Reanalysis of CVD Risk Factors Via Likelihood Methods

NCT ID: NCT00005408

Last Updated: 2016-03-16

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Study Classification

OBSERVATIONAL

Study Start Date

1992-07-31

Study Completion Date

1994-04-30

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Cardiovascular Diseases Heart Diseases Atherosclerosis

Eligibility Criteria

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Inclusion Criteria

No eligibility criteria
Maximum Eligible Age

100 Years

Eligible Sex

MALE

Accepts Healthy Volunteers

No

Sponsors

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National Heart, Lung, and Blood Institute (NHLBI)

NIH

Sponsor Role lead

References

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Williams CJ, Wijesiri UW. Lipid data from NHLBI veteran twins: interpreting genetic analyses when model assumptions fail. Genet Epidemiol. 1993;10(6):551-6. doi: 10.1002/gepi.1370100637.

Reference Type BACKGROUND
PMID: 8314059 (View on PubMed)

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

Reference Type BACKGROUND
PMID: 8369388 (View on PubMed)

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. doi: 10.1007/BF02197179.

Reference Type BACKGROUND
PMID: 7598664 (View on PubMed)

Other Identifiers

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R03HL046674

Identifier Type: NIH

Identifier Source: secondary_id

View Link

4326

Identifier Type: -

Identifier Source: org_study_id

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