Published papers

BACKGROUND: Since there are limited studies on the associations between glycemic variability (GV) and sleep quality or physical activity in subjects without diabetes, we evaluated the associations between GV, as assessed by continuous glucose monitoring (CGM), and both sleep quality and daily steps using wearable devices in healthy individuals. METHODS: Forty participants without diabetes were monitored by both an intermittently scanned CGM and a smartwatch-type activity tracker for 2 weeks. The standard deviation (SD) and coefficient of variation (CV) of glucose were evaluated as indices of GV. The activity tracker was used to calculate each participant's average step count per day. We also calculated sleep duration, sleep efficiency, and sleep latency based on data from the activity tracker. Spearman's correlation coefficient was used to assess the association between GV and sleep indices or daily steps. For each participant, periods were divided into quartiles according to step counts throughout the day. We compared mean parameter differences between the periods of lowest quartile and highest quartile (lower 25% and upper 25%). RESULTS: SD glucose was significantly positively correlated with sleep latency (R = 0.23, P < 0.05). There were no significant correlations among other indices in GV and sleep quality (P > 0.05). SD glucose and CV glucose levels in the upper 25% period of daily steps were lower than those in the lower 25% period in each participant (both, P < 0.01). CONCLUSION: In subjects without diabetes, GV evaluated by intermittently scanned CGM was positively associated with the time to fall asleep. Furthermore, GV in the days of larger daily steps was decreased compared to the days of smaller daily steps in each participant.

AIMS/INTRODUCTION: Changes in histologically quantified β- and α-cell mass during the development of glucose intolerance have not been fully elucidated. The aim of the present study was to explore differences in β- and α-cell mass according to the glucose tolerance status. MATERIALS AND METHODS: Autopsy samples from a total of 103 individuals (40 with normal glucose tolerance, 31 with prediabetes and 32 with type 2 diabetes mellitus) who underwent a 75-g oral glucose tolerance test within 5 years before death were selected from 643 community-based autopsy samples collected from 2002 to 2016. Fractional β-cell area (BCA) and α-cell area were quantified with Image Pro Plus software. Associations of BCA and α-cell area with glucose tolerance status were assessed using a linear regression analysis, and Spearman's correlation coefficients between glycemic markers and β-cell function were estimated. RESULTS: The mean values of BCA decreased significantly with worsening glucose tolerance status (mean ± standard error 1.85 ± 0.10% in normal glucose tolerance, 1.59 ± 0.11% in prediabetes and 1.17 ± 0.11% in type 2 diabetes mellitus, P for trend < 0.001), whereas there was no significant association between α-cell area and glucose tolerance status. BCA was inversely correlated with fasting and 2-h plasma glucose levels during oral glucose tolerance test and glycated hemoglobin measurement, and positively correlated with disposition index (all P < 0.01). CONCLUSIONS: β-Cell mass decreased significantly with worsening glucose tolerance, from the stage of prediabetes, in the Japanese population. Prevention of declining β-cell mass before the onset of glucose intolerance is important to reduce the burden of type 2 diabetes mellitus.

AIMS/INTRODUCTION: There have been few reports about the longitudinal changes in pancreas volume (PV) or pancreatic steatosis (PS) in response to obesity. In this longitudinal analysis using health check-up data, we explored changes in PV, PS and glucose metabolic indices that occurred after weight gain in Japanese without diabetes. MATERIALS/METHODS: Clinical data on 37 Japanese subjects with a ≥1 kg/m(2) increase in body mass index between two health check-ups and without diabetes were collected. PV, pancreas attenuation (PA) and splenic attenuation (SA) were evaluated using computed tomography (CT) images. The pancreas area was outlined by hand in multiple images with slice thickness of 2 mm, and the PV was computed by summing these areas. PS was defined as the difference between SA and PA (SA-PA). Medical records were collected, including findings on immunoreactive insulin (IRI), homeostasis model assessment of insulin resistance (HOMA-R) and beta cell function (HOMA-β). Paired t-test and Spearman's correlation coefficient were used in the analyses. RESULTS: The median follow-up period was 21.1 months and the mean BMI was increased from 25.5 ± 3.3 kg/m(2) to 27.0 ± 3.3 kg/m(2). PV (53.5 ± 15.9 cm(3) vs. 56.2 ± 16.4 cm(3)) and SA-PA (8.7 ± 9.1 HU vs. 13.6 ± 10.9 HU) increased significantly after weight gain (both, P < 0.001). There were significant increases of IRI and HOMA-R with the weight gain (both, P < 0.05), whereas HOMA-β exhibited only a nonsignificant trend of increase (55.4％ (41.5-65.5) vs. 56.8％ (46.2-83.7), P = 0.07). CONCLUSIONS: Both PV and PS were increased longitudinally with weight gain in Japanese without diabetes.

