Validation of plasma biomarker candidates for the prediction of eGFR decline in patients with type 2 diabetes

Objective: The decline of estimated glomerular filtration rate (eGFR) in patients with type 2 diabetes is variable and early interventions would likely be cost effective. We elucidated the contribution of 17 plasma biomarkers to the prediction of eGFR loss on top of clinical risk factors. Research Design and Methods: We studied participants in PROVALID, a prospective multinational cohort study of patients with type 2 diabetes and a follow up of more than 24 months (n = 2560; baseline median eGFR 84 mL/min/1.73m2, UACR 8.1 mg/g). The 17 biomarkers were measured at baseline in 481 samples using Luminex technology and ELISA. The prediction of eGFR decline was evaluated by linear mixed modeling. Results: In univariable analyses nine of the 17 markers showed significant differences in median concentration between the two groups. A linear mixed model for eGFR obtained by variable selection exhibited an adjusted R2 of 62%. A panel of twelve biomarkers was selected by the procedure and accounted for 34% of the total explained variability, of which 32% were due to five markers. Each biomarker’s individual contribution to the prediction of eGFR decline on top of clinical predictors was generally low. When included into the model, baseline eGFR exhibited the largest explained variability of eGFR decline (R2 of 79%) and the contribution of each biomarker dropped below 1%. Conclusions: In this longitudinal study of patients with type 2 diabetes and maintained eGFR at baseline, 12 of the 17 candidate biomarkers were associated with eGFR decline, but their predictive power was low

The impact of donor and recipient common clinical and genetic variation on estimated glomerular filtration rate in a European renal transplant population

Genetic variation across the HLA is known to influence renal‐transplant outcome. However, the impact of genetic variation beyond the HLA is less clear. We tested the association of common genetic variation and clinical characteristics, from both the donor and recipient, with post‐transplant eGFR at different time‐points, out to 5‐years post‐transplantation. We conducted GWAS meta‐analyses across 10,844 donors and recipients from five European ancestry cohorts. We also analysed the impact of polygenic risk scores (PRS), calculated using genetic variants associated with non‐transplant eGFR, on post‐transplant eGFR. PRS calculated using the recipient genotype alone, as well as combined donor and recipient genotypes were significantly associated with eGFR at 1‐year post‐transplant. 32% of the variability in eGFR at 1‐year post‐transplant was explained by our model containing clinical covariates (including weights for death/graft‐failure), principal components and combined donor‐recipient PRS, with 0.3% contributed by the PRS. No individual genetic variant was significantly associated with eGFR post‐transplant in the GWAS. This is the first study to examine PRS, composed of variants that impact kidney function in the general population, in a post‐transplant context. Despite PRS being a significant predictor of eGFR post‐transplant, the effect size of common genetic factors is limited compared to clinical variables

New Polynomial-Based Molecular Descriptors with Low Degeneracy

In this paper, we introduce a novel graph polynomial called the ‘information polynomial’ of a graph. This graph polynomial can be derived by using a probability distribution of the vertex set. By using the zeros of the obtained polynomial, we additionally define some novel spectral descriptors. Compared with those based on computing the ordinary characteristic polynomial of a graph, we perform a numerical study using real chemical databases. We obtain that the novel descriptors do have a high discrimination power

Integrative analysis of prognostic biomarkers derived from multiomics panels for the discrimination of chronic kidney disease trajectories in people with type 2 diabetes

Clinical risk factors explain only a fraction of the variability of estimated glomerular filtration rate (eGFR) decline in people with type 2 diabetes. Cross-omics technologies by virtue of; a wide spectrum screening of plasma samples have the potential to identify biomarkers for the refinement of prognosis in addition to clinical variables. Here we utilized proteomics, metabolomics and lipidomics panel assay measurements in baseline plasma samples from the multinational PROVALID study (PROspective cohort study in patients with type 2 diabetes mellitus for VALIDation of biomarkers) of patients with incident or early chronic kidney disease (median follow-up 35 months, median baseline eGFR 84 mL/min/1.73m2, urine albumin-to-creatinine ratio 8.1 mg/g). In an accelerated case-control study, 258 individuals with a stable eGFR course (median eGFR change 0.1 mL/min/year) were compared to 223 individuals with a rapid eGFR decline (median eGFR decline -6.75 mL/min/year) using Bayesian multivariable logistic regression models to assess the discrimination of eGFR trajectories. The analysis included 402 candidate predictors and showed two protein markers (KIM-1, NTproBNP) to be relevant predictors of the eGFR trajectory with baseline eGFR being an important clinical covariate. The inclusion of metabolomic and lipidomic platforms did not improve discrimination substantially. Predictions using all available variables were statistically indistinguishable from predictions using only KIM-1 and baseline eGFR (area under the receiver operating characteristic curve 0.63). Thus, the discrimination of eGFR trajectories in patients with incident or early diabetic kidney disease and maintained baseline eGFR was modest and the protein marker KIM-1 was the most important predictor

Non-verbal IQ Gains from Relational Operant Training Explain Variance in Educational Attainment: An Active-Controlled Feasibility Study

Research suggests that training relational operant patterns of behavior can lead to increases in general cognitive ability and educational outcomes. Most studies to date have been under-powered and included proxy measures of educational attainment. We attempted to extend previous findings with increased experimental control in younger children (aged 6.9–10.1 years). Participants (N = 49) were assigned to either a relational training or chess control group. Over 5 months, teachers assigned class time to complete either relational training or play chess. Those who were assigned relational training gained 8.9 non-verbal IQ (NVIQ) points, while those in the control condition recorded no gains (dppc2 = .99). Regression analyses revealed that post-training NVIQ predicted reading test scores (conducted approximately 1 month later) over and above baseline NVIQ in the experimental condition only, consistent with what we might expect in a full test of far transfer towards educational outcomes