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Gao N, Zhuang Y, Zheng Y, Li Y, Wang Y, Zhu S, Fan M, Tian W, Jiang Y, Wang Y, Cui M, Suo C, Zhang T, Jin L, Chen X, Xu K. Investigating the link between gut microbiome and bone mineral density: The role of genetic factors. Bone 2024; 188:117239. [PMID: 39179139 DOI: 10.1016/j.bone.2024.117239] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 05/02/2024] [Revised: 07/19/2024] [Accepted: 08/17/2024] [Indexed: 08/26/2024]
Abstract
Osteoporosis is a complex metabolic bone disease that severely undermines the quality of life and overall health of the elderly. While previous studies have established a close relationship between gut microbiome and host bone metabolism, the role of genetic factors has received less scrutiny. This research aims to identify potential taxa associated with various bone mineral density states, incorporating assessments of genetic factors. Fecal microbiome profiles from 605 individuals (334 females and 271 males) aged 55-65 from the Taizhou Imaging Study with osteopenia (n = 270, 170 women) or osteoporosis (n = 94, 85 women) or normal (n = 241, 79 women) were determined using shotgun metagenomic sequencing. The linear discriminant analysis was employed to identify differentially enriched taxa. Utilizing the Kyoto Encyclopedia of Genes and Genomes for annotation, functional pathway analysis was conducted to identify differentially metabolic pathways. Polygenic risk score for osteoporosis was estimated to represent genetic susceptibility to osteoporosis, followed by stratification and interaction analyses. Gut flora diversity did not show significant differences among various bone mineral groups. After multivariable adjustment, certain species, such as Clostridium leptum, Fusicatenibacter saccharivorans and Roseburia hominis, were enriched in osteoporosis patients. Statistically significant interactions between the polygenic risk score and taxa Roseburia faecis, Megasphaera elsdenii were observed (P for interaction = 0.005, 0.018, respectively). Stratified analyses revealed a significantly negative association between Roseburia faecis and bone mineral density in the low-genetic-risk group (β = -0.045, P < 0.05), while Turicimonas muris was positively associated with bone mineral density in the high-genetic-risk group (β = 4.177, P < 0.05) after multivariable adjustments. Functional predictions of the gut microbiome indicated an increase in pathways related to structural proteins in high-genetic-risk patients, while low-genetic-risk patients exhibited enrichment in enzyme-related pathways. This study emphasizes the association between gut microbes and bone mass, offering new insights into the interaction between genetic background and gut microbiome.
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Affiliation(s)
- Ningxin Gao
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Yue Zhuang
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Yi Zheng
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yucan Li
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China
| | - Yawen Wang
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China
| | - Sibo Zhu
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Min Fan
- Taixing Disease Control and Prevention Center, Taizhou, Jiangsu, China
| | - Weizhong Tian
- Taizhou People's Hospital Affiliated to Nantong University, Taizhou, Jiangsu, China
| | - Yanfeng Jiang
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Yingzhe Wang
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Mei Cui
- Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China; Department of Neurology, Huashan Hospital, Fudan University, Shanghai, China
| | - Chen Suo
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Tiejun Zhang
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Li Jin
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China
| | - Xingdong Chen
- State Key Laboratory of Genetic Engineering, Zhangjiang Fudan International Innovation Center, Human Phenome Institute, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China; National Clinical Research Center for Aging and Medicine, Huashan Hospital, Fudan University, Shanghai, China; Yiwu Research Institute of Fudan University, Yiwu, Zhejiang, China.
| | - Kelin Xu
- Department of Biostatistics, School of Public Health, Key Laboratory of Public Health Safety of Ministry of Education, Fudan University, Shanghai, China; Fudan University Taizhou Institute of Health Sciences, Taizhou, Jiangsu, China.
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2
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Ji C, Ge W, Zhu C, Shen F, Yu Y, Pang G, Li Q, Zhu M, Ma Z, Zhu X, Fu Y, Gong L, Wang T, Du L, Jin G, Zhu M. Family history and genetic risk score combined to guide cancer risk stratification: A prospective cohort study. Int J Cancer 2024. [PMID: 39291673 DOI: 10.1002/ijc.35187] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/06/2024] [Revised: 07/18/2024] [Accepted: 08/30/2024] [Indexed: 09/19/2024]
Abstract
Family history (FH) of cancer and polygenic risk scores (PRS) are pivotal for cancer risk assessment, yet their combined impact remains unclear. Participants in the UK Biobank (UKB) were recruited between 2006 and 2010, with complete follow-up data updated until February 2020 for Scotland and January 2021 for England and Wales. Using UKB data (N = 442,399), we constructed PRS and incidence-weighted overall cancer PRS (CPRS). FH was assessed through self-reported standardized questions. Among 202,801 men (34.6% with FH) and 239,598 women (42.0% with FH), Cox regression was used to examine the associations between FH, PRS, and cancer risk. We found a significant dose-response relationship between FH of cancer and corresponding cancer risk (Ptrend < .05), with over 10 significant pairs of cross-cancer effects of FH. FH and PRS are positively correlated and independent. Joint effects of FH of cancer (multiple cancers) and PRS (CPRS) on corresponding cancer risk were observed: for instance, compared with participants with no FH of cancer and low PRS, men with FH of cancer and high PRS had the highest risk of colorectal cancer (hazard ratio [HR]: 3.69, 95% confidence interval [CI]: 3.01-4.52). Additive interactions were observed in prostate and overall cancer risk for men and breast cancer for women, with the most significant result being a relative excess risk of interaction (RERI) of 2.98, accounting for ~34% of the prostate cancer risk. In conclusion, FH and PRS collectively contribute to cancer risk, supporting their combined application in personalized risk assessment and early intervention strategies.
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Affiliation(s)
- Chen Ji
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Wenjing Ge
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Chen Zhu
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China
| | - Fang Shen
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Yuhui Yu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Guanlian Pang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Qiao Li
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Mingxuan Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Zhimin Ma
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Xia Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Yating Fu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Linnan Gong
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Tianpei Wang
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
| | - Lingbin Du
- Department of Cancer Prevention, Zhejiang Cancer Hospital, Hangzhou, China
- Hangzhou Institute of Medicine (HIM), Chinese Academy of Sciences, Hangzhou, China
| | - Guangfu Jin
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
- Public Health Institute of Gusu School, The Affiliated Suzhou Hospital of Nanjing Medical University, Suzhou, China
- The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
| | - Meng Zhu
- Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine and China International Cooperation Center for Environment and Human Health, Nanjing Medical University, Nanjing, China
- Jiangsu Key Laboratory of Molecular and Translational Cancer Research, Jiangsu Cancer Hospital, Jiangsu Institute of Cancer Research, The Affiliated Cancer Hospital of Nanjing Medical University, Nanjing, China
- The Affiliated Wuxi Center for Disease Control and Prevention of Nanjing Medical University, Wuxi Center for Disease Control and Prevention, Wuxi Medical Center, Nanjing Medical University, Wuxi, China
- Research Units of Cohort Study on Cardiovascular Diseases and Cancers, Chinese Academy of Medical Sciences, Beijing, China
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Mauri G, Patelli G, Sartore-Bianchi A, Abrignani S, Bodega B, Marsoni S, Costanzo V, Bachi A, Siena S, Bardelli A. Early-onset cancers: Biological bases and clinical implications. Cell Rep Med 2024; 5:101737. [PMID: 39260369 DOI: 10.1016/j.xcrm.2024.101737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/14/2024] [Revised: 08/02/2024] [Accepted: 08/19/2024] [Indexed: 09/13/2024]
Abstract
Since the nineties, the incidence of sporadic early-onset (EO) cancers has been rising worldwide. The underlying reasons are still unknown. However, identifying them is vital for advancing both prevention and intervention. Here, we exploit available knowledge derived from clinical observations to formulate testable hypotheses aimed at defining the causal factors of this epidemic and discuss how to experimentally test them. We explore the potential impact of exposome changes from the millennials to contemporary young generations, considering both environmental exposures and enhanced susceptibilities to EO-cancer development. We emphasize how establishing the time required for an EO cancer to develop is relevant to defining future screening strategies. Finally, we discuss the importance of integrating multi-dimensional data from international collaborations to generate comprehensive knowledge and translate these findings back into clinical practice.
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Affiliation(s)
- Gianluca Mauri
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Niguarda Cancer Center, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Giorgio Patelli
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Niguarda Cancer Center, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Andrea Sartore-Bianchi
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Niguarda Cancer Center, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Sergio Abrignani
- INGM, Istituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy; Department of Clinical Sciences and Community Health, Università degli Studi di Milano, Milan, Italy
| | - Beatrice Bodega
- INGM, Istituto Nazionale Genetica Molecolare "Romeo ed Enrica Invernizzi", Milan, Italy; Department of Biosciences, University of Milan, Milan, Italy
| | - Silvia Marsoni
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy
| | - Vincenzo Costanzo
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy; Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy
| | - Angela Bachi
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy
| | - Salvatore Siena
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, Milan, Italy; Niguarda Cancer Center, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Alberto Bardelli
- IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy; Department of Oncology, Molecular Biotechnology Center, University of Torino, Torino, Italy.
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Lei Y, Christian Naj A, Xu H, Li R, Chen Y. Balancing the efforts of chart review and gains in PRS prediction accuracy: An empirical study. J Biomed Inform 2024; 157:104705. [PMID: 39134233 DOI: 10.1016/j.jbi.2024.104705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2024] [Revised: 06/12/2024] [Accepted: 08/05/2024] [Indexed: 08/22/2024]
Abstract
OBJECTIVE Phenotypic misclassification in genetic association analyses can impact the accuracy of PRS-based prediction models. The bias reduction method proposed by Tong et al. (2019) has demonstrated its efficacy in reducing the effects of bias on the estimation of association parameters between genotype and phenotype while minimizing variance by employing chart reviews on a subset of the data for validating phenotypes, however its improvement of subsequent PRS prediction accuracy remains unclear. Our study aims to fill this gap by assessing the performance of simulated PRS models and estimating the optimal number of chart reviews needed for validation. METHODS To comprehensively assess the efficacy of the bias reduction method proposed by Tong et al. in enhancing the accuracy of PRS-based prediction models, we simulated each phenotype under different correlation structures (an independent model, a weakly correlated model, a strongly correlated model) and introduced error-prone phenotypes using two distinct error mechanisms (differential and non-differential phenotyping errors). To facilitate this, we used genotype and phenotype data from 12 case-control datasets in the Alzheimer's Disease Genetics Consortium (ADGC) to produce simulated phenotypes. The evaluation included analyses across various misclassification rates of original phenotypes as well as quantities of validation set. Additionally, we determined the median threshold, identifying the minimal validation size required for a meaningful improvement in the accuracy of PRS-based predictions across a broad spectrum. RESULTS This simulation study demonstrated that incorporating chart review does not universally guarantee enhanced performance of PRS-based prediction models. Specifically, in scenarios with minimal misclassification rates and limited validation sizes, PRS models utilizing debiased regression coefficients demonstrated inferior predictive capabilities compared to models using error-prone phenotypes. Put differently, the effectiveness of the bias reduction method is contingent upon the misclassification rates of phenotypes and the size of the validation set employed during chart reviews. Notably, when dealing with datasets featuring higher misclassification rates, the advantages of utilizing this bias reduction method become more evident, requiring a smaller validation set to achieve better performance. CONCLUSION This study highlights the importance of choosing an appropriate validation set size to balance between the efforts of chart review and the gain in PRS prediction accuracy. Consequently, our study establishes a valuable guidance for validation planning, across a diverse array of sensitivity and specificity combinations.
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Affiliation(s)
- Yuqing Lei
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA
| | - Adam Christian Naj
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA; Penn Neurodegeneration Genomics Center, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA
| | - Hua Xu
- Department for Biomedical Informatics and Data Science, Yale School of Medicine, Yale University, New Haven, CT, USA
| | - Ruowang Li
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
| | - Yong Chen
- Department of Biostatistics, Epidemiology and Informatics, Perelman School of Medicine, The University of Pennsylvania, Philadelphia, PA, USA.
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5
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Fu R, Chen X, Seum T, Hoffmeister M, Brenner H. Red and Processed Meat Intake, Polygenic Risk and the Prevalence of Colorectal Neoplasms: Results from a Screening Colonoscopy Population. Nutrients 2024; 16:2609. [PMID: 39203746 PMCID: PMC11357662 DOI: 10.3390/nu16162609] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2024] [Revised: 08/02/2024] [Accepted: 08/05/2024] [Indexed: 09/03/2024] Open
Abstract
High red and processed meat intake and genetic predisposition are risk factors of colorectal cancer (CRC). However, evidence of their independent and joint associations on the risk of colorectal neoplasms is limited. We assessed these associations among 4774 men and women undergoing screening colonoscopy. Polygenic risk scores (PRSs) were calculated based on 140 loci related to CRC. We used multiple logistic regression models to evaluate the associations of red and processed meat intake and PRS with the risk of colorectal neoplasms. Adjusted odds ratios (aORs) were translated to genetic risk equivalents (GREs) to compare the strength of the associations with colorectal neoplasm risk of both factors. Compared to ≤1 time/week, processed meat intake >1 time/week was associated with a significantly increased risk of colorectal neoplasm [aOR (95% CI): 1.28 (1.12-1.46)]. This risk increase was equivalent to the risk increase associated with a 19 percentile higher PRS. The association of red meat intake with colorectal neoplasm was weaker and did not reach statistical significance. High processed meat intake and PRS contribute to colorectal neoplasm risk independently. Limiting processed meat intake may offset a substantial proportion of the genetically increased risk of colorectal neoplasms.
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Affiliation(s)
- Ruojin Fu
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
- College of Pharmacy, Jinan University, Guangzhou 511436, China
| | - Teresa Seum
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Im Neuenheimer Feld 672, 69120 Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Im Neuenheimer Feld 581, 69120 Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Im Neuenheimer Feld 280, 69120 Heidelberg, Germany
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Mallabar-Rimmer B, Merriel SWD, Webster AP, Jackson L, Wood AR, Barclay M, Tyrrell J, Ruth KS, Thirlwell C, Oram R, Weedon MN, Bailey SER, Green HD. Colorectal cancer risk stratification using a polygenic risk score in symptomatic primary care patients-a UK Biobank retrospective cohort study. Eur J Hum Genet 2024:10.1038/s41431-024-01654-3. [PMID: 39090236 DOI: 10.1038/s41431-024-01654-3] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2023] [Revised: 05/15/2024] [Accepted: 06/17/2024] [Indexed: 08/04/2024] Open
Abstract
Colorectal cancer (CRC) is a leading cause of cancer mortality worldwide. Accurate cancer risk assessment approaches could increase rates of early CRC diagnosis, improve health outcomes for patients and reduce pressure on diagnostic services. The faecal immunochemical test (FIT) for blood in stool is widely used in primary care to identify symptomatic patients with likely CRC. However, there is a 6-16% noncompliance rate with FIT in clinic and ~90% of patients over the symptomatic 10 µg/g test threshold do not have CRC. A polygenic risk score (PRS) quantifies an individual's genetic risk of a condition based on many common variants. Existing PRS for CRC have so far been used to stratify asymptomatic populations. We conducted a retrospective cohort study of 50,387 UK Biobank participants with a CRC symptom in their primary care record at age 40+. A PRS based on 201 variants, 5 genetic principal components and 22 other risk factors and markers for CRC were assessed for association with CRC diagnosis within 2 years of first symptom presentation using logistic regression. Associated variables were included in an integrated risk model and trained in 80% of the cohort to predict CRC diagnosis within 2 years. An integrated risk model combining PRS, age, sex, and patient-reported symptoms was predictive of CRC development in a testing cohort (receiver operating characteristic area under the curve, ROCAUC: 0.76, 95% confidence interval: 0.71-0.81). This model has the potential to improve early diagnosis of CRC, particularly in cases of patient noncompliance with FIT.
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Affiliation(s)
| | - Samuel W D Merriel
- Division of Population Health, Health Services Research & Primary Care, University of Manchester, Manchester, UK
| | - Amy P Webster
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Leigh Jackson
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Andrew R Wood
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Matthew Barclay
- Department of Behavioural Science & Health, Institute of Epidemiology & Health Care, University College London, London, UK
| | - Jessica Tyrrell
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Katherine S Ruth
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | | | - Richard Oram
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Michael N Weedon
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK
| | - Sarah E R Bailey
- Department of Health and Community Sciences, University of Exeter, Exeter, UK
| | - Harry D Green
- Department of Clinical and Biomedical Sciences, University of Exeter, Exeter, UK.
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Dezfuli AAZ, Abu-Elghait M, Salem SS. Recent Insights into Nanotechnology in Colorectal Cancer. Appl Biochem Biotechnol 2024; 196:4457-4471. [PMID: 37751009 DOI: 10.1007/s12010-023-04696-3] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 08/16/2023] [Indexed: 09/27/2023]
Abstract
Colorectal cancer (CRC) is the third cancer among the known causes of cancer that impact people. Although CRC drug options are imperfect, primary detection of CRC can play a key role in treating the disease and reducing mortality. Cancer tissues show many molecular markers that can be used as a new way to advance therapeutic methods. Nanotechnology includes a wide range of nanomaterials with high diagnostic and therapeutic power. Several nanomaterials and nanoformulations can be used to treat cancer, especially CRC. In this review, we discuss recent insights into nanotechnology in colorectal cancer.
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Affiliation(s)
- Aram Asareh Zadegan Dezfuli
- Department of Microbiology, Faculty of Medicine, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
| | - Mohammed Abu-Elghait
- Department of Botany and Microbiology, Faculty of Science, Al-Azhar University, Cairo, Egypt
| | - Salem S Salem
- Department of Botany and Microbiology, Faculty of Science, Al-Azhar University, Cairo, Egypt.
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8
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Ye Y, Xu G. Construction of a new prognostic model for colorectal cancer based on bulk RNA-seq combined with The Cancer Genome Atlas data. Transl Cancer Res 2024; 13:2704-2720. [PMID: 38988915 PMCID: PMC11231782 DOI: 10.21037/tcr-23-2281] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 05/08/2024] [Indexed: 07/12/2024]
Abstract
Background Colorectal cancer (CRC) is one of the leading causes of cancer-related deaths, and improving the prognosis of CRC patients is an urgent concern. The aim of this study was to explore new immunotherapy targets to improve survival in CRC patients. Methods We analyzed CRC-related single-cell data GSE201348 from the Gene Expression Omnibus (GEO) database, and identified differentially expressed genes (DEGs). Subsequently, we performed differential analysis on the rectum adenocarcinoma (READ) and colon adenocarcinoma (COAD) transcriptome sequencing data [The Cancer Genome Atlas (TCGA)-CRC queue] and clinical data downloaded from TCGA database. Subgroup analysis was performed using CIBERSORTx and cluster analysis. Finally, biomarkers were identified by one-way cox regression as well as least absolute shrinkage and selection operator (LASSO) analysis. Results In this study, we analyzed CRC-related single-cell data GSE201348, and identified 5,210 DEGs. Subsequently, we performed differential analysis on the TCGA-CRC queue database, and obtained 4,408 DEGs. Then, we categorized the cancer samples in the sequencing data into three groups (k1, k2, and k3), with significant differences observed between the k1 and k2 groups via survival analysis. Further differential analysis on the samples in the k1 and k2 groups identified 1,899 DEGs. A total of 77 DEGs were selected among those DEGs obtained from three differential analyses. Through subsequent Cox univariate analysis and LASSO analysis, seven biomarkers (RETNLB, CLCA4, UGT2A3, SULT1B1, CCL24, BMP5, and ATOH1) were identified and selected to establish a risk score (RS). Conclusions To sum up, this study demonstrates the potential of the seven-gene prognostic risk model as instrumental variables for predicting the prognosis of CRC.
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Affiliation(s)
- Yu Ye
- Department of General Surgery, Zhejiang Hospital of Integrated Traditional Chinese and Western Medicine, Hangzhou, China
| | - Gang Xu
- Department of General Surgery, Zhejiang Hospital, Hangzhou, China
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9
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Zhang Y, Sheng C, Lyu Z, Dai H, Song F, Song F, Huang Y, Chen K. Effectiveness of colorectal cancer screening integrating non-genetic and genetic risk: a prospective study based on UK Biobank data. Cancer Biol Med 2024; 21:j.issn.2095-3941.2024.0096. [PMID: 38899940 PMCID: PMC11359493 DOI: 10.20892/j.issn.2095-3941.2024.0096] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2024] [Accepted: 05/20/2024] [Indexed: 06/21/2024] Open
Abstract
OBJECTIVE Few studies have evaluated the benefits of colorectal cancer (CRC) screening integrating both non-genetic and genetic risk factors. Here, we aimed to integrate an existing non-genetic risk model (QCancer-10) and a 139-variant polygenic risk score to evaluate the effectiveness of screening on CRC incidence and mortality. METHODS We applied the integrated model to calculate 10-year CRC risk for 430,908 participants in the UK Biobank, and divided the participants into low-, intermediate-, and high-risk groups. We calculated the screening-associated hazard ratios (HRs) and absolute risk reductions (ARRs) for CRC incidence and mortality according to risk stratification. RESULTS During a median follow-up of 11.03 years and 12.60 years, we observed 5,158 CRC cases and 1,487 CRC deaths, respectively. CRC incidence and mortality were significantly lower among screened than non-screened participants in both the intermediate- and high-risk groups [incidence: HR: 0.87, 95% confidence interval (CI): 0.81-0.94; 0.81, 0.73-0.90; mortality: 0.75, 0.64-0.87; 0.70, 0.58-0.85], which composed approximately 60% of the study population. The ARRs (95% CI) were 0.17 (0.11-0.24) and 0.43 (0.24-0.61), respectively, for CRC incidence, and 0.08 (0.05-0.11) and 0.24 (0.15-0.33), respectively, for mortality. Screening did not significantly reduce the relative or absolute risk of CRC incidence and mortality in the low-risk group. Further analysis revealed that screening was most effective for men and individuals with distal CRC among the intermediate to high-risk groups. CONCLUSIONS After integrating both genetic and non-genetic factors, our findings provided priority evidence of risk-stratified CRC screening and valuable insights for the rational allocation of health resources.
