Single-Nucleotide Polymorphisms Reveal Spatial Diversity Among Clones of Yersinia pestis During Plague Outbreaks in Colorado and the Western United States.

BACKGROUND: In western North America, plague epizootics caused by Yersinia pestis appear to sweep across landscapes, primarily infecting and killing rodents, especially ground squirrels and prairie dogs. During these epizootics, the risk of Y. pestis transmission to humans is highest. While empirical models that include climatic conditions and densities of rodent hosts and fleas can predict when epizootics are triggered, bacterial transmission patterns across landscapes, and the scale at which Y. pestis is maintained in nature during inter-epizootic periods, are poorly defined. Elucidating the spatial extent of Y. pestis clones during epizootics can determine whether bacteria are propagated across landscapes or arise independently from local inter-epizootic maintenance reservoirs. MATERIAL AND METHODS: We used DNA microarray technology to identify single-nucleotide polymorphisms (SNPs) in 34 Y. pestis isolates collected in the western United States from 1980 to 2006, 21 of which were collected during plague epizootics in Colorado. Phylogenetic comparisons were used to elucidate the hypothesized spread of Y. pestis between the mountainous Front Range and the eastern plains of northern Colorado during epizootics. Isolates collected from across the western United States were included for regional comparisons. RESULTS: By identifying SNPs that mark individual clones, our results strongly suggest that Y. pestis is maintained locally and that widespread epizootic activity is caused by multiple clones arising independently at small geographic scales. This is in contrast to propagation of individual clones being transported widely across landscapes. Regionally, our data are consistent with the notion that Y. pestis diversifies at relatively local scales following long-range translocation events. We recommend that surveillance and prediction by public health and wildlife management professionals focus more on models of local or regional weather patterns and ecological factors that may increase risk of widespread epizootics, rather than predicting or attempting to explain epizootics on the basis of movement of host species that may transport plague.

Assessment of clinical validity of a breast cancer risk model combining genetic and clinical information.

BACKGROUND: The Gail model is widely used for the assessment of risk of invasive breast cancer based on recognized clinical risk factors. In recent years, a substantial number of single-nucleotide polymorphisms (SNPs) associated with breast cancer risk have been identified. However, it remains unclear how to effectively integrate clinical and genetic risk factors for risk assessment. METHODS: Seven SNPs associated with breast cancer risk were selected from the literature and genotyped in white non-Hispanic women in a nested case-control cohort of 1664 case patients and 1636 control subjects within the Women's Health Initiative Clinical Trial. SNP risk scores were computed based on previously published odds ratios assuming a multiplicative model. Combined risk scores were calculated by multiplying Gail risk estimates by the SNP risk scores. The independence of Gail risk and SNP risk was evaluated by logistic regression. Calibration of relative risks was evaluated using the Hosmer-Lemeshow test. The performance of the combined risk scores was evaluated using receiver operating characteristic curves. The net reclassification improvement (NRI) was used to assess improvement in classification of women into low (<1.5%), intermediate (1.5%-2%), and high (>2%) categories of 5-year risk. All tests of statistical significance were two-sided. RESULTS: The SNP risk score was nearly independent of Gail risk. There was good agreement between predicted and observed SNP relative risks. In the analysis for receiver operating characteristic curves, the combined risk score was more discriminating, with area under the curve of 0.594 compared with area under the curve of 0.557 for Gail risk alone (P < .001). Classification also improved for 5.6% of case patients and 2.9% of control subjects, showing an NRI value of 0.085 (P = 1.0 × 10⁻5). Focusing on women with intermediate Gail risk resulted in an improved NRI of 0.195 (P = 8.6 × 10⁻5). CONCLUSIONS: Combining validated common genetic risk factors with clinical risk factors resulted in modest improvement in classification of breast cancer risks in white non-Hispanic postmenopausal women. Classification performance was further improved by focusing on women at intermediate risk.

Resequencing of nicotinic acetylcholine receptor genes and association of common and rare variants with the Fagerström test for nicotine dependence.

Common single-nucleotide polymorphisms (SNPs) at nicotinic acetylcholine receptor (nAChR) subunit genes have previously been associated with measures of nicotine dependence. We investigated the contribution of common SNPs and rare single-nucleotide variants (SNVs) in nAChR genes to Fagerström test for nicotine dependence (FTND) scores in treatment-seeking smokers. Exons of 10 genes were resequenced with next-generation sequencing technology in 448 European-American participants of a smoking cessation trial, and CHRNB2 and CHRNA4 were resequenced by Sanger technology to improve sequence coverage. A total of 214 SNP/SNVs were identified, of which 19.2% were excluded from analyses because of reduced completion rate, 73.9% had minor allele frequencies <5%, and 48.1% were novel relative to dbSNP build 129. We tested associations of 173 SNP/SNVs with the FTND score using data obtained from 430 individuals (18 were excluded because of reduced completion rate) using linear regression for common, the cohort allelic sum test and the weighted sum statistic for rare, and the multivariate distance matrix regression method for both common and rare SNP/SNVs. Association testing with common SNPs with adjustment for correlated tests within each gene identified a significant association with two CHRNB2 SNPs, eg, the minor allele of rs2072660 increased the mean FTND score by 0.6 Units (P=0.01). We observed a significant evidence for association with the FTND score of common and rare SNP/SNVs at CHRNA5 and CHRNB2, and of rare SNVs at CHRNA4. Both common and/or rare SNP/SNVs from multiple nAChR subunit genes are associated with the FTND score in this sample of treatment-seeking smokers.

Variant in PNPLA3 is associated with alcoholic liver disease.

Two genome-wide association studies (GWAS) have described associations of variants in PNPLA3 with nonalcoholic fatty liver and plasma liver enzyme levels. We investigated the contributions of these variants to liver disease in Mestizo subjects with a history of alcohol dependence. We found that rs738409 in PNPLA3 is strongly associated with alcoholic liver disease and clinically evident alcoholic cirrhosis (unadjusted OR= 2.25, P=1.7 x 10(-10); ancestry-adjusted OR=1.79, P=1.9 x 10(-5)).

A genomewide association study of skin pigmentation in a South Asian population.

We have conducted a multistage genomewide association study, using 1,620,742 single-nucleotide polymorphisms to systematically investigate the genetic factors influencing intrinsic skin pigmentation in a population of South Asian descent. Polymorphisms in three genes--SLC24A5, TYR, and SLC45A2--yielded highly significant replicated associations with skin-reflectance measurements, an indirect measure of melanin content in the skin. The associations detected in these three genes, in an additive manner, collectively account for a large fraction of the natural variation of skin pigmentation in a South Asian population. Our study is the first to interrogate polymorphisms across the genome, to find genetic determinants of the natural variation of skin pigmentation within a human population.

Matching strategies for genetic association studies in structured populations.

Association studies in populations that are genetically heterogeneous can yield large numbers of spurious associations if population subgroups are unequally represented among cases and controls. This problem is particularly acute for studies involving pooled genotyping of very large numbers of single-nucleotide-polymorphism (SNP) markers, because most methods for analysis of association in structured populations require individual genotyping data. In this study, we present several strategies for matching case and control pools to have similar genetic compositions, based on ancestry information inferred from genotype data for approximately 300 SNPs tiled on an oligonucleotide-based genotyping array. We also discuss methods for measuring the impact of population stratification on an association study. Results for an admixed population and a phenotype strongly confounded with ancestry show that these simple matching strategies can effectively mitigate the impact of population stratification.