Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: A perspective

Tanabe, Hayato; Masuzaki, Hiroaki; Shimabukuro, Michio

doi:10.1016/j.diabres.2021.109067

Cited by 37 publications

(26 citation statements)

References 100 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Reducing hyperglycemia by SGLT2 inhibitors could correct two core defects present in type 2 diabetes mellitus: pancreatic β-cell dysfunction and insulin resistance. 21 The body weight reduction by SGLT2 inhibitors may influence decreases in HbA1c. 7 Based on data from animal studies and clinical trials, the effects of SGLT2 inhibitors on urinary sodium excretion and diuresis appear to be transient.…”

Section: Discussionmentioning

confidence: 99%

Effect of dapagliflozin on 24-hour glycemic variables in Japanese patients with type 2 diabetes mellitus receiving basal insulin supported oral therapy (DBOT): a multicenter, randomized, open-label, parallel-group study

Kudo

Machii

Ono³

et al. 2023

BMJ Open Diab Res Care

Self Cite

View full text Add to dashboard Cite

IntroductionThis study aimed to evaluate the impacts of dapagliflozin on 24-hour glucose variability and diabetes-related biochemical variables in Japanese patients with type 2 diabetes who had received basal insulin supported oral therapy (BOT).Research design and methodsChanges in mean daily blood glucose level before and after 48–72 hours of add-on or no add-on of dapagliflozin (primary end point) and diabetes-related biochemical variables and major safety variables during the 12 weeks (secondary end point) were evaluated in the multicenter, randomized, two-arm, open-label, parallel-group comparison study.ResultsAmong 36 participants, 18 were included in the no add-on group and 18 were included in the dapagliflozin add-on group. Age, gender, and body mass index were comparable between the groups. There were no changes in continuous glucose monitoring metrics in the no add-on group. In the dapagliflozin add-on group, mean glucose (183–156 mg/dL, p=0.001), maximum glucose (300–253, p<0.01), and SD glucose (57–45, p<0.05) decreased. Time in range increased (p<0.05), while time above the range decreased in the dapagliflozin add-on group but not in the no add-on group. After 12-week treatment with dapagliflozin add-on, 8-hydroxy-2’-deoxyguanosine (8OHdG), as well as hemoglobin A1c (HbA1c), decreased.ConclusionsThis study showed that the mean daily blood glucose and other daily glucose profiles were amended after 48–72 hours of dapagliflozin add-on in Japanese patients with type 2 diabetes who received BOT. The diabetes-related biochemical variables such as HbA1c and urinary 8OHdG were also obtained during the 12 weeks of dapagliflozin add-on without major adverse events. A preferable 24-hour glucose profile in ‘time in ranges’ and an improvement in reactive oxygen species by dapagliflozin warrant us to evaluate these benefits in larger clinical studies.Trial registration numberUMIN000019457.

show abstract

Section: Discussionmentioning

confidence: 99%

Effect of dapagliflozin on 24-hour glycemic variables in Japanese patients with type 2 diabetes mellitus receiving basal insulin supported oral therapy (DBOT): a multicenter, randomized, open-label, parallel-group study

Kudo

Machii

Ono³

et al. 2023

BMJ Open Diab Res Care

Self Cite

View full text Add to dashboard Cite

show abstract

“…Studying the effect of T2D on neurodegeneration is challenging because T2D is a dynamic and highly heterogeneous condition, and proposed subclassification schemes (Fig. 1) 239,240 are difficult to perform retrospectively. Therefore, longer follow‐up of well‐characterized patients with T2D may be necessary to unravel the relative contributions of hyperglycemia, insulin resistance, insulin deficiency, and BMI in determining the risk of PD 77 .…”

Section: Discussionmentioning

confidence: 99%

“…Hypothesized risk of PD (Parkinson's disease) according to T2D (type 2 diabetes) subtype. The T2D subclassification scheme 239,240 illustrated here is based on the age at diabetes onset, body mass index (BMI), glycated hemoglobin A1c (HbA1c), glutamic acid decarboxylase (GAD) antibody status, and homoeostatic model assessment 2 estimates of β-cell function and insulin resistance. The relatively greater increased risk of PD hypothesized for the severe insulin-deficient diabetes (SIDD) subgroup is based on epidemiological evidence, indicating that among people with diabetes, those with earlier age at onset and low BMI appear to have the greatest risk of PD.…”

Section: Pd Phenotype Disease Progression and Survivalmentioning

confidence: 99%

Type 2 Diabetes and Parkinson's Disease: A Focused Review of Current Concepts

et al. 2022

View full text Add to dashboard Cite

Highly reproducible epidemiological evidence shows that type 2 diabetes (T2D) increases the risk and rate of progression of Parkinson's disease (PD), and crucially, the repurposing of certain antidiabetic medications for the treatment of PD has shown early promise in clinical trials, suggesting that the effects of T2D on PD pathogenesis may be modifiable. The high prevalence of T2D means that a significant proportion of patients with PD may benefit from personalized antidiabetic treatment approaches that also confer neuroprotective benefits. Therefore, there is an immediate need to better understand the mechanistic relation between these conditions and the specific molecular pathways affected by T2D in the brain. Although there is considerable evidence that processes such as insulin signaling, mitochondrial function, autophagy, and inflammation are involved in the pathogenesis of both PD and T2D, the primary aim of this review is to highlight the evidence showing that T2D‐associated dysregulation of these pathways occurs not only in the periphery but also in the brain and how this may facilitate neurodegeneration in PD. We also discuss the challenges involved in disentangling the complex relationship between T2D, insulin resistance, and PD, as well as important questions for further research. © 2022 International Parkinson and Movement Disorder Society.

show abstract

“…Although the definitions of NAFLD and MAFLD differ based on history of binge drinking, both are based commonly on evidence of liver fat accumulation (liver steatosis) 1) . Liver steatosis as well as ectopic fat accumulation in the skeletal muscle and cardiovascular system can be a major cause of insulin resistance and its consequences such as T2DM 2) , dyslipidemia, and atherosclerotic cardiovascular disease (ASCVD) 3) .…”

Section: Mafld and Ascvdmentioning

confidence: 99%

MAFLD and ASCVD: Plasma Heparin Cofactor II Activity as an Anti-liver Fibrosis Biomarker

Shimabukuro

2023

JAT

Self Cite

View full text Add to dashboard Cite

show abstract

Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: A perspective

Abstract: Novel strategies for glycaemic control and preventing diabetic complications applying the clustering-based classification of adult-onset diabetes mellitus: A perspective,

Cited by 37 publications

References 100 publications

Effect of dapagliflozin on 24-hour glycemic variables in Japanese patients with type 2 diabetes mellitus receiving basal insulin supported oral therapy (DBOT): a multicenter, randomized, open-label, parallel-group study

Effect of dapagliflozin on 24-hour glycemic variables in Japanese patients with type 2 diabetes mellitus receiving basal insulin supported oral therapy (DBOT): a multicenter, randomized, open-label, parallel-group study

Type 2 Diabetes and Parkinson's Disease: A Focused Review of Current Concepts

MAFLD and ASCVD: Plasma Heparin Cofactor II Activity as an Anti-liver Fibrosis Biomarker

Contact Info

Product

Resources

About