Warfarin-dosing algorithms incorporating CYP2C9 and VKORC1 ؊1639G>A improve dose prediction compared with algorithms based solely on clinical and demographic factors. However, these algorithms better capture dose variability among whites than Asians or blacks. Herein, we evaluate whether other VKORC1 polymorphisms and haplotypes explain additional variation in warfarin dose beyond that explained by VKORC1 ؊1639G>A among Asians (n ‫؍‬ 1103), blacks (n ‫؍‬ 670), and whites (n ‫؍‬ 3113).Participants were recruited from 11 countries as part of the International Warfarin Pharmacogenetics Consortium effort. Evaluation of the effects of individual VKORC1 single nucleotide polymorphisms (SNPs) and haplotypes on warfarin dose used both univariate and multivariable linear regression. VKORC1 ؊1639G>A and 1173C>T individually explained the greatest variance in dose in all 3 racial groups. Incorporation of additional VKORC1 SNPs or haplotypes did not further improve dose prediction.VKORC1 explained greater variability in dose among whites than blacks and Asians. Differences in the percentage of variance in dose explained by VKORC1 across race were largely accounted for by the frequency of the ؊1639A (or 1173T) allele. Thus, clinicians should recognize that, although at a population level, the contribution of VKORC1 toward dose requirements is higher in whites than in nonwhites; genotype predicts similar dose requirements across racial groups. (Blood. 2010;115(18):3827-3834) IntroductionWarfarin, the most commonly prescribed anticoagulant, exhibits large interpatient variability in dose requirements. Patient-specific factors (eg, age, body size, race, concurrent diseases, and medications) explain some of the variability in warfarin dose, but genetic factors influencing warfarin response explain a significantly higher proportion of the variability in dose. 1 Candidate-gene association studies 2-22 have identified 2 genes responsible for the main proportion of the genetic effect: CYP2C9, which codes for the enzyme cytochrome P450 2C9 that metabolizes S-warfarin, 23,24 and VKORC1, which codes for warfarin's target, vitamin K epoxide reductase. 25,26 The influence of CYP2C9 and VKORC1 has also been confirmed by genome-wide association studies among whites. 27,28 These studies suggest that identification of common variants in other genes exhibiting influence of magnitude similar to that of CYP2C9 and VKORC1 is unlikely in whites. The most influential CYP2C9 polymorphisms are nonsynonymous coding variants resulting in reduced enzyme activity and decreased metabolic capacity. [29][30][31] In contrast, common VKORC1 variants associated with warfarin dose are noncoding polymorphisms, the effects of which are thought to be mediated through differential expression of the VKOR protein. 32 These polymorphisms are within a region of strong linkage disequilibrium (LD) among patients of European ancestry; thus, they may all point to the same common causal polymorphism. 10,14 However, neither the causative VKORC1 polymorphism nor the molecula...

Summary Background VKORC1 and CYP2C9 are important contributors to warfarin dose variability, but explain less variability for individuals of African descent than for those of European or Asian descent. We aimed to identify additional variants contributing to warfarin dose requirements in African Americans. Methods We did a genome-wide association study of discovery and replication cohorts. Samples from African-American adults (aged ≥18 years) who were taking a stable maintenance dose of warfarin were obtained at International Warfarin Pharmacogenetics Consortium (IWPC) sites and the University of Alabama at Birmingham (Birmingham, AL, USA). Patients enrolled at IWPC sites but who were not used for discovery made up the independent replication cohort. All participants were genotyped. We did a stepwise conditional analysis, conditioning first for VKORC1 −1639G→A, followed by the composite genotype of CYP2C9*2 and CYP2C9*3. We prespecified a genome-wide significance threshold of p<5×10−8 in the discovery cohort and p<0·0038 in the replication cohort. Findings The discovery cohort contained 533 participants and the replication cohort 432 participants. After the prespecified conditioning in the discovery cohort, we identified an association between a novel single nucleotide polymorphism in the CYP2C cluster on chromosome 10 (rs12777823) and warfarin dose requirement that reached genome-wide significance (p=1·51×10−8). This association was confirmed in the replication cohort (p=5·04×10−5); analysis of the two cohorts together produced a p value of 4·5×10−12. Individuals heterozygous for the rs12777823 A allele need a dose reduction of 6·92 mg/week and those homozygous 9·34 mg/week. Regression analysis showed that the inclusion of rs12777823 significantly improves warfarin dose variability explained by the IWPC dosing algorithm (21% relative improvement). Interpretation A novel CYP2C single nucleotide polymorphism exerts a clinically relevant effect on warfarin dose in African Americans, independent of CYP2C9*2 and CYP2C9*3. Incorporation of this variant into pharmacogenetic dosing algorithms could improve warfarin dose prediction in this population. Funding National Institutes of Health, American Heart Association, Howard Hughes Medical Institute, Wisconsin Network for Health Research, and the Wellcome Trust.

