A catalog of genetic loci associated with kidney function from analyses of a million individuals

The impact of leisure sedentary behaviors on risk of chronic kidney disease, diabetes, and related complications: Mendelian randomization study

BACKGROUND

The causal relationship between leisure sedentary behaviors (LSBs) and chronic kidney disease, diabetes and related complications is still equivocal. In this study, we performed two-sample Mendelian randomization for declaring the potential causal association between LSBs and these diseases and summarized the causal estimates.

METHODS

In this study, we used GWAS summary statistics from the public database for exposures (LSB: television watching, computer use, and driving) and outcomes (chronic kidney diseases, diabetes mellitus, and related complications). To ensure reliable results for this study, we applied several methods including IVW, MR-Egger, and weighted median for the regression process; MR-Egger intercept test, Cochran's Q test, 'leave-one-out' analysis and MR-PRESSO test were used to detect horizontal pleiotropy and heterogeneity for sensitivity analysis.

RESULTS

Television watching was harmful of CKD (OR = 1.26, 95%CI 1.09-1.44; p = 0.0011), T2D (OR = 1.82, 95%CI 1.48-2.24; p = 1.67e - 08) and DM (OR = 2.26, 95%CI 1.75-2.93; p = 6.44e - 10). No horizontal pleiotropy was detected in MR-Egger intercept test (p value > 0.05) and there were no influential SNPs based on 'leave-one-out' analysis.

CONCLUSIONS

Mendelian randomization estimates in our study genetically predicted the causal effect between television watching and CKD, T2D, and DM. However, we cannot get the definitive causal effect of television watching and other related complications, further studies need to be done to explore the mechanism of action of sedentary behavior on the complications of diabetes and chronic kidney disease.

The impact of rising peripheral blood naïve CD8+ T cell levels on chronic kidney disease onset: a Mendelian randomization study

BACKGROUND

The global incidence of chronic kidney disease (CKD) is rising rapidly. Immune cells play a crucial role in the onset and progression of CKD, however, the causal relationships and underlying immunological mechanisms remain incompletely elucidated. This deficiency hinders the development and application of early interventions and immunotherapies for CKD.

METHODS

In this study, we hypothesize that alterations in immune cell phenotypes (ICPs) in the blood may influence the onset of CKD. We collated Genome Wide Association Studies (GWAS) data for 731 ICPs, alongside summary data for CKD and estimated glomerular filtration rate (eGFR). Utilizing bidirectional mendelian randomization analysis (MR), we identified the impact of ICPs on the onset of CKD.

RESULTS

Preliminary MR analyses revealed three ICPs positively associated with CKD onset: the absolute number of CD45RA+ CD28- CD8+ T cells (p = 1.209 × 10-15, 95% CI: 1.0002-1.0003), the percentage of CD28+ CD45RA+ CD8+ T cells of total T cells (p = 5.831 × 10-6, 95% CI: 1.0028-1.0070), and the percentage of CD45RA- CD28- CD8+ T cells of total T cells (p = 4.292 × 10-5, 95% CI: 1.0005-1.0015). After conducting sensitivity and reverse MR analyses, only the percentage of CD28+ CD45RA+ CD8+ T cells (naïve CD8+ T Cells) was found to have a sufficiently robust causal impact on CKD.

CONCLUSION

We are the first to demonstrate a significant positive association between the percentage of naïve CD8+ T cells and CKD onset. This finding offers new insights for early prevention and treatment of CKD.

Causal relationship between chronic kidney disease, renal function, and venous thromboembolism: a bidirectional Mendelian randomization study

BACKGROUND

Chronic kidney disease (CKD) and impaired renal function have been implicated in venous thromboembolism (VTE), but their causal relationships remain uncertain. This study employs Mendelian randomization (MR) to elucidate the potential bidirectional causal effects between CKD, renal function biomarkers, and VTE.

METHODS

We collated datasets from genome-wide association studies conducted among European individuals to perform MR analyses. The primary method utilized was the random-effect inverse variance-weighted (IVW) approach, with MR-Egger and the weighted median approaches employed as supplemental techniques. Several sensitivity studies were performed to assess the findings' robustness.

RESULTS

We identified a link between elevated serum creatinine levels and both VTE (OR: 1.14, 95% CI: 1.05-1.24, p = 0.001) and PE (OR: 1.20, 95% CI: 1.08-1.33, p = 0.001). After outlier removal and Bonferroni correction, the Cr-VTE association lost significance (p = 0.005). A suggestive causal relationship was found between eGFR and VTE (OR: 0.38, 95% CI: 0.20-0.73, p = 0.004), DVT (OR: 0.37, 95% CI: 0.16-0.87, p = 0.022), and PE (OR: 0.29, 95% CI: 0.12-0.66, p = 0.004). No causal effects of CKD or BUN on VTE or its subtypes were observed. Reverse causality inferences did not reveal any meaningful results.

CONCLUSIONS

This MR analysis provides evidence that elevated serum creatinine is associated with a higher risk of VTE and PE, while reduced eGFR may be a potential risk factor for VTE and its subtypes. These findings highlight the need for proactive monitoring and preventive strategies in individuals with impaired renal function. Further studies are warranted to confirm these associations and explore underlying mechanisms.

Causal associations between circulating metabolites and chronic kidney disease: a Mendelian randomization study

BACKGROUND

Circulating metabolites have been associated with cross-sectional renal function in population-based research. Nevertheless, there is currently little proof to support the idea that metabolites either cause or prevent renal function. New treatment targets and ways to screen individuals with impaired renal function will be made possible via an in-depth analysis of the causal relationship between blood metabolites and renal function.

METHODS

We assessed the causal relationship between 452 serum metabolites and six renal phenotypes (CKD, rapid progression to CKD [CKDi25], rapid eGFR decline [CKD rapid3], dialysis, estimated glomerular filtration rate, and blood urea nitrogen) using univariate Mendelian randomization, primarily employing the inverse variance weighted method with robust sensitivity analyses. Heterogeneity and pleiotropy were examined via Cochrane's Q test and MR-Egger regression, and statistical significance was adjusted using Bonferroni correction. To assess potential adverse effects of metabolite modulation, we conducted a phenome-wide Mendelian randomization analysis, followed by multivariate Mendelian randomization to adjust for confounders.

RESULTS

We identified glycine and N-acetylornithine as potential causal mediators of CKD and renal dysfunction. Notably, lowering glycine levels may increase the risk of cholelithiasis and cholecystitis, while reducing N-acetylornithine could have unintended effects on tinnitus.

CONCLUSION

Glycine and N-acetylornithine represent promising therapeutic targets for CKD and renal function preservation, but their modulation requires careful risk-benefit assessment to avoid adverse effects.

Updates on renal phosphate transport

PURPOSE OF REVIEW

The kidneys control systemic phosphate balance by regulating phosphate transporters mediating the reabsorption of inorganic phosphate (Pi). At least three different Na + -driven Pi cotransporters are located in the brush border membrane (BBM) of proximal tubule cells, NaPi-IIa (SLC34A1), NaPi-IIc (SLC34A3) and PiT-2 (SLC20A2). This review will discuss novel aspects of their regulation, pharmacology, and genetics.

RECENT FINDINGS

Renal NaPi transporters are not only acutely regulated by the phosphaturic hormones parathyroid hormone (PTH) and Fibroblast Growth Factor 23 (FGF23) but possibly also by further mechanisms. A role of inositol hexakisphosphate (IP6) kinases has been found and their deletion from kidneys causes hypophosphatemia, hyperphosphaturia, and bone demineralization. Inhibitors of NaPis elicit phosphaturia and may reduce levels of PTH and FGF23 in chronic kidney disease (CKD) models. The relevance of renal NaPi transporters is highlighted by loss-of-function mutations in SLC34 transporters and analysis of patients provides new insights into diseases caused by variants. Major manifestations include nephrocalcinosis and -lithiasis, rickets, and variants may predispose to an accelerated decline in kidney function.

SUMMARY

Renal Pi transporters are regulated, may provide novel drug targets for prevention or treatment of hyperphosphatemia, and contribute to the genetic risk to develop kidney stones and CKD.

