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Conti, David V

0000-0002-2941-7833

Mayo Clinic

Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, California.

Citations 33

Abstract LB390: Genetic risk of prostate cancer: Insights from the Prostate Cancer Sequencing Consortium
Zhang, Yifan , Cheng, Shuyan , Boddicker, Nicholas, Lebo, Matthew , Berry, Alexander S. , Hausler, Ryan , Desai, Heena, Rodriguez, Alex A , Hill, Andrew, Sheng, Xin, Gundell, Susan, Cicek, Mine S., Gignoux, Chris , Garraway, Isla P. , Pasaniuc, Bogdan, Oetjens, Matt, Kibel, Adam S., Kote-Jarai, Zsofia, Couch, Fergus J., Darst, Burcu F., Conti, David V., Haiman, Christopher A., Chen, F Z, Conti, David V. , Conti, David V , Boddicker, Nicholas , Haas, Roni , Dadaev, Tokhir , Desai, Heena , Madduri, Ravi , Sheng, Xin , Lilja, Hans , Melander, Olle , Paşaniuc, Bogdan , Boutros, Paul C. , Oetjens, Matthew T. , Kibel, Adam S. , Klein, Robert J. , Kote‐Jarai, Zsofia , Couch, Fergus J. , Maxwell, Kara N. , Darst, Burcu F. , Haiman, Christopher A.

Cancer Research | April 17, 2026 | Volume: 86 | Issue: 8_Supplement | Pages: LB390-LB390

10.1158/1538-7445.am2026-lb390 Get It

Abstract Inherited susceptibility plays a critical role in prostate cancer (PCa) risk. Using large biobank and case-control datasets, we evaluated the contribution of both common variants and rare germline pathogenic variants (PVs) to overall PCa risk. The Prostate Cancer Exome Sequencing Consortium currently includes 427,388 male participants (51,452 PCa cases and 375,936 controls) with whole-exome sequencing data from ten biobanks and studies: UK Biobank (14,669 cases/195,600 controls), All of Us Research Program (7,577/75,226), African Ancestry Prostate Cancer Consortium (7,176/4,675), Mayo Clinic Biobank (6,031/15,084), Mass General Brigham Biobank (3,393/14,095), Geisinger’s MyCode Community Health Initiative (3,026/15,130), UCLA ATLAS Precision Medicine Biobank (2,850/16,904), Penn Medicine Biobank (2,598/16,255), Colorado Center for Personalized Medicine (2,269/13,399), and Malmo Diet and Cancer (1,863/9,568). Based on self-reported race/ethnicity and estimated genetic ancestry, the cases comprise approximately 79% European, 18% African, and 3% other ancestry populations. Single-variant association analyses tested all variants on chromosomes 1-22 and X with a minor allele count ≥ 5. In gene-based analyses, PVs were defined as rare variants (minor allele frequency [MAF] < 1% in controls) that had either a Variant Effect Predictor (VEP) impact score of “high” or a pathogenic or likely pathogenic ClinVar classification. Associations were estimated using Firth logistic regression, adjusting for age and the top ten genetic principal components. Results from individual studies were combined using fixed-effect meta-analysis. In single-variant association analyses, 496 variants reached genome-wide significance (p<5×10-8; MAF>0.02%). Among these, 458 (92%) variants mapped to previously known risk regions, including three rare PVs in HOXB13 (rs138213197), CHEK2 (rs555607708), and FAM111A (rs533676902). Characterization of the remaining 38 variants is ongoing. Gene-based analyses identified significant associations (p<2.4×10-6) for eight genes: HOXB13 (OR=3.7, 95% CI=3.3-4.2), BRCA2 (OR=2.0, 95% CI=1.7-2.3), CHEK2 (OR=1.6, 95% CI=1.5-1.8), ATM (OR=1.6, 95% CI=1.4-1.9), FAM111A (OR=1.4, 95% CI=1.3-1.5), BIK (OR=1.4, 95% CI=1.2-1.6), SAMHD1 (OR=2.1, 95% CI=1.6-2.7), and SMOC2 (OR=3.2, 95% CI=2.0-5.1). All genes except SMOC2 have been previously implicated in PCa susceptibility. Among cancer predisposition and DNA repair genes, nominal associations were also observed for XRCC2 (OR=1.6, 95% CIs=1.2-2.3) and BRCA1 (OR=1.2, 95% CI=1.0-1.4), whereas the association was not significant for PALB2 (OR=1.2, 95% CI=0.9-1.5). These findings reinforce the role of rare germline PVs, particularly in cancer predisposition and DNA repair genes, in PCa susceptibility. As additional studies are incorporated into the Consortium, we expect this work to provide a more comprehensive characterization of the genetic architecture of PCa. Citation Format: Yifan Zhang, Shuyan Cheng, Nicholas Boddicker, Matthew Lebo, Alexander S. Berry, Roni Haas, Ryan Hausler, Tokhir Dadaev, Heena Desai, Alex A. Rodriguez, Ravi K. Madduri, Andrew Hill, Xin Sheng, Susan M. Gundell, Mine Cicek, Penn Medicine Biobank, Olle Melander, Chris R. Gignoux, Isla P. Garraway, Bogdan Pasaniuc, Paul C. Boutros, Matt Oetjens, Adam S. Kibel, Robert J. Klein, Zsofia Kote-Jarai, Fergus J. Couch, Kara N. Maxwell, Burcu F. Darst, David V. Conti, Christopher A. Haiman, Fei Chen. Genetic risk of prostate cancer: Insights from the Prostate Cancer Sequencing Consortium [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2026; Part 2 (Late-Breaking, Clinical Trial, and Invited Abstracts); 2026 Apr 17-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2026;86(8_Suppl):Abstract nr LB390.
Polygenic Risk Score Modifies Prostate Cancer Risk of Pathogenic Variants in Men of African Ancestry
Hughley, Raymond W. , Matejcic, Marco , Song, Ziwei , Sheng, Xin , Wan, Peggy , Xia, Lucy , Hart, Steven N. , Yadav, Siddhartha , Lubmawa, Alexander, Kiddu, Vicky , Asiimwe, Frank , Amanya, Colline , Mutema, George , Job, Kuteesa , Ssebakumba, Mbaaga K. , Hamilton, Ann S. , Watya, Stephen , Haiman, Christopher A. , Hu, Chunling , Yadav, Siddhartha , Lubmawa, Alexander , Kiddu, Vicky , Asiimwe, Frank , Amanya, Colline , Mutema, George , Job, Kuteesa , Ssebakumba, Mbaaga K , Ingles, Sue A. , Hamilton, Ann S , Couch, Fergus J. , Watya, Stephen , Conti, David V , Darst, Burcu F , Haiman, Christopher A , Hart, Steven N , Hu, Chunling , Couch, Fergus J. , Conti, David V. , Darst, Burcu F.

