Melbourne School of Population and Global Health - Research Publications

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    Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
    Li, S ; MacInnis, RJ ; Lee, A ; Nguyen-Dumont, T ; Dorling, L ; Carvalho, S ; Dite, GS ; Shah, M ; Luccarini, C ; Wang, Q ; Milne, RL ; Jenkins, MA ; Giles, GG ; Dunning, AM ; Pharoah, PDP ; Southey, MC ; Easton, DF ; Hopper, JL ; Antoniou, AC (CELL PRESS, 2022-10-06)
    Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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    Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
    Li, S ; Nguyen, TL ; Tu, N-D ; Dowty, JG ; Dite, GS ; Ye, Z ; Trinh, HN ; Evans, CF ; Tan, M ; Sung, J ; Jenkins, MA ; Giles, GG ; Hopper, JL ; Southey, MC (MDPI, 2022-06)
    Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.
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    Familial Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
    Nguyen, TL ; Li, S ; Dowty, JG ; Dite, GS ; Ye, Z ; Nguyen-Dumont, T ; Trinh, HN ; Evans, CF ; Tan, M ; Sung, J ; Jenkins, MA ; Giles, GG ; Southey, MC ; Hopper, JL (MDPI, 2022-03)
    Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) for breast cancer based on mammographic density defined in effect by different levels of pixel brightness and adjusted for age and body mass index. We measured these MRS from digitized film mammograms for 593 monozygotic (MZ) and 326 dizygotic (DZ) female twin pairs and 1592 of their sisters. We estimated the correlations in relatives (r) and the proportion of variance due to genetic factors (heritability) using the software FISHER and predicted the familial risk ratio (FRR) associated with each MRS. The ρ estimates ranged from: 0.41 to 0.60 (standard error [SE] 0.02) for MZ pairs, 0.16 to 0.26 (SE 0.05) for DZ pairs, and 0.19 to 0.29 (SE 0.02) for sister pairs (including pairs of a twin and her non-twin sister), respectively. Heritability estimates were 39% to 69% under the classic twin model and 36% to 56% when allowing for shared non-genetic factors specific to MZ pairs. The FRRs were 1.08 to 1.17. These MRSs are substantially familial, due mostly to genetic factors that explain one-quarter to one-half as much of the familial aggregation of breast cancer that is explained by the current best polygenic risk score.
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    Risk factors for melanoma by anatomical site: an evaluation of aetiological heterogeneity
    Laskar, R ; Ferreiro-Iglesias, A ; Bishop, DT ; Iles, MM ; Kanetsky, PA ; Armstrong, BK ; Law, MH ; Goldstein, AM ; Aitken, JF ; Giles, GG ; Robbins, HA ; Cust, AE (WILEY, 2021-06)
    BACKGROUND: Melanoma aetiology has been proposed to have two pathways, which are determined by naevi and type of sun exposure and related to the anatomical site where melanoma develops. OBJECTIVES: We examined associations with melanoma by anatomical site for a comprehensive set of risk factors including pigmentary and naevus phenotypes, ultraviolet radiation exposure and polygenic risk. METHODS: We analysed harmonized data from 2617 people with incident first invasive melanoma and 975 healthy controls recruited through two population-based case-control studies in Australia and the UK. Questionnaire data were collected by interview using a single protocol, and pathway-specific polygenic risk scores were derived from DNA samples. We estimated adjusted odds ratios using unconditional logistic regression that compared melanoma cases at each anatomical site with all controls. RESULTS: When cases were compared with control participants, there were stronger associations for many naevi vs. no naevi for melanomas on the trunk, and upper and lower limbs than on the head and neck (P-heterogeneity < 0·001). Very fair skin (vs. olive/brown skin) was more weakly related to melanoma on the trunk than to melanomas at other sites (P-heterogeneity = 0·04). There was no significant difference by anatomical site for polygenic risk. Increased weekday sun exposure was positively associated with melanoma on the head and neck but not on other sites. CONCLUSIONS: We found evidence of aetiological heterogeneity for melanoma, supporting the dual pathway hypothesis. These findings enhance understanding of risk factors for melanoma and can guide prevention and skin examination education and practices.