Background: Poor sleep quality can elevate stress levels and diminish overall well-being. Japanese individuals often experience sleep deprivation, and workers have high levels of stress. Nevertheless, research examining the connection between objective sleep assessments and stress levels, as well as overall well-being, among Japanese workers is lacking. Objective: This study aims to investigate the correlation between physiological data, including sleep duration and heart rate variability (HRV), objectively measured through wearable devices, and 3 states (sleepiness, mood, and energy) assessed through ecological momentary assessment (EMA) and use of rating scales for stress and well-being. Methods: A total of 40 office workers (female, 20/40, 50%; mean age 40.4 years, SD 11.8 years) participated in the study. Participants were asked to wear a wearable wristband device for 8 consecutive weeks. EMA regarding sleepiness, mood, and energy levels was conducted via email messages sent by participants 4 times daily, with each session spaced 3 hours apart. This assessment occurred on 8 designated days within the 8-week timeframe. Participants’ stress levels and perception of well-being were assessed using respective self-rating questionnaires. Subsequently, participants were categorized into quartiles based on their stress and well-being scores, and the sleep patterns and HRV indices recorded by the Fitbit Inspire 2 were compared among these groups. The Mann-Whitney U test was used to assess differences between the quartiles, with adjustments made for multiple comparisons using the Bonferroni correction. Furthermore, EMA results and the sleep and HRV indices were subjected to multilevel analysis for a comprehensive evaluation. Results: The EMA achieved a total response rate of 87.3%, while the Fitbit Inspire 2 wear rate reached 88.0%. When participants were grouped based on quartiles of well-being and stress-related scores, significant differences emerged. Specifically, individuals in the lowest stress quartile or highest subjective satisfaction quartile retired to bed earlier (P<.001 and P=.01, respectively), whereas those in the highest stress quartile exhibited greater variation in the midpoint of sleep (P<.001). A multilevel analysis unveiled notable relationships: intraindividual variability analysis indicated that higher energy levels were associated with lower deviation of heart rate during sleep on the preceding day (β=–.12, P<.001), and decreased sleepiness was observed on days following longer sleep durations (β=–.10, P<.001). Furthermore, interindividual variability analysis revealed that individuals with earlier midpoints of sleep tended to exhibit higher energy levels (β=–.26, P=.04). Conclusions: Increased sleep variabilities, characterized by unstable bedtime or midpoint of sleep, were correlated with elevated stress levels and diminished well-being. Conversely, improved sleep indices (eg, lower heart rate during sleep and earlier average bedtime) were associated with heightened daytime energy levels. Further research with a larger sample size using these methodologies, particularly focusing on specific phenomena such as social jet lag, has the potential to yield valuable insights.

Background There are limited data about the association between body mass index (BMI), glycemic variability (GV), and life-related factors in healthy nondiabetic adults. Methods This cross-sectional study was carried out within our ethics committee-approved study called “Exploring the impact of nutrition advice on blood sugar and psychological status using continuous glucose monitoring (CGM) and wearable devices”. Prediabetes was defined by the HbA1c level of 5.7–6.4% and /or fasting glucose level of 100–125 mg/dL. Glucose levels and daily steps were measured for 40 participants using Free Style Libre and Fitbit Inspire 2 under normal conditions for 14 days. Dietary intakes and eating behaviors were assessed using a brief-type self-administered dietary history questionnaire and a modified questionnaire from the Obesity Guidelines. Results All indices of GV were higher in the prediabetes group than in the healthy group, but a significant difference was observed only in mean amplitude of glycemic excursions (MAGE). In the multivariate analysis, only the presence of prediabetes showed a significant association with the risk of higher than median MAGE (Odds, 6.786; 95% CI, 1.596–28.858; P = 0.010). Additionally, the underweight (BMI < 18.5) group had significantly higher value in standard deviation (23.7 ± 3.5 vs 19.8 ± 3.7 mg/dL, P = 0.038) and coefficient variability (22.6 ± 4.6 vs 18.4 ± 3.2%, P = 0.015), compared to the normal group. This GV can be partially attributed to irregularity of eating habits. On the contrary, the overweight (BMI > 25) group had the longest time above the 140 or 180 mg/dL range, which may be due to eating style and taking fewer steps (6394 ± 2337 vs 9749 ± 2408 steps, P = 0.013). Conclusions Concurrent CGM with diet and activity monitoring could reduce postprandial hyperglycemia through assessment of diet and daily activity, especially in non- normal weight individuals.

