Publications by authors named "Jonathan P Tyrer"

70 Publications

Identification of a Locus Near Associated With Progression-Free Survival in Ovarian Cancer.

Cancer Epidemiol Biomarkers Prev 2021 Jun 23. Epub 2021 Jun 23.

Gynecologic Oncology Center, Kiel, Germany.

Background: Many loci have been found to be associated with risk of epithelial ovarian cancer (EOC). However, although there is considerable variation in progression-free survival (PFS), no loci have been found to be associated with outcome at genome-wide levels of significance.

Methods: We carried out a genome-wide association study (GWAS) of PFS in 2,352 women with EOC who had undergone cytoreductive surgery and standard carboplatin/paclitaxel chemotherapy.

Results: We found seven SNPs at 12q24.33 associated with PFS ( < 5 × 10), the top SNP being rs10794418 (HR = 1.24; 95% CI, 1.15-1.34; = 1.47 × 10). High expression of a nearby gene, , is associated with shorter PFS in EOC, and with poor prognosis in other cancers. SNP rs10794418 is also associated with expression of in ovarian tumors, with the allele associated with shorter PFS being associated with higher expression, and chromatin interactions were detected between the promoter and associated SNPs in serous and endometrioid EOC cell lines. ULK1 knockout ovarian cancer cell lines showed significantly increased sensitivity to carboplatin .

Conclusions: The locus at 12q24.33 represents one of the first genome-wide significant loci for survival for any cancer. is a plausible candidate for the target of this association.

Impact: This finding provides insight into genetic markers associated with EOC outcome and potential treatment options..
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http://dx.doi.org/10.1158/1055-9965.EPI-20-1817DOI Listing
June 2021

A case-only study to identify genetic modifiers of breast cancer risk for BRCA1/BRCA2 mutation carriers.

Nat Commun 2021 02 17;12(1):1078. Epub 2021 Feb 17.

Copenhagen General Population Study, Herlev and Gentofte Hospital Copenhagen University Hospital, Herlev, Denmark.

Breast cancer (BC) risk for BRCA1 and BRCA2 mutation carriers varies by genetic and familial factors. About 50 common variants have been shown to modify BC risk for mutation carriers. All but three, were identified in general population studies. Other mutation carrier-specific susceptibility variants may exist but studies of mutation carriers have so far been underpowered. We conduct a novel case-only genome-wide association study comparing genotype frequencies between 60,212 general population BC cases and 13,007 cases with BRCA1 or BRCA2 mutations. We identify robust novel associations for 2 variants with BC for BRCA1 and 3 for BRCA2 mutation carriers, P < 10, at 5 loci, which are not associated with risk in the general population. They include rs60882887 at 11p11.2 where MADD, SP11 and EIF1, genes previously implicated in BC biology, are predicted as potential targets. These findings will contribute towards customising BC polygenic risk scores for BRCA1 and BRCA2 mutation carriers.
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http://dx.doi.org/10.1038/s41467-020-20496-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7890067PMC
February 2021

Mendelian randomization analyses suggest a role for cholesterol in the development of endometrial cancer.

Int J Cancer 2021 01 7;148(2):307-319. Epub 2020 Aug 7.

Behavioral and Epidemiology Research Group, American Cancer Society, Atlanta, Georgia, USA.

Blood lipids have been associated with the development of a range of cancers, including breast, lung and colorectal cancer. For endometrial cancer, observational studies have reported inconsistent associations between blood lipids and cancer risk. To reduce biases from unmeasured confounding, we performed a bidirectional, two-sample Mendelian randomization analysis to investigate the relationship between levels of three blood lipids (low-density lipoprotein [LDL] and high-density lipoprotein [HDL] cholesterol, and triglycerides) and endometrial cancer risk. Genetic variants associated with each of these blood lipid levels (P < 5 × 10 ) were identified as instrumental variables, and assessed using genome-wide association study data from the Endometrial Cancer Association Consortium (12 906 cases and 108 979 controls) and the Global Lipids Genetic Consortium (n = 188 578). Mendelian randomization analyses found genetically raised LDL cholesterol levels to be associated with lower risks of endometrial cancer of all histologies combined, and of endometrioid and non-endometrioid subtypes. Conversely, higher genetically predicted HDL cholesterol levels were associated with increased risk of non-endometrioid endometrial cancer. After accounting for the potential confounding role of obesity (as measured by genetic variants associated with body mass index), the association between genetically predicted increased LDL cholesterol levels and lower endometrial cancer risk remained significant, especially for non-endometrioid endometrial cancer. There was no evidence to support a role for triglycerides in endometrial cancer development. Our study supports a role for LDL and HDL cholesterol in the development of non-endometrioid endometrial cancer. Further studies are required to understand the mechanisms underlying these findings.
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http://dx.doi.org/10.1002/ijc.33206DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7757859PMC
January 2021

European polygenic risk score for prediction of breast cancer shows similar performance in Asian women.

Nat Commun 2020 07 31;11(1):3833. Epub 2020 Jul 31.

Department of Surgery, Yong Loo Lin School of Medicine, National University of Singapore, 117597, Singapore, Singapore.

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.
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http://dx.doi.org/10.1038/s41467-020-17680-wDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7395776PMC
July 2020

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.

Nat Genet 2020 01 7;52(1):56-73. Epub 2020 Jan 7.

Unit of Medical Genetics, Department of Medical Oncology and Hematology, Fondazione IRCCS Istituto Nazionale dei Tumori di Milano, Milan, Italy.

