Metabolic and proteomic signatures of type 2 diabetes subtypes in an Arab population

Background. Type 2 diabetes (T2D) has a heterogeneous etiology which is increasingly recognized to influence the risk of complications and choice of treatment. A data driven cluster analysis in four separate European populations of patients with type 2 diabetes identified four subtypes of severe insulin dependent (SIDD), severe insulin resistant (SIRD), mild obesity-related (MOD), and mild age-related (MARD) (Ahlqvist et al., Lancet Diabetes Endocrinology, 2018). Our aim was to extend this classification to the Arab population of Qatar and characterize the biological processes that differentiate these subtypes in relation to metabolomic and proteomic signatures. Methods. The Ahlqvist et al. subtype clustering approach was applied to 631 individuals with T2D from the Qatar Biobank (QBB) and validated in an independent set of 420 participants from the same population. The association between blood metabolites (n=1,159) and protein levels (n=1,305) with each cluster were established. Findings. The four subtypes of T2D were reproduced and validated in the population of Qatar. Cluster-specific metabolomic and proteomic associations revealed subtype-specific molecular processes. Activation of the complement system with many features of autoimmune diabetes and reduced 1,5-anhydroglucitol (1,5-AG) characterized SIDD, with evidence of impaired insulin signaling in SIRD, elevated leptin and fatty acid binding protein in MOD, whilst MARD appeared to be the healthiest subgroup. Interpretation. We have replicated the four T2D clusters in an Arab population and identified distinct metabolic and proteomic signatures, providing insights into underlying etiology with the potential to deploy subtype-specific treatment options.

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Age-Related Androgen Deficiency and Type 2 Diabetes

Journal of Pharmacy Practice ◽

10.1177/0897190010397719 ◽

2011 ◽

Vol 24 (3) ◽

pp. 316-322 ◽

Cited By ~ 2

Author(s):

Gina J. Ryan ◽

Lynetta J. Jobe

Keyword(s):

Type 2 Diabetes ◽

Hypogonadotropic Hypogonadism ◽

Treatment Options ◽

Mineral Density ◽

Testosterone Levels ◽

Know How ◽

Age Related ◽

Appropriate Therapy ◽

Low Testosterone

There is a higher prevalence of low testosterone levels in males with type 2 diabetes compared to those without. Additionally, there is evidence that low testosterone levels may predict the development of type 2 diabetes. Symptoms of hypogonadism include decreased libido, decreased bone mineral density (BMD), and decreased lean muscle mass. The majority of the published cases in men with diabetes were attributed to age-related idiopathic hypogonadotropic hypogonadism. This paper reviews the link between type 2 diabetes and age-related hypogonadism and the treatment options for hypogonadism. Pharmacists who provide care for males with diabetes should be aware of the increased incidence of hypogonadism, know how to screen for it, and be able to recommend appropriate therapy.

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Assessing reproducibility and utility of clustering of patients with type 2 diabetes and established CV disease (SAVOR -TIMI 53 trial)

PLoS ONE ◽

10.1371/journal.pone.0259372 ◽

2021 ◽

Vol 16 (11) ◽

pp. e0259372

Author(s):

Yasunori Aoki ◽

Bengt Hamrén ◽

Lindsay E. Clegg ◽

Christina Stahre ◽

Deepak L. Bhatt ◽

...

Keyword(s):

