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1.  A genome-wide association study for colorectal cancer identifies a risk locus in 14q23.1 
Human genetics  2015;134(0):1249-1262.
Over 50 loci associated with colorectal cancer (CRC) have been uncovered by genome-wide association studies (GWAS). Identifying additional loci has the potential to help elucidate aspects of the underlying biological processes leading to better understanding of the pathogenesis of the disease. We re-evaluated a GWAS by excluding controls that have family history of CRC or personal history of CR polyps, as we hypothesized that their inclusion reduces power to detect associations. This is supported empirically and through simulations. Two-phase GWAS analysis was performed in a total of 16,517 cases and 14,487 controls. We identified rs17094983, a SNP associated with risk of CRC (p=2.5×10−10; odds ratio estimated by re-including all controls (OR)=0.87, 95% confidence interval (CI): 0.83–0.91; minor allele frequency (MAF)=13%). Results were replicated in samples of African descent (1,894 cases and 4,703 controls; p=0.01; OR=0.86, 95% CI: 0.77–0.97; MAF=16%). Gene expression data in 195 colon adenocarcinomas and 59 normal colon tissues from two different studies revealed that this locus has genotypes that are associated with RTN1 (Reticulon 1) expression (p=0.001), a protein-coding gene involved in survival and proliferation of cancer cells that is highly expressed in normal colon tissues but has significantly reduced expression in tumor cells (p=1.3×10−8).
doi:10.1007/s00439-015-1598-6
PMCID: PMC4687971  PMID: 26404086
2.  CYP24A1 variant modifies the association between use of oestrogen plus progestogen therapy and colorectal cancer risk 
British Journal of Cancer  2016;114(2):221-229.
Background:
Menopausal hormone therapy (MHT) use has been consistently associated with a decreased risk of colorectal cancer (CRC) in women. Our aim was to use a genome-wide gene–environment interaction analysis to identify genetic modifiers of CRC risk associated with use of MHT.
Methods:
We included 10 835 postmenopausal women (5419 cases and 5416 controls) from 10 studies. We evaluated use of any MHT, oestrogen-only (E-only) and combined oestrogen–progestogen (E+P) hormone preparations. To test for multiplicative interactions, we applied the empirical Bayes (EB) test as well as the Wald test in conventional case–control logistic regression as primary tests. The Cocktail test was used as secondary test.
Results:
The EB test identified a significant interaction between rs964293 at 20q13.2/CYP24A1 and E+P (interaction OR (95% CIs)=0.61 (0.52–0.72), P=4.8 × 10−9). The secondary analysis also identified this interaction (Cocktail test OR=0.64 (0.52–0.78), P=1.2 × 10−5 (alpha threshold=3.1 × 10−4). The ORs for association between E+P and CRC risk by rs964293 genotype were as follows: C/C, 0.96 (0.61–1.50); A/C, 0.61 (0.39–0.95) and A/A, 0.40 (0.22–0.73), respectively.
Conclusions:
Our results indicate that rs964293 modifies the association between E+P and CRC risk. The variant is located near CYP24A1, which encodes an enzyme involved in vitamin D metabolism. This novel finding offers additional insight into downstream pathways of CRC etiopathogenesis.
doi:10.1038/bjc.2015.443
PMCID: PMC4815813  PMID: 26766742
GWAS; colorectal cancer; menopausal hormone therapy; polymorphisms; gene–environment interaction; cytochrome P450
3.  Common genetic variation and survival after colorectal cancer diagnosis: a genome-wide analysis 
Carcinogenesis  2015;37(1):87-95.
Summary
In this genome-wide association study of colorectal cancer outcomes, multiple novel variants in the 6p12.1 region were identified as significantly associated with survival among individuals with distant-metastatic colorectal cancer.
Genome-wide association studies have identified several germline single nucleotide polymorphisms (SNPs) significantly associated with colorectal cancer (CRC) incidence. Common germline genetic variation may also be related to CRC survival. We used a discovery-based approach to identify SNPs related to survival outcomes after CRC diagnosis. Genome-wide genotyping arrays were conducted for 3494 individuals with invasive CRC enrolled in six prospective cohort studies (median study-specific follow-up = 4.2–8.1 years). In pooled analyses, we used Cox regression to assess SNP-specific associations with CRC-specific and overall survival, with additional analyses stratified by stage at diagnosis. Top findings were followed-up in independent studies. A P value threshold of P < 5×10−8 in analyses combining discovery and follow-up studies was required for genome-wide significance. Among individuals with distant-metastatic CRC, several SNPs at 6p12.1, nearest the ELOVL5 gene, were statistically significantly associated with poorer survival, with the strongest associations noted for rs209489 [hazard ratio (HR) = 1.8, P = 7.6×10−10 and HR = 1.8, P = 3.7×10−9 for CRC-specific and overall survival, respectively). No SNPs were statistically significantly associated with survival among all cases combined or in cases without distant-metastases. SNPs in 6p12.1/ELOVL5 were associated with survival outcomes in individuals with distant-metastatic CRC, and merit further follow-up for functional significance. Findings from this genome-wide association study highlight the potential importance of genetic variation in CRC prognosis and provide clues to genomic regions of potential interest.
doi:10.1093/carcin/bgv161
PMCID: PMC4715234  PMID: 26586795
4.  Gene-based meta-analysis of genome-wide association studies implicates new loci involved in obesity 
Human Molecular Genetics  2015;24(23):6849-6860.
To date, genome-wide association studies (GWASs) have identified >100 loci with single variants associated with body mass index (BMI). This approach may miss loci with high allelic heterogeneity; therefore, the aim of the present study was to use gene-based meta-analysis to identify regions with high allelic heterogeneity to discover additional obesity susceptibility loci. We included GWAS data from 123 865 individuals of European descent from 46 cohorts in Stage 1 and Metabochip data from additional 103 046 individuals from 43 cohorts in Stage 2, all within the Genetic Investigation of ANthropometric Traits (GIANT) consortium. Each cohort was tested for association between ∼2.4 million (Stage 1) or ∼200 000 (Stage 2) imputed or genotyped single variants and BMI, and summary statistics were subsequently meta-analyzed in 17 941 genes. We used the ‘VErsatile Gene-based Association Study’ (VEGAS) approach to assign variants to genes and to calculate gene-based P-values based on simulations. The VEGAS method was applied to each cohort separately before a gene-based meta-analysis was performed. In Stage 1, two known (FTO and TMEM18) and six novel (PEX2, MTFR2, SSFA2, IARS2, CEP295 and TXNDC12) loci were associated with BMI (P < 2.8 × 10−6 for 17 941 gene tests). We confirmed all loci, and six of them were gene-wide significant in Stage 2 alone. We provide biological support for the loci by pathway, expression and methylation analyses. Our results indicate that gene-based meta-analysis of GWAS provides a useful strategy to find loci of interest that were not identified in standard single-marker analyses due to high allelic heterogeneity.
