Similar HbA1c, Similar BMI, Different disease: The Adipo-B Index Reveals Hidden Metabolic Heterogeneity in Newly Diagnosed Japanese Subjects with Type 2 Diabetes

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Abstract

Objective

Patients and physicians frequently focus on HbA1c and weight alone. We hypothesized that individuals with similar HbA1c and BMI may present markedly distinct metabolic backgrounds. We investigated whether the adipo-B index- composite of adipose insulin resistance (adipo-IR) and beta-cell function (HOMA-B)-can uncover hidden heterogeneity in this clinically “homogeneous” population.

Methods

A total of 399 newly diagnosed, drug-naïve Japanese subjects with T2DM were analyzed. Histograms of HbA1c and BMI demonstrated peak distributions within HbA1c 8-10% and BMI 24-26 kg/m 2 . Based on these distributions, a clinically homogeneous subgroup was defined to minimize confounding by glycemic severity and adiposity. Metabolic parameters including FBG, insulin, FFA, HOMA-R, HOMA-B, adipo-IR, adipo-B, T-C, TG, HDL-C and non-HDL-C were analyzed. Simple regression, multivariable linear regression, and subgroup stratification analyses were performed.

Results

Despite comparable HbA1c and BMI by design, adipo-B stratification revealed significant differences in HOMA-B, FFA, non-HDL-C, and TG, whereas HOMA-R stratification identified only higher insulin and adipo-IR without differences in lipids or HOMA-B. Thus, adipo-B-but not HOMA-R-identified a lipotoxic, beta-cell-stressed phenotype invisible to conventional markers. Simple regression showed significant positive correlations between adipo-B and HbA1c, FBG, FFA, T-C, TG, and non-HDL-C, and negative correlations with insulin and HOMA-B. Multivariable linear regression confirmed that adipo-B was independently associated with non-HDL cholesterol, TG, and FFA after adjustment for HbA1c and BMI.

Conclusion

Even among patients with identical HbA1c and BMI, the adipo-B index uncovers clinically relevant metabolic heterogeneity, supporting its role as a functional marker of the adipose-pancreas axis and a potential tool for precision phenotyping in early T2DM.

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