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    Mendelian randomisation study of smoking exposure in relation to breast cancer risk
    Park, HA ; Neumeyer, S ; Michailidou, K ; Bolla, MK ; Wang, Q ; Dennis, J ; Ahearn, TU ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Baten, A ; Freeman, LEB ; Becher, H ; Beckmann, MW ; Behrens, S ; Benitez, J ; Bermisheva, M ; Bogdanova, N ; Bojesen, SE ; Brauch, H ; Brenner, H ; Brucker, SY ; Burwinkel, B ; Campa, D ; Canzian, F ; Castelao, JE ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Dork, T ; Dos-Santos-Silva, I ; Dwek, M ; Eccles, DM ; Eliassen, AH ; Engel, C ; Eriksson, M ; Evans, DG ; Fasching, PA ; Flyger, H ; Fritschi, L ; Garcia-Closas, M ; Garcia-Saenz, JA ; Gaudet, MM ; Giles, GG ; Glendon, G ; Goldberg, MS ; Goldgar, DE ; Gonzalez-Neira, A ; Grip, M ; Guenel, P ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Han, S ; Harkness, EF ; Hart, SN ; He, W ; Heemskerk-Gerritsen, BAM ; Hopper, JL ; Hunter, DJ ; Jager, A ; Jakubowska, A ; John, EM ; Jung, A ; Kaaks, R ; Kapoor, PM ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Koppert, LB ; Koutros, S ; Kristensen, VN ; Kurian, AW ; Lacey, J ; Lambrechts, D ; LeMarchand, L ; Lo, W-Y ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; ElenaMartinez, M ; Mavroudis, D ; Meindl, A ; Menon, U ; Milne, RL ; Muranen, TA ; Nevanlinna, H ; Newman, WG ; Nordestgaard, BG ; Offit, K ; Olshan, AF ; Olsson, H ; Park-Simon, T-W ; Peterlongo, P ; Peto, J ; Plaseska-Karanfilska, D ; Presneau, N ; Radice, P ; Rennert, G ; Rennert, HS ; Romero, A ; Saloustros, E ; Sawyer, EJ ; Schmidt, MK ; Schmutzler, RK ; Schoemaker, MJ ; Schwentner, L ; Scott, C ; Shah, M ; Shu, X-O ; Simard, J ; Smeets, A ; Southey, MC ; Spinelli, JJ ; Stevens, V ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Terry, MB ; Tomlinson, I ; Troester, MA ; Truong, T ; Vachon, CM ; van Veen, EM ; Vijai, J ; Wang, S ; Wendt, C ; Winqvist, R ; Wolk, A ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Zheng, W ; Kraft, P ; Chang-Claude, J (SPRINGERNATURE, 2021-10-12)
    BACKGROUND: Despite a modest association between tobacco smoking and breast cancer risk reported by recent epidemiological studies, it is still equivocal whether smoking is causally related to breast cancer risk. METHODS: We applied Mendelian randomisation (MR) to evaluate a potential causal effect of cigarette smoking on breast cancer risk. Both individual-level data as well as summary statistics for 164 single-nucleotide polymorphisms (SNPs) reported in genome-wide association studies of lifetime smoking index (LSI) or cigarette per day (CPD) were used to obtain MR effect estimates. Data from 108,420 invasive breast cancer cases and 87,681 controls were used for the LSI analysis and for the CPD analysis conducted among ever-smokers from 26,147 cancer cases and 26,072 controls. Sensitivity analyses were conducted to address pleiotropy. RESULTS: Genetically predicted LSI was associated with increased breast cancer risk (OR 1.18 per SD, 95% CI: 1.07-1.30, P = 0.11 × 10-2), but there was no evidence of association for genetically predicted CPD (OR 1.02, 95% CI: 0.78-1.19, P = 0.85). The sensitivity analyses yielded similar results and showed no strong evidence of pleiotropic effect. CONCLUSION: Our MR study provides supportive evidence for a potential causal association with breast cancer risk for lifetime smoking exposure but not cigarettes per day among smokers.
