We investigated the association between impaired fasting glucose (IFG) and cardiometabolic multimorbidity (CMM) in the Chinese population.
Materials and Methods
We included 119,368 participants, free of diabetes mellitus and cardiovascular disease, who participated in the health examination (2006, 2008, 2010) of the Kailuan Study. According to World Health Organization diagnostic criteria, participants were divided into normal fasting blood glucose (FBG) (<6.1 mmol/L) and IFG (FBG 6.1–6.9 mmol/L) groups. CMM was defined as having two or more cardiometabolic diseases, including myocardial infarction, stroke and diabetes mellitus. We used Cox proportional hazards models to evaluate associations between IFG and CMM.
Results
During a median follow-up period of 13.94 years, 2,432 CMM incident events occurred. After adjusting potential confounders, the hazard ratio (HR) and 95% confidence interval (CI) for CMM in the IFG group was 2.83 (95% CI 2.58–3.10) versus the normal FBG group. The HR of IFG for diabetes mellitus was 3.43 (95% CI 3.30–3.55), which was >1.25 (95% CI 1.13–1.37) for myocardial infarction, 1.16 (95% CI 1.07–1.25) for ischemic stroke and 1.06 (95% CI 0.88–1.27) for hemorrhagic stroke. Compared with normal FBG, HRs for risk of IFG for CMM were 2.73 (95% CI 2.48–3.02) in men and 3.86 (95% CI 2.92–5.09) in women.
Conclusion
IFG was a risk factor for CMM. The effect of IFG on diabetes mellitus was stronger than that on other cardiometabolic diseases. The effects of IFG for CMM differed by sex.
目的/简介：我们研究了中国人群空腹血糖受损（IFG）与心脏代谢多病（CMM）之间的关系：我们纳入了参加开滦研究健康体检（2006年、2008年和2010年）的119368名无糖尿病和心血管疾病的参与者。根据世界卫生组织的诊断标准，参试者被分为空腹血糖（FBG）正常（结果：FBG正常的参试者中，空腹血糖正常的参试者中，空腹血糖异常的参试者中，空腹血糖异常的参试者中，空腹血糖异常的参试者中，空腹血糖异常的参试者中在13.94年的中位随访期内，共发生了2432例CMM事件。调整潜在混杂因素后，IFG 组与正常 FBG 组相比，CMM 的危险比（HR）和 95% 置信区间（CI）为 2.83（95% CI 2.58-3.10）。IFG组糖尿病的HR为3.43（95% CI 3.30-3.55），心肌梗死的HR>1.25（95% CI 1.13-1.37），缺血性卒中的HR为1.16（95% CI 1.07-1.25），出血性卒中的HR为1.06（95% CI 0.88-1.27）。与正常FBG相比，男性IFG导致CMM的风险HR为2.73（95% CI 2.48-3.02），女性为3.86（95% CI 2.92-5.09）：结论：IFG是CMM的一个危险因素。结论：IFG是CMM的危险因素，IFG对糖尿病的影响强于对其他心血管代谢疾病的影响。IFG对CMM的影响因性别而异。
{"title":"Association of impaired fasting glucose with cardiometabolic multimorbidity: The Kailuan study","authors":"Zhihui Guo, Shouling Wu, Mengyi Zheng, Pengfei Xia, Qiuyun Li, Qing He, Zhenqiang Song","doi":"10.1111/jdi.14316","DOIUrl":"10.1111/jdi.14316","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims/Introduction</h3>\u0000 \u0000 <p>We investigated the association between impaired fasting glucose (IFG) and cardiometabolic multimorbidity (CMM) in the Chinese population.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>We included 119,368 participants, free of diabetes mellitus and cardiovascular disease, who participated in the health examination (2006, 2008, 2010) of the Kailuan Study. According to World Health Organization diagnostic criteria, participants were divided into normal fasting blood glucose (FBG) (<6.1 mmol/L) and IFG (FBG 6.1–6.9 mmol/L) groups. CMM was defined as having two or more cardiometabolic diseases, including myocardial infarction, stroke and diabetes mellitus. We used Cox proportional hazards models to evaluate associations between IFG and CMM.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>During a median follow-up period of 13.94 years, 2,432 CMM incident events occurred. After adjusting potential confounders, the hazard ratio (HR) and 95% confidence interval (CI) for CMM in the IFG group was 2.83 (95% CI 2.58–3.10) versus the normal FBG group. The HR of IFG for diabetes mellitus was 3.43 (95% CI 3.30–3.55), which was >1.25 (95% CI 1.13–1.37) for myocardial infarction, 1.16 (95% CI 1.07–1.25) for ischemic stroke and 1.06 (95% CI 0.88–1.27) for hemorrhagic stroke. Compared with normal FBG, HRs for risk of IFG for CMM were 2.73 (95% CI 2.48–3.02) in men and 3.86 (95% CI 2.92–5.09) in women.