Browsing by Author "Marchand, Loic Le"

Now showing 1 - 4 of 4
  • Thumbnail Image
    Item
    Association of Body Mass Index With Colorectal Cancer Risk by Genome-Wide Variants
    (Oxford University Press, 2021) Campbell, Peter T.; Lin, Yi; Bien, Stephanie A.; Figueiredo, Jane C.; Harrison, Tabitha A.; Guinter, Mark A.; Berndt, Sonja I.; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Gallinger, Steven J.; Gapstur, Susan M.; Giles, Graham G.; Giovannucci, Edward; Gruber, Stephen B.; Gunter, Marc; Hoffmeister, Michael; Jacobs, Eric J.; Jenkins, Mark A.; Marchand, Loic Le; Li, Li; McLaughlin, John R.; Murphy, Neil; Milne, Roger L.; Newcomb, Polly A.; Newton, Christina; Ogino, Shuji; Potter, John D.; Rennert, Gad; Rennert, Hedy S.; Robinson, Jennifer; Sakoda, Lori C.; Slattery, Martha L.; Song, Yiqing; White, Emily; Woods, Michael O.; Casey, Graham; Hsu, Li; Peters, Ulrike; Epidemiology, School of Public Health
    Background: Body mass index (BMI) is a complex phenotype that may interact with genetic variants to influence colorectal cancer risk. Methods: We tested multiplicative statistical interactions between BMI (per 5 kg/m2) and approximately 2.7 million single nucleotide polymorphisms with colorectal cancer risk among 14 059 colorectal cancer case (53.2% women) and 14 416 control (53.8% women) participants. All analyses were stratified by sex a priori. Statistical methods included 2-step (ie, Cocktail method) and single-step (ie, case-control logistic regression and a joint 2-degree of freedom test) procedures. All statistical tests were two-sided. Results: Each 5 kg/m2 increase in BMI was associated with higher risks of colorectal cancer, less so for women (odds ratio [OR] = 1.14, 95% confidence intervals [CI] = 1.11 to 1.18; P = 9.75 × 10-17) than for men (OR = 1.26, 95% CI = 1.20 to 1.32; P = 2.13 × 10-24). The 2-step Cocktail method identified an interaction for women, but not men, between BMI and a SMAD7 intronic variant at 18q21.1 (rs4939827; Pobserved = .0009; Pthreshold = .005). A joint 2-degree of freedom test was consistent with this finding for women (joint P = 2.43 × 10-10). Each 5 kg/m2 increase in BMI was more strongly associated with colorectal cancer risk for women with the rs4939827-CC genotype (OR = 1.24, 95% CI = 1.16 to 1.32; P = 2.60 × 10-10) than for women with the CT (OR = 1.14, 95% CI = 1.09 to 1.19; P = 1.04 × 10-8) or TT (OR = 1.07, 95% CI = 1.01 to 1.14; P = .02) genotypes. Conclusion: These results provide novel insights on a potential mechanism through which a SMAD7 variant, previously identified as a susceptibility locus for colorectal cancer, and BMI may influence colorectal cancer risk for women.
  • Thumbnail Image
    Item
    Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk
    (Oxford, 2022) Tian, Yu; Kim, Andre E.; Bien, Stephanie A.; Lin, Yi; Qu, Conghui; Harrison, Tabitha A.; Carreras-Torres, Robert; Díez-Obrero, Virginia; Dimou, Niki; Drew , David A.; Hidaka, Akihisa; Huyghe, Jeroen R.; Jordahl, Kristina M.; Morrison , John; Murphy, Neil; Obón-Santacana, Mireia; Ulrich, Cornelia M.; Ose, Jennifer; Peoples, Anita R.; Ruiz-Narvaez, Edward A.; Shcherbina, Anna; Stern , Mariana C.; Su, Yu-Ru; van Duijnhoven, Franzel J. B.; Arndt, Volker; Baurley, James W.; Berndt, Sonja I.; Bishop, D. Timothy; Brenner, Hermann; Buchanan, Daniel D.; Chan, Andrew T.; Figueiredo, Jane C.; Gallinger, Steven; Gruber, Stephen B.; Harlid, Sophia; Hoffmeister, Michael; Jenkins, Mark A.; Joshi, Amit D.; Keku, Temitope O.; Larsson, Susanna C.; Marchand, Loic Le; Li, Li; Giles, Graham G.; Milne, Roger L.; Nan, Hongmei; Nassir, Rami; Ogino, Shuji; Budiarto, Arif; Platz, Elizabeth A.; Potter, John D.; Prentice, Ross L.; Rennert, Gad; Sakoda, Lori C.; Schoen, Robert E.; Slattery, Martha L.; Thibodeau, Stephen N.; Van Guelpen, Bethany; Visvanathan, Kala; White, Emily; Wolk, Alicja; Woods, Michael O.; Wu, Anna H.; Campbell, Peter T.; Casey, Graham; Conti, David V.; Gunter, Marc J.; Kundaje, Anshul; Lewinger, Juan Pablo; Moreno, Victor; Newcomb, Polly A.; Pardamean, Bens; Thomas, Duncan C.; Tsilidis, Konstantinos K.; Peters, Ulrike; Gauderman, W. James; Hsu, Li; Chang-Claude, Jenny; Global Health, School of Public Health
    Background: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. Methods: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2– or 3–degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. Results: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2–degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10−4). Conclusion: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.