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    Association Between Smoking and Molecular Subtypes of Colorectal Cancer
    Wang, X ; Amitay, E ; Harrison, TA ; Banbury, BL ; Berndt, S ; Brenner, H ; Buchanan, DD ; Campbell, PT ; Cao, Y ; Chan, AT ; Chang-Claude, J ; Gallinger, SJ ; Giannakis, M ; Giles, GG ; Gunter, MJ ; Hopper, JL ; Jenkins, MA ; Lin, Y ; Moreno, V ; Nishihara, R ; Newcomb, PA ; Ogino, S ; Phipps, A ; Sakoda, LC ; Schoen, RE ; Slattery, ML ; Song, M ; Sun, W ; Thibodeau, SN ; Toland, AE ; Van Guelpen, B ; Woods, MO ; Hsu, L ; Hoffmeister, M ; Peters, U (OXFORD UNIV PRESS, 2021-08)
    BACKGROUND: Smoking is associated with colorectal cancer (CRC) risk. Previous studies suggested this association may be restricted to certain molecular subtypes of CRC, but large-scale comprehensive analysis is lacking. METHODS: A total of 9789 CRC cases and 11 231 controls of European ancestry from 11 observational studies were included. We harmonized smoking variables across studies and derived sex study-specific quartiles of pack-years of smoking for analysis. Four somatic colorectal tumor markers were assessed individually and in combination, including BRAF mutation, KRAS mutation, CpG island methylator phenotype (CIMP), and microsatellite instability (MSI) status. A multinomial logistic regression analysis was used to assess the association between smoking and risk of CRC subtypes by molecular characteristics, adjusting for age, sex, and study. All statistical tests were 2-sided and adjusted for Bonferroni correction. RESULTS: Heavier smoking was associated with higher risk of CRC overall and stratified by individual markers (P trend < .001). The associations differed statistically significantly between all molecular subtypes, which was the most statistically significant for CIMP and BRAF. Compared with never-smokers, smokers in the fourth quartile of pack-years had a 90% higher risk of CIMP-positive CRC (odds ratio = 1.90, 95% confidence interval = 1.60 to 2.26) but only 35% higher risk for CIMP-negative CRC (odds ratio = 1.35, 95% confidence interval = 1.22 to 1.49; P difference = 2.1 x 10-6). The association was also stronger in tumors that were CIMP positive, MSI high, or KRAS wild type when combined (P difference < .001). CONCLUSION: Smoking was associated with differential risk of CRC subtypes defined by molecular characteristics. Heavier smokers had particularly higher risk of CRC subtypes that were CIMP positive and MSI high in combination, suggesting that smoking may be involved in the development of colorectal tumors via the serrated pathway.
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    DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer
    Joo, JE ; Clendenning, M ; Wong, EM ; Rosty, C ; Mahmood, K ; Georgeson, P ; Winship, IM ; Preston, SG ; Win, AK ; Dugue, P-A ; Jayasekara, H ; English, D ; Macrae, FA ; Hopper, JL ; Jenkins, MA ; Milne, RL ; Giles, GG ; Southey, MC ; Buchanan, DD (MDPI, 2021-06)
    We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50-70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10-16) and young people without CRC (p = 5.8 × 10-6). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.
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    Novel mammogram-based measures improve breast cancer risk prediction beyond an established mammographic density measure
    Nguyen, TL ; Schmidt, DF ; Makalic, E ; Maskarinec, G ; Li, S ; Dite, GS ; Aung, YK ; Evans, CF ; Trinh, HN ; Baglietto, L ; Stone, J ; Song, Y-M ; Sung, J ; MacInnis, RJ ; Dugue, P-A ; Dowty, JG ; Jenkins, MA ; Milne, RL ; Southey, MC ; Giles, GG ; Hopper, JL (WILEY, 2021-05-01)
    Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.
