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Fuller H, Zhu Y, Nicholas J, Chatelaine HA, Drzymalla EM, Sarvestani AK, Julián-Serrano S, Tahir UA, Sinnott-Armstrong N, Raffield LM, Rahnavard A, Hua X, Shutta KH, Darst BF. Author Correction: Metabolomic epidemiology offers insights into disease aetiology. Nat Metab 2024; 6:187. [PMID: 38191668 DOI: 10.1038/s42255-023-00967-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/10/2024]
Affiliation(s)
- Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yiwen Zhu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jayna Nicholas
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Haley A Chatelaine
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Emily M Drzymalla
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afrand K Sarvestani
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | | | - Usman A Tahir
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Xinwei Hua
- Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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Fuller H, Zhu Y, Nicholas J, Chatelaine HA, Drzymalla EM, Sarvestani AK, Julián-Serrano S, Tahir UA, Sinnott-Armstrong N, Raffield LM, Rahnavard A, Hua X, Shutta KH, Darst BF. Metabolomic epidemiology offers insights into disease aetiology. Nat Metab 2023; 5:1656-1672. [PMID: 37872285 DOI: 10.1038/s42255-023-00903-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/30/2023] [Accepted: 09/06/2023] [Indexed: 10/25/2023]
Abstract
Metabolomic epidemiology is the high-throughput study of the relationship between metabolites and health-related traits. This emerging and rapidly growing field has improved our understanding of disease aetiology and contributed to advances in precision medicine. As the field continues to develop, metabolomic epidemiology could lead to the discovery of diagnostic biomarkers predictive of disease risk, aiding in earlier disease detection and better prognosis. In this Review, we discuss key advances facilitated by the field of metabolomic epidemiology for a range of conditions, including cardiometabolic diseases, cancer, Alzheimer's disease and COVID-19, with a focus on potential clinical utility. Core principles in metabolomic epidemiology, including study design, causal inference methods and multi-omic integration, are briefly discussed. Future directions required for clinical translation of metabolomic epidemiology findings are summarized, emphasizing public health implications. Further work is needed to establish which metabolites reproducibly improve clinical risk prediction in diverse populations and are causally related to disease progression.
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Affiliation(s)
- Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Yiwen Zhu
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Jayna Nicholas
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Haley A Chatelaine
- National Center for Advancing Translational Sciences, National Institutes of Health, Bethesda, MD, USA
| | - Emily M Drzymalla
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Afrand K Sarvestani
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | | | - Usman A Tahir
- Department of Cardiology, Beth Israel Deaconess Medical Center, Boston, MA, USA
| | | | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Xinwei Hua
- Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Center, Seattle, WA, USA.
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Joshi AD, Rahnavard A, Kachroo P, Mendez KM, Lawrence W, Julián-Serrano S, Hua X, Fuller H, Sinnott-Armstrong N, Tabung FK, Shutta KH, Raffield LM, Darst BF. An epidemiological introduction to human metabolomic investigations. Trends Endocrinol Metab 2023; 34:505-525. [PMID: 37468430 PMCID: PMC10527234 DOI: 10.1016/j.tem.2023.06.006] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/10/2023] [Revised: 06/17/2023] [Accepted: 06/19/2023] [Indexed: 07/21/2023]
Abstract
Metabolomics holds great promise for uncovering insights around biological processes impacting disease in human epidemiological studies. Metabolites can be measured across biological samples, including plasma, serum, saliva, urine, stool, and whole organs and tissues, offering a means to characterize metabolic processes relevant to disease etiology and traits of interest. Metabolomic epidemiology studies face unique challenges, such as identifying metabolites from targeted and untargeted assays, defining standards for quality control, harmonizing results across platforms that often capture different metabolites, and developing statistical methods for high-dimensional and correlated metabolomic data. In this review, we introduce metabolomic epidemiology to the broader scientific community, discuss opportunities and challenges presented by these studies, and highlight emerging innovations that hold promise to uncover new biological insights.