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Affiliation(s)
- Yu Zhang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Chao Sheng
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Zhangyan Lyu
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Hongji Dai
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Fangfang Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Fengju Song
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Yubei Huang
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
| | - Kexin Chen
- Department of Epidemiology and Biostatistics, Key Laboratory of Molecular Cancer Epidemiology, Key Laboratory of Prevention and Control of Human Major Diseases, Ministry of Education, National Clinical Research Center for Cancer, Tianjin Medical University Cancer Institute and Hospital, Tianjin Medical University, Tianjin 300060, China
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Fu QQ, Ma L, Niu XM, Zhao HX, Ge XH, Jin H, Yu DH, Yang S. Trends and hotspots in gastrointestinal neoplasms risk assessment: A bibliometric analysis from 1984 to 2022. World J Gastrointest Oncol 2024; 16:2842-2861. [PMID: 38994129 PMCID: PMC11236220 DOI: 10.4251/wjgo.v16.i6.2842] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/12/2024] [Revised: 03/10/2024] [Accepted: 04/15/2024] [Indexed: 06/13/2024] Open
Abstract
BACKGROUND Gastrointestinal neoplasm (GN) significantly impact the global cancer burden and mortality, necessitating early detection and treatment. Understanding the evolution and current state of research in this field is vital. AIM To conducts a comprehensive bibliometric analysis of publications from 1984 to 2022 to elucidate the trends and hotspots in the GN risk assessment research, focusing on key contributors, institutions, and thematic evolution. METHODS This study conducted a bibliometric analysis of data from the Web of Science Core Collection database using the "bibliometrix" R package, VOSviewer, and CiteSpace. The analysis focused on the distribution of publications, contributions by institutions and countries, and trends in keywords. The methods included data synthesis, network analysis, and visualization of international collaboration networks. RESULTS This analysis of 1371 articles on GN risk assessment revealed a notable evolution in terms of research focus and collaboration. It highlights the United States' critical role in advancing this field, with significant contributions from institutions such as Brigham and Women's Hospital and the National Cancer Institute. The last five years, substantial advancements have been made, representing nearly 45% of the examined literature. Publication rates have dramatically increased, from 20 articles in 2002 to 112 in 2022, reflecting intensified research efforts. This study underscores a growing trend toward interdisciplinary and international collaboration, with the Journal of Clinical Oncology standing out as a key publication outlet. This shift toward more comprehensive and collaborative research methods marks a significant step in addressing GN risks. CONCLUSION This study underscores advancements in GN risk assessment through genetic analyses and machine learning and reveals significant geographical disparities in research emphasis. This calls for enhanced global collaboration and integration of artificial intelligence to improve cancer prevention and treatment accuracy, ultimately enhancing worldwide patient care.
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Affiliation(s)
- Qiang-Qiang Fu
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
- Shanghai General Practice and Community Health Development Research Center, Shanghai 200090, China
| | - Le Ma
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
| | - Xiao-Min Niu
- Department of Shanghai Lung Cancer Center, Shanghai Chest Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200030, China
| | - Hua-Xin Zhao
- Department of Oncology, Shanghai Tenth People’s Hospital, Tongji University School of Medicine, Shanghai 200090, China
| | - Xu-Hua Ge
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
| | - Hua Jin
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
| | - De-Hua Yu
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
- Shanghai General Practice and Community Health Development Research Center, Shanghai 200090, China
| | - Sen Yang
- Department of General Practice, Yangpu Hospital, School of Medicine, Tongji University, Shanghai 200090, China
- Shanghai General Practice and Community Health Development Research Center, Shanghai 200090, China
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11
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Tian J, Zhang M, Zhang F, Gao K, Lu Z, Cai Y, Chen C, Ning C, Li Y, Qian S, Bai H, Liu Y, Zhang H, Chen S, Li X, Wei Y, Li B, Zhu Y, Yang J, Jin M, Miao X, Chen K. Developing an optimal stratification model for colorectal cancer screening and reducing racial disparities in multi-center population-based studies. Genome Med 2024; 16:81. [PMID: 38872215 PMCID: PMC11170922 DOI: 10.1186/s13073-024-01355-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Accepted: 06/05/2024] [Indexed: 06/15/2024] Open
Abstract
BACKGROUND Early detection of colorectal neoplasms can reduce the colorectal cancer (CRC) burden by timely intervention for high-risk individuals. However, effective risk prediction models are lacking for personalized CRC early screening in East Asian (EAS) population. We aimed to develop, validate, and optimize a comprehensive risk prediction model across all stages of the dynamic adenoma-carcinoma sequence in EAS population. METHODS To develop precision risk-stratification and intervention strategies, we developed three trans-ancestry PRSs targeting colorectal neoplasms: (1) using 148 previously identified CRC risk loci (PRS148); (2) SNPs selection from large-scale meta-analysis data by clumping and thresholding (PRS183); (3) PRS-CSx, a Bayesian approach for genome-wide risk prediction (PRSGenomewide). Then, the performance of each PRS was assessed and validated in two independent cross-sectional screening sets, including 4600 patients with advanced colorectal neoplasm, 4495 patients with non-advanced adenoma, and 21,199 normal individuals from the ZJCRC (Zhejiang colorectal cancer set; EAS) and PLCO (the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; European, EUR) studies. The optimal PRS was further incorporated with lifestyle factors to stratify individual risk and ultimately tested in the PLCO and UK Biobank prospective cohorts, totaling 350,013 participants. RESULTS Three trans-ancestry PRSs achieved moderately improved predictive performance in EAS compared to EUR populations. Remarkably, the PRSs effectively facilitated a thorough risk assessment across all stages of the dynamic adenoma-carcinoma sequence. Among these models, PRS183 demonstrated the optimal discriminatory ability in both EAS and EUR validation datasets, particularly for individuals at risk of colorectal neoplasms. Using two large-scale and independent prospective cohorts, we further confirmed a significant dose-response effect of PRS183 on incident colorectal neoplasms. Incorporating PRS183 with lifestyle factors into a comprehensive strategy improves risk stratification and discriminatory accuracy compared to using PRS or lifestyle factors separately. This comprehensive risk-stratified model shows potential in addressing missed diagnoses in screening tests (best NPV = 0.93), while moderately reducing unnecessary screening (best PPV = 0.32). CONCLUSIONS Our comprehensive risk-stratified model in population-based CRC screening trials represents a promising advancement in personalized risk assessment, facilitating tailored CRC screening in the EAS population. This approach enhances the transferability of PRSs across ancestries and thereby helps address health disparity.
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Affiliation(s)
- Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
| | - Ming Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Fuwei Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China
- Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Kai Gao
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Yimin Cai
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Can Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Caibo Ning
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Yanmin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Sangni Qian
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hao Bai
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China
- Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Yizhuo Liu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Heng Zhang
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Shuoni Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Xiangpan Li
- Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China
| | - Yongchang Wei
- Department of Gastrointestinal Oncology, Hubei Cancer Clinical Study Center, Zhongnan Hospital of Wuhan University, Wuhan, China
| | - Bin Li
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, Wuhan University, Wuhan, China
| | - Jinhua Yang
- Jiashan Institute of Cancer Prevention and Treatment, Jiashan, China
| | - Mingjuan Jin
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, Department of Gastrointestinal Oncology, Zhongnan Hospital of Wuhan University, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, 430071, China.
- Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan University, Wuhan, 430071, China.
- Jiangsu Collaborative Innovation Center for Cancer Personalized Medicine, Nanjing Medical University, Nanjing, China.
| | - Kun Chen
- Department of Epidemiology and Biostatistics, School of Public Health, Zhejiang University School of Medicine, Hangzhou, China.
- Department of Colorectal Surgery and Oncology, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China.
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12
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Grunin M, Triffon D, Beykin G, Rahmani E, Schweiger R, Tiosano L, Khateb S, Hagbi-Levi S, Rinsky B, Munitz R, Winkler TW, Heid IM, Halperin E, Carmi S, Chowers I. Genome wide association study and genomic risk prediction of age related macular degeneration in Israel. Sci Rep 2024; 14:13034. [PMID: 38844476 PMCID: PMC11156861 DOI: 10.1038/s41598-024-63065-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Accepted: 05/24/2024] [Indexed: 06/09/2024] Open
Abstract
The risk of developing age-related macular degeneration (AMD) is influenced by genetic background. In 2016, the International AMD Genomics Consortium (IAMDGC) identified 52 risk variants in 34 loci, and a polygenic risk score (PRS) from these variants was associated with AMD. The Israeli population has a unique genetic composition: Ashkenazi Jewish (AJ), Jewish non-Ashkenazi, and Arab sub-populations. We aimed to perform a genome-wide association study (GWAS) for AMD in Israel, and to evaluate PRSs for AMD. Our discovery set recruited 403 AMD patients and 256 controls at Hadassah Medical Center. We genotyped individuals via custom exome chip. We imputed non-typed variants using cosmopolitan and AJ reference panels. We recruited additional 155 cases and 69 controls for validation. To evaluate predictive power of PRSs for AMD, we used IAMDGC summary-statistics excluding our study and developed PRSs via clumping/thresholding or LDpred2. In our discovery set, 31/34 loci reported by IAMDGC were AMD-associated (P < 0.05). Of those, all effects were directionally consistent with IAMDGC and 11 loci had a P-value under Bonferroni-corrected threshold (0.05/34 = 0.0015). At a 5 × 10-5 threshold, we discovered four suggestive associations in FAM189A1, IGDCC4, C7orf50, and CNTNAP4. Only the FAM189A1 variant was AMD-associated in the replication cohort after Bonferroni-correction. A prediction model including LDpred2-based PRS + covariates had an AUC of 0.82 (95% CI 0.79-0.85) and performed better than covariates-only model (P = 5.1 × 10-9). Therefore, previously reported AMD-associated loci were nominally associated with AMD in Israel. A PRS developed based on a large international study is predictive in Israeli populations.
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Affiliation(s)
- Michelle Grunin
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Daria Triffon
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel
| | - Gala Beykin
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Elior Rahmani
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - Regev Schweiger
- Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
- Department of Genetics, University of Cambridge, CB21TN, Cambridge, UK
| | - Liran Tiosano
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Samer Khateb
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Shira Hagbi-Levi
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Batya Rinsky
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Refael Munitz
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel
| | - Thomas W Winkler
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Iris M Heid
- Department of Genetic Epidemiology, University of Regensburg, Regensburg, Germany
| | - Eran Halperin
- Molecular Microbiology and Biotechnology, Tel Aviv University, Tel Aviv, Israel
- Department of Anesthesiology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Human Genetics, University of California, Los Angeles, Los Angeles, CA, USA
| | - Shai Carmi
- Braun School of Public Health and Community Medicine, The Hebrew University of Jerusalem, POB 12271, 9112102, Jerusalem, Israel.
| | - Itay Chowers
- Department of Ophthalmology, Hadassah-Hebrew University Medical Center, POB 12000, 91120, Jerusalem, Israel.
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13
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Fu R, Chen X, Niedermaier T, Seum T, Hoffmeister M, Brenner H. Excess Weight, Polygenic Risk Score, and Findings of Colorectal Neoplasms at Screening Colonoscopy. Am J Gastroenterol 2024; 119:00000434-990000000-01155. [PMID: 38704818 PMCID: PMC11365593 DOI: 10.14309/ajg.0000000000002853] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/12/2024] [Accepted: 04/25/2024] [Indexed: 05/07/2024]
Abstract
INTRODUCTION Excess weight is an established risk factor of colorectal cancer (CRC). However, evidence is lacking on how its impact varies by polygenic risk at different stages of colorectal carcinogenesis. METHODS We assessed the individual and joint associations of body mass index (BMI) and polygenic risk scores (PRSs) with findings of colorectal neoplasms among 4,784 participants of screening colonoscopy. Adjusted odds ratios (aORs) for excess weight derived by multiple logistic regression were converted to genetic risk equivalents (GREs) to quantify the impact of excess weight compared with genetic predisposition. RESULTS Overweight and obesity (BMI 25-<30 and ≥30 kg/m 2 ) were associated with increased risk of any colorectal neoplasm (aOR [95% confidence interval, CI] 1.26 [1.09-1.45] and 1.47 [1.24-1.75]). Obesity was associated with increased risk of advanced colorectal neoplasm (aOR [95% CI] 1.46 [1.16-1.84]). Dose-response relationships were seen for the PRS (stronger for advanced neoplasms than any neoplasms), with no interaction with BMI, suggesting multiplicative effects of both factors. Obese participants with a PRS in the highest tertile had a 2.3-fold (95% CI 1.7-3.1) and 2.9-fold (95% CI 1.9-4.3) increased risk of any colorectal neoplasm and advanced colorectal neoplasm, respectively. The aOR of obesity translated into a GRE of 38, meaning that its impact was estimated to be equivalent to the risk caused by 38 percentiles higher PRS for colorectal neoplasm. DISCUSSION Excess weight and polygenic risk are associated with increased risk of colorectal neoplasms in a multiplicative manner. Maintaining normal weight is estimated to have an equivalent effect as having 38 percentiles lower PRS.
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Affiliation(s)
- Ruojin Fu
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- College of Pharmacy, Jinan University, Guangzhou, China
| | - Tobias Niedermaier
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Teresa Seum
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
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14
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Jiang C, Zhou Q, Yi K, Yuan Y, Xie X. Colorectal cancer initiation: Understanding early-stage disease for intervention. Cancer Lett 2024; 589:216831. [PMID: 38574882 DOI: 10.1016/j.canlet.2024.216831] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/23/2024] [Revised: 03/18/2024] [Accepted: 03/21/2024] [Indexed: 04/06/2024]
Abstract
How tumors arise or the cause of precancerous lesions is a fundamental question in cancer biology. It is generally accepted that tumors originate from normal cells that undergo uncontrolled proliferation owing to genetic alterations. At the onset of adenoma formation, cancer driver mutations confer clonal growth advantage, enabling mutant cells to outcompete and eliminate the surrounding healthy cells. Hence, the development of precancerous lesions is not only attributed to the expansion of pre-malignant clones, but also relies on the relative fitness of mutated cells compared to the neighboring cells. Colorectal cancer (CRC) is an excellent model to investigate cancer origin as it follows a stereotypical process from mutant cell hyperplasia to adenoma formation and progression. Here, we review the evolving understanding of colonic tumor development, focusing on how cell intrinsic and extrinsic factors impact cell competition and the "clone war" between cancer-initiating cells and normal stem cells. We also discuss the promises and limitations of targeting cell competitiveness in cancer prevention and early intervention. The field of tumor initiation is currently in its infancy, elucidating the adenoma origin is crucial for designing effective prevention strategies and early treatments before cancer becomes incurable.
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Affiliation(s)
- Chao Jiang
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Haining, 314400, China
| | - Qiujing Zhou
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Haining, 314400, China; The Second Affiliated Hospital of Zhejiang Chinese Medical University, Hangzhou, Zhejiang, 310005, China
| | - Ke Yi
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Haining, 314400, China
| | - Ying Yuan
- Department of Medical Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, 310009, Zhejiang, China.
| | - Xin Xie
- Zhejiang University-University of Edinburgh Institute, School of Medicine, Zhejiang University, Haining, 314400, China; Department of Medical Oncology, Cancer Institute and Department of Orthopedics, The Second Affiliated Hospital, Zhejiang University School of Medicine, Zhejiang University, Hangzhou, 310029, China; Dr. Li Dak Sum & Yip Yio Chin Center for Stem Cell and Regenerative Medicine, Zhejiang University, Hangzhou, 310058, China.
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15
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Hibler EA, Szymaniak B, Abbass MA. Colorectal Cancer Risk between Mendelian and Non-Mendelian Inheritance. Clin Colon Rectal Surg 2024; 37:140-145. [PMID: 38606051 PMCID: PMC11006447 DOI: 10.1055/s-0043-1770382] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/13/2024]
Abstract
Hereditary colorectal cancer has been an area of focus for research and public health practitioners due to our ability to quantify risk and then act based on such results by enrolling patients in surveillance programs. The wide access to genetic testing and whole-genome sequencing has resulted in identifying many low/moderate penetrance genes. Above all, our understanding of the family component of colorectal cancer has been improving. Polygenic scores are becoming part of the risk assessment for many cancers, and the data about polygenic risk scores for colorectal cancer is promising. The challenge is determining how we incorporate this data in clinical care.
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Affiliation(s)
- Elizabeth A. Hibler
- Department of Preventive Medicine, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Brittany Szymaniak
- Department of Urology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
| | - Mohammad Ali Abbass
- Department of Surgery, Feinberg School of Medicine, Northwestern University, Chicago, Illinois
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Sullivan BA, Lieberman DA. Colon Polyp Surveillance: Separating the Wheat From the Chaff. Gastroenterology 2024; 166:743-757. [PMID: 38224860 DOI: 10.1053/j.gastro.2023.11.305] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/30/2023] [Revised: 11/20/2023] [Accepted: 11/22/2023] [Indexed: 01/17/2024]
Abstract
One goal of colorectal cancer (CRC) screening is to prevent CRC incidence by removing precancerous colonic polyps, which are detected in up to 50% of screening examinations. Yet, the lifetime risk of CRC is 3.9%-4.3%, so it is clear that most of these individuals with polyps would not develop CRC in their lifetime. It is, therefore, a challenge to determine which individuals with polyps will benefit from follow-up, and at what intervals. There is some evidence that individuals with advanced polyps, based on size and histology, benefit from intensive surveillance. However, a large proportion of individuals will have small polyps without advanced histologic features (ie, "nonadvanced"), where the benefits of surveillance are uncertain and controversial. Demand for surveillance will further increase as more polyps are detected due to increased screening uptake, recent United States recommendations to expand screening to younger individuals, and emergence of polyp detection technology. We review the current understanding and clinical implications of the natural history, biology, and outcomes associated with various categories of colon polyps based on size, histology, and number. Our aims are to highlight key knowledge gaps, specifically focusing on certain categories of polyps that may not be associated with future CRC risk, and to provide insights to inform research priorities and potential management strategies. Optimization of CRC prevention programs based on updated knowledge about the future risks associated with various colon polyps is essential to ensure cost-effective screening and surveillance, wise use of resources, and inform efforts to personalize recommendations.
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Affiliation(s)
- Brian A Sullivan
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina; Division of Gastroenterology, Department of Medicine, Duke University Medical Center, Durham, North Carolina.
| | - David A Lieberman
- Portland Veteran Affairs Medical Center, Portland, Oregon; Division of Gastroenterology and Hepatology, School of Medicine, Oregon Health and Science University, Portland, Oregon
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17
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Rosenthal EA, Hsu L, Thomas M, Peters U, Kachulis C, Patterson K, Jarvik GP. Comparing ancestry calibration approaches for a trans-ancestry colorectal cancer polygenic risk score. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2023.10.23.23296753. [PMID: 37961088 PMCID: PMC10635167 DOI: 10.1101/2023.10.23.23296753] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/15/2023]
Abstract
Background Colorectal cancer (CRC) is a complex disease with monogenic, polygenic and environmental risk factors. Polygenic risk scores (PRS) are being developed to identify high polygenic risk individuals. Due to differences in genetic background, PRS distributions vary by ancestry, necessitating calibration. Methods We compared four calibration methods using the All of Us Research Program Whole Genome Sequence data for a CRC PRS previously developed in participants of European and East Asian ancestry. The methods contrasted results from linear models with A) the entire data set or an ancestrally diverse training set AND B) covariates including principal components of ancestry or admixture. Calibration with the training set adjusted the variance in addition to the mean. Results All methods performed similarly within ancestry with OR (95% C.I.) per s.d. change in PRS: African 1.5 (1.02, 2.08), Admixed American 2.2 (1.27, 3.85), European 1.6 (1.43, 1.89), and Middle Eastern 1.1 (0.71, 1.63). Using admixture and an ancestrally diverse training set provided distributions closest to standard Normal with accurate upper tail frequencies. Conclusion Although the PRS is predictive of CRC risk for most ancestries, its performance varies by ancestry. Post-hoc calibration preserves the risk prediction within ancestries. Training a calibration model on ancestrally diverse participants to adjust both the mean and variance of the PRS, using admixture as covariates, created standard Normal z-scores. These z-scores can be used to identify patients at high polygenic risk, and can be incorporated into comprehensive risk scores including other known risk factors, allowing for more precise risk estimates.