doi:10.1093/hmg/ddv379
PMCID: PMC4643645  PMID: 26376864
5.  Analysis of Heritability and Shared Heritability Based on Genome-Wide Association Studies for 13 Cancer Types 
Sampson, Joshua N. | Wheeler, William A. | Yeager, Meredith | Panagiotou, Orestis | Wang, Zhaoming | Berndt, Sonja I. | Lan, Qing | Abnet, Christian C. | Amundadottir, Laufey T. | Figueroa, Jonine D. | Landi, Maria Teresa | Mirabello, Lisa | Savage, Sharon A. | Taylor, Philip R. | Vivo, Immaculata De | McGlynn, Katherine A. | Purdue, Mark P. | Rajaraman, Preetha | Adami, Hans-Olov | Ahlbom, Anders | Albanes, Demetrius | Amary, Maria Fernanda | An, She-Juan | Andersson, Ulrika | Andriole, Gerald | Andrulis, Irene L. | Angelucci, Emanuele | Ansell, Stephen M. | Arici, Cecilia | Armstrong, Bruce K. | Arslan, Alan A. | Austin, Melissa A. | Baris, Dalsu | Barkauskas, Donald A. | Bassig, Bryan A. | Becker, Nikolaus | Benavente, Yolanda | Benhamou, Simone | Berg, Christine | Van Den Berg, David | Bernstein, Leslie | Bertrand, Kimberly A. | Birmann, Brenda M. | Black, Amanda | Boeing, Heiner | Boffetta, Paolo | Boutron-Ruault, Marie-Christine | Bracci, Paige M. | Brinton, Louise | Brooks-Wilson, Angela R. | Bueno-de-Mesquita, H. Bas | Burdett, Laurie | Buring, Julie | Butler, Mary Ann | Cai, Qiuyin | Cancel-Tassin, Geraldine | Canzian, Federico | Carrato, Alfredo | Carreon, Tania | Carta, Angela | Chan, John K. C. | Chang, Ellen T. | Chang, Gee-Chen | Chang, I-Shou | Chang, Jiang | Chang-Claude, Jenny | Chen, Chien-Jen | Chen, Chih-Yi | Chen, Chu | Chen, Chung-Hsing | Chen, Constance | Chen, Hongyan | Chen, Kexin | Chen, Kuan-Yu | Chen, Kun-Chieh | Chen, Ying | Chen, Ying-Hsiang | Chen, Yi-Song | Chen, Yuh-Min | Chien, Li-Hsin | Chirlaque, María-Dolores | Choi, Jin Eun | Choi, Yi Young | Chow, Wong-Ho | Chung, Charles C. | Clavel, Jacqueline | Clavel-Chapelon, Françoise | Cocco, Pierluigi | Colt, Joanne S. | Comperat, Eva | Conde, Lucia | Connors, Joseph M. | Conti, David | Cortessis, Victoria K. | Cotterchio, Michelle | Cozen, Wendy | Crouch, Simon | Crous-Bou, Marta | Cussenot, Olivier | Davis, Faith G. | Ding, Ti | Diver, W. Ryan | Dorronsoro, Miren | Dossus, Laure | Duell, Eric J. | Ennas, Maria Grazia | Erickson, Ralph L. | Feychting, Maria | Flanagan, Adrienne M. | Foretova, Lenka | Fraumeni, Joseph F. | Freedman, Neal D. | Beane Freeman, Laura E. | Fuchs, Charles | Gago-Dominguez, Manuela | Gallinger, Steven | Gao, Yu-Tang | Gapstur, Susan M. | Garcia-Closas, Montserrat | García-Closas, Reina | Gascoyne, Randy D. | Gastier-Foster, Julie | Gaudet, Mia M. | Gaziano, J. Michael | Giffen, Carol | Giles, Graham G. | Giovannucci, Edward | Glimelius, Bengt | Goggins, Michael | Gokgoz, Nalan | Goldstein, Alisa M. | Gorlick, Richard | Gross, Myron | Grubb, Robert | Gu, Jian | Guan, Peng | Gunter, Marc | Guo, Huan | Habermann, Thomas M. | Haiman, Christopher A. | Halai, Dina | Hallmans, Goran | Hassan, Manal | Hattinger, Claudia | He, Qincheng | He, Xingzhou | Helzlsouer, Kathy | Henderson, Brian | Henriksson, Roger | Hjalgrim, Henrik | Hoffman-Bolton, Judith | Hohensee, Chancellor | Holford, Theodore R. | Holly, Elizabeth A. | Hong, Yun-Chul | Hoover, Robert N. | Horn-Ross, Pamela L. | Hosain, G. M. Monawar | Hosgood, H. Dean | Hsiao, Chin-Fu | Hu, Nan | Hu, Wei | Hu, Zhibin | Huang, Ming-Shyan | Huerta, Jose-Maria | Hung, Jen-Yu | Hutchinson, Amy | Inskip, Peter D. | Jackson, Rebecca D. | Jacobs, Eric J. | Jenab, Mazda | Jeon, Hyo-Sung | Ji, Bu-Tian | Jin, Guangfu | Jin, Li | Johansen, Christoffer | Johnson, Alison | Jung, Yoo Jin | Kaaks, Rudolph | Kamineni, Aruna | Kane, Eleanor | Kang, Chang Hyun | Karagas, Margaret R. | Kelly, Rachel S. | Khaw, Kay-Tee | Kim, Christopher | Kim, Hee Nam | Kim, Jin Hee | Kim, Jun Suk | Kim, Yeul Hong | Kim, Young Tae | Kim, Young-Chul | Kitahara, Cari M. | Klein, Alison P. | Klein, Robert J. | Kogevinas, Manolis | Kohno, Takashi | Kolonel, Laurence N. | Kooperberg, Charles | Kricker, Anne | Krogh, Vittorio | Kunitoh, Hideo | Kurtz, Robert C. | Kweon, Sun-Seog | LaCroix, Andrea | Lawrence, Charles | Lecanda, Fernando | Lee, Victor Ho Fun | Li, Donghui | Li, Haixin | Li, Jihua | Li, Yao-Jen | Li, Yuqing | Liao, Linda M. | Liebow, Mark | Lightfoot, Tracy | Lim, Wei-Yen | Lin, Chien-Chung | Lin, Dongxin | Lindstrom, Sara | Linet, Martha S. | Link, Brian K. | Liu, Chenwei | Liu, Jianjun | Liu, Li | Ljungberg, Börje | Lloreta, Josep | Lollo, Simonetta Di | Lu, Daru | Lund, Eiluv | Malats, Nuria | Mannisto, Satu | Marchand, Loic Le | Marina, Neyssa | Masala, Giovanna | Mastrangelo, Giuseppe | Matsuo, Keitaro | Maynadie, Marc | McKay, James | McKean-Cowdin, Roberta | Melbye, Mads | Melin, Beatrice S. | Michaud, Dominique S. | Mitsudomi, Tetsuya | Monnereau, Alain | Montalvan, Rebecca | Moore, Lee E. | Mortensen, Lotte Maxild | Nieters, Alexandra | North, Kari E. | Novak, Anne J. | Oberg, Ann L. | Offit, Kenneth | Oh, In-Jae | Olson, Sara H. | Palli, Domenico | Pao, William | Park, In Kyu | Park, Jae Yong | Park, Kyong Hwa | Patiño-Garcia, Ana | Pavanello, Sofia | Peeters, Petra H. M. | Perng, Reury-Perng | Peters, Ulrike | Petersen, Gloria M. | Picci, Piero | Pike, Malcolm C. | Porru, Stefano | Prescott, Jennifer | Prokunina-Olsson, Ludmila | Qian, Biyun | Qiao, You-Lin | Rais, Marco | Riboli, Elio | Riby, Jacques | Risch, Harvey A. | Rizzato, Cosmeri | Rodabough, Rebecca | Roman, Eve | Roupret, Morgan | Ruder, Avima M. | de Sanjose, Silvia | Scelo, Ghislaine | Schned, Alan | Schumacher, Fredrick | Schwartz, Kendra | Schwenn, Molly | Scotlandi, Katia | Seow, Adeline | Serra, Consol | Serra, Massimo | Sesso, Howard D. | Setiawan, Veronica Wendy | Severi, Gianluca | Severson, Richard K. | Shanafelt, Tait D. | Shen, Hongbing | Shen, Wei | Shin, Min-Ho | Shiraishi, Kouya | Shu, Xiao-Ou | Siddiq, Afshan | Sierrasesúmaga, Luis | Sihoe, Alan Dart Loon | Skibola, Christine F. | Smith, Alex | Smith, Martyn T. | Southey, Melissa C. | Spinelli, John J. | Staines, Anthony | Stampfer, Meir | Stern, Marianna C. | Stevens, Victoria L. | Stolzenberg-Solomon, Rachael S. | Su, Jian | Su, Wu-Chou | Sund, Malin | Sung, Jae Sook | Sung, Sook Whan | Tan, Wen | Tang, Wei | Tardón, Adonina | Thomas, David | Thompson, Carrie A. | Tinker, Lesley F. | Tirabosco, Roberto | Tjønneland, Anne | Travis, Ruth C. | Trichopoulos, Dimitrios | Tsai, Fang-Yu | Tsai, Ying-Huang | Tucker, Margaret | Turner, Jenny | Vajdic, Claire M. | Vermeulen, Roel C. H. | Villano, Danylo J. | Vineis, Paolo | Virtamo, Jarmo | Visvanathan, Kala | Wactawski-Wende, Jean | Wang, Chaoyu | Wang, Chih-Liang | Wang, Jiu-Cun | Wang, Junwen | Wei, Fusheng | Weiderpass, Elisabete | Weiner, George J. | Weinstein, Stephanie | Wentzensen, Nicolas | White, Emily | Witzig, Thomas E. | Wolpin, Brian M. | Wong, Maria Pik | Wu, Chen | Wu, Guoping | Wu, Junjie | Wu, Tangchun | Wu, Wei | Wu, Xifeng | Wu, Yi-Long | Wunder, Jay S. | Xiang, Yong-Bing | Xu, Jun | Xu, Ping | Yang, Pan-Chyr | Yang, Tsung-Ying | Ye, Yuanqing | Yin, Zhihua | Yokota, Jun | Yoon, Ho-Il | Yu, Chong-Jen | Yu, Herbert | Yu, Kai | Yuan, Jian-Min | Zelenetz, Andrew | Zeleniuch-Jacquotte, Anne | Zhang, Xu-Chao | Zhang, Yawei | Zhao, Xueying | Zhao, Zhenhong | Zheng, Hong | Zheng, Tongzhang | Zheng, Wei | Zhou, Baosen | Zhu, Meng | Zucca, Mariagrazia | Boca, Simina M. | Cerhan, James R. | Ferri, Giovanni M. | Hartge, Patricia | Hsiung, Chao Agnes | Magnani, Corrado | Miligi, Lucia | Morton, Lindsay M. | Smedby, Karin E. | Teras, Lauren R. | Vijai, Joseph | Wang, Sophia S. | Brennan, Paul | Caporaso, Neil E. | Hunter, David J. | Kraft, Peter | Rothman, Nathaniel | Silverman, Debra T. | Slager, Susan L. | Chanock, Stephen J. | Chatterjee, Nilanjan
Background:
Studies of related individuals have consistently demonstrated notable familial aggregation of cancer. We aim to estimate the heritability and genetic correlation attributable to the additive effects of common single-nucleotide polymorphisms (SNPs) for cancer at 13 anatomical sites.