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusion</h3>\u0000 \u0000 <p>IFG was a risk factor for CMM. The effect of IFG on diabetes mellitus was stronger than that on other cardiometabolic diseases. The effects of IFG for CMM differed by sex.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 1","pages":"129-136"},"PeriodicalIF":3.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693544/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142491571","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This commentary highlights the role of heart rate variability (HRV) indices in predicting diabetic kidney disease (DKD) progression, based on findings from the PERL and ACCORD trials. HRV-derived measures from routine ECGs are shown to be strong predictors of rapid kidney function decline in both type 1 and type 2 diabetes, suggesting their potential utility in identifying individuals at high risk for DKD and guiding early preventive interventions.
{"title":"Heart rate variability indices for predicting cardiorenal outcomes: A lesson from the PERL and ACCORD cohorts","authors":"Kazuhiro Sugimoto","doi":"10.1111/jdi.14333","DOIUrl":"10.1111/jdi.14333","url":null,"abstract":"<p>This commentary highlights the role of heart rate variability (HRV) indices in predicting diabetic kidney disease (DKD) progression, based on findings from the PERL and ACCORD trials. HRV-derived measures from routine ECGs are shown to be strong predictors of rapid kidney function decline in both type 1 and type 2 diabetes, suggesting their potential utility in identifying individuals at high risk for DKD and guiding early preventive interventions.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 1","pages":"5-7"},"PeriodicalIF":3.1,"publicationDate":"2024-10-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693551/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142454285","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Han Na Jang, Young Suk Park, Joon Ho Moon, Sung Hee Choi, Hak Chul Jang, Tae Jung Oh
Introduction
Cardiovascular autonomic neuropathy (CAN) is a chronic complication of diabetes. As obesity is a major risk factor for CAN, we hypothesized that metabolic bariatric surgery (MBS) could improve CAN indices in Korean patients with obesity.
Materials and Methods
Patients who underwent bariatric surgery between February 2020 and June 2022 were prospectively recruited. CAN was conducted once before surgery and again after surgery, using the Ewing method and heart rate variability (HRV) analysis (standard deviation of the NN interval [SDNN], root mean square of successive RR interval difference [RMSSD], and spectral analysis).
Results
A total of 47 patients were included. The mean age was 39.8 ± 8.7 years, 15 (31.9%) were male, and 26 (55.3%) had diabetes. Resting HR before surgery was 81.0 ± 12.3 bpm, which decreased significantly to 68.0 ± 9.3 bpm after surgery (P < 0.001). Changes in HR and BP according to the Valsalva maneuver, postural changes, and handgrip were not significantly different before and after surgery. However, SDNN significantly increased from 25.2 [15.1, 33.5] to 38.0 [25.4, 45.0] ms (P < 0.001), and RMSSD also significantly increased from 17.0 [9.2, 31.8] to 28.2 [15.3, 45.6] ms (P = 0.001). Both low-frequency power (LF) and high-frequency power (HF) increased significantly, and the LF/HF ratio significantly decreased from 2.1 ± 1.6 to 1.3 ± 1.3 (P = 0.010). Loss of weight, fat mass, and lean body mass were independently associated with improving the HRV variables.