Background Mutations in Leucine-rich repeat kinase 2 (LRRK2) enhance levels of autophosphorylated LRRK2 protein and are the most common known cause of inherited Parkinson disease (PD). LRRK2 has been further implicated in susceptibility to idiopathic PD in genetic association studies. Objective To compare autophosphorylated Ser(P)-1292 LRRK2 levels from biobanked urine samples with clinical data in PD and controls. Methods Ser(P)-1292 LRRK2 levels were measured from urine exosome fractions from 79 PD and 79 neurologically healthy controls enrolled into the Parkinson Disease Biomarker Program at the University of Alabama at Birmingham. Results Ser(P)-1292 LRRK2 levels were higher in males than females (p<0.0001) and elevated in PD compared to controls (p=0.0014). Ser(P)-1292 LRRK2 levels were higher in PD cases with worse cognition and correlated with poor performance in MoCA (r=−0.2679 [−0.4628, −0.0482]), MDS-UPDRS subscales 1 and 2 (r=0.2239 [0.0014, 0,4252], 0.3404 [0.1276, 0.5233] respectively), Epworth Sleepiness Scale (r=0.3215 [0.1066, 0.5077]), and Modified Schwab and England Activities of Daily Living Scales (r=−0.4455 [−0.6078, −0.2475]). Ser(P)-1292 LRRK2 levels predicted those with worse cognitive impairment in PD patients with some success (c=0.73). Conclusions Urinary exosome Ser(P)-1292 LRRK2 levels are elevated in idiopathic PD and correlated with the severity of cognitive impairment and difficultly in accomplishing activities of daily living. These results implicate biochemical changes in LRRK2 in idiopathic PD.

Empirical evidence supporting the commonality of gene × gene interactions, coupled with frequent failure to replicate results from previous association studies, has prompted statisticians to develop methods to handle this important subject. Nonparametric methods have generated intense interest because of their capacity to handle high-dimensional data. Genome-wide association analysis of large-scale SNP data is challenging mathematically and computationally. In this paper, we describe major issues and questions arising from this challenge, along with methodological implications. Data reduction and pattern recognition methods seem to be the new frontiers in efforts to detect gene × gene interactions comprehensively. Currently, there is no single method that is recognized as the ‘best’ for detecting, characterizing, and interpreting gene × gene interactions. Instead, a combination of approaches with the aim of balancing their specific strengths may be the optimal approach to investigate gene × gene interactions in human data.

Background: Although the influence of VKORC1 and CYP2C9 polymorphisms on warfarin response has been studied, variability in dose explained by CYP2C9 and VKORC1 is lower among African-Americans compared with European-Americans. This has lead investigators to hypothesize that assessment of VKORC1 haplotypes may help capture a greater proportion of the variability in dose for this under-represented group. However, the inadequate representation of African-Americans and the assessment of a few VKORC1 polymorphisms have hindered this effort.