No retraction, correction or concern found when last checked on Oct 18, 2026.

Indolepropionic acid and novel lipid metabolites are associated with a lower risk of type 2 diabetes in the Finnish Diabetes Prevention Study

Vanessa D. de Mello, Jussi Paananen, Jaana Lindström and 16 more

Scientific Reports · 2017 · CC BY

Abstract

Wide-scale profiling technologies including metabolomics broaden the possibility of novel discoveries related to the pathogenesis of type 2 diabetes (T2D). By applying non-targeted metabolomics approach, we investigated here whether serum metabolite profile predicts T2D in a well-characterized study population with impaired glucose tolerance by examining two groups of individuals who took part in the Finnish Diabetes Prevention Study (DPS); those who either early developed T2D (n = 96) or did not convert to T2D within the 15-year follow-up (n = 104). Several novel metabolites were associated with lower likelihood of developing T2D, including indole and lipid related metabolites. Higher indolepropionic acid was associated with reduced likelihood of T2D in the DPS. Interestingly, in those who remained free of T2D, indolepropionic acid and various lipid species were associated with better insulin secretion and sensitivity, respectively. Furthermore, these metabolites were negatively correlated with low-grade inflammation. We replicated the association between indolepropionic acid and T2D risk in one Finnish and one Swedish population. We suggest that indolepropionic acid, a gut microbiota-produced metabolite, is a potential biomarker for the development of T2D that may mediate its protective effect by preservation of β-cell function. Novel lipid metabolites associated with T2D may exert their effects partly through enhancing insulin sensitivity.