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
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http://dx.doi.org/10.1038/s41588-019-0537-1DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6974400PMC
January 2020

Shared heritability and functional enrichment across six solid cancers.

Nat Commun 2019 01 25;10(1):431. Epub 2019 Jan 25.

Human Cancer Genetics Programme, Spanish National Cancer Research Centre (CNIO), Calle de Melchor Fernández Almagro, 3, 28029, Madrid, Spain.

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (r = 0.57, p = 4.6 × 10), breast and ovarian cancer (r = 0.24, p = 7 × 10), breast and lung cancer (r = 0.18, p =1.5 × 10) and breast and colorectal cancer (r = 0.15, p = 1.1 × 10). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.
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http://dx.doi.org/10.1038/s41467-018-08054-4DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6347624PMC
January 2019

Genetic Data from Nearly 63,000 Women of European Descent Predicts DNA Methylation Biomarkers and Epithelial Ovarian Cancer Risk.

Cancer Res 2019 02 17;79(3):505-517. Epub 2018 Dec 17.

The Center for Bioinformatics and Functional Genomics at the Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.

DNA methylation is instrumental for gene regulation. Global changes in the epigenetic landscape have been recognized as a hallmark of cancer. However, the role of DNA methylation in epithelial ovarian cancer (EOC) remains unclear. In this study, high-density genetic and DNA methylation data in white blood cells from the Framingham Heart Study ( = 1,595) were used to build genetic models to predict DNA methylation levels. These prediction models were then applied to the summary statistics of a genome-wide association study (GWAS) of ovarian cancer including 22,406 EOC cases and 40,941 controls to investigate genetically predicted DNA methylation levels in association with EOC risk. Among 62,938 CpG sites investigated, genetically predicted methylation levels at 89 CpG were significantly associated with EOC risk at a Bonferroni-corrected threshold of < 7.94 × 10. Of them, 87 were located at GWAS-identified EOC susceptibility regions and two resided in a genomic region not previously reported to be associated with EOC risk. Integrative analyses of genetic, methylation, and gene expression data identified consistent directions of associations across 12 CpG, five genes, and EOC risk, suggesting that methylation at these 12 CpG may influence EOC risk by regulating expression of these five genes, namely , and . We identified novel DNA methylation markers associated with EOC risk and propose that methylation at multiple CpG may affect EOC risk via regulation of gene expression. SIGNIFICANCE: Identification of novel DNA methylation markers associated with EOC risk suggests that methylation at multiple CpG may affect EOC risk through regulation of gene expression.
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http://dx.doi.org/10.1158/0008-5472.CAN-18-2726DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359948PMC
February 2019

Polygenic Risk Scores for Prediction of Breast Cancer and Breast Cancer Subtypes.

Am J Hum Genet 2019 01 13;104(1):21-34. Epub 2018 Dec 13.

Department of Oncology, Helsinki University Hospital, University of Helsinki, Helsinki 00290, Finland; Department of Oncology, Örebro University Hospital, Örebro 70185, Sweden.

Stratification of women according to their risk of breast cancer based on polygenic risk scores (PRSs) could improve screening and prevention strategies. Our aim was to develop PRSs, optimized for prediction of estrogen receptor (ER)-specific disease, from the largest available genome-wide association dataset and to empirically validate the PRSs in prospective studies. The development dataset comprised 94,075 case subjects and 75,017 control subjects of European ancestry from 69 studies, divided into training and validation sets. Samples were genotyped using genome-wide arrays, and single-nucleotide polymorphisms (SNPs) were selected by stepwise regression or lasso penalized regression. The best performing PRSs were validated in an independent test set comprising 11,428 case subjects and 18,323 control subjects from 10 prospective studies and 190,040 women from UK Biobank (3,215 incident breast cancers). For the best PRSs (313 SNPs), the odds ratio for overall disease per 1 standard deviation in ten prospective studies was 1.61 (95%CI: 1.57-1.65) with area under receiver-operator curve (AUC) = 0.630 (95%CI: 0.628-0.651). The lifetime risk of overall breast cancer in the top centile of the PRSs was 32.6%. Compared with women in the middle quintile, those in the highest 1% of risk had 4.37- and 2.78-fold risks, and those in the lowest 1% of risk had 0.16- and 0.27-fold risks, of developing ER-positive and ER-negative disease, respectively. Goodness-of-fit tests indicated that this PRS was well calibrated and predicts disease risk accurately in the tails of the distribution. This PRS is a powerful and reliable predictor of breast cancer risk that may improve breast cancer prevention programs.
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http://dx.doi.org/10.1016/j.ajhg.2018.11.002DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6323553PMC
January 2019

A comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants.

Int J Cancer 2019 05 20;144(9):2192-2205. Epub 2019 Jan 20.

Genome Sciences Centre, BC Cancer Agency, Vancouver, BC, Canada.

As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.
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http://dx.doi.org/10.1002/ijc.32029DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6399057PMC
May 2019

Functional Analysis and Fine Mapping of the 9p22.2 Ovarian Cancer Susceptibility Locus.

Cancer Res 2019 02 28;79(3):467-481. Epub 2018 Nov 28.

Women's Cancer Program at the Samuel Oschin Comprehensive, Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, California.

