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Background While twin and adoption studies point to substantial genetic influence upon alcohol use, dependence, and other alcohol-related phenotypes, few of the genes underlying variation in these phenotypes have been identified. Markers in genes related to GABAergic activity-a system integral to many of alcohol's biological effects-have been implicated in alcohol use and alcohol-related psychopathology in linkage and association studies. Methods Using multiple methods, we conducted a comprehensive examination of the effects of markers in γ-aminobutyric acid ( GABA) system genes in a community-based sample of 7,224 individuals assessed in early and middle adulthood. In addition to testing the effect of individual single nucleotide polymorphism ( SNP) markers on alcohol-related phenotypes, we computed a polygenic score reflecting the aggregated effects of multiple GABA system SNPs. We also estimated the variance in alcohol-related phenotypes attributable to all GABA system markers considered simultaneously and conducted gene-based association tests. Results No method produced results indicative of an effect of GABA system variants on measures of alcohol use or misuse. Conclusions These results reflect alcohol-related behaviors in a population-representative sample, many of whom are still in adolescence, and in which the incidence of heavy drinking and alcohol-related symptomatology are relatively low. Contrasted with existing studies of the association between alcohol use and GABA system genes, our results suggest that the relationship may be limited to particular contexts, such as when accompanied by polysubstance abuse or a familial history of alcoholism. [ABSTRACT FROM AUTHOR]

Background: Suboptimal immunosuppression after kidney transplantation contributes to toxicity and loss of efficacy. Little is known regarding the impact of intra-patient variability of tacrolimus (TAC) doses and troughs in the early post-transplant period or the influence of genetic variants on variability., Methods: Coefficients of variation (CV) of TAC troughs and doses of 1226 European American (EA) and 246 African American (AA) adult recipients enrolled in DeKAF Genomics were compared for association with acute rejection and graft failure. Additionally, the influence of recipients' number of CYP3A5 loss-of-function alleles was assessed., Results: Acute rejection was associated with greater CV of dose in AA (P < 0.001) and EA recipients (P = 0.012). Graft failure was associated with a greater CV of dose (P = 0.022) and trough (P < 0.001) in AA, and higher CV of trough (P = 0.024) in EA recipients. In EA, CYP3A5 loss-of-function alleles were associated with decreased CV of trough (P = 0.0042) and increased CV of dose (P < 0.0001)., Conclusion: CYP3A5 loss-of-function alleles influence intra-patient TAC trough and dose variability. High variability of TAC dose increases risk of acute rejection. High variability of TAC trough increases risk of graft failure. Early clinical recognition of TAC dose and trough variability may improve patient management and outcomes., (© 2018 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

In multilocus association analysis, since some markers may not be associated with a trait, it seems attractive to use penalized regression with the capability of automatic variable selection. On the other hand, in spite of a rapidly growing body of literature on penalized regression, most focus on variable selection and outcome prediction, for which penalized methods are generally more effective than their nonpenalized counterparts. However, for statistical inference, i.e. hypothesis testing and interval estimation, it is less clear how penalized methods would perform, or even how to best apply them, largely due to lack of studies on this topic. In our motivating data for a cohort of kidney transplant recipients, it is of primary interest to assess whether a group of genetic variants are associated with a binary clinical outcome, acute rejection at 6 months. In this article, we study some technical issues and alternative implementations of hypothesis testing in Lasso penalized logistic regression, and compare their performance with each other and with several existing global tests, some of which are specifically designed as variance component tests for high-dimensional data. The most interesting, and perhaps surprising, conclusion of this study is that, for low to moderately high-dimensional data, statistical tests based on Lasso penalized regression are not necessarily more powerful than some existing global tests. In addition, in penalized regression, rather than building a test based on a single selected "best" model, combining multiple tests, each of which is built on a candidate model, might be more promising., (© 2011 Wiley Periodicals, Inc.)

Objective: To identify genes involved in phenotypes that increase one's risk for developing asthma, a complex disease that is likely genetically heterogeneous. Unlike other approaches to locus discovery in the presence of heterogeneity, this method seeks loci that segregate in all or most ascertained families while recognizing that other genes and environmental factors that modify the action of the common gene may vary across families., Methods: The method is based on seeking groups of families that differ, between groups, in the way affected individuals express the genotype. Then we use the distance of each individual to the cluster center for his family to define a quantitative trait. This quantitative trait is then subjected to a genome scan using variance components methods., Results: The method is applied to a data set of 27 multigenerational families with asthma, and a novel locus at 2q33 (at 210 cM) is identified., Conclusions: The proposed method has the potential to identify loci near genes that increase risk for asthma related phenotypes. The method could be used for other complex disorders that exhibit locus heterogeneity., (Copyright (c) 2007 S. Karger AG, Basel.)