est. completion date: April 1994

Study information

• Verified date: May 2000
• Source: National Heart, Lung, and Blood Institute (NHLBI)
• Contact: n/a
• Is FDA regulated: No
• Health authority: United States: Federal Government
• Study type: Observational

Clinical Trial Summary

To reanalyze data on risk factors for cardiovascular disease (CVD) including total cholesterol and high density lipoprotein (HDL) cholesterol for the subjects in the first, second, and third exams of the NHLBI Twin Study.

Description:

BACKGROUND:

The results of these longitudinal analyses yielded new insights on genetic effects affecting CVD risk factors during the aging process.

DESIGN NARRATIVE:

The analyses utilized maximum likelihood estimators of genetic variance which were asymptotically more efficient than the method-of-moments estimators used in previous analyses. The models used incorporated 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 were fitted separately to data from each of the three exams to obtain a cross-sectional analysis. The investigators also extended these models for use with longitudinal data by incorporating terms to represent the covariance of variance components from different exams.

Two important additional objectives of this study were i) to introduce resistant estimation techniques in twin modeling, which trimmed 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 were violated. The results of these parts of the study should yield a more complete understanding of the relative merits and limitations of twin modeling procedures.

The study completion date listed in this record was obtained from the "End Date" entered in the Protocol Registration and Results System (PRS) record.

Recruitment information / eligibility

• Status: Completed
• Enrollment: 0
• Est. completion date: April 1994
• Accepts healthy volunteers: No
• Gender: Male
• Age group: N/A to 100 Years
• Eligibility: No eligibility criteria

Study Design

N/A

Related Conditions & MeSH terms

• Atherosclerosis
• Cardiovascular Diseases
• Heart Diseases

Locations

Country	Name	City	State
n/a

Sponsors (1)

Lead Sponsor	Collaborator
National Heart, Lung, and Blood Institute (NHLBI)

References & Publications (3)

Wijesiri UW, Williams CJ. Approximate solutions for the maximum-likelihood estimates in models of univariate human twin data. Behav Genet. 1995 May;25(3):211-6. Erratum in: Behav Genet 1997 Jan;27(1):83. — View Citation

Williams CJ, Wijesiri UW. Lipid data from NHLBI veteran twins: interpreting genetic analyses when model assumptions fail. Genet Epidemiol. 1993;10(6):551-6. — View Citation

Williams CJ. On the covariance between parameter estimates in models of twin data. Biometrics. 1993 Jun;49(2):557-68. — View Citation