OMICS in Chronic Kidney Disease: Focus on Prognosis and Prediction.
Ontology highlight
ABSTRACT:
SUBMITTER: Provenzano M
PROVIDER: S-EPMC8745343 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:Anemia is common in patients with chronic kidney disease (CKD) and results from the dysregulation of iron metabolism and erythropoiesis. Hepcidin is a key regulator of iron availability and leads to iron sequestration during the state of iron repletion. Decreases in the level of hepcidin in the presence of hypoxia and/or iron limitation allow for greater iron availability for erythropoiesis. However, kidney excretion of hepcidin decreases as the severity of CKD increases, whereas production of hepcidin is increased under inflammatory conditions often present in patients with CKD, both of which contribute to anemia. Assessment of iron status is, therefore, essential in the treatment of anemia. However, current laboratory tests for the determination of the adequate supply of iron have many limitations, including diurnal variation in the levels of biomarkers, lack of standardized reference methods across laboratories, and confounding by the presence of inflammation. In addition, the current treatment paradigm for anemia of CKD can further disrupt iron homeostasis; for example, treatment with erythropoiesis-stimulating agents in the absence of supplemental iron can induce functional iron deficiency. Moreover, supplemental iron can further increase levels of hepcidin. Several novel therapies, including hypoxia-inducible factor prolyl hydroxylase inhibitors and hepcidin inhibitors/antagonists, have shown promise in attenuating the levels and/or activity of hepcidin in anemia of CKD, thus ensuring the availability of iron for erythropoiesis.
| S-EPMC7983022 | biostudies-literature
Project description:BackgroundThe study sought to assess the prognostic impact of chronic kidney disease (CKD) in patients with electrical storm (ES). ES represents a life-threatening heart rhythm disorder. In particular, CKD patients are at risk of suffering from ES. However, data regarding the prognostic impact of CKD on long-term mortality in ES patients is limited.MethodsAll consecutive ES patients with an implantable cardioverter-defibrillator (ICD) were included retrospectively from 2002 to 2016. Patients with CKD (MDRD-GFR < 60 ml/min/1.73 m2) were compared to patients without CKD. The primary endpoint was all-cause mortality at 3 years. Secondary endpoints were in-hospital mortality, cardiac rehospitalization, recurrences of electrical storm (ES-R), and major adverse cardiac events (MACE) at 3 years.ResultsA total of 70 consecutive ES patients were included. CKD was present in 43% of ES patients with a median glomerular filtration rate (GFR) of 43.3 ml/min/1.73 m2. CKD was associated with increased all-cause mortality at 3 years (63% vs. 20%; p = 0.001; HR = 4.293; 95% CI 1.874-9.836; p = 0.001) and MACE (57% vs. 30%; p = 0.025; HR = 3.597; 95% CI 1.679-7.708; p = 0.001). In contrast, first cardiac rehospitalization (43% vs. 45%; log-rank p = 0.889) and ES-R (30% vs. 20%; log-rank p = 0.334) were not affected by CKD. Even after multivariable adjustment, CKD was still associated with increased long-term mortality (HR = 2.397; 95% CI 1.012-5.697; p = 0.047), as well as with the secondary endpoint MACE (HR = 2.520; 95% CI 1.109-5.727; p = 0.027).ConclusionsIn patients with ES, the presence of CKD was associated with increased long-term mortality and MACE.
| S-EPMC8755690 | biostudies-literature
Project description:Based on the high incidence of chronic kidney disease (CKD) in recent years, a better early prediction model for identifying high-risk individuals before end-stage renal failure (ESRD) occurs is needed. We conducted a nested case-control study in 348 subjects (116 cases and 232 controls) from the "Tianjin Medical University Chronic Diseases Cohort". All subjects did not have CKD at baseline, and they were followed up for 5 years until August 2018. Using multivariate Cox regression analysis, we found five nongenetic risk factors associated with CKD risks. Logistic regression was performed to select single nucleotide polymorphisms (SNPs) from which we obtained from GWAS analysis of the UK Biobank and other databases. We used a logistic regression model and natural logarithm OR value weighting to establish CKD genetic/nongenetic risk prediction models. In addition, the final comprehensive prediction model is the arithmetic sum of the two optimal models. The AUC of the prediction model reached 0.894, while the sensitivity was 0.827, and the specificity was 0.801. We found that age, diabetes, and normal high values of urea nitrogen, TGF-β, and ADMA were independent risk factors for CKD. A comprehensive prediction model was also established, which may help identify individuals who are most likely to develop CKD early.