Conclusions
MBS improved HRV variables, and these changes were mainly associated with postoperative weight loss.
{"title":"Improvement of heart rate variability after metabolic bariatric surgery in Korean subjects with obesity","authors":"Han Na Jang, Young Suk Park, Joon Ho Moon, Sung Hee Choi, Hak Chul Jang, Tae Jung Oh","doi":"10.1111/jdi.14332","DOIUrl":"10.1111/jdi.14332","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Introduction</h3>\u0000 \u0000 <p>Cardiovascular autonomic neuropathy (CAN) is a chronic complication of diabetes. As obesity is a major risk factor for CAN, we hypothesized that metabolic bariatric surgery (MBS) could improve CAN indices in Korean patients with obesity.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>Patients who underwent bariatric surgery between February 2020 and June 2022 were prospectively recruited. CAN was conducted once before surgery and again after surgery, using the Ewing method and heart rate variability (HRV) analysis (standard deviation of the NN interval [SDNN], root mean square of successive RR interval difference [RMSSD], and spectral analysis).</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>A total of 47 patients were included. The mean age was 39.8 ± 8.7 years, 15 (31.9%) were male, and 26 (55.3%) had diabetes. Resting HR before surgery was 81.0 ± 12.3 bpm, which decreased significantly to 68.0 ± 9.3 bpm after surgery (<i>P</i> < 0.001). Changes in HR and BP according to the Valsalva maneuver, postural changes, and handgrip were not significantly different before and after surgery. However, SDNN significantly increased from 25.2 [15.1, 33.5] to 38.0 [25.4, 45.0] ms (<i>P</i> < 0.001), and RMSSD also significantly increased from 17.0 [9.2, 31.8] to 28.2 [15.3, 45.6] ms (<i>P</i> = 0.001). Both low-frequency power (LF) and high-frequency power (HF) increased significantly, and the LF/HF ratio significantly decreased from 2.1 ± 1.6 to 1.3 ± 1.3 (<i>P</i> = 0.010). Loss of weight, fat mass, and lean body mass were independently associated with improving the HRV variables.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>MBS improved HRV variables, and these changes were mainly associated with postoperative weight loss.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 12","pages":"1773-1780"},"PeriodicalIF":3.1,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14332","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142454286","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions.
Materials and Methods
Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method.
Results
We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (P < 0.001). Kaplan–Meier curves indicated significant differences in diabetes complication incidences between clusters.
Conclusions
UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.
{"title":"Clustering-based risk stratification of prediabetes populations: Insights from the Taiwan and UK Biobanks","authors":"Djeane Debora Onthoni, Ying-Erh Chen, Yi-Hsuan Lai, Guo-Hung Li, Yong-Sheng Zhuang, Hong-Ming Lin, Yu-Ping Hsiao, Ade Indra Onthoni, Hung-Yi Chiou, Ren-Hua Chung","doi":"10.1111/jdi.14328","DOIUrl":"10.1111/jdi.14328","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims/Introduction</h3>\u0000 \u0000 <p>This study aimed to identify low- and high-risk diabetes groups within prediabetes populations using data from the Taiwan Biobank (TWB) and UK Biobank (UKB) through a clustering-based Unsupervised Learning (UL) approach, to inform targeted type 2 diabetes (T2D) interventions.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>Data from TWB and UKB, comprising clinical and genetic information, were analyzed. Prediabetes was defined by glucose thresholds, and incident T2D was identified through follow-up data. K-means clustering was performed on prediabetes participants using significant features determined through logistic regression and LASSO. Cluster stability was assessed using mean Jaccard similarity, silhouette score, and the elbow method.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>We identified two stable clusters representing high- and low-risk diabetes groups in both biobanks. The high-risk clusters showed higher diabetes incidence, with 15.7% in TWB and 13.0% in UKB, compared to 7.3% and 9.1% in the low-risk clusters, respectively. Notably, males were predominant in the high-risk groups, constituting 76.6% in TWB and 52.7% in UKB. In TWB, the high-risk group also exhibited significantly higher BMI, fasting glucose, and triglycerides, while UKB showed marginal significance in BMI and other metabolic indicators. Current smoking was significantly associated with increased diabetes risk in the TWB high-risk group (<i>P</i> < 0.001). Kaplan–Meier curves indicated significant differences in diabetes complication incidences between clusters.