See also Linking To And Embedding Metabolic Mind’s ”New Study Using CGMs Reveals Surprising Truth About Your Blood Sugar”
Posted on October 8, 2025 by Tom Wade MD. This is a video of the Nature Medicine article below.
Today, I review, link to, and excerpt from Nature Medicine’s Individual variations in glycemic responses to carbohydrates and underlying metabolic physiology [PubMed Abstract] [Full-Text HTML] [Full-Text PDF]. Nat Med. 2025 Jul;31(7):2232-2243. doi: 10.1038/s41591-025-03719-2. Epub 2025 Jun 4.
All that follows is from the above resource.
Abstract
Elevated postprandial glycemic responses (PPGRs) are associated with type 2 diabetes and cardiovascular disease. PPGRs to the same foods have been shown to vary between individuals, but systematic characterization of the underlying physiologic and molecular basis is lacking. We measured PPGRs using continuous glucose monitoring in 55 well-phenotyped participants challenged with seven different standard carbohydrate meals administered in replicate. We also examined whether preloading a rice meal with fiber, protein or fat (‘mitigators’) altered PPGRs. We performed gold-standard metabolic tests and multi-omics profiling to examine the physiologic and molecular basis for interindividual PPGR differences. Overall, rice was the most glucose-elevating carbohydrate meal, but there was considerable interindividual variability. Individuals with the highest PPGR to potatoes (potato-spikers) were more insulin resistant and had lower beta cell function, whereas grape-spikers were more insulin sensitive. Rice-spikers were more likely to be Asian individuals, and bread-spikers had higher blood pressure. Mitigators were less effective in reducing PPGRs in insulin-resistant as compared to insulin-sensitive participants. Multi-omics signatures of PPGR and metabolic phenotypes were discovered, including insulin-resistance-associated triglycerides, hypertension-associated metabolites and PPGR-associated microbiome pathways. These results demonstrate interindividual variability in PPGRs to carbohydrate meals and mitigators and their association with metabolic and molecular profiles.
© 2025. The Author(s).
Conflict of interest statement
Competing interests: M.P.S. is a cofounder, scientific advisor and shareholder of Filtricine, Iollo, January AI, Marble Therapeutics, Next Thought AI, Personalis, Protos Biologics, Qbio, RTHM, SensOmics. M.P.S. is a scientific advisor and equity holder of Abbratech, Applied Cognition, Enovone, M3 Helium, Onza. M.P.S. is a scientific advisor and stock option holder of Jupiter Therapeutics, Mitrix, Neuvivo, Sigil Biosciences, WndrHLTH, Yuvan Research. M.P.S. is a cofounder and stock option holder of Crosshair Therapeutics. M.P.S. is an investor in and scientific advisor of R42 and Swaza. M.P.S. is an investor in Repair Biotechnologies. M.P.S. is a cofounder, shareholder and director of Exposomics, Fodsel, InVu Health. M.P.S. is a cofounder and equity holder of Mirvie, NiMo Therapeutics, Orange Street Ventures. A.A.M. is currently an employee of Google. D.P. and T.M. are members of the scientific advisory board of January AI. The other authors declare no competing interests.
Deep phenotyping of responses to carbohydrate meals and mitigators revealed interindividual differences in postprandial glycemic responses that reflect underlying metabolic physiology, such as insulin resistance and beta cell dysfunction.
Main
One in three adults in the United States has prediabetes, and 70% of these will develop type 2 diabetes (T2D), posing a substantial public health burden1 via complications such as kidney disease, vision loss, neuropathy, cardiovascular disease (CVD) and cancer2–6.
High postprandial glycemic responses (PPGRs) are a hallmark of prediabetes and T2D and are risk factors for T2D, CVD and all-cause mortality independent of fasting blood glucose (FBG) and HbA1c7–9. However, our understanding of glucose dysregulation, especially regarding PPGRs, remains incomplete. Interindividual variability in PPGRs to the same foods has been described7,10. A variety of factors have been identified as contributors to PPGRs, including glycemic index, the total carbohydrate amount, carbohydrate characteristics (starch and simple carbohydrates), food processing, meal macronutrient composition, meal timing, ethnicity and the microbiome11–16. However, the contribution of individual physiologic and metabolic factors to PPGRs and whether they interact with food characteristics have not been well studied.
A gap in understanding how underlying metabolism and physiology affect PPGRs exists largely because quantifying metabolic functions, such as insulin resistance, insulin secretion and the incretin effect, is laborious and costly and has not been extensively employed. However, these metabolic traits differ between individuals17–19 and likely explain, in part, the observed interindividual PPGR differences. Glycemic responses to the oral glucose tolerance test have been linked to underlying physiology such as insulin resistance and beta cell dysfunction19. Prespecified timed blood draws may miss the peak glucose, but continuous glucose monitoring (CGM) devices enable a detailed evaluation of PPGRs and can be linked to individual metabolic traits. Indeed, using CGM, we previously showed that individuals with higher and more variable daily glucose excursions were more insulin resistant (IR) than their lower-glycemic counterparts10. Thus, CGMs have the potential to link underlying metabolic phenotypes to individual responses to food.
To further study individual PPGRs to foods and their association with metabolic subtypes and omics profiles, we conducted a rigorous investigation of responses to a wide variety of standardized carbohydrate meals and standardized preloads (‘mitigators’) to a rice meal in individuals whose metabolic traits were comprehensively profiled with gold-standard tests and whose blood and stool were profiled for metabolites, lipids, proteins and microbiome. We hypothesized that individual PPGRs are associated with the underlying metabolic physiology (for example, insulin resistance and beta cell dysfunction) as well as molecular markers.
