Publications

DNA microarrays may be used to identify microbial species present in environmental and clinical samples. However, automated tools for reliable species identification based on observed microarray hybridization patterns are lacking. We present an algorithm, E-Predict, for microarray-based species identification. E-Predict compares observed hybridization patterns with theoretical energy profiles representing different species. We demonstrate the application of the algorithm to viral detection in a set of clinical samples and discuss its relevance to other metagenomic applications.

The demonstration of association between common genetic variants and chronic human diseases such as obesity could have profound implications for the prediction, prevention, and treatment of these conditions. Unequivocal proof of such an association, however, requires independent replication of initial positive findings. Recently, three (-243 A>G, +61450 C>A, and +83897 T>A) single nucleotide polymorphisms (SNPs) within glutamate decarboxylase 2 (GAD2) were found to be associated with class III obesity (body mass index > 40 kg/m2). The association was observed among 188 families (612 individuals) segregating the condition, and a case-control study of 575 cases and 646 lean controls. Functional data supporting a pathophysiological role for one of the SNPs (-243 A>G) were also presented. The gene GAD2 encodes the 65-kDa subunit of glutamic acid decarboxylase-GAD65. In the present study, we attempted to replicate this association in larger groups of individuals, and to extend the functional studies of the -243 A>G SNP. Among 2,359 individuals comprising 693 German nuclear families with severe, early-onset obesity, we found no evidence for a relationship between the three GAD2 SNPs and obesity, whether SNPs were studied individually or as haplotypes. In two independent case-control studies (a total of 680 class III obesity cases and 1,186 lean controls), there was no significant relationship between the -243 A>G SNP and obesity (OR = 0.99, 95% CI 0.83-1.18, p = 0.89) in the pooled sample. These negative findings were recapitulated in a meta-analysis, incorporating all published data for the association between the -243G allele and class III obesity, which yielded an OR of 1.11 (95% CI 0.90-1.36, p = 0.28) in a total sample of 1,252 class III obese cases and 1,800 lean controls. Moreover, analysis of common haplotypes encompassing the GAD2 locus revealed no association with severe obesity in families with the condition. We also obtained functional data for the -243 A>G SNP that does not support a pathophysiological role for this variant in obesity. Potential confounding variables in association studies involving common variants and complex diseases (low power to detect modest genetic effects, overinterpretation of marginal data, population stratification, and biological plausibility) are also discussed in the context of GAD2 and severe obesity.

Alkaline incubation of NADH results in the formation of a very potent inhibitor of complex I (NADH:ubiquinone oxidoreductase). Mass spectroscopy (molecular mass equal to 696) and absorption spectroscopy suggest that the inhibitor is derived from attachment of two oxygen atoms to the nicotinamide moiety of NADH. The inhibitor is competitive with respect to NADH with a K(i) of about 10(-8)M. The inhibitor efficiently suppresses NADH-oxidase, NADH-artificial acceptor reductase, and NADH-quinone reductase reactions catalyzed by submitochondrial particles, as well as the reactions catalyzed by either isolated complex I or the three subunit flavoprotein fragment of complex I.

Family history is a major risk factor for myocardial infarction (MI). However, known gene variants associated with MI cannot fully explain the genetic component of MI risk. We hypothesized that a gene-centric association study that was not limited to candidate genes could identify novel genetic associations with MI. We studied 11,053 single-nucleotide polymorphisms (SNPs) in 6,891 genes, focusing on SNPs that could influence gene function to increase the likelihood of identifying disease-causing gene variants. To minimize false-positive associations generated by multiple testing, two studies were used to identify a limited number of nominally associated SNPs; a third study tested the hypotheses that these SNPs are associated with MI. In the initial study (of 340 cases and 346 controls), 637 SNPs were associated with MI (P<.05); these were evaluated in a second study (of 445 cases and 606 controls), and 31 of the 637 SNPs were associated with MI (P<.05) and had the same risk allele as in the first study. For each of these 31 SNPs, we tested the hypothesis that it is associated with MI, using a third study (of 560 cases and 891 controls). We found that four of these gene variants were associated with MI (P<.05; false-discovery rate <10%) and had the same risk allele as in the first two studies. These gene variants encode the cytoskeletal protein palladin (KIAA0992 [odds ratio (OR) 1.40]), a tyrosine kinase (ROS1 [OR 1.75]), and two G protein-coupled receptors (TAS2R50 [OR 1.58] and OR13G1 [OR 1.40]); all ORs are for carriers of two versus zero risk alleles. These findings could lead to a better understanding of MI pathophysiology and improved patient risk assessment.