Sleep-time BP: prognostic marker of type 2 diabetes and therapeutic target for prevention

Abstract

Aims/hypothesis We investigated the prognostic value of clinic and ambulatory BP (ABP) to predict new-onset diabetes and whether risk reduction is related to the progressive decrease of clinic BP or awake or asleep ABP. Methods We prospectively evaluated 2,656 individuals without diabetes, 1,292 men and 1,364 women, 50.6±14.3 years of age, with baseline BP ranging from normotension to hypertension according to ABP criteria. At baseline and annually (more frequently if hypertension treatment was adjusted based on ABP) thereafter, ABP and physical activity (wrist actigraphy) were simultaneously monitored for 48 h to accurately derive the awake and asleep BP means. Results During a 5.9-year median follow-up, 190 participants developed type 2 diabetes. The asleep systolic ABP mean was the most significant predictor of new-onset diabetes in a Cox proportional-hazard model adjusted for age, waist circumference, glucose, chronic kidney disease (CKD) and hypertension treatment. Daytime clinic BP and awake or 48 h ABP mean had no predictive value when corrected by the asleep ABP mean. Analyses of BP changes during follow-up revealed a 30% reduction in the risk of new-onset diabetes per 1-SD decrease in asleep systolic ABP mean, independent of changes in clinic BP or awake or 48 h ABP means.Conclusions/interpretation Sleep-time BP is a highly significant independent prognostic marker for new-onset diabetes. Alteration in sleep-time BP regulation seems to precede, rather than follow, the development of new-onset diabetes. Most important, lowering asleep BP, a novel therapeutic target requiring ABP evaluation, could be a significant method for reducing new-onset diabetes risk.

Elevated asleep BP as predictor of type 2 diabetes and therapeutic target for prevention

“…The QDiabetes score, however, does not incorporate fasting plasma glucose concentration or asleep BP mean, which we found to be the two most significant independent prognostic markers of risk for diabetes [2]. Our results document that waist circumference is of significant predictive value for diabetes, whereas BMI (used in QDiabetes only if known) is not.…”

“…Hence, HbA 1c is not a requirement for the diagnosis of diabetes, and the fact that it was not used as a diagnostic tool in our studies should not be considered to be a valid limitation. Point 3 Our first manuscript does not claim causality, but documents an association between elevated asleep SBP mean and increased risk of diabetes [2]. Most important, Dr Rutter in his commentary does not refer to the potentially most relevant finding of the MAPEC trial: that, in addition to the firstdocumented prognostic value of high asleep BP mean, repeated (at least annual) round-the-clock ABPM patient evaluation enabled identification of treatment-induced lowering of asleep SBP mean during follow-up as the most significant marker of reduced risk for future development of diabetes.…”

“…In cases of discordant test results, diagnosis should rely on the single positive test after confirmation by repeated evaluation. Although our study used only fasting glucose for diagnosis, the diagnosis was consistently validated by repeat measurements at clinical assessments ≥3 months apart [2,3]. These same guidelines also emphasise the lower sensitivity of HbA 1c than fasting glucose for diagnosis, as HbA 1c identifies onethird fewer cases of undiagnosed diabetes than elevated fasting glucose [6].…”

“…Point 4 Our first manuscript [2] clearly states: 'All demographic, anthropometric and clinical laboratory variables listed in Table 1 were tested as potential confounding variables. Adjustments were applied for fasting glucose, waist circumference, age, hypertension treatment-time and chronic kidney disease (CKD) diagnosis, as these influential factors were the only ones consistently significant in all tested Cox regression models.'…”

“…Although new-onset diabetes was not a pre-specified endpoint in the published trial design [7,8], the MAPEC study was indeed designed to investigate multiple hypotheses [2,3] associated with multiple risk assessment, including total cardiovascular disease (CVD) morbidity and mortality, major CVD events (composite of CVD death, myocardial infarction, and ischaemic and haemorrhagic stroke) [9,10], new-onset diabetes, and new-onset and progression of CKD. Randomisation of hypertensive participants to treatment-time (awakening or bedtime) was carried out separately for each allowed hypertension medication, as well as according to sex (male/female), diabetes (present/absent), CKD (present/ absent) and baseline ambulatory BP pattern (dipper/nondipper) to ensure balance of these potentially influential factors between treatment-time groups.…”