COSMOS: a platform for real-time morphology-based, label-free cell sorting using deep learning

Cells are the singular building blocks of life, and a comprehensive understanding of morphology, among other properties, is crucial to the assessment of underlying heterogeneity. We developed Computational Sorting and Mapping of Single Cells (COSMOS), a platform based on Artificial Intelligence (AI) and microfluidics to characterize and sort single cells based on real-time deep learning interpretation of high-resolution brightfield images. Supervised deep learning models were applied to characterize and sort cell lines and dissociated primary tissue based on high-dimensional embedding vectors of morphology without the need for biomarker labels and stains/dyes. We demonstrate COSMOS capabilities with multiple human cell lines and tissue samples. These early results suggest that our neural networks embedding space can capture and recapitulate deep visual characteristics and can be used to efficiently purify unlabeled viable cells with desired morphological traits. Our approach resolves a technical gap in the ability to perform real-time deep learning assessment and sorting of cells based on high-resolution brightfield images.

Abstract 5926: High dimensional morphology analysis reveals new insights in melanoma cell heterogeneity

Melanomas are the deadliest skin cancers, in part due to cellular plasticity and heterogeneity within the tumors. These characteristics have made a deeper understanding of melanomas challenging. Classically, melanoma cells are characterized with a limited set of protein biomarkers. Gene expression signatures and mutational analysis (e.g., BRAF and NRAS genotyping) can provide a more detailed view of heterogeneity but may not translate to readily available biomarkers for functional studies. The Deepcell platform enables multi-dimensional morphology analysis and enrichment of unlabeled single cells using artificial intelligence (AI), advanced imaging, and microfluidics, enabling high resolution profiling of population heterogeneity. Label-free multi-dimensional morphology analysis may have higher resolution than a limited set of protein biomarkers, minimizes perturbation to the transcriptome, and reduces cell handling steps. We used patient-derived cell lines and dissociated biopsy samples to train a Deepcell AI model to identify and sort for melanoma cells based on morphology alone. The model was tested on metastatic melanoma biopsies, with identification and enrichment of melanoma cells verified by various downstream assays, including scRNASeq. In addition to melanoma populations, the AI model classified various cells of the microenvironment, such as stromal cells and immune subtypes, based on morphology only. To further characterize tumor heterogeneity, we imaged >25 patient-derived melanoma cell lines representing melanocytic, mesenchymal, and intermediate phenotypic states on the Deepcell platform. Morphology analysis of these images revealed distinct clusters of cells for each phenotype, indicating that there are morphological differences associated with each state. We developed a random forest (RF) classifier to identify the top differential morphological features between the different cell lines, thereby providing a label-free means of phenotyping melanoma samples. The morphology analysis of the cell lines uncovered significant variability in pigmentation; an RF classifier distinguished between pigmented vs non-pigmented cells with >90% accuracy. Pigmentation is a hallmark of melanoma cells, and it has been associated with the melanocytic phenotype and differential drug response in vitro. However, there is not currently a robust method to profile and study pigmentation in live cells. We further investigated this observation by correlating morphological profiles, molecular, and functional information with the level of cell pigmentation. The Deepcell platform presents a new method for sorting and characterizing cellular heterogeneity using morphology, including pigmentation status. As such, multi-dimensional morphology analysis will bolster the understanding of complex melanoma states and tumor microenvironment, particularly in patient derived biopsies.

Citation Format: Evelyn Lattmann, Aizhan Tastanova, Andreja Jovic, Kiran Saini, Tiffine Pham, Christian Corona, Jeanette Mei, Michael Phelan, Stephane C. Boutet, Ryan Carelli, Kevin B. Jacobs, Julie Kim, Manisha Ray, Chassidy Johnson, Nianzhen Li, Mahyar Salek, Maddison Masaeli, Mitchell P. Levesque. High dimensional morphology analysis reveals new insights in melanoma cell heterogeneity [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 5926.

Evaluation of a novel screening method for fetal aneuploidy using cell-free DNA in maternal plasma

Objective

To evaluate the test performance of a novel sequencing technology using molecular inversion probes applied to cell-free DNA screening for fetal aneuploidy.

Methods

Two cohorts were included in the evaluation; a risk-based cohort of women receiving diagnostic testing in the first and second trimesters was combined with stored samples from pregnancies with fetuses known to be aneuploid or euploid. All samples were blinded to testing personnel before being analyzed, and validation occurred after the study closed and results were merged.

Results

Using the new sequencing technology, 1414 samples were analyzed. The findings showed sensitivities and specificities for the common trisomies and the sex chromosome aneuploidies at >99% (Trisomy 21 sensitivity 99.2 CI 95.6–99.2; specificity 99.9 CI 99.6–99.9). Positive predictive values among the trisomies varied from 85.2% (Trisomy 18) to 99.0% (Trisomy 21), reflecting their prevalence rates in the study. Comparisons with a meta-analysis of recent cell-free DNA screening publications demonstrated equivalent test performance.

Conclusion

This new technology demonstrates equivalent test performance compared with alternative sequencing approaches, and demonstrates that each chromosome can be successfully interrogated using a single probe.

hgvs: A Python package for manipulating sequence variants using HGVS nomenclature: 2018 Update

The Human Genome Variation Society (HGVS) nomenclature guidelines encourage the accurate and standard description of DNA, RNA, and protein sequence variants in public variant databases and the scientific literature. Inconsistent application of the HGVS guidelines can lead to misinterpretation of variants in clinical settings. Reliable software tools are essential to ensure consistent application of the HGVS guidelines when reporting and interpreting variants. We present the hgvs Python package, a comprehensive tool for manipulating sequence variants according to the HGVS nomenclature guidelines. Distinguishing features of the hgvs package include: (1) parsing, formatting, validating, and normalizing variants on genome, transcript, and protein sequences; (2) projecting variants between aligned sequences, including those with gapped alignments; (3) flexible installation using remote or local data (fully local installations eliminate network dependencies); (4) extensive automated tests; and (5) open source development by a community from eight organizations worldwide. This report summarizes recent and significant updates to the hgvs package since its original release in 2014, and presents results of extensive validation using clinical relevant variants from ClinVar and HGMD.

Association between GWAS-identified lung adenocarcinoma susceptibility loci and EGFR mutations in never-smoking Asian women, and comparison with findings from Western populations

To evaluate associations by EGFR mutation status for lung adenocarcinoma risk among never-smoking Asian women, we conducted a meta-analysis of 11 loci previously identified in genome-wide association studies (GWAS). Genotyping in an additional 10,780 never-smoking cases and 10,938 never-smoking controls from Asia confirmed associations with eight known single nucleotide polymorphisms (SNPs). Two new signals were observed at genome-wide significance (P < 5 × 10-8), namely, rs7216064 (17q24.3, BPTF), for overall lung adenocarcinoma risk, and rs3817963 (6p21.3, BTNL2) which is specific to cases with EGFR mutations. In further sub-analyses by EGFR status, rs9387478 (ROS1/DCBLD1) and rs2179920 (HLA-DPB1) showed stronger estimated associations in EGFR-positive compared to EGFR-negative cases. Comparison of the overall associations with published results in Western populations revealed that the majority of these findings were distinct, underscoring the importance of distinct contributing factors for smoking and non-smoking lung cancer. Our results extend the catalogue of regions associated with lung adenocarcinoma in non-smoking Asian women and highlight the importance of how the germline could inform risk for specific tumour mutation patterns, which could have important translational implications.

Genomewide meta-analysis identifies loci associated with IGF-I and IGFBP-3 levels with impact on age-related traits

The growth hormone/insulin‐like growth factor (IGF) axis can be manipulated in animal models to promote longevity, and IGF‐related proteins including IGF‐I and IGF‐binding protein‐3 (IGFBP‐3) have also been implicated in risk of human diseases including cardiovascular diseases, diabetes, and cancer. Through genomewide association study of up to 30 884 adults of European ancestry from 21 studies, we confirmed and extended the list of previously identified loci associated with circulating IGF‐I and IGFBP‐3 concentrations (IGF1, IGFBP3,GCKR,TNS3, GHSR, FOXO3, ASXL2, NUBP2/IGFALS, SORCS2, and CELSR2). Significant sex interactions, which were characterized by different genotype–phenotype associations between men and women, were found only for associations of IGFBP‐3 concentrations with SNPs at the loci IGFBP3 and SORCS2. Analyses of SNPs, gene expression, and protein levels suggested that interplay between IGFBP3 and genes within the NUBP2 locus (IGFALS and HAGH) may affect circulating IGF‐I and IGFBP‐3 concentrations. The IGF‐I‐decreasing allele of SNP rs934073, which is an eQTL of ASXL2, was associated with lower adiposity and higher likelihood of survival beyond 90 years. The known longevity‐associated variant rs2153960 (FOXO3) was observed to be a genomewide significant SNP for IGF‐I concentrations. Bioinformatics analysis suggested enrichment of putative regulatory elements among these IGF‐I‐ and IGFBP‐3‐associated loci, particularly of rs646776 at CELSR2. In conclusion, this study identified several loci associated with circulating IGF‐I and IGFBP‐3 concentrations and provides clues to the potential role of the IGF axis in mediating effects of known (FOXO3) and novel (ASXL2) longevity‐associated loci.

Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

[This corrects the article DOI: 10.1371/journal.pgen.1005378.].

Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome

To investigate large structural clonal mosaicism of chromosome X, we analysed the SNP microarray intensity data of 38,303 women from cancer genome-wide association studies (20,878 cases and 17,425 controls) and detected 124 mosaic X events >2 Mb in 97 (0.25%) women. Here we show rates for X-chromosome mosaicism are four times higher than mean autosomal rates; X mosaic events more often include the entire chromosome and participants with X events more likely harbour autosomal mosaic events. X mosaicism frequency increases with age (0.11% in 50-year olds; 0.45% in 75-year olds), as reported for Y and autosomes. Methylation array analyses of 33 women with X mosaicism indicate events preferentially involve the inactive X chromosome. Our results provide further evidence that the sex chromosomes undergo mosaic events more frequently than autosomes, which could have implications for understanding the underlying mechanisms of mosaic events and their possible contribution to risk for chronic diseases.

It is unclear how often genetic mosaicism of chromosome X arises. Here, the authors examine women with cancer and cancer-free controls and show that X chromosome mosaicism occurs more frequently than on autosomes, especially on the inactive X chromosome, but is not linked to non-haematologic cancer risk

The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study

Genome-wide association studies (GWAS) have identified more than 100 genetic variants contributing to BMI, a measure of body size, or waist-to-hip ratio (adjusted for BMI, WHR_adjBMI), a measure of body shape. Body size and shape change as people grow older and these changes differ substantially between men and women. To systematically screen for age- and/or sex-specific effects of genetic variants on BMI and WHR_adjBMI, we performed meta-analyses of 114 studies (up to 320,485 individuals of European descent) with genome-wide chip and/or Metabochip data by the Genetic Investigation of Anthropometric Traits (GIANT) Consortium. Each study tested the association of up to ~2.8M SNPs with BMI and WHR_adjBMI in four strata (men ≤50y, men >50y, women ≤50y, women >50y) and summary statistics were combined in stratum-specific meta-analyses. We then screened for variants that showed age-specific effects (G x AGE), sex-specific effects (G x SEX) or age-specific effects that differed between men and women (G x AGE x SEX). For BMI, we identified 15 loci (11 previously established for main effects, four novel) that showed significant (FDR<5%) age-specific effects, of which 11 had larger effects in younger (<50y) than in older adults (≥50y). No sex-dependent effects were identified for BMI. For WHR_adjBMI, we identified 44 loci (27 previously established for main effects, 17 novel) with sex-specific effects, of which 28 showed larger effects in women than in men, five showed larger effects in men than in women, and 11 showed opposite effects between sexes. No age-dependent effects were identified for WHR_adjBMI. This is the first genome-wide interaction meta-analysis to report convincing evidence of age-dependent genetic effects on BMI. In addition, we confirm the sex-specificity of genetic effects on WHR_adjBMI. These results may provide further insights into the biology that underlies weight change with age or the sexually dimorphism of body shape.

Adult body size and body shape differ substantially between men and women and change over time. More than 100 genetic variants that influence body mass index (measure of body size) or waist-to-hip ratio (measure of body shape) have been identified. While there is evidence that some genetic loci affect body shape differently in men than in women, little is known about whether genetic effects differ in older compared to younger adults, and whether such changes differ between men and women. Therefore, we conducted a systematic genome-wide search, including 114 studies (>320,000 individuals), to specifically identify genetic loci with age- and or sex-dependent effects on body size and shape. We identified 15 loci of which the effect on BMI was different in older compared to younger adults, whereas we found no evidence for loci with different effects in men compared to women. The opposite was seen for body shape as we identified 44 loci of which the effect on waist-to-hip ratio differed between men and women, but no difference between younger and older adults were observed. Our observations may provide new insights into the biology that underlies weight change with age or the sexual dimorphism of body shape.

A Systematic Comparison of Traditional and Multigene Panel Testing for Hereditary Breast and Ovarian Cancer Genes in More Than 1000 Patients

Gene panels for hereditary breast and ovarian cancer risk assessment are gaining acceptance, even though the clinical utility of these panels is not yet fully defined. Technical questions remain, however, about the performance and clinical interpretation of gene panels in comparison with traditional tests. We tested 1105 individuals using a 29-gene next-generation sequencing panel and observed 100% analytical concordance with traditional and reference data on >750 comparable variants. These 750 variants included technically challenging classes of sequence and copy number variation that together represent a significant fraction (13.4%) of the pathogenic variants observed. For BRCA1 and BRCA2, we also compared variant interpretations in traditional reports to those produced using only non-proprietary resources and following criteria based on recent (2015) guidelines. We observed 99.8% net report concordance, albeit with a slightly higher variant of uncertain significance rate. In 4.5% of BRCA-negative cases, we uncovered pathogenic variants in other genes, which appear clinically relevant. Previously unseen variants requiring interpretation accumulated rapidly, even after 1000 individuals had been tested. We conclude that next-generation sequencing panel testing can provide results highly comparable to traditional testing and can uncover potentially actionable findings that may be otherwise missed. Challenges remain for the broad adoption of panel tests, some of which will be addressed by the accumulation of large public databases of annotated clinical variants.

Characterization of large structural genetic mosaicism in human autosomes

Analyses of genome-wide association study (GWAS) data have revealed that detectable genetic mosaicism involving large (>2 Mb) structural autosomal alterations occurs in a fraction of individuals. We present results for a set of 24,849 genotyped individuals (total GWAS set II [TGSII]) in whom 341 large autosomal abnormalities were observed in 168 (0.68%) individuals. Merging data from the new TGSII set with data from two prior reports (the Gene-Environment Association Studies and the total GWAS set I) generated a large dataset of 127,179 individuals; we then conducted a meta-analysis to investigate the patterns of detectable autosomal mosaicism (n = 1,315 events in 925 [0.73%] individuals). Restricting to events >2 Mb in size, we observed an increase in event frequency as event size decreased. The combined results underscore that the rate of detectable mosaicism increases with age (p value = 5.5 × 10(-31)) and is higher in men (p value = 0.002) but lower in participants of African ancestry (p value = 0.003). In a subset of 47 individuals from whom serial samples were collected up to 6 years apart, complex changes were noted over time and showed an overall increase in the proportion of mosaic cells as age increased. Our large combined sample allowed for a unique ability to characterize detectable genetic mosaicism involving large structural events and strengthens the emerging evidence of non-random erosion of the genome in the aging population.

Imputation and subset-based association analysis across different cancer types identifies multiple independent risk loci in the TERT-CLPTM1L region on chromosome 5p15.33

Genome-wide association studies (GWAS) have mapped risk alleles for at least 10 distinct cancers to a small region of 63 000 bp on chromosome 5p15.33. This region harbors the TERT and CLPTM1L genes; the former encodes the catalytic subunit of telomerase reverse transcriptase and the latter may play a role in apoptosis. To investigate further the genetic architecture of common susceptibility alleles in this region, we conducted an agnostic subset-based meta-analysis (association analysis based on subsets) across six distinct cancers in 34 248 cases and 45 036 controls. Based on sequential conditional analysis, we identified as many as six independent risk loci marked by common single-nucleotide polymorphisms: five in the TERT gene (Region 1: rs7726159, P = 2.10 × 10(-39); Region 3: rs2853677, P = 3.30 × 10(-36) and PConditional = 2.36 × 10(-8); Region 4: rs2736098, P = 3.87 × 10(-12) and PConditional = 5.19 × 10(-6), Region 5: rs13172201, P = 0.041 and PConditional = 2.04 × 10(-6); and Region 6: rs10069690, P = 7.49 × 10(-15) and PConditional = 5.35 × 10(-7)) and one in the neighboring CLPTM1L gene (Region 2: rs451360; P = 1.90 × 10(-18) and PConditional = 7.06 × 10(-16)). Between three and five cancers mapped to each independent locus with both risk-enhancing and protective effects. Allele-specific effects on DNA methylation were seen for a subset of risk loci, indicating that methylation and subsequent effects on gene expression may contribute to the biology of risk variants on 5p15.33. Our results provide strong support for extensive pleiotropy across this region of 5p15.33, to an extent not previously observed in other cancer susceptibility loci.

Defining the role of common variation in the genomic and biological architecture of adult human height

Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants.

Sex-stratified genome-wide association studies including 270,000 individuals show sexual dimorphism in genetic loci for anthropometric traits

Given the anthropometric differences between men and women and previous evidence of sex-difference in genetic effects, we conducted a genome-wide search for sexually dimorphic associations with height, weight, body mass index, waist circumference, hip circumference, and waist-to-hip-ratio (133,723 individuals) and took forward 348 SNPs into follow-up (additional 137,052 individuals) in a total of 94 studies. Seven loci displayed significant sex-difference (FDR<5%), including four previously established (near GRB14/COBLL1, LYPLAL1/SLC30A10, VEGFA, ADAMTS9) and three novel anthropometric trait loci (near MAP3K1, HSD17B4, PPARG), all of which were genome-wide significant in women (P<5×10(-8)), but not in men. Sex-differences were apparent only for waist phenotypes, not for height, weight, BMI, or hip circumference. Moreover, we found no evidence for genetic effects with opposite directions in men versus women. The PPARG locus is of specific interest due to its role in diabetes genetics and therapy. Our results demonstrate the value of sex-specific GWAS to unravel the sexually dimorphic genetic underpinning of complex traits.

