Novel Subgroups and Chronic Complications of Diabetes in Middle-Aged and Elderly Chinese:A Prospective Cohort Study

Abstract

BackgroundDiabetes mellitus, especially type 2 diabetes mellitus (T2DM), is regarded as highly heterogeneous. Novel diabetes phenotypes by cluster analysis have been proposed in Europeans but may show different cluster features in Asians. The applicability of cluster analysis in middle-aged and elderly Chinese community T2DM patients needs further investigation.MethodsParticipants were recruited from Jiading community in Shanghai, China. We adopted k-means cluster analysis in 1130 patients (aged ≥ 40 years) with newly-diagnosed T2DM at baseline. Cluster analysis was performed based on seven variables, including fasting plasma glucose, 2 hours postprandial blood glucose, age at diagnosis, body mass index, hemoglobin A1c, homoeostatic model assessment estimates of β-cell function and insulin resistance. All subjects were re-examined at 4.4 years later. Metabolic associated fatty liver disease was diagnosed using B-ultrasound, hepatic fibrosis by non-invasive scores, renal and cardiovascular status by subclinical biomarkers. Multivariable logistic regression models were used to compare the risks of complications between clusters.ResultsPatients were classified into 4 clusters. 381 (33.7%), 456 (40.4%), 87 (7.7%), and 206 (18.2%) patients were separately assigned to mild age-related diabetes (MARD), mild obesity-related diabetes (MOD), severe insulin-deficient and insulin-resistant diabetes (SIDRD), or severe obesity-related and insulin-resistant diabetes (SOIRD), respectively. Participants in MARD, SOIRD, and SIDRD clusters were associated with significantly increased risks of different complications. SOIRD and SIDRD showed novel features in Chinese T2DM patients that were different from those in Europeans.ConclusionsThe refined diabetes phenotypic approach was applicable to Chinese middle-aged and elderly T2DM patients. Patients in different clusters presented significantly different characteristics, progression of metabolic features, and risks of diabetic complications.

A machine learning-based classification of adult-onset diabetes identifies patients at risk of liver-related complications

“… 29 In another study including 80,224 patients who had obesity and 242,822 patients who did not have obesity, the cumulative incidence of severe liver disease at 10 years was <0.15%, <0.2%, and 0.4% in patients who were non-obese, overweight, and obese, respectively. 30 Despite a limited number of events, our results are in line with those of previous studies and suggest that SIRD patients should be carefully followed for liver-related complications. However, this interesting observation should be confirmed in other prospective cohorts with a longer follow-up.…”

“…Two studies have evaluated hepatic fibrosis features among clusters using serum-based markers in a limited number of patients. 12 , 30 Here, we used liver biopsy and elastography to show that patients with SIRD had the highest risk for clinically significant fibrosis ( i.e. F2–F4).…”

Correlation between thyroid function, sensitivity to thyroid hormones and metabolic dysfunction-associated fatty liver disease in euthyroid subjects with newly diagnosed type 2 diabetes

“…To reduce the addictive impact of diabetes progression, patients with newly diagnosed T2DM were enrolled in our study. We found a high prevalence of MAFLD, which was comparable to the one among patients with recently diagnosed T2DM in Pakistan reported by Butt et al [32], but was higher than the ones reported in community-based studies [33,34]. But all the patients in our study were hospitalized and most of them were with high glycemic levels, which might suggest latent diabetes progression and might partly explained the discrepancy.…”

Diabetes duration and types of diabetes treatment in data-driven clusters of patients with diabetes

“…However, there are also differences. In our and other reported studies of East Asians including the Chinese (5,6,8,13), the BMI of the MOD cluster is generally lower than that of Caucasians (4, 7), which may be closely related to the dietary patterns of the different ethnic groups. The Chinese diet is characterized by a high intake of whole grains and vegetables, and a higher intake of fiber, thus reducing the risk of obesity (14).…”