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

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Aetiological differences between novel subtypes of diabetes derived from genetic associations

10.1101/2020.09.29.20203935 ◽

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.

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

Diabetologia ◽

10.1007/s00125-021-05625-x ◽

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

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

10.2337/figshare.15782064.v1 ◽

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+ T cell frequencies were higher in SIRD vs. SAID, MOD and mild age-related diabetes (MARD), and frequencies of CCR4+ 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+ T cells were positively associated with age, BMI, HOMA2-B and HOMA2-IR, and frequencies of CCR4+ 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.

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

10.2337/figshare.14043530.v1 ◽

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.

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A flexible, efficient binomial mixed model for identifying differential DNA methylation in bisulfite sequencing data

10.1101/019562 ◽

2015 ◽

Author(s):

Amanda J Lea ◽

Jenny Tung ◽

Xiang Zhou

Keyword(s):

Dna Methylation ◽

Count Data ◽

Mixed Model ◽

Bisulfite Sequencing ◽

Structured Populations ◽

P Value ◽

Sequencing Data ◽

Data Set ◽

Age Related ◽

Bisulfite Sequencing Data

Identifying sources of variation in DNA methylation levels is important for understanding gene regulation. Recently, bisulfite sequencing has become a popular tool for investigating DNA methylation levels. However, modeling bisulfite sequencing data is complicated by dramatic variation in coverage across sites and individual samples, and because of the computational challenges of controlling for genetic covariance in count data. To address these challenges, we present a binomial mixed model and an efficient, sampling-based algorithm (MACAU: Mixed model association for count data via data augmentation) for approximate parameter estimation and p-value computation. This framework allows us to simultaneously account for both the over-dispersed, count-based nature of bisulfite sequencing data, as well as genetic relatedness among individuals. Using simulations and two real data sets (whole genome bisulfite sequencing (WGBS) data from Arabidopsis thaliana and reduced representation bisulfite sequencing (RRBS) data from baboons), we show that our method provides well-calibrated test statistics in the presence of population structure. Further, it improves power to detect differentially methylated sites: in the RRBS data set, MACAU detected 1.6-fold more age-associated CpG sites than a beta-binomial model (the next best approach). Changes in these sites are consistent with known age-related shifts in DNA methylation levels, and are enriched near genes that are differentially expressed with age in the same population. Taken together, our results indicate that MACAU is an efficient, effective tool for analyzing bisulfite sequencing data, with particular salience to analyses of structured populations. MACAU is freely available at www.xzlab.org/software.html.

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

10.2337/figshare.14043530 ◽

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

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Serum C-reactive protein levels and colorectal cancer mortality.

Journal of Clinical Oncology ◽

10.1200/jco.2013.31.4_suppl.360 ◽

2013 ◽

Vol 31 (4_suppl) ◽

pp. 360-360

Author(s):

Abhishek Goyal ◽

Abby B. Siegel

Keyword(s):

Colorectal Cancer ◽

Cancer Mortality ◽

Risk Groups ◽

Nhanes Iii ◽

Protein Levels ◽

Reactive Protein ◽

Representative Study ◽

Hazard Ratios ◽

Valid Estimate

360 Background: Chronic inflammation has been causally linked to colorectal cancer (CRC), and use of NSAIDs has been associated with reduced risk. Prediagnostic C-reactive protien (CRP) levels, a highly sensitive marker of inflammation, have been weakly associated with increased CRC incidence. However, their relationship with CRC mortality has not been studied well. We hypothesized that elevated baseline CRP levels in general population will predict increased CRC mortality. Methods: This cohort study used CRP data from the Third National Health and Nutrition Examination survey, 1988-94 (NHANES III), with follow-up through 2006. Of the 15,832 eligible adults, NHANES III classified 65% as having CRP levels below detection (≤0.21mg/dL). Using this as the reference, we categorized the remaining participants in three approximately equal groups, and calculated hazard ratios for CRC, all-cancer mortality excluding CRC, and overall mortality due to non-cancer causes. Results: Median follow-up period was 14.2 years. In age adjusted (not shown) and multivariable adjusted models (Table), we observed strong, dose-response associations between CRP levels and CRC mortality. Associations between CRP levels and mortality due to other causes were much weaker. Conclusions: In this large, representative study of U.S. adults, we obtained significantly higher HRs for CRC mortality, as compared to mortality from other cancer and non-cancer causes, making these results unlikely to be explained by residual confounding or other biases. Further, since mortality is a function of both incidence and survival, it provides a more valid estimate of the prognostic value of CRP compared to incidence alone. Further evaluation of CRP may help stratify high risk groups for screening and prognosis, and potentially identify those who might benefit from anti-inflammatory therapy. [Table: see text]

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

International Journal of Environmental Research and Public Health ◽

10.3390/ijerph17249523 ◽

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.

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

10.2337/figshare.15782064 ◽

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

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0599 The Association Between Obstructive Sleep Apnea and Cancer Incidence and Mortality: A Systematic Review and Meta-Analysis

SLEEP ◽

10.1093/sleep/zsaa056.596 ◽

2020 ◽

Vol 43 (Supplement_1) ◽

pp. A229-A229

Author(s):

R Sutherland ◽

J Platt

Keyword(s):

Sleep Apnea ◽

Cancer Incidence ◽

Cancer Mortality ◽

Meta Analysis ◽

Risk Of Bias ◽

P Value ◽

Hazard Ratios ◽

Obstructive Sleep ◽

Incidence And Mortality ◽

Risk Of Cancer

Abstract Introduction Sleep related breathing disorders (SRBD) are common (20% prevalence) in the general population and can have multiple health consequences. There is growing evidence that chronic hypoxia - a key consequence of sleep apnea - is a common feature in solid tumour tissue, therapeutic resistance, tumour progression, and metastasis. However, there is conflicting evidence regarding the association between sleep apnea, cancer incidence, or mortality. A review of all available literature and subsequent meta-analysis was done to clarify these relationships. Methods A thorough literature search was completed using Medline, EMBASE and Web of Science databases. The search resulted in 7222 studies, 1551 duplicates were removed, 5552 studies were removed after abstract screening, and full text review was done on 119 studies, yielding 12 full retrospective cohort studies. The risk of bias was assessed using the Newcastle-Ottawa Scale. Review and data extraction were done in duplicate. Results In the pooled analysis, 9 studies totalling 2,358405 subjects with OSA and 3.97% cancer incidence and 2,442794 subjects without OSA and 3.35% cancer incidence. A random effects model with inverse-variance weighting analysis yielded an unadjusted OR = 1.32 (95% CI: 0.76 - 2.30). After 2 studies with a moderate risk of bias were removed the pooling yielded an OR = 1.89 (95% CI: 0.99 - 3.50). Heterogeneity was high at 99.9% p-value less than 0.01. Meta-regression was then done to assess for the cause(s) of heterogeneity sex, age, or BMI were not significant contributors. A review of 3 studies, which included cancer mortality, was done. Hazard ratios in 2 studies suggested OSA increased the risk of cancer mortality. Hazard ratios also increased with increasing OSA severity. Conclusion Sleep apnea significantly increases cancer mortality and is positively associated with increasing severity. Meta-analysis demonstrated an 86% increase in the unadjusted odds of cancer in those with sleep apnea. However, this result was borderline non-significant with high heterogeneity. Further studies may be helpful in determining the true associations between sleep apnea and cancer. Support None.

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