References 54

1.
Wang T. J.. Metabolite profiles and the risk of developing diabetes. Nat. Med. 17, 448–453 (2011 ).
Not in our library10.1038/nm.2307
2.
Floegel A.. Identification of serum metabolites associated with risk of type 2 diabetes using a targeted metabolomic approach. Diabetes 62, 639–648 (2013 ).
Not in our library10.2337/db12-0495
3.
Menni C.. Biomarkers for type 2 diabetes and impaired fasting glucose using a nontargeted metabolomics approach. Diabetes 62, 4270–4276 (2013 ).
Not in our library10.2337/db13-0570
4.
Plasma Lipid Profiling Shows Similar Associations with Prediabetes and Type 2 Diabetes · 2013
No notice
5.
Hanhineva K.. Nontargeted metabolite profiling discriminates diet-specific biomarkers for consumption of whole grains, fatty fish, and bilberries in a randomized controlled trial. J. Nutr. 145, 7–17 (2015 ).
Not in our library10.3945/jn.114.196840
6.
Lindström J.. Improved lifestyle and decreased diabetes risk over 13 years: long-term follow-up of the randomised Finnish Diabetes Prevention Study (DPS). Diabetologia 56, 284–293 (2013 ).
Not in our library10.1007/s00125-012-2752-5
7.
de Mello V. D.. Insulin secretion and its determinants in the progression of impaired glucose tolerance to type 2 diabetes in impaired glucose-tolerant individuals: the Finnish Diabetes Prevention Study. Diabetes Care 35, 211–217 (2012 ).
Not in our library10.2337/dc11-1272
8.
Lankinen M. A.. Plasma fatty acids as predictors of glycaemia and type 2 diabetes. Diabetologia 58, 2533–2544 (2015 ).
Not in our library10.1007/s00125-015-3730-5
9.
Rolandsson O.. How to diagnose and classify diabetes in primary health care: lessons learned from the Diabetes Register in Northern Sweden (DiabNorth). Scand. J. Prim. Health Care 30, 81–87 (2012 ).
Not in our library10.3109/02813432.2012.675565
10.
Smith E. A. & Macfarlane G. T. Enumeration of human colonic bacteria producing phenolic and indolic compounds: effects of pH, carbohydrate availability and retention time on dissimilatory aromatic amino acid metabolism. J. Appl. Bacteriol. 81, 288–302 (1996 ).
Not in our library10.1111/j.1365-2672.1996.tb04331.x
11.
Smith E. A. & Macfarlane G. T. Formation of Phenolic and Indolic Compounds by Anaerobic Bacteria in the Human Large Intestine. Microb. Ecol. 33, 180–188 (1997 ).
Not in our library10.1007/s002489900020
12.
Wikoff W. R.. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc. Natl. Acad. Sci. USA 106, 3698–3703 (2009 ).
Not in our library10.1073/pnas.0812874106
13.
Haeusler R. A., Astiarraga B., Camastra S., Accili D. & Ferrannini E. Human insulin resistance is associated with increased plasma levels of 12alpha-hydroxylated bile acids. Diabetes 62, 4184–4191 (2013 ).
Not in our library10.2337/db13-0639
14.
Guasch-Ferré M.. Dietary fat intake and risk of cardiovascular disease and all-cause mortality in a population at high risk of cardiovascular disease. The American Journal of Clinical Nutrition(2015 ).
Not in our library10.3945/ajcn.115.116046
15.
Bacterial Metabolite Indole Modulates Incretin Secretion from Intestinal Enteroendocrine L Cells · 2014
No notice
16.
Garber A. J. Incretin effects on beta-cell function, replication, and mass: the human perspective. Diabetes Care 34 Suppl 2, S258–63 (2011 ).
Not in our library10.2337/dc11-s230
17.
Chyan Y. J.. Potent neuroprotective properties against the Alzheimer beta-amyloid by an endogenous melatonin-related indole structure, indole-3-propionic acid. J. Biol. Chem. 274, 21937–21942 (1999 ).
Not in our library10.1074/jbc.274.31.21937
18.
Karbownik M.. Indole-3-propionic acid, a melatonin-related molecule, protects hepatic microsomal membranes from iron-induced oxidative damage: relevance to cancer reduction. J. Cell. Biochem. 81, 507–513 (2001 ).
Not in our library
19.
Halban P. A.. Beta-Cell Failure in Type 2 Diabetes: Postulated Mechanisms and Prospects for Prevention and Treatment. Diabetes Care 37, 1751–1758 (2014 ).
Not in our library10.2337/dc14-0396
20.
Lutz T. A. & Meyer U. Amylin at the interface between metabolic and neurodegenerative disorders. Front. Neurosci. 9, 216 (2015 ).
Not in our library10.3389/fnins.2015.00216
21.
Haro C.. Two healthy diets modulate gut microbial community improving insulin sensitivity in a human obese population. J. Clin. Endocrinol. Metab. 101, 233–242 (2016 ).
Not in our library10.1210/jc.2015-3351
22.
Marchesi J. R.. The gut microbiota and host health: a new clinical frontier. Gut 65, 330–339 (2016 ).
Not in our library10.1136/gutjnl-2015-309990
23.
De Filippis,. F.. High-level adherence to a Mediterranean diet beneficially impacts the gut microbiota and associated metabolome. Gut(2015 ).
Not in our library10.1136/gutjnl-2015-309957
24.
Landberg R., Aman P., Hallmans G. & Johansson I. Long-term reproducibility of plasma alkylresorcinols as biomarkers of whole-grain wheat and rye intake within Northern Sweden Health and Disease Study Cohort. Eur. J. Clin. Nutr. 67, 259–263 (2013 ).
Not in our library10.1038/ejcn.2013.10
25.
Dietary fibre and incidence of type 2 diabetes in eight European countries: the EPIC-InterAct Study and a meta-analysis of prospective studies · 2015
No notice
26.
Qin J.. A metagenome-wide association study of gut microbiota in type 2 diabetes. Nature 490, 55–60 (2012 ).
Not in our library10.1038/nature11450
27.
Soga T.. Lysophosphatidylcholine enhances glucose-dependent insulin secretion via an orphan G-protein-coupled receptor. Biochem. Biophys. Res. Commun. 326, 744–751 (2005).
