Introduction: Diabetic kidney disease (DKD) is characterized by impairment of renal glomerular and tubular cells. Low plasma levels of ceramides and lactosylceramides containing very long-chain (VLC) fatty acid were found to be predictive of DKD development. Elongase 1 (Elovl1) is a ubiquitous elongase that elongates C20-C22 fatty acids to generate VLC C24 fatty acids. Using a novel transgenic (TG) mouse overexpressing Elovl1, we investigated whether modification to sphingolipid fatty acid composition averts DKD development. Methods: A TG mouse overexpressing Elovl1 was created at the Medical University of South Carolina/Transgenic Core. Elovl1 TG and wild type (WT) mice were rendered diabetic using serial streptozotocin injections. Plasma, kidney, liver, and urine sphingolipidomics of diabetic and non-diabetic TG and WT mice were analyzed using mass spectroscopy and matrix-assisted laser desorption/ionization-imaging mass spectrometry. Sphingolipid metabolizing enzymes were analyzed using immunohistochemical and multispectral imaging coupled with digital analysis. Results: Plasma sphingomyelins were higher, but lactosylceramides were lower in diabetic TG than in diabetic WT mice. Kidney lactosylceramides were also lower in diabetic TG mice. In urine, diabetic TG mice excreted more VLC lactosylceramides than diabetic WT mice, but less VLC sphingomyelins, VLC ceramides, sphingosine and sphingosine 1-phosphate. There was extensive damage to proximal tubules in kidneys of diabetic WT mice compared to diabetic TG mice. Glomeruli in diabetic WT kidneys appeared also abnormal, whereas no obvious abnormality of glomeruli in diabetic TG was observed. In diabetic TG, Elovl1 overexpression resulted in decreased kidneys levels of both ceramide synthase and acid sphingomyelinase, but increased acid ceramidase levels compared to non-diabetic TG mice. Conclusion: The diabetic Elovl1 TG mouse revealed interaction between Elovl1 overexpression and DKD development, and showed that distinct VLC sphingolipids could be involved in maintaining cell membrane integrity of renal cells.
Autosomal Dominant Polycystic Kidney Disease (ADPKD) is one of the most common inherited kidney disorders characterized by the progressive formation of renal cysts. It is a systemic disease with significant extra-renal manifestations. Among these, cardiac electrical abnormalities are increasingly recognized as clinically important yet underappreciated contributors to cardiovascular morbidity and mortality. Beyond cyst formation, pathogenic variants in PKD1 or PKD2, which encode polycystin-1 (PC1) and polycystin-2 (PC2), respectively, interfere with calcium homeostasis, mechanotransduction, and mitochondrial function in both kidney and heart tissues. These molecular changes trigger a cascade of pathological events, including RAAS activation, TGF-driven fibrosis, and oxidative stress, leading to structural and electrical remodeling of the heart. These alterations contribute to cardiac electrical remodeling, manifesting clinically as QT interval and corrected QT (QT/QTc) prolongation, left ventricular hypertrophy, atrial fibrillation, ventricular arrhythmias, and other electrocardiographic abnormalities. Despite growing evidence, cardiac electrical abnormalities in ADPKD remain understudied in clinical practice. Early detection of subclinical cardiovascular abnormalities may be facilitated by electrocardiographic monitoring, cardiac imaging, and complementary biomarker assessment. Additionally, findings from iPSC-derived cardiomyocyte models support the translational potential of personalized drug-screening platforms. This review summarizes current evidence linking polycystin dysfunction to cardiac electrical abnormalities in ADPKD by integrating molecular mechanisms with experimental and clinical findings. It also highlights the need for integrated cardio-renal approaches to improve cardiovascular surveillance, risk stratification, and future therapeutic development in ADPKD.
