BackgroundIn the ACCORD study, participants with the haptoglobin (Hp) 2–2 phenotype and glycated hemoglobin (HbA1c) ≥ 8.0% had a higher risk of coronary artery disease (CAD) compared to those with HbA1c 7.0–7.9%. However, this association was not observed in participants without the Hp2-2 phenotype. The optimal glycemic target for CAD prevention for the Hp phenotypes remains uncertain and may vary based on demographic and clinical factors.ObjectiveTo investigate how reaching clinically relevant HbA1c targets relates to the risk of CAD in different Hp phenotype groups among a diverse cohort of individuals with T2DM (the Look AHEAD study, HbA1c ≤ 11% at baseline).MethodsCox regression models with time-varying covariables were used to quantify the association between time-varying achieved HbA1c (< 6.5%, 6.5–6.9%, and ≥ 8.0% compared to 7.0-7.9%), updated at years 1–4, 6, 8, and 10, and incident CAD in the Hp2-2 (n = 1,587) and non-Hp2-2 (n = 2,944) phenotypes separately. Further pre-specified subgroup analyses by age, sex, history of cardiovascular disease (CVD), race, and diabetes duration were performed in each Hp phenotype group separately.ResultsCompared with HbA1c 7.0-7.9%, having HbA1c < 6.5% was associated with a 29% lower CAD risk among participants with the non-Hp2-2 phenotype (adjusted HR 0.71, 95% CI 0.55–0.90). In subgroup analyses, this association was present in participants with the non-Hp2-2 phenotype who were male (0.60, 0.44–0.83), who did not have a history of CVD (0.65, 0.47–0.90), who were aged ≥ 65 years (0.64, 0.44–0.94), who were White (0.68, 0.51–0.91), or who had diabetes duration > 10 years (0.58, 0.35–0.95). HbA1c ≥ 8.0% was associated with CAD risk only among participants with the Hp2-2 phenotype who had a history of CVD (1.79, 1.00-3.20). No associations were found between the other HbA1c targets and CAD risk when participants with the Hp2-2 phenotype were grouped together or divided into subgroups.ConclusionThe differences in our results compared to our previous findings may be due to variations in the study populations and factors associated with weight loss, making it difficult to draw definitive conclusions. Our current findings should be considered in the context of hypothesis generation, and ideally, will encourage additional research in this field.
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