Genome-wide linkage analysis of systolic blood pressure: a comparison of two approaches to phenotype definition

Problem 1 of the Genetic Analysis Workshop 13(GAW13) contains longitudinal data of cardiovascular measurements from 330 pedigrees. The longitudinal data complicates the phenotype definition because multiple measurements are taken on each individual. To address this complication, we propose an approach that uses generalized estimating equations to obtain residuals for each time point for each person. The mean residual is then taken as the new phenotype with which to use in a variance components linkage analysis. We compare our phenotype definition approach to an approach that first reduces the multiple measurements to a single measurement and then models these summary statistics as regression terms in a variance components analysis. For each approach, multipoint linkage analysis was performed using the residuals and the SOLAR computer program. Our results show little difference between the methods based on the LOD scores

Genetic Susceptibility to Chronic Lymphocytic Leukemia

Chronic lymphocytic leukemia (CLL) is the most common adult leukemia in the West and is an incurable malignancy. No firmly established evidence exists for environmental risk factors in the etiology of CLL. However, CLL is estimated to have one of the highest familial risks for a hematologic malignancy; this along with other evidence strongly supports an inherited genetic component. In the past 5 years, genome-wide association studies (GWAS) have provided the foundation for new avenues in the investigation of pathogenesis of this disease with 22 susceptibility loci currently identified. We review here the advances made in identifying these loci, the potential to translate these findings into clinical practice, and future directions needed to advance our understanding of the genetic susceptibility of CLL. (C) 2013 Elsevier Inc. All rights reserved

Identification of genes involved in alcohol consumption and cigarettes smoking

We compared the results of quantitative linkage analysis using single-nucleotide polymorphisms and microsatellite markers and introduced a new screening test for multivariate quantitative linkage analysis using the Collaborative Study on the Genetics of Alcoholism data. We analyzed 115 extended non-Hispanic White families and tested for linkage using two phenotypes: the maximum number of drinks in a 24-hour period and the number of packs smoked per day for one year. Our results showed that the linkage signal increased using single-nucleotide polymorphisms compared with microsatellite markers and that the screening test gave similar results to that of the bivariate analysis, suggesting its potential use in reducing overall analysis time

Comparison of tagging single-nucleotide polymorphism methods in association analyses

Several methods to identify tagging single-nucleotide polymorphisms (SNPs) are in common use for genetic epidemiologic studies; however, there may be loss of information when using only a subset of SNPs. We sought to compare the ability of commonly used pairwise, multimarker, and haplotype-based tagging SNP selection methods to detect known associations with quantitative expression phenotypes. Using data from HapMap release 21 on unrelated Utah residents with ancestors from northern and western Europe (CEPH-Utah, CEU), we selected tagging SNPs in five chromosomal regions using ldSelect, Tagger, and TagSNPs. We found that SNP subsets did not substantially overlap, and that the use of trio data did not greatly impact SNP selection. We then tested associations between HapMap genotypes and expression phenotypes on 28 CEU individuals as part of Genetic Analysis Workshop 15. Relative to the use of all SNPs (n = 210 SNPs across all regions), most subset methods were able to detect single-SNP and haplotype associations. Generally, pairwise selection approaches worked extremely well, relative to use of all SNPs, with marked reductions in the number of SNPs required. Haplotype-based approaches, which had identified smaller SNP subsets, missed associations in some regions. We conclude that the optimal tagging SNP method depends on the true model of the genetic association (i.e., whether a SNP or haplotype is responsible); unfortunately, this is often unknown at the time of SNP selection. Additional evaluations using empirical and simulated data are needed

Associations of common breast cancer susceptibility alleles with risk of breast cancer subtypes in BRCA1 and BRCA2 mutation carriers

Peer reviewedPublisher PD

Blood transfusion history and risk of non-Hodgkin lymphoma : an InterLymph pooled analysis

PURPOSE: To conduct a pooled analysis assessing the association of blood transfusion with risk of non-Hodgkin lymphoma (NHL). METHODS: We used harmonized data from 13 case-control studies (10,805 cases, 14,026 controls) in the InterLymph Consortium. Odds ratios (OR) and 95% confidence intervals (CI) were calculated using unconditional logistic regression, adjusted for study design variables. RESULTS: Among non-Hispanic whites (NHW), history of any transfusion was inversely associated with NHL risk for men (OR 0.74; 95% CI 0.65-0.83) but not women (OR 0.92; 95% CI 0.83-1.03), pheterogeneity = 0.014. Transfusion history was not associated with risk in other racial/ethnic groups. There was no trend with the number of transfusions, time since first transfusion, age at first transfusion, or decade of first transfusion, and further adjustment for socioeconomic status, body mass index, smoking, alcohol use, and HCV seropositivity did not alter the results. Associations for NHW men were stronger in hospital-based (OR 0.56; 95% CI 0.45-0.70) but still apparent in population-based (OR 0.84; 95% CI 0.72-0.98) studies. CONCLUSIONS: In the setting of a literature reporting mainly null and some positive associations, and the lack of a clear methodologic explanation for our inverse association restricted to NHW men, the current body of evidence suggests that there is no association of blood transfusion with risk of NHL