Background Diabetic kidney disease (DKD) is the leading cause of CKD globally. Despite marked heterogeneity in progression, risk stratification remains anchored to single-timepoint measures that fail to capture individual patient trajectories. We aimed to identify clinically meaningful DKD subgroups from real-world longitudinal data and characterise their molecular signatures using integrative multi-omics. Methods In this retrospective cohort study, unsupervised clustering of longitudinal creatinine and haematocrit trajectories was performed in the Salford Kidney Study (SKS; n=335 eligible for clustering, n=303 DKD) and validated in two independent cohorts: Scottish Health Research Register (SHARE; n=824) and CERCA-Diabetes (Spain; n=187). Prognostic performance was assessed by C-statistic, time-dependent area under the curve (AUC), IDI (integrated discrimination improvement), and decision curve analysis relative to the Kidney Failure Risk Equation (KFRE) and Kidney Disease Improving Global Outcomes (KDIGO) risk categorisation. Multi-omic characterisation (proteomics, metabolomics, DNA methylation) was performed in an 87-patient SKS subset using Data Integration Analysis for Biomarker Discovery using Latent Components (DIABLO). Results Two groups with markedly different progression rates were identified: high-risk (SKS-HR; n=173) and low-risk (SKS-LR; n=162). SKS-HR showed eGFR decline nearly four times faster and a higher rate of the composite kidney failure endpoint (HR 4.05 [95% CI 2.77–5.92] adjusted for age, sex, and eGFR; 2.95 [1.90–4.56] after further adjustment for haemoglobin, proteinuria, HbA1c, and cardiovascular burden; both p<0.0001). The signal was specific to renal progression (fully adjusted HR 5.98 [3.32–10.79], p<0.0001) and absent for cardiovascular or renal death (HR 1.00 [0.58–1.71], p=0.984). The subgroup-outcome association was independently replicated in SHARE (p=3.83×10⁻²⁷) and CERCA-Diabetes (p=1.72×10⁻⁴). The subgrouping added prognostic information complementary to the KFRE, raising the C-statistic from 0.689 to 0.721 when added to static KFRE and 0.711 to 0.732 when added to longitudinal KFRE. KDIGO risk categories showed limited discriminatory capacity in this predominantly G3b–G4 cohort. Hypothesis-generating multi-omic profiling showed FDR-significant enrichment for lipid transport pathways and for an independent DKD progression proteomic signature; all multi-omic findings require independent validation. Conclusions Longitudinal creatinine and haematocrit trajectories, available from routine clinical records, identify DKD patients at high risk of kidney failure with prognostic information beyond current risk tools. The high-risk subgroup warrants prospective validation and evaluation of whether subgroup assignment can improve risk stratification beyond existing clinical tools.
Introduction: Mounting evidence suggests dysregulated metabolism as a feature of autosomal dominant polycystic kidney disease (ADPKD) and that mild-to-moderate food restriction significantly slows cyst growth in murine models. Epidemiological data and a pilot and feasibility study in humans further support that targeting weight and adiposity loss via daily caloric restriction (DCR) is a potential strategy to slow kidney growth in adults with ADPKD and overweight or obesity. Methods: This is a single site, randomized, single blind (investigator), parallel-group, controlled trial that randomized 120 participants to a 24-month DCR-based behavioral weight loss intervention or control (standard clinical dietary advice for ADPKD) (NCT04907799). The primary outcome is change in height-adjusted total kidney volume by magnetic resonance imaging over a 24-month duration. 84 women and 36 men were randomized, and the study population was 93% Non-Hispanic White. At baseline, mean ± s.d. age was 45 ± 11 years, the mean CKD-EPI eGFR was 68 ± 26 ml/min/1.73m2, and the median (interquartile range) htTKV was 986 (700, 1398) ml/m. Twenty-nine (24%) participants were using tolvaptan at baseline. The final study cohort will be completed in July 2027. Conclusions: This is the first phase 2, randomized clinical trial targeting caloric restriction in patients with ADPKD, and will provide important insight to the research community, patients, and providers.
Introduction: Fluid intake is widely recommended in clinical practice, yet evidence linking habitual fluid intake to kidney outcomes remains inconsistent. We evaluated dose–response associations between fluid intake volume and kidney function decline or prevalent advanced chronic kidney disease. Methods: We searched EMBASE, PubMed, and the Cochrane Library through Feb 2025 for adult studies reporting total fluid intake, plain water intake, or urine volume in relation to eGFR decline or prevalent advanced-stage chronic kidney disease. Random-effects meta-regression and two-stage dose–response meta-analysis were used to assess linear and non-linear associations, with prespecified subgroup analyses by baseline kidney function. Results: Sixteen studies including 70,053 participants were included. Higher total fluid intake was linearly associated with slower eGFR decline (p = 0.02; β = 0.97 mL/min/1.73 m²/year; 95% CI 0.15–1.79) and with lower odds of prevalent advanced-stage chronic kidney disease (p < 0.001; log-OR −0.27; 95% CI −0.43 to −0.11). In subgroup analyses, this association was observed in studies with mean baseline eGFR ≥60 mL/min/1.73 m² (p = 0.016), but not in studies with mean baseline eGFR <60 mL/min/1.73 m². Evidence for plain water intake and urine volume was limited. Conclusions: Higher daily total fluid intake, within the ranges studied, was associated with slower eGFR decline and lower odds of prevalent advanced CKD, particularly among studies with mean baseline eGFR ≥60 mL/min/1.73 m². Because the evidence was predominantly observational, these findings cannot establish that increasing fluid intake preserves kidney function. Future studies should distinguish plain water from other beverage categories and incorporate objective biomarkers of hydration and volume status. Registration: CRD42024627796
