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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

Background: Breast cancer concern is a major reason for the recent marked reduction in use of postmenopausal hormone therapy, although equally effective means of controlling menopausal symptoms are lacking. Single nucleotide polymorphisms (SNP) in the fibroblast growth factor receptor 2 (FGFR2) gene are substantially associated with postmenopausal breast cancer risk and could influence hormone therapy effects. Participants and Methods: We interrogated eight SNPs in intron 2 of the FGFR2 gene for 2,166 invasive breast cancer cases from the Women's Health Initiative clinical trial and one-to-one matched controls to confirm an association with breast cancer risk. We used case-only analyses to examine the dependence of estrogen plus progestin and estrogen-alone odds ratios on SNP genotype. Results: Seven FGFR2 SNPs, including six in a single linkage disequilibrium region, were found to associate strongly (P < 10−7) with breast cancer risk. SNP rs3750817 (minor allele T with frequency 0.39) had an estimated per-minor-allele odds ratio of 0.78, and was not in such strong linkage disequilibrium with the other SNPs. The genotype of this SNP related significantly (P < 0.05) to hormone therapy odds ratios. For estrogen plus progestin, the odds ratios (95% confidence intervals) at 0, 1, and 2 minor SNP alleles were 1.52 (1.14-2.02), 1.33 (1.01-1.75), and 0.69 (0.41-1.17), whereas the corresponding values for estrogen alone were 0.74 (0.51-1.09), 0.99 (0.68-1.44), and 0.34 (0.15-0.76). Conclusions: Postmenopausal women having TT genotype for SNP rs3750817 have a reduced breast cancer risk and seem to experience comparatively favorable effects of postmenopausal hormone therapy. (Cancer Epidemiol Biomarkers Prev 2009;18(11):3079–85)

Systemic lupus erythematosus (SLE) is a clinically heterogeneous disease in which the risk of disease is influenced by complex genetic and environmental contributions. Alleles of HLA-DRB1, IRF5, and STAT4 are established susceptibility genes; there is strong evidence for the existence of additional risk loci.We genotyped more than 500,000 single-nucleotide polymorphisms (SNPs) in DNA samples from 1311 case subjects with SLE and 1783 control subjects; all subjects were North Americans of European descent. Genotypes from 1557 additional control subjects were obtained from public data repositories. We measured the association between the SNPs and SLE after applying strict quality-control filters to reduce technical artifacts and to correct for the presence of population stratification. Replication of the top loci was performed in 793 case subjects and 857 control subjects from Sweden.Genetic variation in the region upstream from the transcription initiation site of the gene encoding B lymphoid tyrosine kinase (BLK) and C8orf13 (chromosome 8p23.1) was associated with disease risk in both the U.S. and Swedish case-control series (rs13277113; odds ratio, 1.39; P=1x10(-10)) and also with altered levels of messenger RNA in B-cell lines. In addition, variants on chromosome 16p11.22, near the genes encoding integrin alpha M (ITGAM, or CD11b) and integrin alpha X (ITGAX), were associated with SLE in the combined sample (rs11574637; odds ratio, 1.33; P=3x10(-11)).We identified and then confirmed through replication two new genetic loci for SLE: a promoter-region allele associated with reduced expression of BLK and increased expression of C8orf13 and variants in the ITGAM-ITGAX region.

Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2 > 0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P

For admixture mapping studies in Mexican Americans (MAM), we define a genomewide single-nucleotide–polymorphism (SNP) panel that can distinguish between chromosomal segments of Amerindian (AMI) or European (EUR) ancestry. These studies used genotypes for >400,000 SNPs, defined in EUR and both Pima and Mayan AMI, to define a set of ancestry-informative markers (AIMs). The use of two AMI populations was necessary to remove a subset of SNPs that distinguished genotypes of only one AMI subgroup from EUR genotypes. The AIMs set contained 8,144 SNPs separated by a minimum of 50 kb with only three intermarker intervals >1 Mb and had EUR/AMI FST values >0.30 (mean FST=0.48) and Mayan/Pima FST values

Tobacco use is a leading contributor to disability and death worldwide, and genetic factors contribute in part to the development of nicotine dependence. To identify novel genes for which natural variation contributes to the development of nicotine dependence, we performed a comprehensive genome wide association study using nicotine dependent smokers as cases and non-dependent smokers as controls. To allow the efficient, rapid, and cost effective screen of the genome, the study was carried out using a two-stage design. In the first stage, genotyping of over 2.4 million single nucleotide polymorphisms (SNPs) was completed in case and control pools. In the second stage, we selected SNPs for individual genotyping based on the most significant allele frequency differences between cases and controls from the pooled results. Individual genotyping was performed in 1050 cases and 879 controls using 31 960 selected SNPs. The primary analysis, a logistic regression model with covariates of age, gender, genotype and gender by genotype interaction, identified 35 SNPs with P-values less than 10(-4) (minimum P-value 1.53 x 10(-6)). Although none of the individual findings is statistically significant after correcting for multiple tests, additional statistical analyses support the existence of true findings in this group. Our study nominates several novel genes, such as Neurexin 1 (NRXN1), in the development of nicotine dependence while also identifying a known candidate gene, the beta3 nicotinic cholinergic receptor. This work anticipates the future directions of large-scale genome wide association studies with state-of-the-art methodological approaches and sharing of data with the scientific community.

