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Percentage of somatic variants based on 6 mutation types in Asian lung cancers.

Clinical and tissue information on 30 lung cancer patients (S1); Recurrent somatic variants based on presence of the same variant in the COSMIC database or presence of the same variant within the dataset (S2); Variants of the category 'three or more different variants with predicted functional impact within a gene' (S3); Somatic structural variations (S4); Summary of the sequencing statistics by Complete Genomics for 30 tumor/normal paired samples (S5); Validation of somatic variants by Ion Torrent or Sanger sequencing (S6); Validation of EGFR mutations by Sanger sequencing (S7).

Asian nonsmoking populations have a higher incidence of lung cancer compared with their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories of either all the never-smokers or all the smokers or ex-smokers. In addition, nearly one third of the ex-smokers and smokers classified with the never-smoker–like cluster. The somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 to be the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among the 16 never-smokers, 69% had an EGFR mutation compared with 29% of 14 smokers/ex-smokers. Asian never-smokers had lung cancer signatures distinct from the smoker signature and their mutation profiles were similar to European never-smokers. The profiles of Asian and European smokers are also similar. Taken together, these results suggested that the same mutational mechanisms underlie the etiology for both ethnic groups. Thus, the high incidence of lung cancer in Asian never-smokers seems unlikely to be due to second-hand smoke or other carcinogens that cause oxidative DNA damage, implying that routine EGFR testing is warranted in the Asian population regardless of smoking status. Cancer Res; 74(21); 6071–81. ©2014 AACR.

Legend for Supplementary Figures S1-S2.

Asian nonsmoking populations have a higher incidence of lung cancer compared with their European counterparts. There is a long-standing hypothesis that the increase of lung cancer in Asian never-smokers is due to environmental factors such as second-hand smoke. We analyzed whole-genome sequencing of 30 Asian lung cancers. Unsupervised clustering of mutational signatures separated the patients into two categories of either all the never-smokers or all the smokers or ex-smokers. In addition, nearly one third of the ex-smokers and smokers classified with the never-smoker–like cluster. The somatic variant profiles of Asian lung cancers were similar to that of European origin with G.C>T.A being predominant in smokers. We found EGFR and TP53 to be the most frequently mutated genes with mutations in 50% and 27% of individuals, respectively. Among the 16 never-smokers, 69% had an EGFR mutation compared with 29% of 14 smokers/ex-smokers. Asian never-smokers had lung cancer signatures distinct from the smoker signature and their mutation profiles were similar to European never-smokers. The profiles of Asian and European smokers are also similar. Taken together, these results suggested that the same mutational mechanisms underlie the etiology for both ethnic groups. Thus, the high incidence of lung cancer in Asian never-smokers seems unlikely to be due to second-hand smoke or other carcinogens that cause oxidative DNA damage, implying that routine EGFR testing is warranted in the Asian population regardless of smoking status. Cancer Res; 74(21); 6071–81. ©2014 AACR.

A national workgroup convened by the Centers for Disease Control and Prevention identified principles and made recommendations for standardizing the description of sequence data contained within the variant file generated during the course of clinical next-generation sequence analysis for diagnosing human heritable conditions. The specifications for variant files were initially developed to be flexible with regard to content representation to support a variety of research applications. This flexibility permits variation with regard to how sequence findings are described and this depends, in part, on the conventions used. For clinical laboratory testing, this poses a problem because these differences can compromise the capability to compare sequence findings among laboratories to confirm results and to query databases to identify clinically relevant variants. To provide for a more consistent representation of sequence findings described within variant files, the workgroup made several recommendations that considered alignment to a common reference sequence, variant caller settings, use of genomic coordinates, and gene and variant naming conventions. These recommendations were considered with regard to the existing variant file specifications presently used in the clinical setting. Adoption of these recommendations is anticipated to reduce the potential for ambiguity in describing sequence findings and facilitate the sharing of genomic data among clinical laboratories and other entities.

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

Toward $1000 Genomes The ability to generate human genome sequence data that is complete, accurate, and inexpensive is a necessary prerequisite to perform genome-wide disease association studies. Drmanac et al. (p. 78 , published online 5 November) present a technique advancing toward this goal. The method uses Type IIS endonucleases to incorporate short oligonucleotides within a set of randomly sheared circularized DNA. DNA polymerase then generates concatenated copies of the circular oligonucleotides leading to formation of compact but very long oligonucleotides which are then sequenced by ligation. The relatively low cost of this technology, which shows a low error rate, advances sequencing closer to the goal of the $1000 genome.