Not in our library10.1016/j.bbrc.2004.11.120
28.
Yea K.. Lysophosphatidylcholine activates adipocyte glucose uptake and lowers blood glucose levels in murine models of diabetes. J. Biol. Chem. 284, 33833–33840 (2009 ).
Not in our library10.1074/jbc.m109.024869
29.
Pedersen H. K.. Human gut microbes impact host serum metabolome and insulin sensitivity. Nature 535, 376–381 (2016 ).
Not in our library10.1038/nature18646
30.
Wang X.. Inflammatory markers and risk of type 2 diabetes: a systematic review and meta-analysis. Diabetes Care 36, 166–175 (2013 ).
Not in our library10.2337/dc12-0702
31.
Liu C.. Adiponectin, TNF-alpha and inflammatory cytokines and risk of type 2 diabetes: A systematic review and meta-analysis. Cytokine 86, 100–109 (2016 ).
Not in our library10.1016/j.cyto.2016.06.028
32.
Pfeuffer M. & Jaudszus A. Pentadecanoic and Heptadecanoic Acids: Multifaceted Odd-Chain Fatty Acids. Adv. Nutr. 7, 730–734 (2016 ).
Not in our library10.3945/an.115.011387
33.
A Review of Odd-Chain Fatty Acid Metabolism and the Role of Pentadecanoic Acid (C15:0) and Heptadecanoic Acid (C17:0) in Health and Disease · 2015
No notice
34.
Associations between the human intestinal microbiota, Lactobacillus rhamnosus GG and serum lipids indicated by integrated analysis of high-throughput profiling data · 2013
No notice
35.
Fu J.. The Gut Microbiome Contributes to a Substantial Proportion of the Variation in Blood Lipids. Circ. Res. 117, 817–824 (2015 ).
Not in our library10.1161/circresaha.115.306807
36.
Wang-Sattler R.. Novel biomarkers for pre-diabetes identified by metabolomics. Mol. Syst. Biol. 8, 615 (2012 ).
Not in our library10.1038/msb.2012.43
37.
Walford G. A.. Metabolite traits and genetic risk provide complementary information for the prediction of future type 2 diabetes. Diabetes Care 37, 2508–2514 (2014 ).
Not in our library10.2337/dc14-0560
38.
Wittenbecher C.. Amino acids, lipid metabolites, and ferritin as potential mediators linking red meat consumption to type 2 diabetes. Am. J. Clin. Nutr. 101, 1241–1250 (2015 ).
Not in our library10.3945/ajcn.114.099150
39.
Wurtz P.. Circulating metabolite predictors of glycemia in middle-aged men and women. Diabetes Care 35, 1749–1756 (2012 ).
Not in our library10.2337/dc11-1838
40.
Wurtz P.. Branched-chain and aromatic amino acids are predictors of insulin resistance in young adults. Diabetes Care 36, 648–655 (2013 ).
Not in our library10.2337/dc12-0895
41.
Xu F.. Metabolic signature shift in type 2 diabetes mellitus revealed by mass spectrometry-based metabolomics. J. Clin. Endocrinol. Metab. 98, E1060–5 (2013 ).
Not in our library10.1210/jc.2012-4132
42.
Sonne D. P., Hansen M. & Knop F. K. Bile acid sequestrants in type 2 diabetes: potential effects on GLP1 secretion. Eur. J. Endocrinol. 171, R47–65 (2014 ).
Not in our library10.1530/eje-14-0154
43.
Hansen M., Sonne D. P. & Knop F. K. Bile acid sequestrants: glucose-lowering mechanisms and efficacy in type 2 diabetes. Curr. Diab Rep. 14, 482-014-0482-4 (2014 ).
Not in our library10.1007/s11892-014-0482-4
44.
Bile diversion to the distal small intestine has comparable metabolic benefits to bariatric surgery · 2015
No notice
45.
Ridlon J. M., Kang D. J., Hylemon P. B. & Bajaj J. S. Bile acids and the gut microbiome. Curr. Opin. Gastroenterol. 30, 332–338 (2014 ).
Not in our library10.1097/mog.0000000000000057
46.
Venkatesh M.. Symbiotic bacterial metabolites regulate gastrointestinal barrier function via the xenobiotic sensor PXR and Toll-like receptor 4. Immunity 41, 296–310 (2014 ).
Not in our library10.1016/j.immuni.2014.06.014
47.
Cani P. D., Osto M., Geurts L. & Everard A. Involvement of gut microbiota in the development of low-grade inflammation and type 2 diabetes associated with obesity. Gut Microbes 3, 279–288 (2012 ).
Not in our library10.4161/gmic.19625
48.
Tuomilehto J.. Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance. N. Engl. J. Med. 344, 1343–1350 (2001 ).
Not in our library10.1056/nejm200105033441801
49.
Wierzbicka R., Wu H., Franek M., Kamal-Eldin A. & Landberg R. Determination of alkylresorcinols and their metabolites in biological samples by gas chromatography-mass spectrometry. J. Chromatogr. B. Analyt Technol. Biomed. Life. Sci. 1000, 120–129 (2015 ).
Not in our library10.1016/j.jchromb.2015.07.009
50.
Stancáková A.. Changes in insulin sensitivity and insulin release in relation to glycemia and glucose tolerance in 6,414 Finnish men. Diabetes 58, 1212–1221 (2009 ).
Not in our library10.2337/db08-1607
51.
de Mello V. D.. Markers of cholesterol metabolism as biomarkers in predicting diabetes in the Finnish Diabetes Prevention Study. Nutr. Metab. Cardiovasc. Dis. 25, 635–642 (2015 ).
Not in our library10.1016/j.numecd.2015.03.012
52.
Smith C. A., Want E. J., O’Maille G., Abagyan R. & Siuzdak G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem. 78, 779–787 (2006 ).
Not in our library10.1021/ac051437y
53.
Large-scale untargeted LC-MS metabolomics data correction using between-batch feature alignment and cluster-based within-batch signal intensity drift correction · 2016
No notice
54.
Willett W. C. In Monographs in Epidemiology and Biostatistics; Nutritional Epidemiology(eds Kelsey J. L., Marmot M. C., Stolley P. D. & Vessey M. P. ) 1–514 (Oxford University PressWillett, W.C, Oxford, 1998 ).
Not in our library