Performance of Current Chronic Kidney Disease Screening Criteria in Women and Men Across Ethnic Groups: The HELIUS Study

Objective

To investigate whether the currently recommended screening criteria in Kidney Disease: Improving Global Outcomes 2024 guidelines (hypertension, diabetes mellitus, and cardiovascular disease) equally detect women and men across ethnic groups and whether consideration of optional criteria (education level, occupation, obesity, and genetic risk factors) listed in the guideline improves performance.

Patients and Methods

We included 12,384 women and 9046 men of Dutch, South Asian and African Surinamese, Ghanaian, Turkish, and Moroccan origin from the baseline HELIUS Study (January 1, 2011, through December 31, 2015, Amsterdam, the Netherlands). Chronic kidney disease (CKD) was defined as estimated glomerular filtration rate of <60 mL/min/1.73 m2 or albumin-to-creatinine ratio of >3 mg/mmol. Poisson regression analyses estimated associations between CKD and optional criteria on top of current screening criteria. Model comparisons were made with likelihood ratio tests and Akaike information criterion estimations in women and men. Area under the curve (AUC), sensitivity, specificity, and positive and negative predictive values were calculated by sex and ethnicity.

Results

Chronic kidney disease prevalence ranged from 2.9% to 8.8% in women and 3.2% to 8.6% in men. Low educational level (women only) and obesity significantly improved the models with current criteria with CKD. High-risk occupations and polygenic risk score did not improve the model. However, these criteria did not improve predictive measures across ethnic groups. Overall, the AUCs for the current screening criteria were acceptable in men (AUC, 0.75; 95% CI, 0.73-0.77) and poor in women (AUC, 0.65; 95% CI, 0.63-0.67), and showed minimal change after adding the optional criteria.

Conclusion

Current screening criteria may not be equally detecting women and men across ethnic groups with CKD. Optional criteria had limited added value.

Validation of L-type calcium channel blocker amlodipine as a novel ADHD treatment through cross-species analysis, drug-target Mendelian randomization, and clinical evidence from medical records

ADHD is a chronic neurodevelopmental disorder that significantly affects life outcomes, and current treatments often have adverse side effects, high abuse potential, and a 25% non-response rate, highlighting the need for new therapeutics. This study investigates amlodipine, an L-type calcium channel blocker, as a potential foundation for developing a novel ADHD treatment by integrating findings from animal models and human genetic data. Amlodipine reduced hyperactivity in SHR rats and decreased both hyperactivity and impulsivity in adgrl3.1-/- zebrafish. It also crosses the blood-brain barrier, reducing telencephalic activation. Crucially, Mendelian Randomization analysis linked ADHD to genetic variations in L-type calcium channel subunits (α1-C; CACNA1C, β1; CACNB1, α2δ3; CACNA2D3) targeted by amlodipine, while polygenic risk score analysis showed symptom mitigation in individuals with high ADHD genetic liability. With its well-tolerated profile and efficacy across species, supported by genetic evidence, amlodipine shows potential to be refined and developed into a novel treatment for ADHD.

New composite phenotypes enhance chronic kidney disease classification and genetic associations

Chronic kidney disease (CKD) is a multifactorial condition driven by diverse etiologies that lead to a gradual loss of kidney function. Although genome-wide association studies (GWAS) have identified numerous genetic loci linked to CKD, a large portion of its genetic basis remains unexplained. This knowledge gap may partly arise from the reliance on single biomarkers, such as estimated glomerular filtration rate (eGFR), to assess kidney function. To address this limitation, we developed and applied a novel multi-phenotype approach, combinatorial Principal Component Analysis (cPCA), to better understand the complex genetic architecture of CKD. Using UK Biobank dataset (n = 337,112), we analyzed 21 CKD-related phenotypes, generating over 2 million composite phenotypes (CPs) through cPCA. Nearly 50,000 of these CPs demonstrated significantly higher classification power for clinical CKD compared to individual biomarkers. The top-ranked CP-a combination of albumin, cystatin C, eGFR, gamma-glutamyltransferase, HbA1c, low-density lipoprotein, and microalbuminuria, achieved an AUC of 0.878 (95% CI: 0.873-0.882), significantly outperforming eGFR alone (AUC: 0.830, 95% CI: 0.825-0.835). Genetic association analysis of the ~ 50,000 high-performing CPs identified all major eGFR-associated loci, except for the SH2B3 locus rs3184504, a loss-of-function variant, which was uniquely identified in CPs (p = 3.1[Formula: see text]10-56) but not in eGFR within the same sample size. In addition, SH2B3 locus showed strong evidence of colocalization with eGFR, supporting its role in kidney function. These results highlight the power of the multi-phenotype cPCA approach in understanding the genetic basis of CKD, with potential applications to other complex diseases.

Renal-Cardiac Crosstalk in the Pathogenesis and Progression of Heart Failure

Chronic kidney disease (CKD) represents a global health issue with a high socioeconomic impact. Beyond a progressive decline of kidney function, patients with CKD are at increased risk of cardiovascular diseases, including heart failure (HF) and sudden cardiac death. HF in CKD can manifest both as HF with reduced ejection fraction and HF with preserved ejection fraction, with the latter further increasing in relative importance in the more advanced stages of CKD. Typical cardiac remodeling characteristics in uremic cardiomyopathy include left ventricular hypertrophy, myocardial fibrosis, cardiac electrical dysregulation, capillary rarefaction, and microvascular dysfunction, which are triggered by increased cardiac preload, cardiac afterload, and preload and afterload-independent factors. The pathophysiological mechanisms underlying cardiac remodeling in CKD are multifactorial and include neurohormonal activation (with increased activation of the renin-angiotensin-aldosterone system, the sympathetic nervous system, and mineralocorticoid receptor signaling), cardiac steroid activation, mitochondrial dysfunction, inflammation, innate immune activation, and oxidative stress. Furthermore, disturbances in cardiac metabolism and calcium homeostasis, macrovascular and microvascular dysfunction, increased cellular profibrotic responses, the accumulation of uremic retention solutes, and mineral and bone disorders also contribute to cardiovascular disease and HF in CKD. Here, we review the current knowledge of HF in CKD, including the clinical characteristics and pathophysiological mechanisms revealed in animal studies. We also elaborate on the detrimental impact of comorbidities of CKD on HF using hypertension as an example and discuss the clinical characteristics of hypertensive heart disease and the genetic predisposition. Overall, this review aims to increase the understanding of HF in CKD to support future research and clinical translational approaches for improved diagnosis and therapy of this vulnerable patient population.

Genetically proxied glucokinase activation and risk of diabetic complications: Insights from phenome-wide and multi-omics mendelian randomization

AIMS

This study aims to assess the benefits and adverse effects of long-term glucokinase (GK) activation from a genetic perspective.

METHODS

We identified genetic variants in the GCK gene associated with glycated hemoglobin (HbA1c) levels from a genome-wide association study (GWAS) involving 146,806 individuals, which served as proxies for glucokinase activation. To assess the effects and potential pathways of GK activation on a range of diabetic complications and safety outcomes, we integrated drug-target Mendelian randomization (MR), lipidome-wide and proteome-wide MR, phenome-wide MR, and colocalization analyses.

RESULTS

Genetically proxied GK activation was associated with reduced risks of several predefined diabetic complications, including cardiovascular diseases, stroke and diabetic retinopathy. No kidney-related benefits were observed. Safety analysis revealed a relationship between GK activation and elevated AST levels, while impaired interaction between GK and glucokinase regulatory protein (GKRP) was associated with dyslipidemia, increased liver fat content, AST, systolic blood pressure, and uric acid. Phenome-wide MR suggested that GK activation may have potential benefits for lung function and fluid intelligence score.

CONCLUSIONS

Our genetic evidence supports GK as a promising target for reducing the risk of specific diabetic complications. These findings require further validation through cohort studies and randomized controlled trials in patients with diabetes.

Emerging antihypertensive therapies and cardiovascular, kidney, and metabolic outcomes: a Mendelian randomization study

AIMS

Emerging antihypertensive drug classes offer new opportunities to manage hypertension; however, their long-term effects on cardiovascular, kidney, and metabolic (CKM) outcomes remain to be elucidated. This study aims to explore the effects of phosphodiesterase type 5 inhibitors (PDE5i), soluble guanylate cyclase stimulators (sGCs), endothelin receptor antagonists (ERAs), and angiotensinogen inhibitors (AGTis) on a range of CKM outcomes.