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)

Background: Markers for individual genotyping can be selected using quantitative genotyping of pooled DNA. This strategy saves time and money. Methods: To determine the efficacy of this approach, we investigated the bivariate distribution of association test statistics from pooled and individual genotypes. We used a sample of approximately 1,000 samples with individual and pooled genotyping on 40,000 SNPs. Results and Conclusions: We found that the distribution of the joint test statistics can be modelled as a mixture of two bivariate normal distributions. One distribution has a correlation of zero, and is probably due to SNPs whose pooled genotyping was unsuccessful. The other distribution has a correlation of approximately 0.65 in our data. This latter distribution is probably accounted for by SNPs whose pooled genotyping accurately predicts the underlying allele frequency. Approximately 87% of the data belongs to this distribution. We also derived a method to investigate the effect of both the correlation and selection cut-off on the relative power of pooling studies. We demonstrate that pooled genotyping has good power to detect SNPs that are truly associated with disease-causing variants for SNPs showing good correlation between pooled and individual genotyping. Therefore, this approach is a cost effective tool for association studies.

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.

Human cancer is caused by the accumulation of mutations in oncogenes and tumor suppressor genes. To catalog the genetic changes that occur during tumorigenesis, we isolated DNA from 11 breast and 11 colorectal tumors and determined the sequences of the genes in the Reference Sequence database in these samples. Based on analysis of exons representing 20,857 transcripts from 18,191 genes, we conclude that the genomic landscapes of breast and colorectal cancers are composed of a handful of commonly mutated gene “mountains” and a much larger number of gene “hills” that are mutated at low frequency. We describe statistical and bioinformatic tools that may help identify mutations with a role in tumorigenesis. These results have implications for understanding the nature and heterogeneity of human cancers and for using personal genomics for tumor diagnosis and therapy.

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.

Inherited genetic variation has a critical but as yet largely uncharacterized role in human disease. Here we report a public database of common variation in the human genome: more than one million single nucleotide polymorphisms (SNPs) for which accurate and complete genotypes have been obtained in 269 DNA samples from four populations, including ten 500-kilobase regions in which essentially all information about common DNA variation has been extracted. These data document the generality of recombination hotspots, a block-like structure of linkage disequilibrium and low haplotype diversity, leading to substantial correlations of SNPs with many of their neighbours. We show how the HapMap resource can guide the design and analysis of genetic association studies, shed light on structural variation and recombination, and identify loci that may have been subject to natural selection during human evolution. © 2005 Nature Publishing Group., link_to_OA_fulltext

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.

We have identified three novel, rarely expressed human genes that encode new members of the lipid transfer/lipopolysaccharide binding protein (LT/LBP) gene family based on sequence homology. BPI and other members of the LT/LBP family are structurally related proteins capable of binding phospholipids and lipopolysaccharides. Real-time PCR studies indicate that BPIL1 and BPIL3 are highly expressed in hypertrophic tonsils. In situ hybridization analysis of BPIL2 shows prominent expression in skin specimens from psoriasis patients. BPIL1 and BPIL3 map to Chromosome 20q11; thus, these novel genes form a cluster with BPI and two other members of the LT/LBP gene family on the long arm of human Chr 20. BPIL2 maps to Chr 22q13. The exon/intron organization of all three genes is highly conserved with that of BPI, suggesting evolution from a common ancestor.

Defects in the lipoprotein lipase (LPL) gene are associated with dyslipidemia in the general population. Several rare mutations in the gene, as well as two common coding region polymorphisms, D9N and N291S, exhibit deleterious effects on circulating lipid levels. Using a linkage-based approach, we have identified a large Utah kindred segregating the D9N variant in the LPL gene. The kindred was ascertained for premature coronary heart disease and was expanded based on familial dyslipidemia. A genomic scan identified a region of linkage including LPL, and mutation screening identified the segregating variant. In the kindred, the variant shows high penetrance for a hypoalphalipoproteinemia phenotype, but is also associated with hypertriglyceridemia and elevated insulin levels. The strength of linkage was dependent on the combination of phenotype definition and model parameters, favoring the use of a MOD score approach. Most other studies of LPL have proceeded by mutation screening of randomly chosen individuals or selected affected probands; this is the first example identifying a segregating LPL mutation using direct linkage.

