Effect of Age and Body Composition on Beat‐to‐Beat Blood Pressure Dynamics in Pre‐diabetic Rats
Authors: Fares Souha , Bakkar Nour , Yazbi Ahmed 
Published: April 2020

ObjectivesAutonomic hemodynamic regulation exhibits non‐linear patterns of complexity. Our previous work showed that low‐grade perivascular adipose tissue inflammation in prediabetic rats was associated with reduced heart rate variability as one of the manifestations of cardiac autonomic neuropathy. Similar to heart rate, blood pressure normally exhibits substantial short‐ and long‐term variability (BPV). These variability patterns are often considered a positive indicator of cardiovascular health. Here, we assessed the association between age and body composition in prediabetic rats; and beat‐to‐beat BPV indices including correlation properties (detrended fluctuation analysis scale coefficient α) and complexity (Approximate Entropy; ApEn).MethodsWe studied BPV based on a five‐minute time‐series of invasive BP recordings in 3 main groups of Sprague Dawley rats ages and body composition. These groups are: (1) young (16 week‐old) rats receiving a mild hypercaloric diet (MHCyoung, 4.035 kcal of which 15% fat or HFD vs. 3 kcal from normal chow or CTRL) for 12 weeks, to mimic a non‐obese pre‐diabetic state, (2) rats receiving the same MHC but for a longer period (24 weeks, MHCold), and (3) rats developing high fat‐to‐lean ratio in response to a MHC diet of which 35% of calories are from fat. ApEn, DFA coefficient α, standard deviation (SD) and coefficient of variation (CV, %) were compared.ResultsHFD‐fed rats demonstrated insulin resistance without hyperglycemia, consistent with prediabetes. Mean systolic and diastolic BP were similar in rats on HFD as compared to the corresponding control groups. HFD, however, was associated with reduced BPV in young rats as expressed by lower (smoother series) ApEn (less complex) for systolic and diastolic BP (p=0.054 and p = 0.006, respectively), while corresponding α and CV were unchanged. A higher SD for DBP (p = 0.006) was observed. BPV profiles were similar in HFD and CTRL among old rats. Fat‐to‐lean ratio was also associated with altered BPV profiles, which was indicated by significant negative correlations with ApEn for both systolic and diastolic series (p = 0.005 and p = 0.002, respectively) and a positive correlation with α for SBP (p = 0.0522), whereas no significant correlations were found for SD and CV for both SBP and DBP series. Age was accompanied with a decrease in ApEn of SBP (p < 0.1) only among CTRL rats.ConclusionEarly metabolic dysfunction is associated with altered blood pressure variability. Non‐linear patterns of hemodynamic regulation in prediabetic rats is susceptible to changes in age and body composition, which were not reflected in changes in mean systolic and diastolic BP but were clearly indicated in the alterations in BPV profiles. Relatedly, changes in BPV properties potentially have important consequences on treatment and prognosis possibly related to the low‐grade inflammatory changes observed in this metabolic state.Support or Funding InformationThis work was supported by AUB‐FM MPP grant #320148
Comparison of entropy and detrended fluctuation analysis indices in pre‐diabetic rats.

Study Group

Pre‐Diabetes (Young, 12 weeks)

Pre‐Diabetes (Old, 24‐weeks)

Pre‐Diabetes (14 weeks) (n = 13)

CTRL (n = 6)

HFD (n = 6)

CTRL (n = 6)

HFD (n = 8)

Correlation rS

Systolic BP (mmHg)

mean

137.34±15.92

147.24±8.22

166.62±4.70

162.38±3.30

−0.207

α

1.01±0.04

1.01±0.05

0.97±0.06

1.00±0.04

0.44

ApEn

0.47±0.024

0.39±0.03

0.39±0.03

0.45±0.02

−0.59

SD

3.63±0.49

4.50±0.66

3.80±0.28

3.87±0.38

0.386

CV (%)

2.59±0.15

3.01±0.35

2.27±0.13

2.36±0.20

0.39

Diastolic BP (mmHg)

mean

110.98±12.40

110.20±10.54

129.37±4.90

131.80±4.51

−0.02

α

1.01±0.05

1.03±0.06

0.94±0.07

1.02±0.03

0.33

ApEn

0.38±0.02

0.25±0.04

0.29±0.04

0.32±0.03

−0.64

SD

1.83±0.15

3.36±0.63

3.22±0.87

2.64±0.18

0.31

CV

1.71±0.14

3.60±1.27

2.59±0.80

2.01±0.14

0.34

Nbeats ≈ 15000; data shown as mean±std err;
*P<0.05 between CTRL young and HFD young;
‡P=0.054 between CTRL young and HFD young;
bp< 0.05 between HFD young and HFD old
†P = 0.052; comparisons using the rank sum and the Spearman correlation test as appropriate