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Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case–control study in the HUNT and Lifelines cohorts
Introduction Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM). Objectives We asse...
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Published in: | Metabolomics 2019-04, Vol.15 (4), p.60-16, Article 60 |
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creator | Gängler, Stephanie Waldenberger, Melanie Artati, Anna Adamski, Jerzy van Bolhuis, Jurjen N. Sørgjerd, Elin Pettersen van Vliet-Ostaptchouk, Jana Makris, Konstantinos C. |
description | Introduction
Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM).
Objectives
We assessed whether THM were associated with type 2 diabetes (T2D) and we explored alterations in metabolic profiles due to THM exposures or T2D status.
Methods
A prospective 1:1 matched case–control study (n = 430) and a cross-sectional 1:1 matched case–control study (n = 362) nested within the HUNT cohort (Norway) and the Lifelines cohort (Netherlands), respectively, were set up. Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were measured. Associations between THM, clinical markers, metabolites and disease status were evaluated using logistic regressions with Least Absolute Shrinkage and Selection Operator procedure.
Results
Low median THM exposures (ng/g, IQR) were measured in both cohorts (cases and controls of HUNT and Lifelines, respectively, 193 (76, 470), 208 (77, 502) and 292 (162, 595), 342 (180, 602). Neither BrTHM (OR = 0.87; 95% CI: 0.67, 1.11 | OR = 1.09; 95% CI: 0.73, 1.61), nor TCM (OR = 1.03; 95% CI: 0.88, 1.2 | OR = 1.03; 95% CI: 0.79, 1.35) were associated with incident or prevalent T2D, respectively. Metabolomics showed 48 metabolites associated with incident T2D after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent T2D. A total of 34 metabolites were associated with the progression of T2D. In data driven logistic regression, novel biomarkers, such as cinnamoylglycine or 1-methylurate, being protective of T2D were identified. The incident T2D risk prediction model (HUNT) predicted well incident Lifelines cases (AUC = 0.845; 95% CI: 0.72, 0.97).
Conclusion
Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis. |
doi_str_mv | 10.1007/s11306-019-1519-0 |
format | article |
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Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM).
Objectives
We assessed whether THM were associated with type 2 diabetes (T2D) and we explored alterations in metabolic profiles due to THM exposures or T2D status.
Methods
A prospective 1:1 matched case–control study (n = 430) and a cross-sectional 1:1 matched case–control study (n = 362) nested within the HUNT cohort (Norway) and the Lifelines cohort (Netherlands), respectively, were set up. Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were measured. Associations between THM, clinical markers, metabolites and disease status were evaluated using logistic regressions with Least Absolute Shrinkage and Selection Operator procedure.
Results
Low median THM exposures (ng/g, IQR) were measured in both cohorts (cases and controls of HUNT and Lifelines, respectively, 193 (76, 470), 208 (77, 502) and 292 (162, 595), 342 (180, 602). Neither BrTHM (OR = 0.87; 95% CI: 0.67, 1.11 | OR = 1.09; 95% CI: 0.73, 1.61), nor TCM (OR = 1.03; 95% CI: 0.88, 1.2 | OR = 1.03; 95% CI: 0.79, 1.35) were associated with incident or prevalent T2D, respectively. Metabolomics showed 48 metabolites associated with incident T2D after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent T2D. A total of 34 metabolites were associated with the progression of T2D. In data driven logistic regression, novel biomarkers, such as cinnamoylglycine or 1-methylurate, being protective of T2D were identified. The incident T2D risk prediction model (HUNT) predicted well incident Lifelines cases (AUC = 0.845; 95% CI: 0.72, 0.97).