Coronary heart disease (CHD) accounts for half of the 1 million deaths annually ascribed to cardiovascular disease and for almost all of the 1.5 million acute myocardial infarctions. Within families affected by early and apparently heritable CHD, dyslipidemias have a much higher prevalence than in the general population; 20%-30% of early familial CHD has been ascribed to primary hypoalphalipoproteinemia (low HDL-C). This study assesses the evidence for linkage of low HDL-C to chromosomal region 11q23 in 105 large Utah pedigrees ascertained with closely related clusters of early CHD and expanded on the basis of dyslipidemia. Linkage analysis was performed by use of 22 STRP markers in a 55-cM region of chromosome 11. Two-point analysis based on a general, dominant-phenotype model yielded LODs of 2.9 for full pedigrees and 3.5 for 167 four-generation split pedigrees. To define a localization region, model optimization was performed using the heterogeneity, multipoint LOD score (mpHLOD). This linkage defines a region on 11q23.3 that is approximately 10 cM distal to-and apparently distinct from-the ApoAI/CIII/AIV gene cluster and thus represents a putative novel localization for the low HDL-C phenotype.

The ZNF202 gene resides in a chromosomal region linked genetically to low high density lipoprotein cholesterol in Utah families. Here we show that the ZNF202 gene product is a transcriptional repressor that binds to elements found predominantly in genes that participate in lipid metabolism. Among its targets are structural components of lipoprotein particles (apolipoproteins AIV, CIII, and E), enzymes involved in lipid processing (lipoprotein lipase, lecithin cholesteryl ester transferase), and several genes involved in processes related to energy metabolism and vascular disease. Based on the linkage and apparent transcriptional function of ZNF202, we propose that ZNF202 is a candidate susceptibility gene for human dyslipidemia.

Abstract —Clinical familial hypercholesterolemia has been shown to result from mutations in 2 genes, the low density lipoprotein (LDL) receptor on chromosome 19 and apolipoprotein B on chromosome 2. However, we have recently described a Utah pedigree in which linkage to both genes was clearly excluded. A multipoint linkage analysis of 583 markers genotyped on 31 (18 affected) members of this pedigree was undertaken to localize a genetic region that may harbor a third gene that could result in clinical familial hypercholesterolemia. A multipoint log of the odds score of 6.8 was obtained for markers on 1p32. Haplotype carriers and affected status are completely concordant (18/18 persons). The phenotype is also expressed in young children (ages 4 and 9). Specific recombinant individuals in the pedigree restrict the region of linkage to an ≈17 cM interval between polymorphic markers D1S2130 and D1S1596. This region appears to overlap the region found linked to severe hypercholesterolemia in French and Spanish families. The identification of the gene in this region may provide important pathophysiological insights into new mechanisms that may lead to highly elevated LDL cholesterol and other associated dyslipidemic phenotypes.

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)).

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

Hepatitis B virus (HBV) infection is a leading risk factor for hepatocellular carcinoma (HCC). HBV integration into the host genome has been reported, but its scale, impact and contribution to HCC development is not clear. Here, we sequenced the tumor and nontumor genomes (>80× coverage) and transcriptomes of four HCC patients and identified 255 HBV integration sites. Increased sequencing to 240× coverage revealed a proportionally higher number of integration sites. Clonal expansion of HBV-integrated hepatocytes was found specifically in tumor samples. We observe a diverse collection of genomic perturbations near viral integration sites, including direct gene disruption, viral promoter-driven human transcription, viral-human transcript fusion, and DNA copy number alteration. Thus, we report the most comprehensive characterization of HBV integration in hepatocellular carcinoma patients. Such widespread random viral integration will likely increase carcinogenic opportunities in HBV-infected individuals.

Unchained base reads on self-assembling DNA nanoarrays have recently emerged as a promising approach to low-cost, high-quality resequencing of human genomes. Because of unique characteristics of these mated pair reads, existing computational methods for resequencing assembly, such as those based on map-consensus calling, are not adequate for accurate variant calling. We describe novel computational methods developed for accurate calling of SNPs and short substitutions and indels (100 bp); the same methods apply to evaluation of hypothesized larger, structural variations. We use an optimization process that iteratively adjusts the genome sequence to maximize its a posteriori probability given the observed reads. For each candidate sequence, this probability is computed using Bayesian statistics with a simple read generation model and simplifying assumptions that make the problem computationally tractable. The optimization process iteratively applies one-base substitutions, insertions, and deletions until convergence is achieved to an optimum diploid sequence. A local de novo assembly procedure that generalizes approaches based on De Bruijn graphs is used to seed the optimization process in order to reduce the chance of converging to local optima. Finally, a correlation-based filter is applied to reduce the false positive rate caused by the presence of repetitive regions in the reference genome.