Cancer Research Communications | November 28, 2023 | Volume: 3 | Issue: 12 | Pages: 2544-2550

10.1158/2767-9764.crc-23-0022 Get It

Abstract Prostate cancer risk is influenced by rare and common germline variants. We examined the aggregate association of rare germline pathogenic/likely pathogenic/deleterious (P/LP/D) variants in ATM, BRCA2, PALB2, and NBN with a polygenic risk score (PRS) on prostate cancer risk among 1,796 prostate cancer cases (222 metastatic) and 1,424 controls of African ancestry. Relative to P/LP/D non-carriers at average genetic risk (33%–66% of PRS), men with low (0%–33%) and high (66%–100%) PRS had Odds Ratios (ORs) for overall prostate cancer of 2.08 [95% confidence interval (CI) = 0.58–7.49] and 18.06 (95% CI = 4.24–76.84) among P/LP/D carriers and 0.57 (95% CI = 0.46–0.71) and 3.02 (95% CI = 2.53–3.60) among non-carriers, respectively. The OR for metastatic prostate cancer was 2.73 (95% CI = 0.24–30.54) and 28.99 (95% CI = 4.39–191.43) among P/LP/D carriers and 0.54 (95% CI = 0.31–0.95) and 3.22 (95% CI = 2.20–4.73) among non-carriers, for men with low and high PRS, respectively. Lifetime absolute risks of overall prostate cancer increased with PRS (low to high) from 9.8% to 51.5% in P/LP/D carriers and 5.5% to 23.9% in non-carriers. Lifetime absolute risks of metastatic prostate cancer increased with PRS from 1.9% to 18.1% in P/LP/D carriers and 0.3% to 2.2% in non-carriers These findings suggest that assessment of prostate cancer risk for rare variant carriers should include PRS status. Significance: These findings highlight the importance of considering rare and common variants to comprehensively assess prostate cancer risk in men of African ancestry.
A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
Aglago, Elom K. , Kim, Andre E. , Lin, Yi , Qu, Conghui , Evangelou, Marina , Yu, Ren , Morrison, John L. , Albanes, Demetrius , Arndt, Volker , Barry, Elizabeth L. , Baurley, James W. , Berndt, Sonja I. , Bishop, D. Timothy , Bouras, Emmanouil , Brenner, Hermann , Casey, Graham , Chang‐Claude, Jenny , Díez‐Obrero, Virginia , Figueiredo, Jane C. , Gallinger, Steven , Gruber, Stephen B. , Gsur, Andrea , Harlid, Sophia , Harrison, Tabitha A. , Hoffmeister, Michael , Huyghe, Jeroen R. , Jordahl, Kristina M. , Joshi, Amit D. , Kundaje, Anshul , Li, Li , Mandic, Marko , Obón‐Santacana, Mireia , Nan, Hongmei , Nassir, Rami , Ose, Jennifer , Pai, Rish K. , Papadimitriou, Nikos , Prentice, Ross L. , Scacheri, Peter C. , Schmit, Stephanie L. , Slattery, Martha L. , Thibodeau, Stephen N. , Thomas, Duncan C. , Duijnhoven, Fränzel J.B. van , Guelpen, Bethany Van , Visvanathan, Kala , Vodička, Pavel , White, Emily , Woods, Michael O. , Wu, Anna H. , Zemlianskaia, Natalia , Gauderman, W. James , Peters, Ulrike , Kim, Andre E , Ren, Yu , Morrison, John L , Bien, Stephanie A , Bishop, D Timothy , Bouras, Emmanouil , Brenner, Hermann , Buchanan, Daniel D , Budiarto, Arif , Carreras-Torres, Robert , Casey, Graham , Cenggoro, Tjeng Wawan , Chan, Andrew T , Chang-Claude, Jenny , Chen, Xuechen , Conti, David V , Devall, Matthew A M , Diez-Obrero, Virginia , Dimou, Niki , Drew, David A , Figueiredo, Jane C , Gallinger, Steven , Giles, Graham G , Gruber, Stephen B , Gsur, Andrea , Gunter, Marc J , Hampel, Heather , Harlid, Sophia , Hidaka, Akihisa , Harrison, Tabitha A , Hoffmeister, Michael , Huyghe, Jeroen R , Jenkins, Mark A , Jordahl, Kristina M , Joshi, Amit D , Kawaguchi, Eric , Keku, Temitope O , Kundaje, Anshul , Larsson, Susanna C , Marchand, Loïc Le , Lewinger, Juan Pablo , Li, Li , Lynch, Brigid M , Mahesworo, Bharuno , Mandic, Marko , Obón-Santacana, Mireia , Moreno, Victor , Murphy, Neil , Nan, Hongmei , Nassir, Rami , Newcomb, Polly A. , Ogino, Shuji , Ose, Jennifer , Pai, R K , Palmer, Julie R , Papadimitriou, Nikos , Pardamean, Bens , Peoples, Anita R , Platz, Elizabeth A. , Potter, John D , Prentice, Ross L , Rennert, Gad , Ruiz-Narvaez, Edward , Sakoda, Lori C , Scacheri, Peter C , Schmit, Stephanie L , Schoen, Robert E , Shcherbina, Anna , Slattery, Martha L , Stern, Mariana Carla , Su, Yu-Ru , Tangen, Catherine M , Thibodeau, Stephen N , Thomas, Duncan C , Tian, Yu , Ulrich, Cornelia M , van Duijnhoven, Fränzel J B , Van Guelpen, Bethany , Visvanathan, Kala , Vodicka, Pavel , Wang, Jun , White, Emily , Wolk, Alicja , Woods, Michael O , Wu, Anna H. , Zemlianskaia, Natalia , Hsu, Li , Gauderman, W James , Peters, Ulrike , Tsilidis, Konstantinos K , Campbell, Peter T , Arndt, Volker , Aglago, Elom K , Albanes, Demetrius , Qu, Conghui , Bien, Stephanie A. , Buchanan, Daniel D. , Carreras‐Torres, Robert , Chan, Andrew T. , Conti, David V. , Dimou, Niki , Drew, David A. , Giles, Graham G. , Gunter, Marc J. , Hampel, Heather , Hidaka, Akihisa , Jenkins, Mark A. , Larsson, Susanna C. , Marchand, Loı̈c Le , Lewinger, Juan Pablo , Moreno, Vı́ctor , Murphy, Neil , Palmer, Julie R. , Pardamean, Bens , Potter, John D. , Rennert, Gad , Sakoda, Lori C. , Schoen, Robert E. , Shcherbina, Anna , Tangen, Catherine M. , Tian, Yu , Ulrich, Cornelia M. , Wolk, Alicja , Tsilidis, Konstantinos K. , Campbell, Peter T.

