Recently, genetic association findings for nicotine dependence, smoking behavior, and smoking-related diseases converged to implicate the chromosome 15q25.1 region, which includes the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit genes. In particular, association with the nonsynonymous CHRNA5 SNP rs16969968 and correlates has been replicated in several independent studies. Extensive genotyping of this region has suggested additional statistically distinct signals for nicotine dependence, tagged by rs578776 and rs588765. One goal of the Consortium for the Genetic Analysis of Smoking Phenotypes (CGASP) is to elucidate the associations among these markers and dichotomous smoking quantity (heavy versus light smoking), lung cancer, and chronic obstructive pulmonary disease (COPD). We performed a meta-analysis across 34 datasets of European-ancestry subjects, including 38,617 smokers who were assessed for cigarettes-per-day, 7,700 lung cancer cases and 5,914 lung-cancer-free controls (all smokers), and 2,614 COPD cases and 3,568 COPD-free controls (all smokers). We demonstrate statistically independent associations of rs16969968 and rs588765 with smoking (mutually adjusted p-values<10−35 and <10−8 respectively). Because the risk alleles at these loci are negatively correlated, their association with smoking is stronger in the joint model than when each SNP is analyzed alone. Rs578776 also demonstrates association with smoking after adjustment for rs16969968 (p<10−6). In models adjusting for cigarettes-per-day, we confirm the association between rs16969968 and lung cancer (p<10−20) and observe a nominally significant association with COPD (p = 0.01); the other loci are not significantly associated with either lung cancer or COPD after adjusting for rs16969968. This study provides strong evidence that multiple statistically distinct loci in this region affect smoking behavior. This study is also the first report of association between rs588765 (and correlates) and smoking that achieves genome-wide significance; these SNPs have previously been associated with mRNA levels of CHRNA5 in brain and lung tissue.

Genetic association studies have shown the importance of variants in the CHRNA5-CHRNA3-CHRNB4 cholinergic nicotinic receptor subunit gene cluster on chromosome 15q24-25.1 for the risk of nicotine dependence, smoking, and lung cancer in populations of European descent. We have carried out a detailed study of this region using dense genotyping in both European-Americans and African-Americans. We genotyped 75 known single nucleotide polymorphisms (SNPs) and one sequencing-discovered SNP in an African-American sample (N = 710) and in a European-American sample (N = 2,062). Cases were nicotine-dependent and controls were nondependent smokers. The nonsynonymous CHRNA5 SNP rs16969968 is the most significant SNP associated with nicotine dependence in the full sample of 2,772 subjects [P = 4.49 Â 10 À8

A region along chromosome 7q was recently linked to components of the metabolic syndrome (MetS) in several genome-wide linkage studies. Within this region, the CD36 gene, which encodes a membrane receptor for long-chain fatty acids and lipoproteins, is a potentially important candidate. CD36 has been documented to play an important role in fatty acid metabolism in vivo and subsequently may be involved in the etiology of the MetS. The protein also impacts survival to malaria and the influence of natural selection has resulted in high CD36 genetic variability in populations of African descent. We evaluated 36 tag SNPs across CD36 in the HyperGen population sample of 2020 African-Americans for impact on the MetS and its quantitative traits. Five SNPs associated with increased odds for the MetS [P = 0.0027-0.03, odds ratio (OR) = 1.3-1.4]. Coding SNP, rs3211938, previously shown to influence malaria susceptibility, is documented to result in CD36 deficiency in a homozygous subject. This SNP conferred protection against the MetS (P = 0.0012, OR = 0.61, 95%CI: 0.46-0.82), increased high-density lipoprotein cholesterol, HDL-C (P = 0.00018) and decreased triglycerides (P = 0.0059). Fifteen additional SNPs associated with HDL-C (P = 0.0028-0.044). We conclude that CD36 variants may impact MetS pathophysiology and HDL metabolism, both predictors of the risk of heart disease and type 2 diabetes.

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The purpose of this study was to assess the metabolic profile of plasma samples from cows with clinical and subclinical ketosis. According to clinical signs and 3-hydroxybutyrate plasma levels, 81 multiparous Holstein cows were selected from a dairy farm 7 to 21 d after calving. The cows were divided into 3 groups: cows with clinical ketosis, cows with subclinical ketosis, and healthy control cows. (1)H-Nuclear magnetic resonance-based metabolomics was used to assess the plasma metabolic profiles of the 3 groups. The data were analyzed by principal component analysis, partial least squares discriminant analysis, and orthogonal partial least-squares discriminant analysis. The differences in metabolites among the 3 groups were assessed. The orthogonal partial least-squares discriminant analysis model differentiated the 3 groups of plasma samples. The model predicted clinical ketosis with a sensitivity of 100% and a specificity of 100%. In the case of subclinical ketosis, the model had a sensitivity of 97.0% and specificity of 95.7%. Twenty-five metabolites, including acetoacetate, acetone, lactate, glucose, choline, glutamic acid, and glutamine, were different among the 3 groups. Among the 25 metabolites, 4 were upregulated, 7 were downregulated, and 14 were both upregulated and downregulated. The results indicated that plasma (1)H-nuclear magnetic resonance-based metabolomics, coupled with pattern recognition analytical methods, not only has the sensitivity and specificity to distinguish cows with clinical and subclinical ketosis from healthy controls, but also has the potential to be developed into a clinically useful diagnostic tool that could contribute to a further understanding of the disease mechanisms.