Genome-wide analysis of BMI in adolescents and young adults reveals additional insight into the effects of genetic loci over the life course

Genetic loci for body mass index (BMI) in adolescence and young adulthood, a period of high risk for weight gain, are understudied, yet may yield important insight into the etiology of obesity and early intervention. To identify novel genetic loci and examine the influence of known loci on BMI during this critical time period in late adolescence and early adulthood, we performed a two-stage meta-analysis using 14 genome-wide association studies in populations of European ancestry with data on BMI between ages 16 and 25 in up to 29 880 individuals. We identified seven independent loci (P < 5.0 × 10⁻⁸) near FTO (P = 3.72 × 10⁻²³), TMEM18 (P = 3.24 × 10⁻¹⁷), MC4R (P = 4.41 × 10⁻¹⁷), TNNI3K (P = 4.32 × 10⁻¹¹), SEC16B (P = 6.24 × 10⁻⁹), GNPDA2 (P = 1.11 × 10⁻⁸) and POMC (P = 4.94 × 10⁻⁸) as well as a potential secondary signal at the POMC locus (rs2118404, P = 2.4 × 10⁻⁵ after conditioning on the established single-nucleotide polymorphism at this locus) in adolescents and young adults. To evaluate the impact of the established genetic loci on BMI at these young ages, we examined differences between the effect sizes of 32 published BMI loci in European adult populations (aged 18-90) and those observed in our adolescent and young adult meta-analysis. Four loci (near PRKD1, TNNI3K, SEC16B and CADM2) had larger effects and one locus (near SH2B1) had a smaller effect on BMI during adolescence and young adulthood compared with older adults (P < 0.05). These results suggest that genetic loci for BMI can vary in their effects across the life course, underlying the importance of evaluating BMI at different ages.

Genome-wide meta-analysis identifies 11 new loci for anthropometric traits and provides insights into genetic architecture

Approaches exploiting trait distribution extremes may be used to identify loci associated with common traits, but it is unknown whether these loci are generalizable to the broader population. In a genome-wide search for loci associated with the upper versus the lower 5th percentiles of body mass index, height and waist-to-hip ratio, as well as clinical classes of obesity, including up to 263,407 individuals of European ancestry, we identified 4 new loci (IGFBP4, H6PD, RSRC1 and PPP2R2A) influencing height detected in the distribution tails and 7 new loci (HNF4G, RPTOR, GNAT2, MRPS33P4, ADCY9, HS6ST3 and ZZZ3) for clinical classes of obesity. Further, we find a large overlap in genetic structure and the distribution of variants between traits based on extremes and the general population and little etiological heterogeneity between obesity subgroups.

Common genetic polymorphisms modify the effect of smoking on absolute risk of bladder cancer

Bladder cancer results from the combined effects of environmental and genetic factors, smoking being the strongest risk factor. Evaluating absolute risks resulting from the joint effects of smoking and genetic factors is critical to assess the public health relevance of genetic information. Analyses included up to 3,942 cases and 5,680 controls of European background in seven studies. We tested for multiplicative and additive interactions between smoking and 12 susceptibility loci, individually and combined as a polygenic risk score (PRS). Thirty-year absolute risks and risk differences by levels of the PRS were estimated for U.S. males aged 50 years. Six of 12 variants showed significant additive gene-environment interactions, most notably NAT2 (P = 7 × 10(-4)) and UGT1A6 (P = 8 × 10(-4)). The 30-year absolute risk of bladder cancer in U.S. males was 6.2% for all current smokers. This risk ranged from 2.9% for current smokers in the lowest quartile of the PRS to 9.9% for current smokers in the upper quartile. Risk difference estimates indicated that 8,200 cases would be prevented if elimination of smoking occurred in 100,000 men in the upper PRS quartile compared with 2,000 cases prevented by a similar effort in the lowest PRS quartile (P(additive) = 1 × 10(-4)). Thus, the potential impact of eliminating smoking on the number of bladder cancer cases prevented is larger for individuals at higher than lower genetic risk. Our findings could have implications for targeted prevention strategies. However, other smoking-related diseases, as well as practical and ethical considerations, need to be considered before any recommendations could be made.

Testicular germ cell tumor susceptibility associated with the UCK2 locus on chromosome 1q23

Genome-wide association studies (GWASs) have identified multiple common genetic variants associated with an increased risk of testicular germ cell tumors (TGCTs). A previous GWAS reported a possible TGCT susceptibility locus on chromosome 1q23 in the UCK2 gene, but failed to reach genome-wide significance following replication. We interrogated this region by conducting a meta-analysis of two independent GWASs including a total of 940 TGCT cases and 1559 controls for 122 single-nucleotide polymorphisms (SNPs) on chromosome 1q23 and followed up the most significant SNPs in an additional 2202 TGCT cases and 2386 controls from four case-control studies. We observed genome-wide significant associations for several UCK2 markers, the most significant of which was for rs3790665 (PCombined = 6.0 × 10(-9)). Additional support is provided from an independent familial study of TGCT where a significant over-transmission for rs3790665 with TGCT risk was observed (PFBAT = 2.3 × 10(-3)). Here, we provide substantial evidence for the association between UCK2 genetic variation and TGCT risk.

Polymorphisms in genes related to one-carbon metabolism are not related to pancreatic cancer in PanScan and PanC4

PURPOSE

The evidence of a relation between folate intake and one-carbon metabolism (OCM) with pancreatic cancer (PanCa) is inconsistent. In this study, the association between genes and single-nucleotide polymorphisms (SNPs) related to OCM and PanCa was assessed.

METHODS

Using biochemical knowledge of the OCM pathway, we identified thirty-seven genes and 834 SNPs to examine in association with PanCa. Our study included 1,408 cases and 1,463 controls nested within twelve cohorts (PanScan). The ten SNPs and five genes with lowest p values (<0.02) were followed up in 2,323 cases and 2,340 controls from eight case-control studies (PanC4) that participated in PanScan2. The correlation of SNPs with metabolite levels was assessed for 649 controls from the European Prospective Investigation into Cancer and Nutrition.

RESULTS

When both stages were combined, we observed suggestive associations with PanCa for rs10887710 (MAT1A) (OR 1.13, 95 %CI 1.04-1.23), rs1552462 (SYT9) (OR 1.27, 95 %CI 1.02-1.59), and rs7074891 (CUBN) (OR 1.91, 95 %CI 1.12-3.26). After correcting for multiple comparisons, no significant associations were observed in either the first or second stage. The three suggested SNPs showed no correlations with one-carbon biomarkers.

CONCLUSIONS

This is the largest genetic study to date to examine the relation between germline variations in OCM-related genes polymorphisms and the risk of PanCa. Suggestive evidence for an association between polymorphisms and PanCa was observed among the cohort-nested studies, but this did not replicate in the case-control studies. Our results do not strongly support the hypothesis that genes related to OCM play a role in pancreatic carcinogenesis.

Diabetes and risk of pancreatic cancer: a pooled analysis from the pancreatic cancer cohort consortium

PURPOSE

Diabetes is a suspected risk factor for pancreatic cancer, but questions remain about whether it is a risk factor or a result of the disease. This study prospectively examined the association between diabetes and the risk of pancreatic adenocarcinoma in pooled data from the NCI pancreatic cancer cohort consortium (PanScan).

METHODS

The pooled data included 1,621 pancreatic adenocarcinoma cases and 1,719 matched controls from twelve cohorts using a nested case-control study design. Subjects who were diagnosed with diabetes near the time (<2 years) of pancreatic cancer diagnosis were excluded from all analyses. All analyses were adjusted for age, race, gender, study, alcohol use, smoking, BMI, and family history of pancreatic cancer.

RESULTS

Self-reported diabetes was associated with a forty percent increased risk of pancreatic cancer (OR = 1.40, 95 % CI: 1.07, 1.84). The association differed by duration of diabetes; risk was highest for those with a duration of 2-8 years (OR = 1.79, 95 % CI: 1.25, 2.55); there was no association for those with 9+ years of diabetes (OR = 1.02, 95 % CI: 0.68, 1.52).

CONCLUSIONS

These findings provide support for a relationship between diabetes and pancreatic cancer risk. The absence of association in those with the longest duration of diabetes may reflect hypoinsulinemia and warrants further investigation.

A meta-analysis of genome-wide association studies of breast cancer identifies two novel susceptibility loci at 6q14 and 20q11

Genome-wide association studies (GWAS) of breast cancer defined by hormone receptor status have revealed loci contributing to susceptibility of estrogen receptor (ER)-negative subtypes. To identify additional genetic variants for ER-negative breast cancer, we conducted the largest meta-analysis of ER-negative disease to date, comprising 4754 ER-negative cases and 31 663 controls from three GWAS: NCI Breast and Prostate Cancer Cohort Consortium (BPC3) (2188 ER-negative cases; 25 519 controls of European ancestry), Triple Negative Breast Cancer Consortium (TNBCC) (1562 triple negative cases; 3399 controls of European ancestry) and African American Breast Cancer Consortium (AABC) (1004 ER-negative cases; 2745 controls). We performed in silico replication of 86 SNPs at P ≤ 1 × 10(-5) in an additional 11 209 breast cancer cases (946 with ER-negative disease) and 16 057 controls of Japanese, Latino and European ancestry. We identified two novel loci for breast cancer at 20q11 and 6q14. SNP rs2284378 at 20q11 was associated with ER-negative breast cancer (combined two-stage OR = 1.16; P = 1.1 × 10(-8)) but showed a weaker association with overall breast cancer (OR = 1.08, P = 1.3 × 10(-6)) based on 17 869 cases and 43 745 controls and no association with ER-positive disease (OR = 1.01, P = 0.67) based on 9965 cases and 22 902 controls. Similarly, rs17530068 at 6q14 was associated with breast cancer (OR = 1.12; P = 1.1 × 10(-9)), and with both ER-positive (OR = 1.09; P = 1.5 × 10(-5)) and ER-negative (OR = 1.16, P = 2.5 × 10(-7)) disease. We also confirmed three known loci associated with ER-negative (19p13) and both ER-negative and ER-positive breast cancer (6q25 and 12p11). Our results highlight the value of large-scale collaborative studies to identify novel breast cancer risk loci.