Methods:
Between 2007 and 2014, the US National Cancer Institute has generated data from genome-wide association studies (GWAS) for 49 492 cancer case patients and 34 131 control patients. We apply novel mixed model methodology (GCTA) to this GWAS data to estimate the heritability of individual cancers, as well as the proportion of heritability attributable to cigarette smoking in smoking-related cancers, and the genetic correlation between pairs of cancers.
Results:
GWAS heritability was statistically significant at nearly all sites, with the estimates of array-based heritability, hl 2, on the liability threshold (LT) scale ranging from 0.05 to 0.38. Estimating the combined heritability of multiple smoking characteristics, we calculate that at least 24% (95% confidence interval [CI] = 14% to 37%) and 7% (95% CI = 4% to 11%) of the heritability for lung and bladder cancer, respectively, can be attributed to genetic determinants of smoking. Most pairs of cancers studied did not show evidence of strong genetic correlation. We found only four pairs of cancers with marginally statistically significant correlations, specifically kidney and testes (ρ = 0.73, SE = 0.28), diffuse large B-cell lymphoma (DLBCL) and pediatric osteosarcoma (ρ = 0.53, SE = 0.21), DLBCL and chronic lymphocytic leukemia (CLL) (ρ = 0.51, SE =0.18), and bladder and lung (ρ = 0.35, SE = 0.14). Correlation analysis also indicates that the genetic architecture of lung cancer differs between a smoking population of European ancestry and a nonsmoking Asian population, allowing for the possibility that the genetic etiology for the same disease can vary by population and environmental exposures.
Conclusion:
Our results provide important insights into the genetic architecture of cancers and suggest new avenues for investigation.
doi:10.1093/jnci/djv279
PMCID: PMC4806328  PMID: 26464424
6.  Prospective study of DNA methylation at LINE-1 and Alu in peripheral blood and the risk of prostate cancer 
The Prostate  2015;75(15):1718-1725.
BACKGROUND
Evidence suggests that global blood DNA methylation levels may be associated with the risk of various cancers, but no studies have evaluated this relationship for prostate cancer.
METHODS
We used pyrosequencing to quantify DNA methylation levels at the long interspersed nuclear element 1 (LINE-1) and Alu repetitive elements in pre-diagnostic blood samples from 694 prostate cancer cases and 703 controls from the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We evaluated prostate cancer risk associated with the mean methylation level for each element using logistic regression, adjusting for potential confounders.
RESULTS
We did not observe a significant association with prostate cancer for LINE-1 [Odds Ratio (OR) for the highest compared to the lowest quartile=1.01, 95% Confidence Interval (CI): 0.73-1.39, ptrend=0.99] or Alu (OR=0.94, 95% CI: 0.68-1.29, ptrend=0.69) methylation levels overall. However, for Alu, we observed that higher DNA methylation levels were associated with a significant increased risk for those diagnosed 4 or more years after blood draw (OR=2.26, 95% CI: 1.27-4.00, ptrend=4.4×10−3). In contrast, there was no association for those diagnosed 2 (OR=1.13, 95% CI: 0.67-1.90, ptrend=0.64) or 3 years after draw (OR=1.22, 95% CI: 0.71-2.07, ptrend=0.32), and a decreased risk for those diagnosed less than 2 years after draw (OR=0.40, 95% CI: 0.25-0.65, ptrend=3.8×10−5; pheterogeneity=5.3×10−6).
CONCLUSIONS
While LINE-1 DNA methylation levels were not associated with prostate cancer, we observed an association for Alu that varied by time from blood draw to diagnosis. Our study suggests that elevated Alu blood DNA methylation levels several years before diagnosis may be associated with an increased prostate cancer risk.
doi:10.1002/pros.23053
PMCID: PMC4535169  PMID: 26250474
global DNA methylation; pre-diagnostic; prostate cancer; repetitive element
7.  Incidence and Mortality of Colorectal Cancer in Individuals with a Family History of Colorectal Cancer 
Gastroenterology  2015;149(6):1438-1445.e1.
Background and Aims
Little is known about the change in risk conferred by family history of colorectal cancer (CRC) as a person ages. We evaluated the effect of family history on CRC incidence and mortality after age 55 y, when the risk of early onset cancer had passed.
Methods
We collected data from participants in the randomized, controlled Prostate, Lung, Colorectal and Ovarian cancer screening trial of flexible sigmoidoscopy vs usual care (55–74 y old, no history of CRC), performed at 10 US centers from 1993 to 2001. A detailed family history of colorectal cancer was obtained at enrollment and subjects were followed for CRC incidence and mortality for up to 13 years.
Results
Among 144,768 participants, 14,961 (10.3%) reported a family of CRC. Of 2090 incident cases, 273 had a family history of CRC (13.1%); among 538 deaths from CRC, 71 (13.2%) had a family history of CRC. Overall, family history of CRC was associated with an increased risk of CRC incidence (hazard ratio [HR], 1.30; 95% confidence interval [CI], 1.10–1.50; P<.0001) and increased mortality (HR, 1.31; 95% CI, 1.02–1.69; P=.03). Subjects with 1 first-degree relative (FDR) with CRC (n=238; HR, 1.23; 95% CI, 1.07–1.42) or ≥2 FDRs with CRC (n=35; HR, 2.04; 95% CI, 1.44–2.86) were at increased risk for incident CRC. However, among individuals with 1 FDR with CRC, there was no difference in risk based on the age at diagnosis in the FDR (for FDR age <60 y: HR, 1.27; 95% CI, 0.97–1.63; for FDR age 60–70 y: HR, 1.33; 95% CI, 1.06–1.62; for FDR >70 y: HR, 1.14; 95% CI, 0.93–1.45; Ptrend=.59).
Conclusion and Relevance
After an age of 55 y, subjects with 1 FDR with CRC had only a modest increase in risk for CRC incidence and death; age of onset in the FDR was not significantly associated with risk. Individuals with ≥2 FDRs with CRC had continued increased risk in older age. Guidelines and clinical practice for subjects with a family history of CRC should be modified to align CRC testing to risk. Clinical Trials.gov number, NCT00002540
doi:10.1053/j.gastro.2015.07.055
PMCID: PMC4628587  PMID: 26255045
Colon Cancer; screening; genetic; risk factors; adenomatous polyps
8.  Cross Cancer Genomic Investigation of Inflammation Pathway for Five Common Cancers: Lung, Ovary, Prostate, Breast, and Colorectal Cancer 
Background:
Inflammation has been hypothesized to increase the risk of cancer development as an initiator or promoter, yet no large-scale study of inherited variation across cancer sites has been conducted.
Methods:
We conducted a cross-cancer genomic analysis for the inflammation pathway based on 48 genome-wide association studies within the National Cancer Institute GAME-ON Network across five common cancer sites, with a total of 64 591 cancer patients and 74 467 control patients. Subset-based meta-analysis was used to account for possible disease heterogeneity, and hierarchical modeling was employed to estimate the effect of the subcomponents within the inflammation pathway. The network was visualized by enrichment map. All statistical tests were two-sided.
Results:
We identified three pleiotropic loci within the inflammation pathway, including one novel locus in Ch12q24 encoding SH2B3 (rs3184504), which reached GWAS significance with a P value of 1.78 x 10–8, and it showed an association with lung cancer (P = 2.01 x 10–6), colorectal cancer (GECCO P = 6.72x10-6; CORECT P = 3.32x10-5), and breast cancer (P = .009). We also identified five key subpathway components with genetic variants that are relevant for the risk of these five cancer sites: inflammatory response for colorectal cancer (P = .006), inflammation related cell cycle gene for lung cancer (P = 1.35x10-6), and activation of immune response for ovarian cancer (P = .009). In addition, sequence variations in immune system development played a role in breast cancer etiology (P = .001) and innate immune response was involved in the risk of both colorectal (P = .022) and ovarian cancer (P = .003).
Conclusions:
Genetic variations in inflammation and its related subpathway components are keys to the development of lung, colorectal, ovary, and breast cancer, including SH2B3, which is associated with lung, colorectal, and breast cancer.
doi:10.1093/jnci/djv246
PMCID: PMC4675100  PMID: 26319099
9.  Population genetic differentiation of height and body mass index across Europe 
Nature genetics  2015;47(11):1357-1362.
Across-nation differences in the mean of complex traits such as obesity and stature are common1–8, but the reasons for these differences are not known. Here, we find evidence that many independent loci of small effect combine to create population genetic differences in height and body mass index (BMI) in a sample of 9,416 individuals across 14 European countries. Using discovery data on over 250,000 individuals and unbiased estimates of effect sizes from 17,500 sib pairs, we estimate that 24% (95% CI: 9%, 41%) and 8% (95% CI: 4%, 16%) of the captured additive genetic variance for height and BMI across Europe are attributed to among-population genetic differences. Population genetic divergence differed significantly from that expected under a null model (P <3.94e−08 for height and P<5.95e−04 for BMI), and we find an among-population genetic correlation for tall and slender nations (r = −0.80 (95% CI: −0.95, −0.60), contrasting no genetic correlation between height and BMI within populations (r = −0.016, 95% CI: −0.041, 0.001), consistent with selection on height genes that also act to reduce BMI. Observations of mean height across nations correlated with the predicted genetic means for height (r = 0.51, P<0.001), so that a proportion of observed differences in height within Europe reflect genetic factors. In contrast, observed mean BMI did not correlate with the genetic estimates (P<0.58), implying that genetic differentiation in BMI is masked by environmental differences across Europe.
doi:10.1038/ng.3401
PMCID: PMC4984852  PMID: 26366552
10.  Serum metabolomic profiling of prostate cancer risk in the prostate, lung, colorectal, and ovarian cancer screening trial 
British Journal of Cancer  2016;115(9):1087-1095.