Cited by papers we hold 19

Dietary fibre directs microbial tryptophan metabolism via metabolic interactions in the gut microbiota · 2024
No notice
Gut microbiota: A new target for T2DM prevention and treatment · 2022
No notice
Dual Role of Indoles Derived From Intestinal Microbiota on Human Health · 2022
No notice
Gut Microbiota-Derived Tryptophan Metabolites Maintain Gut and Systemic Homeostasis · 2022
No notice
Biological Effects of Indole-3-Propionic Acid, a Gut Microbiota-Derived Metabolite, and Its Precursor Tryptophan in Mammals’ Health and Disease · 2022
No notice
Extensive Summary of the Important Roles of Indole Propionic Acid, a Gut Microbial Metabolite in Host Health and Disease · 2022
No notice
Serum metabolite profiling yields insights into health promoting effect of A. muciniphila in human volunteers with a metabolic syndrome · 2021
Not checked
New Insights Into Gut-Bacteria-Derived Indole and Its Derivatives in Intestinal and Liver Diseases · 2021
No notice
Gut microbiota influence in type 2 diabetes mellitus (T2DM) · 2021
No notice
Gut microbiome variation modulates the effects of dietary fiber on host metabolism · 2021
No notice
The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health · 2021
No notice
“Notame”: Workflow for Non-Targeted LC–MS Metabolic Profiling · 2020
No notice
Role of Gut Microbiota on Onset and Progression of Microvascular Complications of Type 2 Diabetes (T2DM) · 2020
No notice
Random forest-based imputation outperforms other methods for imputing LC-MS metabolomics data: a comparative study · 2019
No notice
Indole-3-propionic acid inhibits gut dysbiosis and endotoxin leakage to attenuate steatohepatitis in rats · 2019
No notice
Associations of serum indolepropionic acid, a gut microbiota metabolite, with type 2 diabetes and low-grade inflammation in high-risk individuals · 2018
No notice
Implication of gut microbiota metabolites in cardiovascular and metabolic diseases · 2018
No notice
Gut microbial diversity is associated with lower arterial stiffness in women · 2018
No notice
Microbial tryptophan catabolites in health and disease · 2018
No notice

Reads

Read by people on this page

None yet.

Checked or read by AI through naulon

None yet.

A person counts once a day per paper. We keep no cookie and no address: a reader is a hash that changes every day. Any month under five reads shows no number.

Are you an author?

Is this your paper?

Claim it to add your note and be paid when agents cite it. Free.