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>UL effectively identified risk-specific groups within prediabetes populations, with high-risk groups strongly associated male gender, higher BMI, smoking, and metabolic markers. Tailored preventive strategies, particularly for young males in Taiwan, are crucial to reducing T2D risk.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 1","pages":"25-35"},"PeriodicalIF":3.1,"publicationDate":"2024-10-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693582/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142454284","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>The principal causes of death among 68,555 patients with diabetes and 164,621 patients without diabetes who died in 208 hospitals throughout Japan between 2011 and 2020 were determined based on a survey of hospital records. The most frequent cause of death in patients with diabetes was malignant neoplasms (38.9%) (lung 7.8%, pancreas 6.5%, liver 4.1%), followed, in order of descending frequency, by infectious diseases (17.0%) and then vascular diseases (10.9%) (cerebrovascular diseases 5.2%, ischemic heart diseases 3.5%, renal failure 2.3%). The proportion of deaths from malignant neoplasms and vascular diseases has trended upward and downward, respectively. Almost all deaths from ischemic heart diseases were due to myocardial infarction, and the proportion of deaths from heart diseases other than ischemic heart diseases was relatively high (9.0%), with most cases due to heart failure. Diabetic coma associated with hyperglycemia accounted for only 0.3% of deaths. The proportion of deaths from malignant neoplasms, infectious diseases, renal failure, ischemic heart diseases, and heart failure was significantly higher in patients with diabetes than in those without diabetes, and the proportion of deaths from cerebrovascular diseases was significantly lower in patients with diabetes. With regard to the relationship between the age and cause of death in patients with diabetes, malignant neoplasms were the most frequent cause of death in all age groups, and the incidence was around 50% for those in their 50s and 60s. The incidence of death due to infectious diseases was highest in patients older than their 70s. The incidence of death due to vascular diseases for patients in their 40s and 50s was higher than that due to infectious diseases. The highest incidence of death due to ischemic heart diseases was observed for patients in their 40s, and that due to renal failure and heart failure in patients older than their 70s. Compared with patients without diabetes, patients with diabetes demonstrated a higher incidence of death due to pancreatic cancer, infectious diseases, renal failure, ischemic heart diseases, and heart failure, and a lower incidence of death due to cerebrovascular diseases in all age groups. The average age at death of patients with diabetes was 74.4 years old in men and 77.4 years old in women, which were lower than the average lifespan of the Japanese general population in 2020 by 7.2 and 10.3 years, respectively. However, these differences were smaller than in previous surveys. The average age at death due to all causes, especially due to ischemic heart diseases, cerebrovascular diseases, heart failure, infectious diseases, and diabetic coma, was lower in patients with ‘poorer’ glycemic control than in those with ‘better’ glycemic control. In the total survey population, the average age at death of patients with diabetes was significantly higher than that of patients without diabetes. The average age at death due to malignant neop
{"title":"Causes of death in Japanese patients with diabetes based on the results of a survey of 68,555 cases during 2011–2020: Committee report on causes of death in diabetes mellitus, Japan Diabetes Society (English version)","authors":"Jiro Nakamura, Narihito Yoshioka, Hideki Katagiri, Kohjiro Ueki, Toshimasa Yamauchi, Nobuya Inagaki, Yukio Tanizawa, Eiichi Araki, Takeo Nakayama, Hideki Kamiya","doi":"10.1111/jdi.14232","DOIUrl":"10.1111/jdi.14232","url":null,"abstract":"<p>The principal causes of death among 68,555 patients with diabetes and 164,621 patients without diabetes who died in 208 hospitals throughout Japan between 2011 and 2020 were determined based on a survey of hospital records. The most frequent cause of death in patients with diabetes was malignant neoplasms (38.9%) (lung 7.8%, pancreas 6.5%, liver 4.1%), followed, in order of descending frequency, by infectious diseases (17.0%) and then vascular diseases (10.9%) (cerebrovascular diseases 5.2%, ischemic heart diseases 3.5%, renal failure 2.3%). The proportion of deaths from malignant neoplasms and vascular diseases has trended upward and downward, respectively. Almost all deaths from ischemic heart diseases were due to myocardial infarction, and the proportion of deaths from heart diseases other than ischemic heart diseases was relatively high (9.0%), with most cases due to heart failure. Diabetic coma associated