Ethnic differences between Asians and non-Asians in clustering-based phenotype classification of adult-onset diabetes mellitus: A systematic narrative review

Varghese, Jithin Sam; Narayan, K.M. Venkat

doi:10.1016/j.pcd.2022.09.007

Cited by 14 publications

(8 citation statements)

References 24 publications

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“…As described, most of the participants who developed T2DM during the 5-year followup period could be classified as either MOD (21.6%) or MARD (75.7%). Although ethnic differences in the frequencies of the T2DM clusters previously reported have been reported, these high frequencies of MOD and MARD are inconsistent with those reported previously [27,28]. Even in a study of a Japanese sample, the frequencies of the SIDD, SIRD, MOD, and MARD clusters were reported to be 19.0, 7.2, 28.9, and 39.5, respectively [10].…”

Section: Discussioncontrasting

confidence: 61%

“…Therefore, to maintain adequate insulin secretion, healthcare should be focused on preventing an increase in blood glucose concentrations for individuals in cluster 2. In addition, as for cluster 1, we also compared the characteristics of cluster 2 at the onset of diabetes to those of the four T2DM clusters previously reported and found that cluster 2 is similar to MARD, which has been shown to have the highest prevalence but the lowest risk of diabetic complications among the four T2DM clusters reported in most previous studies [6,[8][9][10][11][12][16][17][18]27]. This implies that individuals in cluster 2 are at higher risk of incident diabetes, but their risk of subsequently developing diabetes complications may be low, at least over a 5-year period.…”

Section: Discussionmentioning

confidence: 94%

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Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables

ITO

Mizushiri

Nishiya

et al. 2023

JCM

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Recent attempts to classify adult-onset diabetes using only six diabetes-related variables (GAD antibody, age at diagnosis, BMI, HbA1c, and homeostatic model assessment 2 estimates of b-cell function and insulin resistance (HOMA2-B and HOMA2-IR)) showed that diabetes can be classified into five clusters, of which four correspond to type 2 diabetes (T2DM). Here, we classified nondiabetic individuals to identify risk clusters for incident T2DM to facilitate the refinement of prevention strategies. Of the 1167 participants in the population-based Iwaki Health Promotion Project in 2014 (baseline), 868 nondiabetic individuals who attended at least once during 2015–2019 were included in a prospective study. A hierarchical cluster analysis was performed using four variables (BMI, HbA1c, and HOMA2 indices). Of the four clusters identified, cluster 1 (n = 103), labeled as “obese insulin resistant with sufficient compensatory insulin secretion”, and cluster 2 (n = 136), labeled as “low insulin secretion”, were found to be at risk of diabetes during the 5-year follow-up period: the multiple factor-adjusted HRs for clusters 1 and 2 were 14.7 and 53.1, respectively. Further, individuals in clusters 1and 2 could be accurately identified: the area under the ROC curves for clusters 1and 2 were 0.997 and 0.983, respectively. The risk of diabetes could be better assessed on the basis of the cluster that an individual belongs to.

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Section: Discussioncontrasting

confidence: 61%

Section: Discussionmentioning

confidence: 94%

Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables

ITO

Mizushiri

Nishiya

et al. 2023

JCM

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“…One systematic review comparing individuals of Asian versus non-Asian origin showed lower BMI but higher HbA1c in the former group. 25 This is likely related to various genetic and environmental factors, including dietary patterns, socioeconomic levels, and access to advanced technologies. A well-developed study comparing IR in Caucasian versus Thai patients with T1D might also generate interesting results.…”

Section: Discussionmentioning

confidence: 99%

Progression of insulin resistance in individuals with type 1 diabetes: A retrospective longitudinal study on individuals from Thailand

Jirawatwarakul,

Pruktanakul,

Churuangsuk

et al. 2023

Diabetes and Vascular Disease Research

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Aims To investigate temporal changes in glycaemic control and weight contributing to insulin resistance (IR), in Thai individuals with type 1 diabetes (T1D). Methods Longitudinal data of 69 individuals with T1D were retrospectively collected over a median follow-up of 7.2 years. The estimated glucose disposal rate (eGDR), a marker of IR, was calculated using an established formula. Individuals were assigned as insulin-sensitive T1D (the latest eGDR≥8 mg/kg/min), or insulin-resistant T1D/double diabetes (the latest eGDR<8 mg/kg/min). Generalised linear mixed model was employed to compare the temporal patterns of HbA1c, BMI, and eGDR between the two groups. Results 26 insulin-resistant T1D had a gradual decline in eGDR, corresponding with increased weight and HbA1c. In contrast, 43 insulin-sensitive T1D had stable insulin sensitivity with an improvement in HbA1c over time, associated with a modest weight gain. Fluctuations of glucose levels were observed during the early diabetes course leading to unstable eGDR, thus limiting the use of eGDR to classify insulin-resistant T1D. Conclusion T1D individuals who eventually develop IR are likely to experience early increasing IR over time. In contrast, those who ultimately do not have IR, maintain their insulin sensitivity throughout their course at least in the medium term.

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“… 25 Furthermore, recent meta-analysis on diabetes phenotypes reported that Asians in general (including Indians) may have poorer insulin secretion across all reported phenotypes. 26 , 27 …”

Section: A Strategic Research Framework For Diabetes In Indiamentioning

confidence: 99%

“…25 Furthermore, recent meta-analysis on diabetes phenotypes reported that Asians in general (including Indians) may have poorer insulin secretion across all reported phenotypes. 26,27 Understanding the distribution of fat in the abdominal area may be critical to understanding the etiology of diabetes in Indians. The main culprit may be hepatic fat-fat accumulated inside the liver-which has been shown to be higher in Indians compared to Europeans and Pima Indians.…”

Section: Pillar 1: Etiologymentioning

confidence: 99%

A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda

et al. 2023

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Indian people are at high risk for type 2 diabetes (T2DM) even at younger ages and lower body weights. Already 74 million people in India have the disease, and the proportion of those with T2DM is increasing across all strata of society. Unique aspects, related to lower insulin secretion or function, and higher hepatic fat deposition, accompanied by the rise in overweight (related to lifestyle changes) may all be responsible for this unrelenting epidemic of T2DM. Yet, research to understand the causes, pathophysiology, phenotypes, prevention, treatment, and healthcare delivery of T2DM in India seriously lags behind. There are major opportunities for scientific discovery and technological innovation, which if tapped can generate solutions for T2DM relevant to the country’s context and make leading contributions to global science. We analyze the situation of T2DM in India, and present a four-pillar (etiology, precision medicine, implementation research, and health policy) strategic research framework to tackle the challenge. We offer key research questions for each pillar, and identify infrastructure needs. India offers a fertile environment for shifting the paradigm from imprecise late-stage diabetes treatment toward early-stage precision prevention and care. Investing in and leveraging academic and technological infrastructures, across the disciplines of science, engineering, and medicine, can accelerate progress toward a diabetes-free nation.

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Ethnic differences between Asians and non-Asians in clustering-based phenotype classification of adult-onset diabetes mellitus: A systematic narrative review

Cited by 14 publications

References 24 publications

Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables

Two Distinct Groups Are Shown to Be at Risk of Diabetes by Means of a Cluster Analysis of Four Variables

Progression of insulin resistance in individuals with type 1 diabetes: A retrospective longitudinal study on individuals from Thailand

A Strategic Research Framework for Defeating Diabetes in India: A 21st-Century Agenda

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