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Affiliation(s)
- Amit D Joshi
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA
| | - Ali Rahnavard
- Computational Biology Institute, Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, The George Washington University, Washington, DC, USA
| | - Priyadarshini Kachroo
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Kevin M Mendez
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Wayne Lawrence
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA
| | - Sachelly Julián-Serrano
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA; Department of Public Health, University of Massachusetts Lowell, Lowell, MA, USA
| | - Xinwei Hua
- Clinical & Translational Epidemiology Unit, Massachusetts General Hospital, Boston, MA, USA; Department of Cardiology, Peking University Third Hospital, Beijing, China
| | - Harriett Fuller
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nasa Sinnott-Armstrong
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Fred K Tabung
- The Ohio State University College of Medicine and Comprehensive Cancer Center, Columbus, OH, USA
| | - Katherine H Shutta
- Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Laura M Raffield
- Department of Genetics, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA
| | - Burcu F Darst
- Public Health Sciences Division, Fred Hutchinson Cancer Research Center, Seattle, WA, USA.
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Arjani S, Saint-Maurice PF, Julián-Serrano S, Eibl G, Stolzenberg-Solomon R. Body Mass Index Trajectories Across the Adult Life Course and Pancreatic Cancer Risk. JNCI Cancer Spectr 2022; 6:6762867. [PMID: 36255251 PMCID: PMC9651977 DOI: 10.1093/jncics/pkac066] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2022] [Revised: 09/09/2022] [Accepted: 09/16/2022] [Indexed: 01/16/2023] Open
Abstract
BACKGROUND Body mass index (BMI) during adulthood has been associated with pancreatic ductal adenocarcinoma (PDAC), however, patterns of body size across the adult life course have not been studied extensively. We comprehensively evaluated the association between adiposity across adulthood and PDAC. METHODS We conducted a prospective analysis of 269 480 (162 735 males, 106 745 females) National Institutes of Health-AARP Diet and Health Study participants, aged 50-71 years (1995-1996) who self-reported height and weight history. Participants were followed through December 31, 2011. We examined associations between BMI (kg/m2) at ages 18, 35, 50, and 50-71 (baseline) years, their trajectories determined from latent-class trajectory modeling, and incident PDAC. Cox proportional hazard models were used to calculate multivariable adjusted hazards ratios (HRs) and 95% confidence intervals (CIs). RESULTS During up to 15.2 years of follow-up, 3092 (2020 males, 1072 females) patients with incident PDAC were identified. BMI at all 4 ages were statistically significantly associated with increased PDAC (per 5-unit increase, HR = 1.09-1.13) with higher magnitude associations in males than females at ages 35 years and older (Pinteraction < .05). Four BMI trajectories were created. Compared with normal-weight maintainers, normal-to-overweight, normal-to-obese class I, and overweight-to-obese class III trajectories had hazard ratios of 1.15 (95% CI = 1.06 to 1.25), 1.39 (95% CI = 1.25 to 1.54), and 1.48 (95% CI = 1.18 to 1.87), respectively (Pinteraction by sex = .07). CONCLUSIONS High BMI and BMI trajectories that result in overweight or obesity during adulthood were positively associated with PDAC, with stronger associations among those with early onset adiposity and those with male sex. Avoidance of excess body weight throughout the adult life course may prevent PDAC.
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Affiliation(s)
- Simran Arjani
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA,Rutgers New Jersey Medical School, Newark, NJ, USA
| | - Pedro F Saint-Maurice
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA
| | - Sachelly Julián-Serrano
- Metabolic Epidemiology Branch, Division of Cancer Epidemiology & Genetics, National Cancer Institute, National Institutes of Health, Rockville, MD, USA,Department of Public Health, Zuckerberg College of Health Sciences, University of Massachusetts Lowell, Lowell, MA, USA
| | - Guido Eibl
- Department of Surgery, David Geffen School of Medicine at University of California Los Angeles, Los Angeles, CA, USA
| | - Rachael Stolzenberg-Solomon
- Correspondence to: Rachael Stolzenberg-Solomon, RD, MPH, PhD, Metabolic Epidemiology Branch, Division of Cancer Epidemiology and Genetics, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD 20850, USA (e-mail: )