  • Thumbnail Image
    Item
    Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk
    (Springer, 2022-11-07) Haas, Cameron B.; Su, Yu-Ru; Petersen, Paneen; Wang, Xiaoliang; Bien, Stephanie A.; Lin, Yi; Albanes, Demetrius; Weinstein, Stephanie J.; Jenkins, Mark A.; Figueiredo, Jane C.; Newcomb, Polly A.; Casey, Graham; Marchand, Loic Le; Campbell, Peter T.; Moreno, Victor; Potter, John D.; Sakoda, Lori C.; Slattery, Martha L.; Chan, Andrew T.; Li, Li; Giles, Graham G.; Milne, Roger L.; Gruber, Stephen B.; Rennert, Gad; Woods, Michael O.; Gallinger, Steven J.; Berndt, Sonja; Hayes, Richard B.; Huang, Wen-Yi; Wolk, Alicja; White, Emily; Nan, Hongmei; Nassir, Rami; Lindor, Noralane M.; Lewinger, Juan P.; Kim, Andre E.; Conti, David; Gauderman, W. James; Buchanan, Daniel D.; Peters, Ulrike; Hsu , Li; Epidemiology, Richard M. Fairbanks School of Public Health
    Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E-4), and Aspartylglucosaminidase (AGA: p = 4.5E-4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.
  • Thumbnail Image
    Item
    Whole Genome Sequencing Analysis of Body Mass Index Identifies Novel African Ancestry-Specific Risk Allele
    (medRxiv, 2023-08-22) Zhang, Xinruo; Brody, Jennifer A.; Graff, Mariaelisa; Highland, Heather M.; Chami, Nathalie; Xu, Hanfei; Wang, Zhe; Ferrier, Kendra; Chittoor, Geetha; Josyula, Navya S.; Li, Xihao; Li, Zilin; Allison, Matthew A.; Becker, Diane M.; Bielak, Lawrence F.; Bis, Joshua C.; Boorgula, Meher Preethi; Bowden, Donald W.; Broome, Jai G.; Buth, Erin J.; Carlson, Christopher S.; Chang, Kyong-Mi; Chavan, Sameer; Chiu, Yen-Feng; Chuang, Lee-Ming; Conomos, Matthew P.; DeMeo, Dawn L.; Du, Margaret; Duggirala, Ravindranath; Eng, Celeste; Fohner, Alison E.; Freedman, Barry I.; Garrett, Melanie E.; Guo, Xiuqing; Haiman, Chris; Heavner, Benjamin D.; Hidalgo, Bertha; Hixson, James E.; Ho, Yuk-Lam; Hobbs, Brian D.; Hu, Donglei; Hui, Qin; Hwu, Chii-Min; Jackson, Rebecca D.; Jain, Deepti; Kalyani, Rita R.; Kardia, Sharon L. R.; Kelly, Tanika N.; Lange, Ethan M.; LeNoir, Michael; Li, Changwei; Marchand, Loic Le; McDonald, Merry-Lynn N.; McHugh, Caitlin P.; Morrison, Alanna C.; Naseri, Take; NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium; O'Connell, Jeffrey; O'Donnell, Christopher J.; Palmer, Nicholette D.; Pankow, James S.; Perry, James A.; Peters, Ulrike; Preuss, Michael H.; Rao, D. C.; Regan, Elizabeth A.; Reupena, Sefuiva M.; Roden, Dan M.; Rodriguez-Santana, Jose; Sitlani, Colleen M.; Smith, Jennifer A.; Tiwari, Hemant K.; Vasan, Ramachandran S.; Wang, Zeyuan; Weeks, Daniel E.; Wessel, Jennifer; Wiggins, Kerri L.; Wilkens, Lynne R.; Wilson, Peter W. F.; Yanek, Lisa R.; Yoneda, Zachary T.; Zhao, Wei; Zöllner, Sebastian; Arnett, Donna K.; Ashley-Koch, Allison E.; Barnes, Kathleen C.; Blangero, John; Boerwinkle, Eric; Burchard, Esteban G.; Carson, April P.; Chasman, Daniel I.; Chen, Yii-Der Ida; Curran, Joanne E.; Fornage, Myriam; Gordeuk, Victor R.; He, Jiang; Heckbert, Susan R.; Hou, Lifang; Irvin, Marguerite R.; Kooperberg, Charles; Minster, Ryan L.; Mitchell, Braxton D.; Nouraie, Mehdi; Psaty, Bruce M.; Raffield, Laura M.; Reiner, Alexander P.; Rich, Stephen S.; Rotter, Jerome I.; Shoemaker, M. Benjamin; Smith, Nicholas L.; Taylor, Kent D.; Telen, Marilyn J.; Weiss, Scott T.; Zhang, Yingze; Heard-Costa, Nancy; Sun, Yan V.; Lin, Xihong; Cupples, L. Adrienne; Lange, Leslie A.; Liu, Ching-Ti; Loos, Ruth J. F.; North, Kari E.; Justice, Anne E.; Biostatistics and Health Data Science, School of Medicine
    Obesity is a major public health crisis associated with high mortality rates. Previous genome-wide association studies (GWAS) investigating body mass index (BMI) have largely relied on imputed data from European individuals. This study leveraged whole-genome sequencing (WGS) data from 88,873 participants from the Trans-Omics for Precision Medicine (TOPMed) Program, of which 51% were of non-European population groups. We discovered 18 BMI-associated signals (P < 5 × 10−9). Notably, we identified and replicated a novel low frequency single nucleotide polymorphism (SNP) in MTMR3 that was common in individuals of African descent. Using a diverse study population, we further identified two novel secondary signals in known BMI loci and pinpointed two likely causal variants in the POC5 and DMD loci. Our work demonstrates the benefits of combining WGS and diverse cohorts in expanding current catalog of variants and genes confer risk for obesity, bringing us one step closer to personalized medicine.