Mendelian randomization analysis of C-reactive protein on colorectal cancer risk

Background: Chronic inflammation is a risk factor for colorectal cancer (CRC). Circulating C-reactive protein (CRP) is also moderately associated with CRC risk. However, observational studies are susceptible to unmeasured confounding or reverse causality. Using genetic risk variants as instrumental variables, we investigated the causal relationship between genetically elevated CRP concentration and CRC risk, using a Mendelian randomization approach. Methods: Individual-level data from 30 480 CRC cases and 22 844 controls from 33 participating studies in three international consortia were used: the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT) and the Colon Cancer Family Registry (CCFR). As instrumental variables, we included 19 single nucleotide polymorphisms (SNPs) previously associated with CRP concentration. The SNP-CRC associations were estimated using a logistic regression model adjusted for age, sex, principal components and genotyping phases. An inverse-variance weighted method was applied to estimate the causal effect of CRP on CRC risk. Results: Among the 19 CRP-associated SNPs, rs1260326 and rs6734238 were significantly associated with CRC risk (P = 7.5 × 10-4, and P = 0.003, respectively). A genetically predicted one-unit increase in the log-transformed CRP concentrations (mg/l) was not associated with increased risk of CRC [odds ratio (OR) = 1.04; 95% confidence interval (CI): 0.97, 1.12; P = 0.256). No evidence of association was observed in subgroup analyses stratified by other risk factors. Conclusions: In spite of adequate statistical power to detect moderate association, we found genetically elevated CRP concentration was not associated with increased risk of CRC among individuals of European ancestry. Our findings suggested that circulating CRP is unlikely to be a causal factor in CRC development

Discovery of common and rare genetic risk variants for colorectal cancer.

To further dissect the genetic architecture of colorectal cancer (CRC), we performed whole-genome sequencing of 1,439 cases and 720 controls, imputed discovered sequence variants and Haplotype Reference Consortium panel variants into genome-wide association study data, and tested for association in 34,869 cases and 29,051 controls. Findings were followed up in an additional 23,262 cases and 38,296 controls. We discovered a strongly protective 0.3% frequency variant signal at CHD1. In a combined meta-analysis of 125,478 individuals, we identified 40 new independent signals at P < 5 × 10-8, bringing the number of known independent signals for CRC to ~100. New signals implicate lower-frequency variants, Krüppel-like factors, Hedgehog signaling, Hippo-YAP signaling, long noncoding RNAs and somatic drivers, and support a role for immune function. Heritability analyses suggest that CRC risk is highly polygenic, and larger, more comprehensive studies enabling rare variant analysis will improve understanding of biology underlying this risk and influence personalized screening strategies and drug development.Goncalo R Abecasis has received compensation from 23andMe and Helix. He is currently an employee of Regeneron Pharmaceuticals. Heather Hampel performs collaborative research with Ambry Genetics, InVitae Genetics, and Myriad Genetic Laboratories, Inc., is on the scientific advisory board for InVitae Genetics and Genome Medical, and has stock in Genome Medical. Rachel Pearlman has participated in collaborative funded research with Myriad Genetics Laboratories and Invitae Genetics but has no financial competitive interest

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

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.NovartisEli Lilly and CompanyAstraZenecaAbbViePfizer UKCelgeneEisaiGenentechMerck Sharp and DohmeRocheCancer Research UKGovernment of CanadaArray BioPharmaGenome CanadaNational Institutes of HealthEuropean CommissionMinistère de l'Économie, de l’Innovation et des Exportations du QuébecSeventh Framework ProgrammeCanadian Institutes of Health Researc

An original phylogenetic approach identified mitochondrial haplogroup T1a1 as inversely associated with breast cancer risk in BRCA2 mutation carriers

