The gut microbiota has become a significant factor associated with health and disease. Although many studies have reported the implications of changes in the gut microbiota on cardiovascular diseases, there are no reports on the relationship between heart rate variability (HRV) and the gut microbiota. Therefore, we investigated the association between gut microbiota abundance and HRV parameters in this cross-sectional study of the general Japanese population. This study included 950 participants of the Iwaki Health Promotion Project who underwent a medical examination in 2019 that included HRV and gut microbiota measurements. At the genus level, multivariate regression analysis showed that higher gut microbial diversity was associated with a higher standard deviation of RR intervals (SDNN). Moreover, a higher SDNN was associated with a higher relative count of Lachnospiraceae incertae sedis. L. incertae sedis abundance was associated with higher HRV parameters such as SDNN, coefficient of variation of RR intervals, low-frequency component power (LF)/high-frequency component power, and LF. In the general Japanese population, higher gut microbial diversity and L. incertae sedis abundance were associated with higher HRV parameters.

Although many studies have reported factors associated with reduced heart rate variability (HRV) in Western populations, evidence is limited among Asian populations. Therefore, we investigated the factors associated with reduced HRV values in a general Japanese population by measuring HRV among the participants of the Iwaki Health Promotion Project who underwent medical examination in 2019. We performed 90-s HRV measurements in 1065 participants. Of these, we evaluated the coefficient of variation in R–R intervals (CVRR) and standard deviation in R–R intervals (SDNN). Blood was collected under a fasting condition, and investigations of glucose metabolism, lipid metabolism, renal function, liver function, advanced glycation end products, and blood pressure were performed. A multivariate regression analysis of the association between CVRR or SDNN and blood test parameters and blood pressure in 987 participants with adequately completed HRV assessments showed that reduced CVRR or SDNN was associated with higher levels of glycated hemoglobin (HbA1c), glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure. In the general Japanese population, higher levels of HbA1c, glycoalbumin, blood glucose, triglycerides, creatinine, plasma pentosidine, and diastolic blood pressure are associated with reduced CVRR or SDNN, which are typical HRV parameters.

The correlation between diabetes-related biomarkers and quality of life (QOL) remains unclear. In this cross-sectional study, we investigated the correlation between diabetes-related biomarkers and QOL in a general Japanese population who underwent health checkups as a part of the Iwaki Health Promotion Project. Male and female participants aged ≥ 20 years from Iwaki District, Hirosaki City, Aomori Prefecture who participated in the 2019 medical evaluation were recruited. QOL was evaluated using the Short Form Health Survey 36 (SF-36). Fasting blood glucose, homeostatic model assessment-estimated insulin resistance (HOMA-IR), hemoglobin A1c (HbA1c), glycoalbumin, and plasma pentosidine were also evaluated as diabetes-related markers. Of the 1065 recruited participants, 1053 completed the clinical and QOL evaluations. Multivariate regression analysis revealed that upregulated diabetes-related markers levels were correlated with decreased SF-36 scores. Blood glucose, HOMA-IR, HbA1c, glycoalbumin, and plasma pentosidine levels were correlated with general health. Moreover, plasma pentosidine levels were correlated with role physical, social functioning, and role emotional in addition to general health. These results indicated that the levels of diabetes-related biomarkers, particularly the levels of plasma pentosidine, a glycation marker, were associated with QOL in our cohort.

Recently, senescent T cells in the peripheral blood have been detected using senescence-associated β-galactosidase (SA-βGal) activity and have been used as an endpoint in clinical trials. However, the epidemiological association between the abundance of SA-βGal-stained senescent CD8+ T cells and chronological age has not been fully elucidated. To examine the correlation between the proportion of SA-βGal^high CD8+ T cells and age, we analyzed previously collected clinical trial data. We conducted a cross-sectional analysis of 632 Japanese adults aged 40–59 years who participated in the screening phase of a clinical trial. To characterize senescent CD8+ T cells, we measured the proportion of SA-βGal^high in total CD8+ T cells and each subset—naïve, central memory (TCM), effector memory (TEM), and terminally differentiated effector memory (TEMRA). We then calculated the correlation coefficients between the proportion of SA-βGal^high CD8+ T cells and age. The proportion of SA-βGal^high cells in total CD8+ T cells, naïve, TCM, TEM, and TEMRA CD8+ T cells increased significantly with age. In Japanese adults, the proportion of SA-βGal^high in CD8+ T cells may serve as a useful biomarker of immune senescence.

Background: In exercise testing, the ventilatory threshold 1 (VT1) and ventilatory threshold 2 (VT2) are used in lifestyle-related diseases, cardiac rehabilitation, and athletic training. We investigated a VT2 measuring method using a pulse oximeter. Methods: Thirty-four adults (men: 15; women: 19) performed a bicycle ergometer Ramp Test. VT1 values were determined using expiratory gas data. The bifurcation of the curve obtained by designating the pulse rate (PR) as an independent variable and SpO₂/PR as a dependent variable was calculated using the residual sum of squares and defined as the SpO₂ threshold (ST) (SpO₂-Slope method). A second bifurcation with ST as the origin was further defined (ST2). ST2 validity was assessed by comparing and analyzing the differences and correlations with each VT2 obtained by expiratory gas analysis. Results: The correlation between ST2 determined by the SpO₂-Slope method using PR as an index and VT2 obtained from respiratory gas analysis was significant, showing a positive correlation (r = 0.74~0.92; p < 0.01), with most data points falling within the 1.96 ± SD in the Bland–Altman analysis. Conclusions: ST2 values derived from SpO₂ and pulse rate measurements by pulse oximeter may be a valuable VT2 measuring method.