{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,18]],"date-time":"2026-06-18T16:56:31Z","timestamp":1781801791285,"version":"3.54.5"},"reference-count":40,"publisher":"American Diabetes Association","issue":"4","license":[{"start":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T00:00:00Z","timestamp":1770336000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.diabetesjournals.org\/journals\/pages\/license"}],"content-domain":{"domain":["diabetesjournals.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2026,4,1]]},"abstract":"<jats:sec>\n                    <jats:title>OBJECTIVE<\/jats:title>\n                    <jats:p>Understanding the pathophysiology of type 2 diabetes subtypes (severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes, and mild age-related diabetes) before diagnosis can enable precision prevention. We estimated the associations of seven biomarkers with type 2 diabetes subtypes prior to diagnosis.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESEARCH DESIGN AND METHODS<\/jats:title>\n                    <jats:p>We analyzed 69,725 observations from 9,661 adults without diabetes (median follow-up 10 years [range 0\u201317 years]) from four U.S. cohorts. Time-dependent Cox models estimated cause-specific hazard ratios (HRs) of seven pathophysiological biomarkers (BMI [kg\/m2], systolic blood pressure [SBP] [per 10 mmHg], HbA1c [%], LDL cholesterol [per 10 mg\/dL], homeostatic indices [HOMA2 of \u03b2-cell function (HOMA2-%B) (per 10 units) and HOMA2 of insulin resistance (HOMA2-IR)], and estimated glomerular filtration rate [eGFR] [per 10 mL\/min\/1.73 m2]) with incidence of type 2 diabetes and subtypes, adjusting for demographic and clinical covariates. Model performance was evaluated using participants\u2019 first and random visits before last follow-up.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>RESULTS<\/jats:title>\n                    <jats:p>Of the pooled cohort, 1,569 individuals developed type 2 diabetes. 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-%B (HR 0.89 [95% CI 0.87, 0.91]), HOMA2-IR (HR 1.92 [95% CI 1.78, 2.07]), and LDL cholesterol (HR 1.02 [95% CI 1.00, 1.04]), but not eGFR (HR 1.02 [95% CI 0.98, 1.07]), were independently associated with diabetes. Associations were similar across subtypes. Models based on single time points demonstrated a high C-index (0.81\u20130.90) but modest F1 scores (0.26\u20130.51) and varying sensitivity and calibration (slope 0.22\u20131.24).<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>CONCLUSIONS<\/jats:title>\n                    <jats:p>Pathophysiological biomarkers were prospectively associated with type 2 diabetes and subtypes, but single-time-point measurements before diagnosis could not reliably distinguish subtypes at diagnosis.<\/jats:p>\n                  <\/jats:sec>","DOI":"10.2337\/dc25-2069","type":"journal-article","created":{"date-parts":[[2026,2,6]],"date-time":"2026-02-06T14:41:06Z","timestamp":1770388866000},"page":"616-624","update-policy":"https:\/\/doi.org\/10.2337\/ada-journal-policies","source":"Crossref","is-referenced-by-count":0,"title":["Pathophysiological Risk Factors Preceding Incidence of Type 2 Diabetes Subtypes: A Pooled Cohort Study in the United States"],"prefix":"10.2337","volume":"49","author":[{"given":"Jiali","family":"Guo","sequence":"first","affiliation":[{"name":"Emory Global Diabetes Research Center of Woodruff Health Sciences Center, Emory University 1 , Atlanta, GA"},{"name":"Hubert Department of Global Health, Rollins School of Public Health, Emory University 2 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Zhongyu","family":"Li","sequence":"additional","affiliation":[{"name":"Nutrition and Health Sciences Doctoral Program, Laney Graduate School, Emory University 3 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Shivani A.","family":"Patel","sequence":"additional","affiliation":[{"name":"Emory Global Diabetes Research Center of Woodruff Health Sciences Center, Emory University 1 , Atlanta, GA"},{"name":"Hubert Department of Global Health, Rollins School of Public Health, Emory University 2 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Howard H.","family":"Chang","sequence":"additional","affiliation":[{"name":"Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University 4 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Mohammed K.","family":"Ali","sequence":"additional","affiliation":[{"name":"Emory Global Diabetes Research Center of Woodruff Health Sciences Center, Emory University 1 , Atlanta, GA"},{"name":"Hubert Department of Global Health, Rollins School of Public Health, Emory University 2 , Atlanta, GA"},{"name":"Department of Preventive and Family Medicine, School of Medicine, Emory University 5 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3825-9897","authenticated-orcid":false,"given":"Jithin Sam","family":"Varghese","sequence":"additional","affiliation":[{"name":"Emory Global Diabetes Research Center of Woodruff Health Sciences Center, Emory University 1 , Atlanta, GA"},{"name":"Hubert Department of Global Health, Rollins School of Public Health, Emory University 2 , Atlanta, GA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1167","published-online":{"date-parts":[[2026,2,6]]},"reference":[{"key":"2026061812274079300_B1","doi-asserted-by":"crossref","first-page":"S20","DOI":"10.2337\/dc24-S002","article-title":"2. 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