Novel Metabolic Markers for the Risk of Diabetes Development in American Indians

Abstract

OBJECTIVETo identify novel metabolic markers for diabetes development in American Indians.RESEARCH DESIGN AND METHODSUsing an untargeted high-resolution liquid chromatography–mass spectrometry, we conducted metabolomics analysis of study participants who developed incident diabetes (n = 133) and those who did not (n = 298) from 2,117 normoglycemic American Indians followed for an average of 5.5 years in the Strong Heart Family Study. Relative abundances of metabolites were quantified in baseline fasting plasma of all 431 participants. Prospective association of each metabolite with risk of developing type 2 diabetes (T2D) was examined using logistic regression adjusting for established diabetes risk factors.RESULTSSeven metabolites (five known and two unknown) significantly predict the risk of T2D. Notably, one metabolite matching 2-hydroxybiphenyl was significantly associated with an increased risk of diabetes, whereas four metabolites matching PC (22:6/20:4), (3S)-7-hydroxy-2′,3′,4′,5′,8-pentamethoxyisoflavan, or tetrapeptides were significantly associated with decreased risk of diabetes. A multimarker score comprising all seven metabolites significantly improved risk prediction beyond established diabetes risk factors including BMI, fasting glucose, and insulin resistance.CONCLUSIONSThe findings suggest that these newly detected metabolites may represent novel prognostic markers of T2D in American Indians, a group suffering from a disproportionately high rate of T2D.

Metabolomics in Prediabetes and Diabetes: A Systematic Review and Meta-analysis

“…Therefore, according to our prespecified criterion of at least three estimates for a given metabolite required for conducting meta-analysis, it was not feasible to meta-analyze any of the lipid metabolites. The great majority of the studies analyzing lipid metabolites applied targeted approaches, except for two that were untargeted (51,52). On average, 40–50 lipid metabolites were targeted.…”

Integrative Analysis of Multi-omics Data for Discovery and Functional Studies of Complex Human Diseases

“…Li et al, 2013). Using the untargeted approach, recent studies are able to assess the global metabolomic profile involving over 20,000 metabolomic features from many metabolic pathways in human samples (Zhao et al, 2015). The untargeted HRM has demonstrated its unique contribution to understanding fundamental biological processes of human diseases, and identification of uncharacterized chemicals linked to human health and disease (Baker, 2011).…”

“…metabolome-wide association studies) now possible, as a powerful way to investigate complex biological questions (Jones et al, 2012; Kaddurah-Daouk et al, 2008; Patti et al, 2012). Using an untargeted HRM approach, Zhao et al identified five known and two unknown metabolites significantly predict the incidence of type 2 diabetes (T2D) among 2,117 normoglycemic American Indians followed for an average of 5.5 years (Zhao et al, 2015). A multi-metabolite score significantly improved risk prediction beyond established diabetes risk factors.…”

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

“…For example, in a study using PCA of a targeted metabolomics panel, T2D prediction improved by ~ 5% when metabolites were added beyond conventional risk factors and lifestyle characteristics [70•]. Seven metabolites (five known and two unknown) also significantly predict the risk of T2D when added to a multi-marker score beyond established T2D risk factors including BMI, fasting glucose, and IR (AUC RFs = 0.76 vs. AUC RFs + Met = 0.82) [69]. In a different study aimed at investigating whether acylcarnitines improved T2D risk prediction, authors showed that the AUC improved to 0.89 in the full model compared with 0.73 in the conventional model after selecting relevant acylcarnitines using penalized regression models.…”