METHODS AND RESULTS

Mendelian randomization (MR), summary-based MR (SMR), and colocalization analyses were applied to assess the drug effect on coronary artery disease (CAD), myocardial infarction (MI), ischaemic stroke, atrial fibrillation (AF), heart failure (HF), type 2 diabetes (T2D), and chronic kidney disease (CKD). Genetic association and gene expression summary data were obtained from the largest European-ancestry genome-wide association studies (GWAS) and the genotype-tissue expression version 8 for 29 tissues relevant to the outcomes' pathophysiology.Genetically predicted systolic blood pressure (SBP) reduction was associated with reduced risks of all outcomes. PDE5i was associated with reduced risks of CAD (OR per 10-mmHg decrease in SBP: 0.348[95% confidence interval (CI): 0.199-0.607]) and ischaemic stroke (0.588[0.453-0.763]). sGCs showed protective effects against CAD (0.332[0.236-0.469]), MI (0.238[0.168-0.337]), and CKD (0.55[0.398-0.761]). ERA and AGTi showed protective effects against CAD and ischaemic stroke. SMR and colocalization supported the association of gene expression levels of GUCY1A3 and PDE5A with CAD and MI risk.

CONCLUSION

Our study highlights the potential of PDE5i, sGCs, ERA, and AGTi in reducing cardiovascular and renal risks. These findings underscore the necessity for targeted clinical trials to validate the efficacy and safety of these therapies.

Causal Effects From Kidney Function to Plasma Proteome: Integrated Observational and Mendelian Randomization Analysis With >50,000 UK Biobank Participants

PURPOSE

Chronic kidney disease (CKD) causes detrimental systemic effects, including inflammation or apoptosis, which lead to substantial morbidity and mortality. However, the causal effect of reduced kidney function on systemic proteomic signatures is incompletely understood.

METHODS

We performed an integrated Mendelian randomization (MR) and observational analyses to identify the causal association between kidney function and plasma protein levels, based on 1815 plasma protein profiles in 50,407 UK Biobank participants and the CKDGen Phase 4 genome-wide association study (GWAS) meta-analysis for the genetic instruments of eGFR.

RESULTS

The MR analysis revealed 383 plasma proteins causally associated with eGFR. Reduced kidney function was found to be causally associated with an increase in the plasma levels of 381 proteins, among which TNF and IGFBP4 were increased, while the level of two proteins, NPHS1 and SPOCK1, decreased. Apoptosis-related pathway was significantly enriched in the gene-set enrichment analysis. In network analysis, TNF was identified as a hub protein with multiple linkages to molecules included in the TNF-signaling pathways, involved in inflammation, fibrosis, and apoptosis.

CONCLUSIONS

In this proteo-genomic analysis, we identified 383 plasma proteins causally associated with eGFR, highlighting TNF-associated pathways as pathologically relevant processes in kidney disease progression, systemic inflammation, and organ fibrosis, warranting further investigation.

Application of biomarkers in the diagnosis of kidney disease

Worldwide, kidney disease has grown to be an important global public health agenda that reduces longevity. Medical institutions around the globe should enhance screening efforts for kidney disease, to facilitate early kidney disease detection, diagnosis, and intervention. Common screening methods for nephropathy encompass renal tissue biopsy, urine dry chemistry tests, urine formed element analysis, and urine-specific protein assays, among others. These methodologies evaluate renal health by scrutinizing a spectrum of biomarkers. Precise classification and quantitative analysis of these biomarkers can assist in determining the site and extent of kidney injury, as well as in assessing treatment efficacy and prognosis. In this paper, we reviewed the methods and biomarkers for kidney disease and also the integration of multiple biomarkers. With the aim of reasonable applying these markers to the early detection, accurate diagnosis, and scientific management of kidney disease, thereby mitigating the threat posed by kidney disease to human health.

A Mendelian randomization analysis of cardiac MRI measurements as surrogate outcomes for heart failure and atrial fibrillation

BACKGROUND

Drug development and disease prevention of heart failure (HF) and atrial fibrillation (AF) are impeded by a lack of robust early-stage surrogates. We determined to what extent cardiac magnetic resonance (CMR) measurements act as surrogates for the development of HF or AF.

METHODS

Genetic data were sourced on the association with 21 atrial and ventricular CMR measurements. Mendelian randomization was used to determine CMR associations with AF, HF, non-ischaemic cardiomyopathy (NICM), and dilated cardiomyopathy (DCM), noting that the definition of NICM includes DCM as a subset. Additionally, for the CMR surrogates of AF and HF, we explored their association with non-cardiac traits potentially influenced by cardiac disease liability.

RESULTS

In total we find that 7 CMR measures (biventricular ejection fraction (EF) and end-systolic volume (ESV), as well as LV systolic volume (SV), end-diastolic volume (EDV), and mass to volume ratio (MVR)) associate with the development of HF, 5 with the development of NICM (biventricular EDV and ESV, LV-EF), 7 with DCM (biventricular EF, ESV, EDV, and LV end-diastolic mass (EDM), and 3 associate with AF (LV-ESV, RV-EF, RV-ESV). Higher EF of both ventricles associate with lower risk of HF and DCM, with biventricular ESV associating with all four cardiac outcomes. Higher values of biventricular EDV associate with lower risk of HF, and DCM. Exploring the associations of these CMR cardiac disease surrogates with non-cardiac traits confirms a strong link with diastolic blood pressure, as well as more specific associations with lung function (LV-ESV), HbA1c (LV-EDM), and type 2 diabetes (LV-SV).

CONCLUSIONS

The current paper identifies key CMR measurements that may act as surrogate endpoints for the development of HF (including NICM and DCM) or AF.

Genetic analysis of elevated levels of creatinine and cystatin C biomarkers reveals novel genetic loci associated with kidney function

The rising prevalence of chronic kidney disease (CKD), affecting an estimated 37 million adults in the United States, presents a significant global health challenge. CKD is typically assessed using estimated Glomerular Filtration Rate (eGFR), which incorporates serum levels of biomarkers such as creatinine and cystatin C. However, these biomarkers do not directly measure kidney function; their elevation in CKD results from diminished glomerular filtration. Genome-wide association studies (GWAS) based on eGFR formulas using creatinine (eGFRcre) or cystatin C (eGFRcys) have identified distinct non-overlapping loci, raising questions about whether these loci govern kidney function or biomarker metabolism. In this study, we show that GWAS on creatinine and cystatin C levels in healthy individuals reveal both nonoverlapping genetic loci impacting their metabolism as well as overlapping genetic loci associated with kidney function; whereas GWAS on elevated levels of these biomarkers uncover novel loci primarily associated with kidney function in CKD patients.

The Identification of Biomarkers and Therapeutic Targets for Diabetic Kidney Disease by Integrating the Proteome with the Genome

Background: The blood proteome is a major source of biomarkers and therapeutic targets. We conducted a proteome-wide Mendelian randomization (MR) study to identify cardiometabolic protein markers for diabetic kidney disease (DKD). Methods: We measured all 369 proteins in the Olink Explore 384 Cardiometabolic and Cardiometabolic panel of 500 patients with type 2 diabetes from 11 communities in Shanghai. Protein quantitative trait loci (pQTLs) were derived by coupling genomic and proteomic data. Cis-pQTLs identified for proteins were used as instrumental variables in MR analyses of DKD risk, and the outcome data were obtained from 8401 Japanese individuals with type 2 diabetes (2809 cases and 5592 controls). Replication MR analysis was performed in the UK Biobank Pharma Proteomics Project (UKB-PPP). Colocalization analysis and the Heidi test were used to examine whether the identified proteins and DKD shared causal variants. Results: Among the 369 proteins, we identified 66 independent cis-pQTLs for 64 proteins. MR analysis suggested that two cardiometabolic proteins (UMOD and SIRPA) may play a causal role in increasing DKD risk, with UMOD showing replication in UKB-PPP. Bayesian colocalization further supported the causal effects of these proteins. Additional analyses indicated that UMOD is highly expressed in renal macrophages. Further downstream analyses suggested that UMOD could be a potential novel target and that SIRPA could be a potential repurposing target for DKD; however, further validation is needed. Conclusions: By integrating proteomic and genetic data from patients with type 2 diabetes, we identified two protein biomarkers potentially associated with DKD risk. These findings provide insights into DKD pathophysiology and therapeutic target development, but further replication and functional studies are needed to confirm these associations.