Background:
Two recent metabolomic analyses found serum lipid, energy, and other metabolites related to aggressive prostate cancer risk up to 20 years prior to diagnosis.
Methods:
We conducted a serum metabolomic investigation of prostate cancer risk in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial that included annual serum total prostate-specific antigen measurement and digital rectal examination. This nested study included 380 cases diagnosed post-screening and 380 controls individually matched to cases on age, race, study centre, and blood-collection date (median time to diagnosis, 10 years (range 4.4–17 years)). Sera were analysed on a high-resolution accurate mass platform of ultrahigh-performance liquid and gas chromatography/mass spectroscopy that identified 695 known metabolites. Logistic regression conditioned on the matching factors estimated odds ratios (OR) and 95% confidence intervals of risk associated with an 80th percentile increase in the log-metabolite signal.
Results:
Twenty-seven metabolites were associated with prostate cancer at P<0.05. Pyroglutamine, gamma-glutamylphenylalanine, phenylpyruvate, N-acetylcitrulline, and stearoylcarnitine showed the strongest metabolite-risk signals (ORs=0.53, 0.51, 0.46, 0.58, and 1.74, respectively; 0.001⩽P⩽0.006). Findings were similar for aggressive disease (peptide chemical class, P=0.03). None of the P-values were below the threshold of Bonferroni correction, however.
Conclusions:
A unique metabolomic profile associated with post-screening prostate cancer is identified that differs from that in a previously studied, unscreened population.
doi:10.1038/bjc.2016.305
PMCID: PMC5117796  PMID: 27673363
prostate cancer; metabolomic profiling; aggressive; pre-diagnosed serum; pyroglutamine; gamma-glutamyl peptides; N-acetyl amino acids; fatty acids
11.  Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions 
Han, Ying | Hazelett, Dennis J. | Wiklund, Fredrik | Schumacher, Fredrick R. | Stram, Daniel O. | Berndt, Sonja I. | Wang, Zhaoming | Rand, Kristin A. | Hoover, Robert N. | Machiela, Mitchell J. | Yeager, Merideth | Burdette, Laurie | Chung, Charles C. | Hutchinson, Amy | Yu, Kai | Xu, Jianfeng | Travis, Ruth C. | Key, Timothy J. | Siddiq, Afshan | Canzian, Federico | Takahashi, Atsushi | Kubo, Michiaki | Stanford, Janet L. | Kolb, Suzanne | Gapstur, Susan M. | Diver, W. Ryan | Stevens, Victoria L. | Strom, Sara S. | Pettaway, Curtis A. | Al Olama, Ali Amin | Kote-Jarai, Zsofia | Eeles, Rosalind A. | Yeboah, Edward D. | Tettey, Yao | Biritwum, Richard B. | Adjei, Andrew A. | Tay, Evelyn | Truelove, Ann | Niwa, Shelley | Chokkalingam, Anand P. | Isaacs, William B. | Chen, Constance | Lindstrom, Sara | Le Marchand, Loic | Giovannucci, Edward L. | Pomerantz, Mark | Long, Henry | Li, Fugen | Ma, Jing | Stampfer, Meir | John, Esther M. | Ingles, Sue A. | Kittles, Rick A. | Murphy, Adam B. | Blot, William J. | Signorello, Lisa B. | Zheng, Wei | Albanes, Demetrius | Virtamo, Jarmo | Weinstein, Stephanie | Nemesure, Barbara | Carpten, John | Leske, M. Cristina | Wu, Suh-Yuh | Hennis, Anselm J. M. | Rybicki, Benjamin A. | Neslund-Dudas, Christine | Hsing, Ann W. | Chu, Lisa | Goodman, Phyllis J. | Klein, Eric A. | Zheng, S. Lilly | Witte, John S. | Casey, Graham | Riboli, Elio | Li, Qiyuan | Freedman, Matthew L. | Hunter, David J. | Gronberg, Henrik | Cook, Michael B. | Nakagawa, Hidewaki | Kraft, Peter | Chanock, Stephen J. | Easton, Douglas F. | Henderson, Brian E. | Coetzee, Gerhard A. | Conti, David V. | Haiman, Christopher A.
Human Molecular Genetics  2015;24(19):5603-5618.
Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10−4–5.6 × 10−3) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10−6) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.
doi:10.1093/hmg/ddv269
PMCID: PMC4572069  PMID: 26162851
12.  Genome-Wide Interaction Analyses between Genetic Variants and Alcohol Consumption and Smoking for Risk of Colorectal Cancer 
PLoS Genetics  2016;12(10):e1006296.
Genome-wide association studies (GWAS) have identified many genetic susceptibility loci for colorectal cancer (CRC). However, variants in these loci explain only a small proportion of familial aggregation, and there are likely additional variants that are associated with CRC susceptibility. Genome-wide studies of gene-environment interactions may identify variants that are not detected in GWAS of marginal gene effects. To study this, we conducted a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking using data from the Colon Cancer Family Registry (CCFR) and the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Interactions were tested using logistic regression. We identified interaction between CRC risk and alcohol consumption and variants in the 9q22.32/HIATL1 (Pinteraction = 1.76×10−8; permuted p-value 3.51x10-8) region. Compared to non-/occasional drinking light to moderate alcohol consumption was associated with a lower risk of colorectal cancer among individuals with rs9409565 CT genotype (OR, 0.82 [95% CI, 0.74–0.91]; P = 2.1×10−4) and TT genotypes (OR,0.62 [95% CI, 0.51–0.75]; P = 1.3×10−6) but not associated among those with the CC genotype (p = 0.059). No genome-wide statistically significant interactions were observed for smoking. If replicated our suggestive finding of a genome-wide significant interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptibility to the effect of alcohol on CRC risk.
Author Summary
Alcohol consumption and smoking are associated with CRC risk. We performed a genome-wide analysis for interaction between genetic variants and alcohol consumption and cigarette smoking to identify potential new genetic regions associated with CRC. About 8,000 CRC cases and 8,800 controls were included in alcohol-related analysis and over 11,000 cases and 11,000 controls were involved in smoking-related analysis. We identified interaction between variants at 9q22.32/HIATL1 and alcohol consumption in relation to CRC risk (Pinteraction = 1.76×10−8). If replicated our suggested finding of the interaction between genetic variants and alcohol consumption might contribute to understanding colorectal cancer etiology and identifying subpopulations with differential susceptible to the effect of alcohol on CRC risk.
doi:10.1371/journal.pgen.1006296
PMCID: PMC5065124  PMID: 27723779
13.  Genomewide meta‐analysis identifies loci associated with IGF‐I and IGFBP‐3 levels with impact on age‐related traits 
Teumer, Alexander | Qi, Qibin | Nethander, Maria | Aschard, Hugues | Bandinelli, Stefania | Beekman, Marian | Berndt, Sonja I. | Bidlingmaier, Martin | Broer, Linda | Cappola, Anne | Ceda, Gian Paolo | Chanock, Stephen | Chen, Ming‐Huei | Chen, Tai C. | Chen, Yii‐Der Ida | Chung, Jonathan | Del Greco Miglianico, Fabiola | Eriksson, Joel | Ferrucci, Luigi | Friedrich, Nele | Gnewuch, Carsten | Goodarzi, Mark O. | Grarup, Niels | Guo, Tingwei | Hammer, Elke | Hayes, Richard B. | Hicks, Andrew A. | Hofman, Albert | Houwing‐Duistermaat, Jeanine J. | Hu, Frank | Hunter, David J. | Husemoen, Lise L. | Isaacs, Aaron | Jacobs, Kevin B. | Janssen, Joop A. M. J. L. | Jansson, John‐Olov | Jehmlich, Nico | Johnson, Simon | Juul, Anders | Karlsson, Magnus | Kilpelainen, Tuomas O. | Kovacs, Peter | Kraft, Peter | Li, Chao | Linneberg, Allan | Liu, Yongmei | Loos, Ruth J. F. | Lorentzon, Mattias | Lu, Yingchang | Maggio, Marcello | Magi, Reedik | Meigs, James | Mellström, Dan | Nauck, Matthias | Newman, Anne B. | Pollak, Michael N. | Pramstaller, Peter P. | Prokopenko, Inga | Psaty, Bruce M. | Reincke, Martin | Rimm, Eric B. | Rotter, Jerome I. | Saint Pierre, Aude | Schurmann, Claudia | Seshadri, Sudha | Sjögren, Klara | Slagboom, P. Eline | Strickler, Howard D. | Stumvoll, Michael | Suh, Yousin | Sun, Qi | Zhang, Cuilin | Svensson, Johan | Tanaka, Toshiko | Tare, Archana | Tönjes, Anke | Uh, Hae‐Won | van Duijn, Cornelia M. | van Heemst, Diana | Vandenput, Liesbeth | Vasan, Ramachandran S. | Völker, Uwe | Willems, Sara M. | Ohlsson, Claes | Wallaschofski, Henri | Kaplan, Robert C.
