Multiple pathophysiological biomarkers showed associations with incident type 2 diabetes across subtypes, but did not reliably distinguish subtype classification at diagnosis. This prospective cohort analysis, published in Diabetes Care, evaluated 69,725 observations from 9,661 adults without diabetes across four U.S. cohorts, with a median follow-up of 10 years (range 0-17 years). 

Time-dependent Cox models were used to estimate cause-specific hazard ratios (HRs) for seven biomarkers, including body mass index (BMI), systolic blood pressure (SBP), glycated hemoglobin (HbA1c), low-density lipoprotein (LDL) cholesterol, homeostatic model assessment indices for β-cell function (HOMA2-%B) and insulin resistance (HOMA2-IR), and estimated glomerular filtration rate (eGFR), adjusting for demographic and clinical factors.

During follow-up, 1,569 individuals developed type 2 diabetes. Higher BMI (HR 1.03; 95% CI 1.02-1.04), SBP (HR 1.09; 95% CI 1.05-1.13), HbA1c (HR 2.46; 95% CI 1.73-3.52), HOMA2-IR (HR 1.92; 95% CI 1.78-2.07), and LDL cholesterol (HR 1.02; 95% CI 1.00-1.04) were associated with increased risk, while higher HOMA2-%B was associated with lower risk (HR 0.89; 95% CI 0.87-0.91). eGFR was not associated (HR 1.02; 95% CI 0.98-1.07).

Associations were similar across diabetes subtypes. Models based on single time-point measurements showed high discrimination (C-index 0.81-0.90) but modest classification performance (F1 score 0.26-0.51) with variable calibration (slope 0.22-1.24), indicating limited ability to distinguish subtypes prior to diagnosis.