PromarkerD Predicts Renal Function Decline in Type 2 Diabetes in the Canagliflozin Cardiovascular Assessment Study (CANVAS)

APOA1/C3/A4/A5 Gene Cluster at 11q23.3 and Lipid Metabolism Disorders: From Epigenetic Mechanisms to Clinical Practices

The APOA1/C3/A4/A5 cluster is an essential component in regulating lipoprotein metabolism and maintaining plasma lipid homeostasis. A genome-wide association analysis and Mendelian randomization have revealed potential associations between genetic variants within this cluster and lipid metabolism disorders, including hyperlipidemia and cardiovascular events. An enhanced understanding of the complexity of gene regulation has led to growing recognition regarding the role of epigenetic variation in modulating APOA1/C3/A4/A5 gene expression. Intensive research into the epigenetic regulatory patterns of the APOA1/C3/A4/A5 cluster will help increase our understanding of the pathogenesis of lipid metabolism disorders and facilitate the development of new therapeutic approaches. This review discusses the biology of how the APOA1/C3/A4/A5 cluster affects circulating lipoproteins and the current progress in the epigenetic regulation of the APOA1/C3/A4/A5 cluster.

Sodium-glucose co-transporter protein 2 (SGLT2) inhibitors for people with chronic kidney disease and diabetes

BACKGROUND

Diabetes is associated with high risks of premature chronic kidney disease (CKD), cardiovascular diseases, cardiovascular death and impaired quality of life. People with diabetes are more likely to develop kidney impairment, and approximately one in three adults with diabetes have CKD. People with CKD and diabetes experience a substantially higher risk of cardiovascular outcomes. Sodium-glucose co-transporter protein 2 (SGLT2) inhibitors have shown potential effects in preventing kidney and cardiovascular outcomes in people with CKD and diabetes. However, new trials are emerging rapidly, and evidence synthesis is essential to summarising cumulative evidence.

OBJECTIVES

This review aimed to assess the benefits and harms of SGLT2 inhibitors for people with CKD and diabetes.

SEARCH METHODS

We searched the Cochrane Kidney and Transplant Register of Studies up to 17 November 2023 using a search strategy designed by an Information Specialist. Studies in the Register are continually identified through regular searches of CENTRAL, MEDLINE, and EMBASE, conference proceedings, the International Clinical Trials Registry Platform (ICTRP) Search Portal and ClinicalTrials.gov.

SELECTION CRITERIA

Randomised controlled studies were eligible if they evaluated SGLT2 inhibitors versus placebo, standard care or other glucose-lowering agents in people with CKD and diabetes. CKD includes all stages (from 1 to 5), including dialysis patients.

DATA COLLECTION AND ANALYSIS

Two authors independently extracted data and assessed the study risk of bias. Treatment estimates were summarised using random effects meta-analysis and expressed as a risk ratio (RR) or mean difference (MD), with a corresponding 95% confidence interval (CI). Confidence in the evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. The primary review outcomes were all-cause death, 3-point and 4-point major adverse cardiovascular events (MACE), fatal or nonfatal myocardial infarction (MI), fatal or nonfatal stroke, and kidney failure.

