Familial aggregation and genome-wide linkage analysis of carotid artery plaque: the NHLBI family heart study

OBJECTIVE: To evaluate familial and genetic influences on carotid artery plaque, a qualitative marker of the systemic burden of atherosclerosis. METHODS: The design was a cross-sectional study of 2,223 members of 525 randomly-ascertained families and 2,514 members of 589 high coronary heart disease (CHD) risk families from 4 U.S. communities. RESULTS: The prevalence of plaque was 33, 36, and 47%, respectively, among probands with 0, 1, and 2 or more first-degree relatives with a history of CHD. There was evidence of sibling aggregation of plaque in random families (OR = 1.89; 95% CI: 1.44, 2.48), but associations were substantially attenuated when adjusted for major cardiovascular disease risk factors. A genome scan with 420 microsatellite markers revealed no regions of significant or suggestive linkage for plaque in 342 affected sibling pairs, although suggestive linkage (LOD score: 2.43) was found on chromosome 2p11.2 (D2S1790) in pairs aged 55 years or younger. Other markers with nominal evidence for linkage (p < 0.05) were found on chromosomes 2p25, 2q24-q32, 6q21-q23, 7p12-p21, 7q11-q21, 8q24, 12q12-q13, 18p11, 21q21 and Xp11, Xq12, and Xq24. CONCLUSIONS: There was modest familial aggregation of carotid artery plaque, but a genome-wide scan indicated no regions of significant or suggestive linkage.     

Robust regression for clustered data with application to binary responses

Generalized estimating equations (GEE) can be highly influenced by the presence of unusual data points. A generalization of the GEE procedure, which yields parameter estimates and fitted values that are resistant to influential data, is introduced. Resistant generalized estimating equations (REGEE) include weights in the estimating equations to downweight influential observations or clusters. Influential observations are downweighted according to their leverage or residual in an example of correlated binary regression applied to 137 urinary incontinent elderly patients from 38 medical practices.     

Continuous toxicity monitoring in phase II trials in oncology

The goal of a phase II trial in oncology is to evaluate the efficacy of a new therapy. The dose investigated in a phase II trial is usually an estimate of a maximum-tolerated dose obtained in a preceding phase I trial. Because this estimate is imprecise, stopping rules for toxicity are used in many phase II trials. We give recommendations on how to construct stopping rules to monitor toxicity continuously. A table is provided from which Pocock stopping boundaries can be easily obtained for a range of toxicity rates and sample sizes. Estimation of the probability of toxicity and response is also discussed.     

Modified GEE and Goodness of the Marginal Fit (GOMF) Test with Correlated Binary Responses for Contingency Tables

This paper addresses testing the goodness of fit of models for marginal probabilities estimated by generalized estimating equations. We develop a modified version of generalized estimating equation and a goodness‐of‐fit test based on the fitted marginal means. The test statistic is easy to compute and has a simple reference distribution. Its performance is evaluated asymptotically and in small samples. It is also compared to the deviance and Pearson X² statistics. Example applications are given. (© 2004 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim)     

Prevalence of factor V G1691A (Leiden) and prothrombin G20210A polymorphisms among apparently healthy Jordanians

Factor V Leiden and prothrombin G20210A are related genetic risk factors for venous thromboembolism (VTE). Analysis for both mutations is increasingly being performed on patients exhibiting hypercoagulability. The objective of this study was to determine the prevalence of factor V Leiden (FVL), prothrombin-G20210A (PT-G20210A) polymorphisms and their coexistence among apparently healthy Jordanians. One thousand apparently healthy individuals from representative regions of Jordan with no previous history of VTE participated in this study. The mean age of participants was 28.5+/-6.4 years (age range 18-45 years). Two hundred and eighteen subjects were APC resistant with an APC-R mean of 85.52+/-15.35 seconds; the non-resistant subjects had an APC-R mean of 159.90+/-26.96 seconds. A multiplex polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP) for the simultaneous detection of FVL and prothrombin G20210A was used to analyze the 218 DNA samples that were APC-R resistant. Both mutations generate HindIII RFLPs and the prothrombin amplicon contains an invariant HindIII recognition sites. The multiplex PCR-RFLP of Factor V for those 218-samples was: 41 wild-type, 169 heterozygous mutant, and eight homozygous mutant individuals. For prothrombin G20210A, the multiplex PCR-RFLP identified 215 wild-type and three heterozygous mutant individuals. Factor V positive individuals (n=50) had a mean F-V activity of 78.04%+/-25.81. F-V activity among wild type (n=41), F-V Leiden heterozygous (n=169) and F-V Leiden homozygous (n=8) were 92.93%+/-16.17, 87.02%+/-15.21 and 96.14%+/-12.32, respectively. Factor II positive subjects (n=47) had a mean factor II activity of 127.96%+/-21.37. F-II activity among carriers (heterozygous, n=3) and non-carriers (normal, n=215) of PT-G20210A mutation were 107.67%+/-9.29 and 105.00%+/-17.79, respectively. The prevalence of FVL was 21.8% and there is a little likelihood of the co-inheritance of the FVL and PT-G20210A among healthy young adults, since only few cases were found to be carriers for the two alleles.     

Group testing for case identification with correlated responses

This article examines group testing procedures where units within a group (or pool) may be correlated. The expected number of tests per unit (i.e., efficiency) of hierarchical- and matrix-based procedures is derived based on a class of models of exchangeable binary random variables. The effect on efficiency of the arrangement of correlated units within pools is then examined. In general, when correlated units are arranged in the same pool, the expected number of tests per unit decreases, sometimes substantially, relative to arrangements that ignore information about correlation.     

A note on deletion diagnostics for estimating equations

We describe an algorithm based upon the Sherman–Morrison–Woodburyformula for the inversion of matrices with special structurethat occur in formulae for deletion diagnostics. Substantialcomputational savings relative to a method based upon Cholesky'sdecomposition are illustrated. The result has broad applicationto regression diagnostics for clustered data.     

Marginal models for correlated binary responses with multiple classes and multiple levels of nesting.

A model for correlated binary data is presented. Marginal probabilities and odds ratios are allowed to have general regression structures that include multiple classes and multiple levels of nesting. Estimation is done through the generalized estimating equations approach of Liang and Zeger (1986, Biometrika 73, 13-22). They are contrasted with conditional models and recommendations for choosing between the two are given. Examples from genetic epidemiology are presented.