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Sun C, Cheng X, Xu J, Chen H, Tao J, Dong Y, Wei S, Chen R, Meng X, Ma Y, Tian H, Guo X, Bi S, Zhang C, Kang J, Zhang M, Lv H, Shang Z, Lv W, Zhang R, Jiang Y. A review of disease risk prediction methods and applications in the omics era. Proteomics 2024:e2300359. [PMID: 38522029 DOI: 10.1002/pmic.202300359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2023] [Revised: 03/08/2024] [Accepted: 03/12/2024] [Indexed: 03/25/2024]
Abstract
Risk prediction and disease prevention are the innovative care challenges of the 21st century. Apart from freeing the individual from the pain of disease, it will lead to low medical costs for society. Until very recently, risk assessments have ushered in a new era with the emergence of omics technologies, including genomics, transcriptomics, epigenomics, proteomics, and so on, which potentially advance the ability of biomarkers to aid prediction models. While risk prediction has achieved great success, there are still some challenges and limitations. We reviewed the general process of omics-based disease risk model construction and the applications in four typical diseases. Meanwhile, we highlighted the problems in current studies and explored the potential opportunities and challenges for future clinical practice.
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Affiliation(s)
- Chen Sun
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Xiangshu Cheng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Jing Xu
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Haiyan Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Junxian Tao
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Yu Dong
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Siyu Wei
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Rui Chen
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xin Meng
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yingnan Ma
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
| | - Hongsheng Tian
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Xuying Guo
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Shuo Bi
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Chen Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Jingxuan Kang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Mingming Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Hongchao Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Zhenwei Shang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Wenhua Lv
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Ruijie Zhang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
| | - Yongshuai Jiang
- College of Bioinformatics Science and Technology, Harbin Medical University, Harbin, China
- The EWAS Project, Harbin, China
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19
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Hopper JL, Li S, MacInnis RJ, Dowty JG, Nguyen TL, Bui M, Dite GS, Esser VFC, Ye Z, Makalic E, Schmidt DF, Goudey B, Alpen K, Kapuscinski M, Win AK, Dugué PA, Milne RL, Jayasekara H, Brooks JD, Malta S, Calais-Ferreira L, Campbell AC, Young JT, Nguyen-Dumont T, Sung J, Giles GG, Buchanan D, Winship I, Terry MB, Southey MC, Jenkins MA. Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies. Genet Epidemiol 2024. [PMID: 38504141 DOI: 10.1002/gepi.22555] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2023] [Revised: 01/29/2024] [Accepted: 02/23/2024] [Indexed: 03/21/2024]
Abstract
Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.
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Affiliation(s)
- John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Genetic Technologies Ltd., Fitzroy, Victoria, Australia
| | - Vivienne F C Esser
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Daniel F Schmidt
- Department of Data Science and AI, Faculty of Information Technology, Monash University, Melbourne, Victoria, Australia
| | - Benjamin Goudey
- ARC Training Centre in Cognitive Computing for Medical Technologies, University of Melbourne, Carlton, Victoria, Australia
- The Florey Department of Neuroscience and Mental Health, The University of Melbourne, Parkville, Victoria, Australia
| | - Karen Alpen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Miroslaw Kapuscinski
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Aung Ko Win
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
- Genetic Medicine, Royal Melbourne Hospital, Parkville, Victoria, Australia
| | - Pierre-Antoine Dugué
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Roger L Milne
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Harindra Jayasekara
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Jennifer D Brooks
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Sue Malta
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Lucas Calais-Ferreira
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Alexander C Campbell
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
| | - Jesse T Young
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
- Institute for Mental Health Policy Research, Centre for Addiction and Mental Health, Toronto, Ontario, Canada
- Centre for Adolescent Health, Murdoch Children's Research Institute, Parkville, Victoria, Australia
- School of Population and Global Health, The University of Western Australia, Perth, Western Australia, Australia
- Justice Health Group, Curtin School of Population Health, Curtin University, Perth, Western Australia, Australia
| | - Tu Nguyen-Dumont
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
| | - Joohon Sung
- Department of Public Health Sciences, Division of Genome and Health Big Data, Graduate School of Public Health, Seoul National University, Seoul, South Korea
- Genome Medicine Institute, Seoul National University, Seoul, South Korea
- Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Daniel Buchanan
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Ingrid Winship
- Department of Medicine, Royal Melbourne Hospital, The University of Melbourne, Parkville, Victoria, Australia
| | - Mary Beth Terry
- Department of Epidemiology, Mailman School of Public Health, Columbia University, New York, New York, USA
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - Mark A Jenkins
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Melbourne, Victoria, Australia
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20
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Li S, Dite GS, MacInnis RJ, Bui M, Nguyen TL, Esser VFC, Ye Z, Dowty JG, Makalic E, Sung J, Giles GG, Southey MC, Hopper JL. Causation and familial confounding as explanations for the associations of polygenic risk scores with breast cancer: Evidence from innovative ICE FALCON and ICE CRISTAL analyses. Genet Epidemiol 2024. [PMID: 38472646 DOI: 10.1002/gepi.22556] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2023] [Accepted: 02/23/2024] [Indexed: 03/14/2024]
Abstract
A polygenic risk score (PRS) combines the associations of multiple genetic variants that could be due to direct causal effects, indirect genetic effects, or other sources of familial confounding. We have developed new approaches to assess evidence for and against causation by using family data for pairs of relatives (Inference about Causation from Examination of FAmiliaL CONfounding [ICE FALCON]) or measures of family history (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLyses [ICE CRISTAL]). Inference is made from the changes in regression coefficients of relatives' PRSs or PRS and family history before and after adjusting for each other. We applied these approaches to two breast cancer PRSs and multiple studies and found that (a) for breast cancer diagnosed at a young age, for example, <50 years, there was no evidence that the PRSs were causal, while (b) for breast cancer diagnosed at later ages, there was consistent evidence for causation explaining increasing amounts of the PRS-disease association. The genetic variants in the PRS might be in linkage disequilibrium with truly causal variants and not causal themselves. These PRSs cause minimal heritability of breast cancer at younger ages. There is also evidence for nongenetic factors shared by first-degree relatives that explain breast cancer familial aggregation. Familial associations are not necessarily due to genes, and genetic associations are not necessarily causal.
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Affiliation(s)
- Shuai Li
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Murdoch Children's Research Institute, Royal Children's Hospital, Parkville, Victoria, Australia
| | - Gillian S Dite
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Genetic Technologies Ltd., Fitzroy, Victoria, Australia
| | - Robert J MacInnis
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Minh Bui
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Tuong L Nguyen
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Vivienne F C Esser
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Zhoufeng Ye
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - James G Dowty
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Enes Makalic
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
| | - Joohon Sung
- Division of Genome and Health Big Data, Department of Public Health Sciences, Graduate School of Public Health, Seoul National University, Seoul, Korea
- Genomic Medicine Institute, Seoul National University, Euigwahakgwan #402, Seoul National University College of Medicine, 103, Daehak-ro, Jongno-gu, Seoul, South Korea
- Institute of Health and Environment, Seoul National University, 1st GwanakRo, Seoul, South Korea
| | - Graham G Giles
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
| | - Melissa C Southey
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia
- Department of Clinical Pathology, The University of Melbourne, Parkville, Victoria, Australia
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, Victoria, Australia
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21
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Tamlander M, Jermy B, Seppälä TT, Färkkilä M, Widén E, Ripatti S, Mars N. Genome-wide polygenic risk scores for colorectal cancer have implications for risk-based screening. Br J Cancer 2024; 130:651-659. [PMID: 38172535 PMCID: PMC10876651 DOI: 10.1038/s41416-023-02536-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2023] [Revised: 11/27/2023] [Accepted: 11/30/2023] [Indexed: 01/05/2024] Open
Abstract
BACKGROUND Hereditary factors, including single genetic variants and family history, can be used for targeting colorectal cancer (CRC) screening, but limited data exist on the impact of polygenic risk scores (PRS) on risk-based CRC screening. METHODS Using longitudinal health and genomics data on 453,733 Finnish individuals including 8801 CRC cases, we estimated the impact of a genome-wide CRC PRS on CRC screening initiation age through population-calibrated incidence estimation over the life course in men and women. RESULTS Compared to the cumulative incidence of CRC at age 60 in Finland (the current age for starting screening in Finland), a comparable cumulative incidence was reached 5 and 11 years earlier in persons with high PRS (80-99% and >99%, respectively), while those with a low PRS (< 20%) reached comparable incidence 7 years later. The PRS was associated with increased risk of post-colonoscopy CRC after negative colonoscopy (hazard ratio 1.76 per PRS SD, 95% CI 1.54-2.01). Moreover, the PRS predicted colorectal adenoma incidence and improved incident CRC risk prediction over non-genetic risk factors. CONCLUSIONS Our findings demonstrate that a CRC PRS can be used for risk stratification of CRC, with further research needed to optimally integrate the PRS into risk-based screening.
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Affiliation(s)
- Max Tamlander
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Bradley Jermy
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Toni T Seppälä
- Faculty of Medicine and Health Technology, University of Tampere and TAYS Cancer Centre, Tampere, Finland
- Department of Gastroenterology and Alimentary Tract Surgery, Tampere University Hospital, Tampere, Finland
- Applied Tumor Genomics Research Program, University of Helsinki, Helsinki, Finland
- Abdominal Center, Helsinki University Hospital, Helsinki University, Helsinki, Finland
| | - Martti Färkkilä
- Abdominal Center, Helsinki University Hospital, Helsinki University, Helsinki, Finland
| | - Elisabeth Widén
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland
- Clinicum, Department of Public Health, University of Helsinki, Helsinki, Finland
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Nina Mars
- Institute for Molecular Medicine Finland, FIMM, HiLIFE, University of Helsinki, Helsinki, Finland.
- Broad Institute of MIT and Harvard, Cambridge, MA, USA.
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22
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Gibson TM, Karyadi DM, Hartley SW, Arnold MA, Berrington de Gonzalez A, Conces MR, Howell RM, Kapoor V, Leisenring WM, Neglia JP, Sampson JN, Turcotte LM, Chanock SJ, Armstrong GT, Morton LM. Polygenic risk scores, radiation treatment exposures and subsequent cancer risk in childhood cancer survivors. Nat Med 2024; 30:690-698. [PMID: 38454124 PMCID: PMC11029534 DOI: 10.1038/s41591-024-02837-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2023] [Accepted: 01/26/2024] [Indexed: 03/09/2024]
Abstract
Survivors of childhood cancer are at increased risk for subsequent cancers attributable to the late effects of radiotherapy and other treatment exposures; thus, further understanding of the impact of genetic predisposition on risk is needed. Combining genotype data for 11,220 5-year survivors from the Childhood Cancer Survivor Study and the St Jude Lifetime Cohort, we found that cancer-specific polygenic risk scores (PRSs) derived from general population, genome-wide association study, cancer loci identified survivors of European ancestry at increased risk of subsequent basal cell carcinoma (odds ratio per s.d. of the PRS: OR = 1.37, 95% confidence interval (CI) = 1.29-1.46), female breast cancer (OR = 1.42, 95% CI = 1.27-1.58), thyroid cancer (OR = 1.48, 95% CI = 1.31-1.67), squamous cell carcinoma (OR = 1.20, 95% CI = 1.00-1.44) and melanoma (OR = 1.60, 95% CI = 1.31-1.96); however, the association for colorectal cancer was not significant (OR = 1.19, 95% CI = 0.94-1.52). An investigation of joint associations between PRSs and radiotherapy found more than additive increased risks of basal cell carcinoma, and breast and thyroid cancers. For survivors with radiotherapy exposure, the cumulative incidence of subsequent cancer by age 50 years was increased for those with high versus low PRS. These findings suggest a degree of shared genetic etiology for these malignancy types in the general population and survivors, which remains evident in the context of strong radiotherapy-related risk.
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Affiliation(s)
- Todd M Gibson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA.
| | - Danielle M Karyadi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stephen W Hartley
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Michael A Arnold
- Department of Pathology, Children's Hospital of Colorado, University of Colorado, Denver, CO, USA
| | | | - Miriam R Conces
- Department of Pathology and Laboratory Medicine, Nationwide Children's Hospital, Columbus, OH, USA
| | - Rebecca M Howell
- Radiation Physics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Vidushi Kapoor
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Wendy M Leisenring
- Cancer Prevention and Clinical Statistics Programs, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Joseph P Neglia
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Joshua N Sampson
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Lucie M Turcotte
- Department of Pediatrics, University of Minnesota, Minneapolis, MN, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Gregory T Armstrong
- Department of Epidemiology and Cancer Control, St Jude Children's Research Hospital, Memphis, TN, USA
| | - Lindsay M Morton
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
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23
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Sun Q, Rowland BT, Chen J, Mikhaylova AV, Avery C, Peters U, Lundin J, Matise T, Buyske S, Tao R, Mathias RA, Reiner AP, Auer PL, Cox NJ, Kooperberg C, Thornton TA, Raffield LM, Li Y. Improving polygenic risk prediction in admixed populations by explicitly modeling ancestral-differential effects via GAUDI. Nat Commun 2024; 15:1016. [PMID: 38310129 PMCID: PMC10838303 DOI: 10.1038/s41467-024-45135-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2022] [Accepted: 01/16/2024] [Indexed: 02/05/2024] Open
Abstract
Polygenic risk scores (PRS) have shown successes in clinics, but most PRS methods focus only on participants with distinct primary continental ancestry without accommodating recently-admixed individuals with mosaic continental ancestry backgrounds for different segments of their genomes. Here, we develop GAUDI, a novel penalized-regression-based method specifically designed for admixed individuals. GAUDI explicitly models ancestry-differential effects while borrowing information across segments with shared ancestry in admixed genomes. We demonstrate marked advantages of GAUDI over other methods through comprehensive simulation and real data analyses for traits with associated variants exhibiting ancestral-differential effects. Leveraging data from the Women's Health Initiative study, we show that GAUDI improves PRS prediction of white blood cell count and C-reactive protein in African Americans by > 64% compared to alternative methods, and even outperforms PRS-CSx with large European GWAS for some scenarios. We believe GAUDI will be a valuable tool to mitigate disparities in PRS performance in admixed individuals.
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Affiliation(s)
- Quan Sun
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Bryce T Rowland
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Jiawen Chen
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Anna V Mikhaylova
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Christy Avery
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jessica Lundin
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Tara Matise
- Department of Genetics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Steve Buyske
- Department of Statistics, Rutgers University, New Brunswick, NJ, 08901, USA
| | - Ran Tao
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Department of Biostatistics, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Rasika A Mathias
- Department of Medicine, Johns Hopkins University, Baltimore, MD, 21287, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA, 98195, USA
| | - Paul L Auer
- Division of Biostatistics, Institute for Health and Equity, and Cancer Center, Medical College of Wisconsin, Milwaukee, WI, 53226, USA
| | - Nancy J Cox
- Vanderbilt Genetics Institute, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
- Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, 37232, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA, 98195, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
| | - Yun Li
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA.
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Nakase T, Guerra G, Ostrom QT, Ge T, Melin B, Wrensch M, Wiencke JK, Jenkins RB, Eckel-Passow JE, Bondy ML, Francis SS, Kachuri L. Genome-wide Polygenic Risk Scores Predict Risk of Glioma and Molecular Subtypes. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2024:2024.01.10.24301112. [PMID: 38260701 PMCID: PMC10802631 DOI: 10.1101/2024.01.10.24301112] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Background Polygenic risk scores (PRS) aggregate the contribution of many risk variants to provide a personalized genetic susceptibility profile. Since sample sizes of glioma genome-wide association studies (GWAS) remain modest, there is a need to find efficient ways of capturing genetic risk factors using available germline data. Methods We developed a novel PRS (PRS-CS) that uses continuous shrinkage priors to model the joint effects of over 1 million polymorphisms on disease risk and compared it to an approach (PRS-CT) that selects a limited set of independent variants that reach genome-wide significance (P<5×10-8). PRS models were trained using GWAS results stratified by histological (10,346 cases, 14,687 controls) and molecular subtype (2,632 cases, 2,445 controls), and validated in two independent cohorts. Results PRS-CS was consistently more predictive than PRS-CT across glioma subtypes with an average increase in explained variance (R2) of 21%. Improvements were particularly pronounced for glioblastoma tumors, with PRS-CS yielding larger effect sizes (odds ratio (OR)=1.93, P=2.0×10-54 vs. OR=1.83, P=9.4×10-50) and higher explained variance (R2=2.82% vs. R2=2.56%). Individuals in the 95th percentile of the PRS-CS distribution had a 3-fold higher lifetime absolute risk of IDH mutant (0.63%) and IDH wildtype (0.76%) glioma relative to individuals with average PRS. PRS-CS also showed high classification accuracy for IDH mutation status among cases (AUC=0.895). Conclusions Our novel genome-wide PRS may improve the identification of high-risk individuals and help distinguish between prognostic glioma subtypes, increasing the potential clinical utility of germline genetics in glioma patient management.
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Affiliation(s)
- Taishi Nakase
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
| | - Geno Guerra
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Quinn T. Ostrom
- Department of Neurosurgery, Duke University School of Medicine, Durham, NC, USA
| | - Tian Ge
- Psychiatric and Neurodevelopmental Genetics Unit, Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA, USA
- Center for Precision Psychiatry, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Beatrice Melin
- Department of Radiation Sciences, Oncology Umeå University, Umeå, Sweden
| | - Margaret Wrensch
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - John K. Wiencke
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
| | - Robert B. Jenkins
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | | | | | - Melissa L. Bondy
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Stephen S. Francis
- Department of Neurological Surgery, University of California San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California San Francisco, San Francisco, CA, USA
- Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Linda Kachuri
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
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25
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Barnett EJ, Onete DG, Salekin A, Faraone SV. Genomic Machine Learning Meta-regression: Insights on Associations of Study Features With Reported Model Performance. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2024; 21:169-177. [PMID: 38109236 DOI: 10.1109/tcbb.2023.3343808] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/20/2023]
Abstract
Many studies have been conducted with the goal of correctly predicting diagnostic status of a disorder using the combination of genomic data and machine learning. It is often hard to judge which components of a study led to better results and whether better reported results represent a true improvement or an uncorrected bias inflating performance. We extracted information about the methods used and other differentiating features in genomic machine learning models. We used these features in linear regressions predicting model performance. We tested for univariate and multivariate associations as well as interactions between features. Of the models reviewed, 46% used feature selection methods that can lead to data leakage. Across our models, the number of hyperparameter optimizations reported, data leakage due to feature selection, model type, and modeling an autoimmune disorder were significantly associated with an increase in reported model performance. We found a significant, negative interaction between data leakage and training size. Our results suggest that methods susceptible to data leakage are prevalent among genomic machine learning research, resulting in inflated reported performance. Best practice guidelines that promote the avoidance and recognition of data leakage may help the field avoid biased results.
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26
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Zhan J, Cen W, Zhu J, Ye Y. Development of a Novel Lipid Metabolism-related Gene Prognostic Signature for Patients with Colorectal Cancer. Recent Pat Anticancer Drug Discov 2024; 19:209-222. [PMID: 37723964 DOI: 10.2174/1574892818666230731121815] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 07/03/2023] [Accepted: 07/13/2023] [Indexed: 09/20/2023]
Abstract
BACKGROUND The purpose of this study was to explore the expression profiles of lipid metabolism-related genes in patients with Colorectal Cancer (CRC). METHODS The lipid metabolism statuses of CRC patients from The Cancer Genome Atlas (TCGA) were analyzed. Risk characteristics were constructed by univariate Cox regression and minimum Absolute contraction and Selection Operator (LASSO) Cox regression. A histogram was constructed based on factors such as age, sex, TNM stage, T stage, N stage, and risk score to provide a visual tool for clinicians to predict the probability of 1-year, 3-year, and 5-year OS for CRC patients. By determining Area Under Curve (AUC) values, the time-dependent Receiver Operating characteristic Curve (ROC) was used to evaluate the efficiency of our model in predicting prognosis. RESULTS A novel risk signal based on lipid metabolism-related genes was constructed to predict the survival of CRC patients. Risk characteristics were shown to be an independent prognostic factor in CRC patients (p <0.001). There were significant differences in the abundance and immune characteristics of tumor-filtering immune cells between high-risk and low-risk groups. The nomogram had a high potential for clinical application and the ROC AUC value was 0.827. Moreover, ROC analysis demonstrated that the nomogram model was more accurate to predict the survival of CRC patients than age, gender, stage and risk score. CONCLUSION In this study, we demonstrated a lipid metabolism-related genes prognosis biomarker associated with the tumor immune micro-environment in patients with CRC.