MAIN RESULTS

Fifty-three studies randomising 65,241 people with CKD and diabetes were included. SGLT2 inhibitors with or without other background treatments were compared to placebo, standard care, sulfonylurea, dipeptidyl peptidase-4 (DPP-4) inhibitors, or insulin. In the majority of domains, the risks of bias in the included studies were low or unclear. No studies evaluated the treatment in children or in people treated with dialysis. No studies compared SGLT2 inhibitors with glucagon-like peptide-1 receptor agonists or tirzepatide. Compared to placebo, SGLT2 inhibitors decreased the risk of all-cause death (20 studies, 44,397 participants: RR 0.85, 95% CI 0.78 to 0.94; I2 = 0%; high certainty) and cardiovascular death (16 studies, 43,792 participants: RR 0.83, 95% CI 0.74 to 0.93; I2 = 29%; high certainty). Compared to placebo, SGLT2 inhibitors probably make little or no difference to the risk of fatal or nonfatal MI (2 studies, 13,726 participants: RR 0.95, 95% CI 0.80 to 1.14; I2 = 24%; moderate certainty), and fatal or nonfatal stroke (2 studies, 13,726 participants: RR 1.07, 95% CI 0.88 to 1.30; I2 = 0%; moderate certainty). Compared to placebo, SGLT2 inhibitors probably decrease 3-point MACE (7 studies, 38,320 participants: RR 0.89, 95% CI 0.81 to 0.98; I2 = 46%; moderate certainty), and 4-point MACE (4 studies, 23,539 participants: RR 0.82, 95% CI 0.70 to 0.96; I2 = 77%; moderate certainty), and decrease hospital admission due to heart failure (6 studies, 28,339 participants: RR 0.70, 95% CI 0.62 to 0.79; I2 = 17%; high certainty). Compared to placebo, SGLT2 inhibitors may decrease creatinine clearance (1 study, 132 participants: MD -2.63 mL/min, 95% CI -5.19 to -0.07; low certainty) and probably decrease the doubling of serum creatinine (2 studies, 12,647 participants: RR 0.70, 95% CI 0.56 to 0.89; I2 = 53%; moderate certainty). SGLT2 inhibitors decrease the risk of kidney failure (6 studies, 11,232 participants: RR 0.70, 95% CI 0.62 to 0.79; I2 = 0%; high certainty), and kidney composite outcomes (generally reported as kidney failure, kidney death with or without ≥ 40% decrease in estimated glomerular filtration rate (eGFR)) (7 studies, 36,380 participants: RR 0.68, 95% CI 0.59 to 0.78; I2 = 25%; high certainty) compared to placebo. Compared to placebo, SGLT2 inhibitors incur less hypoglycaemia (16 studies, 28,322 participants: RR 0.93, 95% CI 0.89 to 0.98; I2 = 0%; high certainty), and hypoglycaemia requiring third-party assistance (14 studies, 26,478 participants: RR 0.75, 95% CI 0.65 to 0.88; I2 = 0%; high certainty), and probably decrease the withdrawal from treatment due to adverse events (15 studies, 16,622 participants: RR 0.94, 95% CI 0.82 to 1.08; I2 = 16%; moderate certainty). The effects of SGLT2 inhibitors on eGFR, amputation and fracture were uncertain. No studies evaluated the effects of treatment on fatigue, life participation, or lactic acidosis. The effects of SGLT2 inhibitors compared to standard care alone, sulfonylurea, DPP-4 inhibitors, or insulin were uncertain.

AUTHORS' CONCLUSIONS

SGLT2 inhibitors alone or added to standard care decrease all-cause death, cardiovascular death, and kidney failure and probably decrease major cardiovascular events while incurring less hypoglycaemia compared to placebo in people with CKD and diabetes.

Canagliflozin Attenuates PromarkerD Diabetic Kidney Disease Risk Prediction Scores

PromarkerD is a biomarker-based blood test that predicts kidney function decline in people with type 2 diabetes (T2D) who may otherwise be missed by current standard of care tests. This study examined the association between canagliflozin and change in PromarkerD score (Δ score) over a three-year period in T2D participants in the CANagliflozin cardioVascular Assessment Study (CANVAS). PromarkerD scores were measured at baseline and Year 3 in 2008 participants with preserved kidney function (baseline eGFR ≥60 mL/min/1.73 m2). Generalized estimating equations were used to assess the effect of canagliflozin versus placebo on PromarkerD scores. At baseline, the participants (mean age 62 years, 32% females) had a median PromarkerD score of 3.9%, with 67% of participants categorized as low risk, 14% as moderate risk, and 19% as high risk for kidney function decline. After accounting for the known acute drop in eGFR following canagliflozin initiation, there was a significant treatment-by-time interaction (p < 0.001), whereby participants on canagliflozin had decreased mean PromarkerD scores from baseline to Year 3 (Δ score: -1.0% [95% CI: -1.9%, -0.1%]; p = 0.039), while the scores of those on placebo increased over the three-year period (Δ score: 6.4% [4.9%, 7.8%]; p < 0.001). When stratified into PromarkerD risk categories, participants with high risk scores at baseline who were randomized to canagliflozin had significantly lower scores at Year 3 (Δ score: -5.6% [-8.6%, -2.5%]; p < 0.001), while those on placebo retained high scores (Δ score: 4.5% [0.3%, 8.8%]; p = 0.035). This post hoc analysis of data from CANVAS showed that canagliflozin significantly lowered PromarkerD risk scores, with the effect greatest in those T2D participants who were classified at study entry as at high risk of a subsequent decline in kidney function.