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

Rice, the primary source of dietary calories for half of humanity, is the first crop plant for which a high-quality reference genome sequence from a single variety was produced. We used resequencing microarrays to interrogate 100 Mb of the unique fraction of the reference genome for 20 diverse varieties and landraces that capture the impressive genotypic and phenotypic diversity of domesticated rice. Here, we report the distribution of 160,000 nonredundant SNPs. Introgression patterns of shared SNPs revealed the breeding history and relationships among the 20 varieties; some introgressed regions are associated with agronomic traits that mark major milestones in rice improvement. These comprehensive SNP data provide a foundation for deep exploration of rice diversity and gene–trait relationships and their use for future rice improvement.

Two recent genome-wide association studies have described associations of SNP variants in PNPLA3 with nonalcoholic fatty liver and plasma liver enzyme levels in population based cohorts. We investigated the contributions of these variants to clinical outcomes in Mestizo subjects with a history of excessive alcohol consumption. We show that non-synonymous variant rs738409[G] (I148M) in PNPLA3 is strongly associated with alcoholic liver disease and progression to alcoholic cirrhosis (unadjusted OR = 2.25, P = 1.7x10^-10^; ancestry-adjusted OR = 1.79, P = 1.9x10^-5^).

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.

The Genetic Association Information Network (GAIN) is a public-private partnership established to investigate the genetic basis of common diseases through a series of collaborative genome-wide association studies. GAIN has used new approaches for project selection, data deposition and distribution, collaborative analysis, publication and protection from premature intellectual property claims. These demonstrate a new commitment to shared scientific knowledge that should facilitate rapid advances in understanding the genetics of complex diseases.

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

Individual differences in DNA sequence are the genetic basis of human variability. We have characterized whole-genome patterns of common human DNA variation by genotyping 1,586,383 single-nucleotide polymorphisms (SNPs) in 71 Americans of European, African, and Asian ancestry. Our results indicate that these SNPs capture most common genetic variation as a result of linkage disequilibrium, the correlation among common SNP alleles. We observe a strong correlation between extended regions of linkage disequilibrium and functional genomic elements. Our data provide a tool for exploring many questions that remain regarding the causal role of common human DNA variation in complex human traits and for investigating the nature of genetic variation within and between human populations.

Recombination rates seem to vary extensively along the human genome. Pedigree analysis suggests that rates vary by an order of magnitude when measured at the megabase scale 1 , and at a finer scale, sperm typing studies point to the existence of recombination hotspots 2 . These are short regions (1–2 kb) in which recombination rates are 10–1,000 times higher than the background rate. Less is known about how recombination rates change over time. Here we determined to what degree recombination rates are conserved among closely related species by estimating recombination rates from 14 Mb of linkage disequilibrium data in central chimpanzee and human populations. The results suggest that recombination hotspots are not conserved between the two species and that recombination rates in larger (50 kb) genomic regions are only weakly conserved. Therefore, the recombination landscape has changed markedly between the two species.

Epidemiological studies have shown an association of decreased serum bilirubin levels with coronary artery disease. Two segregation analyses in large pedigrees have suggested a major gene responsible for high bilirubin levels occurring in about 12% of the population. Based on a recessive model from a previous segregation analysis, we performed a genome scan using 587 markers genotyped in 862 individuals from 48 Utah pedigrees to detect loci linked to high bilirubin levels. As a complementary approach, non-parametric linkage (NPL) analysis was performed. These two methods identified four regions showing evidence for linkage. The first region is on chromosome 2q34-37 with multipoint LOD and NPL scores of 3.01 and 3.22, respectively, for marker D2S1363. This region contains a previously described gene, uridine diphosphate glycosyltransferase 1, which has been associated with high bilirubin levels. A polymorphism in the promoter of this gene was recently shown to be responsible for Gilbert syndrome which is associated with mild hyperbilirubinemia. The other regions were found on chromosomes 9q21, 10q25-26, and 18q12 with maximum NPL scores of 2.39, 1.55, and 2.79, respectively. Furthermore, we investigated in these pedigrees the association between bilirubin levels and coronary artery disease. One-hundred and sixty-one male and 41 female subjects had already suffered a coronary artery disease event. Male patients showed significantly lower bilirubin concentrations than age-matched controls. This association, however, was not observed in females. These results provide evidence that loci influencing bilirubin variation exist on chromosomes 2q34-37, 9q21, 10q25-26, and 18q12 and confirms the association of low bilirubin levels with coronary artery disease in males.