Sedentary lifestyle and hallux valgus: Unraveling the causal pathways and the mediating role of calcium homeostasis through mendelian randomization

The causal relationships between hallux valgus (HV), sedentary behavior and calcium homeostasis remain unclear. This study aimed to explore these associations using Mendelian randomization (MR) analysis. Leisure screen time (LST) was used as an indicator of sedentary behavior, while seven traits and three diseases were selected to represent calcium homeostasis. Two-sample MR was performed to assess the causal effect of sedentary behavior and calcium homeostasis on HV. Two-step MR was conducted to quantify the mediating roles of calcium homeostasis-related traits in the association between sedentary behavior and HV. Our results showed that longer LST was strongly associated with higher risk of HV (odds ratio (OR) = 1.1902, 95 %CI = 1.0129-1.3986, p = 0.0343). By contrast, serum calcium (S-Ca) levels were negatively associated with HV risk (OR = 0.7530, 95 %CI = 0.5675-0.9992, p = 0.0494). Mediation analyses found that S-Ca played an important mediating role in the effect of LST on HV (proportion mediated = 10.4 %). Our results extend the understanding of the pathogenesis of HV, and highlight the importance of preoperative metabolic optimization and postoperative behavioral and calcium supplementation strategies to enhance surgical outcomes and mitigate recurrence.

Preschool age-specific obesity and later-life kidney health: a Mendelian randomization and colocalization study

OBJECTIVES

While the association between obesity and kidney diseases has been found in previous studies, the relationship between preschool-age obesity and later-life kidney health remains unclear, posing challenges for effective interventions in this critical life period.

METHODS

Utilizing the hitherto largest genome-wide association studies, we conducted two-sample mendelian randomization (MR) to estimate the association of preschool age-specific obesity on kidney health and diseases, including blood urea nitrogen (BUN), eGFRcrea, eGFRcys, chronic kidney disease (CKD), IgA nephropathy, and diabetic nephropathy. Then, we applied multivariable Mendelian randomization (MVMR) and stepwise MR to elucidate the role of adult obesity and 12 other potential factors in the pathway between preschool age-specific obesity and kidney health. Finally, we employed colocalization analysis to understand the mechanism of preschool age-specific obesity and kidney damage further by detecting shared causal variants.

RESULTS

Our two-sample MR results indicated that preschool obesity could be associated with kidney health and disease. In addition, we observed a switch in the direction of associations between age-specific body mass index (BMI) and CKD, manifesting as negative associations before 3 years old and positive associations after 3 years old. Furthermore, MVMR and stepwise MR results suggested potential pathways linking preschool obesity to kidney health, involving factors such as adult BMI, circulating high-density lipoprotein cholesterol levels, and circulating C-reactive protein levels. Finally, we detected that preschool-age BMI and kidney function could share causal variants such as rs76111507, rs62107261, rs77165542 in the region of chromosome 2, and rs571312 in the region of chromosome 18.

CONCLUSION

Our study supports the association between preschool obesity and kidney health, emphasizing the role of adult BMI in this relationship. These findings underscore the importance of interventions starting in early childhood and continuing through adulthood to reduce the long-term risk of obesity-related kidney damage.

The causal relationship of inflammation-related factors with osteoporosis: A Mendelian Randomization Analysis

BACKGROUND

We used Mendelian randomization (MR) approach to examine whether genetically determined inflammation-related risk factors play a role in the onset of osteoporosis (OP) in the European population.

METHODS

Genome-wide association studies (GWASs) summary statistics of estimated bone mineral density (eBMD) obtained from the public database GEnetic Factors for OSteoporosis Consortium (GEFOS) including 142,487 European people. For exposures, we utilized GWAS data of 9 risk factors including diseases chronic kidney disease (CKD) (41,395 cases and 439,303 controls), type 2 diabetes (T2D) (88,427 cases and 566,778 controls), Alzheimer's disease (AD) (71,880 cases, 383,378 controls) and major depression disorder (MDD) (9240 cases and 9519 controls) and lifestyle behaviors are from different consortiums. Inverse variance weighted (IVW) analysis was principal method in this study and random effect model was applied; MR-Egger method and weighted median method were also performed for reliable results. Cochran's Q test and MR-Egger regression were used to detect heterogeneity and pleiotropy and leave-one-out analysis was performed to find out whether there are influential SNPs.

RESULTS

We found that T2D (IVW: β = 0.05, P = 0.0014), FI (IVW: β = -0.22, P < 0.001), CKD (IVW: β = 0.02, P = 0.009), ALZ (IVW: β = 0.06, P = 0.005), Coffee consumption (IVW: β = 0.11, P = 0.003) were causally associated with OP (P<0.006after Bonferroni correction).

CONCLUSIONS

Our study revealed that T2D, FI, CKD, ALZ and coffee consumption are causally associated with OP. Future interventions targeting factors above could provide new clinical strategies for the personalized prevention and treatment of osteoporosis.

Estimated Glomerular Filtration Rate Decline is Causally Associated with Acute Pulmonary Embolism: A Nested Case-Control and Mendelian Randomization Study

Renal dysfunction is highly prevalent among patients with pulmonary embolism (PE). This study combined population-based study and Mendelian randomization (MR) to observe the relationship between renal function and PE.A nested case-control study were performed using data of PE patients and controls were from two nationwide cohorts, the China pUlmonary thromboembolism REgistry Study (CURES) and China Health and Retirement Longitudinal Survey (CHARLS). Baseline characteristics were balanced using propensity score matching and inverse probability of treatment weighting. Restricted cubic spline models were applied for the relationship between estimated glomerular filtration rate (eGFR) decline and the risk of PE. Bidirectional two-sample MR analyses were performed using genome-wide association study summary statistics for eGFR involving 1,201,909 individuals and for PE from the FinnGen consortium.The nested case-control study including 17,547 participants (6,322 PE patients) found that eGFR distribution was significantly different between PE patients and controls (p < 0.001), PE patients had a higher proportion of eGFR < 60 mL/min/1.73 m2. eGFR below 88 mL/min/1.73 m2 was associated with a steep elevation in PE risk. MR analyses indicated a potential causal effect of eGFR decline on PE (odds ratio = 4·26, 95% confidence interval: 2·07-8·79), with no evidence of horizontal pleiotropy and reverse causality.Our findings support the hypothesis that renal function decline contributes to an elevated PE risk. Together with the high prevalence of chronic kidney diseases globally, there arises the necessity for monitoring and modulation of renal function in effective PE prevention.

PPDPF preserves integrity of proximal tubule by modulating NMNAT activity in chronic kidney diseases

Genome-wide association studies (GWAS) have identified loci associated with kidney diseases, but the causal variants, genes, and pathways involved remain elusive. Here, we identified a kidney disease gene called pancreatic progenitor cell differentiation and proliferation factor (PPDPF) through integrating GWAS on kidney function and multiomic analysis. PPDPF was predominantly expressed in healthy proximal tubules of human and mouse kidneys via single-cell analysis. Further investigations revealed that PPDPF functioned as a thiol-disulfide oxidoreductase to maintain cellular NAD+ levels. Deficiency in PPDPF disrupted NAD+ and mitochondrial homeostasis by impairing the activities of nicotinamide mononucleotide adenylyl transferases (NMNATs), thereby compromising the function of proximal tubules during injuries. Consequently, knockout of PPDPF notably accelerated the progression of chronic kidney disease (CKD) in mouse models induced by aging, chemical exposure, and obstruction. These findings strongly support targeting PPDPF as a potential therapy for kidney fibrosis, offering possibilities for future CKD interventions.

Enhanced insights into the genetic architecture of 3D cranial vault shape using pleiotropy-informed GWAS

Large-scale GWAS studies have uncovered hundreds of genomic loci linked to facial and brain shape variation, but only tens associated with cranial vault shape, a largely overlooked aspect of the craniofacial complex. Surrounding the neocortex, the cranial vault plays a central role during craniofacial development and understanding its genetics are pivotal for understanding craniofacial conditions. Experimental biology and prior genetic studies have generated a wealth of knowledge that presents opportunities to aid further genetic discovery efforts. Here, we use the conditional FDR method to leverage GWAS data of facial shape, brain shape, and bone mineral density to enhance SNP discovery for cranial vault shape. This approach identified 120 independent genomic loci at 1% FDR, nearly tripling the number discovered through unconditioned analysis and implicating crucial craniofacial transcription factors and signaling pathways. These results significantly advance our genetic understanding of cranial vault shape and craniofacial development more broadly.

