TY - JOUR
T1 - Changes in metabolomics profiles over ten years and subsequent risk of developing type 2 diabetes
T2 - Results from the Nurses' Health Study
AU - Wittenbecher, Clemens
AU - Guasch-Ferré, Marta
AU - Haslam, Danielle E.
AU - Dennis, Courtney
AU - Li, Jun
AU - Bhupathiraju, Shilpa N.
AU - Lee, Chih Hao
AU - Qi, Qibin
AU - Liang, Liming
AU - Eliassen, A. Heather
AU - Clish, Clary
AU - Sun, Qi
AU - Hu, Frank B.
N1 - Funding Information:
This work was supported by research grants UM1 CA186107, R01 CA49449, DK112940, and DK119268 from the National Institutes of Health. CW was supported by the German Research Foundation's (DFG) individual fellowship #WI5132/1-1 and the Boston Nutrition Obesity Research Center (P30 DK46200). MG-F was supported by the American Diabetes Association grant #1-18-PMF-029. DEH was supported by the National Institutes of Health T32-CA009001. Dr. Li was supported by NIDDK K99 DK122128 and the Boston Nutrition Obesity Research Center (P30 DK46200). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. None of the funding sources played a role in the design, collection, analysis, or interpretation of the data or decision to submit the manuscript for publication.
Funding Information:
This work was supported by research grants UM1 CA186107 , R01 CA49449 , DK112940, and DK119268 from the National Institutes of Health . CW was supported by the German Research Foundation 's (DFG) individual fellowship # WI5132/1-1 and the Boston Nutrition Obesity Research Center (P30 DK46200) . MG-F was supported by the American Diabetes Association grant # 1-18-PMF-029 . DEH was supported by the National Institutes of Health T32-CA009001 . Dr. Li was supported by NIDDK K99 DK122128 and the Boston Nutrition Obesity Research Center (P30 DK46200). The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. None of the funding sources played a role in the design, collection, analysis, or interpretation of the data or decision to submit the manuscript for publication.
Publisher Copyright:
© 2021
PY - 2022/1
Y1 - 2022/1
N2 - Background: Metabolomics profiles were consistently associated with type 2 diabetes (T2D) risk, but evidence on long-term metabolite changes and T2D incidence is lacking. We examined the associations of 10-year plasma metabolite changes with subsequent T2D risk. Methods: We conducted a nested T2D case-control study (n=244 cases, n=244 matched controls) within the Nurses' Health Study. Repeated metabolomics profiling (170 targeted metabolites) was conducted in participant blood specimens from 1989/1990 and 2000/2001, and T2D occurred between 2002 and 2008. We related 10-year metabolite changes (Δ-values) to subsequent T2D risk using conditional logistic models, adjusting for baseline metabolite levels and baseline levels and concurrent changes of BMI, diet quality, physical activity, and smoking status. Findings: The 10-year changes of thirty-one metabolites were associated with subsequent T2D risk (false discovery rate-adjusted p-values [FDR]<0.05). The top three high T2D risk-associated 10-year changes were (odds ratio [OR] per standard deviation [SD], 95%CI): Δisoleucine (2.72, 1.97-3.79), Δleucine (2.53, 1.86-3.47), and Δvaline (1.93, 1.52-2.44); other high-risk-associated metabolite changes included alanine, tri-/diacylglycerol-fragments, short-chain acylcarnitines, phosphatidylethanolamines, some vitamins, and bile acids (ORs per SD between 1.31and 1.82). The top three low T2D risk-associated 10-year metabolite changes were (OR per SD, 95% CI): ΔN-acetylaspartic acid (0.54, 0.42-0.70), ΔC20:0 lysophosphatidylethanolamine (0.68, 0.56-0.82), and ΔC16:1 sphingomyelin (0.68, 0.56-0.83); 10-year changes of other sphingomyelins, plasmalogens, glutamine, and glycine were also associated with lower subsequent T2D risk (ORs per SD between 0.66 and 0.78). Interpretation: Repeated metabolomics profiles reflecting the long-term deterioration of amino acid and lipid metabolism are associated with subsequent risk of T2D.
AB - Background: Metabolomics profiles were consistently associated with type 2 diabetes (T2D) risk, but evidence on long-term metabolite changes and T2D incidence is lacking. We examined the associations of 10-year plasma metabolite changes with subsequent T2D risk. Methods: We conducted a nested T2D case-control study (n=244 cases, n=244 matched controls) within the Nurses' Health Study. Repeated metabolomics profiling (170 targeted metabolites) was conducted in participant blood specimens from 1989/1990 and 2000/2001, and T2D occurred between 2002 and 2008. We related 10-year metabolite changes (Δ-values) to subsequent T2D risk using conditional logistic models, adjusting for baseline metabolite levels and baseline levels and concurrent changes of BMI, diet quality, physical activity, and smoking status. Findings: The 10-year changes of thirty-one metabolites were associated with subsequent T2D risk (false discovery rate-adjusted p-values [FDR]<0.05). The top three high T2D risk-associated 10-year changes were (odds ratio [OR] per standard deviation [SD], 95%CI): Δisoleucine (2.72, 1.97-3.79), Δleucine (2.53, 1.86-3.47), and Δvaline (1.93, 1.52-2.44); other high-risk-associated metabolite changes included alanine, tri-/diacylglycerol-fragments, short-chain acylcarnitines, phosphatidylethanolamines, some vitamins, and bile acids (ORs per SD between 1.31and 1.82). The top three low T2D risk-associated 10-year metabolite changes were (OR per SD, 95% CI): ΔN-acetylaspartic acid (0.54, 0.42-0.70), ΔC20:0 lysophosphatidylethanolamine (0.68, 0.56-0.82), and ΔC16:1 sphingomyelin (0.68, 0.56-0.83); 10-year changes of other sphingomyelins, plasmalogens, glutamine, and glycine were also associated with lower subsequent T2D risk (ORs per SD between 0.66 and 0.78). Interpretation: Repeated metabolomics profiles reflecting the long-term deterioration of amino acid and lipid metabolism are associated with subsequent risk of T2D.
KW - Amino acids
KW - Change analysis
KW - Lipids
KW - Metabolomics
KW - Prospective cohort study
KW - Repeated measurements
KW - Type 2 diabetes
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U2 - 10.1016/j.ebiom.2021.103799
DO - 10.1016/j.ebiom.2021.103799
M3 - Article
C2 - 34979341
AN - SCOPUS:85121985887
SN - 2352-3964
VL - 75
JO - EBioMedicine
JF - EBioMedicine
M1 - 103799
ER -