Impact of Sodium-Glucose Cotransporter-2 Inhibitors on Cardiac Bioenergetic Properties and Cardiorespiratory Fitness: A Special Effect of SGLT2i In Heart Failure?

Recent clinical trials have highlighted the profound benefits of sodium-glucose linked transporter 2 inhibitors (SGLT2i) on cardiovascular mortality and hospitalization for heart failure patients. Modest improvements in glycemic, lipid, or blood pressure control are unlikely to contribute to these significant beneficial outcomes, generating much interest in the relevant mechanisms leading to outcome improvements. In this review, we discuss the current evidence supporting a shift in myocardial substrate utilization from carbohydrates and fat oxidation toward energy efficient ketone bodies in the failing heart and the role of SGLT2i in this key metabolic adaptation to optimize myocardial fuel energetics. Further insights into the effect of SGLT2i on the indices of cardiorespiratory fitness are outlined and provide important clues into their mechanism of benefit. This mechanistic discussion in the context of recent trials of SGLT2i denotes a promising treatment paradigm of heart failure in individuals with and without diabetes.

A systems biology approach to better understand human tick-borne diseases

Tick-borne diseases (TBDs) are a growing global health concern. Despite extensive studies, ill-defined tick-associated pathologies remain with unknown aetiologies. Human immunological responses after tick bite, and inter-individual variations of immune-response phenotypes, are not well characterised. Current reductive experimental methodologies limit our understanding of more complex tick-associated illness, which results from the interactions between the host, tick, and microbes. An unbiased, systems-level integration of clinical metadata and biological host data - obtained via transcriptomics, proteomics, and metabolomics - offers to drive the data-informed generation of testable hypotheses in TBDs. Advanced computational tools have rendered meaningful analysis of such large data sets feasible. This review highlights the advantages of integrative system biology approaches as essential for understanding the complex pathobiology of TBDs.

Molecular Pathways of Diabetic Kidney Disease Inferred from Proteomics

Diabetic kidney disease (DKD) affects an estimated 20-40% of type 2 diabetes patients and is among the most prevalent microvascular complications in this patient population, contributing to high morbidity and mortality rates. Currently, changes in albuminuria status are thought to be a primary indicator of the onset or progression of DKD, yet progressive nephropathy and renal impairment can occur in certain diabetic individuals who exhibit normal urinary albumin levels, emphasizing the lack of sensitivity and specificity associated with the use of albuminuria as a biomarker for detecting diabetic kidney disease and predicting DKD risk. According to the study, a non-invasive method for early detection or prediction of DKD may involve combining proteomic analytical techniques such second generation sequencing, mass spectrometry, two-dimensional gel electrophoresis, and other advanced system biology algorithms. Another category of proteins of relevance may now be provided by renal tissue biomarkers. The establishment of reliable proteomic biomarkers of DKD represents a novel approach to improving the diagnosis, prognostic evaluation, and treatment of affected patients. In the present review, a series of protein biomarkers that have been characterized to date are discussed, offering a theoretical foundation for future efforts to aid patients suffering from this debilitating microvascular complication.

Precision Medicine Approach for Cardiometabolic Risk Factors in Therapeutic Apheresis

Lipoprotein apheresis (LA) is currently the most powerful intervention possible to reach a maximal reduction of lipids in patients with familial hypercholesterolemia and lipoprotein(a) hyperlipidemia. Although LA is an invasive method, it has few side effects and the best results in preventing further major cardiovascular events. It has been suggested that the highly significant reduction of cardiovascular complications in patients with severe lipid disorders achieved by LA is mediated not only by the potent reduction of lipid levels but also by the removal of other proinflammatory and proatherogenic factors. Here we performed a comprehensive proteomic analysis of patients on LA treatment using intra-individually a set of differently sized apheresis filters with the INUSpheresis system. This study revealed that proteomic analysis correlates well with routine clinical chemistry in these patients. The method is eminently suited to discover new biomarkers and risk factors for cardiovascular disease in these patients. Different filters achieve reduction and removal of proatherogenic proteins in different quantities. This includes not only apolipoproteins, C-reactive protein, fibrinogen, and plasminogen but also proteins like complement factor B (CFAB), protein AMBP, afamin, and the low affinity immunoglobulin gamma Fc region receptor III-A (FcγRIIIa) among others that have been described as atherosclerosis and metabolic vascular diseases promoting factors. We therefore conclude that future trials should be designed to develop an individualized therapy approach for patients on LA based on their metabolic and vascular risk profile. Furthermore, the power of such cascade filter treatment protocols may improve the prevention of cardiometabolic disease and its complications.