with hyperglycemia accounted for only 0.3% of deaths. The proportion of deaths from malignant neoplasms, infectious diseases, renal failure, ischemic heart diseases, and heart failure was significantly higher in patients with diabetes than in those without diabetes, and the proportion of deaths from cerebrovascular diseases was significantly lower in patients with diabetes. With regard to the relationship between the age and cause of death in patients with diabetes, malignant neoplasms were the most frequent cause of death in all age groups, and the incidence was around 50% for those in their 50s and 60s. The incidence of death due to infectious diseases was highest in patients older than their 70s. The incidence of death due to vascular diseases for patients in their 40s and 50s was higher than that due to infectious diseases. The highest incidence of death due to ischemic heart diseases was observed for patients in their 40s, and that due to renal failure and heart failure in patients older than their 70s. Compared with patients without diabetes, patients with diabetes demonstrated a higher incidence of death due to pancreatic cancer, infectious diseases, renal failure, ischemic heart diseases, and heart failure, and a lower incidence of death due to cerebrovascular diseases in all age groups. The average age at death of patients with diabetes was 74.4 years old in men and 77.4 years old in women, which were lower than the average lifespan of the Japanese general population in 2020 by 7.2 and 10.3 years, respectively. However, these differences were smaller than in previous surveys. The average age at death due to all causes, especially due to ischemic heart diseases, cerebrovascular diseases, heart failure, infectious diseases, and diabetic coma, was lower in patients with ‘poorer’ glycemic control than in those with ‘better’ glycemic control. In the total survey population, the average age at death of patients with diabetes was significantly higher than that of patients without diabetes. The average age at death due to malignant neop","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 12","pages":"1821-1837"},"PeriodicalIF":3.1,"publicationDate":"2024-10-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14232","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370425","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
<p>Circadian rhythm is an endogenous autonomous oscillator of physiological activities resulting in 24 h day/night cycles. This rhythm is regarded as a system regulating organisms allowing them to carry out efficient biological activities during the day–night cycle. In humans, the rhythm is set at 24 h and 11 ± 16 min, which is slightly longer than the day rhythm (24 h). Therefore, when living in a dark room, the waking time is slightly delayed each day<span><sup>1</sup></span>.</p><p>The invention of electric light revolutionized society, with humans now able to work at night, including shift work, and such disruption of the circadian rhythm reportedly increases insulin resistance, as well as raising the risks of type 2 diabetes and cardiovascular diseases<span><sup>2, 3</sup></span>.</p><p>In humans, the center of the circadian rhythm is located in the suprachiasmatic nucleus, and the rhythm is generated by a set of genes known as clock genes. The following molecular mechanism generates circadian rhythms: first, the heterodimer of CLOCK-BMAL1, a set of the core clock gene products, binds to the promoters of the <i>Per</i> and <i>Cry</i> clock genes, thereby activating both <i>Per</i> and <i>Cry</i> transcription. The translated PER and CRY then suppress CLOCK-BMAL1 transcriptional activity through a negative feedback mechanism, and this loop cycles once every 24 h to generate a circadian rhythm (Figure 1). The genes involved in this circuit are referred to as ‘core clock genes’.</p><p>Core clock genes such as <i>Bmal1</i> and <i>Clock</i> generate circadian rhythms by regulating a group of genes with E-box sequences that provide a rhythm underlying cellular functions. For example, in pancreatic islet β-cells, BMAL1 and CLOCK directly regulate a group of genes related to insulin secretion, generating a distinct circadian rhythm for insulin secretion<span><sup>4</sup></span>. In addition to these direct regulatory factors, another set of transcription factors, referred to as clock output genes, transmit the signals from core clock genes to downstream effector genes. Clock output genes include DBP, TEF, HLF, and E4BP4. We and others have recently conducted rigorous studies of their effects on metabolism (Table 1). Herein, we discuss the roles of these clock output genes, focusing on glucose metabolism.</p><p>Future research is anticipated to reveal the mechanisms underlying peripheral clock gene regulation, opening the way to the development of drugs targeting these genes without disrupting the central circadian rhythm. While drugs influencing core clock genes have shown metabolic benefits in mice, their use in patients with metabolic diseases requires further investigation aimed at minimizing any adverse effects on the central biological clock.</p><p>Yukio Tanizawa is an Editorial Board member of <i>Journal of Diabetes Investigation</i> and a co-author of this article. To minimize bias, he was excluded from all editorial decision-making related t