Conclusion
Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis.</description><identifier>ISSN: 1573-3882</identifier><identifier>EISSN: 1573-3890</identifier><identifier>DOI: 10.1007/s11306-019-1519-0</identifier><identifier>PMID: 30963292</identifier><language>eng</language><publisher>New York: Springer US</publisher><subject>Adult ; Biochemistry ; Biomarkers ; Biomarkers - blood ; Biomarkers - urine ; Biomedical and Life Sciences ; Biomedicine ; Case-Control Studies ; Cell Biology ; Chloroform ; Chloroform - adverse effects ; Cohort Studies ; Developmental Biology ; Diabetes ; Diabetes mellitus ; Diabetes mellitus (non-insulin dependent) ; Diabetes Mellitus, Type 2 - etiology ; Diabetes Mellitus, Type 2 - metabolism ; Disinfectants - adverse effects ; Disinfection ; Female ; Halogenation ; Humans ; Life Sciences ; Male ; Mass spectroscopy ; Metabolism ; Metabolites ; Metabolomics ; Metabolomics - methods ; Middle Aged ; Molecular Medicine ; Original Article ; Prediction models ; Prospective Studies ; Risk Factors ; Trihalomethanes ; Trihalomethanes - adverse effects ; Trihalomethanes - metabolism</subject><ispartof>Metabolomics, 2019-04, Vol.15 (4), p.60-16, Article 60</ispartof><rights>Springer Science+Business Media, LLC, part of Springer Nature 2019</rights><rights>Metabolomics is a copyright of Springer, (2019). All Rights Reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c415t-d68418a1827228e8cb3a6e8b7dbb46a017dc440dfeb6b06c50f7889e5f59b3733</citedby><cites>FETCH-LOGICAL-c415t-d68418a1827228e8cb3a6e8b7dbb46a017dc440dfeb6b06c50f7889e5f59b3733</cites><orcidid>0000-0001-5251-8619</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27924,27925</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/30963292$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Gängler, Stephanie</creatorcontrib><creatorcontrib>Waldenberger, Melanie</creatorcontrib><creatorcontrib>Artati, Anna</creatorcontrib><creatorcontrib>Adamski, Jerzy</creatorcontrib><creatorcontrib>van Bolhuis, Jurjen N.</creatorcontrib><creatorcontrib>Sørgjerd, Elin Pettersen</creatorcontrib><creatorcontrib>van Vliet-Ostaptchouk, Jana</creatorcontrib><creatorcontrib>Makris, Konstantinos C.</creatorcontrib><title>Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case–control study in the HUNT and Lifelines cohorts</title><title>Metabolomics</title><addtitle>Metabolomics</addtitle><addtitle>Metabolomics</addtitle><description>Introduction
Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM).
Objectives
We assessed whether THM were associated with type 2 diabetes (T2D) and we explored alterations in metabolic profiles due to THM exposures or T2D status.
Methods
A prospective 1:1 matched case–control study (n = 430) and a cross-sectional 1:1 matched case–control study (n = 362) nested within the HUNT cohort (Norway) and the Lifelines cohort (Netherlands), respectively, were set up. Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were measured. Associations between THM, clinical markers, metabolites and disease status were evaluated using logistic regressions with Least Absolute Shrinkage and Selection Operator procedure.
Results
Low median THM exposures (ng/g, IQR) were measured in both cohorts (cases and controls of HUNT and Lifelines, respectively, 193 (76, 470), 208 (77, 502) and 292 (162, 595), 342 (180, 602). Neither BrTHM (OR = 0.87; 95% CI: 0.67, 1.11 | OR = 1.09; 95% CI: 0.73, 1.61), nor TCM (OR = 1.03; 95% CI: 0.88, 1.2 | OR = 1.03; 95% CI: 0.79, 1.35) were associated with incident or prevalent T2D, respectively. Metabolomics showed 48 metabolites associated with incident T2D after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent T2D. A total of 34 metabolites were associated with the progression of T2D. In data driven logistic regression, novel biomarkers, such as cinnamoylglycine or 1-methylurate, being protective of T2D were identified. The incident T2D risk prediction model (HUNT) predicted well incident Lifelines cases (AUC = 0.845; 95% CI: 0.72, 0.97).
