Untargeted plasma metabolomics and risk of colorectal cancer-an analysis nested within a large-scale prospective cohort

被引:9
作者
Vidman, Linda [1 ]
Zheng, Rui [2 ]
Boden, Stina [1 ,3 ]
Ribbenstedt, Anton [4 ,5 ]
Gunter, Marc J. [6 ,7 ]
Palmqvist, Richard [8 ]
Harlid, Sophia [1 ]
Brunius, Carl [4 ,5 ]
Van Guelpen, Bethany [1 ,9 ]
机构
[1] Umea Univ, Dept Radiat Sci, Oncol, Umea, Sweden
[2] Uppsala Univ, Dept Surg Sci, Med Epidemiol, Uppsala, Sweden
[3] Umea Univ, Dept Clin Sci, Pediat, Umea, Sweden
[4] Chalmers Univ Technol, Dept Biol & Biol Engn, Gothenburg, Sweden
[5] Chalmers Univ Technol, Chalmers Mass Spectrometry Infrastruct, Gothenburg, Sweden
[6] WHO, Nutr & Metab Branch, Int Agcy Res Canc, Lyon, France
[7] Imperial Coll London, Sch Publ Hlth, Dept Epidemiol & Biostat, London, England
[8] Umea Univ, Dept Med Biosci, Pathol, Umea, Sweden
[9] Umea Univ, Wallenberg Ctr Mol Med, Umea, Sweden
基金
瑞典研究理事会;
关键词
Untargeted metabolomics; Colorectal cancer; Early detection; NORTHERN SWEDEN; METABOLITES; MONICA;
D O I
10.1186/s40170-023-00319-x
中图分类号
R73 [肿瘤学];
学科分类号
100214 ;
摘要
BackgroundColorectal cancer (CRC) is a leading cause of cancer-related death worldwide, but if discovered at an early stage, the survival rate is high. The aim of this study was to identify novel markers predictive of future CRC risk using untargeted metabolomics.MethodsThis study included prospectively collected plasma samples from 902 CRC cases and 902 matched cancer-free control participants from the population-based Northern Sweden Health and Disease Study (NSHDS), which were obtained up to 26 years prior to CRC diagnosis. Using reverse-phase liquid chromatography-mass spectrometry (LC-MS), data comprising 5015 metabolic features were obtained. Conditional logistic regression was applied to identify potentially important metabolic features associated with CRC risk. In addition, we investigated if previously reported metabolite biomarkers of CRC risk could be validated in this study population.ResultsIn the univariable analysis, seven metabolic features were associated with CRC risk (using a false discovery rate cutoff of 0.25). Two of these could be annotated, one as pyroglutamic acid (odds ratio per one standard deviation increase = 0.79, 95% confidence interval, 0.70-0.89) and another as hydroxytigecycline (odds ratio per one standard deviation increase = 0.77, 95% confidence interval, 0.67-0.89). Associations with CRC risk were also found for six previously reported metabolic biomarkers of prevalent and/or incident CRC: sebacic acid (inverse association) and L-tryptophan, 3-hydroxybutyric acid, 9,12,13-TriHOME, valine, and 13-OxoODE (positive associations).ConclusionsThese findings suggest that although the circulating metabolome may provide new etiological insights into the underlying causes of CRC development, its potential application for the identification of individuals at higher risk of developing CRC is limited.
引用
收藏
页数:13
相关论文
共 47 条
  • [1] Plasma Choline Metabolites and Colorectal Cancer Risk in the Women's Health Initiative Observational Study
    Bae, Sajin
    Ulrich, Cornelia M.
    Neuhouser, Marian L.
    Malysheva, Olga
    Bailey, Lynn B.
    Xiao, Liren
    Brown, Elissa C.
    Cushing-Haugen, Kara L.
    Zheng, Yingye
    Cheng, Ting-Yuan David
    Miller, Joshua W.
    Green, Ralph
    Lane, Dorothy S.
    Beresford, Shirley A. A.
    Caudill, Marie A.
    [J]. CANCER RESEARCH, 2014, 74 (24) : 7442 - 7452
  • [2] CONTROLLING THE FALSE DISCOVERY RATE - A PRACTICAL AND POWERFUL APPROACH TO MULTIPLE TESTING
    BENJAMINI, Y
    HOCHBERG, Y
    [J]. JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 1995, 57 (01) : 289 - 300
  • [3] RAMClust: A Novel Feature Clustering Method Enables Spectral-Matching-Based Annotation for Metabolomics Data
    Broeckling, C. D.
    Afsar, F. A.
    Neumann, S.
    Ben-Hur, A.
    Prenni, J. E.
    [J]. ANALYTICAL CHEMISTRY, 2014, 86 (14) : 6812 - 6817
  • [4] Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction
    Brunius, Carl
    Shi, Lin
    Landberg, Rikard
    [J]. METABOLOMICS, 2016, 12 (11)
  • [5] Tumor Tissue-Specific Biomarkers of Colorectal Cancer by Anatomic Location and Stage
    Cai, Yuping
    Rattray, Nicholas J. W.
    Zhang, Qian
    Mironova, Varvara
    Santos-Neto, Alvaro
    Muca, Engjel
    Vollmar, Ana K. Rosen
    Hsu, Kuo-Shun
    Rattray, Zahra
    Cross, Justin R.
    Zhang, Yawei
    Paty, Philip B.
    Khan, Sajid A.
    Johnson, Caroline H.
    [J]. METABOLITES, 2020, 10 (06) : 1 - 13
  • [6] Effects of Freeze-Thaw Cycles of Blood Samples on High-Coverage Quantitative Metabolomics
    Chen, Deying
    Han, Wei
    Huan, Tao
    Li, Liang
    Li, Lanjuan
    [J]. ANALYTICAL CHEMISTRY, 2020, 92 (13) : 9265 - 9272
  • [7] Association between antibiotic consumption and colon and rectal cancer development in older individuals: A territory-wide study
    Cheung, Ka Shing
    Chan, Esther W.
    Tam, Anthony
    Wong, Irene O. L.
    Seto, Wai Kay
    Hung, Ivan F. N.
    Wong, Ian C. K.
    Leung, Wai K.
    [J]. CANCER MEDICINE, 2022, 11 (20): : 3863 - 3872
  • [8] A Prospective Study of Serum Metabolites and Colorectal Cancer Risk
    Cross, Amanda J.
    Moore, Steven C.
    Boca, Simina
    Huang, Wen-Yi
    Xiong, Xiaoqin
    Stolzenberg-Solomon, Rachael
    Sinha, Rashmi
    Sampson, Joshua N.
    [J]. CANCER, 2014, 120 (19) : 3049 - 3057
  • [9] Pyroglutamic acidemia: A cause of high anion gap metabolic acidosis
    Dempsey, GA
    Lyall, HJ
    Corke, CF
    Scheinkestel, CD
    [J]. CRITICAL CARE MEDICINE, 2000, 28 (06) : 1803 - 1807
  • [10] Deng L, 2019, CANCER EPIDEM BIOMAR, V28, P1283, DOI [10.1158/1055-9965.EPI-18-1291, 10.1158/1055-9965.epi-18-1291]