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Julián-Serrano S, Reedy J, Robien K, Stolzenberg-Solomon R. Adherence to 5 Diet Quality Indices and Pancreatic Cancer Risk in a Large US Prospective Cohort. Am J Epidemiol 2022; 191:1584-1600. [PMID: 35474368 PMCID: PMC9989353 DOI: 10.1093/aje/kwac082] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2021] [Revised: 04/21/2022] [Accepted: 04/22/2022] [Indexed: 01/29/2023] Open
Abstract
Few prospective studies have examined associations between diet quality and pancreatic ductal adenocarcinoma (PDAC), or comprehensively compared diet quality indices. We conducted a prospective analysis of adherence to the Healthy Eating Index (HEI)-2015, alternative HEI-2010, alternate Mediterranean diet (aMed), and 2 versions of Dietary Approaches to Stop Hypertension (DASH; Fung and Mellen) and PDAC within the National Institutes of Health (NIH)-AARP Diet and Health Study (United States, 1995-2011). The dietary quality indices were calculated using responses from a 124-item food frequency questionnaire completed by 535,824 participants (315,780 men and 220,044 women). We used Cox proportional hazards regression models to calculate adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) for each diet quality index and PDAC. During follow-up through 2011 (15.5-year median), 3,137 incident PDAC cases were identified. Compared with those with the lowest adherence quintile, participants with the highest adherence to the HEI-2015 (HR = 0.84, 95% CI: 0.75, 0.94), aMed (HR = 0.82, 95% CI: 0.73, 0.93), DASH-Fung (HR = 0.85, 95% CI: 0.77, 0.95), and DASH-Mellen (HR = 0.86, 95% CI: 0.77, 0.96) had a statistically significant, lower PDAC risk; this was not found for the alternative HEI-2010 (HR = 0.93, 95% CI: 0.83, 1.04). This prospective observational study supports the hypothesis that greater adherence to the HEI-2015, aMed, and DASH dietary recommendations may reduce PDAC.
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Affiliation(s)
- Sachelly Julián-Serrano
- Correspondence to Sachelly Julián-Serrano, 9609 Medical Center Drive, NCI Shady Grove, Room 6E574, Rockville, MD 20850 (e-mail: ); or Dr. Rachael Stolzenberg-Solomon, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD 20850 (e-mail: )
| | | | | | - Rachael Stolzenberg-Solomon
- Correspondence to Sachelly Julián-Serrano, 9609 Medical Center Drive, NCI Shady Grove, Room 6E574, Rockville, MD 20850 (e-mail: ); or Dr. Rachael Stolzenberg-Solomon, 9609 Medical Center Drive, NCI Shady Grove, Room 6E420, Rockville, MD 20850 (e-mail: )
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6
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Julián-Serrano S, Yuan F, Barrett MJ, Pfeiffer RM, Stolzenberg-Solomon RZ. Hemochromatosis, Iron Overload-Related Diseases, and Pancreatic Cancer Risk in the Surveillance, Epidemiology, and End Results (SEER)-Medicare. Cancer Epidemiol Biomarkers Prev 2021; 30:2136-2139. [PMID: 34479949 PMCID: PMC8568645 DOI: 10.1158/1055-9965.epi-21-0476] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2021] [Revised: 06/24/2021] [Accepted: 08/24/2021] [Indexed: 01/09/2023] Open
Abstract
BACKGROUND Experimental studies suggest that iron overload might increase pancreatic cancer risk. We evaluated whether prediagnostic hemochromatosis and iron-overload diseases, including sideroblastic and congenital dyserythropoietic anemias, and non-alcoholic-related chronic liver disease (NACLD) were associated with pancreatic cancer risk in older adults. METHODS We conducted a population-based, case-control study within the U.S. Surveillance, Epidemiology, and End Results Program (SEER)-Medicare linked data. Incident primary pancreatic cancer cases were adults > 66 years. Controls were alive at the time cases were diagnosed and matched to cases (4:1 ratio) by age, sex, and calendar year. Hemochromatosis, iron-overload anemias, and NACLD were reported 12 or more months before pancreatic cancer diagnosis or control selection using Medicare claims data. Adjusted unconditional logistic regression models were used to calculate ORs and 95% confidence intervals (CI) between hemochromatosis, sideroblastic and congenital dyserythropoietic anemias, NACLD, and pancreatic cancer. RESULTS Between 1992 and 2015, 80,074 pancreatic cancer cases and 320,296 controls were identified. Overall, we did not observe statistically significant associations between hemochromatosis, sideroblastic anemia, or congenital dyserythropoietic anemia and pancreatic cancer; however, sideroblastic anemia was associated with later primary pancreatic cancer (OR, 1.30; 95% CI, 1.03-1.64). NACLD was associated with first (OR, 1.10; 95% CI, 1.01-1.19), later (OR, 1.17; 95% CI, 1.02-1.35), and all (OR, 1.12; 95% CI, 1.04-1.20) pancreatic cancer. CONCLUSIONS Overall hemochromatosis and iron-overload anemias were not associated with pancreatic cancer, whereas NACLD was associated with increased risk in this large study of older adults. IMPACT These results partly support the hypothesis that iron-overload diseases increase pancreatic cancer risk.