Introduction: Individuals carrying pathogenic mutations in the BRCA1 and BRCA2 genes have a high lifetime risk of breast cancer. BRCA1 and BRCA2 are involved in DNA double-strand break repair, DNA alterations that can be caused by exposure to reactive oxygen species, a main source of which are mitochondria. Mitochondrial genome variations affect electron transport chain efficiency and reactive oxygen species production. Individuals with different mitochondrial haplogroups differ in their metabolism and sensitivity to oxidative stress. Variability in mitochondrial genetic background can alter reactive oxygen species production, leading to cancer risk. In the present study, we tested the hypothesis that mitochondrial haplogroups modify breast cancer risk in BRCA1/2 mutation carriers. Methods: We genotyped 22,214 (11,421 affected, 10,793 unaffected) mutation carriers belonging to the Consortium of Investigators of Modifiers of BRCA1/2 for 129 mitochondrial polymorphisms using the iCOGS array. Haplogroup inference and association detection were performed using a phylogenetic approach. ALTree was applied to explore the reference mitochondrial evolutionary tree and detect subclades enriched in affected or unaffected individuals. Results: We discovered that subclade T1a1 was depleted in affected BRCA2 mutation carriers compared with the rest of clade T (hazard ratio (HR) = 0.55; 95% confidence interval (CI), 0.34 to 0.88; P = 0.01). Compared with the most frequent haplogroup in the general population (that is, H and T clades), the T1a1 haplogroup has a HR of 0.62 (95% CI, 0.40 to 0.95; P = 0.03). We also identified three potential susceptibility loci, including G13708A/rs28359178, which has demonstrated an inverse association with familial breast cancer risk. Conclusions: This study illustrates how original approaches such as the phylogeny-based method we used can empower classical molecular epidemiological studies aimed at identifying association or risk modification effects.Peer reviewe

Genome-wide association study of germline variants and breast cancer-specific mortality

BACKGROUND: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. METHODS: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10

Mendelian randomization analysis of C-reactive protein on colorectal cancer risk.

