Biomarkers of Inflammation and Glomerular Filtration Rate in Individuals with Recent-Onset Type 1 and Type 2 Diabetes

Immune cell signatures and inflammatory mediators: unraveling their genetic impact on chronic kidney disease through Mendelian randomization

Prior research has established associations between immune cells, inflammatory proteins, and chronic kidney disease (CKD). Our Mendelian randomization study aims to elucidate the genetic causal relationships among these factors and CKD. We applied Mendelian randomization using genetic variants associated with CKD from a large genome-wide association study (GWAS) and inflammatory markers from a comprehensive GWAS summary. The causal links between exposures (immune cell subtypes and inflammatory proteins) and CKD were primarily analyzed using the inverse variance-weighted, supplemented by sensitivity analyses, including MR-Egger, weighted median, weighted mode, and MR-PRESSO. Our analysis identified both absolute and relative counts of CD28 + CD45RA + CD8 + T cell (OR = 1.01; 95% CI = 1.01-1.02; p < 0.001, FDR = 0.018) (OR = 1.01; 95% CI = 1.00-1.01; p < 0.001, FDR = 0.002), CD28 on CD39 + CD8 + T cell(OR = 0.97; 95% CI = 0.96-0.99; p < 0.001, FDR = 0.006), CD16 on CD14-CD16 + monocyte (OR = 1.02; 95% CI = 1.01-1.03; p < 0.001, FDR = 0.004) and cytokines, such as IL-17A(OR = 1.11, 95% CI = 1.06-1.16, p < 0.001, FDR = 0.001), and LIF-R(OR = 1.06, 95% CI = 1.02-1.10, p = 0.005, FDR = 0.043) that are genetically predisposed to influence the risk of CKD. Moreover, the study discovered that CKD itself may causatively lead to alterations in certain proteins, including CST5(OR = 1.16, 95% CI = 1.09-1.24, p < 0.001, FDR = 0.001). No evidence of reverse causality was found for any single biomarker and CKD. This comprehensive MR investigation supports a genetic causal nexus between certain immune cell subtypes, inflammatory proteins, and CKD. These findings enhance the understanding of CKD's immunological underpinnings and open avenues for targeted treatments.

Minireview: Understanding and targeting inflammatory, hemodynamic and injury markers for cardiorenal protection in type 1 diabetes

The coexistence of cardiovascular disease (CVD) and diabetic kidney disease (DKD) is common in people with type 1 diabetes (T1D) and is strongly associated with an increased risk of morbidity and mortality. Hence, it is imperative to explore robust tools that can accurately reflect the development and progression of cardiorenal complications. Several cardiovascular and kidney biomarkers have been identified to detect at-risk individuals with T1D. The primary aim of this review is to highlight biomarkers of injury, inflammation, or renal hemodynamic changes that may influence T1D susceptibility to CVD and DKD. We will also examine the impact of approved pharmacotherapies for type 2 diabetes, including renin-angiotensin-aldosterone system (RAAS) inhibitors, sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon-like peptide-1 receptor agonists (GLP-1RAs) on candidate biomarkers for cardiorenal complications in people with T1D and discuss how these changes may potentially mediate kidney and cardiovascular protection. Identifying predictive and prognostic biomarkers for DKD and CVD may highlight potential drug targets to attenuate cardiorenal disease progression, implement novel risk stratification measures in clinical trials, and improve the assessment, diagnosis, and treatment of at-risk individuals with T1D.

Correlates of Skeletal Muscle Mass and Differences Between Novel Subtypes in Recent-Onset Diabetes

CONTEXT

Low skeletal muscle mass (SMM) is associated with long-standing diabetes but little is known about SMM in newly diagnosed diabetes.

OBJECTIVE

We aimed to identify correlates of SMM in recent-onset diabetes and to compare SMM between novel diabetes subtypes.

METHODS

SMM was normalized to body mass index (SMM/BMI) in 842 participants with known diabetes duration of less than 1 year from the German Diabetes Study (GDS). Cross-sectional associations between clinical variables, 79 biomarkers of inflammation, and SMM/BMI were assessed, and differences in SMM/BMI between novel diabetes subtypes were analyzed with different degrees of adjustment for confounders.

RESULTS

Male sex and physical activity were positively associated with SMM/BMI, whereas associations of age, BMI, glycated hemoglobin A1c, homeostatic model assessment for β-cell function, and estimated glomerular filtration rate with SMM/BMI were inverse (all P < .05; model r2 = 0.82). Twenty-three biomarkers of inflammation showed correlations with SMM/BMI after adjustment for sex and multiple testing (all P < .0006), but BMI largely explained these correlations. In a sex-adjusted analysis, individuals with severe autoimmune diabetes had a higher SMM/BMI whereas individuals with severe insulin-resistant diabetes and mild obesity-related diabetes had a lower SMM/BMI than all other subtypes combined. However, differences were attenuated after adjustment for the clustering variables.

CONCLUSION

SMM/BMI differs between diabetes subtypes and may contribute to subtype differences in disease progression. Of note, clinical variables rather than biomarkers of inflammation explain most of the variation in SMM/BMI.