Genome-wide association analysis identifies new lung cancer susceptibility loci in never-smoking women in Asia

To identify common genetic variants that contribute to lung cancer susceptibility, we conducted a multistage genome-wide association study of lung cancer in Asian women who never smoked. We scanned 5,510 never-smoking female lung cancer cases and 4,544 controls drawn from 14 studies from mainland China, South Korea, Japan, Singapore, Taiwan and Hong Kong. We genotyped the most promising variants (associated at P < 5 × 10(-6)) in an additional 1,099 cases and 2,913 controls. We identified three new susceptibility loci at 10q25.2 (rs7086803, P = 3.54 × 10(-18)), 6q22.2 (rs9387478, P = 4.14 × 10(-10)) and 6p21.32 (rs2395185, P = 9.51 × 10(-9)). We also confirmed associations reported for loci at 5p15.33 and 3q28 and a recently reported finding at 17q24.3. We observed no evidence of association for lung cancer at 15q25 in never-smoking women in Asia, providing strong evidence that this locus is not associated with lung cancer independent of smoking.

Genome-wide association study of circulating estradiol, testosterone, and sex hormone-binding globulin in postmenopausal women

Genome-wide association studies (GWAS) have successfully identified common genetic variants that contribute to breast cancer risk. Discovering additional variants has become difficult, as power to detect variants of weaker effect with present sample sizes is limited. An alternative approach is to look for variants associated with quantitative traits that in turn affect disease risk. As exposure to high circulating estradiol and testosterone, and low sex hormone-binding globulin (SHBG) levels is implicated in breast cancer etiology, we conducted GWAS analyses of plasma estradiol, testosterone, and SHBG to identify new susceptibility alleles. Cancer Genetic Markers of Susceptibility (CGEMS) data from the Nurses’ Health Study (NHS), and Sisters in Breast Cancer Screening data were used to carry out primary meta-analyses among ∼1600 postmenopausal women who were not taking postmenopausal hormones at blood draw. We observed a genome-wide significant association between SHBG levels and rs727428 (joint β = -0.126; joint P = 2.09×10^–16), downstream of the SHBG gene. No genome-wide significant associations were observed with estradiol or testosterone levels. Among variants that were suggestively associated with estradiol (P<10^–5), several were located at the CYP19A1 gene locus. Overall results were similar in secondary meta-analyses that included ∼900 NHS current postmenopausal hormone users. No variant associated with estradiol, testosterone, or SHBG at P<10^–5 was associated with postmenopausal breast cancer risk among CGEMS participants. Our results suggest that the small magnitude of difference in hormone levels associated with common genetic variants is likely insufficient to detectably contribute to breast cancer risk.

A subset-based approach improves power and interpretation for the combined analysis of genetic association studies of heterogeneous traits

Pooling genome-wide association studies (GWASs) increases power but also poses methodological challenges because studies are often heterogeneous. For example, combining GWASs of related but distinct traits can provide promising directions for the discovery of loci with small but common pleiotropic effects. Classical approaches for meta-analysis or pooled analysis, however, might not be suitable for such analysis because individual variants are likely to be associated with only a subset of the traits or might demonstrate effects in different directions. We propose a method that exhaustively explores subsets of studies for the presence of true association signals that are in either the same direction or possibly opposite directions. An efficient approximation is used for rapid evaluation of p values. We present two illustrative applications, one for a meta-analysis of separate case-control studies of six distinct cancers and another for pooled analysis of a case-control study of glioma, a class of brain tumors that contains heterogeneous subtypes. Both the applications and additional simulation studies demonstrate that the proposed methods offer improved power and more interpretable results when compared to traditional methods for the analysis of heterogeneous traits. The proposed framework has applications beyond genetic association studies.

Pathway analysis of genome-wide association study data highlights pancreatic development genes as susceptibility factors for pancreatic cancer

Four loci have been associated with pancreatic cancer through genome-wide association studies (GWAS). Pathway-based analysis of GWAS data is a complementary approach to identify groups of genes or biological pathways enriched with disease-associated single-nucleotide polymorphisms (SNPs) whose individual effect sizes may be too small to be detected by standard single-locus methods. We used the adaptive rank truncated product method in a pathway-based analysis of GWAS data from 3851 pancreatic cancer cases and 3934 control participants pooled from 12 cohort studies and 8 case-control studies (PanScan). We compiled 23 biological pathways hypothesized to be relevant to pancreatic cancer and observed a nominal association between pancreatic cancer and five pathways (P < 0.05), i.e. pancreatic development, Helicobacter pylori lacto/neolacto, hedgehog, Th1/Th2 immune response and apoptosis (P = 2.0 × 10(-6), 1.6 × 10(-5), 0.0019, 0.019 and 0.023, respectively). After excluding previously identified genes from the original GWAS in three pathways (NR5A2, ABO and SHH), the pancreatic development pathway remained significant (P = 8.3 × 10(-5)), whereas the others did not. The most significant genes (P < 0.01) in the five pathways were NR5A2, HNF1A, HNF4G and PDX1 for pancreatic development; ABO for H.pylori lacto/neolacto; SHH for hedgehog; TGFBR2 and CCL18 for Th1/Th2 immune response and MAPK8 and BCL2L11 for apoptosis. Our results provide a link between inherited variation in genes important for pancreatic development and cancer and show that pathway-based approaches to analysis of GWAS data can yield important insights into the collective role of genetic risk variants in cancer.

Abstract 3110: The aging genome: Genetic mosaicism and its relationship to cancer

Genetic mosaicism, the coexistence of cells of distinct genetic composition within an organism, has been associated with developmental and somatic disorders. Recently, we reported on 1,991 individuals from a population-based study of adult bladder cancer where we detected autosomal mosaicism in 1.7% of study subjects, suggesting a higher frequency than previously suspected, but did not reveal a significant association with bladder cancer. We have now extended our analysis to 57,853 subjects, 31,717 cancer cases and 26,136 cancer-free controls, using genome-wide SNP array data generated as part of 13 genome-wide association studies drawn from 48 case-control and case-cohort studies. Detection of autosomal mosaic events was based on assessment of allelic imbalance and copy number changes. We found autosomal mosaicism in blood or buccal mucosa DNA for chromosomal events of size &gt;2 Mb on 641 chromosomes in 517 individuals for an overall frequency of individuals with mosaicism of 0.87%. The most frequent type of event observed was copy-neutral LOH (48.2%), while copy-gains and copy-losses were observed for 15.1% and 34.8% of mosaic events, respectively. The strongest predictor of autosomal mosaicism was age at DNA collection. In cancer-free individuals, the frequency of having a mosaic event was 0.23% for those under 50 and 1.91% between 75 and 79 (p=4.8×10-8). Mosaicism was more frequent in males than females (OR=1.42, 1.14-1.80 95% CI, p=0.002) and in individuals with non-hematologic cancer (0.97% versus 0.74% in cancer-free individuals, OR=1.25, 1.04-1.50 95% CI, p=0.016), with a stronger association in cases who had DNA collected prior to treatment (OR=1.45, 1.18-1.80 95% CI, p=0.0005). Notable associations were observed in stratified analyses of lung (OR=1.56, 1.18-2.08 95% CI, p=0.002) and kidney (OR=1.98, 1.27-3.06 95% CI, p=0.002) cancers, both tobacco-associated malignancies. There was no significant association in non-hematological cancer cases overall between smoking (ever/never) and frequency of mosaicism (OR=1.19, 0.92-1.54 95% CI, p=0.19) or when stratified by cancer site. The frequency of mosaicism was higher in individuals diagnosed with leukemia who had DNA collected at least one year prior to diagnosis (overall OR=35.4, 14.7-76.6 95% CI, p=3.8×10-11); 15.8% had myeloid leukemia and 26.3% had lymphocytic leukemia. We conclude that autosomal mosaicism is present in the population with surprising frequency and particularly in the ageing genome. Further work is required to begin to unravel the underlying mechanisms, particularly as it relates to aging, the timing and expansion of distinct populations of cells bearing markedly different structural events in one or more chromosome. These findings underscore the importance of considering the role and time-dependent nature of somatic events in the etiology of cancer and other late-onset diseases.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 103rd Annual Meeting of the American Association for Cancer Research; 2012 Mar 31-Apr 4; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2012;72(8 Suppl):Abstract nr 3110. doi:1538-7445.AM2012-3110

Comprehensive resequence analysis of a 123-kb region of chromosome 11q13 associated with prostate cancer

BACKGROUND

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 11q13.3 in men of European decent. A fine-mapping analysis with tag SNPs in the cancer genetic markers of susceptibility study identified three independent loci, marked by rs10896438, rs12793759, and rs10896449. This study further annotates common and uncommon variation across this region.