Background This cross-sectional study aims to investigate the association between subclinical atherosclerosis and metabolic dysfunction-associated fatty liver disease (MAFLD) or non-alcoholic fatty liver disease (NAFLD), and a synergistic effect of diabetes mellitus (DM) and MAFLD on subclinical atherosclerosis. Methods Of 977 subjects who underwent health checkups with coronary artery calcification (CAC), carotid intima-media thickness, and brachial-ankle pulse wave velocity (ba-PWV), 890 were included in this study. They were classified as MAFLD, NAFLD, or Neither-FLD, and MAFLD was further categorized into three groups by three metabolic disorders (obesity, lean with metabolic dysregulation, DM), according to its new definition: Obesity-MAFLD, Lean-MAFLD and DM-MAFLD. Results In a multivariable analysis, MAFLD and NAFLD were significantly associated with subclinical atherosclerosis, except for an association between ba-PWV and NAFLD. MAFLD had higher odds for CAC than NAFLD (for CAC score > 100, odds ratio (OR) = 2.599, 95% confidence interval (CI) = 1.625–4.157; OR = 1.795, 95%CI = 1.145–2.814, respectively). In a sub-analysis, DM-MAFLD had higher odds for CAC (for CAC score > 100, OR = 5.833, 95% CI = 3.047–11.164) than the other groups of MAFLD, when compared to Neither FLD as a reference. Moreover, DM-MAFLD had a higher level of homeostasis model assessment of insulin resistance and high sensitive C-reactive protein, compared to the other groups of MAFLD. Conclusions MAFLD was significantly associated with subclinical atherosclerosis in the general population. Additionally, DM-MAFLD could be a significant risk factor for cardiovascular disease through insulin resistance and low-grade inflammation and requires careful follow-up or appropriate intervention.

Aims/Introduction: Long-term glycemic variability is important for predicting diabetic complications, but evaluation in a Japanese population is lacking. The aim of this study was to explore the relationship between visit-to-visit glycemic variability (VVV) and cardiovascular diseases (CV) in Japanese patients with type 2 diabetes, using the prospective cohort of the EMPATHY trial. Materials and Methods: Among 4532 participants with at least three HbA1c measurements, VVV was defined using the coefficient of variation (CV-HbA1c). The outcomes were the composite cardiovascular endpoints, including cardiac, cerebral, renal, and vascular events. The odds ratios (ORs) for the development of outcomes were estimated by using logistic regression models. Results: During a median follow-up of 38 months, 190 subjects developed CV events. The risk of developing CV events increased significantly with increasing quintile of CV-HbA1c, after multivariable adjustment including the mean-HbA1c (OR for the fifth vs first quintile, 1.73; 95%CI, 1.03–2.91; P for trend test = 0.003). There was a stronger association between CV-HbA1c and CV events in patients with a mean-HbA1c of <7% compared with those with a mean-HbA1c of ≥7% (OR per 1 standard deviation, 1.51; 95%CI, 1.23–1.85 and 1.13; 95%CI, 0.98–1.29, respectively; P for interaction = 0.02). Conclusions: Increases of VVV were associated with the risk of CV events in Japanese patients with type 2 diabetes independent of the mean-HbA1c. The long-term variability of HbA1c as well as the mean HbA1c might be an important glycemic indicator in the management of patients with type 2 diabetes, especially in those with a mean-HbA1c of <7%.