Conclusion
Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis.</description><subject>Adult</subject><subject>Biochemistry</subject><subject>Biomarkers</subject><subject>Biomarkers - blood</subject><subject>Biomarkers - urine</subject><subject>Biomedical and Life Sciences</subject><subject>Biomedicine</subject><subject>Case-Control Studies</subject><subject>Cell Biology</subject><subject>Chloroform</subject><subject>Chloroform - adverse effects</subject><subject>Cohort Studies</subject><subject>Developmental Biology</subject><subject>Diabetes</subject><subject>Diabetes mellitus</subject><subject>Diabetes mellitus (non-insulin dependent)</subject><subject>Diabetes Mellitus, Type 2 - etiology</subject><subject>Diabetes Mellitus, Type 2 - metabolism</subject><subject>Disinfectants - adverse effects</subject><subject>Disinfection</subject><subject>Female</subject><subject>Halogenation</subject><subject>Humans</subject><subject>Life Sciences</subject><subject>Male</subject><subject>Mass spectroscopy</subject><subject>Metabolism</subject><subject>Metabolites</subject><subject>Metabolomics</subject><subject>Metabolomics - methods</subject><subject>Middle Aged</subject><subject>Molecular Medicine</subject><subject>Original Article</subject><subject>Prediction models</subject><subject>Prospective Studies</subject><subject>Risk Factors</subject><subject>Trihalomethanes</subject><subject>Trihalomethanes - adverse effects</subject><subject>Trihalomethanes - metabolism</subject><issn>1573-3882</issn><issn>1573-3890</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2019</creationdate><recordtype>article</recordtype><recordid>eNp1kc1qFTEYhgdRbK1egBsJuHEzmp_Jz7iTUlvhoJt2HfLzjU2dkxyTDHh2vQfv0CtpxlMrCG6SQJ73yRferntJ8FuCsXxXCGFY9JiMPeFtwY-6Y8Il65ka8eOHs6JH3bNSbjAehlHip90Rw6NgdKTH3e3Zj10qSwZUE_KhhDiBqyFFZPe7nPziakEmepRD-YbShOp-B4g21FioUN4jgyKUCh45U-DX7U-XYs1pRqUufo9CRPUa0MXV58vfmk2YYA4tgVy6TrmW592TycwFXtzvJ93Vx7PL04t-8-X80-mHTe8GwmvvhRqIMkRRSakC5SwzApSV3tpBGEykd8OA_QRWWCwcx5NUagQ-8dEyydhJ9-bgbb_6vrSJ9TYUB_NsIqSlaEqxaGYqVvT1P-hNWnJs060UH4TkHDeKHCiXUykZJr3LYWvyXhOs13r0oR7d6tFrPXrNvLo3L3YL_iHxp48G0ANQ2lX8Cvnv0_-33gGfWJuz</recordid><startdate>20190401</startdate><enddate>20190401</enddate><creator>Gängler, Stephanie</creator><creator>Waldenberger, Melanie</creator><creator>Artati, Anna</creator><creator>Adamski, Jerzy</creator><creator>van Bolhuis, Jurjen N.</creator><creator>Sørgjerd, Elin Pettersen</creator><creator>van Vliet-Ostaptchouk, Jana</creator><creator>Makris, Konstantinos C.</creator><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7X7</scope><scope>7XB</scope><scope>8FE</scope><scope>8FH</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BBNVY</scope><scope>BENPR</scope><scope>BHPHI</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>HCIFZ</scope><scope>K9.</scope><scope>LK8</scope><scope>M0S</scope><scope>M7P</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>7X8</scope><orcidid>https://orcid.org/0000-0001-5251-8619</orcidid></search><sort><creationdate>20190401</creationdate><title>Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case–control study in the HUNT and Lifelines cohorts</title><author>Gängler, Stephanie ; Waldenberger, Melanie ; Artati, Anna ; Adamski, Jerzy ; van Bolhuis, Jurjen N. ; Sørgjerd, Elin Pettersen ; van Vliet-Ostaptchouk, Jana ; Makris, Konstantinos C.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c415t-d68418a1827228e8cb3a6e8b7dbb46a017dc440dfeb6b06c50f7889e5f59b3733</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2019</creationdate><topic>Adult</topic><topic>Biochemistry</topic><topic>Biomarkers</topic><topic>Biomarkers - blood</topic><topic>Biomarkers - urine</topic><topic>Biomedical and Life Sciences</topic><topic>Biomedicine</topic><topic>Case-Control Studies</topic><topic>Cell Biology</topic><topic>Chloroform</topic><topic>Chloroform - adverse effects</topic><topic>Cohort Studies</topic><topic>Developmental Biology</topic><topic>Diabetes</topic><topic>Diabetes mellitus</topic><topic>Diabetes mellitus (non-insulin dependent)</topic><topic>Diabetes Mellitus, Type 2 - etiology</topic><topic>Diabetes Mellitus, Type 2 - metabolism</topic><topic>Disinfectants - adverse effects</topic><topic>Disinfection</topic><topic>Female</topic><topic>Halogenation</topic><topic>Humans</topic><topic>Life Sciences</topic><topic>Male</topic><topic>Mass spectroscopy</topic><topic>Metabolism</topic><topic>Metabolites</topic><topic>Metabolomics</topic><topic>Metabolomics - methods</topic><topic>Middle Aged</topic><topic>Molecular Medicine</topic><topic>Original Article</topic><topic>Prediction models</topic><topic>Prospective Studies</topic><topic>Risk Factors</topic><topic>Trihalomethanes</topic><topic>Trihalomethanes - adverse effects</topic><topic>Trihalomethanes - metabolism</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Gängler, Stephanie</creatorcontrib><creatorcontrib>Waldenberger, Melanie</creatorcontrib><creatorcontrib>Artati, Anna</creatorcontrib><creatorcontrib>Adamski, Jerzy</creatorcontrib><creatorcontrib>van Bolhuis, Jurjen N.