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Affiliation(s)
- Jing Zhan
- Department of Surgery, Wenzhou Hospital of Traditional Chinese Medicine Affiliated to Zhejiang Chinese Medicine University, Wenzhou, Zhejiang, 325000, China
| | - Wei Cen
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China
| | - Junchang Zhu
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China
| | - Yunliang Ye
- Department of Colorectal and Anal Surgery, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, 325000, China
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Chen X, Heisser T, Cardoso R, Hibbert J, Hoffmeister M, Brenner H. Beyond familial risk: deriving risk-adapted starting ages of screening among people with a family history of colorectal cancer. Cancer Commun (Lond) 2023; 43:1377-1380. [PMID: 37874634 PMCID: PMC10693305 DOI: 10.1002/cac2.12499] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/10/2023] [Revised: 10/05/2023] [Accepted: 10/16/2023] [Indexed: 10/25/2023] Open
Affiliation(s)
- Xuechen Chen
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
- Medical Faculty HeidelbergHeidelberg UniversityHeidelbergGermany
| | - Thomas Heisser
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Rafael Cardoso
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Julia Hibbert
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
- Medical Faculty HeidelbergHeidelberg UniversityHeidelbergGermany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergGermany
- Division of Preventive OncologyGerman Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT)HeidelbergGermany
- German Cancer Consortium (DKTK)German Cancer Research Center (DKFZ)HeidelbergGermany
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28
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Ladabaum U, Ko CW. Colorectal Cancer Risk Prediction to Tailor Screening: Will We Embrace It or KISS It Goodbye? Clin Gastroenterol Hepatol 2023; 21:3236-3237. [PMID: 37100217 DOI: 10.1016/j.cgh.2023.04.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/10/2023] [Accepted: 04/12/2023] [Indexed: 04/28/2023]
Affiliation(s)
- Uri Ladabaum
- Division of Gastroenterology and Hepatology, Department of Medicine, Stanford University School of Medicine, Stanford, California
| | - Cynthia W Ko
- Division of Gastroenterology, University of Washington School of Medicine, Seattle, Washington
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29
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van den Puttelaar R, Meester RGS, Peterse EFP, Zauber AG, Zheng J, Hayes RB, Su YR, Lee JK, Thomas M, Sakoda LC, Li Y, Corley DA, Peters U, Hsu L, Lansdorp-Vogelaar I. Risk-Stratified Screening for Colorectal Cancer Using Genetic and Environmental Risk Factors: A Cost-Effectiveness Analysis Based on Real-World Data. Clin Gastroenterol Hepatol 2023; 21:3415-3423.e29. [PMID: 36906080 PMCID: PMC10491743 DOI: 10.1016/j.cgh.2023.03.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Revised: 02/22/2023] [Accepted: 03/01/2023] [Indexed: 03/13/2023]
Abstract
BACKGROUND & AIMS Previous studies on the cost-effectiveness of personalized colorectal cancer (CRC) screening were based on hypothetical performance of CRC risk prediction and did not consider the association with competing causes of death. In this study, we estimated the cost-effectiveness of risk-stratified screening using real-world data for CRC risk and competing causes of death. METHODS Risk predictions for CRC and competing causes of death from a large community-based cohort were used to stratify individuals into risk groups. A microsimulation model was used to optimize colonoscopy screening for each risk group by varying the start age (40-60 years), end age (70-85 years), and screening interval (5-15 years). The outcomes included personalized screening ages and intervals and cost-effectiveness compared with uniform colonoscopy screening (ages 45-75, every 10 years). Key assumptions were varied in sensitivity analyses. RESULTS Risk-stratified screening resulted in substantially different screening recommendations, ranging from a one-time colonoscopy at age 60 for low-risk individuals to a colonoscopy every 5 years from ages 40 to 85 for high-risk individuals. Nevertheless, on a population level, risk-stratified screening would increase net quality-adjusted life years gained (QALYG) by only 0.7% at equal costs to uniform screening or reduce average costs by 1.2% for equal QALYG. The benefit of risk-stratified screening improved when it was assumed to increase participation or costs less per genetic test. CONCLUSIONS Personalized screening for CRC, accounting for competing causes of death risk, could result in highly tailored individual screening programs. However, average improvements across the population in QALYG and cost-effectiveness compared with uniform screening are small.
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Affiliation(s)
| | - Reinier G S Meester
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Elisabeth F P Peterse
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands; Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Ann G Zauber
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Jiayin Zheng
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Richard B Hayes
- Division of Epidemiology, Department of Population Health, New York University School of Medicine, New York, New York
| | - Yu-Ru Su
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington; Biostatistics Unit, Kaiser Permanente Washington Health Research Institute, Seattle, Washington
| | - Jeffrey K Lee
- Division of Research, Kaiser Permanente Northern California, Oakland, California; Department of Gastroenterology, Kaiser Permanente San Francisco, San Francisco, California
| | - Minta Thomas
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Lori C Sakoda
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington; Division of Research, Kaiser Permanente Northern California, Oakland, California
| | - Yi Li
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, California; Department of Gastroenterology, Kaiser Permanente San Francisco, San Francisco, California
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, Washington
| | - Iris Lansdorp-Vogelaar
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
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30
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Yang M, Narasimhan VM, Zhan FB. High polygenic risk score is a risk factor associated with colorectal cancer based on data from the UK Biobank. PLoS One 2023; 18:e0295155. [PMID: 38032963 PMCID: PMC10688735 DOI: 10.1371/journal.pone.0295155] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2023] [Accepted: 11/15/2023] [Indexed: 12/02/2023] Open
Abstract
Colorectal cancer (CRC) is a common cancer among both men and women and is one of the leading causes of cancer death worldwide. It is important to identify risk factors that may be used to help reduce morbidity and mortality of the disease. We used a case-control study design to explore the association between CRC, polygenic risk scores (PRS), and other factors. We extracted data about 2,585 CRC cases and 9,362 controls from the UK Biobank, calculated the PRS for these cases and controls based on 140 single nucleotide polymorphisms, and performed logistic regression analyses for the 11,947 cases and controls, for an older group (ages 50+), and for a younger group (younger than 50). Five significant risk factors were identified when all 11,947 cases and controls were considered. These factors were, in descending order of the values of the adjusted odds ratios (aOR), high PRS (aOR: 2.70, CI: 2.27-3.19), male sex (aOR: 1.52, CI: 1.39-1.66), unemployment (aOR: 1.47, CI: 1.17-1.85), family history of CRC (aOR: 1.44, CI: 1.28-1.62), and age (aOR: 1.01, CI: 1.01-1.02). These five risk factors also remained significant in the older group. For the younger group, only high PRS (aOR: 2.87, CI: 1.65-5.00) and family history of CRC (aOR: 1.73, CI: 1.12-2.67) were significant risk factors. These findings indicate that genetic risk for the disease is a significant risk factor for CRC even after adjusting for family history. Additional studies are needed to examine this association using larger samples and different population groups.
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Affiliation(s)
- Mei Yang
- Department of Geography and Environmental Studies, Texas State University, San Marcos, Texas, United States of America
| | - Vagheesh M. Narasimhan
- Department of Integrative Biology, The University of Texas at Austin, Austin, Texas, United States of America
- Department of Statistics and Data Science, The University of Texas at Austin, Austin, Texas, United States of America
| | - F. Benjamin Zhan
- Department of Geography and Environmental Studies, Texas State University, San Marcos, Texas, United States of America
- Department of Population Health, University of Texas Dell Medical School, Austin, Texas, United States of America
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Yu S, Cheng J, Li P, Tian L, Chen Z, Chen Z, Li Y, Song J. Association study for the role of MMP8 gene polymorphisms in Colorectal cancer susceptibility. BMC Cancer 2023; 23:1169. [PMID: 38031100 PMCID: PMC10688471 DOI: 10.1186/s12885-023-11662-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/19/2023] [Accepted: 11/21/2023] [Indexed: 12/01/2023] Open
Abstract
BACKGROUND Colorectal cancer (CRC) is one of the most common malignant tumors, influenced by several genetic loci in its clinical phenotypes. The aim of this study was to determine the relationship between the MMP8 gene polymorphism and CRC risk in the Chinese Han population. METHOD This study recruited 688 CRC patients and 690 healthy controls. The relationship between MMP8 polymorphism and CRC susceptibility was assessed by calculating the odds ratio (OR) and 95% confidence interval (CI) after stratifying by age, gender, body mass index (BMI), smoking, and alcohol consumption under a multi-genetic model. RESULTS MMP8 rs3740938 was associated with increased CRC predisposition (p = 0.016, OR = 1.24, 95% CI: 1.04-1.48), and this association was detected particularly in subjects aged > 60 years, females, people with BMI > 24 kg/m2, smokers, and drinkers. Moreover, rs3740938 was found to be associated with the pathological type of rectal cancer. CONCLUSIONS Our results first displayed that rs3740938 in MMP8 was a risk factor for CRC predisposition. This finding may provide a new biological perspective for understanding the role of the MMP8 gene in CRC pathogenesis.
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Affiliation(s)
- Shuyong Yu
- Department of Gastrointestinal Surgery IV, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Jiajia Cheng
- Department of Gastrointestinal Surgery IV, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Ping Li
- Department of Digestive Endoscopy, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Le Tian
- Department of Digestive Endoscopy, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Zhuang Chen
- Department of Gastroenterology, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Zhaowei Chen
- Department of Gastroenterology, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Yongyu Li
- Department of Gastroenterology, Hainan Cancer Hospital, 570100, Haikou, Hainan, China
| | - Jian Song
- Department of Gastroenterology, Southern University of Science and Technology Hospital, No. 6019 Liuxian Avenue, Nanshan District, 518000, Shenzhen, Guangdong, China.
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Dueñas N, Klinkhammer H, Bonifaci N, Spier I, Mayr A, Hassanin E, Diez-Villanueva A, Moreno V, Pineda M, Maj C, Capellà G, Aretz S, Brunet J. Ability of a polygenic risk score to refine colorectal cancer risk in Lynch syndrome. J Med Genet 2023; 60:1044-1051. [PMID: 37321833 DOI: 10.1136/jmg-2023-109344] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/21/2023] [Accepted: 05/12/2023] [Indexed: 06/17/2023]
Abstract
BACKGROUND Polygenic risk scores (PRSs) have been used to stratify colorectal cancer (CRC) risk in the general population, whereas its role in Lynch syndrome (LS), the most common type of hereditary CRC, is still conflicting. We aimed to assess the ability of PRS to refine CRC risk prediction in European-descendant individuals with LS. METHODS 1465 individuals with LS (557 MLH1, 517 MSH2/EPCAM, 299 MSH6 and 92 PMS2) and 5656 CRC-free population-based controls from two independent cohorts were included. A 91-SNP PRS was applied. A Cox proportional hazard regression model with 'family' as a random effect and a logistic regression analysis, followed by a meta-analysis combining both cohorts were conducted. RESULTS Overall, we did not observe a statistically significant association between PRS and CRC risk in the entire cohort. Nevertheless, PRS was significantly associated with a slightly increased risk of CRC or advanced adenoma (AA), in those with CRC diagnosed <50 years and in individuals with multiple CRCs or AAs diagnosed <60 years. CONCLUSION The PRS may slightly influence CRC risk in individuals with LS in particular in more extreme phenotypes such as early-onset disease. However, the study design and recruitment strategy strongly influence the results of PRS studies. A separate analysis by genes and its combination with other genetic and non-genetic risk factors will help refine its role as a risk modifier in LS.
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Affiliation(s)
- Nuria Dueñas
- Hereditary Cancer Program, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Oncology (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
| | - Hannah Klinkhammer
- Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
| | - Nuria Bonifaci
- Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Oncology (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
| | - Isabel Spier
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
- Institute of Human Genetics, Medical Faculty, University of Bonn, Bonn, Germany
- National Center for Hereditary Tumor Syndromes, University of Bonn, Bonn, Germany
| | - Andreas Mayr
- Institute for Medical Biometry, Informatics and Epidemiology, Medical Faculty, University of Bonn, Bonn, Germany
| | - Emadeldin Hassanin
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Anna Diez-Villanueva
- Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Colorectal Cancer Group (ONCOBELL), Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Epidemiology and Public Health (CIBERESP), Instituto Salud Carlos III, Madrid, Spain
| | - Victor Moreno
- Oncology Data Analytics Program (ODAP), Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Colorectal Cancer Group (ONCOBELL), Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Epidemiology and Public Health (CIBERESP), Instituto Salud Carlos III, Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine and Health Sciences and Universitat de Barcelona Institute of Complex Systems (UBICS), Universitat de Barcelona, Barcelona, Spain
| | - Marta Pineda
- Hereditary Cancer Program, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Oncology (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, Medical Faculty, University of Bonn, Bonn, Germany
| | - Gabriel Capellà
- Hereditary Cancer Program, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Oncology (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
| | - Stefan Aretz
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
- Institute of Human Genetics, Medical Faculty, University of Bonn, Bonn, Germany
- National Center for Hereditary Tumor Syndromes, University of Bonn, Bonn, Germany
| | - Joan Brunet
- Hereditary Cancer Program, Catalan Institute of Oncology - ICO, L'Hospitalet de Llobregat, Spain
- Hereditary Cancer Group, Molecular Mechanisms and Experimental Therapy in Oncology Program, Institut d'Investigació Biomèdica de Bellvitge - IDIBELL, L'Hospitalet de Llobregat, Spain
- Biomedical Research Centre Network for Oncology (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
- European Reference Network on Genetic Tumour Risk Syndromes (ERN GENTURIS), Nijmegen, Netherlands
- Hereditary Cancer Program, Catalan Institute of Oncology - ICO, Girona, Spain
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Sullivan BA, Qin X, Redding TS, Weiss D, Upchurch J, Sims KJ, Dominitz JA, Stone A, Ear B, Williams CD, Lieberman DA, Hauser ER. Colorectal Cancer Polygenic Risk Score Is Associated With Screening Colonoscopy Findings but Not Follow-Up Outcomes. GASTRO HEP ADVANCES 2023; 3:151-161. [PMID: 39129957 PMCID: PMC11307447 DOI: 10.1016/j.gastha.2023.10.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/21/2023] [Accepted: 10/03/2023] [Indexed: 08/13/2024]
Abstract
Background and Aims Colorectal cancer (CRC) polygenic risk scores (PRS) may help personalize CRC prevention strategies. We investigated whether an existing PRS was associated with advanced neoplasia (AN) in a population undergoing screening and follow-up colonoscopy. Methods We evaluated 10-year outcomes in the Cooperative Studies Program #380 screening colonoscopy cohort, which includes a biorepository of selected individuals with baseline AN (defined as CRC or adenoma ≥10 mm or villous histology, or high-grade dysplasia) and matched individuals without AN. A PRS was constructed from 136 prespecified CRC-risk single nucleotide polymorphisms. Multivariate logistic regression was used to evaluate the PRS for associations with AN prevalence at baseline screening colonoscopy or incident AN in participants with at least one follow-up colonoscopy. Results The PRS was associated with AN risk at baseline screening colonoscopy (P = .004). Participants in the lowest PRS quintile had more than a 70% decreased risk of AN at baseline (odds ratio 0.29, 95% confidence interval 0.14-0.58; P < .001) compared to participants with a PRS in the middle quintile. Using a PRS cut-off of more than the first quintile to indicate need for colonoscopy as primary screening, the sensitivity for detecting AN at baseline is 91.8%. We did not observe a relationship between the PRS and incident AN during follow-up (P = .28). Conclusion A PRS could identify individuals at low risk for prevalent AN. Ongoing work will determine whether this PRS can identify a subset of individuals at sufficiently low risk who could safely delay or be reassured about noninvasive screening. Otherwise, more research is needed to augment these genetic tools to predict incident AN during long-term follow-up.
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Affiliation(s)
- Brian A. Sullivan
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
- Division of Gastroenterology, Duke University, Durham, North Carolina
| | - Xuejun Qin
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
- Division of Gastroenterology, Duke University, Durham, North Carolina
| | - Thomas S. Redding
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
| | - David Weiss
- Cooperative Studies Program Coordinating Center, Perry Point VA Medical Center, Perry Point, Maryland
| | - Julie Upchurch
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
| | - Kellie J. Sims
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
| | - Jason A. Dominitz
- Division of Gastroenterology, VA Puget Sound Health Care System, Seattle, Washington
- Division of Gastroenterology, University of Washington School of Medicine, Seattle, Washington
| | - Anjanette Stone
- Cooperative Studies Program Pharmacogenomics Analysis Laboratory, Central Arkansas Veterans Health System, Little Rock, Arkansas
| | - Belinda Ear
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
| | - Christina D. Williams
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
- Division of Gastroenterology, Duke University, Durham, North Carolina
| | - David A. Lieberman
- Division of Gastroenterology, VA Portland Health Care System, Portland, Oregon
- Division of Gastroenterology, Oregon Health & Science University, Portland, Oregon
| | - Elizabeth R. Hauser
- Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, North Carolina
- Division of Gastroenterology, Duke University, Durham, North Carolina
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Thomas M, Su YR, Rosenthal EA, Sakoda LC, Schmit SL, Timofeeva MN, Chen Z, Fernandez-Rozadilla C, Law PJ, Murphy N, Carreras-Torres R, Diez-Obrero V, van Duijnhoven FJB, Jiang S, Shin A, Wolk A, Phipps AI, Burnett-Hartman A, Gsur A, Chan AT, Zauber AG, Wu AH, Lindblom A, Um CY, Tangen CM, Gignoux C, Newton C, Haiman CA, Qu C, Bishop DT, Buchanan DD, Crosslin DR, Conti DV, Kim DH, Hauser E, White E, Siegel E, Schumacher FR, Rennert G, Giles GG, Hampel H, Brenner H, Oze I, Oh JH, Lee JK, Schneider JL, Chang-Claude J, Kim J, Huyghe JR, Zheng J, Hampe J, Greenson J, Hopper JL, Palmer JR, Visvanathan K, Matsuo K, Matsuda K, Jung KJ, Li L, Le Marchand L, Vodickova L, Bujanda L, Gunter MJ, Matejcic M, Jenkins MA, Slattery ML, D'Amato M, Wang M, Hoffmeister M, Woods MO, Kim M, Song M, Iwasaki M, Du M, Udaltsova N, Sawada N, Vodicka P, Campbell PT, Newcomb PA, Cai Q, Pearlman R, Pai RK, Schoen RE, Steinfelder RS, Haile RW, Vandenputtelaar R, Prentice RL, Küry S, Castellví-Bel S, Tsugane S, Berndt SI, Lee SC, Brezina S, Weinstein SJ, Chanock SJ, Jee SH, Kweon SS, Vadaparampil S, Harrison TA, Yamaji T, Keku TO, Vymetalkova V, Arndt V, Jia WH, Shu XO, Lin Y, Ahn YO, Stadler ZK, Van Guelpen B, Ulrich CM, Platz EA, Potter JD, Li CI, Meester R, Moreno V, Figueiredo JC, Casey G, Lansdorp Vogelaar I, Dunlop MG, Gruber SB, Hayes RB, Pharoah PDP, Houlston RS, Jarvik GP, Tomlinson IP, Zheng W, Corley DA, Peters U, Hsu L. Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations. Nat Commun 2023; 14:6147. [PMID: 37783704 PMCID: PMC10545678 DOI: 10.1038/s41467-023-41819-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/05/2023] [Accepted: 09/19/2023] [Indexed: 10/04/2023] Open
Abstract
Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice.
