scholarly journals A novel diabetes typology: towards precision diabetology from pathogenesis to treatment

Diabetologia ◽  
2022 ◽  
Author(s):  
Christian Herder ◽  
Michael Roden
Keyword(s):  
Clinical Features ◽  
Autoimmune Diabetes ◽  
Routine Care ◽  
Insulin Resistant ◽  
Open Questions ◽  
Age Related ◽  
The Stability ◽  
Mild Obesity ◽  
Insight Into

AbstractThe current classification of diabetes, based on hyperglycaemia, islet-directed antibodies and some insufficiently defined clinical features, does not reflect differences in aetiological mechanisms and in the clinical course of people with diabetes. This review discusses evidence from recent studies addressing the complexity of diabetes by proposing novel subgroups (subtypes) of diabetes. The most widely replicated and validated approach identified, in addition to severe autoimmune diabetes, four subgroups designated severe insulin-deficient diabetes, severe insulin-resistant diabetes, mild obesity-related diabetes and mild age-related diabetes subgroups. These subgroups display distinct patterns of clinical features, disease progression and onset of comorbidities and complications, with severe insulin-resistant diabetes showing the highest risk for cardiovascular, kidney and fatty liver diseases. While it has been suggested that people in these subgroups would benefit from stratified treatments, RCTs are required to assess the clinical utility of any reclassification effort. Several methodological and practical issues also need further study: the statistical approach used to define subgroups and derive recommendations for diabetes care; the stability of subgroups over time; the optimal dataset (e.g. phenotypic vs genotypic) for reclassification; the transethnic generalisability of findings; and the applicability in clinical routine care. Despite these open questions, the concept of a new classification of diabetes has already allowed researchers to gain more insight into the colourful picture of diabetes and has stimulated progress in this field so that precision diabetology may become reality in the future. Graphical abstract

scholarly journals The Identification of Diabetes Mellitus Subtypes Applying Cluster Analysis Techniques: A Systematic Review

2020 ◽  
Vol 17 (24) ◽  
pp. 9523
Author(s):  
Antonio Sarría-Santamera ◽  
Binur Orazumbekova ◽  
Tilektes Maulenkul ◽  
Abduzhappar Gaipov ◽  
Kuralay Atageldiyeva
Keyword(s):  
Diabetes Mellitus ◽  
Systematic Review ◽  
Cluster Analysis ◽  
Autoimmune Diabetes ◽  
Insulin Resistant ◽  
Age Related ◽  
Mild Obesity ◽  
Diabetes Patients

Diabetes Mellitus is a chronic and lifelong disease that incurs a huge burden to healthcare systems. Its prevalence is on the rise worldwide. Diabetes is more complex than the classification of Type 1 and 2 may suggest. The purpose of this systematic review was to identify the research studies that tried to find new sub-groups of diabetes patients by using unsupervised learning methods. The search was conducted on Pubmed and Medline databases by two independent researchers. All time publications on cluster analysis of diabetes patients were selected and analysed. Among fourteen studies that were included in the final review, five studies found five identical clusters: Severe Autoimmune Diabetes; Severe Insulin-Deficient Diabetes; Severe Insulin-Resistant Diabetes; Mild Obesity-Related Diabetes; and Mild Age-Related Diabetes. In addition, two studies found the same clusters, except Severe Autoimmune Diabetes cluster. Results of other studies differed from one to another and were less consistent. Cluster analysis enabled finding non-classic heterogeneity in diabetes, but there is still a necessity to explore and validate the capabilities of cluster analysis in more diverse and wider populations.

scholarly journals Differences in Biomarkers of Inflammation Between Novel Subgroups of Recent-Onset Diabetes

2021 ◽  
Author(s):  
Christian Herder ◽  
Haifa Maalmi ◽  
Klaus Strassburger ◽  
Oana-Patricia Zaharia ◽  
Jacqueline M. Ratter ◽  
...  
Keyword(s):  
Autoimmune Diabetes ◽  
Serum Levels ◽  
Recent Onset ◽  
Insulin Resistant ◽  
Onset Diabetes ◽  
Age Related ◽  
Multiple Biomarkers ◽  
Adult Onset Diabetes ◽  
Clustering Approach ◽  
Mild Obesity