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Affiliation(s)
| | - Fangcheng Yuan
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland
| | | | - Ruth M Pfeiffer
- Division of Cancer Epidemiology and Genetics, NCI, NIH, Bethesda, Maryland
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7
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Julián-Serrano S, Yuan F, Wheeler W, Benyamin B, Machiela MJ, Arslan AA, Beane-Freeman LE, Bracci PM, Duell EJ, Du M, Gallinger S, Giles GG, Goodman PJ, Kooperberg C, Marchand LL, Neale RE, Shu XO, Van Den Eeden SK, Visvanathan K, Zheng W, Albanes D, Andreotti G, Ardanaz E, Babic A, Berndt SI, Brais LK, Brennan P, Bueno-de-Mesquita B, Buring JE, Chanock SJ, Childs EJ, Chung CC, Fabiánová E, Foretová L, Fuchs CS, Gaziano JM, Gentiluomo M, Giovannucci EL, Goggins MG, Hackert T, Hartge P, Hassan MM, Holcátová I, Holly EA, Hung RI, Janout V, Kurtz RC, Lee IM, Malats N, McKean D, Milne RL, Newton CC, Oberg AL, Perdomo S, Peters U, Porta M, Rothman N, Schulze MB, Sesso HD, Silverman DT, Thompson IM, Wactawski-Wende J, Weiderpass E, Wenstzensen N, White E, Wilkens LR, Yu H, Zeleniuch-Jacquotte A, Zhong J, Kraft P, Li D, Campbell PT, Petersen GM, Wolpin BM, Risch HA, Amundadottir LT, Klein AP, Yu K, Stolzenberg-Solomon RZ. Hepcidin-regulating iron metabolism genes and pancreatic ductal adenocarcinoma: a pathway analysis of genome-wide association studies. Am J Clin Nutr 2021; 114:1408-1417. [PMID: 34258619 PMCID: PMC8488877 DOI: 10.1093/ajcn/nqab217] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/14/2021] [Accepted: 06/08/2021] [Indexed: 12/14/2022] Open
Abstract
BACKGROUND Epidemiological studies have suggested positive associations for iron and red meat intake with risk of pancreatic ductal adenocarcinoma (PDAC). Inherited pathogenic variants in genes involved in the hepcidin-regulating iron metabolism pathway are known to cause iron overload and hemochromatosis. OBJECTIVES The objective of this study was to determine whether common genetic variation in the hepcidin-regulating iron metabolism pathway is associated with PDAC. METHODS We conducted a pathway analysis of the hepcidin-regulating genes using single nucleotide polymorphism (SNP) summary statistics generated from 4 genome-wide association studies in 2 large consortium studies using the summary data-based adaptive rank truncated product method. Our population consisted of 9253 PDAC cases and 12,525 controls of European descent. Our analysis included 11 hepcidin-regulating genes [bone morphogenetic protein 2 (BMP2), bone morphogenetic protein 6 (BMP6), ferritin heavy chain 1 (FTH1), ferritin light chain (FTL), hepcidin (HAMP), homeostatic iron regulator (HFE), hemojuvelin (HJV), nuclear factor erythroid 2-related factor 2 (NRF2), ferroportin 1 (SLC40A1), transferrin receptor 1 (TFR1), and transferrin receptor 2 (TFR2)] and their surrounding genomic regions (±20 kb) for a total of 412 SNPs. RESULTS The hepcidin-regulating gene pathway was significantly associated with PDAC (P = 0.002), with the HJV, TFR2, TFR1, BMP6, and HAMP genes contributing the most to the association. CONCLUSIONS Our results support that genetic susceptibility related to the hepcidin-regulating gene pathway is associated with PDAC risk and suggest a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate effect modification by intake of iron-rich foods on this association.