{"title":"The roles of output clock genes in regulating glucose metabolism","authors":"Akihiko Taguchi, Yasuharu Ohta, Yuko Nagao, Yukio Tanizawa","doi":"10.1111/jdi.14295","DOIUrl":"10.1111/jdi.14295","url":null,"abstract":"<p>Circadian rhythm is an endogenous autonomous oscillator of physiological activities resulting in 24 h day/night cycles. This rhythm is regarded as a system regulating organisms allowing them to carry out efficient biological activities during the day–night cycle. In humans, the rhythm is set at 24 h and 11 ± 16 min, which is slightly longer than the day rhythm (24 h). Therefore, when living in a dark room, the waking time is slightly delayed each day<span><sup>1</sup></span>.</p><p>The invention of electric light revolutionized society, with humans now able to work at night, including shift work, and such disruption of the circadian rhythm reportedly increases insulin resistance, as well as raising the risks of type 2 diabetes and cardiovascular diseases<span><sup>2, 3</sup></span>.</p><p>In humans, the center of the circadian rhythm is located in the suprachiasmatic nucleus, and the rhythm is generated by a set of genes known as clock genes. The following molecular mechanism generates circadian rhythms: first, the heterodimer of CLOCK-BMAL1, a set of the core clock gene products, binds to the promoters of the <i>Per</i> and <i>Cry</i> clock genes, thereby activating both <i>Per</i> and <i>Cry</i> transcription. The translated PER and CRY then suppress CLOCK-BMAL1 transcriptional activity through a negative feedback mechanism, and this loop cycles once every 24 h to generate a circadian rhythm (Figure 1). The genes involved in this circuit are referred to as ‘core clock genes’.</p><p>Core clock genes such as <i>Bmal1</i> and <i>Clock</i> generate circadian rhythms by regulating a group of genes with E-box sequences that provide a rhythm underlying cellular functions. For example, in pancreatic islet β-cells, BMAL1 and CLOCK directly regulate a group of genes related to insulin secretion, generating a distinct circadian rhythm for insulin secretion<span><sup>4</sup></span>. In addition to these direct regulatory factors, another set of transcription factors, referred to as clock output genes, transmit the signals from core clock genes to downstream effector genes. Clock output genes include DBP, TEF, HLF, and E4BP4. We and others have recently conducted rigorous studies of their effects on metabolism (Table 1). Herein, we discuss the roles of these clock output genes, focusing on glucose metabolism.</p><p>Future research is anticipated to reveal the mechanisms underlying peripheral clock gene regulation, opening the way to the development of drugs targeting these genes without disrupting the central circadian rhythm. While drugs influencing core clock genes have shown metabolic benefits in mice, their use in patients with metabolic diseases requires further investigation aimed at minimizing any adverse effects on the central biological clock.</p><p>Yukio Tanizawa is an Editorial Board member of <i>Journal of Diabetes Investigation</i> and a co-author of this article. To minimize bias, he was excluded from all editorial decision-making related t","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 12","pages":"1707-1710"},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14295","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370427","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Yutaka Seino, Daisuke Yabe, Kazuhiro Tsumura, Chien-Ning Huang, So Hun Kim, Weiping Jia, Altaisaikhan Khasag, Takashi Kadowaki
Many Asian countries, including Japan, China, and South Korea, continue to use terms that reference sugar and urine, contributing to ongoing stigma, while most of the rest of the world seem to use terms related to the original “Diabetes,” meaning “to pass through.” The 16th Scientific Meeting of the Asian Association for the Study of Diabetes (AASD) was held, featuring a pivotal joint symposium organized by AASD and the Japanese Association of Diabetes Education and Care where an in-depth discussion was carried out on diabetes-related terminology across various Asian countries and regions, with a particular focus on the stigma associated with existing terms. The symposium participants reached a consensus on the necessity of revising the stigmatizing diabetes terminology across Asia and agreed to continue discussions and monitor progress at the 17th AASD Scientific Meeting, scheduled to be held in 2025.