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    CYP3A7*1C allele: linking premenopausal oestrone and progesterone levels with risk of hormone receptor-positive breast cancers
    Johnson, N ; Maguire, S ; Morra, A ; Kapoor, PM ; Tomczyk, K ; Jones, ME ; Schoemaker, MJ ; Gilham, C ; Bolla, MK ; Wang, Q ; Dennis, J ; Ahearn, TU ; Andrulis, IL ; Anton-Culver, H ; Antonenkova, NN ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Baynes, C ; Freeman, LEB ; Beckmann, MW ; Benitez, J ; Bermisheva, M ; Blomqvist, C ; Boeckx, B ; Bogdanova, NV ; Bojesen, SE ; Brauch, H ; Brenner, H ; Burwinkel, B ; Campa, D ; Canzian, F ; Castelao, JE ; Chanock, SJ ; Chenevix-Trench, G ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Doerk, T ; Eliassen, AH ; Engel, C ; Evans, DG ; Fasching, PA ; Figueroa, J ; Floris, G ; Flyger, H ; Gago-Dominguez, M ; Gapstur, SM ; Garcia-Closas, M ; Gaudet, MM ; Giles, GG ; Goldberg, MS ; Gonzalez-Neira, A ; Guenel, P ; Hahnen, E ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Harrington, PA ; Hart, SN ; Hooning, MJ ; Hopper, JL ; Howell, A ; Hunter, DJ ; Jager, A ; Jakubowska, A ; John, EM ; Kaaks, R ; Keeman, R ; Khusnutdinova, E ; Kitahara, CM ; Kosma, V-M ; Koutros, S ; Kraft, P ; Kristensen, VN ; Kurian, AW ; Lambrechts, D ; Le Marchand, L ; Linet, M ; Lubinski, J ; Mannermaa, A ; Manoukian, S ; Margolin, S ; Martens, JWM ; Mavroudis, D ; Mayes, R ; Meindl, A ; Milne, RL ; Neuhausen, SL ; Nevanlinna, H ; Newman, WG ; Nielsen, SF ; Nordestgaard, BG ; Obi, N ; Olshan, AF ; Olson, JE ; Olsson, H ; Orban, E ; Park-Simon, T-W ; Peterlongo, P ; Plaseska-Karanfilska, D ; Pylkas, K ; Rennert, G ; Rennert, HS ; Ruddy, KJ ; Saloustros, E ; Sandler, DP ; Sawyer, EJ ; Schmutzler, RK ; Scott, C ; Shu, X-O ; Simard, J ; Smichkoska, S ; Sohn, C ; Southey, MC ; Spinelli, JJ ; Stone, J ; Tamimi, RM ; Taylor, JA ; Tollenaar, RAEM ; Tomlinson, I ; Troester, MA ; Truong, T ; Vachon, CM ; van Veen, EM ; Wang, SS ; Weinberg, CR ; Wendt, C ; Wildiers, H ; Winqvist, R ; Wolk, A ; Zheng, W ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Howie, AF ; Peto, J ; dos-Santos-Silva, I ; Swerdlow, AJ ; Chang-Claude, J ; Schmidt, MK ; Orr, N ; Fletcher, O (SPRINGERNATURE, 2021-02-16)
    BACKGROUND: Epidemiological studies provide strong evidence for a role of endogenous sex hormones in the aetiology of breast cancer. The aim of this analysis was to identify genetic variants that are associated with urinary sex-hormone levels and breast cancer risk. METHODS: We carried out a genome-wide association study of urinary oestrone-3-glucuronide and pregnanediol-3-glucuronide levels in 560 premenopausal women, with additional analysis of progesterone levels in 298 premenopausal women. To test for the association with breast cancer risk, we carried out follow-up genotyping in 90,916 cases and 89,893 controls from the Breast Cancer Association Consortium. All women were of European ancestry. RESULTS: For pregnanediol-3-glucuronide, there were no genome-wide significant associations; for oestrone-3-glucuronide, we identified a single peak mapping to the CYP3A locus, annotated by rs45446698. The minor rs45446698-C allele was associated with lower oestrone-3-glucuronide (-49.2%, 95% CI -56.1% to -41.1%, P = 3.1 × 10-18); in follow-up analyses, rs45446698-C was also associated with lower progesterone (-26.7%, 95% CI -39.4% to -11.6%, P = 0.001) and reduced risk of oestrogen and progesterone receptor-positive breast cancer (OR = 0.86, 95% CI 0.82-0.91, P = 6.9 × 10-8). CONCLUSIONS: The CYP3A7*1C allele is associated with reduced risk of hormone receptor-positive breast cancer possibly mediated via an effect on the metabolism of endogenous sex hormones in premenopausal women.