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Affiliation(s)
| | - Fangcheng Yuan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | | | - Beben Benyamin
- Australian Centre for Precision Health, Allied Health and Human Performance, University of South Australia, Adelaide, Australia
- South Australian Health and Medical Research Institute, Adelaide, Australia
| | - Mitchell J Machiela
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Alan A Arslan
- Department of Obstetrics and Gynecology, New York University School of Medicine, New York, NY, USA
| | - Laura E Beane-Freeman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Paige M Bracci
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Eric J Duell
- Unit of Biomarkers and Susceptibility, Oncology Data Analytics Program, Catalan Institute of Oncology, L'Hospitalet de Llobregat, Barcelona, Spain
- Colorectal Cancer Group, ONCOBELL Program, Bellvitge Biomedical Research Institute (IDIBELL), L'Hospitalet de Llobregat, Barcelona, Spain
- Consortium for Biomedical Research in Epidemiology and Public Health (CIBERESP), Madrid, Spain
| | - Mengmeng Du
- Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Steven Gallinger
- Lunenfeld–Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Graham G Giles
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australia
| | - Phyllis J Goodman
- SWOG Statistical Center, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Loic Le Marchand
- Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Rachel E Neale
- Population Health Department, QIMR Berghofer Medical Research Institute, Brisbane, Australia
| | - Xiao-Ou Shu
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt–Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | | | - Kala Visvanathan
- Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, MD, USA
| | - Wei Zheng
- Division of Epidemiology, Department of Medicine, Vanderbilt Epidemiology Center, Vanderbilt–Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA
| | - Demetrius Albanes
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Gabriella Andreotti
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Eva Ardanaz
- Navarra Public Health Institute, Pamplona, Spain
- IdiSNA, Navarra Institute for Health Research, Pamplona, Spain
- CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain
| | - Ana Babic
- Department of Medical Oncology, Dana–Farber Cancer Institute, Boston, MA, USA
| | - Sonja I Berndt
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Lauren K Brais
- Department of Medical Oncology, Dana–Farber Cancer Institute, Boston, MA, USA
| | - Paul Brennan
- International Agency for Research on Cancer (IARC), Lyon, France
| | - Bas Bueno-de-Mesquita
- Department for Determinants of Chronic Diseases, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands
| | - Julie E Buring
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Stephen J Chanock
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Erica J Childs
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Charles C Chung
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Eleonora Fabiánová
- Specialized Institute of Hygiene and Epidemiology, Banska Bystrica, Slovakia
| | - Lenka Foretová
- Department of Cancer Epidemiology and Genetics, Masaryk Memorial Cancer Institute, Brno, Czech Republic
| | - Charles S Fuchs
- Yale Cancer Center and Smilow Cancer Hospital, New Haven, CT, USA
| | | | - Manuel Gentiluomo
- Department of Biology, University of Pisa, Italy
- Genomic Epidemiology Group, German Cancer Research Center, (DKFZ), Heidelberg, Germany
| | | | - Michael G Goggins
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Thilo Hackert
- Department of General, Visceral and Transplantation Surgery, Heidelberg University Hospital, Heidelberg, Germany
| | - Patricia Hartge
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Manal M Hassan
- Department of Epidemiology, University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Ivana Holcátová
- Institute of Public Health and Preventive Medicine, Second Faculty of Medicine, Charles University, Prague, Czech Republic
| | - Elizabeth A Holly
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
| | - Rayjean I Hung
- Lunenfeld–Tanenbaum Research Institute, Sinai Health System, Toronto, Canada
| | - Vladimir Janout
- Faculty of Health Sciences, University of Olomouc, Olomouc, Czech Republic
| | - Robert C Kurtz
- Department of Medicine, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - I-Min Lee
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Núria Malats
- Genetic and Molecular Epidemiology Group, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - David McKean
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
| | - Roger L Milne
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
- Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, The University of Melbourne, Melbourne, Australia
- Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Australia
| | - Christina C Newton
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Ann L Oberg
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Sandra Perdomo
- International Agency for Research on Cancer (IARC), Lyon, France
| | - Ulrike Peters