Cancer Research | May 30, 2023 | Volume: 83 | Issue: 15 | Pages: 2572-2583

10.1158/0008-5472.can-22-3713 Get It

Abstract Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. Significance: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.
Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response
Carreras‐Torres, Robert , Kim, Andre E. , Lin, Yi , Díez‐Obrero, Virginia , Bien, Stephanie A. , Qu, Conghui , Dimou, Niki , Aglago, Elom K. , Albanes, Demetrius , Baurley, James W. , Berndt, Sonja I. , Bishop, D. Timothy , Bouras, Emmanouil , Brenner, Hermann , Casey, Graham , Chang‐Claude, Jenny , Drew, David A. , Figueiredo, Jane C. , Gallinger, Steven , Gruber, Stephen B. , Gsur, Andrea , Harrison, Tabitha A. , Hoffmeister, Michael , Huyghe, Jeroen R. , Jordahl, Kristina M. , Kundaje, Anshul , Li, Li , Nan, Hongmei , Nassir, Rami , Obón‐Santacana, Mireia , Ose, Jennifer , Pai, Rish K. , Papadimitriou, Nikos , Scacheri, Peter C. , Schmit, Stephanie L. , Slattery, Martha L. , Thomas, Duncan C. , Duijnhoven, Fränzel J.B. van , Guelpen, Bethany Van , Visvanathan, Kala , Vodička, Pavel , Weinstein, Stephanie J. , White, Emily , Woods, Michael O. , Peters, Ulrike , Gauderman, W. James , Wang, Jun , Dimou, Niki , Aglago, Elom K , Albanes, Demetrius , Arndt, Volker , Baurley, James W , Berndt, Sonja I , Bézieau, Stéphane , Bishop, D Timothy , Bouras, Emmanouil , Brenner, Hermann , Budiarto, Arif , Campbell, Peter T , Casey, Graham , Chan, Andrew T , Chang-Claude, Jenny , Chen, Xuechen , Conti, David V , Dampier, Christopher H , Devall, Matthew A M , Drew, David A , Figueiredo, Jane C , Gallinger, Steven , Giles, Graham G , Gruber, Stephen B , Gsur, Andrea , Gunter, Marc J , Harrison, Tabitha A , Hidaka, Akihisa , Hoffmeister, Michael , Huyghe, Jeroen R , Jenkins, Mark A , Jordahl, Kristina M , Kawaguchi, Eric , Keku, Temitope O , Kundaje, Anshul , Marchand, Loïc Le , Lewinger, Juan Pablo , Li, Li , Mahesworo, Bharuno , Morrison, John L , Murphy, Neil , Nan, Hongmei , Nassir, Rami , Newcomb, Polly A. , Obón-Santacana, Mireia , Ogino, Shuji , Ose, Jennifer , Pai, R K , Palmer, Julie R , Papadimitriou, Nikos , Pardamean, Bens , Peoples, Anita R , Pharoah, Paul D P , Platz, Elizabeth A. , Rennert, Gad , Ruiz-Narvaez, Edward , Sakoda, Lori C , Scacheri, Peter C , Schmit, Stephanie L , Schoen, Robert E , Shcherbina, Anna , Slattery, Martha L , Stern, Mariana Carla , Su, Yu-Ru , Tangen, Catherine M , Thomas, Duncan C , Tian, Yu , Tsilidis, Konstantinos K , Ulrich, Cornelia M , van Duijnhoven, Fränzel J B , Van Guelpen, Bethany , Visvanathan, Kala , Vodicka, Pavel , Cenggoro, Tjeng Wawan , Weinstein, Stephanie J , White, Emily , Wolk, Alicja , Woods, Michael O , Hsu, Li , Peters, Ulrike , Moreno, Victor , Gauderman, W James , Bien, Stephanie A , Carreras-Torres, Robert , Diez-Obrero, Virginia , Qu, Conghui , Arndt, Volker , Bezieau, Stéphane , Campbell, Peter T. , Chan, Andrew T. , Conti, David V. , Dampier, Christopher H. , Giles, Graham G. , Gunter, Marc J. , Hidaka, Akihisa , Jenkins, Mark A. , Marchand, Loı̈c Le , Lewinger, Juan Pablo , Morrison, John L. , Murphy, Neil , Palmer, Julie R. , Pardamean, Bens , Pharoah, Paul D.P. , Rennert, Gad , Sakoda, Lori C. , Schoen, Robert E. , Shcherbina, Anna , Tangen, Catherine M. , Tian, Yu , Tsilidis, Konstantinos K. , Ulrich, Cornelia M. , Wolk, Alicja , Moreno, Vı́ctor