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    Genetic architectures of proximal and distal colorectal cancer are partly distinct
    Huyghe, JR ; Harrison, TA ; Bien, SA ; Hampel, H ; Figueiredo, JC ; Schmit, SL ; Conti, D ; Chen, S ; Qu, C ; Lin, Y ; Barfield, R ; Baron, JA ; Cross, AJ ; Diergaarde, B ; Duggan, D ; Harlid, S ; Imaz, L ; Kang, HM ; Levine, DM ; Perduca, V ; Perez-Cornago, A ; Sakoda, LC ; Schumacher, FR ; Slattery, ML ; Toland, AE ; van Duijnhoven, FJB ; Van Guelpen, B ; Agudo, A ; Albanes, D ; Alonso, MH ; Anderson, K ; Arnau-Collell, C ; Arndt, V ; Banbury, BL ; Bassik, MC ; Berndt, S ; Bezieau, S ; Bishop, DT ; Boehm, J ; Boeing, H ; Boutron-Ruault, M-C ; Brenner, H ; Brezina, S ; Buch, S ; Buchanan, DD ; Burnett-Hartman, A ; Caan, BJ ; Campbell, PT ; Carr, PR ; Castells, A ; Castellvi-Bel, S ; Chan, AT ; Chang-Claude, J ; Chanock, SJ ; Curtis, KR ; de la Chapelle, A ; Easton, DF ; English, DR ; Feskens, EJM ; Gala, M ; Gallinger, SJ ; Gauderman, WJ ; Giles, GG ; Goodman, PJ ; Grady, WM ; Grove, JS ; Gsur, A ; Gunter, MJ ; Haile, RW ; Hampe, J ; Hoffmeister, M ; Hopper, JL ; Hsu, W-L ; Huang, W-Y ; Hudson, TJ ; Jenab, M ; Jenkins, MA ; Joshi, AD ; Keku, TO ; Kooperberg, C ; Kuhn, T ; Kury, S ; Le Marchand, L ; Lejbkowicz, F ; Li, C ; Li, L ; Lieb, W ; Lindblom, A ; Lindor, NM ; Mannisto, S ; Markowitz, SD ; Milne, RL ; Moreno, L ; Murphy, N ; Nassir, R ; Offit, K ; Ogino, S ; Panico, S ; Parfrey, PS ; Pearlman, R ; Pharoah, PDP ; Phipps, A ; Platz, EA ; Potter, JD ; Prentice, RL ; Qi, L ; Raskin, L ; Rennert, G ; Rennert, HS ; Riboli, E ; Schafmayer, C ; Schoen, RE ; Seminara, D ; Song, M ; Su, Y-R ; Tangen, CM ; Thibodeau, SN ; Thomas, DC ; Trichopoulou, A ; Ulrich, CM ; Visvanathan, K ; Vodicka, P ; Vodickova, L ; Vymetalkova, V ; Weigl, K ; Weinstein, SJ ; White, E ; Wolk, A ; Woods, MO ; Wu, AH ; Abecasis, GR ; Nickerson, DA ; Scacheri, PC ; Kundaje, A ; Casey, G ; Gruber, SB ; Hsu, L ; Moreno, V ; Hayes, RB ; Newcomb, PA ; Peters, U (BMJ PUBLISHING GROUP, 2021-07)
    OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.