Type 2 Diabetes ◽

Renal Function ◽

Disease Progression ◽

Risk Scores ◽

Predictive Utility ◽

Insulin Resistant ◽

Age Related ◽

Cardiovascular Outcome Trial ◽

Cv Disease

Objective To assess the reproducibility and clinical utility of clustering-based subtyping of patients with type 2 diabetes (T2D) and established cardiovascular (CV) disease. Methods The cardiovascular outcome trial SAVOR-TIMI 53 (n = 16,492) was used. Analyses focused on T2D patients with established CV disease. Unsupervised machine learning technique called “k-means clustering” was used to divide patients into subtypes. K-means clustering including HbA1c, age of diagnosis, BMI, HOMA2-IR and HOMA2-B was used to assign clusters to the following diabetes subtypes: severe insulin deficient diabetes (SIDD); severe insulin-resistant diabetes (SIRD); mild obesity-related diabetes (MOD); mild age-related diabetes (MARD). We refer these subtypes as “clustering-based diabetes subtypes”. A simulation study using randomly generated data was conducted to understand how correlations between the above variables influence the formation of the cluster-based diabetes subtypes. The predictive utility of clustering-based diabetes subtypes for CV events (3-point MACE), renal function reduction (eGFR decrease >30%) and diabetic disease progression (introduction of additional anti-diabetic medication) were compared with conventional risk scores. Hazard ratios (HR) were estimated by Cox-proportional hazard models. Results In the SAVOR-TIMI 53 trial based dataset, the percentage of the clustering-based T2D subtypes were; SIDD (18%), SIRD (17%), MOD (29%), MARD (37%). Using the simulated dataset, the diabetes subtypes could be largely reproduced from a log-normal distribution when including known correlations between variables. The predictive utility of clustering-based diabetic subtypes on CV events, renal function reduction, and diabetic disease progression did not show an advantage compared to conventional risk scores. Conclusions The consistent reproduction of four clustering-based T2D subtypes can be explained by the correlations between the variables used for clustering. Subtypes of T2D based on clustering had limited advantage compared to conventional risk scores to predict clinical outcome in patients with T2D and established CV disease.

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Insulin Resistance as a Predictor of Age-Related Diseases

The Journal of Clinical Endocrinology & Metabolism ◽

10.1210/jcem.86.8.7763 ◽

2001 ◽

Vol 86 (8) ◽

pp. 3574-3578 ◽

Cited By ~ 259

Author(s):

Francesco S. Facchini ◽

Nancy Hua ◽

Fahim Abbasi ◽

Gerald M. Reaven

Keyword(s):

Insulin Resistance ◽

Type 2 Diabetes ◽

Coronary Heart Disease ◽

Heart Disease ◽

Proportional Hazards ◽

Clinical Event ◽

Insulin Resistant ◽

Clinical Events ◽

Age Related

The current study was initiated to evaluate the ability of insulin resistance to predict a variety of age-related diseases. Baseline measurements of insulin resistance and related variables were made between 1988–1995 in 208 apparently healthy, nonobese (body mass index < 30 kg/m2) individuals, who were then evaluated 4–11 yr later (mean ± sem = 6.3 ± 0.2 yr) for the appearance of the following age-related diseases: hypertension, coronary heart disease, stroke, cancer, and type 2 diabetes. The effect of insulin resistance on the development of clinical events was evaluated by dividing the study group into tertiles of insulin resistance at baseline and comparing the events in these 3 groups. Clinical endpoints (n = 40) were identified in 37 individuals (18%) of those evaluated, including 12 with hypertension, 3 with hypertension + type 2 diabetes, 9 with cancer, 7 with coronary heart disease, 4 with stroke, and 2 with type 2 diabetes. Twenty-eight out of the total 40 clinical events were seen in 25 individuals (36%) in the most insulin-resistant tertile, with the other 12 occurring in the group with an intermediate degree of insulin resistance. Furthermore, insulin resistance was an independent predictor of all clinical events, using both multiple logistic regression and Cox’s proportional hazards analysis. The fact that an age-related clinical event developed in approximately 1 out of 3 healthy individuals in the upper tertile of insulin resistance at baseline, followed for an average of 6 yr, whereas no clinical events were observed in the most insulin-sensitive tertile, should serve as a strong stimulus to further efforts to define the role of insulin resistance in the genesis of age-related diseases.

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Heart failure with preserved ejection fraction in patients with type 2 diabetes mellitus: pathophysiology and treatment options

Medical Herald of the South of Russia ◽

10.21886/2219-8075-2021-12-2-6-15 ◽

2021 ◽

Vol 12 (2) ◽

pp. 6-15

Author(s):

A. A. Borisov ◽

A. D. Gvozdeva ◽

F. T. Ageev

Keyword(s):

Diabetes Mellitus ◽

Heart Failure ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Ejection Fraction ◽

Treatment Options ◽

Specific Treatment ◽

Preserved Ejection Fraction ◽

Patients With Heart Failure

Type 2 diabetes mellitus is known to increase the risk of the development of heart failure with preserved ejection fraction and worsen its symptoms. To date, no specific treatment has been shown to reduce morbidity and mortality in patients with heart failure with preserved ejection fraction. In this review, the authors summarized the existing evidence on how diabetes mellitus can promote the development and progression of heart failure with preserved ejection fraction. The authors also addressed medications including experimental ones that can potentially be beneficial in patients of this group.