| S-EPMC8854510 | biostudies-literature
Project description: Not available
| S-EPMC10836873 | biostudies-literature
Project description:Nephrotoxic drugs prescriptions are often prescribed inappropriately by general practitioners (GPs), increasing the risk of chronic kidney disease (CKD). The aim of this study was to detect inappropriate prescriptions in patients with CKD and to identify their predictive factors. A retrospective study on patients with creatinine values recorded in the period 2014-2016 followed by 10 GPs was performed. The estimated glomerular filtration rate (eGFR) was used to identify CKD patients. The demographic and clinical characteristics and drugs prescriptions were collected. A descriptive analysis was conducted to compare the characteristics and logistic regression models to estimate the predictive factors of inappropriate prescriptions. Of 4098 patients with creatinine values recorded, 21.9% had an eGFR <60 mL/min/1.73m2. Further, 56.8% received inappropriate prescriptions, with a significantly lower probability in subjects with at least a nephrologist visit (Adj OR 0.54 (95% CI 0.36-0.81)) and a greater probability in patients treated with more active substances (1.10 (1.08-1.12)), affected by more comorbidities (1.14 (1.06-1.230)), or with serious CKD (G4/G5 21.28 (7.36-61.57)). Nonsteroidal anti-inflammatory drugs (NSAIDs) were the most used contraindicated drugs (48.5%), while acetylsalicylic acid was the most inappropriately prescribed (39.5%). Our results highlight the inappropriate prescriptions for CKD authorized by GPs and underline the need of strategies to improve prescribing patterns.
| S-EPMC7290782 | biostudies-literature
Project description:BackgroundObstructive uropathy (OU) is a leading cause of pediatric kidney injury. Accurate prediction of kidney disease progression may improve clinical outcomes. We aimed to examine discrimination and accuracy of a validated kidney failure risk equation (KFRE), previously developed in adults, in children with OU.MethodsWe identified 118 children with OU and an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m2 in the Chronic Kidney Disease in Children study, a national, longitudinal, observational cohort. Each patient's 5-year risk of kidney failure was estimated using baseline data and published parameters for the 4- and 8-variable KFREs. Discriminative ability of the KFRE was estimated using the C statistic for time-to-event analysis. Sensitivity and specificity were evaluated across varying risk thresholds.ResultsAmong the 118 children, 100 (85%) were boys, with median baseline age of 10 years (interquartile range, 6-14). Median eGFR was 42 mL/min/1.73m 2 (32-53), with a median follow-up duration of 4.5 years (2.7-7.2); 23 patients (19.5%) developed kidney failure within 5 years. The 4-variable KFRE discriminated kidney failure risk with a C statistic of 0.75 (95% CI, 0.68-0.82). A 4-variable risk threshold of ≥ 30% yielded 82.6% sensitivity and 75.0% specificity. Results were similar using the 8-variable KFRE.ConclusionsIn children with OU, the KFRE discriminated the 5-year risk of kidney failure at C statistic values lower than previously published in adults but comparable with suboptimal values reported in the overall CKiD population. The 8-variable equation did not improve model discrimination or accuracy, suggesting the need for continued research into additional, disease-specific markers.