Nicotine dependence is one of the world's leading causes of preventable death. To discover genetic variants that influence risk for nicotine dependence, we targeted over 300 candidate genes and analyzed 3713 single nucleotide polymorphisms (SNPs) in 1050 cases and 879 controls. The Fagerström test for nicotine dependence (FTND) was used to assess dependence, in which cases were required to have an FTND of 4 or more. The control criterion was strict: control subjects must have smoked at least 100 cigarettes in their lifetimes and had an FTND of 0 during the heaviest period of smoking. After correcting for multiple testing by controlling the false discovery rate, several cholinergic nicotinic receptor genes dominated the top signals. The strongest association was from an SNP representing CHRNB3, the beta3 nicotinic receptor subunit gene (P = 9.4 x 10(-5)). Biologically, the most compelling evidence for a risk variant came from a non-synonymous SNP in the alpha5 nicotinic receptor subunit gene CHRNA5 (P = 6.4 x 10(-4)). This SNP exhibited evidence of a recessive mode of inheritance, resulting in individuals having a 2-fold increase in risk of developing nicotine dependence once exposed to cigarette smoking. Other genes among the top signals were KCNJ6 and GABRA4. This study represents one of the most powerful and extensive studies of nicotine dependence to date and has found novel risk loci that require confirmation by replication studies.

Allelic variation of gene expression is common in humans, and is of interest because of its potential contribution to variation in heritable traits. To identify human genes with allelic expression differences, we genotype DNA and examine mRNA isolated from the white blood cells of 12 unrelated individuals using oligonucleotide arrays containing 8406 exonic SNPs. Of the exonic SNPs, 1983, located in 1389 genes, are both expressed in the white blood cells and heterozygous in at least one of the 12 individuals, and thus can be examined for differential allelic expression. Of the 1389 genes, 731 (53%) show allele expression differences in at least one individual. To gain insight into the regulatory mechanisms governing allelic expression differences, we analyze a set of 60 genes containing exonic SNPs that are heterozygous in three or more samples, and for which all heterozygotes display differential expression. We find three patterns of allelic expression, suggesting different underlying regulatory mechanisms. Exonic SNPs in three of the 60 genes are monoallelically expressed in the human white blood cells, and when examined in families show expression of only the maternal copy, consistent with regulation by imprinting. Approximately one-third of the genes have the same allele expressed more highly in all heterozygotes, suggesting that their regulation is predominantly influenced by cis-elements in strong linkage disequilibrium with the assayed exonic SNP. The remaining two-thirds of the genes have different alleles expressed more highly in different heterozygotes, suggesting that their expression differences are influenced by factors not in strong linkage disequilibrium with the assayed exonic SNP.

Association studies are used to identify genetic determinants of complex human traits of medical interest. With the large number of validated single nucleotide polymorphisms (SNPs) currently available, two limiting factors in association studies are genotyping capability and costs. Pooled DNA genotyping has been proposed as an efficient means of screening SNPs for allele frequency differences in case-control studies and for prioritising them for subsequent individual genotyping analysis. Here, we apply quantitative pooled genotyping followed by individual genotyping and replication to identify associations with human serum high-density lipoprotein (HDL) cholesterol levels. The DNA from individuals with low and high HDL cholesterol levels was pooled separately, each pool was amplified by polymerase chain reaction in triplicate and each amplified product was separately hybridised to a high-density oligonucleotide array. Allele frequency differences between case and control groups with low and high HDL cholesterol levels were estimated for 7,283 SNPs distributed across 71 candidate gene regions spanning a total of 17.1 megabases. A novel method was developed to take advantage of independently derived haplotype map information to improve the pooled estimates of allele frequency differences. A subset of SNPs with the largest estimated allele frequency differences between low and high HDL cholesterol groups was chosen for individual genotyping in the study population, as well as in a separate replication population. Four SNPs in a single haplotype block within the cholesteryl ester transfer protein (CETP) gene interval were significantly associated with HDL cholesterol levels in both populations. Our study is among the first to demonstrate the application of pooled genotyping followed by confirmation with individual genotyping to identify genetic determinants of a complex trait.

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.