Big databases and biobanks for studying the links between CKD, cognitive impairment, and dementia

Research on cognitive function in individuals with chronic kidney disease (CKD) is critical due to the significant public health challenge posed by both CKD and cognitive impairment. CKD affects approximately 10-15% of the adult population, with higher prevalence in the elderly, who are already at increased risk for cognitive decline. Cognitive impairment is notably higher in CKD patients, particularly those with severe stages of the disease, and progresses more rapidly in those on dialysis. This review explores how data from large biobank studies such as the Alzheimer's Disease Neuroimaging Initiative, UK Biobank, and others could be used to enhance understanding the progression and interplay between CKD and cognitive decline. Each of these data sources has specific strengths and limitations. Strengths include large sample sizes and longitudinal data across different groups, and in different settings. Addressing limitations leads to challenges in dealing with heterogeneous data collection methods, and addressing missing data, which requires the use of sophisticated statistical techniques. Combining data from multiple databases can mitigate individual study limitations, particularly via the 'epidemiological triangulation' concept. Using such data appropriately holds immense potential to better understand the pathobiology underlying CKD and cognitive impairment. Addressing the inherent challenges with a clear strategy is crucial for advancing our understanding and improving the lives of those affected by both CKD and cognitive impairment.

Global, regional, and national burden of chronic kidney disease, 1990-2021: a systematic analysis for the global burden of disease study 2021

Background

Chronic kidney disease (CKD) continues to represent a significant public health concern, with both prevalence and incidence rates on the rise globally. Therefore, the study employed the Global Burden of Disease (GBD) database to investigate the global burden of CKD from 1990 to 2021.

Methods

This study utilized data from the GBD 2021. Join-point regression models were developed for the estimation of the average annual percentage change (AAPC) in the prevalence and mortality rates of CKD. Subsequently, stepwise multiple linear regression analysis was conducted to examine the trends in disability adjusted life years (DALYs) and DALYs rate for CKD across diverse populations between 1990 and 2021. Moreover, the influence of age, gender, and socio-demographic index (SDI) on the burden of CKD among patients from 1990 to 2021 was examined. Furthermore, the projection of the burden of CKD from 2022 to 2032 was also conducted.

Results

The AAPC for prevalence and mortality rates across the entire period spanning 1990 to 2021 was 0.92 and 2.66, respectively. A notable increase in the DALYs and DALYs rate for CKD was demonstrated over time, indicating a growing CKD burden on society since 1990. Furthermore, the DALYs rates for CKD were lowest in the 5-9 year age group for both genders, rising thereafter with age. Notably, the DALYs rate for CKD was higher in males than in females. Regions with higher SDI, generally exhibited a lower burden of CKD, while less developed regions, demonstrated the opposite pattern. Additionally, the age-standardized prevalence and mortality rates for CKD would be projected to increase to 8,773.85 and 21.26 per 100,000 individuals, respectively, by 2032.

Conclusion

The research indicated a gradual increase in the global prevalence and mortality rates of CKD over time, which might prompt the formulation of more efficient health policies to alleviate its burden.

The landscape of renal protein S-acylation in mice with lipid-induced nephrotoxicity

Excess fat intake is associated with kidney toxicity and dysfunction. Because fatty acids can also be reversibly attached onto cysteine residues and modulate the function of several membrane-bound proteins, we studied the effect of high-fat diet (HFD) on the S-acylated proteome of mouse kidneys to uncover novel biochemical changes that might contribute to lipid-induced nephrotoxicity. We compared the S-acylated proteome of kidneys from mice fed a chow diet (CD) or a HFD. HFD caused albuminuria. The HFD intervention induced a large-scale repression of protein S-acylation as well as of the most abundant ceramides and sphingomyelin species, which are highly suggestive of a reduction in acyl-CoA availability. The HFD-induced S-acylation repression mostly affected proteins involved in endocytosis and intracellular transport. Notably, the kidneys of mice fed a HFD displayed a marked decrease in the total amount and in the S-acylated form of megalin, the main tubular protein retrieval system. Further in vitro experiments indicated that S-acylation inhibition results in a reduction of megalin protein level. We conclude that diet-induced derangement of fatty acid metabolism modifies the renal landscape of the S-acylated proteome during the early stages of the kidney injury, which might reduce the efficiency of protein reabsorption by the proximal tubule.

Donor and Recipient Polygenic Risk Scores Influence Kidney Transplant Function

Kidney transplant outcomes are influenced by donor and recipient age, sex, HLA mismatch, donor type, anti-rejection medication adherence and disease recurrence, but variability in transplant outcomes remains unexplained. We hypothesise that donor and recipient polygenic burden for traits related to kidney function may also influence graft function. We assembled a cohort of 6,060 living and deceased kidney donor-recipient pairs. We calculated polygenic risk scores (PRSs) for kidney function-related traits in both donors and recipients. We investigated the association between these PRSs and recipient eGFR at 1- and 5-year post-transplant as well as graft failure. Donor: hypertension PRS (P < 0.001), eGFR PRS (P < 0.001), and intracranial aneurysm PRS (P = 0.01), along with recipient eGFR PRS (P = 0.001) were associated with eGFR at 1-year post-transplantation. Clinical factors explained 25% of the variation in eGFR at 1-year and 13% at 5-year, with PRSs cumulatively adding 1% in both cases. PRSs were not associated with long-term graft survival. We demonstrate a small, but statistically significant association between donor and recipient PRSs and recipient graft function at 1- and 5-year post-transplant. This effect is, at present, unlikely to have clinical application and further research is required to improve PRS performance.

Polygenic risk scores for eGFR are associated with age at kidney failure

BACKGROUND

The genetic architecture of chronic kidney disease (CKD) is complex, including monogenic and polygenic contributions. CKD progression to kidney failure is influenced by factors including male sex, baseline estimated glomerular filtration rate (eGFR), hypertension, diabetes, proteinuria, and the underlying kidney disease. These traits all have strong genetic components, which can be partially quantified using polygenic risk scores. This paper examines the association between polygenic risk scores for CKD-related traits and age at kidney failure development.

METHODS

Genome-wide genotype data from 10,586 patients with kidney failure were compiled from 12 cohorts. Polygenic risk scores for hypertension, albuminuria, rapid decline in eGFR, decreased total kidney volume, and decreased eGFR were calculated using weights from published independent population-scale genome-wide association studies. The association between each polygenic risk score and age at kidney failure was investigated using logistic regression models. The association between polygenic risk score and age at kidney failure was also investigated separately for each primary kidney disease.

RESULTS

Individuals in the highest 10% of polygenic risk score for decreased eGFR developed kidney failure 2 years earlier than those in the bottom 90% (49.9 years and 47.9 years, P = 5e-5). A standard deviation increase in decreased eGFR polygenic risk score was associated with increased odds of developing kidney failure before the age of 60 years (Odds ratio (OR) = 1.05; 95% CI 1.01-1.10; P = 0.01), as was high decreased eGFR polygenic risk score (OR = 1.26; 95% CI 1.08-1.46; P = 0.003).

CONCLUSIONS

We conclude that decreased eGFR polygenic risk score explains a portion of the variation in age at development of kidney failure.

Emerging role of genetics in kidney transplantation

The advent of more affordable genomic analytical pipelines has facilitated the expansion of genetic studies in kidney transplantation. Advances in genetic sequencing have allowed for a greater understanding of the genetic basis of chronic kidney disease, which has helped to guide transplant management and address issues related to living donation in specific disease settings. Recent efforts have shown significant effects of genetic ancestry and donor APOL1 risk genotypes in determining worse allograft outcomes and increased donation risks. Genetic studies in kidney transplantation outcomes have started to assess the effects of donor and recipient genetics in primary disease recurrence and transplant-related comorbidities, while genome-wide donor-recipient genetic incompatibilities have been shown to represent an important determinant of alloimmunity. Future large-scale comprehensive studies will shed light on the clinical utility of integrative genomics in the kidney transplantation setting.