| S-EPMC10928559 | biostudies-literature
Project description:Importance:Early identification of individuals at elevated risk of developing chronic kidney disease (CKD) could improve clinical care through enhanced surveillance and better management of underlying health conditions. Objective:To develop assessment tools to identify individuals at increased risk of CKD, defined by reduced estimated glomerular filtration rate (eGFR). Design, Setting, and Participants:Individual-level data analysis of 34 multinational cohorts from the CKD Prognosis Consortium including 5?222?711 individuals from 28 countries. Data were collected from April 1970 through January 2017. A 2-stage analysis was performed, with each study first analyzed individually and summarized overall using a weighted average. Because clinical variables were often differentially available by diabetes status, models were developed separately for participants with diabetes and without diabetes. Discrimination and calibration were also tested in 9 external cohorts (n?=?2?253?540). Exposures:Demographic and clinical factors. Main Outcomes and Measures:Incident eGFR of less than 60 mL/min/1.73 m2. Results:Among 4?441?084 participants without diabetes (mean age, 54 years, 38% women), 660?856 incident cases (14.9%) of reduced eGFR occurred during a mean follow-up of 4.2 years. Of 781?627 participants with diabetes (mean age, 62 years, 13% women), 313?646 incident cases (40%) occurred during a mean follow-up of 3.9 years. Equations for the 5-year risk of reduced eGFR included age, sex, race/ethnicity, eGFR, history of cardiovascular disease, ever smoker, hypertension, body mass index, and albuminuria concentration. For participants with diabetes, the models also included diabetes medications, hemoglobin A1c, and the interaction between the 2. The risk equations had a median C statistic for the 5-year predicted probability of 0.845 (interquartile range [IQR], 0.789-0.890) in the cohorts without diabetes and 0.801 (IQR, 0.750-0.819) in the cohorts with diabetes. Calibration analysis showed that 9 of 13 study populations (69%) had a slope of observed to predicted risk between 0.80 and 1.25. Discrimination was similar in 18 study populations in 9 external validation cohorts; calibration showed that 16 of 18 (89%) had a slope of observed to predicted risk between 0.80 and 1.25. Conclusions and Relevance:Equations for predicting risk of incident chronic kidney disease developed from more than 5 million individuals from 34 multinational cohorts demonstrated high discrimination and variable calibration in diverse populations. Further study is needed to determine whether use of these equations to identify individuals at risk of developing chronic kidney disease will improve clinical care and patient outcomes.
| S-EPMC6865298 | biostudies-literature
Project description:This study sought to evaluate whether impaired vasodilator function, an early manifestation of coronary artery disease, which precedes angiographic stenosis, accounts for increased risk among patients with moderate to severe renal dysfunction.Patients with renal dysfunction are at increased risk of adverse cardiac outcomes, even in the absence of overt myocardial ischemia or infarction.We included 866 consecutive patients with moderate to severe renal dysfunction referred for rest and stress myocardial perfusion positron emission tomography and followed them for a median of 1.28 years (interquartile range: 0.64 to 2.34). Regional myocardial perfusion abnormalities were assessed by semiquantitative visual analysis of positron emission tomography images. Rest and stress myocardial blood flow were calculated using factor analysis and a 2-compartment kinetic model; they were also used to compute coronary flow reserve (stress/rest myocardial blood flow). The primary endpoint was cardiac death.Overall, 3-year cardiac mortality was 16.2%. After adjusting for clinical risk, left ventricular ejection fraction, as well as the magnitude of scar and/or ischemia, coronary flow reserve below the median (<1.5) was associated with a 2.1-fold increase in the risk of cardiac death (95% confidence interval [CI]: 1.3 to 3.5, p = 0.004). Incorporation of coronary flow reserve into cardiac death risk assessment models resulted in an increase in the C-index from 0.75 to 0.77 (p = 0.05) and in a net reclassification improvement of 0.142 (95% CI: 0.076 to 0.219). Among patients at intermediate risk based on all data other than coronary flow reserve, the net reclassification improvement was 0.489 (95% CI: 0.192 to 0.836). Corresponding improvements in risk assessment for mortality from any cause were also demonstrated.The presence of coronary vascular dysfunction in patients with moderate to severe renal dysfunction, as assessed by positron emission tomography, is a powerful, independent predictor of cardiac mortality and provides meaningful incremental risk stratification over conventional markers of clinical risk.