A novel clustering approach identified five subgroups of diabetes with distinct progression trajectories of complications. We hypothesized that these subgroups differ in multiple biomarkers of inflammation. Serum levels of 74 biomarkers of inflammation were measured in 414 individuals with recent adult-onset diabetes from the German Diabetes Study (GDS) allocated to five subgroups based on data-driven analysis. Pairwise differences between subgroups for biomarkers were assessed with generalized linear mixed models before (model 1) and after adjustment (model 2) for the clustering variables. Participants were assigned to five subgroups: severe autoimmune diabetes (SAID, 21%), severe insulin-deficient diabetes (SIDD, 3%), severe insulin-resistant diabetes (SIRD, 9%), mild obesity-related diabetes (MOD, 32%) and mild age-related diabetes (MARD, 35%). In model 1, 23 biomarkers showed ≥1 pairwise difference between subgroups (Bonferroni-corrected p<0.0007). Biomarker levels were generally highest in SIRD and lowest in SIDD. All 23 biomarkers correlated with ≥1 of the clustering variables. In model 2, three biomarkers (CASP-8, EN-RAGE, IL-6) showed at least one pairwise difference between subgroups (e.g. lower CASP8, EN-RAGE and IL-6 in SIDD vs. all other subgroups, all p<0.0007). Thus, novel diabetes subgroups show multiple differences in biomarkers of inflammation, underlining a prominent role of inflammatory pathways in particular in SIRD.

scholarly journals Differences in Biomarkers of Inflammation Between Novel Subgroups of Recent-Onset Diabetes

2021 ◽  
Author(s):  
Christian Herder ◽  
Haifa Maalmi ◽  
Klaus Strassburger ◽  
Oana-Patricia Zaharia ◽  
Jacqueline M. Ratter ◽  
...  
Keyword(s):  
Autoimmune Diabetes ◽  
Serum Levels ◽  
Recent Onset ◽  
Insulin Resistant ◽  
Onset Diabetes ◽  
Age Related ◽  
Multiple Biomarkers ◽  
Adult Onset Diabetes ◽  
Clustering Approach ◽  
Mild Obesity

A novel clustering approach identified five subgroups of diabetes with distinct progression trajectories of complications. We hypothesized that these subgroups differ in multiple biomarkers of inflammation. Serum levels of 74 biomarkers of inflammation were measured in 414 individuals with recent adult-onset diabetes from the German Diabetes Study (GDS) allocated to five subgroups based on data-driven analysis. Pairwise differences between subgroups for biomarkers were assessed with generalized linear mixed models before (model 1) and after adjustment (model 2) for the clustering variables. Participants were assigned to five subgroups: severe autoimmune diabetes (SAID, 21%), severe insulin-deficient diabetes (SIDD, 3%), severe insulin-resistant diabetes (SIRD, 9%), mild obesity-related diabetes (MOD, 32%) and mild age-related diabetes (MARD, 35%). In model 1, 23 biomarkers showed ≥1 pairwise difference between subgroups (Bonferroni-corrected p<0.0007). Biomarker levels were generally highest in SIRD and lowest in SIDD. All 23 biomarkers correlated with ≥1 of the clustering variables. In model 2, three biomarkers (CASP-8, EN-RAGE, IL-6) showed at least one pairwise difference between subgroups (e.g. lower CASP8, EN-RAGE and IL-6 in SIDD vs. all other subgroups, all p<0.0007). Thus, novel diabetes subgroups show multiple differences in biomarkers of inflammation, underlining a prominent role of inflammatory pathways in particular in SIRD.

Bone Dysplasias

2018 ◽  
Author(s):  
Jürgen W. Spranger ◽  
Paula W. Brill ◽  
Christine Hall ◽  
Gen Nishimura ◽  
Andrea Superti-Furga ◽  
...  
Keyword(s):  
Bone Density ◽  
Clinical Features ◽  
Differential Diagnoses ◽  
Short List ◽  
Age Related ◽  
Bone Dysplasias ◽  
Text Presentation ◽  
Skeletal Disorders

This is a unique atlas presenting age-related radiographs on more than 250 rare constitutional skeletal diseases (dysplasias, dysostoses, osteolyses, disorders of bone density, and more) focusing on diagnostically essential radiographic and clinical features. Each chapter is supplemented with prognostic and therapeutic information, a guide to differential diagnoses, and a short list of the most relevant publications. A major advantage is the systematic conformation of chapters, sparing the reader a cumbersome read-through of longer text. Presentation in accordance with the most recent International Nosology and Classification of Genetic Skeletal Disorders.

scholarly journals Aetiological differences between novel subtypes of diabetes derived from genetic associations