Adherence to a Healthful Plant-Based Diet and Risk of Chronic Kidney Disease Among Individuals with Diabetes

OBJECTIVE

Chronic kidney disease (CKD) is highly prevalent among people with diabetes. While identifying modifiable risk factors to prevent a decline in kidney function among those living with diabetes is pivotal, there is limited evidence on dietary risk factors for CKD. In this study, we examined the associations between healthy and less healthy plant-based diets (PBDs) and the risk of CKD among those with diabetes, and to identify potential underlying mechanisms.

METHODS

We conducted a prospective analysis among 7,747 UK Biobank participants with prevalent diabetes. Multivariable Cox proportional hazard regression models were used to examine the associations between healthful and unhealthful PBDs and the risk of CKD. Causal mediation analyses were further employed to explore the underlying mechanisms of the observed associations.

RESULTS

Among 7,747 study participants with diabetes, 1,030 developed incident CKD over 10.2 years of follow-up. Higher adherence to a healthy PBD was associated with a 24% lower CKD risk (HRQ4 versus Q1: 0.76 [95%CI: 0.63-0.92], ptrend = 0.002), while higher adherence to an unhealthy PBD was associated with a 35% higher risk (HRQ4 versus Q1: 1.35 [95%CI: 1.11-1.65], ptrend = 0.006). The observed associations were predominantly mediated by markers of body fatness (proportion mediated: 11-25%) and kidney function (23-89%).

CONCLUSIONS

In this prospective cohort study of middle-aged adults with diabetes, adherence to a healthy PBD was associated with lower CKD risk, whereas adherence to an unhealthy PBD was associated with a higher CKD risk. Associations were primarily mediated by markers of lower body fatness and improved kidney function.

Increased risk of chronic diseases and multimorbidity in middle-aged and elderly individuals with early vision, hearing, or dual sensory impairments: insights from prospective cohort studies and Mendelian randomization analysis

BACKGROUND

Sensory impairments (SI), including vision (VI), hearing (HI), and dual sensory impairments (DSI), are prevalent with aging, but their impact on disease risk remains unclear. This study investigates the epidemiological and genetic associations between SIs and 10 chronic disease categories and multimorbidity.

METHODS

Using the CHARLS study, participants were classified by their self-reported VI/HI/DSI status in 2011 and 2013 into groups: "new onset, remission, persistent, and no SI." Their chronic disease incidence was tracked until 2018 in sub-cohorts respectively. Mendelian randomization (MR) analyses used genetic instruments from UK Biobank GWAS data on 88,250/504,307 individuals for vision/hearing loss, with outcome datasets from consortia including FinnGen, DIAMANTE, CKDGen, PGC, GWAS Catalog, and International Parkinson's Disease Genomics Consortium.

RESULTS

The cohort study revealed that persistent HI significantly increased the risk of heart disease (P < 0.001, HR 1.63, 95% CI 1.31-2.03), stroke (P 0.004, HR 1.59, 95% CI 1.16-2.18), chronic lung disease (P 0.002, HR 1.53, 95% CI 1.17-1.99), and emotional, nervous, or psychiatric problems (P 0.016, HR 2.03, 95% CI 1.14-3.60). Persistent VI was significantly associated with diabetes or high blood sugar (DM/Hglu) (P 0.012, HR 1.63, 95% CI 1.11-2.38) and chronic lung disease (P 0.042, HR 1.53, 95% CI 1.02-2.31). MR confirmed these strong or suggestive associations, indicating that HI significantly increased the risk of cardiovascular and cerebrovascular events by 61-170%, bronchitis by 160%, and schizophrenia by 36%. In addition, VI significantly raised the risk of hyperglycemia or diabetes by 2-4% and the risk of lung function decline. Additionally, cohort studies confirmed that early DSI significantly raised the risk of multiple diseases, while MR identified genetic links between VI and hepatic failure, Parkinson's, and Alzheimer's disease, and between HI and hypertension, chronic kidney disease, and renal failure.

CONCLUSIONS

This study provides evidence from epidemiological or genetic perspectives demonstrates that early exposure to HI/VI/DSI increases the risk of developing chronic diseases. These findings underscore the need for continuous monitoring and timely intervention for SI to manage chronic disease risks in aging populations.

2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association

BACKGROUND

The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors (smoking, physical activity, nutrition, sleep, and obesity) and health factors (cholesterol, blood pressure, glucose control, and metabolic syndrome) that contribute to cardiovascular health. The AHA Heart Disease and Stroke Statistical Update presents the latest data on a range of major clinical heart and circulatory disease conditions (including stroke, brain health, complications of pregnancy, kidney disease, congenital heart disease, rhythm disorders, sudden cardiac arrest, subclinical atherosclerosis, coronary heart disease, cardiomyopathy, heart failure, valvular disease, venous thromboembolism, and peripheral artery disease) and the associated outcomes (including quality of care, procedures, and economic costs).

METHODS

The AHA, through its Epidemiology and Prevention Statistics Committee, continuously monitors and evaluates sources of data on heart disease and stroke in the United States and globally to provide the most current information available in the annual Statistical Update with review of published literature through the year before writing. The 2025 AHA Statistical Update is the product of a full year's worth of effort in 2024 by dedicated volunteer clinicians and scientists, committed government professionals, and AHA staff members. This year's edition includes a continued focus on health equity across several key domains and enhanced global data that reflect improved methods and incorporation of ≈3000 new data sources since last year's Statistical Update.

RESULTS

Each of the chapters in the Statistical Update focuses on a different topic related to heart disease and stroke statistics.

CONCLUSIONS

The Statistical Update represents a critical resource for the lay public, policymakers, media professionals, clinicians, health care administrators, researchers, health advocates, and others seeking the best available data on these factors and conditions.

Psychiatric disorders and following risk of chronic kidney disease: a prospective cohort study from UK Biobank

BACKGROUND

Psychiatric disorders have been reported to influence many health outcomes, but evidence about their impact on chronic kidney disease (CKD) has not been fully explored, as well as possible mechanisms implicated are still unclear.

METHODS

Four hundred forty-one thousand eight hundred ninety-three participants from UK Biobank were included in this study. To assess the association between psychiatric disorders mainly including depression, anxiety, stress-related disorders, substance misuse as well as psychotic disorder, and CKD, a Cox regression model using age as the underlying time scale was employed. This approach considers the age progression of participants from the beginning to the end of the study as the elapsed time. Flexible nonparametric smoothing model was conducted to illustrate the temporal patterns. Subgroup analyses were performed by stratification of gender, genetic susceptibility to CKD, age at entry or exit the cohort, follow-up duration, and the number of psychiatric disorders at baseline. Mediation analysis was implemented to evaluate the roles of body mass index (BMI), hypertension, and diabetes.

RESULTS

Compared with individuals without psychiatric disorders, an increased risk of CKD was observed in patients with psychiatric disorders (hazard ratios (HR) = 1.52, 95% confidence intervals (CI): 1.40-1.65, p-value < 0.001). The hazard ratio among psychiatric patients gradually increased, and became significant after about 10 years follow-ups. The HR for patients followed up for 10-12 years was 1.60 (95% CI: 1.34-1.91, p-value < 0.001), and the HR was 1.66 (95% CI: 1.29-2.13, p-value < 0.001) for patients followed up for 12-13 years. Five distinct psychiatric disorders were found to be significantly associated with an increased risk of developing CKD. The highest HR was observed between stress-related disorder and CKD (HR = 1.95, 95%CI: 1.28-2.97, p-value = 0.002). When adjusting genetic susceptibility to CKD, the HR for the association between stress-related disorders and CKD became 1.86 (95%CI: 1.14-3.04, p-value = 0.013). Although these associations were nominally significant, they did not reach statistical significance after applying the Bonferroni multiple corrections, potentially due to the limited sample size. Subgroup analysis revealed that psychiatric patients who are under age 60, with multiple psychiatric morbidities or having been diagnosed with psychiatric disorders for over 10 years may be high-risk populations. Hypertension, BMI and diabetes mediated 49.13% (95% CI: 37.60%-67.08%), 12.11% (95% CI: 8.49%-17.24%) and 3.78% (95% CI: 1.58%-6.52%) of the total effect, respectively.

CONCLUSIONS

Psychiatric disorders were associated with a delayed onset of an elevated risk for CKD, this association was only observed in patients with psychiatric disorders for more than 10 years. Our study highlights the significance of lifestyle interventions, routine monitoring of kidney function, early screening for CKD, and personalized management strategies for psychiatric patients as potential approaches to the precise prevention of CKD.