Aging Cell  2016;15(5):811-824.
Summary
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.
doi:10.1111/acel.12490
PMCID: PMC5013013  PMID: 27329260
aging; genomewide association study; growth hormone axis; IGF‐I; IGFBP‐3; longevity
14.  Identification of a common variant with potential pleiotropic effect on risk of inflammatory bowel disease and colorectal cancer 
Carcinogenesis  2015;36(9):999-1007.
Summary
We identified the minor allele (T) in SNP rs11676348 to have pleiotropic effect on risk of UC and CRC, particularly in tumors with an inflammatory component. Our findings offer the promise of risk stratification of UC patients for developing CRC.
Although genome-wide association studies (GWAS) have separately identified many genetic susceptibility loci for ulcerative colitis (UC), Crohn’s disease (CD) and colorectal cancer (CRC), there has been no large-scale examination for pleiotropy, or shared genetic susceptibility, for these conditions. We used logistic regression modeling to examine the associations of 181 UC and CD susceptibility variants previously identified by GWAS with risk of CRC using data from the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. We also examined associations of significant variants with clinical and molecular characteristics in a subset of the studies. Among 11794 CRC cases and 14190 controls, rs11676348, the susceptibility single nucleotide polymorphism (SNP) for UC, was significantly associated with reduced risk of CRC (P = 7E−05). The multivariate-adjusted odds ratio of CRC with each copy of the T allele was 0.93 (95% CI 0.89–0.96). The association of the SNP with risk of CRC differed according to mucinous histological features (P heterogeneity = 0.008). In addition, the (T) allele was associated with lower risk of tumors with Crohn’s-like reaction but not tumors without such immune infiltrate (P heterogeneity = 0.02) and microsatellite instability-high (MSI-high) but not microsatellite stable or MSI-low tumors (P heterogeneity = 0.03). The minor allele (T) in SNP rs11676348, located downstream from CXCR2 that has been implicated in CRC progression, is associated with a lower risk of CRC, particularly tumors with a mucinous component, Crohn’s-like reaction and MSI-high. Our findings offer the promise of risk stratification of inflammatory bowel disease patients for complications such as CRC.
doi:10.1093/carcin/bgv086
PMCID: PMC4573660  PMID: 26071399
15.  Genome-wide association study of colorectal cancer identifies six new susceptibility loci 
Schumacher, Fredrick R. | Schmit, Stephanie L. | Jiao, Shuo | Edlund, Christopher K. | Wang, Hansong | Zhang, Ben | Hsu, Li | Huang, Shu-Chen | Fischer, Christopher P. | Harju, John F. | Idos, Gregory E. | Lejbkowicz, Flavio | Manion, Frank J. | McDonnell, Kevin | McNeil, Caroline E. | Melas, Marilena | Rennert, Hedy S. | Shi, Wei | Thomas, Duncan C. | Van Den Berg, David J. | Hutter, Carolyn M. | Aragaki, Aaron K. | Butterbach, Katja | Caan, Bette J. | Carlson, Christopher S. | Chanock, Stephen J. | Curtis, Keith R. | Fuchs, Charles S. | Gala, Manish | Giovannucci, Edward L. | Gogarten, Stephanie M. | Hayes, Richard B. | Henderson, Brian | Hunter, David J. | Jackson, Rebecca D. | Kolonel, Laurence N. | Kooperberg, Charles | Küry, Sébastien | LaCroix, Andrea | Laurie, Cathy C. | Laurie, Cecelia A. | Lemire, Mathieu | Levine, David | Ma, Jing | Makar, Karen W. | Qu, Conghui | Taverna, Darin | Ulrich, Cornelia M. | Wu, Kana | Kono, Suminori | West, Dee W. | Berndt, Sonja I. | Bezieau, Stéphane | Brenner, Hermann | Campbell, Peter T. | Chan, Andrew T. | Chang-Claude, Jenny | Coetzee, Gerhard A. | Conti, David V. | Duggan, David | Figueiredo, Jane C. | Fortini, Barbara K. | Gallinger, Steven J. | Gauderman, W. James | Giles, Graham | Green, Roger | Haile, Robert | Harrison, Tabitha A. | Hoffmeister, Michael | Hopper, John L. | Hudson, Thomas J. | Jacobs, Eric | Iwasaki, Motoki | Jee, Sun Ha | Jenkins, Mark | Jia, Wei-Hua | Joshi, Amit | Li, Li | Lindor, Noralene M. | Matsuo, Keitaro | Moreno, Victor | Mukherjee, Bhramar | Newcomb, Polly A. | Potter, John D. | Raskin, Leon | Rennert, Gad | Rosse, Stephanie | Severi, Gianluca | Schoen, Robert E. | Seminara, Daniela | Shu, Xiao-Ou | Slattery, Martha L. | Tsugane, Shoichiro | White, Emily | Xiang, Yong-Bing | Zanke, Brent W. | Zheng, Wei | Le Marchand, Loic | Casey, Graham | Gruber, Stephen B. | Peters, Ulrike
Nature communications  2015;6:7138.
Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08. These findings provide additional insight into the underlying biological mechanisms of colorectal cancer and demonstrate the scientific value of large consortia-based genetic epidemiology studies.
doi:10.1038/ncomms8138
PMCID: PMC4967357  PMID: 26151821
16.  Fine-Mapping of Common Genetic Variants Associated with Colorectal Tumor Risk Identified Potential Functional Variants 
PLoS ONE  2016;11(7):e0157521.
Genome-wide association studies (GWAS) have identified many common single nucleotide polymorphisms (SNPs) associated with colorectal cancer risk. These SNPs may tag correlated variants with biological importance. Fine-mapping around GWAS loci can facilitate detection of functional candidates and additional independent risk variants. We analyzed 11,900 cases and 14,311 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colon Cancer Family Registry. To fine-map genomic regions containing all known common risk variants, we imputed high-density genetic data from the 1000 Genomes Project. We tested single-variant associations with colorectal tumor risk for all variants spanning genomic regions 250-kb upstream or downstream of 31 GWAS-identified SNPs (index SNPs). We queried the University of California, Santa Cruz Genome Browser to examine evidence for biological function. Index SNPs did not show the strongest association signals with colorectal tumor risk in their respective genomic regions. Bioinformatics analysis of SNPs showing smaller P-values in each region revealed 21 functional candidates in 12 loci (5q31.1, 8q24, 11q13.4, 11q23, 12p13.32, 12q24.21, 14q22.2, 15q13, 18q21, 19q13.1, 20p12.3, and 20q13.33). We did not observe evidence of additional independent association signals in GWAS-identified regions. Our results support the utility of integrating data from comprehensive fine-mapping with expanding publicly available genomic databases to help clarify GWAS associations and identify functional candidates that warrant more onerous laboratory follow-up. Such efforts may aid the eventual discovery of disease-causing variant(s).
doi:10.1371/journal.pone.0157521
PMCID: PMC4933364  PMID: 27379672
17.  Genetic variants of adiponectin and risk of colorectal cancer 
Circulating adiponectin has been associated with lower risk of colorectal cancer (CRC). Genome-wide association studies have identified several single-nucleotide polymorphisms (SNPs) associated with adiponectin levels. However, it is unclear whether these SNPs are associated with CRC risk. In addition, previous data on SNPs in the adiponectin pathway and their associations with CRC are inconsistent. Therefore, we examined 19 SNPs in genes related to adiponectin or its receptors and their associations with CRC using logistic regression among 7,020 cases and 7,631 controls drawn from 10 studies included in the Genetics and Epidemiology of Colorectal Cancer Consortium. Using data from a subset of two large cohort studies, we also assessed the contribution of individual SNPs and an adiponectin genetic score to plasma adiponectin after accounting for lifestyle factors among 2,217 women and 619 men. We did not find any statistically significant association between the 19 adiponectin-associated SNPs and CRC risk (multivariable-adjusted odds ratios ranged from 0.89 to 1.05, all P > 0.05). Each SNP explained less than 2.50% of the variance of plasma adiponectin, and the genetic score collectively accounted for 2.95% and 1.42% of the variability of adiponectin in women and men, respectively, after adjustment for age, body mass index, physical activity, smoking, alcohol consumption, regular use of aspirin or non-steroidal anti-inflammatory drug and postmenopausal hormone use. In conclusion, our findings do not support an association between known adiponectin-related common SNPs and CRC incidence. However, known common SNPs account for only a limited proportion of the interindividual variance in circulating adiponectin. Further work is warranted to investigate the relationship between adiponectin and CRC while accounting for other components in the pathway.
doi:10.1002/ijc.29360
PMCID: PMC4405454  PMID: 25431318
adiponectin; single-nucleotide polymorphism; Mendelian randomization; colorectal cancer; lifestyle factors
18.  Mendelian randomization study of body mass index and colorectal cancer risk 
Background
High body mass index (BMI) is consistently linked to increased risk of colorectal cancer (CRC) for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and CRC.
Methods
We used data from 10,226 CRC cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis.
Results
Individuals carrying greater numbers of BMI-increasing alleles had higher CRC risk (per weighted allele OR, 1.31; 95% confidence interval [CI], 1.10–1.57). Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for CRC (IV-OR per 5 kg/m2, 1.50; 95% CI, 1.13–2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of CRC among women (IV-OR per 5 kg/m2, 1.82; 95% CI, 1.26–2.61). For men, genetically influenced BMI was not associated with CRC (IV-OR per 5 kg/m2, 1.18; 95% CI, 0.73–1.92).
