Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Xia, Zhiyu; Su, Yu Ru; Petersen, Paneen; Qi, Lihong; Kim, Andre E.; Figueiredo, Jane C.; Lin, Yi; Nan, Hongmei; Sakoda, Lori C.; Albanês, Demetrius; Berndt, Sonja I.; Bézieau, Stéphane; Bien, Stephanie A.; Buchanan, Daniel D.; Casey, Graham; Chan, Andrew T.; Conti, David V.; Drew, David A.; Gallinger, Steven; Gauderman, W. James; Giles, Graham G.; Gruber, Stephen B.; Gunter, Marc J.; Hoffmeister, Michael; Jenkins, Mark A.; Joshi, Amit D.; Marchand, Loı̈c Le; Lewinger, Juan Pablo; Li, Li; Lindor, Noralane M.; Murphy, Neil; Nassir, Rami; Newcomb, Polly A.; Ogino, Shuji; Rennert, Gad; Song, Mingyang; Wang, Xiaoliang; Wolk, Alicja; Woods, Michael O.; Brenner, Hermann; White, Emily; Slattery, Martha L.; Giovannucci, Edward; Chang‐Claude, Jenny; Pharoah, Paul D.P.; Hsu, Li; Campbell, Peter T.; Peters, Ulrike

doi:10.1002/cam4.2971

Cited by 7 publications

(10 citation statements)

References 55 publications

(55 reference statements)

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“…Since the preceding studies included a part of the study population presented here, we investigated the accuracy of the predicted gene expression levels for the previously identified genes. These previous studies reported that the expression of TRIM4 and PYGL in colon transverse tissue was associated with colorectal cancer risk [21], while PTPN2 expression in colon transverse tissue modified the association of diabetes with colorectal cancer risk [22]. The expression of PTPN2 was not measured in our study of 91 participants and could thus not be further investigated.…”

Section: Association Of Genetically Predictedmentioning

confidence: 55%

“…PrediXcan has been previously applied to identify novel colorectal the preceding studies included a part of the study population presente accuracy of the predicted gene expression levels for the previously iden studies reported that the expression of TRIM4 and PYGL in colon tran with colorectal cancer risk [21], while PTPN2 expression in colon tra association of diabetes with colorectal cancer risk [22]. The expression o in our study of 91 participants and could thus not be further investigat the correlation between measured and predicted gene expression for TR and observed a correlation of ϱ = 0.19 for TRIM4 and a negative correlatio SNPs as well as the corresponding regression coefficients used to pre TRIM4 and PYGL are provided in Table S3.…”

Section: Int J Mol Sci 2020 21 X 3 Of 13mentioning

confidence: 99%

“…Char overall survival (OS) and disease-sp Table 1. PrediXcan has been previously applied to identify novel colorectal cancer risk loci [21,22]. Since the preceding studies included a part of the study population presented here, we investigated the accuracy of the predicted gene expression levels for the previously identified genes.…”

Section: Association Of Genetically Predictedmentioning

confidence: 99%

“…Association tests were restricted to genes with a predictive ρ ≥ 0.10, i.e., ≥10% correlation between predicted and observed expression (cf. [21,22]).…”

Section: Gene Expression Predictionmentioning

confidence: 99%

“…Genome-wide association studies have identified thousands of loci associated with complex traits [15]. The use of PrediXcan is increasingly common in genetic association studies [16][17][18][19][20][21][22][23][24] and recently contributed to the identification of genes associated with lipid levels and schizophrenia [19,20], cutaneous squamous cell carcinoma [23], lung cancer [24], and colorectal cancer [21]. For example, TRIM4 and PYGL, both related to cellular metabolic programming, were associated with CRC risk [21].…”

Section: Introductionmentioning

confidence: 99%

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Genotype-Based Gene Expression in Colon Tissue—Prediction Accuracy and Relationship with the Prognosis of Colorectal Cancer Patients

Deutelmoser

Bermejo

Benner

et al. 2020

IJMS

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Colorectal cancer (CRC) survival has environmental and inherited components. The expression of specific genes can be inferred based on individual genotypes—so called expression quantitative trait loci. In this study, we used the PrediXcan method to predict gene expression in normal colon tissue using individual genotype data from 91 CRC patients and examined the correlation ρ between predicted and measured gene expression levels. Out of 5434 predicted genes, 58% showed a negative ρ value and only 16% presented a ρ higher than 0.10. We subsequently investigated the association between genotype-based gene expression in colon tissue for genes with ρ > 0.10 and survival of 4436 CRC patients. We identified an inverse association between the predicted expression of ARID3B and CRC-specific survival for patients with a body mass index greater than or equal to 30 kg/m2 (HR (hazard ratio) = 0.66 for an expression higher vs. lower than the median, p = 0.005). This association was validated using genotype and clinical data from the UK Biobank (HR = 0.74, p = 0.04). In addition to the identification of ARID3B expression in normal colon tissue as a candidate prognostic biomarker for obese CRC patients, our study illustrates the challenges of genotype-based prediction of gene expression, and the advantage of reassessing the prediction accuracy in a subset of the study population using measured gene expression data.

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Section: Association Of Genetically Predictedmentioning

confidence: 55%

Section: Int J Mol Sci 2020 21 X 3 Of 13mentioning

confidence: 99%

Section: Association Of Genetically Predictedmentioning

confidence: 99%

“…Association tests were restricted to genes with a predictive ρ ≥ 0.10, i.e., ≥10% correlation between predicted and observed expression (cf. [21,22]).…”

Section: Gene Expression Predictionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Genotype-Based Gene Expression in Colon Tissue—Prediction Accuracy and Relationship with the Prognosis of Colorectal Cancer Patients

Deutelmoser

Bermejo

Benner

et al. 2020

IJMS

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Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Xia

Petersen

et al. 2020

Cancer Medicine

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Probing the diabetes and colorectal cancer relationship using gene – environment interaction analyses

et al. 2023

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Background Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. Methods We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). Results Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 – ORAA: 1.62, 95% CI: 1.34–1.96; ORAG: 1.41, 95% CI: 1.30–1.54; ORGG: 1.22, 95% CI: 1.13–1.31; p-value3-d.f.: 5.46 × 10−11) and 13q14.13 (rs9526201, LRCH1 – ORGG: 2.11, 95% CI: 1.56–2.83; ORGA: 1.52, 95% CI: 1.38–1.68; ORAA: 1.13, 95% CI: 1.06–1.21; p-value2-d.f.: 7.84 × 10−09). Discussion These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

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Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Abstract: This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Cited by 7 publications

References 55 publications

Genotype-Based Gene Expression in Colon Tissue—Prediction Accuracy and Relationship with the Prognosis of Colorectal Cancer Patients

Genotype-Based Gene Expression in Colon Tissue—Prediction Accuracy and Relationship with the Prognosis of Colorectal Cancer Patients

Functional informed genome‐wide interaction analysis of body mass index, diabetes and colorectal cancer risk

Probing the diabetes and colorectal cancer relationship using gene – environment interaction analyses

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