Genome-wide association studies have identified 40 ovarian cancer risk loci. However, the mechanisms underlying these associations remain elusive. In this study, we conducted a two-pronged approach to identify candidate causal SNPs and assess underlying biological mechanisms at chromosome 9p22.2, the first and most statistically significant associated locus for ovarian cancer susceptibility. Three transcriptional regulatory elements with allele-specific effects and a scaffold/matrix attachment region were characterized and, through physical DNA interactions, was established as the most likely target gene. We determined the consensus binding sequence for BNC2 , verified its enrichment in BNC2 ChIP-seq regions, and validated a set of its downstream target genes. Fine-mapping by dense regional genotyping in over 15,000 ovarian cancer cases and 30,000 controls identified SNPs in the scaffold/matrix attachment region as among the most likely causal variants. This study reveals a comprehensive regulatory landscape at 9p22.2 and proposes a likely mechanism of susceptibility to ovarian cancer. SIGNIFICANCE: Mapping the 9p22.2 ovarian cancer risk locus identifies as an ovarian cancer risk gene..
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http://dx.doi.org/10.1158/0008-5472.CAN-17-3864DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6359979PMC
February 2019

rs495139 in the TYMS-ENOSF1 Region and Risk of Ovarian Carcinoma of Mucinous Histology.

Int J Mol Sci 2018 Aug 21;19(9). Epub 2018 Aug 21.

Department of Gynecology, Jena University Hospital-Friedrich Schiller University, Jena 07743, Germany.

Thymidylate synthase (TYMS) is a crucial enzyme for DNA synthesis. TYMS expression is regulated by its antisense mRNA, ENOSF1. Disrupted regulation may promote uncontrolled DNA synthesis and tumor growth. We sought to replicate our previously reported association between rs495139 in the 3' gene region and increased risk of mucinous ovarian carcinoma (MOC) in an independent sample. Genotypes from 24,351 controls to 15,000 women with invasive OC, including 665 MOC, were available. We estimated per-allele odds ratios (OR) and 95% confidence intervals (CI) using unconditional logistic regression, and meta-analysis when combining these data with our previous report. The association between rs495139 and MOC was not significant in the independent sample (OR = 1.09; 95% CI = 0.97⁻1.22; = 0.15; N = 665 cases). Meta-analysis suggested a weak association (OR = 1.13; 95% CI = 1.03⁻1.24; = 0.01; N = 1019 cases). No significant association with risk of other OC histologic types was observed ( = 0.05 for tumor heterogeneity). In expression quantitative trait locus (eQTL) analysis, the rs495139 allele was positively associated with ENOSF1 mRNA expression in normal tissues of the gastrointestinal system, particularly esophageal mucosa ( = 0.51, = 1.7 × 10), and nonsignificantly in five MOC tumors. The association results, along with inconclusive tumor eQTL findings, suggest that a true effect of rs495139 might be small.
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http://dx.doi.org/10.3390/ijms19092473DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6163881PMC
August 2018

Identification of nine new susceptibility loci for endometrial cancer.

Nat Commun 2018 08 9;9(1):3166. Epub 2018 Aug 9.

Department of Obstetrics and Gynecology, University Hospitals KU Leuven, University of Leuven, Division of Gynecologic Oncology, Leuven, 3000, Belgium.

Endometrial cancer is the most commonly diagnosed cancer of the female reproductive tract in developed countries. Through genome-wide association studies (GWAS), we have previously identified eight risk loci for endometrial cancer. Here, we present an expanded meta-analysis of 12,906 endometrial cancer cases and 108,979 controls (including new genotype data for 5624 cases) and identify nine novel genome-wide significant loci, including a locus on 12q24.12 previously identified by meta-GWAS of endometrial and colorectal cancer. At five loci, expression quantitative trait locus (eQTL) analyses identify candidate causal genes; risk alleles at two of these loci associate with decreased expression of genes, which encode negative regulators of oncogenic signal transduction proteins (SH2B3 (12q24.12) and NF1 (17q11.2)). In summary, this study has doubled the number of known endometrial cancer risk loci and revealed candidate causal genes for future study.
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http://dx.doi.org/10.1038/s41467-018-05427-7DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6085317PMC
August 2018

Variants in genes encoding small GTPases and association with epithelial ovarian cancer susceptibility.

PLoS One 2018 6;13(7):e0197561. Epub 2018 Jul 6.

Gynaecology Research Unit, Hannover Medical School, Hannover, Germany.

Epithelial ovarian cancer (EOC) is the fifth leading cause of cancer mortality in American women. Normal ovarian physiology is intricately connected to small GTP binding proteins of the Ras superfamily (Ras, Rho, Rab, Arf, and Ran) which govern processes such as signal transduction, cell proliferation, cell motility, and vesicle transport. We hypothesized that common germline variation in genes encoding small GTPases is associated with EOC risk. We investigated 322 variants in 88 small GTPase genes in germline DNA of 18,736 EOC patients and 26,138 controls of European ancestry using a custom genotype array and logistic regression fitting log-additive models. Functional annotation was used to identify biofeatures and expression quantitative trait loci that intersect with risk variants. One variant, ARHGEF10L (Rho guanine nucleotide exchange factor 10 like) rs2256787, was associated with increased endometrioid EOC risk (OR = 1.33, p = 4.46 x 10-6). Other variants of interest included another in ARHGEF10L, rs10788679, which was associated with invasive serous EOC risk (OR = 1.07, p = 0.00026) and two variants in AKAP6 (A-kinase anchoring protein 6) which were associated with risk of invasive EOC (rs1955513, OR = 0.90, p = 0.00033; rs927062, OR = 0.94, p = 0.00059). Functional annotation revealed that the two ARHGEF10L variants were located in super-enhancer regions and that AKAP6 rs927062 was associated with expression of GTPase gene ARHGAP5 (Rho GTPase activating protein 5). Inherited variants in ARHGEF10L and AKAP6, with potential transcriptional regulatory function and association with EOC risk, warrant investigation in independent EOC study populations.
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http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0197561PLOS
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6034790PMC
December 2018

Genetic overlap between endometriosis and endometrial cancer: evidence from cross-disease genetic correlation and GWAS meta-analyses.