{"title":"The Ulaanbaatar agreement: Revising diabetes terminology in Asia to combat stigma","authors":"Yutaka Seino, Daisuke Yabe, Kazuhiro Tsumura, Chien-Ning Huang, So Hun Kim, Weiping Jia, Altaisaikhan Khasag, Takashi Kadowaki","doi":"10.1111/jdi.14330","DOIUrl":"10.1111/jdi.14330","url":null,"abstract":"<p>Many Asian countries, including Japan, China, and South Korea, continue to use terms that reference sugar and urine, contributing to ongoing stigma, while most of the rest of the world seem to use terms related to the original “Diabetes,” meaning “to pass through.” The 16th Scientific Meeting of the Asian Association for the Study of Diabetes (AASD) was held, featuring a pivotal joint symposium organized by AASD and the Japanese Association of Diabetes Education and Care where an in-depth discussion was carried out on diabetes-related terminology across various Asian countries and regions, with a particular focus on the stigma associated with existing terms. The symposium participants reached a consensus on the necessity of revising the stigmatizing diabetes terminology across Asia and agreed to continue discussions and monitor progress at the 17th AASD Scientific Meeting, scheduled to be held in 2025.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 11","pages":"1533-1536"},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14330","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370428","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Despite the reported success of low-carbohydrate diets in improving glycemic control in the Western countries, no studies have investigated the effects of such diets in Asians. We aimed to conduct a systematic review and meta-analysis of randomized controlled trials to examine the effects of low-carbohydrate diets on glycemic control in East Asian adults.
Materials and Methods
We systematically searched the PubMed, Cochrane Library, and Embase databases from inception to June 28, 2023, to identify randomized controlled trials examining the efficacy of low-carbohydrate diets in patients with type 2 diabetes (PROSPERO number CRD 42023453007). The primary outcome was the difference in glycated hemoglobin levels between the low-carbohydrate diet and control groups. The secondary outcome was the difference in body mass index, fasting blood glucose level, blood pressure, and lipid profile.
Results
Six randomized controlled trials met the eligibility criteria. The study duration ranged from 3 to 18 months, with five studies conducted within 6 months. The results showed that low-carbohydrate diets were more beneficial in lowering glycated hemoglobin levels and body mass index than control diets. The risk of bias for the six studies was minimal for two and moderate for four. The heterogeneity among the studies was low.
Conclusions
Low-carbohydrate diets improved glycated hemoglobin levels and body mass index in East Asians compared with control diets. Therefore, carbohydrate restriction may be effective for glycemic management in East Asians with type 2 diabetes for at least 6 months.
