Vascular phenotypes in early hypertension

Abstract

The study characterises vascular phenotypes of hypertensive patients utilising machine learning approaches. Newly diagnosed and treatment-naïve primary hypertensive patients without co-morbidities (aged 18-55, n = 73), and matched normotensive controls (n = 79) were recruited (NCT04015635). Blood pressure (BP) and BP variability were determined using 24 h ambulatory monitoring. Vascular phenotyping included SphygmoCor® measurement of pulse wave velocity (PWV), pulse wave analysis-derived augmentation index (PWA-AIx), and central BP; EndoPAT™-2000® provided reactive hyperaemia index (LnRHI) and augmentation index adjusted to heart rate of 75bpm. Ultrasound was used to analyse flow mediated dilatation and carotid intima-media thickness (CIMT). In addition to standard statistical methods to compare normotensive and hypertensive groups, machine learning techniques including biclustering explored hypertensive phenotypic subgroups. We report that arterial stiffness (PWV, PWA-AIx, EndoPAT-2000-derived AI@75) and central pressures were greater in incident hypertension than normotension. Endothelial function, percent nocturnal dip, and CIMT did not differ between groups. The vascular phenotype of white-coat hypertension imitated sustained hypertension with elevated arterial stiffness and central pressure; masked hypertension demonstrating values similar to normotension. Machine learning revealed three distinct hypertension clusters, representing 'arterially stiffened', 'vaso-protected', and 'non-dipper' patients. Key clustering features were nocturnal- and central-BP, percent dipping, and arterial stiffness measures. We conclude that untreated patients with primary hypertension demonstrate early arterial stiffening rather than endothelial dysfunction or CIMT alterations. Phenotypic heterogeneity in nocturnal and central BP, percent dipping, and arterial stiffness observed early in the course of disease may have implications for risk stratification.

Fig. 1. Correlation matrix of Cardiovascular and blood pressure parameters.

All studied participants (Panel A), and separately by normotension and hypertension groups (Panels B and C). Colour and colour intensity indicate r values i.e., direction and strength of correlation (red negative correlation, blue positive), as per X axis. *P < 0.05 **P < 0.01 ***P < 0.001. BMI body mass index; CIMT carotid intima media thickness, DBP diastolic blood pressure, SD standard deviation, DCP diastolic central pressure, AI@75% AIx adjusted for heart rate, FMD% percent flow-mediated dilatation, HR heart rate, IDQ interheart diet score, IPAQ International Physical Activity Questionnaire, LnRHI logarithmic transformation of reactive hyperaemia index, PWV pulse wave velocity, PWA pulse wave analysis, AIx augmentation index, SBP systolic blood pressure, SCP systolic central pressure.

Fig. 2. Cluster analyses of the hypertensive group.

Spectral Biclustering with three subgroups of patients and eight groups of features (Panel A). Boxplots of key features discriminating bicluster groups (Panel B). Both panels: Group 0 ‘arterially stiffened’ hypertension, Group 1 ‘vasoprotected’ hypertension, Group 2 ‘non-dippers’. SBP24, 24 h average systolic BP; DBP24, 24 h average diastolic BP; SBP SD standard deviation i.e., variability of systolic BP; DBP SD, standard deviation i.e., variability of diastolic BP; FMD flow mediated dilatation, BMI body-mass index, dip percentage reduction from day to night BP, LnRHI logarithmic reactive hyperaemia index, AIx EndoPAT-2000-derived augmentation index, AI@75% AIx adjusted for heart rate, HR range day daytime heart rate range, PWV pulse wave velocity, PWA pulse wave analysis, SCP systolic central pressure, DCP diastolic central pressure.