| S-EPMC3471090 | biostudies-literature
Project description:Primary kidney disease is suggested to affect renal prognosis of CKD patients; however, whether nephrology care modifies this association is unknown. We studied patients with CKD stage I-IV treated in a renal clinic and with established diagnosis of CKD cause to evaluate whether the risk of renal event (composite of end-stage renal disease and eGFR decline ? 40%) linked to the specific diagnosis is modified by the achievement or maintenance in the first year of nephrology care of therapeutic goals for hypertension (BP ? 130/80 mmHg in patients with proteinuria ? 1 50 mg/24h and/or diabetes and ? 140/90 in those with proteinuria <150 mg/24h and without diabetes) anemia (hemoglobin, Hb ? 11 g/dL), and proteinuria (? 0.5 g/24h). Survival analysis started after first year of nephrology care. We studied 729 patients (age 64 ± 15 y; males 59.1%; diabetes 34.7%; cardiovascular disease (CVD) 44.9%; hypertensive nephropathy, HTN 53.8%; glomerulonephritis, GN 17.3%; diabetic nephropathy, DN 15.9%; tubule-interstitial nephropathy, TIN 9.5%; polycystic kidney disease, PKD 3.6%). During first year of Nephrology care, therapy was overall intensified in most patients and prevalence of main therapeutic goals generally improved. During subsequent follow up (median 3.3 years, IQR 1.9-5.1), 163 renal events occurred. Cox analysis disclosed a higher risk for PKD (Hazard Ratio 5.46, 95% Confidence Intervals 2.28-10.6) and DN (1.28,2.99-3.05), versus HTN (reference), independently of age, gender, CVD, BMI, eGFR or CKD stage, use of RAS inhibitors and achievement or maintenance in the first year of nephrology care of each of the three main therapeutic goals. No interaction was found on the risk of CKD progression between diagnostic categories and month-12 eGFR (P=0.737), as with control of BP (P=0.374), Hb (P=0.248) or proteinuria (P=0.590). Therefore, in CKD patients under nephrology care, diagnosis of kidney disease should be considered in conjunction with the main risk factors to refine renal risk stratification.
| S-EPMC4439030 | biostudies-literature
Project description:Mild cognitive impairment (MCI) is a clinical precursor of Alzheimer’s disease (AD). Many MCI subjects convert to AD, although others remain stable as MCI or sometimes return to cognitive normal. Currently, there are no curative treatments for patients who are already in AD, and therefore biomarkers for early detection of high risk MCI-to-AD conversion subjects are rapidly required. Here, we investigated potential biomarkers from blood-based miRNA (miR) expression profiles and genomic data of 197 Japanese MCI patients. Using the candidate biomarkers, we constructed a prognosis prediction model based on a Cox proportional hazard model. The final prediction model, composed of 24 miR-eQTLs (i.e. SNP-miRNA pairs) and three clinical factors (age, sex and ApoE ε4 carriers), successfully classified MCI patients into two groups, low and high, in terms of risk of MCI-to-AD conversion (log-rank trend test P=3.44×10^(-4)), and achieved a concordance index of 0.702 on an independent test set. Network-based meta-analysis using target genes of the miR-eQTLs further revealed four important hub genes (SHC1, FOXO1, GSK3B, and PTEN) associated with the pathogenesis of AD. Statistically significant differences were observed in PTEN expression between MCI and AD and SHC1 expression between cognitively normal elder subjects (CN) and AD when examining RNA-seq data from 610 blood samples (PTEN, P=0.023; SHC1, P=0.049), although FOXO1 and GSK3B showed low levels of expression in blood. Accurate prediction of MCI-to-AD conversion enables earlier appropriate intervention for those MCI patients and can lead to a reduction of MCI patients that convert to AD with high risk. We believe that further investigation with larger sample sizes will contribute to practical clinical use of our approach in MCI-to-AD conversion in the near future.
2020-11-11 | GSE150693 | GEO