Search for Early Pancreatic Cancer Blood Biomarkers in Five European Prospective Population Biobanks Using Metabolomics

Author:

Fest Jesse12,Vijfhuizen Lisanne S3,Goeman Jelle J4,Veth Olga3ORCID,Joensuu Anni56ORCID,Perola Markus56,Männistö Satu5,Ness-Jensen Eivind7ORCID,Hveem Kristian7,Haller Toomas8ORCID,Tonisson Neeme89,Mikkel Kairit8,Metspalu Andres8ORCID,van Duijn Cornelia M2,Ikram Arfan2,Stricker Bruno H2,Ruiter Rikje2,van Eijck Casper H J1,van Ommen Gert-Jan B3ORCID,ʼt Hoen Peter A C310ORCID

Affiliation:

1. Department of Surgery, Erasmus Medical Center, Rotterdam, Netherlands

2. Department of Epidemiology, Erasmus Medical Center, Rotterdam, Netherlands

3. Department of Human Genetics, Leiden University Medical Center, Leiden, Netherlands

4. Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, Netherlands

5. Department of Public Health Solutions, National Institute for Health and Welfare, Helsinki, Finland

6. Research Program for Clinical and Molecular Metabolism, Faculty of Medicine, University of Helsinki, Helsinki, Finland

7. HUNT Research Center, Department of Public Health and Nursing, Norwegian University of Science and Technology, Levanger, Norway

8. Institute of Genomics, University of Tartu, Tartu, Estonia

9. Department of Clinical Genetics, Tartu University Hospital, Tartu, Estonia

10. Center for Molecular and Biomolecular Informatics, Radboud Institute for Molecular Life Sciences, Radboud University Medical Center, Nijmegen, Netherlands

Abstract

Abstract Most patients with pancreatic cancer present with advanced disease and die within the first year after diagnosis. Predictive biomarkers that signal the presence of pancreatic cancer in an early stage are desperately needed. We aimed to identify new and validate previously found plasma metabolomic biomarkers associated with early stages of pancreatic cancer. Prediagnostic blood samples from individuals who were to receive a diagnosis of pancreatic cancer between 1 month and 17 years after sampling (N = 356) and age- and sex-matched controls (N = 887) were collected from five large population cohorts (HUNT2, HUNT3, FINRISK, Estonian Biobank, Rotterdam Study). We applied proton nuclear magnetic resonance–based metabolomics on the Nightingale platform. Logistic regression identified two interesting hits: glutamine (P = 0.011) and histidine (P = 0.012), with Westfall–Young family-wise error rate adjusted P values of 0.43 for both. Stratification in quintiles showed a 1.5-fold elevated risk for the lowest 20% of glutamine and a 2.2-fold increased risk for the lowest 20% of histidine. Stratification by time to diagnosis suggested glutamine to be involved in an earlier process (2 to 5 years before diagnosis), and histidine in a process closer to the actual onset (<2 years). Our data did not support the branched-chain amino acids identified earlier in several US cohorts as potential biomarkers for pancreatic cancer. Thus, although we identified glutamine and histidine as potential biomarkers of biological interest, our results imply that a study at this scale does not yield metabolomic biomarkers with sufficient predictive value to be clinically useful per se as prognostic biomarkers.

Funder

FP7 Research infrastructures

H2020 Research Infrastructures

Finnish Academy

Yrjö Jahnssonin Säätiö

Horizon 2020 Framework Programme

Estonian Government

European Regional Development Fund

National Institutes of Health

Publisher

The Endocrine Society

Subject

Endocrinology

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3