Multivariate QTL linkage analysis suggests a QTL for platelet count on chromosome 19q

Platelet count is a highly heritable trait with genetic factors responsible for around 80% of the phenotypic variance. We measured platelet count longitudinally in 327 monozygotic and 418 dizygotic twin pairs at 12, 14 and 16 years of age. We also performed a genome-wide linkage scan of these twins and their families in an attempt to localize QTLs that influenced variation in platelet concentrations. Suggestive linkage was observed on chromosome 19q13.13-19q13.31 at 12 (LOD=2.12, P=0.0009), 14 (LOD=2.23, P=0.0007) and 16 (LOD=1.01, P=0.016) years of age and multivariate analysis of counts at all three ages increased the LOD to 2.59 (P=0.0003). A possible candidate in this region is the gene for glycoprotein VI, a receptor involved in platelet aggregation. Smaller linkage peaks were also seen at 2p, 5p, 5q, 10p and 15q. There was little evidence for linkage to the chromosomal regions containing the genes for thrombopoietin (3q27) and the thrombopoietin receptor (1q34), suggesting that polymorphisms in these genes do not contribute substantially to variation in platelet count between healthy individuals.

Major quantitative trait locus for eosinophil count is located on chromosome 2q

Background: Eosinophils are granulocytic white blood cells implicated in asthma and atopic disease. The degree of eosinophilia in the blood of patients with asthma correlates with the severity of asthmatic symptoms. Quantitative trait loci (QTL) linkage analysis of eosinophil count may be a more powerful strategy of mapping genes involved in asthma than linkage analysis using affected relative pairs. 1 Objective: To identify QTLs responsible for variation in eosinophil count in adolescent twins. Methods: We measured eosinophil count longitudinally in 738 pairs of twins at 12, 14, and 16 years of age. We typed 757 highly polymorphic microsatellite markers at an average spacing of similar to5 centimorgans across the genome. We then used multipoint variance components linkage analysis to test for linkage between marker loci and eosinophil concentrations at each age across the genome. Results: We found highly significant linkage on chromosome 2q33 in 12-year-old twins (logarithm of the odds = 4.6; P = .000002) and suggestive evidence of linkage in the same region in 14-year-olds (logarithm of the odds = 1.0; P = .016). We also found suggestive evidence of linkage at other areas of the genome, including regions on chromosomes 2, 3, 4, 8, 9, 11, 12, 17, 20, and 22. Conclusion: A QTL for eosinophil count is present on chromosome 2q33. This QTL might represent a gene involved in asthma pathophysiology.

White blood cell count predicts reduction in coronary heart disease mortality with pravastatin

Background-Elevated serum inflammatory marker levels are associated with a greater long-term risk of cardiovascular events. Because 3-hydroxy-3-methylglutaryl coenzyme-A reductase inhibitors (statins) may have an antiinflammatory action, it has been suggested that patients with elevated inflammatory marker levels may have a greater reduction in cardiovascular risk with statin treatment. Methods and Results-We evaluated the association between the white blood cell count (WBC) and coronary heart disease mortality during a mean follow-up of 6.0 years in the Long-Term Intervention With Pravastatin in Ischemic Disease (LIPID) Study, a clinical trial comparing pravastatin (40 mg/d) with a placebo in 9014 stable patients with previous myocardial infarction or unstable angina. An increase in baseline WBC was associated with greater coronary heart disease mortality in patients randomized to placebo (hazard ratio for 1 X 10(9)/L increase in WBC, 1.18; 95% CI, 1.12 to 1.25; P<0.001) but not pravastatin (hazard ratio, 1.02; 95% CI, 0.96 to 1.09; P=0.56; P for interaction=0.004). The numbers of coronary heart disease deaths prevented per 1000 patients treated with pravastatin were 0, 9, 30, and 38 for baseline WBC quartiles of <5.9, 6.0 to 6.9, 7.0 to 8.1, and >8.2X10(9)/L, respectively. WBC was a stronger predictor of this treatment benefit than the ratio of total to high-density lipoprotein cholesterol and a global measure of cardiac risk. There was also a greater reduction (P=0.052) in the combined incidence of cardiovascular mortality, nonfatal myocardial infarction, and stroke with pravastatin as baseline WBC increased ( by quartile: 3, 41, 61, and 60 events prevented per 1000 patients treated, respectively). Conclusions-These data support the hypothesis that individuals with evidence of inflammation may obtain a greater benefit from statin therapy.

A Score Test for Zero-Inflation in Correlated Count Data

To account for the preponderance of zero counts and simultaneous correlation of observations, a class of zero-inflated Poisson mixed regression models is applicable for accommodating the within-cluster dependence. In this paper, a score test for zero-inflation is developed for assessing correlated count data with excess zeros. The sampling distribution and the power of the test statistic are evaluated by simulation studies. The results show that the test statistic performs satisfactorily under a wide range of conditions. The test procedure is further illustrated using a data set on recurrent urinary tract infections. Copyright (c) 2005 John Wiley & Sons, Ltd.

Multi-level zero-inflated Poisson regression modelling of correlated count data with excess zeros

Count data with excess zeros relative to a Poisson distribution are common in many biomedical applications. A popular approach to the analysis of such data is to use a zero-inflated Poisson (ZIP) regression model. Often, because of the hierarchical Study design or the data collection procedure, zero-inflation and lack of independence may occur simultaneously, which tender the standard ZIP model inadequate. To account for the preponderance of zero counts and the inherent correlation of observations, a class of multi-level ZIP regression model with random effects is presented. Model fitting is facilitated using an expectation-maximization algorithm, whereas variance components are estimated via residual maximum likelihood estimating equations. A score test for zero-inflation is also presented. The multi-level ZIP model is then generalized to cope with a more complex correlation structure. Application to the analysis of correlated count data from a longitudinal infant feeding study illustrates the usefulness of the approach.