2020 ◽  
Author(s):  
Dina Mansour Aly ◽  
Om Prakash Dwivedi ◽  
Rashmi B Prasad ◽  
Annemari Karajamaki ◽  
Rebecka Hjort ◽  
...  
Keyword(s):  
Insulin Secretion ◽  
Family History ◽  
Autoimmune Diabetes ◽  
Genetic Risk Score ◽  
Strong Association ◽  
Genetic Associations ◽  
Insulin Resistant ◽  
Age Related ◽  
Patients With Diabetes ◽  
History Of

Background: Type 2 diabetes (T2D) is a multi-organ disease defined by hyperglycemia resulting from different disease mechanisms. Using clinical parameters measured at diagnosis (age, BMI, HbA1c, HOMA2-B, HOMA2-IR and GAD autoantibodies) adult patients with diabetes have been reproducibly clustered into five subtypes, that differed clinically with respect to disease progression and outcomes.1 In this study we use genetic information to investigate if these subtypes have distinct underlying genetic drivers. Methods: Genome-wide association (GWAS) and genetic risk score (GRS) analysis was performed in Swedish (N=12230) and Finnish (N=4631) cohorts. Family history was recorded by questionnaires. Results: Severe insulin-deficient diabetes (SIDD) and mild obesity-related diabetes (MOD) groups had the strongest family history of T2D. A GRS including known T2D loci was strongly associated with SIDD (OR per 1 SD increment [95% CI]=1.959 [1.814-2.118]), MOD (OR 1.726 [1.607-1.855]) and mild age-related diabetes (MARD) (OR 1.771 [1.671-1.879]), whereas it was less strongly associated with severe insulin-resistant diabetes (SIRD, OR 1.244 [1.157-1.337]), which was similar to severe autoimmune diabetes (SAID, OR 1.282 [1.160-1.418]). SAID showed strong association with the GRS for T1D, whereas the non-autoimmune subtype SIDD was most strongly associated with the GRS for insulin secretion rate (P<7.43x10-9). SIRD showed no association with variants in TCF7L2 or any GRS reflecting insulin secretion. Instead, only SIRD was associated with GRS for fasting insulin (P=3.10x10-8). Finally, a T2D locus, rs10824307 near the ZNF503 gene was uniquely associated with MOD (ORmeta=1.266 (1.170-1.369), P=4.3x10-9). Conclusions: New diabetes subtypes have partially different genetic backgrounds and subtype-specific risk loci can be identified. Especially the SIRD subtype stands out by having lower heritability and less involvement of beta-cell related pathways in its pathogenesis.

scholarly journals Leukocyte Counts and T Cell Frequencies Differ Between Novel Subgroups of Diabetes and Associate with Metabolic Parameters and Biomarkers of Inflammation

2021 ◽  
Author(s):  
Jacqueline M. Ratter-Rieck ◽  
Haifa Maalmi ◽  
Sandra Trenkamp ◽  
Oana-Patricia Zaharia ◽  
Wolfgang Rathmann ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Regulatory T Cells ◽  
Immune Cell ◽  
Autoimmune Diabetes ◽  
Cell Types ◽  
Recent Onset ◽  
Insulin Resistant ◽  
Cell Counts ◽  
Age Related

Frequencies of circulating immune cells are altered in type 1 and type 2 diabetes compared with healthy individuals and associate with insulin sensitivity, glycemic control and lipid levels. This study aimed to determine whether specific immune cell types are associated with novel diabetes subgroups. We analyzed automated white blood cell counts (n=669) and flow cytometry data (n=201) of participants of the German Diabetes Study with recent-onset (<1 year) diabetes, who were allocated to five subgroups based on data-driven analysis of clinical variables. Leukocyte numbers were highest in severe insulin-resistant diabetes (SIRD) and moderate obesity-related diabetes (MOD) and lowest in severe autoimmune diabetes (SAID). CD4<sup>+</sup> T cell frequencies were higher in SIRD vs. SAID, MOD and mild age-related diabetes (MARD), and frequencies of CCR4<sup>+</sup> regulatory T cells were higher in SIRD vs. SAID and MOD and MARD vs. SAID. Pairwise differences between subgroups were partially explained by differences in clustering variables. Frequencies of CD4<sup>+</sup> T cells were positively associated with age, BMI, HOMA2-B and HOMA2-IR, and frequencies of CCR4<sup>+</sup> regulatory T cells with age, HOMA2-B and HOMA2-IR. In conclusion, different leukocyte profiles exist between novel diabetes subgroups and suggest distinct inflammatory processes in these diabetes subgroups.