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Affiliation(s)
- Minta Thomas
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Yu-Ru Su
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Biostatistics Division, Kaiser Permanente Washington Health Research Institute, Seattle, USA
| | - Elisabeth A Rosenthal
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, 98195, USA
| | - Lori C Sakoda
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Stephanie L Schmit
- Genomic Medicine Institute, Cleveland Clinic, Cleveland, OH, USA
- Population and Cancer Prevention Program, Case Comprehensive Cancer Center, Cleveland, USA
| | - Maria N Timofeeva
- Danish Institute for Advanced Study (DIAS), Epidemiology, Biostatistics and Biodemography, Department of Public Health, University of Southern Denmark, Odense, Denmark
- Colon Cancer Genetics Group, Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, U, Germany
| | - Zhishan Chen
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Ceres Fernandez-Rozadilla
- Instituto de Investigacion Sanitaria de Santiago (IDIS), Choupana sn, 15706, Santiago de Compostela, Spain
- Edinburgh Cancer Research Centre, Institute of Genomics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Philip J Law
- Division of Genetics and Epidemiology, The Institute of Cancer Reseach, London, SW7 3RP, UK
| | - Neil Murphy
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | - Robert Carreras-Torres
- Digestive Diseases and Microbiota Group, Girona Biomedical Research Institute (IDIBGI), Salt, 17190, Girona, Spain
| | - Virginia Diez-Obrero
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology, Barcelona, 08908, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute, Barcelona, 08908, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, 08908, Spain
| | | | - Shangqing Jiang
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Aesun Shin
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul National University Cancer Research Institute, Seoul, South Korea
| | - Alicja Wolk
- Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
| | - Amanda I Phipps
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | | | - Andrea Gsur
- .Center for Cancer Research, Medical University Vienna, Vienna, Austria
| | - Andrew T Chan
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Channing Division of Network Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Broad Institute of Harvard and MIT, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
- Department of Immunology and Infectious Diseases, Harvard T.H. Chan School of Public Health, Harvard University, Boston, MA, USA
| | - Ann G Zauber
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Anna H Wu
- University of Southern California, Preventative Medicine, Los Angeles, CA, USA
| | - Annika Lindblom
- Department of Clinical Genetics, Karolinska University Hospital, Stockholm, Sweden
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Caroline Y Um
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Catherine M Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Chris Gignoux
- Colorado Center for Personalized Medicine, University of Colorado - Anschutz Medical Campus, Aurora, CO, USA
| | - Christina Newton
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Christopher A Haiman
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Conghui Qu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - D Timothy Bishop
- Leeds Institute of Cancer and Pathology, University of Leeds, Leeds, UK
| | - Daniel D Buchanan
- Colorectal Oncogenomics Group, Department of Clinical Pathology, The University of Melbourne, Parkville, VIC, 3000, Australia
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC, 3000, Australia
- Genomic Medicine and Family Cancer Clinic, The Royal Melbourne Hospital, Parkville, VIC, 3000, Australia
| | - David R Crosslin
- Department of Bioinformatics and Medical Education, University of Washington Medical Center, Seattle, WA, 98195, USA
| | - David V Conti
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Dong-Hyun Kim
- Department of Social and Preventive Medicine, Hallym University College of Medicine, Okcheon-dong, South Korea
| | - Elizabeth Hauser
- VA Cooperative Studies Program Epidemiology Center, Durham Veterans Affairs Health Care System, Durham, NC, USA
- Duke Molecular Physiology Institute, Duke University Medical Center, Durham, NC, USA
| | - Emily White
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
- Department of Epidemiology, University of Washington School of Public Health, Seattle, WA, USA
| | - Erin Siegel
- Cancer Epidemiology Program, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA
| | - Fredrick R Schumacher
- Department of Population and Quantitative Health Sciences, Case Western Reserve University, Cleveland, OH, USA
| | - Gad Rennert
- Department of Community Medicine and Epidemiology, Lady Davis Carmel Medical Center, Haifa, Israel
- Ruth and Bruce Rappaport Faculty of Medicine, Technion-Israel Institute of Technology, Haifa, Israel
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia
| | - Heather Hampel
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Isao Oze
- .Division of Cancer Epidemiology and Prevention, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Jae Hwan Oh
- .Research Institute and Hospital, National Cancer Center, Goyang, South Korea, South Korea
| | - Jeffrey K Lee
- .Department of Gastroenterology, Kaiser Permanente San Francisco Medical Center, San Francisco, CA, USA
- Department of Pathology, University of Michigan, Ann Arbor, MI, 48104, USA
| | | | - Jenny Chang-Claude
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
- University Medical Centre Hamburg-Eppendorf, University Cancer Centre Hamburg (UCCH), Hamburg, Germany
| | - Jeongseon Kim
- Department of Cancer Biomedical Science, Graduate School of Cancer Science and Policy, National Cancer Center, Gyeonggi-do, South Korea
| | - Jeroen R Huyghe
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jiayin Zheng
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Jochen Hampe
- Department of Medicine I, University Hospital Dresden, Technische Universität Dresden (TU Dresden), Dresden, Germany
| | - Joel Greenson
- Department of Pathology, University of Michigan, Ann Arbor, MI, 48104, USA
| | - John L Hopper
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
- Department of Epidemiology, School of Public Health and Institute of Health and Environment, Seoul National University, Seoul, South Korea
| | - Julie R Palmer
- Slone Epidemiology Center, School of Medicine, Boston University, Boston, MA, USA
| | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Keitaro Matsuo
- Division of Molecular and Clinical Epidemiology, Aichi Cancer Center Research Institute, Nagoya, Japan
| | - Koichi Matsuda
- Laboratory of Clinical Genome Sequencing, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, University of Tokyo, Tokyo, Japan
| | - Keum Ji Jung
- Institute for Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Li Li
- Department of Family Medicine, University of Virginia, Charlottesville, VA, USA
| | | | - Ludmila Vodickova
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
- Faculty of Medicine and Biomedical Center in Pilsen, Charles University, Pilsen, Czech Republic
| | - Luis Bujanda
- Department of Gastroenterology, Biodonostia Health Research Institute, Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Universidad del País Vasco (UPV/EHU), San Sebastián, Spain
| | - Marc J Gunter
- Nutrition and Metabolism Branch, International Agency for Research on Cancer, World Health Organization, Lyon, France
| | | | - Mark A Jenkins
- University of Melbourne Centre for Cancer Research, Victorian Comprehensive Cancer Centre, Parkville, VIC, 3000, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, VIC, Australia
| | - Martha L Slattery
- Department of Internal Medicine, University of Utah, Salt Lake City, UT, USA
| | - Mauro D'Amato
- Department of Medicine and Surgery, LUM University, Camassima, Italy
- Gastrointestinal Genetics Lab, CIC bioGUNE-BRTA, Derio, Spain
| | - Meilin Wang
- Department of Environmental Genomics, School of Public Health, Nanjing Medical University, Nanjing, China
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Michael O Woods
- Memorial University of Newfoundland, Discipline of Genetics, St. John's, Canada
| | - Michelle Kim
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Mingyang Song
- Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Clinical and Translational Epidemiology Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA, USA
- Departments of Epidemiology and Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Motoki Iwasaki
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, National Cancer Center, Tokyo, Japan
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, National Cancer Center, Tokyo, Japan
| | - Mulong Du
- Department of Biostatistics, School of Public Health, Nanjing Medical University, Nanjing, China
- Department of Environmental Health, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Natalia Udaltsova
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Norie Sawada
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, National Cancer Center, Tokyo, Japan
| | - Pavel Vodicka
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Peter T Campbell
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Polly A Newcomb
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Qiuyin Cai
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Rachel Pearlman
- Division of Human Genetics, Department of Internal Medicine, The Ohio State University Comprehensive Cancer Center, Columbus, OH, USA
| | - Rish K Pai
- Department of Laboratory Medicine and Pathology, Mayo Clinic Arizona, Scottsdale, AZ, USA
| | - Robert E Schoen
- Department of Medicine and Epidemiology, University of Pittsburgh Medical Center, Pittsburgh, PA, USA
| | - Robert S Steinfelder
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Robert W Haile
- Samuel Oschin Comprehensive Cancer Institute, CEDARS-SINAI, Los Angeles, CA, USA
| | - Rosita Vandenputtelaar
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Ross L Prentice
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Sébastien Küry
- Nantes Université, CHU Nantes, Service de Génétique Médicale, F-44000, Nantes, France
| | - Sergi Castellví-Bel
- Gastroenterology Department, Hospital Clínic, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBEREHD), University of Barcelona, Barcelona, Spain
| | - Shoichiro Tsugane
- Division of Cohort Research, National Cancer Center Institute for Cancer Control, National Cancer Center, Tokyo, Japan
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Soo Chin Lee
- National University Cancer Institute, Singapore, Singapore
| | - Stefanie Brezina
- .Center for Cancer Research, Medical University Vienna, Vienna, Austria
| | - Stephanie J Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sun Ha Jee
- Department of Epidemiology and Health Promotion, Graduate School of Public Health, Yonsei University, Seoul, Korea
| | - Sun-Seog Kweon
- Department of Preventive Medicine, Chonnam National University Medical School, Gwangju, Korea
- Jeonnam Regional Cancer Center, Chonnam National University Hwasun Hospital, Hwasun, Korea
| | - Susan Vadaparampil
- Departments of Epidemiology and Nutrition, Harvard TH Chan School of Public Health, Boston, MA, USA
| | - Tabitha A Harrison
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Taiki Yamaji
- Division of Epidemiology, National Cancer Center Institute for Cancer Control, National Cancer Center, Tokyo, Japan
| | - Temitope O Keku
- Center for Gastrointestinal Biology and Disease, University of North Carolina, Chapel Hill, NC, USA
| | - Veronika Vymetalkova
- Department of Molecular Biology of Cancer, Institute of Experimental Medicine of the Czech Academy of Sciences, Prague, Czech Republic
- Institute of Biology and Medical Genetics, First Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Volker Arndt
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Wei-Hua Jia
- State Key Laboratory of Oncology in South China, Cancer Center, Sun Yat-sen University, Guangzhou, China
| | - Xiao-Ou Shu
- Vanderbilt University Medical Center, Nashville, TN, USA
| | - Yi Lin
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Yoon-Ok Ahn
- Department of Preventive Medicine, Seoul National University College of Medicine, Seoul National University Cancer Research Institute, Seoul, South Korea
| | - Zsofia K Stadler
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Bethany Van Guelpen
- Department of Radiation Sciences, Oncology Unit, Umeå University, Umeå, Sweden
- Wallenberg Centre for Molecular Medicine, Umeå University, Umeå, Sweden
| | - Cornelia M Ulrich
- Huntsman Cancer Institute and Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA
| | - Elizabeth A Platz
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - John D Potter
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Christopher I Li
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA
| | - Reinier Meester
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Victor Moreno
- Oncology Data Analytics Program, Catalan Institute of Oncology-IDIBELL, L'Hospitalet de Llobregat, Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
- Department of Clinical Sciences, Faculty of Medicine, University of Barcelona, Barcelona, Spain
- ONCOBEL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
| | - Jane C Figueiredo
- Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Medicine, Samuel Oschin Comprehensive Cancer Institute, Cedars-Sinai Medical Center, Los Angeles, CA, USA
| | - Graham Casey
- Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA
| | - Iris Lansdorp Vogelaar
- Department of Public Health, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Malcolm G Dunlop
- Colon Cancer Genetics Group, Medical Research Council Human Genetics Unit, Institute of Genetics and Cancer, University of Edinburgh, Edinburgh, EH4 2XU, U, Germany
| | - Stephen B Gruber
- Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, CA, USA
| | - Richard B Hayes
- Division of Epidemiology, Department of Population Health, New York University School of Medicine, New York, NY, USA
| | - Paul D P Pharoah
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Richard S Houlston
- Division of Genetics and Epidemiology, The Institute of Cancer Reseach, London, SW7 3RP, UK
| | - Gail P Jarvik
- Department of Medicine (Medical Genetics), University of Washington Medical Center, Seattle, WA, 98195, USA
| | - Ian P Tomlinson
- Edinburgh Cancer Research Centre, Institute of Genomics and Cancer, University of Edinburgh, Crewe Road, Edinburgh, EH4 2XU, UK
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN, USA
| | - Douglas A Corley
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
- Department of Gastroenterology, Kaiser Permanente Medical Center, San Francisco, CA, USA
| | - Ulrike Peters
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA.
- Department of Epidemiology, University of Washington, Seattle, WA, USA.
| | - Li Hsu
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, 98109, USA.
- Department of Biostatistics, University of Washington, Seattle, WA, USA.
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Chen X, Heisser T, Cardoso R, Hoffmeister M, Brenner H. Personalized Initial Screening Age for Colorectal Cancer in Individuals at Average Risk. JAMA Netw Open 2023; 6:e2339670. [PMID: 37878311 PMCID: PMC10600582 DOI: 10.1001/jamanetworkopen.2023.39670] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/15/2023] [Accepted: 09/12/2023] [Indexed: 10/26/2023] Open
Abstract
Importance Colorectal cancer (CRC) risk varies widely in the population at average risk without a family history, but there are no established routines for translating this variation into personalized starting ages of screening. Objective To illustrate derivation of risk-adapted starting ages of CRC screening based on the concept of risk advancement period (RAP) using sex and a polygenic risk score (PRS) as an example. Design, Setting, and Participants This cohort study included participants in the UK Biobank study recruited in England, Wales, and Scotland between March 13, 2006, and October 1, 2010. Participants were aged 40 to 69 years, with no previous bowel cancer screening and no family history of CRC. Follow-up of cancer data was completed February 29, 2020, for England and Wales and January 31, 2021, for Scotland. The censoring date for death data was September 30, 2021, for England and Wales and October 31, 2021, for Scotland. Exposures Data on age, sex, and family history were collected at the baseline interview. A PRS was calculated based on 139 CRC-related risk loci. Main Outcomes and Measures Hazard ratios (HRs) of sex and PRS with CRC risk and mortality were estimated using Cox proportional hazards regression models and were translated to RAPs to quantify how many years of age earlier or later men and individuals in higher or lower PRS deciles would reach risks comparable with those of the reference group (ie, women or those in the 5th and 6th PRS deciles). Results Among 242 779 participants (median age, 55 [IQR, 48-61] years; 55.7% women), 2714 incident CRC cases were identified during a median follow-up of 11.2 (IQR, 10.5-11.8) years and 758 deaths during a median follow-up of 12.8 (IQR, 12.0-13.4) years. The HRs of CRC risk were 1.57 (95% CI, 1.46-1.70) for men vs women and ranged from 0.51 (95% CI, 0.41-0.62) to 2.29 (95% CI, 2.01-2.62) across PRS deciles compared with the reference. The RAPs were 5.6 (95% CI, 4.6-6.6) years for men vs women and ranged from -8.4 (95% CI, -11.0 to -5.9) to 10.3 (95% CI, 8.5-12.1) years across PRS deciles compared with the reference deciles. Risk-adapted starting ages of screening would vary by 24 years between men in the highest PRS decile and women in the lowest PRS decile. Similar results were obtained regarding CRC mortality. Conclusions and Relevance In this large cohort study including women and men at average risk of CRC, risk-adapted starting ages of screening strongly varied by sex and a PRS. The RAP concept could easily accommodate additional factors for defining personalized starting ages of screening.
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Affiliation(s)
- Xuechen Chen
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Medical Faculty Heidelberg, Heidelberg University, Heidelberg, Germany
| | - Thomas Heisser
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Rafael Cardoso
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany
- German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
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Grunin M, Triffon D, Beykin G, Rahmani E, Schweiger R, Tiosano L, Khateb S, Hagbi-Levi S, Rinsky B, Munitz R, Winkler TW, Heid IM, Halperin E, Carmi S, Chowers I. Genome-wide association study and genomic risk prediction of age-related macular degeneration in Israel. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.09.06.23295126. [PMID: 37732190 PMCID: PMC10508791 DOI: 10.1101/2023.09.06.23295126] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 09/22/2023]
Abstract
Purpose The risk of developing age-related macular degeneration(AMD) is influenced by genetic background. In 2016, International AMD Genomics Consortium(IAMDGC) identified 52 risk variants in 34 loci, and a polygenic risk score(PRS) based on these variants was associated with AMD. The Israeli population has a unique genetic composition: Ashkenazi Jewish(AJ), Jewish non-Ashkenazi, and Arab sub-populations. We aimed to perform a genome-wide association study(GWAS) for AMD in Israel, and to evaluate PRSs for AMD. Methods For our discovery set, we recruited 403 AMD patients and 256 controls at Hadassah Medical Center. We genotyped all individuals via custom exome chip. We imputed non-typed variants using cosmopolitan and AJ reference panels. We recruited additional 155 cases and 69 controls for validation. To evaluate predictive power of PRSs for AMD, we used IAMDGC summary statistics excluding our study and developed PRSs via either clumping/thresholding or LDpred2. Results In our discovery set, 31/34 loci previously reported by the IAMDGC were AMD associated with P<0.05. Of those, all effects were directionally consistent with the IAMDGC and 11 loci had a p-value under Bonferroni-corrected threshold(0.05/34=0.0015). At a threshold of 5x10 -5 , we discovered four suggestive associations in FAM189A1 , IGDCC4 , C7orf50 , and CNTNAP4 . However, only the FAM189A1 variant was AMD associated in the replication cohort after Bonferroni-correction. A prediction model including LDpred2-based PRS and other covariates had an AUC of 0.82(95%CI:0.79-0.85) and performed better than a covariates-only model(P=5.1x10 -9 ). Conclusions Previously reported AMD-associated loci were nominally associated with AMD in Israel. A PRS developed based on a large international study is predictive in Israeli populations.
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Abstract
Since the publication of the first genome-wide association study for cancer in 2007, thousands of common alleles that are associated with the risk of cancer have been identified. The relative risk associated with individual variants is small and of limited clinical significance. However, the combined effect of multiple risk variants as captured by polygenic scores (PGSs) may be much greater and therefore provide risk discrimination that is clinically useful. We review the considerable research efforts over the past 15 years for developing statistical methods for PGSs and their application in large-scale genome-wide association studies to develop PGSs for various cancers. We review the predictive performance of these PGSs and the multiple challenges currently limiting the clinical application of PGSs. Despite this, PGSs are beginning to be incorporated into clinical multifactorial risk prediction models to stratify risk in both clinical trials and clinical implementation studies.
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Affiliation(s)
- Xin Yang
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Siddhartha Kar
- MRC Integrative Epidemiology Unit, Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- Early Cancer Institute, Department of Oncology, University of Cambridge, Cambridge, UK
| | - Antonis C Antoniou
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | - Paul D P Pharoah
- Department of Computational Biomedicine, Cedars-Sinai Medical Center, Los Angeles, CA, USA.
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Shannon ML, Muhammad A, James NT, Williams ML, Breeyear J, Edwards T, Mosley JD, Choi L, Kannankeril P, Van Driest S. Variant-based heritability assessment of dexmedetomidine and fentanyl clearance in pediatric patients. Clin Transl Sci 2023; 16:1628-1638. [PMID: 37353859 PMCID: PMC10499425 DOI: 10.1111/cts.13574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2023] [Revised: 04/12/2023] [Accepted: 06/01/2023] [Indexed: 06/25/2023] Open
Abstract
Despite complex pathways of drug disposition, clinical pharmacogenetic predictors currently rely on only a few high effect variants. Quantification of the polygenic contribution to variability in drug disposition is necessary to prioritize target drugs for pharmacogenomic approaches and guide analytic methods. Dexmedetomidine and fentanyl, often used in postoperative care of pediatric patients, have high rates of inter-individual variability in dosing requirements. Analyzing previously generated population pharmacokinetic parameters, we used Bayesian hierarchical mixed modeling to measure narrow-sense (additive) heritability (h SNP 2 ) of dexmedetomidine and fentanyl clearance in children and identify relative contributions of small, moderate, and large effect-size variants toh SNP 2 . We used genome-wide association studies (GWAS) to identify variants contributing to variation in dexmedetomidine and fentanyl clearance, followed by functional analyses to identify associated pathways. For dexmedetomidine, median clearance was 33.0 L/h (interquartile range [IQR] 23.8-47.9 L/h) andh SNP 2 was estimated to be 0.35 (90% credible interval 0.00-0.90), with 45% ofh SNP 2 attributed to large-, 32% to moderate-, and 23% to small-effect variants. The fentanyl cohort had median clearance of 8.2 L/h (IQR 4.7-16.7 L/h), with estimatedh SNP 2 of 0.30 (90% credible interval 0.00-0.84). Large-effect variants accounted for 30% ofh SNP 2 , whereas moderate- and small-effect variants accounted for 37% and 33%, respectively. As expected, given small sample sizes, no individual variants or pathways were significantly associated with dexmedetomidine or fentanyl clearance by GWAS. We conclude that clearance of both drugs is highly polygenic, motivating the future use of polygenic risk scores to guide appropriate dosing of dexmedetomidine and fentanyl.
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Affiliation(s)
| | - Ayesha Muhammad
- School of MedicineVanderbilt UniversityNashvilleTennesseeUSA
| | - Nathan T. James
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Berry Consultants, LLCAustinTexasUSA
| | - Michael L. Williams
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
Department of Clinical Pharmacology and Quantitative PharmacologyAstraZenecaGothenburgSweden
| | - Joseph Breeyear
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Todd Edwards
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Jonathan D. Mosley
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Department of Biomedical InformaticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Leena Choi
- Department of BiostatisticsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Prince Kannankeril
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
| | - Sara Van Driest
- Department of MedicineVanderbilt University Medical CenterNashvilleTennesseeUSA
- Center for Pediatric Precision Medicine, Department of PediatricsVanderbilt University Medical CenterNashvilleTennesseeUSA
- Present address:
All of Us Research ProgramNational Institutes of HealthWashingtonDCUSA
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He H, Shen Q, He MM, Qiu W, Wang H, Zhang S, Qin S, Lu Z, Zhu Y, Tian J, Chang J, Wang K, Zhang X, Miao X, Song M, Zhong R. In Utero and Childhood/Adolescence Exposure to Tobacco Smoke, Genetic Risk, and Cancer Incidence in Adulthood: A Prospective Cohort Study. Mayo Clin Proc 2023; 98:1164-1176. [PMID: 37422733 DOI: 10.1016/j.mayocp.2023.03.024] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/31/2022] [Revised: 03/11/2023] [Accepted: 03/28/2023] [Indexed: 07/10/2023]
Abstract
OBJECTIVE To evaluate the association of early-life tobacco smoke exposure, especially interacting with cancer genetic variants, with adult cancer. PARTICIPANTS AND METHODS We examined the associations of in utero tobacco smoke exposure, age of smoking initiation, and their interaction with genetic risk levels with cancer incidence in 393,081 participants from the UK Biobank. Information on tobacco exposure was obtained by self-reported questionnaires. A cancer polygenic risk score was constructed by weighting and integrating 702 genome-wide association studies-identified risk variants. Cox proportional hazards regression models were used to calculate hazard ratios (HRs) for overall cancer and organ-specific cancer incidence. RESULTS During 11.8 years of follow-up, 23,450 (5.97%) and 23,413 (6.03%) incident cancers were included in the analyses of in utero exposure and age of smoking initiation, respectively. The HR (95% CI) for incident cancer in participants with in utero exposure to tobacco smoke was 1.04 (1.01-1.07) for overall cancer, 1.59 (1.44-1.75) for respiratory cancer, and 1.09 (1.03-1.17) for gastrointestinal cancer. The relative risk of incident cancer increased with earlier smoking initiation (Ptrend<.001), with the HR (95% CI) of 1.44 (1.36-1.51) for overall cancer, 13.28 (11.39-15.48) for respiratory cancer, and 1.72 (1.54-1.91) for gastrointestinal cancer in smokers with initiation in childhood compared with never smokers. Importantly, a positive additive interaction between age of smoking initiation and genetic risk was observed for overall cancer (Padditive=.04) and respiratory cancer (Padditive=.003) incidence. CONCLUSION In utero exposure and earlier smoking initiation are associated with overall and organ-specific cancer, and age of smoking initiation interaction with genetic risk is associated with respiratory cancer.
