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1.  Resequencing of Nicotinic Acetylcholine Receptor Genes and Association of Common and Rare Variants with the Fagerström Test for Nicotine Dependence 
Neuropsychopharmacology  2010;35(12):2392-2402.
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.
PMCID: PMC3055324  PMID: 20736995
Fagerström test for nicotine dependence; single-nucleotide polymorphism; candidate gene association scan; treatment-seeking smokers; addiction & substance abuse; clinical pharmacology; clinical trials; neurogenetics; acetylcholine
2.  MicroRNA expression differentiates histology and predicts survival of lung cancer 
The molecular drivers that determine histology in lung cancer are largely unknown. We investigated whether microRNA (miR) expression profiles can differentiate histological subtypes and predict survival for non-small cell lung cancer.
Experimental design
We analyzed miR expression in 165 adenocarcinoma (AD) and 125 squamous cell carcinoma (SQ) tissue samples from the Environmental And Genetics in Lung cancer Etiology (EAGLE) study using a custom oligo array with 440 human mature antisense miRs. We compared miR expression profiles using t-tests and F-tests and accounted for multiple testing using global permutation tests. We assessed the association of miR expression with tobacco smoking using Spearman correlation coefficients and linear regression models, and with clinical outcome using log-rank tests, Cox proportional hazards and survival risk prediction models, accounting for demographic and tumor characteristics.
MiR expression profiles strongly differed between AD and SQ (global p<0.0001), particularly in the early stages, and included miRs located on chromosome loci most often altered in lung cancer (e.g., 3p21-22). Most miRs, including all members of the let-7 family, were down-regulated in SQ. Major findings were confirmed by QRT-PCR in EAGLE samples and in an independent set of lung cancer cases. In SQ, low expression of miRs down-regulated in the histology comparison was associated with 1.2 to 3.6-fold increased mortality risk. A 5-miR signature significantly predicted survival for SQ.
We identified a miR expression profile that strongly differentiated AD from SQ and had prognostic implications. These findings may lead to histology-based therapeutic approaches.
PMCID: PMC3163170  PMID: 20068076
3.  Association Study of 182 Candidate Genes in Anorexia Nervosa 
We performed association studies with 5,151 SNPs that were judged as likely candidate genetic variations conferring susceptibility to anorexia nervosa (AN) based on location under reported linkage peaks, previous results in the literature (182 candidate genes), brain expression, biological plausibility, and estrogen responsivity. We employed a case–control design that tested each SNP individually as well as haplotypes derived from these SNPs in 1,085 case individuals with AN diagnoses and 677 control individuals. We also performed separate association analyses using three increasingly restrictive case definitions for AN: all individuals with any subtype of AN (All AN: n = 1,085); individuals with AN with no binge eating behavior (AN with No Binge Eating: n = 687); and individuals with the restricting subtype of AN (Restricting AN: n = 421). After accounting for multiple comparisons, there were no statistically significant associations for any individual SNP or haplotype block with any definition of illness. These results underscore the importance of large samples to yield appropriate power to detect genotypic differences in individuals with AN and also motivate complementary approaches involving Genome-Wide Association (GWA) studies, Copy Number Variation (CNV) analyses, sequencing-based rare variant discovery assays, and pathway-based analysis in order to make up for deficiencies in traditional candidate gene approaches to AN.
PMCID: PMC2963154  PMID: 20468064
single nucleotide polymorphisms; probands; anorexia nervosa; bulimia nervosa
4.  Using DNA fingerprints to infer familial relationships within NHANES III households 
Developing, targeting, and evaluating genomic strategies for population-based disease prevention require population-based data. In response to this urgent need, genotyping has been conducted within the Third National Health and Nutrition Examination (NHANES III), the nationally-representative household-interview health survey in the U.S. However, before these genetic analyses can occur, family relationships within households must be accurately ascertained. Unfortunately, reported family relationships within NHANES III households based on questionnaire data are incomplete and inconclusive with regards to actual biological relatedness of family members. We inferred family relationships within households using DNA fingerprints (Identifiler®) that contain the DNA loci used by law enforcement agencies for forensic identification of individuals. However, performance of these loci for relationship inference is not well understood. We evaluated two competing statistical methods for relationship inference on pairs of household members: an exact likelihood ratio relying on allele frequencies to an Identical By State (IBS) likelihood ratio that only requires matching alleles. We modified these methods to account for genotyping errors and population substructure. The two methods usually agree on the rankings of the most likely relationships. However, the IBS method underestimates the likelihood ratio by not accounting for the informativeness of matching rare alleles. The likelihood ratio is sensitive to estimates of population substructure, and parent-child relationships are sensitive to the specified genotyping error rate. These loci were unable to distinguish second-degree relationships and cousins from being unrelated. The genetic data is also useful for verifying reported relationships and identifying data quality issues. An important by-product is the first explicitly nationally-representative estimates of allele frequencies at these ubiquitous forensic loci.
PMCID: PMC2909633  PMID: 20664713
Forensics; allele sharing; population structure; CODIS; IBS; IBD

Results 1-4 (4)