To the Editor: In this issue, four independent research teams present new genetic association data for 13 SNPs previously reported by us to be potentially associated with Parkinson disease (PD [MIM 168600]).1 Two groups2,3 report statistically significant association between one or more of these SNPs and PD, whereas two groups4,5 find no statistically significant association between PD and any of the SNPs investigated. In an accompanying letter,6 Dr. Richard H. Myers provides his qualitative assessment of the implications of these new results. We have performed a Mantel-Haenszel analysis, using 10 of the 13 SNPs not displaying linkage disequilibrium (LD) with each other—combining the data of Li et al.,3 Farrer et al.,4 and Goris et al.5—to provide an overall quantitative assessment of the new results. The odds ratios (ORs) are reported for the SNP alleles that increase the risk of PD1 (table 1). The X-linked SNP rs7878232 was not included in this analysis, since subgroup-level data for males and females were not reported by all groups. The results of Clarimon et al.2 were also not included, given the significant difference in SNP allele frequency observed between the European and Taiwanese control samples. This analysis reveals that none of the 10 SNPs shows statistically significant association with PD (i.e., P

Background Genome-wide association studies have identified several genomic regions that are associated with stroke risk, but these provide an explanation for only a small fraction of familial stroke aggregation. Genotype by environment interactions may contribute further to such an explanation. The Women's Health Initiative (WHI) clinical trial found increased stroke risk with postmenopausal hormone therapy (HT) and provides an efficient setting for evaluating genotype-HT interaction on stroke risk. Methods We examined HT by genotype interactions for 392 SNPs selected from candidate gene studies, and 2,371 SNPs associated with changes in blood protein concentrations after hormone therapy, in analyses that included 2,045 postmenopausal women who developed stroke during WHI clinical trial and observational study follow-up and one-to-one matched controls. A two-stage procedure was implemented where SNPs passing the first stage screening based on marginal association with stroke risk were tested in the second stage for interaction with HT using case-only analysis. Results The two-stage procedure identified two SNPs, rs2154299 and rs12194855, in the coagulation factor XIII subunit A (F13A1) region and two SNPs, rs630431 and rs560892, in the proprotein convertase subtilisin kexin 9 (PCSK9) region, with an estimated false discovery rate

Background: The Women's Health Initiative dietary modification (DM) trial provided suggestive evidence of a benefit of a low-fat dietary pattern on breast cancer risk, with stronger evidence among women whose baseline diet was high in fat. Single nucleotide polymorphisms (SNP) in the FGFR2 gene relate strongly to breast cancer risk and could influence intervention effects. Methods: All 48,835 trial participants were postmenopausal and ages 50 to 79 years at enrollment (1993-1998). We interrogated eight SNPs in intron 2 of the FGFR2 gene for 1,676 women who developed breast cancer during trial follow-up (1993-2005). Case-only analyses were used to estimate odds ratios for the DM intervention in relation to SNP genotype. Results: Odds ratios for the DM intervention did not vary significantly with the genotype for any of the eight FGFR2 SNPs (P ≥ 0.18). However, odds ratios varied (P < 0.05) with the genotype of six of these SNPs, among women having baseline percent of energy from fat in the upper quartile (≥36.8%). This variation is most evident for SNP rs3750817, with odds ratios for the DM intervention at 0, 1, and 2 minor SNP alleles of 1.06 [95% confidence intervals (95% CI), 0.80-1.41], 0.53 (95% CI, 0.38-0.74), and 0.62 (95% CI, 0.33-1.15). The nominal significance level for this interaction is P = 0.005, and P = 0.03 following multiple testing adjustment, with most evidence deriving from hormone receptor–positive tumors. Conclusion: Invasive breast cancer odds ratios for a low-fat dietary pattern, among women whose usual diets are high in fat, seem to vary with SNP rs3750817 in the FGFR2 gene. Cancer Epidemiol Biomarkers Prev; 19(1); 74–9

Background: Circulating levels of sex hormone-binding globulin (SHBG) are inversely associated with breast cancer risk in postmenopausal women. Three polymorphisms within the SHBG gene have been reported to affect SHBG levels, but there has been no systematic attempt to identify other such variants. Methods: We looked for associations between SHBG levels in 1,134 healthy, postmenopausal women and 11 tagging single nucleotide polymorphisms (SNP) in or around the SHBG gene. Associations between SHBG SNPs and breast cancer were tested in up to 6,622 postmenopausal breast cancer cases and 6,784 controls. Results: Ten SNPs within or close to the SHBG gene were significantly associated with SHBG levels as was the (TAAAA)n polymorphism. The best-fitting combination of rs6259, rs858521, and rs727428 and body mass index, waist, hip, age, and smoking status accounted for 24% of the variance in SHBG levels (natural logarithm transformed). Haplotype analysis suggested that rs858518, rs727428, or a variant in linkage disequilibrium with them acts to decrease SHBG levels but that this effect is neutralized by rs6259 (D356N). rs1799941 increases SHBG levels, but the previously reported association with (TAAAA)n repeat length appears to be a consequence of linkage disequilibrium with these SNPs. One further SHBG SNP was significantly associated with breast cancer (rs6257, per-allele odds ratio, 0.88; 95% confidence interval, 0.82-0.95; P = 0.002). Conclusion: At least 3 SNPs showed associations with SHBG levels that were highly significant but relatively small in magnitude. rs6257 is a potential breast cancer susceptibility variant, but relationships between the genetic determinants of SHBG levels and breast cancer are complex. (Cancer Epidemiol Biomarkers Prev 2008;17(12):3490–8)