Cancer Epidemiology, Biomarkers & Prevention | December 28, 2022 | Volume: 32 | Issue: 3 | Pages: 315-328

10.1158/1055-9965.epi-22-0763 Get It

Abstract Background: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. Methods: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. Results: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10−8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20–1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10−8) and 8q24.23 (rs7005722, P = 2.88 × 10−8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09–1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07–1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). Conclusions: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. Impact: These findings can guide potential prevention treatments.
Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region
Jordahl, Kristina M. , Shcherbina, Anna , Kim, Andre E. , Arndt, Volker , Baurley, James W. , Berndt, Sonja I. , Bishop, D. Timothy , Bouras, Emmanouil , Brenner, Hermann , Carreras‐Torres, Robert , Casey, Graham , Conti, David V. , Díez‐Obrero, Virginia , Dimou, Niki , Drew, David A. , Figueiredo, Jane C. , Gallinger, Steven , Gruber, Stephen B. , Gsur, Andrea , Harlid, Sophia , Harrison, Tabitha A. , Hoffmeister, Michael , Huyghe, Jeroen R. , Joshi, Amit D. , Li, Li , Nan, Hongmei , Nassir, Rami , Obón‐Santacana, Mireia , Ose, Jennifer , Pai, Rish K. , Papadimitriou, Nikos , Pardamean, Bens , Prentice, Ross L. , Rennert, Gad , Scacheri, Peter C. , Schmit, Stephanie L. , Slattery, Martha L. , Thibodeau, Stephen N. , Thomas, Duncan C. , Tian, Yu , Tsilidis, Konstantinos K. , Duijnhoven, Fränzel J.B. van , Guelpen, Bethany Van , Visvanathan, Kala , Vodička, Pavel , White, Emily , Woods, Michael O. , Wu, Anna H. , Zemlianskaia, Natalia , Chang‐Claude, Jenny , Gauderman, W. James , Kundaje, Anshul , Peters, Ulrike , Arndt, Volker , Bien, Stephanie A , Bishop, D Timothy , Brenner, Hermann , Buchanan, Daniel D , Campbell, Peter T , Carreras-Torres, Robert , Chan, Andrew T , Dampier, Christopher H , Dimou, Niki , Drew, David A , Figueiredo, Jane C , Giles, Graham G , Gruber, Stephen B , Gsur, Andrea , Gunter, Marc J , Hampel, Heather , Harlid, Sophia , Harrison, Tabitha A , Hidaka, Akihisa , Hoffmeister, Michael , Huyghe, Jeroen R , Larsson, Susanna C , Mahesworo, Bharuno , Moreno, Victor , Morrison, John L , Nassir, Rami , Ogino, Shuji , Ose, Jennifer , Pai, R K , Palmer, Julie R , Peoples, Anita R , Pharoah, Paul D P , Platz, Elizabeth A. , Potter, John D , Rennert, Gad , Ruiz-Narvaez, Edward , Sakoda, Lori C , Schmit, Stephanie L , Schoen, Robert E , Slattery, Martha L , Stern, Mariana Carla , Thomas, Duncan C , Tian, Yu , Tsilidis, Konstantinos K , Ulrich, Cornelia M , van Duijnhoven, Fränzel J B , Van Guelpen, Bethany , Visvanathan, Kala , Wolk, Alicja , Woods, Michael O , Chang-Claude, Jenny , Gauderman, W James , Hsu, Li , Kundaje, Anshul , Peters, Ulrike , Pardamean, Bens , Bouras, Emmanouil , Conti, David V , Nan, Hongmei , Obón-Santacana, Mireia , Papadimitriou, Nikos , Shcherbina, Anna , Vodicka, Pavel , Diez-Obrero, Virginia , Su, Yu-Ru , Lin, Yi , Wang, Jun , Qu, Conghui , Albanes, Demetrius , Bien, Stephanie A. , Buchanan, Daniel D. , Budiarto, Arif , Campbell, Peter T. , Cenggoro, Tjeng Wawan , Chan, Andrew T. , Dampier, Christopher H. , Devall, Matthew A M , Giles, Graham G. , Gunter, Marc J. , Hampel, Heather , Hidaka, Akihisa , Jenkins, Mark A. , Keku, Temitope O , Larsson, Susanna C. , Marchand, Loı̈c Le , Lewinger, Juan Pablo , Moreno, Vı́ctor , Morrison, John L. , Murphy, Neil , Newcomb, Polly A. , Palmer, Julie R. , Pharoah, Paul D.P. , Potter, John D. , Sakoda, Lori C. , Schoen, Robert E. , Tangen, Catherine M. , Ulrich, Cornelia M. , Wolk, Alicja