Cancer Med 2018 05 2;7(5):1978-1987. Epub 2018 Apr 2.

Department of Obstetrics and Gynecology, Division of Gynecologic Oncology, University Hospitals KU Leuven, University of Leuven, Leuven, Belgium.

Epidemiological, biological, and molecular data suggest links between endometriosis and endometrial cancer, with recent epidemiological studies providing evidence for an association between a previous diagnosis of endometriosis and risk of endometrial cancer. We used genetic data as an alternative approach to investigate shared biological etiology of these two diseases. Genetic correlation analysis of summary level statistics from genomewide association studies (GWAS) using LD Score regression revealed moderate but significant genetic correlation (r = 0.23, P = 9.3 × 10 ), and SNP effect concordance analysis provided evidence for significant SNP pleiotropy (P = 6.0 × 10 ) and concordance in effect direction (P = 2.0 × 10 ) between the two diseases. Cross-disease GWAS meta-analysis highlighted 13 distinct loci associated at P ≤ 10 with both endometriosis and endometrial cancer, with one locus (SNP rs2475335) located within PTPRD associated at a genomewide significant level (P = 4.9 × 10 , OR = 1.11, 95% CI = 1.07-1.15). PTPRD acts in the STAT3 pathway, which has been implicated in both endometriosis and endometrial cancer. This study demonstrates the value of cross-disease genetic analysis to support epidemiological observations and to identify biological pathways of relevance to multiple diseases.
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http://dx.doi.org/10.1002/cam4.1445DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5943470PMC
May 2018

Adult height is associated with increased risk of ovarian cancer: a Mendelian randomisation study.

Br J Cancer 2018 04 20;118(8):1123-1129. Epub 2018 Mar 20.

Radiation Oncology Research Unit, Hannover Medical School, Carl-Neuberg-Str. 1, D-30625, Hannover, Germany.

Background: Observational studies suggest greater height is associated with increased ovarian cancer risk, but cannot exclude bias and/or confounding as explanations for this. Mendelian randomisation (MR) can provide evidence which may be less prone to bias.

Methods: We pooled data from 39 Ovarian Cancer Association Consortium studies (16,395 cases; 23,003 controls). We applied two-stage predictor-substitution MR, using a weighted genetic risk score combining 609 single-nucleotide polymorphisms. Study-specific odds ratios (OR) and 95% confidence intervals (CI) for the association between genetically predicted height and risk were pooled using random-effects meta-analysis.

Results: Greater genetically predicted height was associated with increased ovarian cancer risk overall (pooled-OR (pOR) = 1.06; 95% CI: 1.01-1.11 per 5 cm increase in height), and separately for invasive (pOR = 1.06; 95% CI: 1.01-1.11) and borderline (pOR = 1.15; 95% CI: 1.02-1.29) tumours.

Conclusions: Women with a genetic propensity to being taller have increased risk of ovarian cancer. This suggests genes influencing height are involved in pathways promoting ovarian carcinogenesis.
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http://dx.doi.org/10.1038/s41416-018-0011-3DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5931085PMC
April 2018

Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 05;50(5):766-767

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.
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http://dx.doi.org/10.1038/s41588-018-0082-3DOI Listing
May 2018

Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Nat Genet 2018 01 22;50(1):26-41. Epub 2017 Dec 22.

Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany.

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.
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http://dx.doi.org/10.1038/s41588-017-0011-xDOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5945951PMC
January 2018

Analyses of germline variants associated with ovarian cancer survival identify functional candidates at the 1q22 and 19p12 outcome loci.

Oncotarget 2017 Sep 15;8(39):64670-64684. Epub 2017 Jun 15.

Department of Health Sciences Research, Mayo Clinic, Rochester, MN, USA.

We previously identified associations with ovarian cancer outcome at five genetic loci. To identify putatively causal genetic variants and target genes, we prioritized two ovarian outcome loci (1q22 and 19p12) for further study. Bioinformatic and functional genetic analyses indicated that and are targets of candidate outcome variants at 1q22 and 19p12, respectively. At 19p12, the chromatin interaction of a putative regulatory element with the promoter region correlated with candidate outcome variants. At 1q22, putative regulatory elements enhanced promoter activity and haplotypes containing candidate outcome variants modulated these effects. In a public dataset, and expression were both associated with ovarian cancer progression-free or overall survival time. In an extended set of 6,162 epithelial ovarian cancer patients, we found that functional candidates at the 1q22 and 19p12 loci, as well as other regional variants, were nominally associated with patient outcome; however, no associations reached our threshold for statistical significance (<1×10). Larger patient numbers will be needed to convincingly identify any true associations at these loci.
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http://dx.doi.org/10.18632/oncotarget.18501DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5630285PMC
September 2017

Germline whole exome sequencing and large-scale replication identifies as a likely high grade serous ovarian cancer susceptibility gene.

Oncotarget 2017 Aug 3;8(31):50930-50940. Epub 2017 Mar 3.

Department of Health Research and Policy - Epidemiology, Stanford University School of Medicine, Stanford, California, USA.