BACKGROUND: Chronic inflammation is a risk factor for colorectal cancer (CRC). Circulating C-reactive protein (CRP) is also moderately associated with CRC risk. However, observational studies are susceptible to unmeasured confounding or reverse causality. Using genetic risk variants as instrumental variables, we investigated the causal relationship between genetically elevated CRP concentration and CRC risk, using a Mendelian randomization approach. METHODS: Individual-level data from 30 480 CRC cases and 22 844 controls from 33 participating studies in three international consortia were used: the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO), the Colorectal Transdisciplinary Study (CORECT) and the Colon Cancer Family Registry (CCFR). As instrumental variables, we included 19 single nucleotide polymorphisms (SNPs) previously associated with CRP concentration. The SNP-CRC associations were estimated using a logistic regression model adjusted for age, sex, principal components and genotyping phases. An inverse-variance weighted method was applied to estimate the causal effect of CRP on CRC risk. RESULTS: Among the 19 CRP-associated SNPs, rs1260326 and rs6734238 were significantly associated with CRC risk (P = 7.5 × 10-4, and P = 0.003, respectively). A genetically predicted one-unit increase in the log-transformed CRP concentrations (mg/l) was not associated with increased risk of CRC [odds ratio (OR) = 1.04; 95% confidence interval (CI): 0.97, 1.12; P = 0.256). No evidence of association was observed in subgroup analyses stratified by other risk factors. CONCLUSIONS: In spite of adequate statistical power to detect moderate association, we found genetically elevated CRP concentration was not associated with increased risk of CRC among individuals of European ancestry. Our findings suggested that circulating CRP is unlikely to be a causal factor in CRC development.GECCO (Genetics and Epidemiology of Colorectal Cancer Consortium) is supported by the National Cancer Institute (NCI), National Institutes of Health (NIH), U.S. Department of Health and Human Services (U01 CA137088; R01 CA059045; U01 CA164930). ASTERISK was funded by a Hospital Clinical Research Program (PHRC-BRD09/C) from the University Hospital Center of Nantes (CHU de Nantes) and supported by the Regional Council of Pays de la Loire, the Groupement des Entreprises Françaises dans la Lutte Contre le Cancer (GEFLUC), the Association Anne de Bretagne Génétique and the Ligue Régionale Contre le Cancer (LRCC). COLO2&3 (Hawai’i Colorectal Cancer Studies 2 & 3) is supported by the NIH (R01 CA60987). DACHS (Darmkrebs: Chancen der Verhutüng durch Screening) was supported by the German Research Council (BR 1704/6-1, BR 1704/6-3, BR 1704/6-4, CH 117/1-1, HO 5117/2-1, HE 5998/2-1, KL 2354/3-1, RO 2270/8-1 and BR 1704/17-1), the Interdisciplinary Research Program of the National Center for Tumor Diseases (NCT), Germany, and the German Federal Ministry of Education and Research (01KH0404, 01ER0814, 01ER0815, 01ER1505A and 01ER1505B). DALS (Diet, Activity and Lifestyle Survey) is supported by the NIH (R01 CA48998 to P.A. Slattery). HPFS (Health Professionals Follow-up Study) is supported by the NIH (P01 CA055075, UM1 CA167552, R01 CA137178, R01 CA151993, R35 CA197735, K07 CA190673, and P50 CA127003), NHS (Nurses’ Health Study) by the NIH (R01 CA137178, P01 CA087969, UM1 CA186107, R01 CA151993, R35 CA197735, K07 CA190673, and P50 CA127003) and PHS (Physician’s Health Study) by the NIH (R01 CA042182). MEC (Multiethnic Cohort Study) is supported by the NIH (R37 CA54281, P01 CA033619, and R01 CA63464). OFCCR (the Ontario Registry for Studies of Familial Colorectal Cancer) was supported by NIH (U01 CA074783; see CCFR section above), and additional funding toward genetic analyses of OFCCR was supported by a GL2 grant from the Ontario Research Fund, Canadian Institutes of Health Research and a Cancer Risk Evaluation (CaRE) Program grant from the Canadian Cancer Society Research Institute. PLCO (Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial) is supported by the Intramural Research Program of the Division of Cancer Epidemiology and Genetics and supported by contracts from the Division of Cancer Prevention, National Cancer Institute, NIH, DHHS. PMH-CCFR (Postmenopausal Hormone Study-Colon Cancer Family Registry) is supported by the NIH (R01 CA076366 to P.A. Newcomb). VITAL (VITamins And Lifestyle) is supported by the NIH (K05 CA154337 to E.White). WHI (Women’s Health Initiative) is supported by the National Heart, Lung, and Blood Institute, National Institutes of Health, U.S. Department of Health and Human Services through contracts HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, and HHSN271201100004C. X.Wang and E. White were also supported by the NCI (R25 CA094880). CORECT (the Colorectal Transdisciplinary Study) is supported by the NCI under RFA # CA-09-002 as part of the GAME-ON consortium (US NIH, U19 CA148107) with additional support from the NCI grants (R01 CA81488 and P30 CA14089), the National Human Genome Research Institute at the US NIH (T32 HG000040) and the National Institute of Environmental Health Sciences at the US NIH (T32 ES013678). The content of this manuscript does not necessarily reflect the views or policies of the National Cancer Institute or any of the collaborating centers in CORECT, nor does mention of trade names, commercial products, or organizations imply endorsement by the US Government or CORECT. CCFR (the Colon Cancer Family Registry) is supported by grant UM1 CA167551 from the US NCI and through cooperative agreements with members of the CCFR and principal investigators of the Australasian Colorectal Cancer Family Registry (US NIH, U01 CA074778 and U01/U24 CA097735), University of South California Consortium Colorectal Cancer Family Registry for Colon Cancer Studies (US NIH, U01/U24 CA074799), the Mayo Clinic Cooperative Family Registry for Colon Cancer Studies (US NIH, U01/U24 CA074800), Ontario Registry for Studies of Familial Colorectal Cancer (US NIH, U01/U24 CA074783), Seattle Colorectal Cancer Family Registry (US NIH, U01/U24 CA074794), and the University of Hawaii Colorectal Cancer Family Registry (US NIH, U01/U24 CA074806). The Colon CFR Illumina GWAS was supported by NCI/NIH grant U01 CA122839 and R01 CA143237 to G Casey. CPSII (the Cancer Prevention Study-II Nutrition Cohort) is funded by the American Cancer Society. MECC was supported by the NIH, U.S. Department of Health and Human Services (R01 CA81488 to SB Gruber and G Rennert). The MCCS cohort recruitment was funded by VicHealth and Cancer Council Victoria, GALEON: FIS Intrasalud (PI13/01136). The MCCS was further supported by Australian NHMRC grants 509348, 209057, 251553 and 504711, and by infrastructure provided by Cancer Council Victoria. The NFCCR (Newfoundland Colorectal Cancer Registry) was supported by an Interdisciplinary Health Research Team award from the Canadian Institutes of Health Research (CRT 43821); the NIH, U.S. Department of Health and Human Serivces (U01 CA74783); and National Cancer Institute of Canada grants (18223 and 18226). The Kentucky study was supported by the US NCI R01 CA136726, and the Clinical Investigator Award from Damon Runyon Cancer Research Foundation (CI-8). The Spain study was supported by Instituto de Salud Carlos III, co-funded by FEDER funds –a way to build Europe– grants PI14-613 and PI09-1286. SEARCH was supported by the Cancer Research UK (C490/A16561). The Sweden-Wolk was supported by grants from the Swedish Research Council/Infrastructure grant, the Swedish Cancer Foundation and Karolinska Institute’s Distinguished Professor Award to Alicja Wolk. The ATBC Study is supported by the Intramural Research Program of the U.S. NCI and by U.S. Public Health Service contract HHSN261201500005C from the NCI, Department of Health and Human Services. The ColoCare-heidelberg and the ColoCare-Seattle studies were funded by the US NIH (grants 2P30CA015704-40, R01 CA189184 and U01 CA152756), the Matthias Lackas-Foundation, the German Consortium for Translational Cancer Research, and the EU TRANSCAN initiative. ESTER_VERDI was supported by grants from the Baden-Wϋrttemberg Ministry of Science. The work at MSKCC (Memorial Sloan Kettering Cancer Center in New York) was supported by the Robert and Kate Niehaus Center for Inherited Cancer Genomics and the Romeo Milio Foundation. D. Buchanan is also supported by University of Melbourne Research at Melbourne Accelerator Program (R@MAP) and NHMRC R.D. Wright Career Development Fellowship. Dr. M. Song was supported by the American Cancer Society (Grant number MRSG-17-220-01 – NEC to M.S.); by the 2017 AACR-AstraZeneca Fellowship in Immuno-oncology Research (Grant Number 17-40-12-SONG to M.S.); by the U.S. National Institutes of Health (NIH) grants [K99 CA215314 to M.S.]