Cancer Epidemiology, Biomarkers & Prevention | April 19, 2022 | Volume: 31 | Issue: 5 | Pages: 1077-1089

10.1158/1055-9965.epi-21-1003 Get It

Abstract Background: Currently known associations between common genetic variants and colorectal cancer explain less than half of its heritability of 25%. As alcohol consumption has a J-shape association with colorectal cancer risk, nondrinking and heavy drinking are both risk factors for colorectal cancer. Methods: Individual-level data was pooled from the Colon Cancer Family Registry, Colorectal Transdisciplinary Study, and Genetics and Epidemiology of Colorectal Cancer Consortium to compare nondrinkers (≤1 g/day) and heavy drinkers (>28 g/day) with light-to-moderate drinkers (1–28 g/day) in GxE analyses. To improve power, we implemented joint 2df and 3df tests and a novel two-step method that modifies the weighted hypothesis testing framework. We prioritized putative causal variants by predicting allelic effects using support vector machine models. Results: For nondrinking as compared with light-to-moderate drinking, the hybrid two-step approach identified 13 significant SNPs with pairwise r2 > 0.9 in the 10q24.2/COX15 region. When stratified by alcohol intake, the A allele of lead SNP rs2300985 has a dose–response increase in risk of colorectal cancer as compared with the G allele in light-to-moderate drinkers [OR for GA genotype = 1.11; 95% confidence interval (CI), 1.06–1.17; OR for AA genotype = 1.22; 95% CI, 1.14–1.31], but not in nondrinkers or heavy drinkers. Among the correlated candidate SNPs in the 10q24.2/COX15 region, rs1318920 was predicted to disrupt an HNF4 transcription factor binding motif. Conclusions: Our study suggests that the association with colorectal cancer in 10q24.2/COX15 observed in genome-wide association study is strongest in nondrinkers. We also identified rs1318920 as the putative causal regulatory variant for the region. Impact: The study identifies multifaceted evidence of a possible functional effect for rs1318920.
Abstract PO-197: Combined effect of a prostate cancer polygenic risk score and germline pathogenic variants in DNA damage repair genes on prostate cancer risk in men of African ancestry
Matejcic, Marco , Patel, Yesha , Lilyquist, Jenna , Xia, Lucy , Sheng, Xin , Lubmawa, Alexander, Watya, Stephen , Conti, David V. , Haiman, Christopher A. , Conti, David V , Hughley, Raymond W. , Darst, Burcu F. , Hart, Steven N. , Polley, Eric C. , Ingles, Sue A. , Wilkens, Lynne R. , Marchand, Loı̈c Le , Couch, Fergus J.

Cancer Epidemiology, Biomarkers & Prevention | January 11, 2022 | Volume: 31 | Issue: 1_Supplement | Pages: PO-197-PO-197