</creatorcontrib><creatorcontrib>Sørgjerd, Elin Pettersen</creatorcontrib><creatorcontrib>van Vliet-Ostaptchouk, Jana</creatorcontrib><creatorcontrib>Makris, Konstantinos C.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Natural Science Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central</collection><collection>ProQuest Central Essentials</collection><collection>Biological Science Collection</collection><collection>ProQuest Central</collection><collection>ProQuest Natural Science Collection</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>ProQuest Biological Science Collection</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>ProQuest Biological Science Journals</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>MEDLINE - Academic</collection><jtitle>Metabolomics</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Gängler, Stephanie</au><au>Waldenberger, Melanie</au><au>Artati, Anna</au><au>Adamski, Jerzy</au><au>van Bolhuis, Jurjen N.</au><au>Sørgjerd, Elin Pettersen</au><au>van Vliet-Ostaptchouk, Jana</au><au>Makris, Konstantinos C.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case–control study in the HUNT and Lifelines cohorts</atitle><jtitle>Metabolomics</jtitle><stitle>Metabolomics</stitle><addtitle>Metabolomics</addtitle><date>2019-04-01</date><risdate>2019</risdate><volume>15</volume><issue>4</issue><spage>60</spage><epage>16</epage><pages>60-16</pages><artnum>60</artnum><issn>1573-3882</issn><eissn>1573-3890</eissn><abstract>Introduction
Environmental chemicals acting as metabolic disruptors have been implicated with diabetogenesis, but evidence is weak among short-lived chemicals, such as disinfection byproducts (trihalomethanes, THM composed of chloroform, TCM and brominated trihalomethanes, BrTHM).
Objectives
We assessed whether THM were associated with type 2 diabetes (T2D) and we explored alterations in metabolic profiles due to THM exposures or T2D status.
Methods
A prospective 1:1 matched case–control study (n = 430) and a cross-sectional 1:1 matched case–control study (n = 362) nested within the HUNT cohort (Norway) and the Lifelines cohort (Netherlands), respectively, were set up. Urinary biomarkers of THM exposure and mass spectrometry-based serum metabolomics were measured. Associations between THM, clinical markers, metabolites and disease status were evaluated using logistic regressions with Least Absolute Shrinkage and Selection Operator procedure.
Results
Low median THM exposures (ng/g, IQR) were measured in both cohorts (cases and controls of HUNT and Lifelines, respectively, 193 (76, 470), 208 (77, 502) and 292 (162, 595), 342 (180, 602). Neither BrTHM (OR = 0.87; 95% CI: 0.67, 1.11 | OR = 1.09; 95% CI: 0.73, 1.61), nor TCM (OR = 1.03; 95% CI: 0.88, 1.2 | OR = 1.03; 95% CI: 0.79, 1.35) were associated with incident or prevalent T2D, respectively. Metabolomics showed 48 metabolites associated with incident T2D after adjusting for sex, age and BMI, whereas a total of 244 metabolites were associated with prevalent T2D. A total of 34 metabolites were associated with the progression of T2D. In data driven logistic regression, novel biomarkers, such as cinnamoylglycine or 1-methylurate, being protective of T2D were identified. The incident T2D risk prediction model (HUNT) predicted well incident Lifelines cases (AUC = 0.845; 95% CI: 0.72, 0.97).
Conclusion
Such exposome-based approaches in cohort-nested studies are warranted to better understand the environmental origins of diabetogenesis.</abstract><cop>New York</cop><pub>Springer US</pub><pmid>30963292</pmid><doi>10.1007/s11306-019-1519-0</doi><tpages>16</tpages><orcidid>https://orcid.org/0000-0001-5251-8619</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Biochemistry Biomarkers Biomarkers - blood Biomarkers - urine Biomedical and Life Sciences Biomedicine Case-Control Studies Cell Biology Chloroform Chloroform - adverse effects Cohort Studies Developmental Biology Diabetes Diabetes mellitus Diabetes mellitus (non-insulin dependent) Diabetes Mellitus, Type 2 - etiology Diabetes Mellitus, Type 2 - metabolism Disinfectants - adverse effects Disinfection Female Halogenation Humans Life Sciences Male Mass spectroscopy Metabolism Metabolites Metabolomics Metabolomics - methods Middle Aged Molecular Medicine Original Article Prediction models Prospective Studies Risk Factors Trihalomethanes Trihalomethanes - adverse effects Trihalomethanes - metabolism |
title | Exposure to disinfection byproducts and risk of type 2 diabetes: a nested case–control study in the HUNT and Lifelines cohorts |
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