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Miquel Porta
- Hospital del Mar Institute of Medical Research (IMIM), Universitat Autònoma de Barcelona, Barcelona, Spain
| | - Nathaniel Rothman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Matthias B Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany
- Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany
| | - Howard D Sesso
- Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | - Debra T Silverman
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Ian M Thompson
- CHRISTUS Santa Rosa Hospital–Medical Center, San Antonio, TX, USA
| | - Jean Wactawski-Wende
- Department of Epidemiology and Environmental Health, University at Buffalo, Buffalo, NY, USA
| | - Elisabete Weiderpass
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Nicolas Wenstzensen
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Emily White
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, USA
| | - Lynne R Wilkens
- Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Herbert Yu
- Department of Epidemiology, University of Hawaii Cancer Center, Honolulu, HI, USA
| | - Anne Zeleniuch-Jacquotte
- Department of Population Health and Perlmutter Cancer Center, New York University School of Medicine, New York, NY, USA
| | - Jun Zhong
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Peter Kraft
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | - Dounghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center, Houston, TX, USA
| | - Peter T Campbell
- Department of Population Science, American Cancer Society, Atlanta, GA, USA
| | - Gloria M Petersen
- Department of Health Sciences Research, Mayo Clinic College of Medicine, Rochester, MN, USA
| | - Brian M Wolpin
- Department of Medical Oncology, Dana–Farber Cancer Institute, Boston, MA, USA
| | - Harvey A Risch
- Department of Chronic Disease Epidemiology, Yale School of Public Health, New Haven, CT, USA
| | - Laufey T Amundadottir
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
| | - Alison P Klein
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore, MD, USA
- Department of Pathology, Sol Goldman Pancreatic Cancer Research Center, Johns Hopkins School of Medicine, Baltimore, MD, USA
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA
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Julián-Serrano S, Reedy J, Robien K, Stolzenberg-Solomon R. Abstract 852: Index-based dietary patterns and risk of pancreatic ductal adenocarcinoma: Results from the NIH-AARP Diet and Health Study. Cancer Res 2021. [DOI: 10.1158/1538-7445.am2021-852] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Abstract
Background: There is limited-suggestive evidence for individual dietary components, and few studies have examined whether dietary patterns are associated with pancreatic cancer risk.
Objective: We examined the associations between five established index-based dietary quality patterns and pancreatic ductal adenocarcinoma (PDAC) risk in middle aged and older US adults.
Methods: The Healthy Eating Index (HEI)-2015, Alternative HEI-2010 (AHEI-2010), alternate Mediterranean diet (aMED), and two Dietary Approaches to Stop Hypertension (DASH) scores (Fung et al. and Mellen et al.) were calculated using responses from a food frequency questionnaire data from 535,398 (315,780 men and 224,044 women) NIH-AARP Diet and Health Study participants aged 51-70 years at baseline (1995-1996). Cox proportional hazards regression models were used to calculate hazard ratios (HRs) and 95% confidence intervals (CIs) for PDAC risk according to each dietary pattern quintile. Covariates included in multivariable models were age, sex, smoking, body mass index, diabetes, and energy intake.
Results: During follow-up though 2011 (15.5 years median), 3,137 incident PDAC cases were identified. Participants with the highest adherence scores compared to those with the lowest adherence scores for each dietary pattern (Q5 versus Q1), had a significantly lower risk of PDAC, except for AHEI-2010: HRs (95% CIs) for HEI-2015 [0.84 (0.75, 0.94)], aMED [0.82 (0.73, 0.93)], DASH-Fung [0.86 (0.77, 0.96)], DASH-Mellen [0.86 (0.77, 0.99)] and AHEI-2010 [0.93 (0.83, 1.04)]. Sex-stratified analyses showed stronger results in men for the HEI-2015 [0.78 (0.68, 0.90)], DASH-Fung [0.78 (0.67, 0.91)], and DASH-Mellen [0.82 (0.71, 0.95)] indices. Only the aMED score remained statistically significantly associated with PDAC risk in women [0.76 (0.63, 0.92)]. Tests for interaction by sex were not significant (P-values > 0.07).
Conclusions: In this analysis of dietary patterns and PDAC, we observed a 14-24% lower cancer risk with greater adherence to index-based dietary quality patterns. Our findings support the hypothesis that adherence to dietary recommendations such as the Dietary Guidelines for Americans, Harvard's Healthy Eating Plate, the Mediterranean Diet and the DASH diet may reduce the risk of developing PDAC
Citation Format: Sachelly Julián-Serrano, Jill Reedy, Kim Robien, Rachael Stolzenberg-Solomon. Index-based dietary patterns and risk of pancreatic ductal adenocarcinoma: Results from the NIH-AARP Diet and Health Study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr 852.