10.1158/1538-7755.disp21-po-197 Get It

Abstract Introduction: Prostate Cancer (PCa) risk is influenced by both rare germline pathogenic variants (GPVs) in DNA damage repair genes and common variants as measured by polygenic risk scores (PRS) however, the combined effect of GPVs and PRS on PCa risk in men of African ancestry has not been investigated. Methods: We examined the combined effect of rare GPVs and PRS on PCa risk in 1,795 PCa cases and 1,424 controls of African ancestry men from the Multiethnic Cohort, the Los Angeles Study of Aggressive Prostate Cancer, and the Uganda Prostate Cancer Study. GPVs in 19 DNA genes were defined as clinically validated missense variants and variants that alter the protein sequence. The PRS was constructed as a weighted sum of 267 established PCa risk variants. The combined effect of the PRS and GPV status on PCa risk was evaluated using logistic regression models adjusting for age, study, and the first 10 principal components of ancestry to account for population stratification. Results: We identified 91 GPVs carried by 31 controls and 68 cases. Among GPV non-carriers, compared to those with average PRS (33.3-66.7%), odds ratios for PCa ranged from 0.56 (95% CI=0.45-0.70; P=1.2E-7) in low PRS men (0-33.3%) to 3.04 (95% CI=2.54-3.63; P=5.6E-35) in high PRS men (66.7-100%). Among GPV carriers, odds ratios for PCa ranged from 2.09 (95% CI=0.85-5.12; P=0.11) in low PRS men to 5.03 (95% CI=2.37-10.66; P=2.5E-5) in high PRS men, compared to GPV non-carriers with average PRS. Next, we restricted GPVs to ATM, BRCA2, PALB2, and NBN[BD2] (n=51 variants carried by 8 controls and 44 cases), which we previously reported as being the genes most strongly associated with advanced PCa in this population and study sample. Among GPV non-carriers, odds ratios for PCa ranged from 0.56 (95% CI=0.46-0.71; P=2.7E-7) in low PRS men to 5.03 (95% CI=0.85-5.12; P=0.11) in high PRS men, while among GPV carriers, odd ratios for PCa ranged from 2.08 (95% CI=0.58-7.49; P=0.26) in low PRS men to 18.06 (95% CI=4.24-76.84; P=9.0E-5) in high PRS men, compared to average PRS GPV non-carriers. When comparing aggressive cases to controls, considering the top four genes, GPV non-carrier odds ratios for PCa ranged from 0.52 (95% CI=0.40-0.70; P=6.2E-6) in low PRS men to 3.16 (95% CI=2.56-3.91; P=1.6E-26) in high PRS men, while among GPV carriers, odd ratios for PCa ranged from 2.97 (95% CI=073-12.16; P=0.13) in low PRS men to 23.58 (95% CI=5.39-103.20; P=2.7E-5) in high PRS men, compared to average PRS GPV non-carriers. Conclusion: We found that PCa risk in African ancestry men carrying GPVs in DNA damage repair and cancer predisposition genes, particularly ATM, BRCA2, PALB2, and NBN, varied depending on an individual's PRS. This implies that to comprehensively assess genetic risk of PCa, it is important to consider both rare and common variants. These findings could have implications for risk stratification in this high-risk population and emphasize the need for larger genetic studies of PCa in African ancestry men to identify and characterize genetic risk factors in this population. Citation Format: Raymond W. Hughley, Burcu F. Darst, Marco Matejcic, Yesha Patel, Jenna Lilyquist, Steven N. Hart, Eric C. Polley, Lucy Xia, Xin Sheng, Alexander Lubmawa, Sue A. Ingles, Lynne Wilkens, Loïc L. Marchand, Stephen Watya, Fergus J. Couch, David V. Conti, Christopher A. Haiman. Combined effect of a prostate cancer polygenic risk score and germline pathogenic variants in DNA damage repair genes on prostate cancer risk in men of African ancestry [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr PO-197.
Abstract PR05: A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans
Du, Zhaohui , Weinhold, Niels , Song, Gregory, Rand, K.A., Hwang, Amie E. , Sheng, Xin , Hom, Victor, Pawlish, Karen , Peters, Edward , Mohrbacher, Ann, Stram, Alexander , Berndt, Sonja I. , Blot, William J. , Stevens, Victoria L. , Goodman, Phyllis J. , Hennis, Anselm , Nemesure, Barbara , Stanford, Janet L. , Witte, John S. , Signorello, Lisa B., John, Esther M. , Stroup, Antoinette M. , Zangari, Maurizio , Zheng, Wei , Hu, Jennifer J. , Carpten, John D. , Mehta, Jayesh, Wolf, Jeffrey L. , Martin, Thomas G. , Terebelo, Howard R. , Janakiraman, Nalini, Kolonel, Laurence N. , Auclair, Daniel , Vij, Ravi , Bernal‐Mizrachi, Leon , Zonder, Jeffrey A. , Huff, Carol Ann , Conti, David V. , Haiman, Christopher A. , John, Esther M , Zheng, Wei , Conti, David V , Berg, David Van Den , Ailawadhi, Sikander , Nooka, Ajay K. , Singhal, Seema , Bock, Cathryn Hufford , Stram, Alex , Casey, Graham , Kittles, Rick A. , Diver, W. Ryan , Klein, Eric A. , Rybicki, Benjamin A. , Bernstein, Leslie , Stephens, Owen , Rhee, Frits van , Olshan, Andrew F. , Ziegler, Regina G. , Nyante, Sarah J. , Ingles, Sue A. , Press, Michael F. , Chanock, Stephen Jacob , Colditz, Graham A. , Tomasson, Michael H. , Fiala, Mark A. , Anderson, Kenneth C. , Marchand, Loı̈c Le , Chiu, Brian C.‐H. , Ziv, Elad , Stram, Daniel O. , Morgan, Gareth J. , Lonial, Sagar , Orlowski, Robert Z. , Cozen, Wendy

Cancer Epidemiology, Biomarkers & Prevention | September 1, 2020 | Volume: 29 | Issue: 6_Supplement_2 | Pages: PR05-PR05