METHODS

A next generation resequence analysis of a 122.9-kb region of 11q13.3(68,642,755-68,765,690) was conducted in 78 unrelated individuals of European background,1 CEPH trio, and 1 YRI trio.

RESULTS

In total, 644 polymorphic loci were identified by our sequence analysis. Of these,166 variants—118 SNPs and 48 insertion-deletion polymorphisms (indels)—were novel,namely not present in the 1000 Genomes or International HapMap Projects. We identified 22,25, 6, and 4 variants strongly correlated (r2 ≥ 0.8) with rs10896438, rs10896449, rs12793759,and rs11228565, respectively. HapMap SNPs were in linkage disequilibrium (r2 ≥ 0.8) with 48%, 69%, 14%, and 60% of SNPs marking bins by rs10896438, rs10896449, rs12793759, and rs11228565, respectively.

CONCLUSIONS

Our next generation resequence analysis compliments publicly available datasets of European descent (HapMap, build 28 and 1000 Genome, Pilot 1, October 2010),underscoring the value of targeted resequence analysis prior to initiating functional studies based on public databases alone. Increasing the number of common variants enables investigators to better prioritize variants for functional studies designed to uncover the biological basis of the direct association(s) in the region.

Genotypic variants at 2q33 and risk of esophageal squamous cell carcinoma in China: a meta-analysis of genome-wide association studies

Genome-wide association studies have identified susceptibility loci for esophageal squamous cell carcinoma (ESCC). We conducted a meta-analysis of all single-nucleotide polymorphisms (SNPs) that showed nominally significant P-values in two previously published genome-wide scans that included a total of 2961 ESCC cases and 3400 controls. The meta-analysis revealed five SNPs at 2q33 with P< 5 × 10(-8), and the strongest signal was rs13016963, with a combined odds ratio (95% confidence interval) of 1.29 (1.19-1.40) and P= 7.63 × 10(-10). An imputation analysis of 4304 SNPs at 2q33 suggested a single association signal, and the strongest imputed SNP associations were similar to those from the genotyped SNPs. We conducted an ancestral recombination graph analysis with 53 SNPs to identify one or more haplotypes that harbor the variants directly responsible for the detected association signal. This showed that the five SNPs exist in a single haplotype along with 45 imputed SNPs in strong linkage disequilibrium, and the strongest candidate was rs10201587, one of the genotyped SNPs. Our meta-analysis found genome-wide significant SNPs at 2q33 that map to the CASP8/ALS2CR12/TRAK2 gene region. Variants in CASP8 have been extensively studied across a spectrum of cancers with mixed results. The locus we identified appears to be distinct from the widely studied rs3834129 and rs1045485 SNPs in CASP8. Future studies of esophageal and other cancers should focus on comprehensive sequencing of this 2q33 locus and functional analysis of rs13016963 and rs10201587 and other strongly correlated variants.

Y chromosome haplogroups and prostate cancer in populations of European and Ashkenazi Jewish ancestry

Genetic variation on the Y chromosome has not been convincingly implicated in prostate cancer risk. To comprehensively analyze the role of inherited Y chromosome variation in prostate cancer risk in individuals of European ancestry, we genotyped 34 binary Y chromosome markers in 3,995 prostate cancer cases and 3,815 control subjects drawn from four studies. In this set, we identified nominally significant association between a rare haplogroup, E1b1b1c, and prostate cancer in stage I (P = 0.012, OR = 0.51; 95% confidence interval 0.30–0.87). Population substructure of E1b1b1c carriers suggested Ashkenazi Jewish ancestry, prompting a replication phase in individuals of both European and Ashkenazi Jewish ancestry. The association was not significant for prostate cancer overall in studies of either Ashkenazi Jewish (1,686 cases and 1,597 control subjects) or European (686 cases and 734 control subjects) ancestry (P_meta = 0.078), but a meta-analysis of stage I and II studies revealed a nominally significant association with prostate cancer risk (P_meta = 0.010, OR = 0.77; 95% confidence interval 0.62–0.94). Comparing haplogroup frequencies between studies, we noted strong similarities between those conducted in the US and France, in which the majority of men carried R1 haplogroups, resembling Northwestern European populations. On the other hand, Finns had a remarkably different haplogroup distribution with a preponderance of N1c and I1 haplogroups. In summary, our results suggest that inherited Y chromosome variation plays a limited role in prostate cancer etiology in European populations but warrant follow-up in additional large and well characterized studies of multiple ethnic backgrounds.

Large-scale pathway-based analysis of bladder cancer genome-wide association data from five studies of European background

Pathway analysis of genome-wide association studies (GWAS) offer a unique opportunity to collectively evaluate genetic variants with effects that are too small to be detected individually. We applied a pathway analysis to a bladder cancer GWAS containing data from 3,532 cases and 5,120 controls of European background (n = 5 studies). Thirteen hundred and ninety-nine pathways were drawn from five publicly available resources (Biocarta, Kegg, NCI-PID, HumanCyc, and Reactome), and we constructed 22 additional candidate pathways previously hypothesized to be related to bladder cancer. In total, 1421 pathways, 5647 genes and ∼90,000 SNPs were included in our study. Logistic regression model adjusting for age, sex, study, DNA source, and smoking status was used to assess the marginal trend effect of SNPs on bladder cancer risk. Two complementary pathway-based methods (gene-set enrichment analysis [GSEA], and adapted rank-truncated product [ARTP]) were used to assess the enrichment of association signals within each pathway. Eighteen pathways were detected by either GSEA or ARTP at P≤0.01. To minimize false positives, we used the I² statistic to identify SNPs displaying heterogeneous effects across the five studies. After removing these SNPs, seven pathways (‘Aromatic amine metabolism’ [P_GSEA = 0.0100, P_ARTP = 0.0020], ‘NAD biosynthesis’ [P_GSEA = 0.0018, P_ARTP = 0.0086], ‘NAD salvage’ [P_ARTP = 0.0068], ‘Clathrin derived vesicle budding’ [P_ARTP = 0.0018], ‘Lysosome vesicle biogenesis’ [P_GSEA = 0.0023, P_ARTP<0.00012], ’Retrograde neurotrophin signaling’ [P_GSEA = 0.00840], and ‘Mitotic metaphase/anaphase transition’ [P_GSEA = 0.0040]) remained. These pathways seem to belong to three fundamental cellular processes (metabolic detoxification, mitosis, and clathrin-mediated vesicles). Identification of the aromatic amine metabolism pathway provides support for the ability of this approach to identify pathways with established relevance to bladder carcinogenesis.

A genome-wide association study of bladder cancer identifies a new susceptibility locus within SLC14A1, a urea transporter gene on chromosome 18q12.3

Genome-wide and candidate-gene association studies of bladder cancer have identified 10 susceptibility loci thus far. We conducted a meta-analysis of two previously published genome-wide scans (4501 cases and 6076 controls of European background) and followed up the most significant association signals [17 single nucleotide polymorphisms (SNPs) in 10 genomic regions] in 1382 cases and 2201 controls from four studies. A combined analysis adjusted for study center, age, sex, and smoking status identified a novel susceptibility locus that mapped to a region of 18q12.3, marked by rs7238033 (P = 8.7 × 10(-9); allelic odds ratio 1.20 with 95% CI: 1.13-1.28) and two highly correlated SNPs, rs10775480/rs10853535 (r(2)= 1.00; P = 8.9 × 10(-9); allelic odds ratio 1.16 with 95% CI: 1.10-1.22). The signal localizes to the solute carrier family 14 member 1 gene, SLC14A1, a urea transporter that regulates cellular osmotic pressure. In the kidney, SLC14A1 regulates urine volume and concentration whereas in erythrocytes it determines the Kidd blood groups. Our findings suggest that genetic variation in SLC14A1 could provide new etiological insights into bladder carcinogenesis.

A genome-wide association study identifies a novel susceptibility locus for renal cell carcinoma on 12p11.23

Renal cell carcinoma (RCC) is the most lethal urologic cancer. Only two common susceptibility loci for RCC have been confirmed to date. To identify additional RCC common susceptibility loci, we conducted an independent genome-wide association study (GWAS). We analyzed 533 191 single nucleotide polymorphisms (SNPs) for association with RCC in 894 cases and 1516 controls of European descent recruited from MD Anderson Cancer Center in the primary scan, and validated the top 500 SNPs in silico in 3772 cases and 8505 controls of European descent involved in the only published GWAS of RCC. We identified two common variants in linkage disequilibrium, rs718314 and rs1049380 (r(2) = 0.64, D ' = 0.84), in the inositol 1,4,5-triphosphate receptor, type 2 (ITPR2) gene on 12p11.23 as novel susceptibility loci for RCC (P = 8.89 × 10(-10) and P = 6.07 × 10(-9), respectively, in meta-analysis) with an allelic odds ratio of 1.19 [95% confidence interval (CI): 1.13-1.26] for rs718314 and 1.18 (95% CI: 1.12-1.25) for rs1049380. It has been recently identified that rs718314 in ITPR2 is associated with waist-hip ratio (WHR) phenotype. To our knowledge, this is the first genetic locus associated with both cancer risk and WHR.

