Skin autofluorescence predicts incident type 2 diabetes, cardiovascular disease and mortality in the general population
van Waateringe RP, Fokkens BT, Slagter SN, van der Klauw MM, van Vliet-Ostaptchouk JV, et al. Diabetologia 2019; 62(2): 269–280
AIMS/HYPOTHESIS: Earlier studies have shown that skin autofluorescence measured with an AGE reader estimates the accumulation of AGEs in the skin, which increases with ageing and is associated with the metabolic syndrome and type 2 diabetes. In the present study, we examined whether the measurement of skin autofluorescence can predict 4-year risk of incident type 2 diabetes, cardiovascular disease (CVD) and mortality in the general population.
METHODS: For this prospective analysis, we included 72 880 participants of the Dutch Lifelines Cohort Study, who underwent baseline investigations between 2007 and 2013, had validated baseline skin autofluorescence values available and were not known to have diabetes or CVD. Individuals were diagnosed with incident type 2 diabetes by self-report or by a fasting blood glucose ≥7.0 mmol/L or HbA1c ≥48 mmol/mol (≥6.5%) at follow-up. Participants were diagnosed as having incident CVD (myocardial infarction, coronary interventions, cerebrovascular accident, transient ischaemic attack, intermittent claudication or vascular surgery) by self-report. Mortality was ascertained using the Municipal Personal Records Database.
RESULTS: After a median follow-up of 4 years (range 0.5–10 years), 1056 participants (1.4%) had developed type 2 diabetes, 1258 individuals (1.7%) were diagnosed with CVD, while 928 (1.3%) had died. Baseline skin autofluorescence was elevated in participants with incident type 2 diabetes and/or CVD and in those who had died (all P< 0.001), compared with individuals who survived and remained free of the two diseases. Skin autofluorescence predicted the development of type 2 diabetes, CVD and mortality, independent of several traditional risk factors, such as the metabolic syndrome, glucose and HbA1c.
CONCLUSIONS/INTERPRETATION: The non-invasive skin autofluorescence measurement is of clinical value for screening for future risk of type 2 diabetes, CVD and mortality, independent of glycaemic measures and the metabolic syndrome.
A renal genetic risk score (GRS) is associated with kidney dysfunction in people with type 2 diabetes
Zusi C, Trombetta M, Bonetti S, Dauriz M, Boselli ML, et al. Diabetes Res Clin Pract 2018; 144: 137–143
This study aims to investigate whether renal and cardiovascular phenotypes in Italian patients with type 2 diabetes (T2D) could be influenced by a number of disease risk SNPs recently found in genome-wide association studies (GWAS). In 1591 Italian subjects with T2D: (1) 47SNPs associated to kidney function and/or chronic kidney disease (CKD) and 49SNPs associated to cardiovascular disease (CVD) risk were genotyped; (2) urinary albumin/creatinine (A/C) ratio, glomerular filtration rate (eGFR) and lipid profile were assessed; (3) a standard electrocardiogram was performed; (4) two genotype risk scores (GRS) were computed (a renal GRS calculated selecting 39 SNPs associated with intermediate traits of kidney damage and a cardiovascular GRS determined selecting 42 SNPs associated to CVD risk phenotypes). After correction for multiple comparisons, the renal GRS was not associated to A/C ratio (P=0.33), but it was significantly related to decreased eGFR (P=0.005). No association between the cardiovascular GRS and electrocardiogram was detected. Thus, in Italian patients with T2D a renal GRS might predict the decline in glomerular function, suggesting that the clock of diabetes associated CKD starts ticking long before hyperglycemia. Our data support the feasibility of gene-based prediction of complications in people with T2D.
Protein markers and risk of type 2 diabetes and prediabetes: a targeted proteomics approach in the KORA F4/FF4 study
Huth C, von Toerne C, Schederecker F, de Las Heras Gala T, Herder C, et al. Eur J Epidemiol 2018: doi: 10.1007/s10654-018-0475-8 [Epub ahead of print]
The objective of the present study was to identify proteins that contribute to pathophysiology and allow prediction of incident type 2 diabetes or incident prediabetes. We quantified 14 candidate proteins using targeted mass spectrometry in plasma samples of the prospective, population-based German KORA F4/FF4 study (6.5-year follow-up). 892 participants aged 42–81 years were selected using a case-cohort design, including 123 persons with incident type 2 diabetes and 255 persons with incident WHO-defined prediabetes. Prospective associations between protein levels and diabetes, prediabetes as well as continuous fasting and 2 h glucose, fasting insulin and insulin resistance were investigated using regression models adjusted for established risk factors. The best predictive panel of proteins on top of a non-invasive risk factor model or on top of HbA1c, age and sex was selected. Mannan-binding lectin serine peptidase (MASP) levels were positively associated with both incident type 2 diabetes and prediabetes. Adiponectin was inversely associated with incident type 2 diabetes. MASP, adiponectin, apolipoprotein A-IV, apolipoprotein C-II, C-reactive protein, and glycosylphosphatidylinositol specific phospholipase D1 were associated with individual continuous outcomes. The combination of MASP, apolipoprotein E (apoE) and adiponectin improved diabetes prediction on top of both reference models, while prediabetes prediction was improved by MASP plus CRP on top of the HbA1c model. In conclusion, our mass spectrometric approach revealed a novel association of MASP with incident type 2 diabetes and incident prediabetes. In combination, MASP, adiponectin and apoE improved type 2 diabetes prediction beyond non-invasive risk factors or HbA1c, age and sex.