{"title":"Low-carbohydrate diets in East Asians with type 2 diabetes: A systematic review and meta-analysis of randomized controlled trials","authors":"Junya Hironaka, Masahide Hamaguchi, Takahiro Ichikawa, Hanako Nakajima, Takuro Okamura, Saori Majima, Takafumi Senmaru, Hiroshi Okada, Emi Ushigome, Naoko Nakanishi, Erina Joo, Kenichiro Shide, Michiaki Fukui","doi":"10.1111/jdi.14326","DOIUrl":"10.1111/jdi.14326","url":null,"abstract":"<div>\u0000 \u0000 \u0000 <section>\u0000 \u0000 <h3> Aims</h3>\u0000 \u0000 <p>Despite the reported success of low-carbohydrate diets in improving glycemic control in the Western countries, no studies have investigated the effects of such diets in Asians. We aimed to conduct a systematic review and meta-analysis of randomized controlled trials to examine the effects of low-carbohydrate diets on glycemic control in East Asian adults.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Materials and Methods</h3>\u0000 \u0000 <p>We systematically searched the PubMed, Cochrane Library, and Embase databases from inception to June 28, 2023, to identify randomized controlled trials examining the efficacy of low-carbohydrate diets in patients with type 2 diabetes (PROSPERO number CRD 42023453007). The primary outcome was the difference in glycated hemoglobin levels between the low-carbohydrate diet and control groups. The secondary outcome was the difference in body mass index, fasting blood glucose level, blood pressure, and lipid profile.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Results</h3>\u0000 \u0000 <p>Six randomized controlled trials met the eligibility criteria. The study duration ranged from 3 to 18 months, with five studies conducted within 6 months. The results showed that low-carbohydrate diets were more beneficial in lowering glycated hemoglobin levels and body mass index than control diets. The risk of bias for the six studies was minimal for two and moderate for four. The heterogeneity among the studies was low.</p>\u0000 </section>\u0000 \u0000 <section>\u0000 \u0000 <h3> Conclusions</h3>\u0000 \u0000 <p>Low-carbohydrate diets improved glycated hemoglobin levels and body mass index in East Asians compared with control diets. Therefore, carbohydrate restriction may be effective for glycemic management in East Asians with type 2 diabetes for at least 6 months.</p>\u0000 </section>\u0000 </div>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 12","pages":"1753-1762"},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14326","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142363624","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In both human clinical and animal experimental studies, the altered expression of regulatory RNAs such as miRNAs, lncRNAs, and circRNAs are reported in diabetes and its complications by investigating various samples of serum, plasma, whole blood, and tissues. These identified ncRNAs are candidates for the disease diagnostic markers, prognostic markers, and also therapeutic targets. In the updates, the recently published ncRNAs involved in the onset and progression of DKD are discussed.
{"title":"Noncoding RNAs and diabetic kidney disease","authors":"Jun Wada","doi":"10.1111/jdi.14331","DOIUrl":"10.1111/jdi.14331","url":null,"abstract":"<p>In both human clinical and animal experimental studies, the altered expression of regulatory RNAs such as miRNAs, lncRNAs, and circRNAs are reported in diabetes and its complications by investigating various samples of serum, plasma, whole blood, and tissues. These identified ncRNAs are candidates for the disease diagnostic markers, prognostic markers, and also therapeutic targets. In the updates, the recently published ncRNAs involved in the onset and progression of DKD are discussed.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"16 1","pages":"8-9"},"PeriodicalIF":3.1,"publicationDate":"2024-10-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11693531/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142370426","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
There are several physiological and pharmacological actions of glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide/gastric inhibitory polypeptide for the regulation of blood glucose and bodyweight.
{"title":"Regulation of glucose and energy metabolism through actions of glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide","authors":"Yasuo Zenimaru, Norio Harada","doi":"10.1111/jdi.14305","DOIUrl":"10.1111/jdi.14305","url":null,"abstract":"<p>There are several physiological and pharmacological actions of glucagon-like peptide-1 and glucose-dependent insulinotropic polypeptide/gastric inhibitory polypeptide for the regulation of blood glucose and bodyweight.\u0000 <figure>\u0000 <div><picture>\u0000 <source></source></picture><p></p>\u0000 </div>\u0000 </figure></p>","PeriodicalId":51250,"journal":{"name":"Journal of Diabetes Investigation","volume":"15 12","pages":"1725-1726"},"PeriodicalIF":3.1,"publicationDate":"2024-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1111/jdi.14305","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142337882","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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