10.1158/1538-7755.disp19-pr05 Get It

Abstract Background: Persons of African ancestry (AA) experience a 1.5-2-fold risk of multiple myeloma (MM) compared to persons of European ancestry (EA). We assembled a set of MM patients with self-reported AA in order to evaluate the contribution of genetics to etiology in this high-risk group. Methods: Here we present the results of a meta-analysis of two GWAS in 1,813 cases and 8,871 controls of AA. We also conducted an admixture mapping scan to identify risk alleles associated with local ancestry, fine-mapped the 23 known susceptibility loci to find markers that could better capture MM risk in individuals of AA, and constructed a polygenic risk score (PRS) to assess the aggregated effect of known MM risk alleles. Finally, we conducted an eQTL analysis measuring gene expression in those genes harboring a risk variant in malignant plasma cells from 292 of the patients from a single site. Results: In GWAS analysis, we identified two suggestive novel loci located at 9p24.3 and 9p13.1 at P<1 × 10-6, but no genome-wide significant association was noted. In admixture mapping, we observed a genome-wide significant inverse association between local AA at 2p24.1-23.1 and MM risk in AA individuals. 20 of the 23 known EA risk variants showed directional consistency and 9 replicated at P<0.05 in AA individuals. In eight regions, we identified markers that better capture MM risk in persons of AA. AA individuals with a PRS in the top 10% had a 1.82-fold (95%CI: 1.56, 2.11) increased MM risk compared to those with average risk (25-75%). The strongest functional association was between the risk allele for variant rs56219066 at 5q15 and lower ELL2 expression (P= 5.1 × 10–12). Conclusion: Our study shows that common genetic variation contributes to MM risk individuals of AA. This abstract is also being presented as Poster C040. Citation Format: Zhaohui Du, Niels Weinhold, Gregory Chi Song, Kristen A. Rand, David J. Van Den Berg, Amie E. Hwang, Xin Sheng, Victor Hom, Sikander Ailawadhi, Ajay K. Nooka, Seema Singhal, Karen Pawlish, Edward Peters, Cathryn Bock, Ann Mohrbacher, Alexander Stram, Sonja I. Berndt, William J. Blot, Graham Casey, Victoria L. Stevens, Rick Kittles, Phyllis J. Goodman, W. Ryan Diver, Anselm Hennis, Barbara Nemesure, Eric A. Klein, Benjamin A. Rybicki, Janet L. Stanford, John S. Witte, Lisa Signorello, Esther M. John, Leslie Bernstein, Antoinette Stroup, Owen W. Stephens, Maurizio Zangari, Frits Van Rhee, Andrew Olshan, Wei Zheng, Jennifer J. Hu, Regina Ziegler, Sarah J. Nyante, Sue Ann Ingles, Michael Press, John David Carpten, Stephen Chanock, Jayesh Mehta, Graham A Colditz, Jeffrey Wolf, Thomas G. Martin, Michael Tomasson, Mark A. Fiala, Howard Terebelo, Nalini Janakiraman, Laurence Kolonel, Kenneth C. Anderson, Loic Le Marchand, Daniel Auclair, Brian C.-H. Chiu, Elad Ziv, Daniel Stram, Ravi Vij, Leon Bernal-Mizrachi, Gareth J. Morgan, Jeffrey A. Zonder, Carol Ann Huff, Sagar Lonial, Robert Z. Orlowski, David V. Conti, Christopher A. Haiman, Wendy Cozen. A meta-analysis of genome-wide association study and eQTL analysis of multiple myeloma among African Americans [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR05.
Variability in Cytogenetic Testing for Multiple Myeloma: A Comprehensive Analysis From Across the United States
Yu, Yang , Wadé, Niquelle Brown , Hwang, Amie E. , Nooka, Ajay K. , Fiala, Mark A. , Mohrbacher, Ann , Peters, Edward , Pawlish, Karen , Rand, Kristin A. , Conti, David V. , Auclair, Daniel , Mehta, Jayesh, Haiman, Christopher A. , Terebelo, Howard R. , Janakiraman, Nalini, Vij, Ravi , Bernal‐Mizrachi, Leon , Zonder, Jeffrey A. , Huff, Carol Ann , Orlowski, Robert Z. , Brown Wade, Niquelle , Van Den Berg, David J , Auclair, Daniel , Vij, Ravi , Zonder, Jeffrey A , Huff, Carol A , Cozen, Wendy , Ailawadhi, Sikander , Orlowski, Robert Z. , Fiala, Mark A , Nooka, Ajay K , Conti, David V , Yu, Yang, Bock, Cathryn Hufford , Berg, David Van Den , Stram, Daniel O. , Colditz, Graham A. , Singhal, Seema , Chiu, Brian C.‐H. , Lonial, Sagar , Cozen, Wendy , Ailawadhi, Sikander

JCO Oncology Practice | May 29, 2020 | Volume: 16 | Issue: 10 | Pages: e1169-e1180

10.1200/jop.19.00639 Get It

Purpose: Multiple myeloma (MM) treatment has changed tremendously, with significant improvement in patient out-comes. One group with a suboptimal benefit is patients with high-risk cytogenetics, as tested by conventional karyotyping or fluorescence in situ hybridization (FISH). Methodology for these tests has been published, but not necessarily standardized. Methods: We address variability in the testing and reporting methodology for MM cytogenetics in the United States using the ongoing African American Multiple Myeloma Study (AAMMS). We evaluated clinical and cytogenetic data from 1,221 patients (1,161 with conventional karyotyping and 976 with FISH) tested between 1998 and 2016 across 58 laboratories nationwide. Results: Interlab and intralab variability was noted for the number of cells analyzed for karyotyping, with a significantly higher number of cells analyzed in patients in whom cytogenetics were normal (P 5.0025). For FISH testing, CD138-positive cell enrichment was used in 29.7% of patients and no enrichment in 50% of patients, whereas the remainder had unknown status. A significantly smaller number of cells was analyzed for patients in which CD138 cell enrichment was used compared with those without such enrichment (median, 50 v 200; P, .0001). A median of 7 loci probes (range, 1-16) were used for FISH testing across all laboratories, with variability in the loci probed even within a given laboratory. Chromosome 13–related abnormalities were the most frequently tested abnormality (n5956; 97.9%), and t(14;16) was the least frequently tested abnormality (n 5 119; 12.2%). Conclusions: We report significant variability in cytogenetic testing across the United States for MM, potentially leading to variability in risk stratification, with possible clinical implications and personalized treatment approaches.
Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk
Xia, Zhiyu , Petersen, Paneen S., Qi, Lihong , Kim, Andre E. , Figueiredo, Jane C. , Nan, Hongmei , Berndt, Sonja I. , Casey, Graham , Conti, David V. , Gallinger, Steven , Gauderman, W. James, Gruber, Stephen B. , Gunter, Marc J. , Hoffmeister, Michael , Joshi, Amit D. , Li, Li , Lindor, Noralane M. , Moreno, Vı́ctor , Murphy, Neil , Nassir, Rami , Rennert, Gad , Wang, Xiaoliang , Woods, Michael O. , Brenner, Hermann , Slattery, Martha L. , Giovannucci, Edward L. , Chang‐Claude, Jenny, Peters, Ulrike , Kim, Andre E , Buchanan, Daniel D , Hoffmeister, Michael , Rennert, Gad , Moreno, Victor , Gunter, Marc J , Brenner, Hermann , Murphy, Neil , Nassir, Rami , Wang, Xiaoliang , Conti, David V , Nan, Hongmei , Su, Yu-Ru , Lin, Yi , Sakoda, Lori C. , Albanes, Demetrius , Bezieau, Stéphane , Bien, Stephanie A. , Buchanan, Daniel D. , Chan, Andrew T. , Drew, David A. , Giles, Graham G. , Jenkins, Mark A. , Marchand, Loı̈c Le , Lewinger, Juan Pablo , Newcomb, Polly A. , Ogino, Shuji , Song, Mingyang , Wolk, Alicja , White, Emily E. , Pharoah, Paul D.P. , Hsu, Li , Campbell, Peter T.

