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Aims: We recently reported that genetic variability in the TKT gene encoding transketolase, a key enzyme in the pentose phosphate pathway, is associated with measures of diabetic sensorimotor polyneuropathy (DSPN) in recent‐onset diabetes. Here, we aimed to substantiate these findings in a population‐based KORA F4 study. Materials and Methods: In this cross‐sectional study, we assessed seven single nucleotide polymorphisms (SNPs) in the transketolase gene in 952 participants from the KORA F4 study with normal glucose tolerance (NGT; n = 394), prediabetes (n = 411), and type 2 diabetes (n = 147). DSPN was defined by the examination part of the Michigan Neuropathy Screening Instrument (MNSI) using the original MNSI > 2 cut‐off and two alternative versions extended by touch/pressure perception (TPP) (MNSI > 3) and by TPP plus cold perception (MNSI > 4). Results: After adjustment for sex, age, BMI, and HbA1c, in type 2 diabetes participants, four out of seven transketolase SNPs were associated with DSPN for all three MNSI versions (all p ≤ 0.004). The odds ratios of these associations increased with extending the MNSI score, for example, OR (95% CI) for SNP rs62255988 with MNSI > 2: 1.99 (1.16–3.41), MNSI > 3: 2.27 (1.26–4.09), and MNSI > 4: 4.78 (2.22–10.26); SNP rs9284890 with MNSI > 2: 2.43 (1.42–4.16), MNSI > 3: 3.46 (1.82–6.59), and MNSI > 4: 4.75 (2.15–10.51). In contrast, no associations were found between transketolase SNPs and the three MNSI versions in the NGT and prediabetes groups. Conclusions: The link of genetic variation in transketolase enzyme to diabetic polyneuropathy corroborated at the population level strengthens the concept suggesting an important role of pathways metabolising glycolytic intermediates in the evolution of diabetic polyneuropathy. [ABSTRACT FROM AUTHOR]

Aims: The aim of this study was to assess associations between neurological biomarkers and distal sensorimotor polyneuropathy (DSPN). Materials and Methods: Cross‐sectional analyses were based on 1032 participants aged 61–82 years from the population‐based KORA F4 survey, 177 of whom had DSPN at baseline. The prevalence of type 2 diabetes was 20%. Prospective analyses used data from 505 participants without DSPN at baseline, of whom 125 had developed DSPN until the KORA FF4 survey. DSPN was defined based on the examination part of the Michigan Neuropathy Screening Instrument. Serum levels of neurological biomarkers were measured using proximity extension assay technology. Associations between 88 biomarkers and prevalent or incident DSPN were estimated using Poisson regression with robust error variance and are expressed as risk ratios (RR) and 95% CI per 1‐SD increase. Results were adjusted for multiple confounders and multiple testing using the Benjamini–Hochberg procedure. Results: Higher serum levels of CTSC (cathepsin C; RR [95% CI] 1.23 (1.08; 1.39), pB‐H = 0.044) and PDGFRα (platelet‐derived growth factor receptor A; RR [95% CI] 1.21 (1.08; 1.35), pB‐H = 0.044) were associated with prevalent DSPN in the total study sample. CDH3, JAM‐B, LAYN, RGMA and SCARA5 were positively associated with DSPN in the diabetes subgroup, whereas GCP5 was positively associated with DSPN in people without diabetes (all pB‐H for interaction <0.05). None of the biomarkers showed an association with incident DSPN (all pB‐H>0.05). Conclusions: This study identified multiple novel associations between neurological biomarkers and prevalent DSPN, which may be attributable to functions of these proteins in neuroinflammation, neural development and myelination. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Background Inflammatory processes have been implicated in the development of chronic kidney disease (CKD). We investigated the association of a large panel of inflammatory biomarkers reflecting aspects of immunity with kidney function and CKD incidence. Methods We used data from two independent population-based studies, KORA F4 (discovery, n  = 1110, mean age 70.3 years, 48.7% male) and ESTHER (replication, n  = 1672, mean age 61.9 years, 43.6% male). Serum levels of biomarkers were measured using proximity extension assay technology. The association of biomarkers with estimated glomerular filtration rate (eGFR) at baseline and with incident CKD was investigated using linear and logistic regression models adjusted for cardiorenal risk factors. Independent results from prospective analyses of both studies were pooled. The significance level was corrected for multiple testing by false-discovery rate (PFDR < 0.05). Results In the KORA F4 discovery study, 52 of 71 inflammatory biomarkers were inversely associated with eGFR based on serum creatinine. Top biomarkers included CD40, TNFRSF9 and IL10RB. Forty-two of these 52 biomarkers were replicated in the ESTHER study. Nine of the 42 biomarkers were associated with incident CKD independent of cardiorenal risk factors in the meta-analysis of the KORA (n  = 142, mean follow-up 6.5 years) and ESTHER (n  = 103, mean follow-up 8 years) studies. Pathway analysis revealed the involvement of inflammatory and immunomodulatory processes reflecting cross-communication of innate and adaptive immune cells. Conclusions Novel and known biomarkers of inflammation were reproducibly associated with kidney function. Future studies should investigate their clinical utility and underlying molecular mechanisms in independent cohorts. [ABSTRACT FROM AUTHOR]

Background Uromodulin is a kidney-specific glycoprotein synthesized in tubular cells of Henle's loop exerting nephroprotective and immunomodulatory functions in the urinary tract. A small amount of uromodulin is also released into the systemic circulation, where its physiological role is unknown. Serum uromodulin (sUmod) has been associated with metabolic risk factors and with cardiovascular events and mortality, where these associations were partly stronger in men than in women. In this study, we investigated the associations of sUmod with biomarkers of subclinical inflammation in a population-based sample of women and men. Methods Associations of sUmod with 10 biomarkers of subclinical inflammation were assessed in 1065 participants of the Cooperative Health Research in the Region of Augsburg (KORA) F4 study aged 62–81 years using linear regression models adjusted for sex, age, body mass index, estimated glomerular filtration rate and diabetes. Analyses were performed in the total study sample and stratified by sex. Results sUmod was inversely associated with white blood cell count, high-sensitive C-reactive protein, interleukin (IL)-6, tumour necrosis factor-α, myeloperoxidase, superoxide dismutase-3, IL-1 receptor antagonist and IL-22 after multivariable adjustment and correction for multiple testing (P < 0.001 for each observation). There was a trend towards a stronger association of sUmod with pro-inflammatory markers in men than in women, with a significant P for sex interaction (<0.001) regarding the relation of sUmod with IL-6. Conclusions sUmod was inversely associated with biomarkers of subclinical inflammation in older participants of the KORA F4 study. The association of sUmod with IL-6 differed between women and men. Future research should focus on whether the immunomodulatory properties of sUmod are one explanation for the association of sUmod with cardiovascular outcomes and mortality. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]