Genome-wide association study identifies new prostate cancer susceptibility loci

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10(-8)). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10(-9)). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.

Genome-wide association study of circulating retinol levels

Retinol is one of the most biologically active forms of vitamin A and is hypothesized to influence a wide range of human diseases including asthma, cardiovascular disease, infectious diseases and cancer. We conducted a genome-wide association study of 5006 Caucasian individuals drawn from two cohorts of men: the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. We identified two independent single-nucleotide polymorphisms associated with circulating retinol levels, which are located near the transthyretin (TTR) and retinol binding protein 4 (RBP4) genes which encode major carrier proteins of retinol: rs1667255 (P =2.30× 10(-17)) and rs10882272 (P =6.04× 10(-12)). We replicated the association with rs10882272 in RBP4 in independent samples from the Nurses' Health Study and the Invecchiare in Chianti Study (InCHIANTI) that included 3792 women and 504 men (P =9.49× 10(-5)), but found no association for retinol with rs1667255 in TTR among women, thus suggesting evidence for gender dimorphism (P-interaction=1.31× 10(-5)). Discovery of common genetic variants associated with serum retinol levels may provide further insight into the contribution of retinol and other vitamin A compounds to the development of cancer and other complex diseases.

Large-scale fine mapping of the HNF1B locus and prostate cancer risk

Previous genome-wide association studies have identified two independent variants in HNF1B as susceptibility loci for prostate cancer risk. To fine-map common genetic variation in this region, we genotyped 79 single nucleotide polymorphisms (SNPs) in the 17q12 region harboring HNF1B in 10 272 prostate cancer cases and 9123 controls of European ancestry from 10 case-control studies as part of the Cancer Genetic Markers of Susceptibility (CGEMS) initiative. Ten SNPs were significantly related to prostate cancer risk at a genome-wide significance level of P < 5 × 10(-8) with the most significant association with rs4430796 (P = 1.62 × 10(-24)). However, risk within this first locus was not entirely explained by rs4430796. Although modestly correlated (r(2)= 0.64), rs7405696 was also associated with risk (P = 9.35 × 10(-23)) even after adjustment for rs4430769 (P = 0.007). As expected, rs11649743 was related to prostate cancer risk (P = 3.54 × 10(-8)); however, the association within this second locus was stronger for rs4794758 (P = 4.95 × 10(-10)), which explained all of the risk observed with rs11649743 when both SNPs were included in the same model (P = 0.32 for rs11649743; P = 0.002 for rs4794758). Sequential conditional analyses indicated that five SNPs (rs4430796, rs7405696, rs4794758, rs1016990 and rs3094509) together comprise the best model for risk in this region. This study demonstrates a complex relationship between variants in the HNF1B region and prostate cancer risk. Further studies are needed to investigate the biological basis of the association of variants in 17q12 with prostate cancer.

Meta-analysis for linkage to asthma and atopy in the chromosome 5q31-33 candidate region

Asthma is a common, complex human disease. Gene discovery in asthma has been complicated by substantial etiological heterogeneity, the possibility of genes of small effect and the concomitant requirement for large sample sizes. Linkage to asthma phenotypes has been investigated most intensively in the 5q chromosomal region, although results have been inconsistent across studies and all studies have had modest sample sizes. One potential solution to these issues is to combine data from multiple studies in a retrospective meta-analysis by pooling either summary statistics or raw data. The International Consortium on Asthma Genetics combined data from 11 data sets (n = 6277 subjects) to investigate evidence for linkage of 35 markers spanning the cytokine cluster on chromosome 5q31–33 to 'asthma' dichotomy and total serum immunoglobulin E (IgE) levels. Chromosome 5q markers typed in different centers were integrated into a consensus map to facilitate effective data pooling. Multipoint linkage analyses using a new Haseman–Elston method were performed with all data sets pooled together, and also separately with the resulting linkage statistics pooled by meta-analytic methods. Our results did not provide any evidence significant at the 5% level that loci conferring susceptibility to asthma or atopy are present in the 5q31–33 region; however, there was some weak evidence (empirical P = 0.077) of linkage to asthma affection. This study suggests that loci in 5q31–33 have at most a modest effect on susceptibility to asthma or total serum IgE levels, may not be detectable or present in all human populations and are difficult to detect even using combined linkage evidence from 2400–2600 full sibling pairs.

Comprehensive resequence analysis of a 97 kb region of chromosome 10q11.2 containing the MSMB gene associated with prostate cancer

Genome-wide association studies of prostate cancer have identified single nucleotide polymorphism (SNP) markers in a region of chromosome 10q11.2, harboring the microseminoprotein-β (MSMB) gene. Both the gene product of MSMB, the prostate secretory protein 94 (PSP94) and its binding protein (PSPBP), have been previously investigated as serum biomarkers for prostate cancer progression. Recent functional work has shown that different alleles of the significantly associated SNP in the promoter of MSMB found to be associated with prostate cancer risk, rs10993994, can influence its expression in tumors and in vitro studies. Since it is plausible that additional variants in this region contribute to the risk of prostate cancer, we have used next-generation sequencing technology to resequence a ~97-kb region that includes the area surrounding MSMB (chr10: 51,168,025–51,265,101) in 36 prostate cancer cases, 26 controls of European origin, and 8 unrelated CEPH individuals in order to identify additional variants to investigate in functional studies. We identified 241 novel polymorphisms within this region, including 142 in the 51-kb block of linkage disequilibrium (LD) that contains rs10993994 and the proximal promoter of MSMB. No sites were observed to be polymorphic within the exons of MSMB.

Fine mapping of a region of chromosome 11q13 reveals multiple independent loci associated with risk of prostate cancer

Genome-wide association studies have identified prostate cancer susceptibility alleles on chromosome 11q13. As part of the Cancer Genetic Markers of Susceptibility (CGEMS) Initiative, the region flanking the most significant marker, rs10896449, was fine mapped in 10 272 cases and 9123 controls of European origin (10 studies) using 120 common single nucleotide polymorphisms (SNPs) selected by a two-staged tagging strategy using HapMap SNPs. Single-locus analysis identified 18 SNPs below genome-wide significance (P< 10(-8)) with rs10896449 the most significant (P= 7.94 × 10(-19)). Multi-locus models that included significant SNPs sequentially identified a second association at rs12793759 [odds ratio (OR) = 1.14, P= 4.76 × 10(-5), adjusted P= 0.004] that is independent of rs10896449 and remained significant after adjustment for multiple testing within the region. rs10896438, a proxy of previously reported rs12418451 (r(2)= 0.96), independent of both rs10896449 and rs12793759 was detected (OR = 1.07, P= 5.92 × 10(-3), adjusted P= 0.054). Our observation of a recombination hotspot that separates rs10896438 from rs10896449 and rs12793759, and low linkage disequilibrium (rs10896449-rs12793759, r(2)= 0.17; rs10896449-rs10896438, r(2)= 0.10; rs12793759-rs10896438, r(2)= 0.12) corroborate our finding of three independent signals. By analysis of tagged SNPs across ∼123 kb using next generation sequencing of 63 controls of European origin, 1000 Genome and HapMap data, we observed multiple surrogates for the three independent signals marked by rs10896449 (n= 31), rs10896438 (n= 24) and rs12793759 (n= 8). Our results indicate that a complex architecture underlying the common variants contributing to prostate cancer risk at 11q13. We estimate that at least 63 common variants should be considered in future studies designed to investigate the biological basis of the multiple association signals.

Abstract 4726: Genetic determinants of serum retinol: A genome-wide association study

Background: Retinol, the most biologically active form of vitamin A, is hypothesized to influence a wide range of diseases. We recently reported results from the Alpha-Tocopherol, Beta-Carotene Cancer Prevention (ATBC) Study suggesting that higher serum retinol is related to increased prostate cancer risk. Circulating retinol concentrations are influenced by many factors in addition to dietary and supplemental intake, including those related to intestinal absorption, transport, and cleavage of pro-vitamin A compounds to form retinol. Thus, genetic factors that influence retinol concentrations may also impact human disease risk.

Methods: We conducted a genome-wide association study (GWAS) of 4,041 Caucasian individuals drawn from two cohorts: the ATBC Study and the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Screening Trial. Our findings were replicated in an independent sample of 2,056 individuals from the Nurses’ Health Study.

Results: We identified two independent SNPs near the genes encoding key retinol carrier proteins, transthyretin (TTR) and retinol binding protein 4 (RBP4), that were associated at the level of genome-wide significance with retinol concentrations: rs1667255 (in 18q12.1) and rs10882272 (in 10q23.33). After meta-analysis with the replication sample, these SNPs remained highly significant (rs1667255: p = 2.33 × 10-14; rs10882272: p = 1.08 × 10-13). In the two GWAS studies, mean serum retinol concentrations increased with number of risk alleles (0,1,2) for TTR from 556-578-602 μg/L in ATBC and 654-688-711 μg/L in PLCO, and decreased for 0,1,2 risk alleles in RBP4 (580-567-541 μg/L in ATBC and 697-668-653 μg/L in PLCO).