Cancer Medicine | March 24, 2020 | Volume: 9 | Issue: 10 | Pages: 3563-3573

10.1002/cam4.2971 Get It

AbstractBackgroundBody mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology.MethodsTo improve statistical power and interpretation for gene‐environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype‐Tissue Expression Project for all genes with heritability ≥1%. We used a mixed‐effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI‐CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2.ResultsAmong 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5).ConclusionsAggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.
Mendelian Randomization of Circulating Polyunsaturated Fatty Acids and Colorectal Cancer Risk
Khankari, Nikhil K. , Banbury, Barbara L. , Borges, Maria Carolina , Haycock, Philip , Arndt, Volker , Berndt, Sonja I. , Brenner, Hermann , Casey, Graham , Chang‐Claude, Jenny , Conti, David V. , English, Dallas R. , Figueiredo, Jane C. , Giovannucci, Edward L. , Gunter, Marc J. , Hampe, Jochen , Hoffmeister, Michael , Joshi, Amit D. , Lemire, Mathieu , Li, Li , Lindblom, Annika , Martín, Vicente , Moreno, Vı́ctor , Offit, Kenneth, Rennert, Gad , Schafmayer, Clemens , Schmit, Stephanie L. , Slattery, Martha L. , Thibodeau, Stephen N. , Weinstein, Stephanie J. , Win, Aung Ko , Woods, Michael O. , Wu, Anna H. , Murff, Harvey J. , Gruber, Stephen B. , Peters, Ulrike , Brenner, Hermann , Borges, Maria C , Arndt, Volker , Brenner, Hermann , Chang-Claude, Jenny , English, Dallas R , Giles, Graham G , Hoffmeister, Michael , Martín, Vicente , Moreno, Victor , Pharoah, Paul D P , Rennert, Gad , Sakoda, Lori C , Slattery, Martha L , Weinstein, Stephanie J , Win, Aung K , Wolk, Alicja , Denny, Joshua C , Gunter, Marc J , Haycock, Philip , Brenner, Hermann , Hampe, Jochen , Conti, David V , Lindblom, Annika , Albanes, Demetrius , Bezieau, Stéphane , Campbell, Peter T. , Chan, Andrew T. , Cotterchio, Michelle , Giles, Graham G. , Hopper, John L. , Jenkins, Mark A. , Marchand, Loı̈c Le , Li, Christopher I , Newcomb, Polly A. , Pharoah, Paul D.P. , Sakoda, Lori C. , Song, Mingyang , Ulrich, Cornelia M. , White, Emily , Wolk, Alicja , Cai, Qiuyin , Denny, Joshua C. , Edwards, Todd L. , Zheng, Wei

Cancer Epidemiology, Biomarkers & Prevention | February 12, 2020 | Volume: 29 | Issue: 4 | Pages: 860-870

10.1158/1055-9965.epi-19-0891 Get It

Abstract Background: Results from epidemiologic studies examining polyunsaturated fatty acids (PUFA) and colorectal cancer risk are inconsistent. Mendelian randomization may strengthen causal inference from observational studies. Given their shared metabolic pathway, examining the combined effects of aspirin/NSAID use with PUFAs could help elucidate an association between PUFAs and colorectal cancer risk. Methods: Information was leveraged from genome-wide association studies (GWAS) regarding PUFA-associated SNPs to create weighted genetic scores (wGS) representing genetically predicted circulating blood PUFAs for 11,016 non-Hispanic white colorectal cancer cases and 13,732 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Associations per SD increase in the wGS were estimated using unconditional logistic regression. Interactions between PUFA wGSs and aspirin/NSAID use on colorectal cancer risk were also examined. Results: Modest colorectal cancer risk reductions were observed per SD increase in circulating linoleic acid [ORLA = 0.96; 95% confidence interval (CI) = 0.93–0.98; P = 5.2 × 10−4] and α-linolenic acid (ORALA = 0.95; 95% CI = 0.92–0.97; P = 5.4 × 10−5), whereas modest increased risks were observed for arachidonic (ORAA = 1.06; 95% CI = 1.03–1.08; P = 3.3 × 10−5), eicosapentaenoic (OREPA = 1.04; 95% CI = 1.01–1.07; P = 2.5 × 10−3), and docosapentaenoic acids (ORDPA = 1.03; 95% CI = 1.01–1.06; P = 1.2 × 10−2). Each of these effects was stronger among aspirin/NSAID nonusers in the stratified analyses. Conclusions: Our study suggests that higher circulating shorter-chain PUFAs (i.e., LA and ALA) were associated with reduced colorectal cancer risk, whereas longer-chain PUFAs (i.e., AA, EPA, and DPA) were associated with an increased colorectal cancer risk. Impact: The interaction of PUFAs with aspirin/NSAID use indicates a shared colorectal cancer inflammatory pathway. Future research should continue to improve PUFA genetic instruments to elucidate the independent effects of PUFAs on colorectal cancer.