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Affiliation(s)
- Heng He
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China; Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Qian Shen
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ming-Ming He
- Department of Medical Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China
| | - Weihong Qiu
- Department of Epidemiology and Health Statistics, School of Public Health, Fujian Medical University, Fuzhou, China
| | - Haoxue Wang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shanshan Zhang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Shifan Qin
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Zequn Lu
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Ying Zhu
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jianbo Tian
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Jiang Chang
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China
| | - Kai Wang
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Xuehong Zhang
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA
| | - Xiaoping Miao
- Department of Epidemiology and Biostatistics, School of Public Health, TaiKang Center for Life and Medical Sciences, Wuhan University, Wuhan, China
| | - Mingyang Song
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA; Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA; Clinical and Translational Epidemiology Unit, Division of Gastroenterology, Massachusetts General Hospital, Harvard Medical School, Boston, MA
| | - Rong Zhong
- Department of Epidemiology and Biostatistics, Ministry of Education Key Lab of Environment and Health, School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Niedermaier T, Alwers E, Chen X, Heisser T, Hoffmeister M, Brenner H. A single measurement of fecal hemoglobin concentration outperforms polygenic risk score in colorectal cancer risk assessment. Cancer Commun (Lond) 2023; 43:947-950. [PMID: 37272255 PMCID: PMC10397559 DOI: 10.1002/cac2.12448] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/02/2022] [Revised: 04/14/2023] [Accepted: 05/25/2023] [Indexed: 06/06/2023] Open
Affiliation(s)
- Tobias Niedermaier
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
| | - Elizabeth Alwers
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
| | - Xuechen Chen
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
- Medical Faculty HeidelbergHeidelberg UniversityHeidelbergBaden‐WürttembergGermany
| | - Thomas Heisser
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
- Medical Faculty HeidelbergHeidelberg UniversityHeidelbergBaden‐WürttembergGermany
| | - Michael Hoffmeister
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging ResearchGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
- Division of Preventive OncologyGerman Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
- German Cancer Consortium (DKTK)German Cancer Research Center (DKFZ)HeidelbergBaden‐WürttembergGermany
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41
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Yoon N, Cho YS. Development of a Polygenic Risk Score for BMI to Assess the Genetic Susceptibility to Obesity and Related Diseases in the Korean Population. Int J Mol Sci 2023; 24:11560. [PMID: 37511320 PMCID: PMC10380444 DOI: 10.3390/ijms241411560] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2023] [Revised: 07/03/2023] [Accepted: 07/11/2023] [Indexed: 07/30/2023] Open
Abstract
Hundreds of genetic variants for body mass index (BMI) have been identified from numerous genome-wide association studies (GWAS) in different ethnicities. In this study, we aimed to develop a polygenic risk score (PRS) for BMI for predicting susceptibility to obesity and related traits in the Korean population. For this purpose, we obtained base data resulting from a GWAS on BMI using 57,110 HEXA study subjects from the Korean Genome and Epidemiology Study (KoGES). Subsequently, we calculated PRSs in 13,504 target subjects from the KARE and CAVAS studies of KoGES using the PRSice-2 software. The best-fit PRS for BMI (PRSBMI) comprising 53,341 SNPs was selected at a p-value threshold of 0.064, at which the model fit had the greatest R2 score. The PRSBMI was tested for its association with obesity-related quantitative traits and diseases in the target dataset. Linear regression analyses demonstrated significant associations of PRSBMI with BMI, blood pressure, and lipid traits. Logistic regression analyses revealed significant associations of PRSBMI with obesity, hypertension, and hypo-HDL cholesterolemia. We observed about 2-fold, 1.1-fold, and 1.2-fold risk for obesity, hypertension, and hypo-HDL cholesterolemia, respectively, in the highest-risk group in comparison to the lowest-risk group of PRSBMI in the test population. We further detected approximately 26.0%, 2.8%, and 3.9% differences in prevalence between the highest and lowest risk groups for obesity, hypertension, and hypo-HDL cholesterolemia, respectively. To predict the incidence of obesity and related diseases, we applied PRSBMI to the 16-year follow-up data of the KARE study. Kaplan-Meier survival analysis showed that the higher the PRSBMI, the higher the incidence of dyslipidemia and hypo-HDL cholesterolemia. Taken together, this study demonstrated that a PRS developed for BMI may be a valuable indicator to assess the risk of obesity and related diseases in the Korean population.
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Affiliation(s)
- Nara Yoon
- Department of Biomedical Science, Hallym University, Chuncheon 24252, Republic of Korea
| | - Yoon Shin Cho
- Department of Biomedical Science, Hallym University, Chuncheon 24252, Republic of Korea
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Darst BF, Shen J, Madduri RK, Rodriguez AA, Xiao Y, Sheng X, Saunders EJ, Dadaev T, Brook MN, Hoffmann TJ, Muir K, Wan P, Le Marchand L, Wilkens L, Wang Y, Schleutker J, MacInnis RJ, Cybulski C, Neal DE, Nordestgaard BG, Nielsen SF, Batra J, Clements JA, Cancer BioResource AP, Grönberg H, Pashayan N, Travis RC, Park JY, Albanes D, Weinstein S, Mucci LA, Hunter DJ, Penney KL, Tangen CM, Hamilton RJ, Parent MÉ, Stanford JL, Koutros S, Wolk A, Sørensen KD, Blot WJ, Yeboah ED, Mensah JE, Lu YJ, Schaid DJ, Thibodeau SN, West CM, Maier C, Kibel AS, Cancel-Tassin G, Menegaux F, John EM, Grindedal EM, Khaw KT, Ingles SA, Vega A, Rosenstein BS, Teixeira MR, Kogevinas M, Cannon-Albright L, Huff C, Multigner L, Kaneva R, Leach RJ, Brenner H, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Neuhausen SL, Isaacs WB, Nemesure B, Hennis AJ, Carpten J, Pandha H, De Ruyck K, Xu J, Razack A, Teo SH, Newcomb LF, Fowke JH, Neslund-Dudas C, Rybicki BA, Gamulin M, Usmani N, Claessens F, Gago-Dominguez M, Castelao JE, Townsend PA, Crawford DC, Petrovics G, Casey G, Roobol MJ, Hu JF, Berndt SI, Van Den Eeden SK, Easton DF, Chanock SJ, Cook MB, Wiklund F, Witte JS, Eeles RA, Kote-Jarai Z, Watya S, Gaziano JM, Justice AC, Conti DV, Haiman CA. Evaluating approaches for constructing polygenic risk scores for prostate cancer in men of African and European ancestry. Am J Hum Genet 2023; 110:1200-1206. [PMID: 37311464 PMCID: PMC10357473 DOI: 10.1016/j.ajhg.2023.05.010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Revised: 05/17/2023] [Accepted: 05/19/2023] [Indexed: 06/15/2023] Open
Abstract
Genome-wide polygenic risk scores (GW-PRSs) have been reported to have better predictive ability than PRSs based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer-risk variants from multi-ancestry GWASs and fine-mapping studies (PRS269). GW-PRS models were trained with a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls that we previously used to develop the multi-ancestry PRS269. Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI = 0.635-0.677) in African and 0.844 (95% CI = 0.840-0.848) in European ancestry men and corresponding prostate cancer ORs of 1.83 (95% CI = 1.67-2.00) and 2.19 (95% CI = 2.14-2.25), respectively, for each SD unit increase in the GW-PRS. Compared to the GW-PRS, in African and European ancestry men, the PRS269 had larger or similar AUCs (AUC = 0.679, 95% CI = 0.659-0.700 and AUC = 0.845, 95% CI = 0.841-0.849, respectively) and comparable prostate cancer ORs (OR = 2.05, 95% CI = 1.87-2.26 and OR = 2.21, 95% CI = 2.16-2.26, respectively). Findings were similar in the validation studies. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the PRS269 developed from multi-ancestry GWASs and fine-mapping.
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Affiliation(s)
- Burcu F Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA.
| | - Jiayi Shen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Yukai Xiao
- Argonne National Laboratory, Lemont, IL, USA
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | | | - Thomas J Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Peggy Wan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lynne Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Ying Wang
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | | | - Robert J MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, VIC, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Carlton, VIC, Australia
| | - Cezary Cybulski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - David E Neal
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK; University of Cambridge, Department of Oncology, Addenbrooke's Hospital, Cambridge, UK; Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge, UK
| | - Børge G Nordestgaard
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Sune F Nielsen
- Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark; Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Denmark
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia; Translational Research Institute, Brisbane, QLD, Australia
| | - Judith A Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, QLD, Australia; Translational Research Institute, Brisbane, QLD, Australia
| | - Australian Prostate Cancer BioResource
- Translational Research Institute, Brisbane, QLD, Australia; Australian Prostate Cancer Research Centre-Qld, Queensland University of Technology, Brisbane, QLD, Australia; Prostate Cancer Research Program, Monash University, Melbourne, VIC, Australia; Dame Roma Mitchell Cancer Centre, University of Adelaide, Adelaide, SA, Australia; Chris O'Brien Lifehouse and The Kinghorn Cancer Centre, Sydney, NSW, Australia
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Nora Pashayan
- University College London, Department of Applied Health Research, London, UK; Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Ruth C Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jong Y Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephanie Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Lorelei A Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David J Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kathryn L Penney
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital/Harvard Medical School, Boston, MA, USA
| | - Catherine M Tangen
- SWOG Statistical Center, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Robert J Hamilton
- Department of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, ON, Canada; Department of Surgery (Urology), University of Toronto, Toronto, ON, Canada
| | - Marie-Élise Parent
- Epidemiology and Biostatistics Unit, Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique, Laval, QC, Canada; Department of Social and Preventive Medicine, School of Public Health, University of Montreal, Montreal, QC, Canada
| | - Janet L Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Alicja Wolk
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden; Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Karina D Sørensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus N, Denmark; Department of Clinical Medicine, Aarhus University, Aarhus N, Denmark
| | - William J Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA; International Epidemiology Institute, Rockville, MD, USA
| | - Edward D Yeboah
- University of Ghana Medical School, Accra, Ghana; Korle Bu Teaching Hospital, Accra, Ghana
| | - James E Mensah
- University of Ghana Medical School, Accra, Ghana; Korle Bu Teaching Hospital, Accra, Ghana
| | - Yong-Jie Lu
- Centre for Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | - Daniel J Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Stephen N Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Catharine M West
- Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | | | - Adam S Kibel
- Division of Urologic Surgery, Brigham and Women's Hospital, Boston, MA, USA
| | - Géraldine Cancel-Tassin
- CeRePP, Tenon Hospital, Paris, France; Sorbonne Universite, GRC 5 Predictive Onco-urology, Tenon Hospital, Paris, France
| | - Florence Menegaux
- "Exposome and Heredity", CESP (UMR 1018), Faculté de Médecine, Université Paris-Saclay, Inserm, Gustave Roussy, Villejuif, France
| | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA; Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, USA; Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Sue A Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ana Vega
- Fundación Pública Galega Medicina Xenómica, Santiago De Compostela, Spain; Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain; Centro de Investigación en Red de Enfermedades Raras (CIBERER), Madrid, Spain
| | - Barry S Rosenstein
- Department of Radiation Oncology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manuel R Teixeira
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), Porto, Portugal; Biomedical Sciences Institute (ICBAS), University of Porto, Porto, Portugal
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain; IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain; Universitat Pompeu Fabra (UPF), Barcelona, Spain; CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Lisa Cannon-Albright
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, UT, USA; George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, UT, USA
| | - Chad Huff
- Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Luc Multigner
- University Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Radka Kaneva
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Robin J Leach
- Department of Urology, Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio, TX, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany; German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Ann W Hsing
- Department of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Rick A Kittles
- Division of Health Equities, Department of Population Sciences, City of Hope, Duarte, CA, USA
| | - Adam B Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Christopher J Logothetis
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - William B Isaacs
- James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anselm J Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA; Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Hardev Pandha
- Faculty of Health and Medical Sciences, The University of Surrey, Guildford, Surrey, UK
| | - Kim De Ruyck
- Ghent University, Faculty of Medicine and Health Sciences, Basic Medical Sciences, Gent, Belgium
| | - Jianfeng Xu
- Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Azad Razack
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Cancer Research Malaysia (CRM), Outpatient Centre, Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Lisa F Newcomb
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA; Department of Urology, University of Washington, Seattle, WA, USA
| | - Jay H Fowke
- Division of Epidemiology, Department of Preventive Medicine, The University of Tennessee Health Science Center, Memphis, TN, USA
| | | | - Benjamin A Rybicki
- Department of Public Health Sciences, Henry Ford Hospital, Detroit, MI, USA
| | - Marija Gamulin
- Department of Oncology, University Hospital Centre Zagreb, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Nawaid Usmani
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, AB, Canada; Division of Radiation Oncology, Cross Cancer Institute, Edmonton, AB, Canada
| | - Frank Claessens
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
| | - Manuela Gago-Dominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, Servicio Galego de Saúde, SERGAS, Santiago de Compostela, Spain; University of California San Diego, Moores Cancer Center, La Jolla, CA, USA
| | - Jose Esteban Castelao
- Genetic Oncology Unit, CHUVI Hospital, Complexo Hospitalario Universitario de Vigo, Instituto de Investigación Biomédica Galicia Sur (IISGS), Vigo (Pontevedra), Spain
| | - Paul A Townsend
- Division of Cancer Sciences, Manchester Cancer Research Centre, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Health Innovation Manchester, University of Manchester, Manchester, UK; The University of Surrey, Guildford, Surrey, UK
| | - Dana C Crawford
- Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - Gyorgy Petrovics
- Center for Prostate Disease Research, Uniformed Services University, Bethesda, MD, USA
| | - Graham Casey
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Monique J Roobol
- 109 Department of Urology, Erasmus University Medical Center, Cancer Institute, Rotterdam, the Netherlands
| | - Jennifer F Hu
- The University of Miami School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephen K Van Den Eeden
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA; Department of Urology, University of California San Francisco, San Francisco, CA, USA
| | - Douglas F Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael B Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - John S Witte
- Department of Epidemiology and Population Health, Department of Biomedical Data Science, Stanford Cancer Institute, Stanford, CA, USA
| | - Rosalind A Eeles
- The Institute of Cancer Research, Sutton, London, UK; Royal Marsden NHS Foundation Trust, London, UK
| | | | - Stephen Watya
- School of Public Health, Makerere University College of Health Sciences, Kampala, Uganda
| | - John M Gaziano
- VA Boston Healthcare System, Boston, MA, USA; Department of Medicine, Harvard Medical School, Boston, MA, USA; Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Amy C Justice
- VA Connecticut Healthcare System, West Haven, CT, USA; Yale School of Medicine, New Haven, CT, USA
| | - David V Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Badré A, Pan C. Explainable multi-task learning improves the parallel estimation of polygenic risk scores for many diseases through shared genetic basis. PLoS Comput Biol 2023; 19:e1011211. [PMID: 37418352 DOI: 10.1371/journal.pcbi.1011211] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2023] [Accepted: 05/23/2023] [Indexed: 07/09/2023] Open
Abstract
Many complex diseases share common genetic determinants and are comorbid in a population. We hypothesized that the co-occurrences of diseases and their overlapping genetic etiology can be exploited to simultaneously improve multiple diseases' polygenic risk scores (PRS). This hypothesis was tested using a multi-task learning (MTL) approach based on an explainable neural network architecture. We found that parallel estimations of the PRS for 17 prevalent cancers in a pan-cancer MTL model were generally more accurate than independent estimations for individual cancers in comparable single-task learning (STL) models. Such performance improvement conferred by positive transfer learning was also observed consistently for 60 prevalent non-cancer diseases in a pan-disease MTL model. Interpretation of the MTL models revealed significant genetic correlations between the important sets of single nucleotide polymorphisms used by the neural network for PRS estimation. This suggested a well-connected network of diseases with shared genetic basis.
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Affiliation(s)
- Adrien Badré
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
| | - Chongle Pan
- School of Computer Science, University of Oklahoma, Norman, Oklahoma, United States of America
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, Oklahoma, United States of America
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44
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Darst BF, Shen J, Madduri RK, Rodriguez AA, Xiao Y, Sheng X, Saunders EJ, Dadaev T, Brook MN, Hoffmann TJ, Muir K, Wan P, Le Marchand L, Wilkens L, Wang Y, Schleutker J, MacInnis RJ, Cybulski C, Neal DE, Nordestgaard BG, Nielsen SF, Batra J, Clements JA, Grönberg H, Pashayan N, Travis RC, Park JY, Albanes D, Weinstein S, Mucci LA, Hunter DJ, Penney KL, Tangen CM, Hamilton RJ, Parent MÉ, Stanford JL, Koutros S, Wolk A, Sørensen KD, Blot WJ, Yeboah ED, Mensah JE, Lu YJ, Schaid DJ, Thibodeau SN, West CM, Maier C, Kibel AS, Cancel-Tassin G, Menegaux F, John EM, Grindedal EM, Khaw KT, Ingles SA, Vega A, Rosenstein BS, Teixeira MR, Kogevinas M, Cannon-Albright L, Huff C, Multigner L, Kaneva R, Leach RJ, Brenner H, Hsing AW, Kittles RA, Murphy AB, Logothetis CJ, Neuhausen SL, Isaacs WB, Nemesure B, Hennis AJ, Carpten J, Pandha H, De Ruyck K, Xu J, Razack A, Teo SH, Newcomb LF, Fowke JH, Neslund-Dudas C, Rybicki BA, Gamulin M, Usmani N, Claessens F, GagoDominguez M, Castelao JE, Townsend PA, Crawford DC, Petrovics G, Casey G, Roobol MJ, Hu JF, Berndt SI, Van Den Eeden SK, Easton DF, Chanock SJ, Cook MB, Wiklund F, Witte JS, Eeles RA, Kote-Jarai Z, Watya S, Gaziano JM, Justice AC, Conti DV, Haiman CA. Evaluating Approaches for Constructing Polygenic Risk Scores for Prostate Cancer in Men of African and European Ancestry. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.05.12.23289860. [PMID: 37292833 PMCID: PMC10246022 DOI: 10.1101/2023.05.12.23289860] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
Abstract
Genome-wide polygenic risk scores (GW-PRS) have been reported to have better predictive ability than PRS based on genome-wide significance thresholds across numerous traits. We compared the predictive ability of several GW-PRS approaches to a recently developed PRS of 269 established prostate cancer risk variants from multi-ancestry GWAS and fine-mapping studies (PRS 269 ). GW-PRS models were trained using a large and diverse prostate cancer GWAS of 107,247 cases and 127,006 controls used to develop the multi-ancestry PRS 269 . Resulting models were independently tested in 1,586 cases and 1,047 controls of African ancestry from the California/Uganda Study and 8,046 cases and 191,825 controls of European ancestry from the UK Biobank and further validated in 13,643 cases and 210,214 controls of European ancestry and 6,353 cases and 53,362 controls of African ancestry from the Million Veteran Program. In the testing data, the best performing GW-PRS approach had AUCs of 0.656 (95% CI=0.635-0.677) in African and 0.844 (95% CI=0.840-0.848) in European ancestry men and corresponding prostate cancer OR of 1.83 (95% CI=1.67-2.00) and 2.19 (95% CI=2.14-2.25), respectively, for each SD unit increase in the GW-PRS. However, compared to the GW-PRS, in African and European ancestry men, the PRS 269 had larger or similar AUCs (AUC=0.679, 95% CI=0.659-0.700 and AUC=0.845, 95% CI=0.841-0.849, respectively) and comparable prostate cancer OR (OR=2.05, 95% CI=1.87-2.26 and OR=2.21, 95% CI=2.16-2.26, respectively). Findings were similar in the validation data. This investigation suggests that current GW-PRS approaches may not improve the ability to predict prostate cancer risk compared to the multi-ancestry PRS 269 constructed with fine-mapping.