The SCAN domain is described as a highly conserved, leucine-rich motif of approximately 60 amino acids found at the amino-terminal end of zinc finger transcription factors. Although no specific biological function has been attributed to the SCAN domain, its predicted amphipathic secondary structure led to the suggestion that this domain may mediate protein-protein associations. A yeast two-hybrid screen identified members of two SCAN domain protein families that interact with the SCAN domain of the zinc finger protein ZNF202. The interacting ZNF191 protein represents the family of SCAN domain-containing zinc finger proteins, whereas the novel SDP1 protein establishes a new family of genes that encode an isolated SCAN domain. Isolated SCAN domain proteins may form asymmetric homodimers in solution. Biochemical binding studies confirmed the associations of ZNF191 and SDP1 with ZNF202 and established the SCAN domain as a selective hetero- and homotypic oligomerization domain. SCAN mediated protein associations might therefore represent a new regulatory mechanism of transcriptional activity.

Loss of heterozygosity data from familial tumors suggest that BRCA1, a gene that confers susceptibility to ovarian and early-onset breast cancer, encodes a tumor suppressor. The BRCA1 region is also subject to allelic loss in sporadic breast and ovarian cancers, an indication that BRCA1 mutations may occur somatically in these tumors. The BRCA1 coding region was examined for mutations in primary breast and ovarian tumors that show allele loss at the BRCA1 locus. Mutations were detected in 3 of 32 breast and 1 of 12 ovarian carcinomas; all four mutations were germline alterations and occurred in early-onset cancers. These results suggest that mutation of BRCA1 may not be critical in the development of the majority of breast and ovarian cancers that arise in the absence of a mutant germline allele.

Complete Genomics has sequenced the genomes of over 100 tumor-normal sample pairs from a variety of cancers (e.g. Lee, et al., Nature 465: 473-477, 2010) using a unique high throughput sequencing platform (Drmanac, et al., Science 327:78-81, 2010). We have assembled a tool set to investigate somatic mutations in these samples, including small variations (SNVs, deletions, insertions and substitutions), as well as larger structural variations, copy number variations and regions of LOH (Loss of Heterozygosity). Included in this sample set are 12 cancer cell lines and matched normal cell lines obtained from the American Type Tissue Culture collection (ATCC), comprising 10 breast cancers and 2 lung cancers. We have developed and characterized somatic variation scoring methods for each variant class that can be tuned for particular applications and sample types. Comparative analyses with previously published data show high specificity and sensitivity of somatic variation detection. We will discuss the application of these methods for somatic variation analysis in larger cancer genome studies. Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 102nd Annual Meeting of the American Association for Cancer Research; 2011 Apr 2-6; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2011;71(8 Suppl):Abstract nr 4821. doi:10.1158/1538-7445.AM2011-4821

Background Genome-wide association studies have identified several genomic regions that are associated with breast cancer risk, but these provide an explanation for only a small fraction of familial breast cancer aggregation. Genotype by environment interactions may contribute further to such explanation, and may help to refine the genomic regions of interest. Methods We examined genotypes for 4,988 SNPs, selected from recent genome-wide studies, and four randomized hormonal and dietary interventions among 2,166 women who developed invasive breast cancer during the intervention phase of the Women's Health Initiative (WHI) clinical trial (1993 to 2005), and one-to-one matched controls. These SNPs derive from 3,224 genomic regions having pairwise squared correlation (r2) between adjacent regions less than 0.2. Breast cancer and SNP associations were identified using a test statistic that combined evidence of overall association with evidence for SNPs by intervention interaction. Results The combined 'main effect' and interaction test led to a focus on two genomic regions, the fibroblast growth factor receptor two (FGFR2) and the mitochondrial ribosomal protein S30 (MRPS30) regions. The ranking of SNPs by significance level, based on this combined test, was rather different from that based on the main effect alone, and drew attention to the vicinities of rs3750817 in FGFR2 and rs7705343 in MRPS30. Specifically, rs7705343 was included with several FGFR2 SNPs in a group of SNPs having an estimated false discovery rate < 0.05. In further analyses, there were suggestions (nominal P < 0.05) that hormonal and dietary intervention hazard ratios varied with the number of minor alleles of rs7705343. Conclusions Genotype by environment interaction information may help to define genomic regions relevant to disease risk. Combined main effect and intervention interaction analyses raise novel hypotheses concerning the MRPS30 genomic region and the effects of hormonal and dietary exposures on postmenopausal breast cancer risk.

The calphotin protein, encoded by the calphotin (cap) gene, is expressed in the soma and axons of all Drosophila photoreceptor cells. It is expressed early in photo-receptor cell development, at the time when cell-type decisions are being made. Expression of calphotin is not altered by the glass mutation, which blocks photoreceptor cell development. The calphotin protein binds calcium and contains a long C-terminal leucine zipper. Potential implications of these properties are discussed.

Nat. Genet. 37, 429–434 (2005). The dbSNP accession numbers for the chimpanzee data are ss35040256 through ss35071793.