We analyzed whole exome sequencing data in germline DNA from 412 high grade serous ovarian cancer (HGSOC) cases from The Cancer Genome Atlas Project and identified 5,517 genes harboring a predicted deleterious germline coding mutation in at least one HGSOC case. Gene-set enrichment analysis showed enrichment for genes involved in DNA repair (p = 1.8×10). Twelve DNA repair genes - and - were prioritized for targeted sequencing in up to 3,107 HGSOC cases, 1,491 cases of other epithelial ovarian cancer (EOC) subtypes and 3,368 unaffected controls of European origin. We estimated mutation prevalence for each gene and tested for associations with disease risk. Mutations were identified in both cases and controls in all genes except , where we found no evidence of mutations in controls. In we observed a higher mutation frequency in HGSOC cases compared to controls (29/3,107 cases, 0.96 percent; 13/3,368 controls, 0.38 percent; P=0.008) with little evidence for association with other subtypes (6/1,491, 0.40 percent; P=0.82). The relative risk of HGSOC associated with deleterious mutations was estimated to be 2.5 (95% CI 1.3 - 5.0; P=0.006). In summary, whole exome sequencing of EOC cases with large-scale replication in case-control studies has identified as a likely novel susceptibility gene for HGSOC, with mutations associated with a moderate increase in risk. These data may have clinical implications for risk prediction and prevention approaches for high-grade serous ovarian cancer in the future and a significant impact on reducing disease mortality.
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http://dx.doi.org/10.18632/oncotarget.15871DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5584218PMC
August 2017

Robust Tests for Additive Gene-Environment Interaction in Case-Control Studies Using Gene-Environment Independence.

Am J Epidemiol 2018 02;187(2):366-377

Department of Obstetrics and Gynecology, Duke University Medical Center, Durham, North Carolina.

There have been recent proposals advocating the use of additive gene-environment interaction instead of the widely used multiplicative scale, as a more relevant public health measure. Using gene-environment independence enhances statistical power for testing multiplicative interaction in case-control studies. However, under departure from this assumption, substantial bias in the estimates and inflated type I error in the corresponding tests can occur. In this paper, we extend the empirical Bayes (EB) approach previously developed for multiplicative interaction, which trades off between bias and efficiency in a data-adaptive way, to the additive scale. An EB estimator of the relative excess risk due to interaction is derived, and the corresponding Wald test is proposed with a general regression setting under a retrospective likelihood framework. We study the impact of gene-environment association on the resultant test with case-control data. Our simulation studies suggest that the EB approach uses the gene-environment independence assumption in a data-adaptive way and provides a gain in power compared with the standard logistic regression analysis and better control of type I error when compared with the analysis assuming gene-environment independence. We illustrate the methods with data from the Ovarian Cancer Association Consortium.
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http://dx.doi.org/10.1093/aje/kwx243DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5860584PMC
February 2018

Prediction of Breast and Prostate Cancer Risks in Male BRCA1 and BRCA2 Mutation Carriers Using Polygenic Risk Scores.

J Clin Oncol 2017 Jul 27;35(20):2240-2250. Epub 2017 Apr 27.