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Affiliation(s)
- Burcu F. Darst
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Jiayi Shen
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | - Yukai Xiao
- Argonne National Laboratory, Lemont, IL, USA
| | - Xin Sheng
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | | | | | - Thomas J. Hoffmann
- Department of Epidemiology and Biostatistics, University of California, San Francisco, CA, USA
| | - Kenneth Muir
- Division of Population Health, Health Services Research and Primary Care, School of Health Sciences, Faculty of Biology, Medicine and Health, University of Manchester, Manchester, UK
| | - Peggy Wan
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Loic Le Marchand
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Lynne Wilkens
- Epidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Ying Wang
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | | | - Robert J. MacInnis
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Victoria, Australia
| | - Cezary Cybulski
- International Hereditary Cancer Center, Department of Genetics and Pathology, Pomeranian Medical University, Szczecin, Poland
| | - David E. Neal
- Nuffield Department of Surgical Sciences, University of Oxford, John Radcliffe Hospital, Headington, Oxford, UK
- University of Cambridge, Department of Oncology, Addenbrooke’s Hospital, Cambridge, UK
- Cancer Research UK, Cambridge Research Institute, Li Ka Shing Centre, Cambridge UK
| | - Børge G. Nordestgaard
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Sune F. Nielsen
- Faculty of Health and Medical Sciences, University of Copenhagen, Denmark
- Department of Clinical Biochemistry, Herlev and Gentofte Hospital, Copenhagen University Hospital, Herlev, Copenhagen, Denmark
| | - Jyotsna Batra
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Judith A. Clements
- Australian Prostate Cancer Research Centre-Qld, Institute of Health and Biomedical Innovation and School of Biomedical Sciences, Queensland University of Technology, Brisbane, Australia
- Translational Research Institute, Brisbane, Queensland, Australia
| | - Australian Prostate Cancer BioResource
- Translational Research Institute, Brisbane, Queensland, Australia
- Australian Prostate Cancer Research Centre-Qld, Queensland University of Technology, Brisbane; Prostate Cancer Research Program, Monash University, Melbourne; Dame Roma Mitchell Cancer Centre, University of Adelaide, Adelaide; Chris O’Brien Lifehouse and The Kinghorn Cancer Centre, Sydney, Australia
| | - Henrik Grönberg
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - Nora Pashayan
- University College London, Department of Applied Health Research, London, UK
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Ruth C. Travis
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Jong Y. Park
- Department of Cancer Epidemiology, Moffitt Cancer Center, Tampa, FL, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephanie Weinstein
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Lorelei A. Mucci
- Department of Epidemiology, Harvard T. H. Chan School of Public Health, Boston, MA, USA
| | - David J. Hunter
- Nuffield Department of Population Health, University of Oxford, Oxford, UK
| | - Kathryn L. Penney
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital/Harvard Medical School, Boston, MA, USA
| | | | - Robert J. Hamilton
- Dept. of Surgical Oncology, Princess Margaret Cancer Centre, Toronto, Canada
- Dept. of Surgery (Urology), University of Toronto, Canada
| | - Marie-Élise Parent
- Epidemiology and Biostatistics Unit, Centre Armand-Frappier Santé Biotechnologie, Institut national de la recherche scientifique, Laval, QC, Canada
- Department of Social and Preventive Medicine, School of Public Health, University of Montreal, Montreal, QC, Canada
| | - Janet L. Stanford
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology, School of Public Health, University of Washington, Seattle, WA, USA
| | - Stella Koutros
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Alicja Wolk
- Division of Nutritional Epidemiology, Institute of Environmental Medicine, Karolinska Institutet, Stockholm, Sweden
- Department of Surgical Sciences, Uppsala University, Uppsala, Sweden
| | - Karina D. Sørensen
- Department of Molecular Medicine, Aarhus University Hospital, Aarhus N, Denmark
- Department of Clinical Medicine, Aarhus University, Aarhus N, Denmark
| | - William J. Blot
- Division of Epidemiology, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA
- International Epidemiology Institute, Rockville, MD, USA
| | - Edward D. Yeboah
- University of Ghana Medical School, Accra, Ghana
- Korle Bu Teaching Hospital, Accra, Ghana
| | - James E. Mensah
- University of Ghana Medical School, Accra, Ghana
- Korle Bu Teaching Hospital, Accra, Ghana
| | - Yong-Jie Lu
- Centre for Biomarkers and Biotherapeutics, Barts Cancer Institute, Queen Mary University of London, John Vane Science Centre, London, UK
| | - Daniel J. Schaid
- Department of Quantitative Health Sciences, Mayo Clinic, Rochester, MN, USA
| | - Stephen N. Thibodeau
- Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN, USA
| | - Catharine M. West
- Division of Cancer Sciences, University of Manchester, Manchester Academic Health Science Centre, Radiotherapy Related Research, The Christie Hospital NHS Foundation Trust, Manchester, UK
| | | | - Adam S. Kibel
- Division of Urologic Surgery, Brigham and Womens Hospital, Boston, MA, USA
| | - Géraldine Cancel-Tassin
- CeRePP, Tenon Hospital, Paris, France
- Sorbonne Universite, GRC 5 Predictive Onco-urology, Tenon Hospital, Paris, France
| | - Florence Menegaux
- “Exposome and Heredity”, CESP (UMR 1018), Faculté de Médecine, Université Paris-Saclay, Inserm, Gustave Roussy, Villejuif, France
| | - Esther M. John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Division of Oncology, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | | | - Kay-Tee Khaw
- Clinical Gerontology Unit, University of Cambridge, Cambridge, UK
| | - Sue A. Ingles
- Department of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Ana Vega
- Fundación Pública Galega Medicina Xenómica, Santiago De Compostela, Spain
- Instituto de Investigación Sanitaria de Santiago de Compostela, Santiago De Compostela, Spain
- Centro de Investigación en Red de Enfermedades Raras (CIBERER), Spain
| | - Barry S. Rosenstein
- Department of Radiation Oncology and Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, NY, USA
| | - Manuel R. Teixeira
- Department of Genetics, Portuguese Oncology Institute of Porto (IPO-Porto), Porto, Portugal
- Biomedical Sciences Institute (ICBAS), University of Porto, Porto, Portugal
| | - NC-LA PCaP Investigators
- Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
- Epidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC, USA
| | - Manolis Kogevinas
- ISGlobal, Barcelona, Spain
- IMIM (Hospital del Mar Medical Research Institute), Barcelona, Spain
- Universitat Pompeu Fabra (UPF), Barcelona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Madrid, Spain
| | - Lisa Cannon-Albright
- Division of Epidemiology, Department of Internal Medicine, University of Utah School of Medicine, Salt Lake City, Utah, USA
- George E. Wahlen Department of Veterans Affairs Medical Center, Salt Lake City, Utah, USA
| | - Chad Huff
- Department of Epidemiology, The University of Texas M. D. Anderson Cancer Center, Houston, TX, USA
| | - Luc Multigner
- Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France
| | - Radka Kaneva
- Molecular Medicine Center, Department of Medical Chemistry and Biochemistry, Medical University of Sofia, Sofia, Bulgaria
| | - Robin J. Leach
- Department of Urology, Cancer Therapy and Research Center, University of Texas Health Science Center at San Antonio, San Antonio Texas, USA
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center (DKFZ), Heidelberg, Germany
- German Cancer Consortium (DKTK), German Cancer Research Center (DKFZ), Heidelberg, Germany
- Division of Preventive Oncology, German Cancer Research Center (DKFZ) and National Center for Tumor Diseases (NCT), Heidelberg, Germany
| | - Ann W. Hsing
- Department of Medicine and Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Rick A. Kittles
- Division of Health Equities, Department of Population Sciences, City of Hope, Duarte, CA, USA
| | - Adam B. Murphy
- Department of Urology, Northwestern University, Chicago, IL, USA
| | - Christopher J. Logothetis
- The University of Texas M. D. Anderson Cancer Center, Department of Genitourinary Medical Oncology, Houston, TX, USA
| | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of the City of Hope, Duarte, CA, USA
| | - William B. Isaacs
- James Buchanan Brady Urological Institute, Johns Hopkins Hospital and Medical Institution, Baltimore, MD, USA
| | - Barbara Nemesure
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
| | - Anselm J. Hennis
- Department of Family, Population and Preventive Medicine, Stony Brook University, Stony Brook, NY, USA
- Chronic Disease Research Centre and Faculty of Medical Sciences, University of the West Indies, Bridgetown, Barbados
| | - John Carpten
- Department of Translational Genomics, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Hardev Pandha
- Faculty of Health and Medical Sciences, The University of Surrey, Guildford, Surrey, UK
| | - Kim De Ruyck
- Ghent University, Faculty of Medicine and Health Sciences, Basic Medical Sciences, Gent, Belgium
| | - Jianfeng Xu
- Program for Personalized Cancer Care and Department of Surgery, NorthShore University HealthSystem, Evanston, IL, USA
| | - Azad Razack
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Soo-Hwang Teo
- Cancer Research Malaysia (CRM), Outpatient Centre, Subang Jaya Medical Centre, Subang Jaya, Selangor, Malaysia
| | - Canary PASS Investigators
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Lisa F. Newcomb
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Urology, University of Washington, Seattle, WA, USA
| | - Jay H. Fowke
- Division of Epidemiology, Department of Preventive Medicine, The University of Tennessee Health Science Center, TN, USA
| | | | | | - Marija Gamulin
- Department of Oncology, University Hospital Centre Zagreb, University of Zagreb School of Medicine, Zagreb, Croatia
| | - Nawaid Usmani
- Department of Oncology, Cross Cancer Institute, University of Alberta, Edmonton, Alberta, Canada
- Division of Radiation Oncology, Cross Cancer Institute, Edmonton, Alberta, Canada
| | - Frank Claessens
- Molecular Endocrinology Laboratory, Department of Cellular and Molecular Medicine, Leuven, Belgium
| | - Manuela GagoDominguez
- Genomic Medicine Group, Galician Foundation of Genomic Medicine, Instituto de Investigacion Sanitaria de Santiago de Compostela (IDIS), Complejo Hospitalario Universitario de Santiago, Servicio Galego de Saúde, SERGAS, Santiago de Compostela, Spain
- University of California San Diego, Moores Cancer Center, La Jolla, CA, USA
| | - Jose Esteban Castelao
- Genetic Oncology Unit, CHUVI Hospital, Complexo Hospitalario Universitario de Vigo, Instituto de Investigación Biomédica Galicia Sur (IISGS), Vigo (Pontevedra), Spain
| | - Paul A. Townsend
- Division of Cancer Sciences, Manchester Cancer Research Centre, Faculty of Biology, Medicine and Health, Manchester Academic Health Science Centre, NIHR Manchester Biomedical Research Centre, Health Innovation Manchester, University of Manchester, UK
- The University of Surrey, Guildford, Surrey, UK
| | - Dana C. Crawford
- Case Western Reserve University, Department of Population and Quantitative Health Sciences, Cleveland Institute for Computational Biology, Cleveland, OH, USA
| | - Gyorgy Petrovics
- Center for Prostate Disease Research, Uniformed Services University, Bethesda, MD, USA
| | - Graham Casey
- Center for Public Health Genomics, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, USA
| | - Monique J. Roobol
- 109 Department of Urology, Erasmus University Medical Center, Cancer Institute, Rotterdam, The Netherlands
| | - Jennifer F. Hu
- The University of Miami School of Medicine, Sylvester Comprehensive Cancer Center, Miami, FL, USA
| | - Sonja I. Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Stephen K. Van Den Eeden
- Division of Research, Kaiser Permanente, Northern California, Oakland, CA, USA
- Department of Urology, University of California San Francisco, San Francisco, CA, USA
| | - Douglas F. Easton
- Centre for Cancer Genetic Epidemiology, Department of Public Health and Primary Care, University of Cambridge, Strangeways Research Laboratory, Cambridge, UK
| | - Stephen J. Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Michael B. Cook
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, NIH, Bethesda, MD, USA
| | - Fredrik Wiklund
- Department of Medical Epidemiology and Biostatistics, Karolinska Institute, Stockholm, Sweden
| | - John S. Witte
- Department of Epidemiology and Population Health, Department of Biomedical Data Science, Stanford Cancer Institute, Stanford, CA, USA
| | - Rosalind A. Eeles
- The Institute of Cancer Research, Sutton, London, UK
- Royal Marsden NHS Foundation Trust, London, UK
| | | | - Stephen Watya
- School of Public Health, Makerere University College of Health Sciences, Kampala Uganda
| | - John M. Gaziano
- VA Boston Healthcare System, Boston, MA, USA
- Department of Medicine, Harvard Medical School, Boston, MA, USA
- Department of Medicine, Brigham and Women’s Hospital, Boston, MA, USA
| | - Amy C. Justice
- VA Connecticut Healthcare System, West Haven, CT, USA
- Yale School of Medicine, New Haven, CT, USA
| | - David V. Conti
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Christopher A. Haiman
- Center for Genetic Epidemiology, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
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Shieh Y, Roger J, Yau C, Wolf DM, Hirst GL, Swigart LB, Huntsman S, Hu D, Nierenberg JL, Middha P, Heise RS, Shi Y, Kachuri L, Zhu Q, Yao S, Ambrosone CB, Kwan ML, Caan BJ, Witte JS, Kushi LH, 't Veer LV, Esserman LJ, Ziv E. Development and testing of a polygenic risk score for breast cancer aggressiveness. NPJ Precis Oncol 2023; 7:42. [PMID: 37188791 PMCID: PMC10185660 DOI: 10.1038/s41698-023-00382-z] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2022] [Accepted: 04/28/2023] [Indexed: 05/17/2023] Open
Abstract
Aggressive breast cancers portend a poor prognosis, but current polygenic risk scores (PRSs) for breast cancer do not reliably predict aggressive cancers. Aggressiveness can be effectively recapitulated using tumor gene expression profiling. Thus, we sought to develop a PRS for the risk of recurrence score weighted on proliferation (ROR-P), an established prognostic signature. Using 2363 breast cancers with tumor gene expression data and single nucleotide polymorphism (SNP) genotypes, we examined the associations between ROR-P and known breast cancer susceptibility SNPs using linear regression models. We constructed PRSs based on varying p-value thresholds and selected the optimal PRS based on model r2 in 5-fold cross-validation. We then used Cox proportional hazards regression to test the ROR-P PRS's association with breast cancer-specific survival in two independent cohorts totaling 10,196 breast cancers and 785 events. In meta-analysis of these cohorts, higher ROR-P PRS was associated with worse survival, HR per SD = 1.13 (95% CI 1.06-1.21, p = 4.0 × 10-4). The ROR-P PRS had a similar magnitude of effect on survival as a comparator PRS for estrogen receptor (ER)-negative versus positive cancer risk (PRSER-/ER+). Furthermore, its effect was minimally attenuated when adjusted for PRSER-/ER+, suggesting that the ROR-P PRS provides additional prognostic information beyond ER status. In summary, we used integrated analysis of germline SNP and tumor gene expression data to construct a PRS associated with aggressive tumor biology and worse survival. These findings could potentially enhance risk stratification for breast cancer screening and prevention.
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Affiliation(s)
- Yiwey Shieh
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA.
| | - Jacquelyn Roger
- PhD Program in Biological and Medical Informatics, University of California, San Francisco, San Francisco, CA, USA
| | - Christina Yau
- Department of Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Denise M Wolf
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Gillian L Hirst
- Department of Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Lamorna Brown Swigart
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Scott Huntsman
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jovia L Nierenberg
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Pooja Middha
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Rachel S Heise
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Yushu Shi
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Linda Kachuri
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Qianqian Zhu
- Department of Biostatistics and Bioinformatics, Roswell Park Cancer Institute, Buffalo, NY, USA
| | - Song Yao
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Christine B Ambrosone
- Department of Cancer Prevention and Control, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA
| | - Marilyn L Kwan
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Bette J Caan
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - John S Witte
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | - Laura van 't Veer
- Department of Laboratory Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Laura J Esserman
- Department of Surgery, University of California, San Francisco, San Francisco, CA, USA
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
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46
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Ren J, Zhang P, Li Z, Zhang X, Shen D, Chen P, Huang Q, Gao P, Mao C. Association of screening status, polygenic risk score and environmental risk factors with colorectal cancer incidence and mortality risks. Int J Cancer 2023; 152:1778-1788. [PMID: 36537585 DOI: 10.1002/ijc.34407] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/08/2022] [Revised: 12/12/2022] [Accepted: 12/13/2022] [Indexed: 12/24/2022]
Abstract
Whether screening can attenuate the influence of genetic risk and environmental risk factors for colorectal cancer (CRC) mortality risk remains unknown. Our study is to investigate the association of the screening history, genetic risk and environmental risk factors with CRC incidence and mortality risks using UK Biobank data. Screening history was associated with lower CRC incidence (hazard ratio [HR]: 0.63, 95% confidence interval [CI]: 0.58-0.69) and mortality risk (HR: 0.56, 95% CI: 0.49-0.63). Compared to the HRs of participants with a low genetic risk, low environmental risk and no screening history, the HRs of participants with a high genetic risk, high environmental risk and no screening history were 3.42 (95% CI: 2.76-4.24) for CRC incidence and 3.36 (95% CI: 2.48-4.56) for CRC mortality. In contrast, the HRs of participants with a high genetic risk and no screening history, but a low environmental risk, were 1.92 (95% CI: 1.55-2.36) for CRC incidence and 1.88 (95% CI: 1.39-2.53) for CRC mortality. Furthermore, the HRs of participants with a high genetic risk and a low environmental risk, but a screening history were 1.62 (95% CI: 1.15-2.28) for CRC incidence and 1.77 (95% CI: 1.08-2.89) for CRC mortality. Participants benefited more substantially from screenings for CRC mortality than for CRC incidence risk. A higher environmental risk was associated with higher risk of CRC incidence and mortality within each category of genetic risk. These findings emphasize the importance of CRC screening and identifying environmental factors to reduce CRC incidence and mortality risks.
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Affiliation(s)
- Jiaojiao Ren
- Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, Guangdong, China
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Peidong Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
- Department of Neurosurgery, Nanfang Hospital, Southern Medical University, Guangzhou, Guangdong, China
| | - Zhihao Li
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Xiru Zhang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Dong Shen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Peiliang Chen
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Qingmei Huang
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
| | - Pingming Gao
- Affiliated Foshan Maternity & Child Healthcare Hospital, Southern Medical University, Foshan, Guangdong, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, Guangdong, China
| | - Chen Mao
- Department of Epidemiology, School of Public Health, Southern Medical University, Guangzhou, Guangdong, China
- Microbiome Medicine Center, Department of Laboratory Medicine, Zhujiang Hospital, Southern Medical University, Guangzhou, Guangdong, China
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47
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Kastrinos F, Kupfer SS, Gupta S. Colorectal Cancer Risk Assessment and Precision Approaches to Screening: Brave New World or Worlds Apart? Gastroenterology 2023; 164:812-827. [PMID: 36841490 PMCID: PMC10370261 DOI: 10.1053/j.gastro.2023.02.021] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Revised: 02/12/2023] [Accepted: 02/17/2023] [Indexed: 02/27/2023]
Abstract
Current colorectal cancer (CRC) screening recommendations take a "one-size-fits-all" approach using age as the major criterion to initiate screening. Precision screening that incorporates factors beyond age to risk stratify individuals could improve on current approaches and optimally use available resources with benefits for patients, providers, and health care systems. Prediction models could identify high-risk groups who would benefit from more intensive screening, while low-risk groups could be recommended less intensive screening incorporating noninvasive screening modalities. In addition to age, prediction models incorporate well-established risk factors such as genetics (eg, family CRC history, germline, and polygenic risk scores), lifestyle (eg, smoking, alcohol, diet, and physical inactivity), sex, and race and ethnicity among others. Although several risk prediction models have been validated, few have been systematically studied for risk-adapted population CRC screening. In order to envisage clinical implementation of precision screening in the future, it will be critical to develop reliable and accurate prediction models that apply to all individuals in a population; prospectively study risk-adapted CRC screening on the population level; garner acceptance from patients and providers; and assess feasibility, resources, cost, and cost-effectiveness of these new paradigms. This review evaluates the current state of risk prediction modeling and provides a roadmap for future implementation of precision CRC screening.
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Affiliation(s)
- Fay Kastrinos
- Herbert Irving Comprehensive Cancer Center, Columbia University Medical Center, New York, New York; Division of Digestive and Liver Diseases, Columbia University Medical Center and Vagelos College of Physicians and Surgeons, New York, New York.
| | - Sonia S Kupfer
- University of Chicago, Section of Gastroenterology, Hepatology and Nutrition, Chicago, Illinois
| | - Samir Gupta
- Division of Gastroenterology, Department of Internal Medicine, University of California, San Diego, La Jolla, California; Veterans Affairs San Diego Healthcare System, San Diego, California
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48
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Hassanin E, Spier I, Bobbili DR, Aldisi R, Klinkhammer H, David F, Dueñas N, Hüneburg R, Perne C, Brunet J, Capella G, Nöthen MM, Forstner AJ, Mayr A, Krawitz P, May P, Aretz S, Maj C. Clinically relevant combined effect of polygenic background, rare pathogenic germline variants, and family history on colorectal cancer incidence. BMC Med Genomics 2023; 16:42. [PMID: 36872334 PMCID: PMC9987090 DOI: 10.1186/s12920-023-01469-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2022] [Accepted: 02/21/2023] [Indexed: 03/07/2023] Open
Abstract
BACKGROUND AND AIMS Summarised in polygenic risk scores (PRS), the effect of common, low penetrant genetic variants associated with colorectal cancer (CRC), can be used for risk stratification. METHODS To assess the combined impact of the PRS and other main factors on CRC risk, 163,516 individuals from the UK Biobank were stratified as follows: 1. carriers status for germline pathogenic variants (PV) in CRC susceptibility genes (APC, MLH1, MSH2, MSH6, PMS2), 2. low (< 20%), intermediate (20-80%), or high PRS (> 80%), and 3. family history (FH) of CRC. Multivariable logistic regression and Cox proportional hazards models were applied to compare odds ratios and to compute the lifetime incidence, respectively. RESULTS Depending on the PRS, the CRC lifetime incidence for non-carriers ranges between 6 and 22%, compared to 40% and 74% for carriers. A suspicious FH is associated with a further increase of the cumulative incidence reaching 26% for non-carriers and 98% for carriers. In non-carriers without FH, but high PRS, the CRC risk is doubled, whereas a low PRS even in the context of a FH results in a decreased risk. The full model including PRS, carrier status, and FH improved the area under the curve in risk prediction (0.704). CONCLUSION The findings demonstrate that CRC risks are strongly influenced by the PRS for both a sporadic and monogenic background. FH, PV, and common variants complementary contribute to CRC risk. The implementation of PRS in routine care will likely improve personalized risk stratification, which will in turn guide tailored preventive surveillance strategies in high, intermediate, and low risk groups.