Association between circulating tumor necrosis factor-related biomarkers and estimated glomerular filtration rate in type 2 diabetes.
Kamei N, Yamashita M, Nishizaki Y, Yanagisawa N, Nojiri S, et al. Sci Rep 2018; 8(1): 15302
Chronic inflammation plays a crucial role in the development/progression of diabetic kidney disease. The involvement of tumor necrosis factor (TNF)-related biomarkers [TNFα, progranulin (PGRN), TNF receptors (TNFR1 and TNFR2)] and uric acid (UA) in renal function decline was investigated in patients with type 2 diabetes (T2D). Serum TNF-related biomarkers and UA levels were measured in 594 Japanese patients with T2D and an eGFR ≥30 mL/min/1.73 m2. Four TNF-related biomarkers and UA were negatively associated with estimated glomerular filtration rate (eGFR). In a logistic multivariate model, each TNF-related biomarker and UA was associated with lower eGFR (eGFR <60 mL/min/1.73 m2) after adjustment for relevant covariates (basic model). Furthermore, UA and TNF-related biomarkers other than PGRN added a significant benefit for the risk factors of lower eGFR when measured together with a basic model (UA, ΔAUC, 0.049, P<0.001; TNFα, ΔAUC, 0.022, P=0.007; TNFR1, ΔAUC, 0.064, P<0.001; TNFR2, ΔAUC, 0.052, P<0.001) in receiver operating characteristic curve analysis. TNFR ligands were associated with lower eGFR, but the associations were not as strong as those with TNFRs or UA in patients with T2D and an eGFR ≥30 mL/min/1.73 m2.
Plasma endostatin predicts kidney outcomes in patients with type 2 diabetes
Chauhan K, Verghese DA, Rao V, Chan L, Parikh CR, et al. Kidney Int 2019; 95(2): 439–446
Novel biomarkers are needed to predict kidney function decline in patients with type 2 diabetes, especially those with preserved glomerular filtration rate (GFR). There are limited data on the association of markers of endothelial dysfunction with longitudinal GFR decline. We used banked specimens from a nested case-control study in the Action to Control Cardiovascular Disease (ACCORD) trial (n=187 cases; 187 controls) and from a diverse contemporary cohort of type 2 diabetic patients from the Mount Sinai BioMe Biobank (n=871) to assess the association of plasma endostatin and kidney outcomes. We measured plasma endostatin at enrolment and examined its association with a composite kidney outcome of sustained 40% decline in estimated GFR or end-stage renal disease. Baseline plasma endostatin levels were higher in participants with the composite outcome. Each log2 increment in plasma endostatin was associated with approximately 2.5-fold higher risk of the kidney outcome (adjusted odds ratio [OR] 2.5; 95% confidence interval [CI] 1.5–4.3 in ACCORD and adjusted hazard ratio [HR] 2.6; 95% CI 1.8-3.8 in BioMe). Participants in the highest versus lowest quartile of plasma endostatin had approximately fourfold higher risk for the kidney outcome (adjusted OR 3.6; 95% CI 1.8-7.3 in ACCORD and adjusted HR 4.4; 95% CI 2.3-8.5 in BioMe). The AUC for the kidney outcome improved from 0.74 to 0.77 in BioMe with the addition of endostatin to a base clinical model. Plasma endostatin was strongly associated with kidney outcomes in type 2 diabetics with preserved eGFR and improved risk discrimination over traditional predictors
Relation of serum and urine renal biomarkers to cardiovascular risk in patients with type 2 diabetes mellitus and recent acute coronary syndromes (from the EXAMINE Trial)
Vaduganathan M, White WB, Charytan DM, Morrow DA, Liu Y, et al. Am J Cardiol 2019; 123(3): 382–391
A deeper understanding of the interplay between the renal axis and cardiovascular (CV) disease is needed in type 2 diabetes mellitus (T2DM). We aimed to explore the prognostic value of a comprehensive panel of renal biomarkers in patients with T2DM at high CV risk. We evaluated the prognostic performance of both serum (Cystatin C) and urine renal biomarkers (neutrophil gelatinase-associated lipocalin, kidney injury molecule-1 protein, and indices of urinary protein excretion) in 5380 patients with T2DM and recent acute coronary syndromes in the EXAMINE trial. Patients requiring dialysis within 14 days were excluded. Single- and multimarker covariate-adjusted Cox proportional hazards models were developed to predict times to events. Primary endpoint was composite nonfatal myocardial infarction, nonfatal stroke, or CV death. Median age was 61 years, 68% were men, and mean baseline estimated glomerular filtration rate (eGFR) was 74 mL/min/1.73 m2. During median follow-up of 18 months, 621 (11.5%) experienced the primary endpoint and 326 (6.1%) patients had died. All renal biomarkers were robustly associated with adverse CV events in step-wise fashion, independent of baseline eGFR. However, in the multimarker prediction model, only Cystatin C (per 1 SD) was associated with the primary endpoint (hazard ratio [HR] 1.28 [1.14 to 1.45]; P≤0.001), death (HR 1.51 [1.30 to 1.74]; P≤0.001), and heart failure hospitalization (HR 1.20 [0.96 to 1.49]; P=0.11). Association between Cystatin C and the primary endpoint was similar in baseline eGFR above and below 60 mL/min/1.73 m2 (Pinteraction >0.05). In conclusion, serum and urine renal biomarkers, when tested alone, independently predict long-term adverse CV events in high-risk patients with T2DM. In an integrative panel of renal biomarkers, only serum Cystatin C remained independently associated with subsequent CV risk. Renal biomarkers informing various aspects of kidney function may further our understanding of the complex interplay between diabetic kidney disease and CV disease.
