Latent class growth mixture modeling of HbA1C trajectories identifies individuals at high risk of developing complications of type 2 diabetes mellitus in the UK Biobank.

Dale Handley, Alexandra C Gillett, Renu Bala, Jessica Tyrrell, Cathryn M Lewis

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Article in BMJ open diabetes research & care, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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4 citing papers in PubMed.

Joint trajectories of adiposity and systemic inflammation and incident diabetes among older adults: a bi-cohort prospective study with mediation analysis.Frontiers in nutrition · 2026
Article
Baseline RDW combined with dynamic trajectory: Predictive value for 30-day all-cause mortality in patients with sepsis-induced coagulopathy and development of a nomogram.PloS one · 2026
Article
A non-invasive predictive model for identifying non-diabetic kidney disease in type 2 diabetes mellitus: development and multicenter validation.American journal of clinical and experimental urology · 2026
Article
Dynamic Hemoglobin Trajectories in Renal Anemia and Their Association with Frailty Progression and Cardiovascular Events in Non-Dialysis Chronic Kidney Disease.Mediterranean journal of hematology and infectious diseases · 2026
Article

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Dale Handley *NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK dale.handley@kcl.ac.uk.ORCID http://orcid.org/0009-0008-0944-1634

Alexandra C Gillett *NIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.

Renu BalaClinical and Biomedical Science, Institute of Health and Life Sciences, University of Exeter, Exeter, UK.

Jessica TyrrellClinical and Biomedical Science, Institute of Health and Life Sciences, University of Exeter, Exeter, UK.

Cathryn M LewisNIHR Maudsley Biomedical Research Centre, South London and Maudsley NHS Foundation Trust, London, UK.

Funding

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6 · The paper itself

Abstract

introductionFrequent glycated hemoglobin A1c (HbA1c) monitoring is recommended in individuals with type 2 diabetes mellitus (T2D). We aimed to identify distinct, long-term HbA1c trajectories following a T2D diagnosis and investigate how these glycemic control trajectories were associated with health-related traits and T2D complications. RESEARCH DESIGN AND

methodsA cohort of 12,435 unrelated individuals of European ancestry with T2D was extracted from the UK Biobank data linked to primary care records. Latent class growth mixture modeling was applied to identify classes with similar HbA1c trajectories over the 10 years following T2D diagnosis. Associations between HbA1c class membership and sociodemographic factors, biomarkers, polygenic scores, and T2D-related outcomes, were tested using logistic regression and Cox proportional hazards models.

resultsSix HbA1c trajectory classes were identified. The largest class (76.8%) maintained low and stable HbA1c levels over time. Five additional smaller classes with distinct, but more variable, trajectories were found and were associated with younger age at T2D diagnosis, higher fasting glucose levels, higher random glucose levels, higher body mass index polygenic score and increased healthcare use before T2D diagnosis. Relative to the low and stable class, these five showed increased risks of T2D complications, including stroke (HR=1.55 (1.31-1.84)), kidney disease (HR=1.39 (1.27-1.53)), all-cause mortality (HR=1.36 (1.23-1.51)), and progression to combination therapy (HR=3.22 (3.04-3.41)) or insulin (HR=3.21 (2.89-3.55)).

conclusionIndividuals with T2D who show higher and more variable HbA1c trajectories are at increased risk of developing T2D-related complications. Early identification of patients at risk, based on factors such as age at diagnosis and previous healthcare utilization could improve patient outcomes.

Indexed as

BiomarkersDiabetes ComplicationsDiabetes Mellitus, Type 2Glycated HemoglobinAgedBiological Specimen BanksBlood GlucoseFemaleFollow-Up StudiesHumansLatent Class AnalysisMaleMiddle AgedPrognosisRisk FactorsUK BiobankBiomarkersBlood GlucoseGlycated Hemoglobinhemoglobin A1c protein, humanClassificationDepressionDiabetes Mellitus, Type 2HbA1c

Identifiers

PMID40921490

DOI10.1136/bmjdrc-2024-004826

PMCPMC12421182

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