Are the Different Diabetes Subgroups Correlated With All-Cause, Cancer-Related, and Cardiovascular-Related Mortality?

2020 ◽  
Vol 105 (12) ◽  
pp. e4240-e4251
Author(s):  
Peng-Fei Li ◽  
Wei-Liang Chen
Keyword(s):  
Cancer Mortality ◽  
Autoimmune Diabetes ◽  
Primary Outcome Measure ◽  
Nhanes Iii ◽  
P Value ◽  
Data Set ◽  
Insulin Resistant ◽  
Age Related ◽  
Hazard Ratios ◽  
Related Mortality

Abstract Context Numerous studies have shown that cardiovascular disease (CVD) represents the most important cause of mortality among people with diabetes mellitus (DM). However, no studies have evaluated the risk of CVD-related mortality among different DM subgroups. Objective We aimed to examine all-cause, CVD-related, and cancer-related mortality for different DM subgroups. Design, Setting, Patients, and Interventions We included participants (age ≥ 20 years) from the National Health and Nutrition Examination Survey III (NHANES III) data set. We evaluated the risks of all-cause and cause-specific (CVD and cancer) mortality among 5 previously defined diabetes subgroups: severe autoimmune diabetes (SAID), severe insulin-deficient diabetes (SIDD), severe insulin-resistant diabetes (SIRD), mild obesity-related diabetes (MOD), and mild age-related diabetes (MARD). Primary Outcome Measure The hazard ratios (HRs) for all-cause and cause-specific (CVD and cancer) mortality were measured for each of the 5 DM subgroups. We also evaluated the odds ratios (ORs) for retinopathy and nephropathy in each subgroup. Results A total of 712 adults were enrolled and the median follow-up time was 12.71 years (range, 0.25-18.08 years). The number of deaths in the 5 subgroups (SAID, SIDD, SIRD, MOD, and MARD) were 50, 75, 64, 7, and 18, respectively, and the number of CVD-related deaths in the 5 subgroups was 29, 30, 26, 2, and 11, respectively. Compared to the MOD subgroup, the adjusted HRs and 95% CIs of CVD-related mortality for the SAID, SIDD, SIRD, and MARD subgroups were 3.23 (95% CI, 0.77-13.61), 2.87 (95% CI, 0.68-12.06), 2.23 (95% CI, 0.53-9.50), and 4.75 (95% CI, 1.05-21.59), respectively (the HR for the MARD subgroup had a P value of .04). In addition, compared to the MARD subgroup, the adjusted ORs and 95% CIs for retinopathy in the SAID and SIDD groups were 2.38 (95% CI, 1.13-5.01, P = .02) and 3.34 (95% CI, 1.17-6.88, P = .001), respectively. The ORs for nephropathy were nonsignificant. Conclusions Our study of patients from the NHANES III data set indicated that among the different DM subgroups, the MARD subgroup tended to have a higher CVD-related mortality than the MOD subgroup. The all-cause and cancer-related mortality rates were similar across the different diabetes subgroups. In addition, compared to the MARD subgroup, the SAID and SIDD subgroups had a higher retinopathy risk, but there was no difference in nephropathy among the subgroups.

scholarly journals Leukocyte Counts and T Cell Frequencies Differ Between Novel Subgroups of Diabetes and Associate with Metabolic Parameters and Biomarkers of Inflammation

2021 ◽  
Author(s):  
Jacqueline M. Ratter-Rieck ◽  
Haifa Maalmi ◽  
Sandra Trenkamp ◽  
Oana-Patricia Zaharia ◽  
Wolfgang Rathmann ◽  
...  
Keyword(s):  
T Cells ◽  
T Cell ◽  
Regulatory T Cells ◽  
Immune Cell ◽  
Autoimmune Diabetes ◽  
Cell Types ◽  
Recent Onset ◽  
Insulin Resistant ◽  
Cell Counts ◽  
Age Related

