Cardiorenal Risk Profiles Among Data-Driven Type 2 Diabetes Sub-Phenotypes: A Post-Hoc Analysis of the China Health and Nutrition Survey

Impact of finerenone on chronic kidney disease progression in Chinese patients with type 2 diabetes: a FIGARO-DKD subgroup analysis

Background

Type 2 diabetes (T2D) is a considerable and growing burden in the Chinese population, and affected adults are at high risk of developing chronic kidney disease (CKD). This subgroup analysis of the FIGARO-DKD trial explored the cardiovascular and kidney benefits of finerenone in Chinese patients with CKD and T2D on optimized renin-angiotensin system blockade.

Methods

Patients with urine albumin-to-creatinine ratio (UACR) ≥30-<300 mg/g and estimated glomerular filtration rate (eGFR) ≥25-≤90 mL/min/1.73 m2, or UACR ≥300-≤5000 mg/g and eGFR ≥60 mL/min/1.73 m2, were randomized to finerenone or placebo. The primary cardiovascular composite outcome was time to cardiovascular death, non-fatal myocardial infarction, non-fatal stroke, or hospitalization for heart failure. The secondary kidney composite outcome was time to kidney failure, sustained eGFR decline ≥40% from baseline, or kidney-related death.

Results

A total of 325 Chinese patients were included. Finerenone resulted in a numerical decrease in the risk of the cardiovascular composite outcome (hazard ratio 0.91; 95% confidence interval 0.50-1.67) and a significantly reduced risk of the key secondary kidney outcome (hazard ratio 0.48; 95% confidence interval 0.29-0.79; p = 0.0029). The incidence of investigator-reported hyperkalemia was high across both treatment arms. Nevertheless, the incidence of hyperkalemia leading to hospitalization and treatment discontinuation was low across treatment arms.

Conclusions

Finerenone significantly reduced the composite kidney outcome, showed a trend to reduce cardiovascular outcomes, and demonstrated an acceptable safety profile in Chinese patients.

Risk Evaluation of Progression of Proteinuria and Renal Decline Based on a Novel Subgroup Classification in Chinese Patients with Type 2 Diabetes

INTRODUCTION

Type 2 diabetes mellitus (T2DM) is a highly heterogeneous disease with a varying risk of complications. The recent novel subgroup classification using cluster analysis contributed to the risk evaluation of diabetic complications. However, whether the subgroup classification strategy could be adopted to predict the risk of onset and progression of diabetic kidney disease (DKD) in Chinese individuals with T2DM remains to be elucidated.

METHODS

In this retrospective study, 612 Chinese patients with T2DM were enrolled, and the median follow-up time was 3.5 years. The T2DM subgroups were categorized by a two-step cluster analysis based on five parameters, including age at onset of diabetes, body mass index (BMI), glycosylated hemoglobin (HbA1c), homeostasis model assessment 2 of insulin resistance (HOMA2-IR), and homeostasis model assessment 2 of β-cell function (HOMA2-β). Clinical characteristics across subgroups were compared using t-tests and chi-square tests. Furthermore, multivariate logistic regression models were adopted to assess the risk of albuminuria progression and renal function decline among different subgroups.

RESULTS

The cohort was categorized into four groups: severe insulin-deficient diabetes (SIDD), with 146 patients (23.9%); mild insulin resistance (MIRD), with 81 patients (13.2%); moderate glycemic control diabetes (MGCD), with 211 patients (34.5%); and moderate weight insulin deficiency diabetes (MWIDD), with 174 patients (28.4%). The MIRD group exhibited an increased risk of progression from non-albuminuria to albuminuria as compared with the MWIDD group, with an adjusted odds ratio (OR) and 95% confidence interval (CI) of 2.92 (1.06, 8.04). The SIDD group had a higher risk of progression from micro-albuminuria to macro-albuminuria as compared with the MGCD group, with an adjusted OR and 95% CI of 3.39 (1.01, 11.41). There was no significant difference in the glomerular filtration rate (GFR) decline among all groups.

CONCLUSION

The present study offered the first evidence for risk evaluation of the development of DKD in the novel cluster-based T2DM Chinese subgroups. It suggested that the MIRD subgroup had a higher risk of DKD onset than the MWIDD subgroup. Meanwhile, the SIDD subgroup showed a higher risk of progression of albuminuria than the MGCD subgroup. This novel classification system could be effective in predicting the risk of DKD in Chinese patients with T2DM, which could facilitate the implementation of personalized therapeutic strategies.