Julie Lecarpentier, Karoline B. Kuchenbaecker, Daniel Barrowdale, Joe Dennis, Lesley McGuffog, Goska Leslie, Andrew Lee, Ali Amin Al Olama, Jonathan P. Tyrer, Debra Frost, Steve Ellis, Douglas F. Easton, and Antonis C. Antoniou, University of Cambridge; Karoline B. Kuchenbaecker, The Wellcome Trust Sanger Institute, Hinxton; Marc Tischkowitz, Addenbrooke's Treatment Centre, Addenbrooke's Hospital, Cambridge; D. Gareth Evans, Manchester University, Central Manchester University Hospitals NHS Foundation Trust, Manchester; Alex Henderson, Newcastle Upon Tyne Hospitals NHS Trust, Newcastle upon Tyne; Carole Brewer, Royal Devon and Exeter Hospital, Exeter; Diana Eccles, Southampton University Hospitals NHS Trust, Southampton; Jackie Cook, Sheffield Children's Hospital, Sheffield; Kai-ren Ong, Birmingham Women's Hospital Healthcare NHS Trust, Edgbaston, Birmingham; Lisa Walker, Churchill Hospital, Oxford; Lucy E. Side, Great Ormond Street Hospital for Children NHS Trust; Shirley Hodgson, St George's, University of London; Louise Izatt, Guy's and St Thomas' NHS Foundation Trust; Ros Eeles, The Institute of Cancer Research and Royal Marsden NHS Foundation Trust; Nick Orr, The Institute of Cancer Research, London; Mary E. Porteous, Western General Hospital, Edinburgh; Rosemarie Davidson, South Glasgow University Hospitals, Glasgow; Julian Adlard, Chapel Allerton Hospital, Leeds, United Kingdom; Valentina Silvestri, Piera Rizzolo, Anna Sara Navazio, Virginia Valentini, Veronica Zelli, and Laura Ottini, Sapienza University of Rome, Rome; Angela Toss, Veronica Medici, and Laura Cortesi, University of Modena and Reggio Emilia, Modena; Ines Zanna and Domenico Palli, Cancer Research and Prevention Institute, Florence; Paolo Radice, Siranoush Manoukian, Bernard Peissel, and Jacopo Azzollini, Fondazione Istituto Di Ricovero e Cura a Carattere Scientifico (IRCCS) Istituto Nazionale Tumori (INT); Paolo Peterlongo, Italian Foundation for Cancer Research Institute of Molecular Oncology (IFOM), Milan; Alessandra Viel and Giulia Cini, CRO Aviano, National Cancer Institute, Aviano; Giuseppe Damante, University of Udine, Udine; Stefania Tommasi, Istituto Nazionale Tumori "Giovanni Paolo II", Bari; Elisa Alducci, Silvia Tognazzo, and Marco Montagna, Veneto Institute of Oncology IOV - IRCCS, Padua; Maria A. Caligo, University and University Hospital of Pisa, Pisa, Italy; Penny Soucy and Jacques Simard, Centre Hospitalier Universitaire de Québec Research Center and Laval University, Quebec City, Quebec; Anna Marie Mulligan and Irene L. Andrulis, University of Toronto; Gord Glendon and Irene L. Andrulis, Mount Sinai Hospital, Toronto, Ontario, Canada; Melissa Southey, Ian Campbell, Paul James, and Gillian Mitchell, University of Melbourne, Parkville, Victoria; Amanda B. Spurdle, Helene Holland, and Georgia Chenevix-Trench, QIMR Berghofer Medical Research Institute, Brisbane, Queensland; Ian Campbell, Paul James, and Gillian Mitchell, Peter MacCallum Cancer Centre, East Melbourne, New South Wales, Australia; Esther M. John, Cancer Prevention Institute of California, Fremont; Linda Steele, Yuan Chun Ding, Susan L. Neuhausen, and Jeffrey N. Weitzel, City of Hope, Duarte, CA; Thomas A. Conner and Saundra S. Buys, Huntsman Cancer Institute; David E. Goldgar, University of Utah School of Medicine, Salt Lake City, UT; Andrew K. Godwin, University of Kansas Medical Center, Kansas City; Priyanka Sharma, University of Kansas Medical Center, Westwood, KS; Timothy R. Rebbeck, Harvard TH Chan School of Public Health and Dana Farber Cancer Institute, Boston, MA; Joseph Vijai, Mark Robson, Anne Lincoln, Jacob Musinsky, Pragna Gaddam, and Kenneth Offit, Memorial Sloan Kettering Cancer Center, New York, NY; Jennifer T. Loud and Mark H. Greene, National Cancer Institute, Bethesda, MD; Amanda Ewart Toland and Leigha Senter, The Ohio State University, Columbus, OH; Dezheng Huo, Sarah M. Nielsen, and Olufunmilayo I. Olopade, University of Chicago Medical Center, Chicago, IL; Katherine L. Nathanson and Susan M. Domchek, University of Pennsylvania, Philadelphia; Christa Lorenchick and Rachel C. Jankowitz, University of Pittsburgh Medical Center, Pittsburgh, PA; Fergus J. Couch, Mayo Clinic, Rochester, MN; Ramunas Janavicius, State Research Institute Innovative Medicine Center, Vilnius, Lithuania; Thomas V.O. Hansen, Rigshospitalet, Copenhagen University Hospital, Copenhagen; Anders Bojesen and Henriette Roed Nielsen, Vejle Hospital, Vejle; Anne-Bine Skytte, Lone Sunde, and Uffe Birk Jensen, Aarhus University Hospital, Aarhus; Inge Sokilde Pedersen, Aalborg University Hospital, Aalborg; Lotte Krogh, Torben A. Kruse, and Mads Thomassen, Odense University Hospital, Odense, Denmark; Ana Osorio, National Cancer Research Centre and Spanish Network on Rare Diseases; Miguel de la Hoya, Vanesa Garcia-Barberan, Trinidad Caldes, and Pedro Perez Segura, Hospital Clinico San Carlos, El Instituto de Investigación Sanitaria del Hospital Clínico San Carlos, Madrid; Judith Balmaña, University Hospital, Vall d'Hebron; Sara Gutiérrez-Enríquez and Orland Diez, Vall d'Hebron Institute of Oncology; Orland Diez, University Hospital Vall d'Hebron; Alex Teulé, Jesús Del Valle, Lidia Feliubadalo, Miquel Angel Pujana, and Conxi Lazaro, Bellvitge Biomedical Research Institute, Catalan Institute of Oncology, Barcelona; Angel Izquierdo, Esther Darder, and Joan Brunet, Institut d'Investigació Biomèdica de Girona, Catalan Institute of Oncology, Girona, Spain; Florentia Fostira, National Centre for Scientific Research "Demokritos," Athens, Greece; Ute Hamann, German Cancer Research Center (DKFZ); Christian Sutter, University Hospital Heidelberg, Heidelberg; Alfons Meindl, Klinikumrechts der Isar, Technical University Munich; Nina Ditsch, Ludwig-Maximilian University, Munich; Andrea Gehrig, University Würzburg, Würzburg; Bernd Dworniczak, University of Münster, Münster; Christoph Engel, University of Leipzig; Dorothea Wand, University Hospital, Leipzig; Dieter Niederacher, University Hospital Düsseldorf, Heinrich-Heine University, Düsseldorf; Doris Steinemann, Hannover Medical School, Hannover; Eric Hahnen, Jan Hauke, Kerstin Rhiem, Barbara Wappenschmidt, and Rita K. Schmutzler, University Hospital Cologne, Cologne; Karin Kast, University Hospital Carl Gustav Carus, Technical University Dresden, Dresden; Norbert Arnold, University Hospital of Schleswig-Holstein, Christian-Albrechts University Kiel, Kiel; Shan Wang-Gohrke, University Hospital Ulm, Ulm, Germany; Christine Lasset, Francesca Damiola, and Laure Barjhoux, Centre Léon Bérard; Sylvie Mazoyer, University of Lyon, Lyon; Dominique Stoppa-Lyonnet and Muriel Belotti, Institut Curie, Paris, France; Mattias Van Heetvelde, Bruce Poppe, Kim De Leeneer, and Kathleen B.M. Claes, Ghent University, Gent, Belgium; Johanna I. Kiiski, Sofia Khan, and Heli Nevanlinna, University of Helsinki; Johanna I. Kiiski, Kristiina Aittomäki, Sofia Khan, and Heli Nevanlinna, Helsinki University Hospital, Helsinki, Finland; Christi J. van Asperen, Leiden University Medical Center, Leiden, the Netherlands; Tibor Vaszko, Miklos Kasler, and Edith Olah, National Institute of Oncology, Budapest, Hungary; Adalgeir Arason, Bjarni A. Agnarsson, Oskar Th. Johannsson, and Rosa B. Barkardottir, Landspitali University Hospital and Biomedical Centre, University of Iceland, Reykjavik, Iceland; Manuel R. Teixeira and Pedro Pinto, Portuguese Oncology Institute; Manuel R. Teixeira, Porto University, Porto, Portugal; Jong Won Lee, Ulsan College of Medicine and Asan Medical Center; Min Hyuk Lee and Jihyoun Lee, Soonchunhyang University and Hospital; Sung-Won Kim and Eunyoung Kang, Daerim St Mary's Hospital; Sue Kyung Park, Seoul National University College of Medicine, Seoul; Zisun Kim, Soonchunhyang University Bucheon Hospital, Bucheon, Korea; Yen Y. Tan, Andreas Berger, and Christian F. Singer, Medical University of Vienna, Vienna, Austria; Sook-Yee Yoon and Soo-Hwang Teo, Sime Darby Medical Centre, Subang Jaya, Malaysia; and Anna von Wachenfeldt, Karolinska University Hospital, Stockholm, Sweden.