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Affiliation(s)
| | - Jill Reedy
- 1National Cancer Institute, National Institutes of Health, Rockville, MD
| | - Kim Robien
- 2George Washington University, Washington, DC
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9
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Julián-Serrano S, Yuan F, Benyamin B, Wheeler W, Amundadottir L, Jacobs E, Kraft P, Li D, Petersen GM, Risch HA, Wolpin B, Yu K, Klein AP, Stolzenberg-Solomon R. Hepcidin-regulating Iron-metabolism Genes and Pancreatic Ductal Adenocarcinoma: A Pathway Analysis of Genome-wide Association Studies. Cancer Epidemiol Biomarkers Prev 2020. [DOI: 10.1158/1055-9965.epi-20-0056] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Abstract
Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal cancer, and epidemiological studies have suggested positive associations with iron and red meat intake. Rare mutations in genes involved in the hepcidin-regulating pathway are known to cause iron overload and hemochromatosis. We hypothesize that the hepcidin-regulating pathway as characterized by common variants from genome-wide association studies will be associated with PDAC. Methods: We conducted a large pathway-based meta-analysis of the hepcidin-regulating genes using the summary based adaptive rank truncated product (sARTP) method in 9,253 PDAC cases and 12,525 controls of European descent from the Pancreatic Cancer Cohort (PanScan) and the Pancreatic Cancer Case-Control (PANC4) consortia. Our analysis included 11 hepcidin-regulating genes (BMP2, BMP6, FTH1, FTL, HAMP, HFE, HJV, NRF2, SLC40A1, TFR1, TFR2) and adjacent genomic regions (20 kb upstream and downstream) with a total of 412 single-nucleotide polymorphisms (SNPs). We also conducted the sARTP with four iron status biomarkers (serum iron, transferrin, transferrin saturation, and ferritin, n = 23,986) using summary statistics from previous GWAS studies (Benyamin, et al. 2014) to examine if the hepcidin-regulating genes were also associated with these iron traits. The sARTP method combines SNP-level associations across variants in a gene or a pathway. Signals from up to five of the most associated SNPs for each gene studied were accumulated. Results: The hepcidin-regulating pathway was significantly associated with PDAC (P-value = 0.002) with the HJV, TFR2, and TFR1 genes contributing the most to the association (gene level P-values = 0.001, 0.014, and 0.019, respectively). The pathway associations were more significant in women than men. This pathway was also significantly associated with the four biomarkers of iron metabolism (P-values <1.5 × 10–7). Conclusions: Our results support that genetic susceptibility related to the hepcidin-regulating pathway is associated with PDAC and a potential role of iron metabolism in pancreatic carcinogenesis. Further studies are needed to evaluate the modifying effect of iron-rich foods and genetic susceptibility of this pathway and PDAC risk.
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Julián-Serrano S, Dodd K, Angleró I, Emenaker N. Ethnic Disparities in EPA and DHA Intake in US Adults: Results from the NHANES 2011–2014 (P04-107-19). Curr Dev Nutr 2019. [DOI: 10.1093/cdn/nzz051.p04-107-19] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Abstract
Abstract
Objectives
Recent studies suggest a large percentage of US adults are not meeting recommended dietary intakes for omega-3 polyunsaturated fatty acids (n-3 PUFA), specifically eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA). Meanwhile, the Institute of Medicine has yet to establish Dietary Reference Intakes for either EPA or DHA and some US populations may be particularly vulnerable. Therefore, we investigated dietary consumption and main food sources of EPA and DHA across racial and ethnic group potentially at-risk. We hypothesized differences in mean dietary intakes of EPA and DHA (P < 0.05) may exist across targeted groups due to differences in ethnocentric dietary patterns.
Methods
For these investigations, data from the NHANES 2011–2014 was analyzed. Group mean daily EPA and DHA intake in grams (g), along with 95% confidence intervals (CI), were computed from up to two 24-hour recall measurements in Hispanics, non-Hispanics whites and others (NHW), non-Hispanic blacks (NHB), and non-Hispanic Asians (NHA). For major food sources across race/ethnic group, the fractions of total intake (and corresponding 95% CIs) from each food item were calculated from the first day's 24-hour recall.