The clinical overlap between monogenic Familial Hemiplegic Migraine (FHM) and common migraine subtypes, and the fact that all three FHM genes are involved in the transport of ions, suggest that ion transport genes may underlie susceptibility to common forms of migraine. To test this leading hypothesis, we examined common variation in 155 ion transport genes using 5257 single nucleotide polymorphisms (SNPs) in a Finnish sample of 841 unrelated migraine with aura cases and 884 unrelated non-migraine controls. The top signals were then tested for replication in four independent migraine case-control samples from the Netherlands, Germany and Australia, totalling 2835 unrelated migraine cases and 2740 unrelated controls. SNPs within 12 genes (KCNB2, KCNQ3, CLIC5, ATP2C2, CACNA1E, CACNB2, KCNE2, KCNK12, KCNK2, KCNS3, SCN5A and SCN9A) with promising nominal association (0.00041 < P < 0.005) in the Finnish sample were selected for replication. Although no variant remained significant after adjusting for multiple testing nor produced consistent evidence for association across all cohorts, a significant epistatic interaction between KCNB2 SNP rs1431656 (chromosome 8q13.3) and CACNB2 SNP rs7076100 (chromosome 10p12.33) (pointwise P = 0.00002; global P = 0.02) was observed in the Finnish case-control sample. We conclude that common variants of moderate effect size in ion transport genes do not play a major role in susceptibility to common migraine within these European populations, although there is some evidence for epistatic interaction between potassium and calcium channel genes, KCNB2 and CACNB2. Multiple rare variants or trans-regulatory elements of these genes are not ruled out.

In a genome-wide association study to identify loci associated with colorectal cancer (CRC) risk, we genotyped 555,510 SNPs in 1,012 early-onset Scottish CRC cases and 1,012 controls (phase 1). In phase 2, we genotyped the 15,008 highest-ranked SNPs in 2,057 Scottish cases and 2,111 controls. We then genotyped the five highest-ranked SNPs from the joint phase 1 and 2 analysis in 14,500 cases and 13,294 controls from seven populations, and identified a previously unreported association, rs3802842 on 11q23 (OR = 1.1; P = 5.8 x 10(-10)), showing population differences in risk. We also replicated and fine-mapped associations at 8q24 (rs7014346; OR = 1.19; P = 8.6 x 10(-26)) and 18q21 (rs4939827; OR = 1.2; P = 7.8 x 10(-28)). Risk was greater for rectal than for colon cancer for rs3802842 (P < 0.008) and rs4939827 (P < 0.009). Carrying all six possible risk alleles yielded OR = 2.6 (95% CI = 1.75-3.89) for CRC. These findings extend our understanding of the role of common genetic variation in CRC etiology.

Admixture mapping requires a genomewide panel of relatively evenly spaced markers that can distinguish the ancestral origins of chromosomal segments in admixed individuals. Through use of the results of the International HapMap Project and specific selection criteria, the current study has examined the ability of selected single-nucleotide polymorphisms (SNPs) to extract continental ancestry information in African American subjects and to explore parameters for admixture mapping. Genotyping of two linguistically diverse West African populations (Bini and Kanuri Nigerians, who are Niger-Congo [Bantu] and Nilo-Saharan speakers, respectively), European Americans, and African Americans validated a genomewide set of >4,000 SNP ancestry-informative markers with mean and median FST values >0.59 and mean and median Fisher’s information content >2.5. This set of SNPs extracted a larger amount of ancestry information in African Americans than previously reported SNP panels and provides nearly uniform coverage of the genome. Moreover, in the current study, simulations show that this more informative panel improves power for admixture mapping in African Americans when ethnicity risk ratios are modest. This is particularly important in the application of admixture mapping in complex genetic diseases for which only modest ethnicity risk ratios of relevant susceptibility genes are expected.

We performed a two-tiered, whole-genome association study of Parkinson disease (PD). For tier 1, we individually genotyped 198,345 uniformly spaced and informative single-nucleotide polymorphisms (SNPs) in 443 sibling pairs discordant for PD. For tier 2a, we individually genotyped 1,793 PD-associated SNPs (P