Background: We investigated the changes in blood glucose fluctuation, gastric emptying, and vascular endothelial function by switching from an exenatide twice-daily formulation (BID) to a once-weekly formulation (QW) since the evaluation of postprandial glucose excursion and glycemic variability (GV) by continuous glucose monitoring (CGM) after switching was lacking. Methods: Twenty-nine patients with type 2 diabetes treated with exenatide BID were included in this study and switched to exenatide QW for 24 weeks. GV assessed by CGM, gastric emptying (by 13 C-acetate breath test) and vascular endothelial function (by reactive hyperemia - peripheral arterial tonometry) were evaluated at baseline and 24 weeks after switching. Results: HbA1c decreased significantly from the baseline to week 24, while postprandial glucose levels after breakfast and dinner significantly increased (both P <0.05). However, the increases in GV indices were modest and not statistically significant at week 24. Vascular endothelial function was also not significantly changed after switching (P >0.05). Gastric emptying was significantly accelerated at week 24 (Tmax 83.4 ± 12.1 min vs. 58.2 ± 16.4 min) (P <0.001) and correlated with increased postprandial glucose levels after breakfast and dinner (both P <0.05). Conclusions: Despite the increase in postprandial glucose associated with accelerated gastric emptying after switching from exenatide BID to QW, change in GV was modest and no significant deterioration in vascular endothelial function was observed after switching. These results support the superiority of treatment with exenatide QW over exenatide BID in clinical practice; however, attention should be paid to the monitoring and management of postprandial glucose levels when selecting exenatide QW. Trial registration: Clinical trial registry number; UMIN000016390 and jRCTs031180320. Approval date of Registry and the Registration: December 12, 2014.

Exenatide is one of the exendin-based glucagon-like peptide 1 receptor agonists (GLP-1RAs) and is currently available in two formulations, ie, exenatide twice daily (BID), a short-acting GLP-1RA, and exenatide once weekly (QW), a long-acting GLP-1RA. Clinical efficacy and safety of exenatide 2 mg QW in patients with type 2 diabetes (T2DM) has been demonstrated in the DURATION study program. Exenatide QW has been shown to achieve greater HbA1c reduction compared with exenatide BID, with less injection frequency and greater treatment satisfaction. However, exenatide QW failed to show a significant cardiovascular risk reduction in a cardiovascular outcome trial (CVOT), the EXSCEL trial, while other GLP-1RAs have shown positive CV outcomes. Furthermore, exenatide QW has been shown to be inferior to liraglutide and semaglutide with respect to HbA1c or body weight reduction in the head-to-head trials. Thus, although the long-term efficacy and safety of exenatide QW have been demonstrated, exenatide QW might be selected with lower priority within the class of GLP1-RAs for the management of T2DM, especially for patients at high CV risk. On the other hand, exenatide QW is now expected to be a treatment option for children with T2DM or patients with Parkinson’s disease. This review provides an overview of the current evidence regarding the clinical efficacy and safety of exenatide QW and discusses the current perspectives on exenatide QW for treatment of T2DM.

The development of pancreatic cancer (PC) is associated with worsening of glucose tolerance. However, there is limited information about the effects of PC on islet morphology. The aim of this study was to elucidate changes in alpha and beta cell mass in patients with PC. We enrolled 30 autopsy cases with death due to PC (9 with diabetes; DM) and 31 age-and BMI-matched autopsy cases without PC (controls, 12 with DM). Tumor-free pancreatic sections were stained for insulin and glucagon, and fractional beta cell (BCA) and alpha cell area (ACA) were quantified. In addition, expression of de-differentiation markers, i.e., ALDH1A3 and UCN3, was qualitatively evaluated. The pancreas of subjects with PC showed atrophic and fibrotic changes. There was no significant difference in BCA in subjects with PC compared to controls (1.53 ± 1.26% vs. 0.95 ± 0.42%, p = 0.07). However, ACA and ACA to BCA ratio were significantly higher in subjects with PC compared to controls (2.48 ± 2.39% vs. 0.53 ± 0.26% and 1.94 ± 1.93 vs. 0.59 ± 0.26, respectively, both p < 0.001). Increased ACA to BCA ratio was observed in subjects with PC irrespective of the presence of DM. Qualitative evaluation of ALDH1A3 and UCN3 expression showed no significant difference between the groups. In conclusion, in subjects with PC, alpha to beta cell mass ratio is increased, which may contribute to the increased risk of worsening glucose metabolism. Further studies are warranted to elucidate the mechanisms of increased alpha to beta cell mass in patients with PC.