Conclusions: This is the first GWAS of circulating retinol levels to reveal novel, genome-wide significant loci, one near TTR and one near RBP4, genes that encode the two major retinol carrier proteins. Understanding the genetic and other determinants of retinol status may help shed light on the etiology of cancer and other diseases associated with vitamin A.

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 4726. doi:10.1158/1538-7445.AM2011-4726

Novel breast cancer susceptibility locus at 9q31.2: results of a genome-wide association study

BACKGROUND

Genome-wide association studies have identified several common genetic variants associated with breast cancer risk. It is likely, however, that a substantial proportion of such loci have not yet been discovered.

METHODS

We compared 296,114 tagging single-nucleotide polymorphisms in 1694 breast cancer case subjects (92% with two primary cancers or at least two affected first-degree relatives) and 2365 control subjects, with validation in three independent series totaling 11,880 case subjects and 12,487 control subjects. Odds ratios (ORs) and associated 95% confidence intervals (CIs) in each stage and all stages combined were calculated using unconditional logistic regression. Heterogeneity was evaluated with Cochran Q and I(2) statistics. All statistical tests were two-sided.

RESULTS

We identified a novel risk locus for breast cancer at 9q31.2 (rs865686: OR = 0.89, 95% CI = 0.85 to 0.92, P = 1.75 × 10(-10)). This single-nucleotide polymorphism maps to a gene desert, the nearest genes being Kruppel-like factor 4 (KLF4, 636 kb centromeric), RAD23 homolog B (RAD23B, 794 kb centromeric), and actin-like 7A (ACTL7A, 736 kb telomeric). We also identified two variants (rs3734805 and rs9383938) mapping to 6q25.1 estrogen receptor 1 (ESR1), which were associated with breast cancer in subjects of northern European ancestry (rs3734805: OR = 1.19, 95% CI = 1.11 to 1.27, P = 1.35 × 10(-7); rs9383938: OR = 1.18, 95% CI = 1.11 to 1.26, P = 1.41 × 10(-7)). A variant mapping to 10q26.13, approximately 300 kb telomeric to the established risk locus within the second intron of FGFR2, was also associated with breast cancer risk, although not at genome-wide statistical significance (rs10510102: OR = 1.12, 95% CI = 1.07 to 1.17, P = 1.58 × 10(-6)).

CONCLUSIONS

These findings provide further evidence on the role of genetic variation in the etiology of breast cancer. Fine mapping will be needed to identify causal variants and to determine their functional effects.

Quality control and quality assurance in genotypic data for genome-wide association studies

Genome-wide scans of nucleotide variation in human subjects are providing an increasing number of replicated associations with complex disease traits. Most of the variants detected have small effects and, collectively, they account for a small fraction of the total genetic variance. Very large sample sizes are required to identify and validate findings. In this situation, even small sources of systematic or random error can cause spurious results or obscure real effects. The need for careful attention to data quality has been appreciated for some time in this field, and a number of strategies for quality control and quality assurance (QC/QA) have been developed. Here we extend these methods and describe a system of QC/QA for genotypic data in genome-wide association studies (GWAS). This system includes some new approaches that (1) combine analysis of allelic probe intensities and called genotypes to distinguish gender misidentification from sex chromosome aberrations, (2) detect autosomal chromosome aberrations that may affect genotype calling accuracy, (3) infer DNA sample quality from relatedness and allelic intensities, (4) use duplicate concordance to infer SNP quality, (5) detect genotyping artifacts from dependence of Hardy-Weinberg equilibrium test P-values on allelic frequency, and (6) demonstrate sensitivity of principal components analysis to SNP selection. The methods are illustrated with examples from the "Gene Environment Association Studies" (GENEVA) program. The results suggest several recommendations for QC/QA in the design and execution of GWAS.

A multi-stage genome-wide association study of bladder cancer identifies multiple susceptibility loci

We conducted a multi-stage, genome-wide association study of bladder cancer with a primary scan of 591,637 SNPs in 3,532 affected individuals (cases) and 5,120 controls of European descent from five studies followed by a replication strategy, which included 8,382 cases and 48,275 controls from 16 studies. In a combined analysis, we identified three new regions associated with bladder cancer on chromosomes 22q13.1, 19q12 and 2q37.1: rs1014971, (P = 8 × 10⁻¹²) maps to a non-genic region of chromosome 22q13.1, rs8102137 (P = 2 × 10⁻¹¹) on 19q12 maps to CCNE1 and rs11892031 (P = 1 × 10⁻⁷) maps to the UGT1A cluster on 2q37.1. We confirmed four previously identified genome-wide associations on chromosomes 3q28, 4p16.3, 8q24.21 and 8q24.3, validated previous candidate associations for the GSTM1 deletion (P = 4 × 10⁻¹¹) and a tag SNP for NAT2 acetylation status (P = 4 × 10⁻¹¹), and found interactions with smoking in both regions. Our findings on common variants associated with bladder cancer risk should provide new insights into the mechanisms of carcinogenesis.

Variant ABO blood group alleles, secretor status, and risk of pancreatic cancer: results from the pancreatic cancer cohort consortium

BACKGROUND

Subjects with non-O ABO blood group alleles have increased risk of pancreatic cancer. Glycosyltransferase activity is greater for the A(1) versus A(2) variant, whereas O01 and O02 variants are nonfunctioning. We hypothesized: 1) A(1) allele would confer greater risk than A(2) allele, 2) protective effect of the O allele would be equivalent for O01 and O02 variants, 3) secretor phenotype would modify the association with risk.

METHODS

We determined ABO variants and secretor phenotype from single nucleotide polymorphisms in ABO and FUT2 genes in 1,533 cases and 1,582 controls from 12 prospective cohort studies. Adjusted odds ratios (OR) for pancreatic cancer were calculated using logistic regression.

RESULTS

An increased risk was observed in participants with A(1) but not A(2) alleles. Compared with subjects with genotype O/O, genotypes A(2)/O, A(2)/A(1), A(1)/O, and A(1)/A(1) had ORs of 0.96 (95% CI, 0.72-1.26), 1.46 (95% CI, 0.98-2.17), 1.48 (95% CI, 1.23-1.78), and 1.71 (95% CI, 1.18-2.47). Risk was similar for O01 and O02 variant O alleles. Compared with O01/O01, the ORs for each additional allele of O02, A(1), and A(2) were 1.00 (95% CI, 0.87-1.14), 1.38 (95% CI, 1.20-1.58), and 0.96 (95% CI, 0.77-1.20); P, O01 versus O02 = 0.94, A(1) versus A(2) = 0.004. Secretor phenotype was not an effect modifier (P-interaction = 0.63).

CONCLUSIONS

Among participants in a large prospective cohort consortium, ABO allele subtypes corresponding to increased glycosyltransferase activity were associated with increased pancreatic cancer risk.

IMPACT

These data support the hypothesis that ABO glycosyltransferase activity influences pancreatic cancer risk rather than actions of other nearby genes on chromosome 9q34.

Family history of cancer and risk of pancreatic cancer: a pooled analysis from the Pancreatic Cancer Cohort Consortium (PanScan)

A family history of pancreatic cancer has consistently been associated with increased risk of pancreatic cancer. However, uncertainty remains about the strength of this association. Results from previous studies suggest a family history of select cancers (i.e., ovarian, breast and colorectal) could also be associated, although not as strongly, with increased risk of pancreatic cancer. We examined the association between a family history of 5 types of cancer (pancreas, prostate, ovarian, breast and colorectal) and risk of pancreatic cancer using data from a collaborative nested case-control study conducted by the Pancreatic Cancer Cohort Consortium. Cases and controls were from cohort studies from the United States, Europe and China, and a case-control study from the Mayo Clinic. Analyses of family history of pancreatic cancer included 1,183 cases and 1,205 controls. A family history of pancreatic cancer in a parent, sibling or child was associated with increased risk of pancreatic cancer [multivariate-adjusted odds ratios (ORs) = 1.76, 95% confidence interval (CI) = 1.19-2.61]. A family history of prostate cancer was also associated with increased risk (OR = 1.45, 95% CI = 1.12-1.89). There were no statistically significant associations with a family history of ovarian cancer (OR = 0.82, 95% CI = 0.52-1.31), breast cancer (OR = 1.21, 95% CI = 0.97-1.51) or colorectal cancer (OR = 1.17, 95% CI = 0.93-1.47). Our results confirm a moderate sized association between a family history of pancreatic cancer and risk of pancreatic cancer and also provide evidence for an association with a family history of prostate cancer worth further study.

A shared susceptibility locus in PLCE1 at 10q23 for gastric adenocarcinoma and esophageal squamous cell carcinoma

We conducted a genome-wide association study of gastric cancer (GC) and esophageal squamous cell carcinoma (ESCC) in ethnic Chinese subjects in which we genotyped 551,152 single nucleotide polymorphisms (SNPs). We report a combined analysis of 2,240 GC cases, 2,115 ESCC cases, and 3,302 controls drawn from five studies. In logistic regression models adjusted for age, sex, and study, multiple variants at 10q23 had genome-wide significance for GC and ESCC independently. A notable signal was rs2274223, a nonsynonymous SNP located in PLCE1, for GC (P=8.40×10⁻⁹; per allele odds ratio (OR) = 1.31) and ESCC (P=3.85×10⁻⁹; OR = 1.34). The association with GC differed by anatomic subsite. For tumors located in the cardia the association was stronger (P=4.19 × 10⁻¹⁵; OR= 1.57) and for those located in the noncardia stomach it was absent (P=0.44; OR=1.05). Our findings at 10q23 could provide insight into the high incidence rates of both cancers in China.