TRIAL REGISTRATION

This study was registered in the Chinese Clinical Trial Registry (ChiCTR2300077183).

The positive association between the atherogenic index of plasma and the risk of new-onset hypertension: a nationwide cohort study in China

BACKGROUND

The atherogenic index of plasma (AIP) is a novel metabolic biomarker of atherosclerosis. Nevertheless, the association between the AIP and new-onset hypertension has not been elucidated in the Chinese population.

METHODS

Prospective data were obtained from 3150 participants aged ≥ 18 years in the China Health and Nutrition Survey from 2009 to 2015. The AIP is a logarithmically transformed ratio of triglycerides to high-density lipoprotein cholesterol in molar concentration. Cox regression analysis was used to determine the association of AIP index with new-onset hypertension.

RESULTS

After the six-year follow-up, 1054 (33.4%) participants developed new-onset hypertension. The participants were divided into AIP quartile groups (Q1-Q4). Compared with those in Q1, subjects in Q3-4 had nearly 1.35 times the risk of new-onset hypertension after full adjustment [Q3: hazard ratio (HR): 1.35, 95% confidence interval (CI): 1.13-1.62; Q4: HR: 1.35, 95% CI: 1.13-1.64]. The risks of new-onset hypertension were nearly 1.30 times higher in subjects in Q2-4 than in subjects in Q1 (p < .01) after the full adjustment when we excluded subjects with diabetes and/or chronic kidney diseases. There was a significant difference [HR (CI): 1.27 (1.04-1.54) vs. 0.90 (0.69-1.18)] when subjects were divided into two groups according to body mass index (BMI) level (<24 vs. ≥24 kg/m2).

CONCLUSIONS

The present study suggested that individuals with a higher AIP index are associated with new-onset hypertension, independent of kidney function and glucose levels. The association was stronger in subjects with normal BMI, which may provide early screening of metabolomics in hypertension prevention.

Precision subclassification of type 2 diabetes: a systematic review

BACKGROUND

Heterogeneity in type 2 diabetes presentation and progression suggests that precision medicine interventions could improve clinical outcomes. We undertook a systematic review to determine whether strategies to subclassify type 2 diabetes were associated with high quality evidence, reproducible results and improved outcomes for patients.

METHODS

We searched PubMed and Embase for publications that used 'simple subclassification' approaches using simple categorisation of clinical characteristics, or 'complex subclassification' approaches which used machine learning or 'omics approaches in people with established type 2 diabetes. We excluded other diabetes subtypes and those predicting incident type 2 diabetes. We assessed quality, reproducibility and clinical relevance of extracted full-text articles and qualitatively synthesised a summary of subclassification approaches.

RESULTS

Here we show data from 51 studies that demonstrate many simple stratification approaches, but none have been replicated and many are not associated with meaningful clinical outcomes. Complex stratification was reviewed in 62 studies and produced reproducible subtypes of type 2 diabetes that are associated with outcomes. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into clinically meaningful subtypes.

CONCLUSION

Critical next steps toward clinical implementation are to test whether subtypes exist in more diverse ancestries and whether tailoring interventions to subtypes will improve outcomes.

Systematic review of precision subclassification of type 2 diabetes

Heterogeneity in type 2 diabetes presentation, progression and treatment has the potential for precision medicine interventions that can enhance care and outcomes for affected individuals. We undertook a systematic review to ascertain whether strategies to subclassify type 2 diabetes are associated with improved clinical outcomes, show reproducibility and have high quality evidence. We reviewed publications that deployed 'simple subclassification' using clinical features, biomarkers, imaging or other routinely available parameters or 'complex subclassification' approaches that used machine learning and/or genomic data. We found that simple stratification approaches, for example, stratification based on age, body mass index or lipid profiles, had been widely used, but no strategy had been replicated and many lacked association with meaningful outcomes. Complex stratification using clustering of simple clinical data with and without genetic data did show reproducible subtypes of diabetes that had been associated with outcomes such as cardiovascular disease and/or mortality. Both approaches require a higher grade of evidence but support the premise that type 2 diabetes can be subclassified into meaningful groups. More studies are needed to test these subclassifications in more diverse ancestries and prove that they are amenable to interventions.