Aims/Introduction: As estimated glomerular filtration rate (eGFR) progression might correlate with cardiovascular prognosis, the correlation between 1-year decline in eGFR and cardiovascular incidences and renal outcome was investigated. Materials and Methods: The 1-year percentage decline in eGFR at the first observation year was calculated in a cohort of the standard versus intEnsive statin therapy for hypercholesteroleMic Patients with diAbetic retinopaTHY (EMPATHY) trial participants. The primary end-point was the composite cardiovascular end-point including the renal end-point. The associations between the incidence of each end-point and clinical markers were analyzed using the Cox proportional hazards regression model. Results: A total of 4,461 patients were analyzed. The mean observation period was 765.3 ± 363.1 days. The best cut-off value of 1-year eGFR decline was 0.099 in the first year for renal end-point prediction by receiver operating characteristic curve analysis. The area under the curve of the model including the 1-year eGFR decline of the first year was significantly larger than the model without it (0.943, 95% confidence interval 0.915–0.971 to 0.967, 95% confidence interval 0.950–0.983, P = 0.019). Primary end-point incidences and the renal end-point were much higher in rapid eGFR decliners compared with non-decliners (P < 0.0001). The cardiovascular end-point incidence, except for the renal end-point, was not different between the groups. According to Cox regression analysis, 1-year eGFR decline during the first year was a significant risk factor for the end-points, including the renal end-point, independent of albuminuria and eGFR at baseline. Conclusions: The 1-year eGFR decline rate provided useful information for cardiovascular end-point predictions, including the renal end-point, in addition to the conventional risk factors.

Aims/hypothesis: Type 2 diabetes is characterised by reduced beta cell mass (BCM). However, it remains uncertain whether the reduction in BCM in type 2 diabetes is due to a decrease in size or number of beta cells. Our aim was to examine the impact of beta cell size and number on islet morphology in humans with and without type 2 diabetes. Methods: Pancreas samples were obtained from 64 Japanese adults with (n = 26) and without (n = 38) type 2 diabetes who underwent pancreatectomy. Using pancreatic tissues stained for insulin, we estimated beta cell size based on beta cell diameter. Beta cell number was estimated from the product of fractional beta cell area and pancreas volume divided by beta cell size. The associations of beta cell size and number with islet morphology and metabolic status were examined. Results: Both beta cell size (548.7 ± 58.5 vs 606.7 ± 65.0 μm3, p < 0.01) and number (5.10 × 108 ± 2.35 × 108 vs 8.16 × 108 ± 4.27 × 108, p < 0.01) were decreased in participants with type 2 diabetes compared with those without diabetes, with the relative reduction in beta cell number (37%) being greater than for beta cell size (10%). Beta cell number but not size was positively correlated with BCM in participants with and without type 2 diabetes (r = 0.97 and r = 0.98, both p < 0.01) and negatively correlated with HbA1c (r = −0.45, p < 0.01). Conclusions/interpretation: Both beta cell size and number were reduced in participants with type 2 diabetes, with the relative reduction in beta cell number being greater. Decrease in beta cell number appears to be a major contributor to reduced BCM in type 2 diabetes. Graphical abstract: [Figure not available: see fulltext.]

Type 2 diabetes (T2DM) is characterized by insulin resistance and β-cell dysfunction. Because patients with T2DM have inadequate β-cell mass (BCM) and β-cell dysfunction worsens glycemic control and makes treatment difficult, therapeutic strategies to preserve and restore BCM are needed. In rodent models, obesity increases BCM about 3-fold, but the increase in BCM in humans is limited. Besides, obesity-induced changes in BCM may show racial differences between East Asians and Caucasians. Recently, the developmental origins of health and disease hypothesis, which states that the risk of developing noncommunicable diseases including T2DM is influenced by the fetal environment, has been proposed. It is known in rodents that animals with low birthweight have reduced BCM through epigenetic modifications, making them more susceptible to diabetes in the future. Similarly, in humans, we revealed that individuals born with low birthweight have lower BCM in adulthood. Because β-cell replication is more frequently observed in the 5 years after birth, and β cells are found to be more plastic in that period, a history of childhood obesity increases BCM. BCM in patients with T2DM is reduced by 20% to 65% compared with that in individuals without T2DM. However, since BCM starts to decrease from the stage of borderline diabetes, early intervention is essential for β-cell protection. In this review, we summarize the current knowledge on regulatory factors of human BCM in health and diabetes and propose the β-cell-centric concept of diabetes to enhance a more pathophysiology-based treatment approach for T2DM.