Purpose BRCA1/2 mutations increase the risk of breast and prostate cancer in men. Common genetic variants modify cancer risks for female carriers of BRCA1/2 mutations. We investigated-for the first time to our knowledge-associations of common genetic variants with breast and prostate cancer risks for male carriers of BRCA1/ 2 mutations and implications for cancer risk prediction. Materials and Methods We genotyped 1,802 male carriers of BRCA1/2 mutations from the Consortium of Investigators of Modifiers of BRCA1/2 by using the custom Illumina OncoArray. We investigated the combined effects of established breast and prostate cancer susceptibility variants on cancer risks for male carriers of BRCA1/2 mutations by constructing weighted polygenic risk scores (PRSs) using published effect estimates as weights. Results In male carriers of BRCA1/2 mutations, PRS that was based on 88 female breast cancer susceptibility variants was associated with breast cancer risk (odds ratio per standard deviation of PRS, 1.36; 95% CI, 1.19 to 1.56; P = 8.6 × 10). Similarly, PRS that was based on 103 prostate cancer susceptibility variants was associated with prostate cancer risk (odds ratio per SD of PRS, 1.56; 95% CI, 1.35 to 1.81; P = 3.2 × 10). Large differences in absolute cancer risks were observed at the extremes of the PRS distribution. For example, prostate cancer risk by age 80 years at the 5th and 95th percentiles of the PRS varies from 7% to 26% for carriers of BRCA1 mutations and from 19% to 61% for carriers of BRCA2 mutations, respectively. Conclusion PRSs may provide informative cancer risk stratification for male carriers of BRCA1/2 mutations that might enable these men and their physicians to make informed decisions on the type and timing of breast and prostate cancer risk management.
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http://dx.doi.org/10.1200/JCO.2016.69.4935DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501359PMC
July 2017

Genomic analyses identify hundreds of variants associated with age at menarche and support a role for puberty timing in cancer risk.

Nat Genet 2017 Jun 24;49(6):834-841. Epub 2017 Apr 24.

Institute of Genetics and Biophysics, CNR, Naples, Italy.

The timing of puberty is a highly polygenic childhood trait that is epidemiologically associated with various adult diseases. Using 1000 Genomes Project-imputed genotype data in up to ∼370,000 women, we identify 389 independent signals (P < 5 × 10) for age at menarche, a milestone in female pubertal development. In Icelandic data, these signals explain ∼7.4% of the population variance in age at menarche, corresponding to ∼25% of the estimated heritability. We implicate ∼250 genes via coding variation or associated expression, demonstrating significant enrichment in neural tissues. Rare variants near the imprinted genes MKRN3 and DLK1 were identified, exhibiting large effects when paternally inherited. Mendelian randomization analyses suggest causal inverse associations, independent of body mass index (BMI), between puberty timing and risks for breast and endometrial cancers in women and prostate cancer in men. In aggregate, our findings highlight the complexity of the genetic regulation of puberty timing and support causal links with cancer susceptibility.
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http://dx.doi.org/10.1038/ng.3841DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5841952PMC
June 2017

Identification of 12 new susceptibility loci for different histotypes of epithelial ovarian cancer.

Nat Genet 2017 May 27;49(5):680-691. Epub 2017 Mar 27.

N.N. Alexandrov National Cancer Centre of Belarus, Minsk, Belarus.