Increased risk of lung cancer in individuals with a family history of the disease: A pooled analysis from the International Lung Cancer Consortium

Familial aggregation of lung cancer exists after accounting for cigarette smoking. However, the extent to which family history affects risk by smoking status, histology, relative type and ethnicity is not well described. This pooled analysis included 24 case-control studies in the International Lung Cancer Consortium. Each study collected age of onset/interview, gender, race/ethnicity, cigarette smoking, histology and first-degree family history of lung cancer. Data from 24,380 lung cancer cases and 23,305 healthy controls were analysed. Unconditional logistic regression models and generalised estimating equations were used to estimate odds ratios and 95% confidence intervals. Individuals with a first-degree relative with lung cancer had a 1.51-fold increase in the risk of lung cancer, after adjustment for smoking and other potential confounders (95% CI: 1.39, 1.63). The association was strongest for those with a family history in a sibling, after adjustment (odds ratios (OR)=1.82, 95% CI: 1.62, 2.05). No modifying effect by histologic type was found. Never smokers showed a lower association with positive familial history of lung cancer (OR=1.25, 95% CI: 1.03, 1.52), slightly stronger for those with an affected sibling (OR=1.44, 95% CI: 1.07, 1.93), after adjustment. The occurrence of lung cancer among never smokers and similar magnitudes of the effect of family history on lung cancer risk across histological types suggests familial aggregation of lung cancer is independent of those risks associated with cigarette smoking. While the role of genetic variation in the aetiology of lung cancer remains to be fully characterised, family history assessment is immediately available and those with a positive history represent a higher risk group