Type 1 and Type 2 Diabetes Mellitus: Commonalities, Differences and the Importance of Exercise and Nutrition

Diabetes mellitus represents a group of physiological dysfunctions characterized by hyperglycaemia resulting directly from insulin resistance (in the case of type 2 diabetes mellitus-T2DM), inadequate insulin secretion/production, or excessive glucagon secretion (in type 1 diabetes mellitus-T1DM) [...].

Effects of Short- And Medium-Term Exposures to Lower Air Temperature on 71 Novel Biomarkers of Subclinical Inflammation: Results from the KORA F4 Study

Increasing evidence has revealed that exposure to low temperatures is linked to a higher risk of chronic diseases and death; however, the mechanisms underlying the observed associations are still poorly understood. We performed a cross-sectional analysis with 1115 participants from the population-based KORA F4 study, which was conducted in Augsburg, Germany, from 2006 to 2008. Seventy-one inflammation-related protein biomarkers were analyzed in serum using proximity extension assay technology. We employed generalized additive models to explore short- and medium-term effects of air temperature on biomarkers of subclinical inflammation at cumulative lags of 0-1 days, 2-6 days, 0-13 days, 0-27 days, and 0-55 days. We found that short- and medium-term exposures to lower air temperature were associated with higher levels in 64 biomarkers of subclinical inflammation, such as Protein S100-A12 (EN-RAGE), Interleukin-6 (IL-6), Interleukin-10 (IL-10), C-C motif chemokine 28 (CCL28), and Neurotrophin-3 (NT-3). More pronounced associations between lower air temperature and higher biomarker of subclinical inflammation were observed among older participants, people with cardiovascular disease or prediabetes/diabetes, and people exposed to higher levels of air pollution (PM2.5, NO2, and O3). Our findings provide intriguing insight into how low air temperature may cause adverse health effects by activating inflammatory pathways.

Proteomic profiling of longitudinal changes in kidney function among middle-aged and older men and women: the KORA S4/F4/FF4 study

BACKGROUND

Due to the asymptomatic nature of the early stages, chronic kidney disease (CKD) is usually diagnosed at late stages and lacks targeted therapy, highlighting the need for new biomarkers to better understand its pathophysiology and to be used for early diagnosis and therapeutic targets. Given the close relationship between CKD and cardiovascular disease (CVD), we investigated the associations of 233 CVD- and inflammation-related plasma proteins with kidney function decline and aimed to assess whether the observed associations are causal.

METHODS

We included 1140 participants, aged 55-74 years at baseline, from the Cooperative Health Research in the Region of Augsburg (KORA) cohort study, with a median follow-up time of 13.4 years and 2 follow-up visits. We measured 233 plasma proteins using a proximity extension assay at baseline. In the discovery analysis, linear regression models were used to estimate the associations of 233 proteins with the annual rate of change in creatinine-based estimated glomerular filtration rate (eGFRcr). We further investigated the association of eGFRcr-associated proteins with the annual rate of change in cystatin C-based eGFR (eGFRcys) and eGFRcr-based incident CKD. Two-sample Mendelian randomization was used to infer causality.

RESULTS

In the fully adjusted model, 66 out of 233 proteins were inversely associated with the annual rate of change in eGFRcr, indicating that higher baseline protein levels were associated with faster eGFRcr decline. Among these 66 proteins, 21 proteins were associated with both the annual rate of change in eGFRcys and incident CKD. Mendelian randomization analyses on these 21 proteins suggest a potential causal association of higher tumor necrosis factor receptor superfamily member 11A (TNFRSF11A) level with eGFR decline.

CONCLUSIONS

We reported 21 proteins associated with kidney function decline and incident CKD and provided preliminary evidence suggesting a potential causal association between TNFRSF11A and kidney function decline. Further Mendelian randomization studies are needed to establish a conclusive causal association.

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

The 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.

Leukocyte Counts and T-Cell Frequencies Differ Between Novel Subgroups of Diabetes and Are Associated With Metabolic Parameters and Biomarkers of Inflammation

Frequencies of circulating immune cells are altered in those with type 1 and type 2 diabetes compared with healthy individuals and are associated 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 cytometric data (n = 201) of participants in 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 mild obesity-related diabetes (MOD) and lowest in severe autoimmune diabetes (SAID). CD4⁺ T-cell frequencies were higher in SIRD versus SAID, MOD, and mild age-related diabetes (MARD), and frequencies of CCR4⁺ regulatory T cells were higher in SIRD versus SAID and MOD and in MARD versus 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 estimate of β-cell function (HOMA2-B), and HOMA2 estimate of insulin resistance (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.

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

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 cluster analysis. Pairwise differences between subgroups for biomarkers were assessed with generalized linear mixed models before (model 1) and after (model 2) adjustment for the clustering variables. Participants were assigned to five subgroups: severe autoimmune diabetes (21%), severe insulin-deficient diabetes (SIDD) (3%), severe insulin-resistant diabetes (SIRD) (9%), mild obesity-related diabetes (32%), and mild age-related diabetes (35%). In model 1, 23 biomarkers showed one or more pairwise differences between subgroups (Bonferroni-corrected P < 0.0007). Biomarker levels were generally highest in SIRD and lowest in SIDD. All 23 biomarkers correlated with one or more 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.