Association between obstructive sleep apnea and chronic kidney disease: A cross-sectional and Mendelian randomization study

Previous observational studies have shown that obstructive sleep apnea (OSA) was associated with chronic kidney disease(CKD). Early diagnosis of OSA usually helps better prevent the occurrence of CKD. This cross-sectional investigation was conducted using data from the National Health and Nutrition Examination Survey, which was carried out between 2007 to 2008 and 2015 to 2016. Logistic regression model was employed to assess the impact of OSA on CKD. We did a mediation analysis to assess how much of the effect of OSA on CKD was mediated through mediators. Additionally, Mendelian randomization (MR) analysis assessed the causal link between OSA and various measures of renal impairment and possible mediators: obesity, hypertension and type 2 diabetes mellitus. In the cross-sectional study, the results of unadjusted model showed that participants with OSA had a higher risk of CKD compared to non-OSA (OR = 1.14, 95% confidence intervals [CI]: 1.01-1.28, P < .05). In mediation analysis, the proportion of hypertension and obesity mediating the effect of OSA on CKD was 41.83% and 30.74%, respectively. Univariate MR analysis results showed that: genetically predicted OSA was associated with decreased estimated glomerular filtration ratecystatin c (eGFRcystatin c) level (OR = 0.997, 95% CI: 0.995-0.999, P < .05), increased blood urea nitrogen (BUN) levels (OR = 1.023, 95% CI: 1.008-1.038, P < .05), increased serum creatinine levels (OR = 1.010, 95% CI: 1.002-1.018, P < .05), increased serum cystatin C levels (OR = 1.015, 95% CI: 1.005-1.026, P < .05). Multivariable MR results showed that obesity mediated the causal effect of OSA on eGFRcystatin c, BUN levels and serum cystatin C levels. The cross-sectional study revealed a positive relationship between OSA and CKD, which was mediated by hypertension and obesity. The MR analysis suggest that OSA was associated with several measures of renal impairment, which was mediated by obesity. These findings may inform prevention and intervention strategies against CKD.

Kidney multiome-based genetic scorecard reveals convergent coding and regulatory variants

Kidney dysfunction is a major cause of mortality, but its genetic architecture remains elusive. In this study, we conducted a multiancestry genome-wide association study in 2.2 million individuals and identified 1026 (97 previously unknown) independent loci. Ancestry-specific analysis indicated an attenuation of newly identified signals on common variants in European ancestry populations and the power of population diversity for further discoveries. We defined genotype effects on allele-specific gene expression and regulatory circuitries in more than 700 human kidneys and 237,000 cells. We found 1363 coding variants disrupting 782 genes, with 601 genes also targeted by regulatory variants and convergence in 161 genes. Integrating 32 types of genetic information, we present the "Kidney Disease Genetic Scorecard" for prioritizing potentially causal genes, cell types, and druggable targets for kidney disease.

Characterizing substructure via mixture modeling in large-scale genetic summary statistics

Genetic summary data are broadly accessible and highly useful, including for risk prediction, causal inference, fine mapping, and incorporation of external controls. However, collapsing individual-level data into summary data, such as allele frequencies, masks intra- and inter-sample heterogeneity, leading to confounding, reduced power, and bias. Ultimately, unaccounted-for substructure limits summary data usability, especially for understudied or admixed populations. There is a need for methods to enable the harmonization of summary data where the underlying substructure is matched between datasets. Here, we present Summix2, a comprehensive set of methods and software based on a computationally efficient mixture model to enable the harmonization of genetic summary data by estimating and adjusting for substructure. In extensive simulations and application to public data, we show that Summix2 characterizes finer-scale population structure, identifies ascertainment bias, and scans for potential regions of selection due to local substructure deviation. Summix2 increases the robust use of diverse, publicly available summary data, resulting in improved and more equitable research.

Systematic Mendelian Randomization Exploring Druggable Genes for Hemorrhagic Strokes

Patients with hemorrhagic stroke have high rates of morbidity and mortality, and drugs for prevention are very limited. Mendelian randomization (MR) analysis can increase the success rate of drug development by providing genetic evidence. Previous MR analyses only analyzed the role of individual drug target genes in hemorrhagic stroke; therefore, we used MR analysis to systematically explore the druggable genes for hemorrhagic stroke. We sequentially performed summary-data-based MR analysis and two-sample MR analysis to assess the associations of all genes within the database with intracranial aneurysm, intracerebral hemorrhage, and their subtypes. Validated genes were further analyzed by colocalization. Only genes that were positive in all three analyses and were druggable were considered desirable genes. We also explored the mediators of genes affecting hemorrhagic stroke incidence. Finally, the associations of druggable genes with other cardiovascular diseases were analyzed to assess potential side effects. We identified 56 genes that significantly affected hemorrhagic stroke incidence. Moreover, TNFSF12, SLC22A4, SPARC, KL, RELT, and ADORA3 were found to be druggable. The inhibition of TNFSF12, SLC22A4, and SPARC can reduce the risk of intracranial aneurysm, subarachnoid hemorrhage, and intracerebral hemorrhage. Gene-induced hypertension may be a potential mechanism by which these genes cause hemorrhagic stroke. We also found that blocking these genes may cause side effects, such as ischemic stroke and its subtypes. Our study revealed that six druggable genes were associated with hemorrhagic stroke, and the inhibition of TNFSF12, SLC22A4, and SPARC had preventive effects against hemorrhagic strokes.

Separating the Effects of Early-Life and Adult Body Size on Chronic Kidney Disease Risk: A Mendelian Randomization Study

Background

Whether there is a causal relationship between childhood obesity and increased risk of chronic kidney disease (CKD) remains controversial. This study sought to explore how body size in childhood and adulthood independently affects CKD risk in later life using a Mendelian randomization (MR) approach.

Methods

Univariate and multivariate MR was used to estimate total and independent effects of body size exposures. Genetic associations with early-life and adult body size were obtained from a genome-wide association study of 453,169 participants in the U.K. Biobank, and genetic associations with CKD were obtained from the CKDGen and FinnGen consortia.

Results

A larger genetically predicted early-life body size was associated with an increased risk of CKD (odds ratio [OR], 1.27; 95% confidence interval [CI], 1.14 to 1.41; P=1.70E-05) and increased blood urea nitrogen (BUN) levels (β=0.010; 95% CI, 0.005 to 0.021; P=0.001). However, the association between the impact of early-life body size on CKD (OR, 1.12; 95% CI, 0.95 to 1.31; P=0.173) and BUN level (β=0.001; 95% CI, -0.010 to 0.012; P=0.853) did not remain statistically significant after adjustment for adult body size. Larger genetically predicted adult body size was associated with an increased risk of CKD (OR, 1.37; 95% CI, 1.21 to 1.54; P=4.60E-07), decreased estimated glomerular filtration rate (β=-0.011; 95% CI, -0.017 to -0.006; P=5.79E-05), and increased BUN level (β=0.010; 95% CI, 0.002 to 0.019; P=0.018).

Conclusion

Our research indicates that the significant correlation between early-life body size and CKD risk is likely due to maintaining a large body size into adulthood.

Bias-corrected serum creatinine from UK Biobank electronic medical records generates an important data resource for kidney function trajectories

Loss of kidney function is a substantial personal and public health burden. Kidney function is typically assessed as estimated glomerular filtration rate (eGFR) based on serum creatinine. UK Biobank provides serum creatinine measurements from study center assessments (SC, n = 425,147 baseline, n = 15,314 with follow-up) and emerging electronic Medical Records (eMR, "GP-clinical") present a promising resource to augment this data longitudinally. However, it is unclear whether eMR-based and SC-based creatinine values can be used jointly for research on eGFR decline. When comparing eMR-based with SC-based creatinine by calendar year (n = 70,231), we found a year-specific multiplicative bias for eMR-based creatinine that decreased over time (factor 0.84 for 2007, 0.97 for 2013). Deriving eGFR based on SC- and bias-corrected eMR-creatinine yielded 454,907 individuals with ≥ 1eGFR assessment (2,102,174 assessments). This included 206,063 individuals with ≥ 2 assessments over up to 60.2 years (median 6.00 assessments, median time = 8.7 years), where we also obtained eMR-based information on kidney disease or renal replacement therapy. We found an annual eGFR decline of 0.11 (95%-CI = 0.10-0.12) versus 1.04 mL/min/1.73m2/year (95%-CI = 1.03-1.05) without and with bias-correction, the latter being in line with literature. In summary, our bias-corrected eMR-based creatinine values enabled a 4-fold increased number of eGFR assessments in UK Biobank suitable for kidney function research.