Increased risk of lung cancer in individuals with a family history of the disease: A pooled analysis from the International Lung Cancer Consortium

Background and methods: Familial aggregation of lung cancer exists after accounting for cigarette smoking. However, the extent to which family history affects risk by smoking status, histology, relative type and ethnicity is not well described. This pooled analysis included 24 case-control studies in the International Lung Cancer Consortium. Each study collected age of onset/interview, gender, race/ethnicity, cigarette smoking, histology and first-degree family history of lung cancer. Data from 24,380 lung cancer cases and 23,305 healthy controls were analysed. Unconditional logistic regression models and generalised estimating equations were used to estimate odds ratios and 95% confidence intervals. Results: Individuals with a first-degree relative with lung cancer had a 1.51-fold increase in the risk of lung cancer, after adjustment for smoking and other potential confounders (95% CI: 1.39, 1.63). The association was strongest for those with a family history in a sibling, after adjustment (odds ratios (OR) = 1.82, 95% CI: 1.62, 2.05). No modifying effect by histologic type was found. Never smokers showed a lower association with positive familial history of lung cancer (OR = 1.25, 95% CI: 1.03, 1.52), slightly stronger for those with an affected sibling (OR = 1.44, 95% CI: 1.07, 1.93), after adjustment. Conclusions: The occurrence of lung cancer among never smokers and similar magnitudes of the effect of family history on lung cancer risk across histological types suggests familial aggregation of lung cancer is independent of those risks associated with cigarette smoking. While the role of genetic variation in the aetiology of lung cancer remains to be fully characterised, family history assessment is immediately available and those with a positive history represent a higher risk group

Genome-wide association study of germline variants and breast cancer-specific mortality

Abstract Background: We examined the associations between germline variants and breast cancer mortality using a large meta-analysis of women of European ancestry. Methods: Meta-analyses included summary estimates based on Cox models of twelve datasets using ~10.4 million variants for 96,661 women with breast cancer and 7697 events (breast cancer-specific deaths). Oestrogen receptor (ER)-specific analyses were based on 64,171 ER-positive (4116) and 16,172 ER-negative (2125) patients. We evaluated the probability of a signal to be a true positive using the Bayesian false discovery probability (BFDP). Results: We did not find any variant associated with breast cancer-specific mortality at P &lt; 5 × 10−8. For ER-positive disease, the most significantly associated variant was chr7:rs4717568 (BFDP = 7%, P = 1.28 × 10−7, hazard ratio [HR] = 0.88, 95% confidence interval [CI] = 0.84–0.92); the closest gene is AUTS2. For ER-negative disease, the most significant variant was chr7:rs67918676 (BFDP = 11%, P = 1.38 × 10−7, HR = 1.27, 95% CI = 1.16–1.39); located within a long intergenic non-coding RNA gene (AC004009.3), close to the HOXA gene cluster. Conclusions: We uncovered germline variants on chromosome 7 at BFDP &lt; 15% close to genes for which there is biological evidence related to breast cancer outcome. However, the paucity of variants associated with mortality at genome-wide significance underpins the challenge in providing genetic-based individualised prognostic information for breast cancer patients

Polygenic risk scores for prediction of breast cancer and breast cancer subtypes

Abstract 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