Derivation and validation of a machine learning risk score using biomarker and electronic patient data to predict progression of diabetic kidney disease

AIM

Predicting progression in diabetic kidney disease (DKD) is critical to improving outcomes. We sought to develop/validate a machine-learned, prognostic risk score (KidneyIntelX™) combining electronic health records (EHR) and biomarkers.

METHODS

This is an observational cohort study of patients with prevalent DKD/banked plasma from two EHR-linked biobanks. A random forest model was trained, and performance (AUC, positive and negative predictive values [PPV/NPV], and net reclassification index [NRI]) was compared with that of a clinical model and Kidney Disease: Improving Global Outcomes (KDIGO) categories for predicting a composite outcome of eGFR decline of ≥5 ml/min per year, ≥40% sustained decline, or kidney failure within 5 years.

RESULTS

In 1146 patients, the median age was 63 years, 51% were female, the baseline eGFR was 54 ml min-1 [1.73 m]-2, the urine albumin to creatinine ratio (uACR) was 6.9 mg/mmol, follow-up was 4.3 years and 21% had the composite endpoint. On cross-validation in derivation (n = 686), KidneyIntelX had an AUC of 0.77 (95% CI 0.74, 0.79). In validation (n = 460), the AUC was 0.77 (95% CI 0.76, 0.79). By comparison, the AUC for the clinical model was 0.62 (95% CI 0.61, 0.63) in derivation and 0.61 (95% CI 0.60, 0.63) in validation. Using derivation cut-offs, KidneyIntelX stratified 46%, 37% and 17% of the validation cohort into low-, intermediate- and high-risk groups for the composite kidney endpoint, respectively. The PPV for progressive decline in kidney function in the high-risk group was 61% for KidneyIntelX vs 40% for the highest risk strata by KDIGO categorisation (p < 0.001). Only 10% of those scored as low risk by KidneyIntelX experienced progression (i.e., NPV of 90%). The NRIevent for the high-risk group was 41% (p < 0.05).

CONCLUSIONS

KidneyIntelX improved prediction of kidney outcomes over KDIGO and clinical models in individuals with early stages of DKD.

Assessment of biomarkers associated with rapid renal decline in the detection of retinopathy and its progression in type 2 diabetes: The Fremantle Diabetes Study Phase II

AIMS

To determine whether biomarkers for diabetic kidney disease (DKD) can be used to determine the prevalence, progression and/or incidence of diabetic retinopathy (DR) complicating type 2 diabetes.

METHODS

Proteomic biomarkers were measured in baseline fasting plasma from 958 Fremantle Diabetes Study Phase II participants whose baseline and, in those returning for follow-up (n = 764), Year 4 fundus photographs were graded for DR presence/severity. The performance of PromarkerD (three biomarkers and readily available clinical variables which identify prevalent DKD and predict incident DKD and estimated glomerular filtration rate decline ≥30% over four years) for detecting DR prevalence, progression and incidence was assessed using the area under the receiver operating curve (AUC). Logistic regression determined whether individual proteins were associated with DR outcomes after adjusting for the most parsimonious model.

RESULTS

Plasma apolipoprotein A-IV (APOA4) was independently associated with moderate non-proliferative DR at baseline (OR (95% CI): 1.64 (1.01, 2.67), P = 0.047). Model discrimination was poor for all PromarkerD predicted probabilities against all DR outcomes (AUC ≤0.681).

CONCLUSIONS

PromarkerD and its constituent biomarkers were not consistently associated with DR prevalence or temporal change. APOA4 was associated with prevalent DR, but not DR incidence or progression. Distinct pathophysiological mechanisms may underlie DKD and DR.