To identify common alleles associated with different histotypes of epithelial ovarian cancer (EOC), we pooled data from multiple genome-wide genotyping projects totaling 25,509 EOC cases and 40,941 controls. We identified nine new susceptibility loci for different EOC histotypes: six for serous EOC histotypes (3q28, 4q32.3, 8q21.11, 10q24.33, 18q11.2 and 22q12.1), two for mucinous EOC (3q22.3 and 9q31.1) and one for endometrioid EOC (5q12.3). We then performed meta-analysis on the results for high-grade serous ovarian cancer with the results from analysis of 31,448 BRCA1 and BRCA2 mutation carriers, including 3,887 mutation carriers with EOC. This identified three additional susceptibility loci at 2q13, 8q24.1 and 12q24.31. Integrated analyses of genes and regulatory biofeatures at each locus predicted candidate susceptibility genes, including OBFC1, a new candidate susceptibility gene for low-grade and borderline serous EOC.
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http://dx.doi.org/10.1038/ng.3826DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5612337PMC
May 2017

Rare and low-frequency coding variants alter human adult height.

Nature 2017 02 1;542(7640):186-190. Epub 2017 Feb 1.

Netherlands Comprehensive Cancer Organisation, Utrecht, 3501 DB, The Netherlands.

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.
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http://dx.doi.org/10.1038/nature21039DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5302847PMC
February 2017

Genetic Risk Score Mendelian Randomization Shows that Obesity Measured as Body Mass Index, but not Waist:Hip Ratio, Is Causal for Endometrial Cancer.

Cancer Epidemiol Biomarkers Prev 2016 11 22;25(11):1503-1510. Epub 2016 Aug 22.

Department of Gynaecology, Jena University Hospital, Friedrich Schiller University, Jena, Germany.

Background: The strongest known risk factor for endometrial cancer is obesity. To determine whether SNPs associated with increased body mass index (BMI) or waist-hip ratio (WHR) are associated with endometrial cancer risk, independent of measured BMI, we investigated relationships between 77 BMI and 47 WHR SNPs and endometrial cancer in 6,609 cases and 37,926 country-matched controls.

Methods: Logistic regression analysis and fixed effects meta-analysis were used to test for associations between endometrial cancer risk and (i) individual BMI or WHR SNPs, (ii) a combined weighted genetic risk score (wGRS) for BMI or WHR. Causality of BMI for endometrial cancer was assessed using Mendelian randomization, with BMIwGRS as instrumental variable.

Results: The BMIwGRS was significantly associated with endometrial cancer risk (P = 3.4 × 10). Scaling the effect of the BMIwGRS on endometrial cancer risk by its effect on BMI, the endometrial cancer OR per 5 kg/m of genetically predicted BMI was 2.06 [95% confidence interval (CI), 1.89-2.21], larger than the observed effect of BMI on endometrial cancer risk (OR = 1.55; 95% CI, 1.44-1.68, per 5 kg/m). The association attenuated but remained significant after adjusting for BMI (OR = 1.22; 95% CI, 1.10-1.39; P = 5.3 × 10). There was evidence of directional pleiotropy (P = 1.5 × 10). BMI SNP rs2075650 was associated with endometrial cancer at study-wide significance (P < 4.0 × 10), independent of BMI. Endometrial cancer was not significantly associated with individual WHR SNPs or the WHRwGRS.

Conclusions: BMI, but not WHR, is causally associated with endometrial cancer risk, with evidence that some BMI-associated SNPs alter endometrial cancer risk via mechanisms other than measurable BMI.

Impact: The causal association between BMI SNPs and endometrial cancer has possible implications for endometrial cancer risk modeling. Cancer Epidemiol Biomarkers Prev; 25(11); 1503-10. ©2016 AACR.
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http://dx.doi.org/10.1158/1055-9965.EPI-16-0147DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5093082PMC
November 2016

Association of vitamin D levels and risk of ovarian cancer: a Mendelian randomization study.

Int J Epidemiol 2016 10 4;45(5):1619-1630. Epub 2016 Sep 4.

Department of Obstetrics, Gynecology and Reproductive Sciences, Division of Gynecologic Oncology, University of Pittsburgh School of Medicine, Pittsburgh, PA, USA.

Background: In vitro and observational epidemiological studies suggest that vitamin D may play a role in cancer prevention. However, the relationship between vitamin D and ovarian cancer is uncertain, with observational studies generating conflicting findings. A potential limitation of observational studies is inadequate control of confounding. To overcome this problem, we used Mendelian randomization (MR) to evaluate the association between single nucleotide polymorphisms (SNPs) associated with circulating 25-hydroxyvitamin D [25(OH)D] concentration and risk of ovarian cancer.

Methods: We employed SNPs with well-established associations with 25(OH)D concentration as instrumental variables for MR: rs7944926 (DHCR7), rs12794714 (CYP2R1) and rs2282679 (GC). We included 31 719 women of European ancestry (10 065 cases, 21 654 controls) from the Ovarian Cancer Association Consortium, who were genotyped using customized Illumina Infinium iSelect (iCOGS) arrays. A two-sample (summary data) MR approach was used and analyses were performed separately for all ovarian cancer (10 065 cases) and for high-grade serous ovarian cancer (4121 cases).

Results: The odds ratio for epithelial ovarian cancer risk (10 065 cases) estimated by combining the individual SNP associations using inverse variance weighting was 1.27 (95% confidence interval: 1.06 to 1.51) per 20 nmol/L decrease in 25(OH)D concentration. The estimated odds ratio for high-grade serous epithelial ovarian cancer (4121 cases) was 1.54 (1.19, 2.01).

Conclusions: Genetically lowered 25-hydroxyvitamin D concentrations were associated with higher ovarian cancer susceptibility in Europeans. These findings suggest that increasing plasma vitamin D levels may reduce risk of ovarian cancer.
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http://dx.doi.org/10.1093/ije/dyw207DOI Listing
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC5100621PMC
October 2016