A plasma circulating miRNAs profile predicts type 2 diabetes mellitus and prediabetes: from the CORDIOPREV study
Jiménez-Lucena R, Camargo A, Alcalá-Diaz JF, Romero-Baldonado C, Luque RM, et al. Exp Mol Med 2018; 50(12): 168
We aimed to explore whether changes in circulating levels of miRNAs according to type 2 diabetes mellitus (T2DM) or prediabetes status could be used as biomarkers to evaluate the risk of developing the disease. The study included 462 patients without T2DM at baseline from the CORDIOPREV trial. After a median follow-up of 60 months, 107 of the subjects developed T2DM, 30 developed prediabetes, 223 maintained prediabetes and 78 remained disease-free. Plasma levels of four miRNAs related to insulin signalling and beta-cell function were measured by RT-PCR. We analysed the relationship between miRNAs levels and insulin signalling and release indexes at baseline and after the follow-up period. The risk of developing disease based on tertiles (T1-T2-T3) of baseline miRNAs levels was evaluated by Cox analysis. Thus, we observed higher miR-150 and miR-30a-5p and lower miR-15a and miR-375 baseline levels in subjects with T2DM than in disease-free subjects. Patients with high miR-150 and miR-30a-5p baseline levels had lower disposition index (P=0.047 and P=0.007, respectively). The higher risk of disease was associated with high levels (T3) of miR-150 and miR-30a-5p (HRT3-T1 = 4.218 and HRT3-T1=2.527, respectively) and low levels (T1) of miR-15a and miR-375 (HRT1-T3 = 3.269 and HRT1-T3=1.604, respectively). In conclusion, our study showed that deregulated plasma levels of miR-150, miR-30a-5p, miR-15a, and miR-375 were observed years before the onset of T2DM and pre-DM and could be used to evaluate the risk of developing the disease, which may improve prediction and prevention among individuals at high risk for T2DM.
Emerging biomarkers, tools, and treatments for diabetic polyneuropathy
Bönhof GJ, Herder C, Strom A, Papanas N, Roden M, Ziegler D. Endocr Rev. 2019; 40(1): 153–192
Diabetic neuropathy, with its major clinical sequels, notably neuropathic pain, foot ulcers, and autonomic dysfunction, is associated with substantial morbidity, increased risk of mortality, and reduced quality of life. Despite its major clinical impact, diabetic neuropathy remains underdiagnosed and undertreated. Moreover, the evidence supporting a benefit for causal treatment is weak at least in patients with type 2 diabetes, and current pharmacotherapy is largely limited to symptomatic treatment options. Thus, a better understanding of the underlying pathophysiology is mandatory for translation into new diagnostic and treatment approaches. Improved knowledge about pathogenic pathways implicated in the development of diabetic neuropathy could lead to novel diagnostic techniques that have the potential of improving the early detection of neuropathy in diabetes and prediabetes to eventually embark on new treatment strategies. In this review, we first provide an overview on the current clinical aspects and illustrate the pathogenetic concepts of (pre)diabetic neuropathy. We then describe the biomarkers emerging from these concepts and novel diagnostic tools and appraise their utility in the early detection and prediction of predominantly distal sensorimotor polyneuropathy. Finally, we discuss the evidence for and limitations of the current and novel therapy options with particular emphasis on lifestyle modification and pathogenesis-derived treatment approaches. Altogether, recent years have brought forth a multitude of emerging biomarkers reflecting different pathogenic pathways such as oxidative stress and inflammation and diagnostic tools for an early detection and prediction of (pre)diabetic neuropathy. Ultimately, these insights should culminate in improving our therapeutic armamentarium against this common and debilitating or even life-threatening condition.