Results
A total of 9848 individuals were included in this analysis, representing 21% Hispanics, 44% NHW, 23% NHB, and 12% NHA. As expected, significant differences (P < 0.0001 for all tests) in mean intake were observed across racial and ethnic groups for energy, total/saturated/monounsaturated/PUFA fat, cholesterol, EPA, and DHA. NHB reported highest total PUFA intake (Mean: 19.60 g; 95% CI: 18.99–20.22) and NHA reported the lowest (Mean: 16.57 g; 95% CI: 15.86–17.27). However, NHA reported an intake 3x higher of EPA (Mean: 0.07 g; 95% CI: 0.06–0.07) and 2x higher of DHA (Mean: 0.12 g; 95% CI: 0.11–0.14) than other ethnic groups. For NHA, oily fish, which are food sources higher in EPA and DHA, were the largest total EPA and DHA contributors. On the other hand, main contributors to EPA and DHA in Hispanics were food sources lower in EPA and DHA.
Conclusions
In summary, we observed EPA and DHA mean daily intakes differ significantly across racial/ethnic groups. Further studies assessing dietary n-3 PUFA intakes in the US population should include differences in ethnocentric dietary patterns.
Funding Sources
This project was funded by the NCI Introduction to Cancer Research Careers.
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Affiliation(s)
| | - Kevin Dodd
- Division of Cancer Prevention, National Cancer Institute
| | | | - Nancy Emenaker
- Division of Cancer Prevention, National Cancer Institute
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Julián-Serrano S, Yu K, Yuan F, Wheeler W, Karimi P, Amundadottir L, Jacobs E, Kraft P, Li D, Petersen GM, Risch HA, Wolphin B, Klein A, Stolzenberg-Solomon R. A Pathway Analysis of Hereditary Hemochromatosis-related Genes and Pancreatic Ductal Adenocarcinoma Risk (FS11-05-19). Curr Dev Nutr 2019. [DOI: 10.1093/cdn/nzz037.fs11-05-19] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Objectives
Hereditary primary hemochromatosis is characterized by dysregulation of iron homeostasis and is caused by a genetic predisposition to absorb too much iron from foods. Hemochromatosis has been associated with some chronic diseases, including hepatocellular carcinoma and type 2 diabetes mellitus. Type 2 diabetes is an established risk factor and high red meat intake has been associated with pancreatic ductal adenocarcinoma (PDAC). We hypothesize that genetic susceptibility to hemochromatosis as determined by known hereditary hemochromatosis-related genes will be associated with PDAC.
Methods
We conducted a pathway analysis of genes known to contribute to hereditary hemochromatosis using the summary-based adaptive rank truncated product (sARTP) method on GWAS summary statistics derived from 9038 PDAC cases and 12,389 controls of European descent collected by the Pancreatic Cancer Cohort Consortium (PanScan) and the Pancreatic Cancer Case-Control Consortium (PANC4).Our analysis included 7 hereditary hemochromatosis genes (HFE, BMP2, HJV, HAMP, TFR2, SLC40A1, and FTH1) and close genomic regions (20 kb upstream and 20 kb downstream) with a total of 176 single nucleotide polymorphisms (SNPs). The sARTP method combines SNP-level associations across SNPs in a gene or a pathway.
Results
The hereditary hemochromatosis pathway was significantly associated with PDAC (P-value = 0.011). HJV and TFR2 genes contributed the most to the association with PDAC risk (gene level P-values = 0.003 and 0.013, respectively).
Conclusions
This study supports the hypothesis that genetic susceptibility related to hereditary hemochromatosis genes are associated with PDAC. Further studies should evaluate the modifying effect of iron-rich foods and genetic susceptibility of hemochromatosis and PDAC risk.
Funding Sources
This work was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health.
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Affiliation(s)
| | - Kai Yu
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
| | - Fangcheng Yuan
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
| | | | - Parisa Karimi
- Division of Cancer Epidemiology and Genetics, National Cancer Institute
| | | | - Eric Jacobs
- Behavioral and Epidemiology Research Group, American Cancer Society
| | - Peter Kraft
- Department of Epidemiology and Department of Biostatistics, Harvard T.H. Chan School of Public Health
| | - Donghui Li
- Department of Gastrointestinal Medical Oncology, The University of Texas MD Anderson Cancer Center
| | | | - Harvey A Risch
- Department of Epidemiology, Yale University School of Public Health
| | - Brian Wolphin
- Department of Medical Oncology, Dana-Farber Cancer Institute
| | - Alison Klein
- Department of Oncology, The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins
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