Anthropometric measures, body mass index, and pancreatic cancer: a pooled analysis from the Pancreatic Cancer Cohort Consortium (PanScan)

BACKGROUND

Obesity has been proposed as a risk factor for pancreatic cancer.

METHODS

Pooled data were analyzed from the National Cancer Institute Pancreatic Cancer Cohort Consortium (PanScan) to study the association between prediagnostic anthropometric measures and risk of pancreatic cancer. PanScan applied a nested case-control study design and included 2170 cases and 2209 control subjects. Odds ratios (ORs) and 95% confidence intervals (CIs) were estimated using unconditional logistic regression for cohort-specific quartiles of body mass index (BMI [calculated as weight in kilograms divided by height in meters squared]), weight, height, waist circumference, and waist to hip ratio as well as conventional BMI categories (underweight, <18.5; normal weight, 18.5-24.9; overweight, 25.0-29.9; obese, 30.0-34.9; and severely obese, > or = 35.0). Models were adjusted for potential confounders.

RESULTS

In all of the participants, a positive association between increasing BMI and risk of pancreatic cancer was observed (adjusted OR for the highest vs lowest BMI quartile, 1.33; 95% CI, 1.12-1.58; P(trend) < .001). In men, the adjusted OR for pancreatic cancer for the highest vs lowest quartile of BMI was 1.33 (95% CI, 1.04-1.69; P(trend) < .03), and in women it was 1.34 (95% CI, 1.05-1.70; P(trend) = .01). Increased waist to hip ratio was associated with increased risk of pancreatic cancer in women (adjusted OR for the highest vs lowest quartile, 1.87; 95% CI, 1.31-2.69; P(trend) = .003) but less so in men.

CONCLUSIONS

These findings provide strong support for a positive association between BMI and pancreatic cancer risk. In addition, centralized fat distribution may increase pancreatic cancer risk, especially in women.

Genome-wide association study of circulating vitamin D levels

The primary circulating form of vitamin D, 25-hydroxy-vitamin D [25(OH)D], is associated with multiple medical outcomes, including rickets, osteoporosis, multiple sclerosis and cancer. In a genome-wide association study (GWAS) of 4501 persons of European ancestry drawn from five cohorts, we identified single-nucleotide polymorphisms (SNPs) in the gene encoding group-specific component (vitamin D binding) protein, GC, on chromosome 4q12-13 that were associated with 25(OH)D concentrations: rs2282679 (P = 2.0 × 10⁻³⁰), in linkage disequilibrium (LD) with rs7041, a non-synonymous SNP (D432E; P = 4.1 × 10⁻²²) and rs1155563 (P = 3.8 × 10⁻²⁵). Suggestive signals for association with 25(OH)D were also observed for SNPs in or near three other genes involved in vitamin D synthesis or activation: rs3829251 on chromosome 11q13.4 in NADSYN1 [encoding nicotinamide adenine dinucleotide (NAD) synthetase; P = 8.8 × 10⁻⁷], which was in high LD with rs1790349, located in DHCR7, the gene encoding 7-dehydrocholesterol reductase that synthesizes cholesterol from 7-dehydrocholesterol; rs6599638 in the region harboring the open-reading frame 88 (C10orf88) on chromosome 10q26.13 in the vicinity of ACADSB (acyl-Coenzyme A dehydrogenase), involved in cholesterol and vitamin D synthesis (P = 3.3 × 10⁻⁷); and rs2060793 on chromosome 11p15.2 in CYP2R1 (cytochrome P450, family 2, subfamily R, polypeptide 1, encoding a key C-25 hydroxylase that converts vitamin D₃ to an active vitamin D receptor ligand; P = 1.4 × 10⁻⁵). We genotyped SNPs in these four regions in 2221 additional samples and confirmed strong genome-wide significant associations with 25(OH)D through meta-analysis with the GWAS data for GC (P = 1.8 × 10⁻⁴⁹), NADSYN1/DHCR7 (P = 3.4 × 10⁻⁹) and CYP2R1 (P = 2.9 × 10⁻¹⁷), but not C10orf88 (P = 2.4 × 10⁻⁵).

Refining the prostate cancer genetic association within the JAZF1 gene on chromosome 7p15.2

BACKGROUND

Genome-wide association studies have identified multiple genetic variants associated with susceptibility to prostate cancer (PrCa). In the two-stage Cancer Genetic Markers of Susceptibility prostate cancer scan, a single-nucleotide polymorphism (SNP), rs10486567, located within intron 2 of JAZF1 gene on chromosome 7p15.2, showed a promising association with PrCa overall (P=2.14x10(-6)), with a suggestion of stronger association with aggressive disease (P=1.2x10(-7)).

METHODS

In the third stage of genome-wide association studies, we genotyped 106 JAZF1 SNPs in 10,286 PrCa cases and 9,135 controls of European ancestry.

RESULTS

The strongest association was observed with the initial marker rs10486567, which now achieves genome-wide significance [P=7.79x10(-11); ORHET, 1.19 (95% confidence interval, 1.12-1.27); ORHOM, 1.37 (95% confidence interval, 1.20-1.56)]. We did not confirm a previous suggestion of a stronger association of rs10486567 with aggressive disease (P=1.60x10(-4) for aggressive cancer, n=4,597; P=3.25x10(-8) for nonaggressive cancer, n=4,514). Based on a multilocus model with adjustment for rs10486567, no additional independent signals were observed at chromosome 7p15.2. There was no association between PrCa risk and SNPs in JAZF1 previously associated with height (rs849140; P=0.587), body stature (rs849141, tagged by rs849136; P=0.171), and risk of type 2 diabetes and systemic lupus erythematosus (rs864745, tagged by rs849142; P=0.657).

CONCLUSION

rs10486567 remains the most significant marker for PrCa risk within JAZF1 in individuals of European ancestry.

IMPACT

Future studies should identify all variants in high linkage disequilibrium with rs10486567 and evaluate their functional significance for PrCa.

Abstract LB-404: Genome-wide association study of circulating estradiol, testosterone, and sex hormone-binding globulin levels in postmenopausal women

Factors that influence endogenous and exogenous exposure to steroid hormones are associated with increased cancer risk of hormonally regulated tissues. Epidemiologic studies indicate that high circulating estrogens and androgens are strongly associated with increased postmenopausal breast cancer risk. Conversely, higher levels of sex hormone-binding globulin (SHBG), which binds to estrogens and androgens with high affinity, may be associated with reduced breast cancer risk. The regulation of plasma levels of sex steroid hormones is complex and not fully understood. Therefore, genetic variants not within candidate gene regions may be associated with sex hormone levels.

To identify such variants, we used existing data on 528,173 SNPs genotyped on the Illumina HumanHap500 array as part of the NCI Cancer Genetic Markers of Susceptibility Project to conduct genome-wide association analyses among the subset of Nurses’ Health Study (NHS) postmenopausal women (N=1377) with measured levels of estradiol (E2), testosterone (T), and SHBG. Analyses were stratified by postmenopausal hormone use at blood draw. Generalized linear models of the log transformed hormone levels were adjusted for age at blood draw and laboratory batch. We used weighted Z scores to generate p-values for the combined effect of the two groups. Independent single nucleotide polymorphisms (SNPs) with the smallest p-values for E2 (N=48), T (N=35), and SHBG (N=45) were genotyped in a different set of women with measured hormone levels from the NHS (N=619). An additional 359 women from CGEMS who only had SHBG data available were added to the replication set.

No SNP association reached the GWAS significance threshold of 5 × 10-08. The SNP most strongly associated with SHBG levels was rs2955617 (joint Ptrend = 2.3 × 10-07), which is located on chromosome 17, ∼2 kb downstream of the SHBG gene. The subsequent 4 SNPs with the smallest joint Ptrend values (rs1010889 = 1.3 × 10-06, rs10822129 = 3.6 × 10-06, rs10509186 = 9.2 × 10-06, rs7923609 = 1.6 × 10-05) identify a locus on chromosome 10 containing the NRBF2 and JMJD1C genes, both of which have some evidence of modulating nuclear receptor activity. SNPs most strongly associated with E2 levels were located within potassium channel genes: KCNMA1 on chromosome 10 (joint Ptrend for rs10509385 = 2.4 × 10-06) and KCTD1 on chromosome 18 (joint Ptrend for rs4480883 = 9.9 × 10-06). For T levels, the most strongly associated SNPs were located on chromosome 7 within the MAGI2 gene (joint Ptrend for rs7787781 = 6.0 × 10-06) and chromosome 1 near the WNT2B/ST7L locus (joint Ptrend for rs11102457 = 9.6 × 10-06).

These results provide some evidence for the association of genetic variation in the vicinity of a candidate gene as well as novel loci with steroid hormone levels. Additional replication and meta-analysis with other genome-wide association studies are needed to verify these findings.

Citation Format: {Authors}. {Abstract title} [abstract]. In: Proceedings of the 101st Annual Meeting of the American Association for Cancer Research; 2010 Apr 17-21; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2010;70(8 Suppl):Abstract nr LB-404.