Conclusions
High BMI was associated with increased CRC risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation.
Impact
Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of CRC.
doi:10.1158/1055-9965.EPI-14-1309
PMCID: PMC4490960  PMID: 25976416
Colorectal cancer; Obesity; Epidemiology; Sex; Risk factors
19.  Correction: The Influence of Age and Sex on Genetic Associations with Adult Body Size and Shape: A Large-Scale Genome-Wide Interaction Study 
Winkler, Thomas W. | Justice, Anne E. | Graff, Mariaelisa | Barata, Llilda | Feitosa, Mary F. | Chu, Su | Czajkowski, Jacek | Esko, Tõnu | Fall, Tove | Kilpeläinen, Tuomas O. | Lu, Yingchang | Mägi, Reedik | Mihailov, Evelin | Pers, Tune H. | Rüeger, Sina | Teumer, Alexander | Ehret, Georg B. | Ferreira, Teresa | Heard-Costa, Nancy L. | Karjalainen, Juha | Lagou, Vasiliki | Mahajan, Anubha | Neinast, Michael D. | Prokopenko, Inga | Simino, Jeannette | Teslovich, Tanya M. | Jansen, Rick | Westra, Harm-Jan | White, Charles C. | Absher, Devin | Ahluwalia, Tarunveer S. | Ahmad, Shafqat | Albrecht, Eva | Alves, Alexessander Couto | Bragg-Gresham, Jennifer L. | de Craen, Anton J. M. | Bis, Joshua C. | Bonnefond, Amélie | Boucher, Gabrielle | Cadby, Gemma | Cheng, Yu-Ching | Chiang, Charleston W. K. | Delgado, Graciela | Demirkan, Ayse | Dueker, Nicole | Eklund, Niina | Eiriksdottir, Gudny | Eriksson, Joel | Feenstra, Bjarke | Fischer, Krista | Frau, Francesca | Galesloot, Tessel E. | Geller, Frank | Goel, Anuj | Gorski, Mathias | Grammer, Tanja B. | Gustafsson, Stefan | Haitjema, Saskia | Hottenga, Jouke-Jan | Huffman, Jennifer E. | Jackson, Anne U. | Jacobs, Kevin B. | Johansson, Åsa | Kaakinen, Marika | Kleber, Marcus E. | Lahti, Jari | Mateo Leach, Irene | Lehne, Benjamin | Liu, Youfang | Lo, Ken Sin | Lorentzon, Mattias | Luan, Jian'an | Madden, Pamela A. F. | Mangino, Massimo | McKnight, Barbara | Medina-Gomez, Carolina | Monda, Keri L. | Montasser, May E. | Müller, Gabriele | Müller-Nurasyid, Martina | Nolte, Ilja M. | Panoutsopoulou, Kalliope | Pascoe, Laura | Paternoster, Lavinia | Rayner, Nigel W. | Renström, Frida | Rizzi, Federica | Rose, Lynda M. | Ryan, Kathy A. | Salo, Perttu | Sanna, Serena | Scharnagl, Hubert | Shi, Jianxin | Smith, Albert Vernon | Southam, Lorraine | Stančáková, Alena | Steinthorsdottir, Valgerdur | Strawbridge, Rona J. | Sung, Yun Ju | Tachmazidou, Ioanna | Tanaka, Toshiko | Thorleifsson, Gudmar | Trompet, Stella | Pervjakova, Natalia | Tyrer, Jonathan P. | Vandenput, Liesbeth | van der Laan, Sander W | van der Velde, Nathalie | van Setten, Jessica | van Vliet-Ostaptchouk, Jana V. | Verweij, Niek | Vlachopoulou, Efthymia | Waite, Lindsay L. | Wang, Sophie R. | Wang, Zhaoming | Wild, Sarah H. | Willenborg, Christina | Wilson, James F. | Wong, Andrew | Yang, Jian | Yengo, Loïc | Yerges-Armstrong, Laura M. | Yu, Lei | Zhang, Weihua | Zhao, Jing Hua | Andersson, Ehm A. | Bakker, Stephan J. L. | Baldassarre, Damiano | Banasik, Karina | Barcella, Matteo | Barlassina, Cristina | Bellis, Claire | Benaglio, Paola | Blangero, John | Blüher, Matthias | Bonnet, Fabrice | Bonnycastle, Lori L. | Boyd, Heather A. | Bruinenberg, Marcel | Buchman, Aron S | Campbell, Harry | Chen, Yii-Der Ida | Chines, Peter S. | Claudi-Boehm, Simone | Cole, John | Collins, Francis S. | de Geus, Eco J. C. | de Groot, Lisette C. P. G. M. | Dimitriou, Maria | Duan, Jubao | Enroth, Stefan | Eury, Elodie | Farmaki, Aliki-Eleni | Forouhi, Nita G. | Friedrich, Nele | Gejman, Pablo V. | Gigante, Bruna | Glorioso, Nicola | Go, Alan S. | Gottesman, Omri | Gräßler, Jürgen | Grallert, Harald | Grarup, Niels | Gu, Yu-Mei | Broer, Linda | Ham, Annelies C. | Hansen, Torben | Harris, Tamara B. | Hartman, Catharina A. | Hassinen, Maija | Hastie, Nicholas | Hattersley, Andrew T. | Heath, Andrew C. | Henders, Anjali K. | Hernandez, Dena | Hillege, Hans | Holmen, Oddgeir | Hovingh, Kees G | Hui, Jennie | Husemoen, Lise L. | Hutri-Kähönen, Nina | Hysi, Pirro G. | Illig, Thomas | De Jager, Philip L. | Jalilzadeh, Shapour | Jørgensen, Torben | Jukema, J. Wouter | Juonala, Markus | Kanoni, Stavroula | Karaleftheri, Maria | Khaw, Kay Tee | Kinnunen, Leena | Kittner, Steven J. | Koenig, Wolfgang | Kolcic, Ivana | Kovacs, Peter | Krarup, Nikolaj T. | Kratzer, Wolfgang | Krüger, Janine | Kuh, Diana | Kumari, Meena | Kyriakou, Theodosios | Langenberg, Claudia | Lannfelt, Lars | Lanzani, Chiara | Lotay, Vaneet | Launer, Lenore J. | Leander, Karin | Lindström, Jaana | Linneberg, Allan | Liu, Yan-Ping | Lobbens, Stéphane | Luben, Robert | Lyssenko, Valeriya | Männistö, Satu | Magnusson, Patrik K. | McArdle, Wendy L. | Menni, Cristina | Merger, Sigrun | Milani, Lili | Montgomery, Grant W. | Morris, Andrew P. | Narisu, Narisu | Nelis, Mari | Ong, Ken K. | Palotie, Aarno | Pérusse, Louis | Pichler, Irene | Pilia, Maria G. | Pouta, Anneli | Rheinberger, Myriam | Ribel-Madsen, Rasmus | Richards, Marcus | Rice, Kenneth M. | Rice, Treva K. | Rivolta, Carlo | Salomaa, Veikko | Sanders, Alan R. | Sarzynski, Mark A. | Scholtens, Salome | Scott, Robert A. | Scott, William R. | Sebert, Sylvain | Sengupta, Sebanti | Sennblad, Bengt | Seufferlein, Thomas | Silveira, Angela | Slagboom, P. Eline | Smit, Jan H. | Sparsø, Thomas H. | Stirrups, Kathleen | Stolk, Ronald P. | Stringham, Heather M. | Swertz, Morris A | Swift, Amy J. | Syvänen, Ann-Christine | Tan, Sian-Tsung | Thorand, Barbara | Tönjes, Anke | Tremblay, Angelo | Tsafantakis, Emmanouil | van der Most, Peter J. | Völker, Uwe | Vohl, Marie-Claude | Vonk, Judith M. | Waldenberger, Melanie | Walker, Ryan W. | Wennauer, Roman | Widén, Elisabeth | Willemsen, Gonneke | Wilsgaard, Tom | Wright, Alan F. | Zillikens, M. Carola | van Dijk, Suzanne C. | van Schoor, Natasja M. | Asselbergs, Folkert W. | de Bakker, Paul I. W. | Beckmann, Jacques S. | Beilby, John | Bennett, David A. | Bergman, Richard N. | Bergmann, Sven | Böger, Carsten A. | Boehm, Bernhard O. | Boerwinkle, Eric | Boomsma, Dorret I. | Bornstein, Stefan R. | Bottinger, Erwin P. | Bouchard, Claude | Chambers, John C. | Chanock, Stephen J. | Chasman, Daniel I. | Cucca, Francesco | Cusi, Daniele | Dedoussis, George | Erdmann, Jeanette | Eriksson, Johan G. | Evans, Denis A. | de Faire, Ulf | Farrall, Martin | Ferrucci, Luigi | Ford, Ian | Franke, Lude | Franks, Paul W. | Froguel, Philippe | Gansevoort, Ron T. | Gieger, Christian | Grönberg, Henrik | Gudnason, Vilmundur | Gyllensten, Ulf | Hall, Per | Hamsten, Anders | van der Harst, Pim | Hayward, Caroline | Heliövaara, Markku | Hengstenberg, Christian | Hicks, Andrew A | Hingorani, Aroon | Hofman, Albert | Hu, Frank | Huikuri, Heikki V. | Hveem, Kristian | James, Alan L. | Jordan, Joanne M. | Jula, Antti | Kähönen, Mika | Kajantie, Eero | Kathiresan, Sekar | Kiemeney, Lambertus A. L. M. | Kivimaki, Mika | Knekt, Paul B. | Koistinen, Heikki A. | Kooner, Jaspal S. | Koskinen, Seppo | Kuusisto, Johanna | Maerz, Winfried | Martin, Nicholas G | Laakso, Markku | Lakka, Timo A. | Lehtimäki, Terho | Lettre, Guillaume | Levinson, Douglas F. | Lind, Lars | Lokki, Marja-Liisa | Mäntyselkä, Pekka | Melbye, Mads | Metspalu, Andres | Mitchell, Braxton D. | Moll, Frans L. | Murray, Jeffrey C. | Musk, Arthur W. | Nieminen, Markku S. | Njølstad, Inger | Ohlsson, Claes | Oldehinkel, Albertine J. | Oostra, Ben A. | Palmer, Lyle J | Pankow, James S. | Pasterkamp, Gerard | Pedersen, Nancy L. | Pedersen, Oluf | Penninx, Brenda W. | Perola, Markus | Peters, Annette | Polašek, Ozren | Pramstaller, Peter P. | Psaty, Bruce M. | Qi, Lu | Quertermous, Thomas | Raitakari, Olli T. | Rankinen, Tuomo | Rauramaa, Rainer | Ridker, Paul M. | Rioux, John D. | Rivadeneira, Fernando | Rotter, Jerome I. | Rudan, Igor | den Ruijter, Hester M. | Saltevo, Juha | Sattar, Naveed | Schunkert, Heribert | Schwarz, Peter E. H. | Shuldiner, Alan R. | Sinisalo, Juha | Snieder, Harold | Sørensen, Thorkild I. A. | Spector, Tim D. | Staessen, Jan A. | Stefania, Bandinelli | Thorsteinsdottir, Unnur | Stumvoll, Michael | Tardif, Jean-Claude | Tremoli, Elena | Tuomilehto, Jaakko | Uitterlinden, André G. | Uusitupa, Matti | Verbeek, André L. M. | Vermeulen, Sita H. | Viikari, Jorma S. | Vitart, Veronique | Völzke, Henry | Vollenweider, Peter | Waeber, Gérard | Walker, Mark | Wallaschofski, Henri | Wareham, Nicholas J. | Watkins, Hugh | Zeggini, Eleftheria | Chakravarti, Aravinda | Clegg, Deborah J. | Cupples, L. Adrienne | Gordon-Larsen, Penny | Jaquish, Cashell E. | Rao, D. C. | Abecasis, Goncalo R. | Assimes, Themistocles L. | Barroso, Inês | Berndt, Sonja I. | Boehnke, Michael | Deloukas, Panos | Fox, Caroline S. | Groop, Leif C. | Hunter, David J. | Ingelsson, Erik | Kaplan, Robert C. | McCarthy, Mark I. | Mohlke, Karen L. | O'Connell, Jeffrey R. | Schlessinger, David | Strachan, David P. | Stefansson, Kari | van Duijn, Cornelia M. | Hirschhorn, Joel N. | Lindgren, Cecilia M. | Heid, Iris M. | North, Kari E. | Borecki, Ingrid B. | Kutalik, Zoltán | Loos, Ruth J. F.
PLoS Genetics  2016;12(6):e1006166.
doi:10.1371/journal.pgen.1006166
PMCID: PMC4927064  PMID: 27355579
20.  Prospective Investigation of Body Mass Index, Colorectal Adenoma, and Colorectal Cancer in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial 
Journal of Clinical Oncology  2013;31(19):2450-2459.
Purpose
Obesity has consistently been linked to an increased risk of colorectal cancer, particularly among men. Whether body mass index (BMI) differentially influences the risk across the stages of colorectal cancer development remains unclear. We evaluated the associations of BMI with colorectal adenoma incidence, adenoma recurrence, and cancer in the context of a large screening trial, in which cases and controls had an equal chance for disease detection.
Methods
We prospectively evaluated the association between baseline BMI and the risk of incident distal adenoma (1,213 cases), recurrent adenoma (752 cases), and incident colorectal cancer (966 cases) among men and women, ages 55 to 74 years, randomly assigned to receive flexible sigmoidoscopy screening as part of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. We calculated odds ratios (ORs) and 95% CIs for adenoma incidence and recurrence, and hazard ratios (HRs) and 95% CIs for colorectal cancer incidence, using multivariable-adjusted models.
Results
Compared with normal-weight men (18.5 to 24.9 kg/m2), obese men (≥ 30 kg/m2) had significantly higher risk of incident adenoma (OR, 1.32; 95% CI, 1.06 to 1.65) and colorectal cancer (HR, 1.48; 95% CI, 1.16 to 1.89) and a borderline increased risk of recurrent adenoma (OR, 1.50; 95% CI, 0.98 to 2.30). No associations were observed for either adenoma or cancer in women.
Conclusion
Data from this large prospective study suggest that obesity is important throughout the natural history of colorectal cancer, at least in men, and colorectal cancer prevention efforts should encourage the achievement and maintenance of a healthy body weight in addition to regular screenings.
doi:10.1200/JCO.2012.48.4691
PMCID: PMC3691360  PMID: 23715565
21.  Female chromosome X mosaicism is age-related and preferentially affects the inactivated X chromosome 
Machiela, Mitchell J. | Zhou, Weiyin | Karlins, Eric | Sampson, Joshua N. | Freedman, Neal D. | Yang, Qi | Hicks, Belynda | Dagnall, Casey | Hautman, Christopher | Jacobs, Kevin B. | Abnet, Christian C. | Aldrich, Melinda C. | Amos, Christopher | Amundadottir, Laufey T. | Arslan, Alan A. | Beane-Freeman, Laura E. | Berndt, Sonja I. | Black, Amanda | Blot, William J. | Bock, Cathryn H. | Bracci, Paige M. | Brinton, Louise A. | Bueno-de-Mesquita, H Bas | Burdett, Laurie | Buring, Julie E. | Butler, Mary A. | Canzian, Federico | Carreón, Tania | Chaffee, Kari G. | Chang, I-Shou | Chatterjee, Nilanjan | Chen, Chu | Chen, Constance | Chen, Kexin | Chung, Charles C. | Cook, Linda S. | Crous Bou, Marta | Cullen, Michael | Davis, Faith G. | De Vivo, Immaculata | Ding, Ti | Doherty, Jennifer | Duell, Eric J. | Epstein, Caroline G. | Fan, Jin-Hu | Figueroa, Jonine D. | Fraumeni, Joseph F. | Friedenreich, Christine M. | Fuchs, Charles S. | Gallinger, Steven | Gao, Yu-Tang | Gapstur, Susan M. | Garcia-Closas, Montserrat | Gaudet, Mia M. | Gaziano, J. Michael | Giles, Graham G. | Gillanders, Elizabeth M. | Giovannucci, Edward L. | Goldin, Lynn | Goldstein, Alisa M. | Haiman, Christopher A. | Hallmans, Goran | Hankinson, Susan E. | Harris, Curtis C. | Henriksson, Roger | Holly, Elizabeth A. | Hong, Yun-Chul | Hoover, Robert N. | Hsiung, Chao A. | Hu, Nan | Hu, Wei | Hunter, David J. | Hutchinson, Amy | Jenab, Mazda | Johansen, Christoffer | Khaw, Kay-Tee | Kim, Hee Nam | Kim, Yeul Hong | Kim, Young Tae | Klein, Alison P. | Klein, Robert | Koh, Woon-Puay | Kolonel, Laurence N. | Kooperberg, Charles | Kraft, Peter | Krogh, Vittorio | Kurtz, Robert C. | LaCroix, Andrea | Lan, Qing | Landi, Maria Teresa | Marchand, Loic Le | Li, Donghui | Liang, Xiaolin | Liao, Linda M. | Lin, Dongxin | Liu, Jianjun | Lissowska, Jolanta | Lu, Lingeng | Magliocco, Anthony M. | Malats, Nuria | Matsuo, Keitaro | McNeill, Lorna H. | McWilliams, Robert R. | Melin, Beatrice S. | Mirabello, Lisa | Moore, Lee | Olson, Sara H. | Orlow, Irene | Park, Jae Yong | Patiño-Garcia, Ana | Peplonska, Beata | Peters, Ulrike | Petersen, Gloria M. | Pooler, Loreall | Prescott, Jennifer | Prokunina-Olsson, Ludmila | Purdue, Mark P. | Qiao, You-Lin | Rajaraman, Preetha | Real, Francisco X. | Riboli, Elio | Risch, Harvey A. | Rodriguez-Santiago, Benjamin | Ruder, Avima M. | Savage, Sharon A. | Schumacher, Fredrick | Schwartz, Ann G. | Schwartz, Kendra L. | Seow, Adeline | Wendy Setiawan, Veronica | Severi, Gianluca | Shen, Hongbing | Sheng, Xin | Shin, Min-Ho | Shu, Xiao-Ou | Silverman, Debra T. | Spitz, Margaret R. | Stevens, Victoria L. | Stolzenberg-Solomon, Rachael | Stram, Daniel | Tang, Ze-Zhong | Taylor, Philip R. | Teras, Lauren R. | Tobias, Geoffrey S. | Van Den Berg, David | Visvanathan, Kala | Wacholder, Sholom | Wang, Jiu-Cun | Wang, Zhaoming | Wentzensen, Nicolas | Wheeler, William | White, Emily | Wiencke, John K. | Wolpin, Brian M. | Wong, Maria Pik | Wu, Chen | Wu, Tangchun | Wu, Xifeng | Wu, Yi-Long | Wunder, Jay S. | Xia, Lucy | Yang, Hannah P. | Yang, Pan-Chyr | Yu, Kai | Zanetti, Krista A. | Zeleniuch-Jacquotte, Anne | Zheng, Wei | Zhou, Baosen | Ziegler, Regina G. | Perez-Jurado, Luis A. | Caporaso, Neil E. | Rothman, Nathaniel | Tucker, Margaret | Dean, Michael C. | Yeager, Meredith | Chanock, Stephen J.