Frequencies of circulating immune cells are altered in type 1 and type 2 diabetes compared with healthy individuals and associate with insulin sensitivity, glycemic control and lipid levels. This study aimed to determine whether specific immune cell types are associated with novel diabetes subgroups. We analyzed automated white blood cell counts (n=669) and flow cytometry data (n=201) of participants of the German Diabetes Study with recent-onset (<1 year) diabetes, who were allocated to five subgroups based on data-driven analysis of clinical variables. Leukocyte numbers were highest in severe insulin-resistant diabetes (SIRD) and moderate obesity-related diabetes (MOD) and lowest in severe autoimmune diabetes (SAID). CD4<sup>+</sup> T cell frequencies were higher in SIRD vs. SAID, MOD and mild age-related diabetes (MARD), and frequencies of CCR4<sup>+</sup> regulatory T cells were higher in SIRD vs. SAID and MOD and MARD vs. SAID. Pairwise differences between subgroups were partially explained by differences in clustering variables. Frequencies of CD4<sup>+</sup> T cells were positively associated with age, BMI, HOMA2-B and HOMA2-IR, and frequencies of CCR4<sup>+</sup> regulatory T cells with age, HOMA2-B and HOMA2-IR. In conclusion, different leukocyte profiles exist between novel diabetes subgroups and suggest distinct inflammatory processes in these diabetes subgroups.

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

Gerontology ◽  
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

<b><i>Aims:</i></b> 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. <b><i>Materials and Methods:</i></b> A total of 541 T2DM patients were divided into 4 subgroups by <i>k</i>-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. <b><i>Results:</i></b> 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 (<i>p</i> = 0.0012), and this difference in TL disappeared after metformin (<i>p</i> = 0.880) and acarbose treatment (<i>p</i> = 0.058). The linear analysis showed that metformin can more obviously reduce telomere shortening in the MARD group (<i>r</i> = 0.030, 95% CI 0.010–0.051,<i> p</i> = 0.004), and acarbose can more apparently promote telomere attrition in the SIRD group (<i>r</i> = –0.069, 95% CI –0.100 to –0.039, <i>p</i>&#x3c; 0.001) compared with other T2DM patients after adjusting for age and gender. <b><i>Conclusions:</i></b> 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.

scholarly journals Trends in prevalence of diabetes subgroups in U.S. adults: A data-driven cluster analysis spanning three decades from NHANES (1988-2018)

2020 ◽  
Author(s):  
Neftali Eduardo Antonio-Villa ◽  
Luisa Fernández-Chirino ◽  
Arsenio Vargas-Vázquez ◽  
Jessica Paola Bahena-López ◽  
Carlos A Aguilar-Salinas ◽  
...  
Keyword(s):  
Mexican Americans ◽  
Population Aging ◽  
Data Driven ◽  
Significant Heterogeneity ◽  
Obesity Prevalence ◽  
Insulin Resistant ◽  
Age Related ◽  
The Us ◽  
Mild Obesity ◽  
The U.S

AIMS: Data-driven diabetes subgroups have been proposed as an alternative to address diabetes heterogeneity; changes in trends for these subgroups have not previously been reported. Here, we analyzed trends of diabetes subgroups, stratified by sex, race, education level, and age categories in the U.S. METHODS: We used data from consecutive NHANES cycles spanning the 1988-2018 period. Diabetes subgroups (mild obesity-related [MOD], severe-insulin deficient [SIID], severe-insulin resistant [SIRD], and age-related diabetes [MARD]) were classified using self-normalizing neural networks. SAID was assessed for NHANES-III cycles. Prevalence was estimated using examination sample weights considering 2-year cycles (biannual change [B.C.]) to evaluate trends. RESULTS: Diabetes prevalence in the US increased from 7.5% (95%CI 7.1-7.9) in 1988-1989 to 13.9% (95%CI 13.4-14.4) in 2016-2018 (BC 1.09%, 95%CI 0.98-1.31, p<0.001). Non-Hispanic Blacks had the highest prevalence. Overall, MOD, MARD, and SIID had the highest increase during the studied period. Non-Hispanic Blacks had a sharp increase in MARD and SIID, Mexican Americans in SIID, and non-Hispanic Whites in MARD. Males, subjects with primary school/no-education, and adults aged 40-64 years had the highest increase in MOD prevalence. Trends in diabetes subgroups sustained after stratification by body-mass index categories. CONCLUSIONS: The prevalence of diabetes and its data-driven subgroups in the U.S. has increased from 1988-2018. These trends were different across sex, ethnicities, education, and age categories, indicating significant heterogeneity in diabetes within the U.S. Sex-specific factors, population aging, and socioeconomic aspects, together with obesity prevalence increase, could be implicated in the uprising trends of diabetes in the U.S.

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