Summary: Caloric restriction (CR) retards aging in laboratory rodents. No information is available on the effects of long‐term CR on physiologic markers of aging and longevity in humans. Heart rate variability (HRV) is a marker for cardiac autonomic functioning. The progressive decline in HRV with aging and the association of higher HRV with better health outcomes are well established. Heart rate variability assessment is a reliable tool by which the effects of CR on autonomic function can be assessed. Time‐ and frequency‐domain analyses compared 24‐h HRV in 22 CR individuals aged 35–82 years and 20 age‐matched controls eating Western diets (WD). The CR group was significantly leaner than the WD group. Heart rate was significantly lower, and virtually, all HRV values were significantly higher in the CR group than in the WD group (P < 0.002). Heart rate variability in the CR individuals was comparable with published norms for healthy individuals 20 years younger. In addition, when differences in heart rate (HR) and HRV between CR and WD were compared with previously published changes in HRV induced in healthy adults given atenolol, percent differences in each measure were generally similar in direction and magnitude and suggested declines in sympathetic and increases in parasympathetic modulation of HR and increased circadian variability associated with CR. These findings provide evidence that CR has direct systemic effects that counter the expected age‐associated changes in autonomic function so that HRV indexes in CR individuals are similar to those of individuals 20 years younger eating WDs.

Direct and indirect links between brain regions and cardiac function have been reported. We performed a systematic literature review to summarize current knowledge regarding the associations of heart rate variability (HRV) and brain region morphology, activity and connectivity involved in autonomic control at rest in healthy subjects. Both positive and negative correlations of cortical thickness and gray matter volumes of brain structures with HRV were observed. The strongest were found for a cluster located within the cingulate cortex. A decline in HRV, as well as cortical thickness with increasing age, especially in the orbitofrontal cortex were noted. When associations of region-specific brain activity with HRV were examined, HRV correlated most strongly with activity in the insula, cingulate cortex, frontal and prefrontal cortices, hippocampus, thalamus, striatum and amygdala. Furthermore, significant correlations, largely positive, between HRV and brain region connectivity (in the amygdala, cingulate cortex and prefrontal cortex) were observed. Notably, right-sided neural structures may be preferentially involved in heart rate and HRV control. However, the evidence for left hemispheric control of cardiac vagal function has also been reported. Our findings provide support for the premise that the brain and the heart are interconnected by both structural and functional networks and indicate complex multi-level interactions. Further studies of brain–heart associations promise to yield insights into their relationship to health and disease.

Background: Heart rate variability ( HRV ) characterizes cardiac autonomic functioning. The association of HRV with stroke is uncertain. We examined whether 24‐hour HRV added predictive value to the Cardiovascular Health Study clinical stroke risk score ( CHS ‐ SCORE ), previously developed at the baseline examination. Methods and Results: N=884 stroke‐free CHS participants (age 75.3±4.6), with 24‐hour Holters adequate for HRV analysis at the 1994–1995 examination, had 68 strokes over ≤8 year follow‐up (median 7.3 [interquartile range 7.1–7.6] years). The value of adding HRV to the CHS ‐ SCORE was assessed with stepwise Cox regression analysis. The CHS ‐ SCORE predicted incident stroke ( HR =1.06 per unit increment, P =0.005). Two HRV parameters, decreased coefficient of variance of NN intervals ( CV %, P =0.031) and decreased power law slope ( SLOPE , P =0.033) also entered the model, but these did not significantly improve the c‐statistic ( P =0.47). In a secondary analysis, dichotomization of CV % ( LOWCV % ≤12.8%) was found to maximally stratify higher‐risk participants after adjustment for CHS ‐ SCORE . Similarly, dichotomizing SLOPE ( LOWSLOPE <−1.4) maximally stratified higher‐risk participants. When these HRV categories were combined (eg, HIGHCV % with HIGHSLOPE ), the c‐statistic for the model with the CHS ‐ SCORE and combined HRV categories was 0.68, significantly higher than 0.61 for the CHS ‐ SCORE alone ( P =0.02). Conclusions: In this sample of older adults, 2 HRV parameters, CV % and power law slope, emerged as significantly associated with incident stroke when added to a validated clinical risk score. After each parameter was dichotomized based on its optimal cut point in this sample, their composite significantly improved prediction of incident stroke during ≤8‐year follow‐up. These findings will require validation in separate, larger cohorts.

Aim: The aim of this review was to summarize current knowledge about the scientific findings and potential clinical utility of heart rate variability measures in patients with systemic lupus erythematosus. Methods: PubMed, Embase and Scopus databases were searched for the terms associated with systemic lupus erythematosus and heart rate variability, including controlled vocabulary, when appropriate. Articles published in English and available in full text were considered. Finally, 11 publications were selected, according to the systematic review protocol and were analyzed. Results: In general, heart rate variability, measured in the time and frequency domains, was reported to be decreased in patients with systemic lupus erythematosus compared with controls. In some systemic lupus erythematosus studies, heart rate variability was found to correlate with inflammatory markers and albumin levels. A novel heart rate variability measure, heart rate turbulence onset, was shown to be increased, while heart rate turbulence slope was decreased in systemic lupus erythematosus patients. Reports of associations of changes in heart rate variability parameters with increasing systemic lupus erythematosus activity were inconsistent, showing decreasing heart rate variability or no relationship. However, the low/high frequency ratio was, in some studies, reported to increase with increasing disease activity or to be inversely correlated with albumin levels. Conclusions: Patients with systemic lupus erythematosus have abnormal heart rate variability, which reflects cardiac autonomic dysfunction and may be related to inflammatory cytokines but not necessarily to disease activity. Thus measurement of heart rate variability could be a useful clinical tool for monitoring autonomic dysfunction in systemic lupus erythematosus, and may potentially provide prognostic information.