Nature Communications  2016;7:11843.
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
doi:10.1038/ncomms11843
PMCID: PMC4909985  PMID: 27291797
22.  A Model to Determine Colorectal Cancer Risk Using Common Genetic Susceptibility Loci 
Gastroenterology  2015;148(7):1330-1339.e14.
Background & Aims
Risk for colorectal cancer (CRC) can be greatly reduced through screening. To aid in development of screening strategies, we refined models designed to determine risk of CRC by incorporating information from common genetic susceptibility loci.
Methods
Using data collected from more than 12,000 participants in 6 studies performed from 1990 through 2011 in the United States (US) and Germany, we developed risk determination models based on sex, age, family history, genetic risk score (number of risk alleles carried at 27 validated common CRC susceptibility loci), and history of endoscopic examinations. The model was validated using data collected from approximately 1800 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, conducted from 1993 through 2001 in US.
Results
We identified a CRC genetic risk score that independently predicted which patients in the training set would develop CRC. Compared with determination of risk based only on family history, adding the genetic risk score increased discriminatory accuracy from 0.51 to 0.59 (P=.0028) for men and from 0.52 to 0.56 (P=.14) for women. We calculated age- and sex-specific 10 y CRC absolute risk estimates based on the number of risk alleles, family history, and history of endoscopic examinations. A model that included a genetic risk score better determined the recommended starting age for screening in subjects with and without family histories of CRC. The starting age for high-risk men (family history of CRC and genetic risk score=90%) was 42 y, and for low-risk men (no family history of CRC and genetic risk score=10%) was 52 years. For men with no family history and a high genetic risk score (90%), the starting age would be 47 years; this is an intermediate value that is 5 years earlier than it would be for men with a genetic risk score of 10%. Similar trends were observed in women.
Conclusions
By incorporating information on CRC risk alleles, we created a model to more accurately determine risk for CRC. This model might be used to develop screening and prevention strategies.
doi:10.1053/j.gastro.2015.02.010
PMCID: PMC4446193  PMID: 25683114
Risk determination; genome-wide association study; colorectal cancer screening; risk stratification
23.  Associations between unprocessed red and processed meat, poultry, seafood and egg intake and the risk of prostate cancer: A pooled analysis of 15 prospective cohort studies 
International journal of cancer  2016;138(10):2368-2382.
Reports relating meat intake to prostate cancer risk are inconsistent. Associations between these dietary factors and prostate cancer were examined in a consortium of 15 cohort studies. During follow-up, 52, 683 incident prostate cancer cases, including 4,924 advanced cases, were identified among 842, 149 men. Cox proportional hazard models were used to calculate study-specific relative risks (RR) and then pooled using random effects models. Results do not support a substantial effect of total red, unprocessed red and processed meat for all prostate cancer outcomes, except for a modest positive association for tumors identified as advanced stage at diagnosis (advanced(r)). For seafood, no substantial effect was observed for prostate cancer regardless of stage or grade. Poultry intake was inversely associated with risk of advanced and fatal cancers (pooled multivariable RR [MVRR], 95% confidence interval, comparing ≥45 vs. <5 g/day: advanced 0.83, 0.70–0.99; trend test p value 0.29), fatal, 0.69, 0.59–0.82, trend test p value 0.16). Participants who ate ≥25 versus <5 g/day of eggs (1 egg ~ 50 g) had a significant 14% increased risk of advanced and fatal cancers (advanced 1.14, 1.01–1.28, trend test p value 0.01; fatal 1.14, 1.00–1.30, trend test p value 0.01). When associations were analyzed separately by geographical region (North America vs. other continents), positive associations between unprocessed red meat and egg intake, and inverse associations between poultry intake and advanced, advanced(r) and fatal cancers were limited to North American studies. However, differences were only statistically significant for eggs. Observed differences in associations by geographical region warrant further investigation.
doi:10.1002/ijc.29973
PMCID: PMC4837898  PMID: 26685908
prostate cancer; diet; unprocessed red meat; processed meat; poultry; seafood; egg
24.  A Bayesian Approach to the Overlap Analysis of Epidemiologically Linked Traits 
Genetic Epidemiology  2015;39(8):624-634.
ABSTRACT
Diseases often cooccur in individuals more often than expected by chance, and may be explained by shared underlying genetic etiology. A common approach to genetic overlap analyses is to use summary genome‐wide association study data to identify single‐nucleotide polymorphisms (SNPs) that are associated with multiple traits at a selected P‐value threshold. However, P‐values do not account for differences in power, whereas Bayes’ factors (BFs) do, and may be approximated using summary statistics. We use simulation studies to compare the power of frequentist and Bayesian approaches with overlap analyses, and to decide on appropriate thresholds for comparison between the two methods. It is empirically illustrated that BFs have the advantage over P‐values of a decreasing type I error rate as study size increases for single‐disease associations. Consequently, the overlap analysis of traits from different‐sized studies encounters issues in fair P‐value threshold selection, whereas BFs are adjusted automatically. Extensive simulations show that Bayesian overlap analyses tend to have higher power than those that assess association strength with P‐values, particularly in low‐power scenarios. Calibration tables between BFs and P‐values are provided for a range of sample sizes, as well as an approximation approach for sample sizes that are not in the calibration table. Although P‐values are sometimes thought more intuitive, these tables assist in removing the opaqueness of Bayesian thresholds and may also be used in the selection of a BF threshold to meet a certain type I error rate. An application of our methods is used to identify variants associated with both obesity and osteoarthritis.
doi:10.1002/gepi.21919
PMCID: PMC4832282  PMID: 26411566
Bayes’ factor; P‐value; obesity; osteoarthritis; overlap analysis; threshold calibration
25.  A Genome-wide Pleiotropy Scan for Prostate Cancer Risk 
European urology  2014;67(4):649-657.
Background
No single-nucleotide polymorphisms (SNPs) specific for aggressive prostate cancer have been identified in genome-wide association studies (GWAS).
Objective
To test if SNPs associated with other traits may also affect the risk of aggressive prostate cancer.
Design, setting, and participants
SNPs implicated in any phenotype other than prostate cancer (p ≤ 10−7) were identified through the catalog of published GWAS and tested in 2891 aggressive prostate cancer cases and 4592 controls from the Breast and Prostate Cancer Cohort Consortium (BPC3). The 40 most significant SNPs were followed up in 4872 aggressive prostate cancer cases and 24 534 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.
Outcome measurements and statistical analysis
Odds ratios (ORs) and 95% confidence intervals (CIs) for aggressive prostate cancer were estimated.
Results and limitations
A total of 4666 SNPs were evaluated by the BPC3. Two signals were seen in regions already reported for prostate cancer risk. rs7014346 at 8q24.21 was marginally associated with aggressive prostate cancer in the BPC3 trial (p = 1.6 × 10-6), whereas after meta-analysis by PRACTICAL the summary OR was 1.21 (95%CI 1.16–1.27; p = 3.22 × 10−18). rs9900242 at 17q24.3 was also marginally associated with aggressive disease in the meta-analysis (OR 0.90, 95% CI 0.86–0.94; p = 2.5 × 10−6). Neither of these SNPs remained statistically significant when conditioning on correlated known prostate cancer SNPs. The meta-analysis by BPC3 and PRACTICAL identified a third promising signal, marked by rs16844874 at 2q34, independent of known prostate cancer loci (OR 1.12,95% CI 1.06–1.19; p = 4.67 × 10−5); it has been shown that SNPs correlated with this signal affect glycine concentrations. The main limitation is the heterogeneity in the definition of aggressive prostate cancer between BPC3 and PRACTICAL.
Conclusions
We did not identify new SNPs for aggressive prostate cancer. However, rs16844874 may provide preliminary genetic evidence on the role of the glycine pathway in prostate cancer etiology.
Patient summary
We evaluated whether genetic variants associated with several traits are linked to the risk of aggressive prostate cancer. No new such variants were identified.
doi:10.1016/j.eururo.2014.09.020
PMCID: PMC4359641  PMID: 25277271
Aggressive prostate cancer; Genome-wide association study; Pleiotropy; Single-nucleotide polymorphism; Glycine

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