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Affiliation(s)
- Emadeldin Hassanin
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany.,Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg
| | - Isabel Spier
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany.,European Reference Network on Genetic Tumour Rsik Syndromes (ERNGENTURIS) - Project ID No 739547, Nijmegen, The Netherlands
| | - Dheeraj R Bobbili
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg
| | - Rana Aldisi
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany
| | - Hannah Klinkhammer
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany.,Medical Faculty, Institute for Medical Biometry, Informatics and Epidemiology, University Bonn, Bonn, Germany
| | - Friederike David
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Nuria Dueñas
- Hereditary Cancer Program, Catalan Institute of Oncology-IDIBELL, ONCOBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
| | - Robert Hüneburg
- National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany.,Department of Internal Medicine I, University Hospital Bonn, Bonn, Germany
| | - Claudia Perne
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany
| | - Joan Brunet
- European Reference Network on Genetic Tumour Rsik Syndromes (ERNGENTURIS) - Project ID No 739547, Nijmegen, The Netherlands.,Hereditary Cancer Program, Catalan Institute of Oncology-IDIBELL, ONCOBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto Salud Carlos III, Madrid, Spain.,Hereditary Cancer Program, Catalan Institute of Oncology-IDBIGI, 17007, Girona, Spain
| | - Gabriel Capella
- European Reference Network on Genetic Tumour Rsik Syndromes (ERNGENTURIS) - Project ID No 739547, Nijmegen, The Netherlands.,Hereditary Cancer Program, Catalan Institute of Oncology-IDIBELL, ONCOBELL, Hospitalet de Llobregat, Barcelona, Spain.,Centro de Investigación Biomédica en Red de Cáncer (CIBERONC), Instituto Salud Carlos III, Madrid, Spain
| | - Markus M Nöthen
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany
| | - Andreas J Forstner
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.,Centre for Human Genetics, University of Marburg, Marburg, Germany.,Institute of Neuroscience and Medicine (INM-1), Research Center Jülich, Jülich, Germany
| | - Andreas Mayr
- Medical Faculty, Institute for Medical Biometry, Informatics and Epidemiology, University Bonn, Bonn, Germany
| | - Peter Krawitz
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany
| | - Patrick May
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Esch-Sur-Alzette, Luxembourg
| | - Stefan Aretz
- Institute of Human Genetics, Medical Faculty, University of Bonn, Venusberg-Campus 1, 53127, Bonn, Germany. .,National Center for Hereditary Tumor Syndromes, University Hospital Bonn, Bonn, Germany. .,European Reference Network on Genetic Tumour Rsik Syndromes (ERNGENTURIS) - Project ID No 739547, Nijmegen, The Netherlands.
| | - Carlo Maj
- Institute for Genomic Statistics and Bioinformatics, University Hospital Bonn, Bonn, Germany
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49
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Cavestro GM, Mannucci A, Balaguer F, Hampel H, Kupfer SS, Repici A, Sartore-Bianchi A, Seppälä TT, Valentini V, Boland CR, Brand RE, Buffart TE, Burke CA, Caccialanza R, Cannizzaro R, Cascinu S, Cercek A, Crosbie EJ, Danese S, Dekker E, Daca-Alvarez M, Deni F, Dominguez-Valentin M, Eng C, Goel A, Guillem JG, Houwen BBSL, Kahi C, Kalady MF, Kastrinos F, Kühn F, Laghi L, Latchford A, Liska D, Lynch P, Malesci A, Mauri G, Meldolesi E, Møller P, Monahan KJ, Möslein G, Murphy CC, Nass K, Ng K, Oliani C, Papaleo E, Patel SG, Puzzono M, Remo A, Ricciardiello L, Ripamonti CI, Siena S, Singh SK, Stadler ZK, Stanich PP, Syngal S, Turi S, Urso ED, Valle L, Vanni VS, Vilar E, Vitellaro M, You YQN, Yurgelun MB, Zuppardo RA, Stoffel EM. Delphi Initiative for Early-Onset Colorectal Cancer (DIRECt) International Management Guidelines. Clin Gastroenterol Hepatol 2023; 21:581-603.e33. [PMID: 36549470 PMCID: PMC11207185 DOI: 10.1016/j.cgh.2022.12.006] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 12/01/2022] [Accepted: 12/01/2022] [Indexed: 12/24/2022]
Abstract
BACKGROUND & AIMS Patients with early-onset colorectal cancer (eoCRC) are managed according to guidelines that are not age-specific. A multidisciplinary international group (DIRECt), composed of 69 experts, was convened to develop the first evidence-based consensus recommendations for eoCRC. METHODS After reviewing the published literature, a Delphi methodology was used to draft and respond to clinically relevant questions. Each statement underwent 3 rounds of voting and reached a consensus level of agreement of ≥80%. RESULTS The DIRECt group produced 31 statements in 7 areas of interest: diagnosis, risk factors, genetics, pathology-oncology, endoscopy, therapy, and supportive care. There was strong consensus that all individuals younger than 50 should undergo CRC risk stratification and prompt symptom assessment. All newly diagnosed eoCRC patients should receive germline genetic testing, ideally before surgery. On the basis of current evidence, endoscopic, surgical, and oncologic treatment of eoCRC should not differ from later-onset CRC, except for individuals with pathogenic or likely pathogenic germline variants. The evidence on chemotherapy is not sufficient to recommend changes to established therapeutic protocols. Fertility preservation and sexual health are important to address in eoCRC survivors. The DIRECt group highlighted areas with knowledge gaps that should be prioritized in future research efforts, including age at first screening for the general population, use of fecal immunochemical tests, chemotherapy, endoscopic therapy, and post-treatment surveillance for eoCRC patients. CONCLUSIONS The DIRECt group produced the first consensus recommendations on eoCRC. All statements should be considered together with the accompanying comments and literature reviews. We highlighted areas where research should be prioritized. These guidelines represent a useful tool for clinicians caring for patients with eoCRC.
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Affiliation(s)
- Giulia Martina Cavestro
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy.
| | - Alessandro Mannucci
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Francesc Balaguer
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain; Centro de Investigación Biomédica en Red de Enfermedades Hepáticas y Digestivas (CIBERehd), University of Barcelona, Barcelona, Spain
| | - Heather Hampel
- Department of Medical Oncology & Therapeutics Research, City of Hope National Medical Center, Duarte, California
| | - Sonia S Kupfer
- Department of Medicine, Section of Gastroenterology, Hepatology, and Nutrition, University of Chicago Medicine, Chicago, Illinois
| | - Alessandro Repici
- Gastrointestinal Endoscopy Unit, Humanitas University, Humanitas Research Hospital, Rozzano, Italy
| | - Andrea Sartore-Bianchi
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, and Department of Hematology Oncology, and Molecular Medicine, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Toni T Seppälä
- Faculty of Medicine and Medical Technology, University of Tampere and TAYS Cancer Centre, Arvo Ylpön katu, Tampere, Finland; Unit of Gastroenterological Surgery, Tampere University Hospital, Elämänaukio, Tampere, Finland; Applied Tumor Genomics Research Program and Department of Surgery, Helsinki University and Helsinki University Hospital, Helsinki, Finland
| | - Vincenzo Valentini
- Department of Radiology, Radiation Oncology and Hematology, Università Cattolica del Sacro Cuore di Roma, Fondazione Policlinico Universitario A. Gemelli - IRCCS, Rome, Italy
| | - Clement Richard Boland
- Department of Medicine, Division of Gastroenterology, University of California San Diego, San Diego, California
| | - Randall E Brand
- Division of Gastroenterology, Hepatology & Nutrition, University of Pittsburgh, Pittsburgh, Pennsylvania
| | - Tineke E Buffart
- Department of Medical Oncology. Amsterdam UMC, Location de Boelelaan, Amsterdam, The Netherlands
| | - Carol A Burke
- Department of Gastroenterology, Hepatology and Nutrition, Cleveland Clinic, Cleveland, Ohio
| | - Riccardo Caccialanza
- Clinical Nutrition and Dietetics Unit, Fondazione IRCCS Policlinico San Matteo, Pavia, Italy
| | - Renato Cannizzaro
- SOC Gastroenterologia Oncologica e Sperimentale Centro di Riferimento Oncologico di Aviano (CRO) IRCCS 33081, Aviano, Italy
| | - Stefano Cascinu
- Oncology Department, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Cercek
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Emma J Crosbie
- Division of Cancer Sciences, Faculty of Biology, Medicine and Health, University of Manchester, St Mary's Hospital, Manchester, United Kingdom; Division of Gynaecology, St Mary's Hospital, Manchester University NHS Foundation Trust, Manchester Academic Health Science Centre, Manchester, United Kingdom
| | - Silvio Danese
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Evelien Dekker
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Maria Daca-Alvarez
- Department of Gastroenterology, Hospital Clínic de Barcelona, Institut d'Investigacions Biomèdiques August Pi i Sunyer (IDIBAPS), Barcelona, Spain
| | - Francesco Deni
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Mev Dominguez-Valentin
- Department of Tumor Biology, Institute of Cancer Research, The Norwegian Radium Hospital, Oslo, Norway
| | - Cathy Eng
- Department of Medicine, Division of Hematology and Oncology, Vanderbilt-Ingram Cancer Center, Nashville, Tennessee
| | - Ajay Goel
- Department of Molecular Diagnostics & Experimental Therapeutics, Beckman Research Institute of City of Hope Comprehensive Cancer Center, Duarte, California
| | - Josè G Guillem
- Department of Surgery and Lineberger Cancer Center, University of North Carolina at Chapel Hill, Chapel Hill, North Carolina
| | - Britt B S L Houwen
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Charles Kahi
- Department of Medicine, Division of Gastroenterology and Hepatology, Indiana University School of Medicine, Indianapolis, Indiana
| | - Matthew F Kalady
- Department of Surgery, The Ohio State University Wexner Medical Center, Columbus, Ohio
| | - Fay Kastrinos
- Division of Digestive and Liver Diseases, Herbert Irving Comprehensive Cancer Center, Columbia University Irving Medical Center and the Vagelos College of Physicians and Surgeons, New York, New York
| | - Florian Kühn
- Department of General, Visceral and Transplant Surgery, Ludwig-Maximilians-University Munich, Munich, Germany
| | - Luigi Laghi
- Department of Medicine and Surgery, University of Parma, Parma, and Laboratory of Molecular Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano-Milan, Italy
| | - Andrew Latchford
- Lynch Syndrome Clinic, Centre for Familial Intestinal Cancer, St Mark's Hospital, London North West University Healthcare NHS Trust, Harrow, United Kingdom
| | - David Liska
- Department of Colorectal Surgery and Edward J. DeBartolo Jr Family Center for Young-Onset Colorectal Cancer, Digestive Disease and Surgery Institute, Cleveland Clinic, Cleveland, Ohio
| | - Patrick Lynch
- Department of Gastroenterology, M. D. Anderson Cancer Center, Houston, Texas
| | - Alberto Malesci
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Gianluca Mauri
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, and Department of Hematology Oncology, and Molecular Medicine, Grande Ospedale Metropolitano Niguarda, Milan, Italy; IFOM ETS - The AIRC Institute of Molecular Oncology, Milan, Italy
| | - Elisa Meldolesi
- Department of Radiology, Radiation Oncology and Hematology, Università Cattolica del Sacro Cuore di Roma, Fondazione Policlinico Universitario A. Gemelli - IRCCS, Rome, Italy
| | - Pål Møller
- Department of Tumor Biology, Institute of Cancer Research, The Norwegian Radium Hospital, Oslo, Norway
| | - Kevin J Monahan
- Lynch Syndrome Clinic, Centre for Familial Intestinal Cancer, St Mark's Hospital, London North West University Healthcare NHS Trust, Harrow, United Kingdom; Faculty of Medicine, Department of Surgery & Cancer, Imperial College, London, United Kingdom
| | - Gabriela Möslein
- Surgical Center for Hereditary Tumors, Ev. BETHESDA Khs. Duisburg, Academic Hospital University of Düsseldorf, Düsseldorf, Germany
| | - Caitlin C Murphy
- School of Public Health, University of Texas Health Science Center at Houston, Houston, Texas
| | - Karlijn Nass
- Department of Gastroenterology and Hepatology, Amsterdam University Medical Centers, University of Amsterdam, Amsterdam, the Netherlands
| | - Kimmie Ng
- Young-Onset Colorectal Cancer Center, Dana-Farber Cancer Institute, Harvard Medical School, Boston, Massachusetts
| | - Cristina Oliani
- Medical Oncology, AULSS 5 Polesana, Santa Maria Della Misericordia Hospital, Rovigo, Italy
| | - Enrico Papaleo
- Centro Scienze della Natalità, Department of Obstetrics and Gynecology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Swati G Patel
- University of Colorado Anschutz Medical Center and Rocky Mountain Regional Veterans Affairs Medical Center, Aurora, Colorado
| | - Marta Puzzono
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Andrea Remo
- Pathology Unit, Mater Salutis Hospital, ULSS9, Legnago, Verona, Italy
| | - Luigi Ricciardiello
- Department of Medical and Surgical Sciences, Universita degli Studi di Bologna, Bologna, Italy
| | - Carla Ida Ripamonti
- Department of Onco-Haematology, Fondazione IRCCS, Istituto Nazionale dei Tumori, Milan, Italy
| | - Salvatore Siena
- Department of Oncology and Hemato-Oncology, Università degli Studi di Milano, and Department of Hematology Oncology, and Molecular Medicine, Grande Ospedale Metropolitano Niguarda, Milan, Italy
| | - Satish K Singh
- Department of Medicine, Section of Gastroenterology, VA Boston Healthcare System and Boston University, Boston, Massachusetts
| | - Zsofia K Stadler
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, New York
| | - Peter P Stanich
- Division of Gastroenterology, Hepatology and Nutrition, Department of Internal Medicine, The Ohio State University Wexner Medical Center, Columbus, Ohio
| | - Sapna Syngal
- Brigham and Women's Hospital, Harvard Medical School, Dana Farber Cancer Institute, Boston, Massachusetts
| | - Stefano Turi
- Department of Anesthesia and Intensive Care, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Emanuele Damiano Urso
- Chirurgia Generale 3, Department of Surgical, Oncological and Gastroenterological Sciences (DiSCOG), University Hospital of Padova, Padova, Italy
| | - Laura Valle
- Hereditary Cancer Program, Catalan Institute of Oncology, Oncobell Program, Bellvitge Biomedical Research Center (IDIBELL), Hospitalet de Llobregat, Barcelona, Spain; Centro de Investigación Biomédica en Red en Cáncer (CIBERONC), Madrid, Spain
| | - Valeria Stella Vanni
- Centro Scienze della Natalità, Department of Obstetrics and Gynecology, IRCCS San Raffaele Scientific Institute, Milano, Italy
| | - Eduardo Vilar
- Department of Clinical Cancer Prevention, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Marco Vitellaro
- Unit of Hereditary Digestive Tract Tumours, Department of Surgery, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Yi-Qian Nancy You
- Department of Colon & Rectal Surgery, Division of Surgery, The University of Texas MD Anderson Cancer Center, Houston, Texas
| | - Matthew B Yurgelun
- Brigham and Women's Hospital, Harvard Medical School, Dana Farber Cancer Institute, Boston, Massachusetts
| | - Raffaella Alessia Zuppardo
- Gastroenterology and Gastrointestinal Endoscopy Unit, Vita-Salute San Raffaele University, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elena M Stoffel
- Division of Gastroenterology and Hepatology, Department of Internal Medicine and Rogel Cancer Center, University of Michigan Medical School, Ann Arbor, Michigan
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50
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Chen H, Shi J, Lu M, Li Y, Du L, Liao X, Wei D, Dong D, Gao Y, Zhu C, Ying R, Zheng W, Yan S, Xiao H, Zhang J, Kong Y, Li F, Zou S, Liu C, Wang H, Zhang Y, Lu B, Luo C, Cai J, Tian J, Miao X, Ding K, Brenner H, Dai M. Comparison of Colonoscopy, Fecal Immunochemical Test, and Risk-Adapted Approach in a Colorectal Cancer Screening Trial (TARGET-C). Clin Gastroenterol Hepatol 2023; 21:808-818. [PMID: 35964896 DOI: 10.1016/j.cgh.2022.08.003] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 07/30/2022] [Accepted: 08/02/2022] [Indexed: 02/07/2023]
Abstract
BACKGROUND & AIMS The screening yield and related cost of a risk-adapted screening approach compared with established screening strategies in population-based colorectal cancer (CRC) screening are not clear. METHODS We randomly allocated 19,373 participants into 1 of the 3 screening arms in a 1:2:2 ratio: (1) one-time colonoscopy (n = 3883); (2) annual fecal immunochemical test (FIT) (n = 7793); (3) annual risk-adapted screening (n = 7697), in which, based on the risk-stratification score, high-risk participants were referred for colonoscopy and low-risk ones were referred for FIT. Three consecutive screening rounds were conducted for both the FIT and the risk-adapted screening arms. Follow-up to trace the health outcome for all the participants was conducted over the 3-year study period. The detection rate of advanced colorectal neoplasia (CRC and advanced precancerous lesions) was the main outcome. The trial was registered in the Chinese Clinical Trial Registry (number: ChiCTR1800015506). RESULTS In the colonoscopy, FIT, and risk-adapted screening arms over 3 screening rounds, the participation rates were 42.4%, 99.3%, and 89.2%, respectively; the detection rates for advanced neoplasm (intention-to-treat analysis) were 2.76%, 2.17%, and 2.35%, respectively, with an odds ratio (OR)colonoscopy vs FIT of 1.27 (95% confidence interval [CI]: 0.99-1.63; P = .056), an ORcolonoscopy vsrisk-adapted screening of 1.17 (95% CI, 0.91-1.49; P = .218), and an ORrisk-adapted screeningvs FIT of 1.09 (95% CI, 0.88-1.35; P = .438); the numbers of colonoscopies needed to detect 1 advanced neoplasm were 15.4, 7.8, and 10.2, respectively; the costs for detecting 1 advanced neoplasm from a government perspective using package payment format were 6928 Chinese Yuan (CNY) ($1004), 5821 CNY ($844), and 6694 CNY ($970), respectively. CONCLUSIONS The risk-adapted approach is a feasible and cost-favorable strategy for population-based CRC screening and therefore could complement the well-established one-time colonoscopy and annual repeated FIT screening strategies. (Chinese Clinical Trial Registry; ChiCTR1800015506).
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Affiliation(s)
- Hongda Chen
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jufang Shi
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Ming Lu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yanjie Li
- Office of Cancer Screening, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Lingbin Du
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Xianzhen Liao
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Donghua Wei
- Department of Cancer Prevention, Anhui Provincial Cancer Hospital, Hefei, China
| | - Dong Dong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Yi Gao
- Department of Colorectum Surgery, Tumor Hospital of Yunnan Province/Third Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Chen Zhu
- Department of Cancer Prevention, Institute of Cancer and Basic Medicine, Chinese Academy of Sciences/Cancer Hospital of University of Chinese Academy of Sciences/Zhejiang Cancer Hospital, Hangzhou, China
| | - Rongbiao Ying
- Department of Surgical Oncology, Taizhou Cancer Hospital, Taizhou, China
| | - Weifang Zheng
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Department of Proctology, Lanxi Red Cross Hospital, Jinhua, China
| | - Shipeng Yan
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Haifan Xiao
- Department of Cancer Prevention, Hunan Cancer Hospital, Changsha, China
| | - Juan Zhang
- Department of Cancer Prevention, Anhui Provincial Cancer Hospital, Hefei, China
| | - Yunxin Kong
- Office of Cancer Prevention and Treatment, Xuzhou Cancer Hospital, Xuzhou, China
| | - Furong Li
- Department of Colorectum Surgery, Tumor Hospital of Yunnan Province/Third Affiliated Hospital of Kunming Medical University, Kunming, China
| | - Shuangmei Zou
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chengcheng Liu
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Wang
- Department of Cancer Epidemiology, Affiliated Cancer Hospital of Zhengzhou University/Henan Cancer Hospital, Zhengzhou, China
| | - Yuhan Zhang
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Bin Lu
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Chenyu Luo
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jie Cai
- Department of General Surgery, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jianbo Tian
- School of Public Health, Taikang Center for Life and Medical Sciences, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
| | - Xiaoping Miao
- School of Public Health, Taikang Center for Life and Medical Sciences, Wuhan University; Research Center of Public Health, Renmin Hospital of Wuhan University, Wuhan, China
| | - Kefeng Ding
- Department of Colorectal Surgery and Oncology, Key Laboratory of Cancer Prevention and Intervention, Ministry of Education, The Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, China; Cancer Center, Zhejiang University, Hangzhou, China
| | - Hermann Brenner
- Division of Clinical Epidemiology and Aging Research, German Cancer Research Center, Heidelberg, Germany; Division of Preventive Oncology, German Cancer Research Center and National Center for Tumor Diseases, Heidelberg, Germany; German Cancer Consortium, German Cancer Research Center, Heidelberg, Germany
| | - Min Dai
- Medical Research Center, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
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