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The Association between Antidiabetic Agents and Leukocyte Telomere Length in the Novel Classification of Type 2 Diabetes Mellitus

Gerontology ◽

10.1159/000511362 ◽

2020 ◽

pp. 1-9

Author(s):

Jiaojiao Huang ◽

Xuemin Peng ◽

Kun Dong ◽

Jing Tao ◽

Yan Yang

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Type 2 Diabetes Mellitus ◽

Telomere Length ◽

The Novel ◽

Telomere Attrition ◽

Insulin Resistant ◽

Age Related

Aims: This study aimed to explore the new role of telomere length (TL) in the novel classification of type 2 diabetes mellitus (T2DM) patients driven by cluster analysis. Materials and Methods: A total of 541 T2DM patients were divided into 4 subgroups by k-means analysis: mild obesity-related diabetes (MOD), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), and mild age-related diabetes (MARD). After patients with insufficient data were excluded, further analysis was conducted on 246 T2DM patients. The TL was detected using telomere restriction fragment, and the related diabetic indexes were also measured by clinical standard procedures. Results: The MARD group had significantly shorter TLs than the MOD and SIDD groups. Then, we subdivided all T2DM patients into the MARD and NONMARD groups, which included the MOD, SIDD, and SIRD groups. The TLs of the MARD group, associated with age, were discovered to be significantly shorter than those of the NONMARD group (p = 0.0012), and this difference in TL disappeared after metformin (p = 0.880) and acarbose treatment (p = 0.058). The linear analysis showed that metformin can more obviously reduce telomere shortening in the MARD group (r = 0.030, 95% CI 0.010–0.051, p = 0.004), and acarbose can more apparently promote telomere attrition in the SIRD group (r = –0.069, 95% CI –0.100 to –0.039, p< 0.001) compared with other T2DM patients after adjusting for age and gender. Conclusions: The MARD group was found to have shorter TLs and benefit more from the antiaging effect of metformin than other T2DM. Shorter TLs were observed in the SIRD group after acarbose use.

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Type 2 Diabetes Mellitus (T2DM) may have Four Subtypes Beneficial for Adequate Treatment

Asploro Journal of Biomedical and Clinical Case Reports ◽

10.36502/2021/asjbccr.6226 ◽

2021 ◽

Vol 4 (1) ◽

pp. 38-41

Author(s):

Bando H

Keyword(s):

Type 2 Diabetes ◽

Diabetes Type 2 ◽

Adequate Treatment ◽

Insulin Resistant ◽

Age Related ◽

Cluster A ◽

Diabetic Treatment ◽

Mild Obesity

Diabetes includes various heterogeneous factors. Similar to subtypes of type 1 diabetes, type 2 diabetes may show four subtype clusters. They are cluster A: severe insulin-deficient diabetes, B: severe insulin-resistant diabetes, C: mild obesity-related diabetes, and D: mild age-related diabetes. Comparing them, the prevalence of nephropathy and cardiovascular events was highest in the cluster A. Reference data are i) the ratio of cluster A-D is 18.7%, 23.7%, 21.1%, 36.4%, ii) HbA1c for A-D is 11.05%, 8.17%, 8.49%, 7.95%, iii) event ratio of MACE is 14.4%, 10.6%, 11.4%, 9.1%. Future diabetic treatment is hopefully provided suitable for each subtype.

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Novel subgroups of type 2 diabetes and their association with microvascular outcomes in an Asian Indian population: a data-driven cluster analysis: the INSPIRED study

BMJ Open Diabetes Research & Care ◽

10.1136/bmjdrc-2020-001506 ◽

2020 ◽

Vol 8 (1) ◽

pp. e001506 ◽

Cited By ~ 3

Author(s):

Ranjit Mohan Anjana ◽

Viswanathan Baskar ◽

Anand Thakarakkattil Narayanan Nair ◽

Saravanan Jebarani ◽

Moneeza Kalhan Siddiqui ◽

...

Keyword(s):

Type 2 Diabetes ◽

Asian Indian ◽

Indian Population ◽

Microvascular Complications ◽

Data Set ◽

Insulin Resistant ◽

Age Related ◽

Increased Risk ◽

Asian Indian Population

IntroductionType 2 diabetes is characterized by considerable heterogeneity in its etiopathogenesis and clinical presentation. We aimed to identify clusters of type 2 diabetes in Asian Indians and to look at the clinical implications and outcomes of this clustering.Research design and methodsFrom a network of 50 diabetes centers across nine states of India, we selected 19 084 individuals with type 2 diabetes (aged 10–97 years) with diabetes duration of less than 5 years at the time of first clinic visit and performed k-means clustering using the following variables: age at diagnosis, body mass index, waist circumference, glycated hemoglobin, serum triglycerides, serum high-density lipoprotein cholesterol and C peptide (fasting and stimulated). This was then validated in a national epidemiological data set of representative individuals from 15 states across India.ResultsWe identified four clusters of patients, differing in phenotypic characteristics as well as disease outcomes: cluster 1 (Severe Insulin Deficient Diabetes, SIDD), cluster 2 (Insulin Resistant Obese Diabetes, IROD), cluster 3 (Combined Insulin Resistant and Deficient Diabetes, CIRDD) and cluster 4 (Mild Age-Related Diabetes, MARD). While SIDD and MARD are similar to clusters reported in other populations, IROD and CIRDD are novel clusters. Cox proportional hazards showed that SIDD had the highest hazards for developing retinopathy, followed by CIRDD, while CIRDD had the highest hazards for kidney disease.ConclusionsCompared with previously reported clustering, we show two novel subgroups of type 2 diabetes in the Asian Indian population with important implications for prognosis and management. The coexistence of insulin deficiency and insulin resistance seems to be peculiar to the Asian Indian population and is associated with an increased risk of microvascular complications.

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Chronic kidney disease in patients with diabetes mellitus

Endocrine Connections ◽

10.1530/ec-21-0097 ◽

2021 ◽

Vol 10 (5) ◽

pp. R151-R159

Author(s):

Espen Nordheim ◽

Trond Geir Jenssen

Keyword(s):

Diabetes Mellitus ◽

Type 2 Diabetes ◽

Chronic Kidney Disease ◽

Kidney Disease ◽

Treatment Options ◽

Specific Treatment ◽

Patients With Diabetes ◽

Concomitant Condition

Chronic kidney disease is a common complication and concomitant condition of diabetes mellitus. The treatment of patients with diabetes and chronic kidney disease, including intensive control of blood sugar and blood pressure, has been very similar for type 1 and type 2 diabetes patients. New therapeutic targets have shown promising results and may lead to more specific treatment options for patients with type 1 and type 2 diabetes.

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Roles of plasma leptin and resistin in novel subgroups of type 2 diabetes driven by cluster analysis

Lipids in Health and Disease ◽

10.1186/s12944-022-01623-z ◽

2022 ◽

Vol 21 (1) ◽

Author(s):

Xuemin Peng ◽

Jiaojiao Huang ◽

Huajie Zou ◽

Bei Peng ◽

Sanshan Xia ◽

...

Keyword(s):

Type 2 Diabetes ◽

Diabetic Nephropathy ◽

Statistical Significance ◽

Area Under The Curve ◽

Roc Curves ◽

Enzyme Linked Immunosorbent Assay ◽

Insulin Resistant ◽

Age Related ◽

Plasma Leptin

Abstract Background A novel classification has been introduced to promote precision medicine in diabetes. The current study aimed to investigate the relationship between leptin and resistin levels with novel refined subgroups in patients with type 2 diabetes mellitus (T2DM). Methods The k-means analysis was conducted to cluster 541 T2DM patients into the following four subgroups: mild obesity-related diabetes (MOD), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD) and mild age-related diabetes (MARD). Individuals meeting the exclusion criteria were eliminated, the data for 285 patients were analyzed. Characteristics were determined using various clinical parameters. Both the leptin and resistin levels were determined using enzyme-linked immunosorbent assay. Results The highest levels of plasma leptin were in the MOD group with relatively lower levels in the SIDD and SIRD groups (P < 0.001). The SIRD group had a higher resistin concentration than the MARD group (P = 0.024) while no statistical significance in resistin levels was found between the SIDD and MOD groups. Logistic regression demonstrated that plasma resistin was associated with a higher risk of diabetic nephropathy (odds ratios (OR) = 2.255, P = 0.001). According to receiver operating characteristic (ROC) curves, the area under the curve (AUC) of resistin (0.748, 95% CI 0.610–0.887) was significantly greater than that of HOMA2-IR (0.447, 95% CI 0.280–0.614) (P < 0.05) for diabetic nephropathy in the SIRD group. Conclusions Leptin levels were different in four subgroups of T2DM and were highest in the MOD group. Resistin was elevated in the SIRD group and was closely related to diabetic nephropathy.

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