Epigenome-wide association study of Chinese monozygotic twins identifies DNA methylation loci associated with estimated glomerular filtration rate

BACKGROUND

DNA methylation (DNAm) has been shown in multiple studies to be associated with the estimated glomerular filtration rate (eGFR). However, studies focusing on Chinese populations are lacking. We conducted an epigenome-wide association study to investigate the association between DNAm and eGFR in Chinese monozygotic twins.

METHODS

Genome-wide DNAm level was detected using Reduced Representation Bisulfite Sequencing test. Generalized estimation equation (GEE) was used to examine the association between Cytosine-phosphate-Guanines (CpGs) DNAm and eGFR. Inference about Causation from Examination of FAmiliaL CONfounding was employed to infer the causal relationship. The comb-p was used to identify differentially methylated regions (DMRs). GeneMANIA was used to analyze the gene interaction network. The Genomic Regions Enrichment of Annotations Tool enriched biological functions and pathways. Gene expression profiling sequencing was employed to measure mRNA expression levels, and the GEE model was used to investigate the association between gene expression and eGFR. The candidate gene was validated in a community population by calculating the methylation risk score (MRS).

RESULTS

A total of 80 CpGs and 28 DMRs, located at genes such as OLIG2, SYNGR3, LONP1, CDCP1, and SHANK1, achieved genome-wide significance level (FDR < 0.05). The causal effect of DNAm on eGFR was supported by 12 CpGs located at genes such as SYNGR3 and C9orf3. In contrast, the causal effect of eGFR on DNAm is proved by 13 CpGs located at genes such as EPHB3 and MLLT1. Enrichment analysis revealed several important biological functions and pathways related to eGFR, including alpha-2A adrenergic receptor binding pathway and corticotropin-releasing hormone receptor activity pathway. GeneMANIA results showed that SYNGR3 was co-expressed with MLLT1 and had genetic interactions with AFF4 and EDIL3. Gene expression analysis found that SYNGR3 expression was negatively associated with eGFR. Validation analysis showed that the MRS of SYNGR3 was positively associated with low eGFR levels.

CONCLUSIONS

We identified a set of CpGs, DMRs, and pathways potentially associated with eGFR, particularly in the SYNGR3 gene. These findings provided new insights into the epigenetic modifications related to the decline in eGFR and chronic kidney disease.

Genetic association analysis of lipid-lowering drug target genes in chronic kidney disease

Objective

The impact of lipid-lowering medications on chronic kidney disease (CKD) remains a subject of debate. This Mendelian randomization (MR) study aims to elucidate the potential effects of lipid-lowering drug targets on CKD development.

Methods

We extracted 11 genetic variants encoding targets of lipid-lowering drugs from published genome-wide association study (GWAS) summary statistics, encompassing LDLR, HMGCR, PCSK9, NPC1L1, APOB, ABCG5/ABCG8, LPL, APOC3, ANGPTL3, and PPARA. A Mendelian randomization analysis was conducted targeting these drug-related genes. CKD risk was designated as the primary outcome, while estimated glomerular filtration rate (eGFR) and blood urea nitrogen (BUN) were assessed as secondary outcomes. Additionally, mediation analysis was performed utilizing 731 immune cell phenotypes to identify potential mediators.

Results

The meta-analysis revealed a significant association between ANGPTL3 inhibitors and a reduced risk of CKD (OR [95% CI] = 0.85 [0.75-0.96]). Conversely, LDLR agonists were significantly linked to an increased risk of CKD (OR [95% CI] = 1.11 [1.02-1.22]). Regarding secondary outcomes, lipid-lowering drugs did not significantly affect eGFR and BUN levels. Mediation analysis indicated that the reduction in CKD risk by ANGPTL3 inhibitors was mediated through modulation of the immune cell phenotype, specifically HLA-DR on CD14+ CD16+ monocytes (Mediated proportion: 4.69%; Mediated effect: -0.00899).

Conclusion

Through drug-targeted MR analysis, we identified a causal relationship between lipid-lowering drug targets and CKD. ANGPTL3 and LDLR may represent promising candidate drug targets for CKD treatment.

Genome-wide characterization of 54 urinary metabolites reveals molecular impact of kidney function

Dissecting the genetic mechanisms underlying urinary metabolite concentrations can provide molecular insights into kidney function and open possibilities for causal assessment of urinary metabolites with risk factors and disease outcomes. Proton nuclear magnetic resonance metabolomics provides a high-throughput means for urinary metabolite profiling, as widely applied for blood biomarker studies. Here we report a genome-wide association study meta-analysed for 3 European cohorts comprising 8,011 individuals, covering both people with type 1 diabetes and general population settings. We identify 54 associations (p < 9.3 × 10-10) for 19 of 54 studied metabolite concentrations. Out of these, 33 were not reported previously for relevant urinary or blood metabolite traits. Subsequent two-sample Mendelian randomization analysis suggests that estimated glomerular filtration rate causally affects 13 urinary metabolite concentrations whereas urinary ethanolamine, an initial precursor for phosphatidylcholine and phosphatidylethanolamine, was associated with higher eGFR lending support for a potential protective role. Our study provides a catalogue of genetic associations for 53 metabolites, enabling further investigation on how urinary metabolites are linked to human health.

Frequency of adding salt is a stronger predictor of chronic kidney disease in individuals with genetic risk

The incidence of chronic kidney disease (CKD) is increasing worldwide, but there is no specific treatment available. Therefore, understanding and controlling the risk factors for CKD are essential for preventing disease occurrence. Salt intake raises blood pressure by increasing fluid volume and contributes to the deterioration of kidney function by enhancing the renin-angiotensin system and sympathetic tone. Thus, a low-salt diet is important to reduce blood pressure and prevent kidney diseases. With recent advancements in genetic research, our understanding of the etiology and genetic background of CKD has deepened, enabling the identification of populations with a high genetic predisposition to CKD. It is thought that the impact of lifestyle or environmental factors on disease occurrence or prevention may vary based on genetic factors. This study aims to investigate whether frequency of adding salt has different effects depending on genetic risk for CKD. CKD polygenic risk scores (PRS) were generated using CKDGen Consortium GWAS (N= 765,348) summary statics. Then we applied the CKD PRS to UK Biobank subjects. A total of 331,318 European individuals aged 40-69 without CKD were enrolled in the study between 2006-2010. The average age at enrollment of the participants in this study was 56.69, and 46% were male. Over an average follow-up period of 8 years, 12,279 CKD cases were identified. The group that developed CKD had a higher percentage of individuals who added salt (46.37% vs. 43.04%) and higher CKD high-risk PRS values compared to the group that did not develop CKD (23.53% vs. 19.86%). We classified the individuals into four groups based on PRS: low (0-19%), intermediate (20-79%), high (80-94%), very high (≥ 95%). Incidence of CKD increased incrementally according to CKD PRS even after adjusting for age, sex, race, Townsend deprivation index, body mass index, estimated glomerular filtration rate, smoking, alcohol, physical activity, diabetes mellitus, dyslipidemia, hypertension, coronary artery diseases, cerebrovascular diseases at baseline. Compared to the "never/rarely" frequency of adding salt group, "always" frequency of adding salt group had an increasing incidence of CKD proportionate to the degree of frequency of adding salt. However, the significant association of "always" group on incident CKD disappeared in the low PRS group. This study validated the signal from PRSs for CKD across a large cohort and confirmed that frequency of adding salt contributes to the occurrence of CKD. Additionally, it confirmed that the effect of frequency of "always" adding salt on CKD incidence is greater in those with more than intermediate CKD-PRS. This study suggests that increased salt intake is particularly concerning for individuals with genetic risk factors for CKD, underscoring the clinical importance of reducing salt intake for these individuals.

Shared genetic architecture and bidirectional clinical risks within the psycho-metabolic nexus

BACKGROUND

Increasing evidence suggests a complex interplay between psychiatric disorders and metabolic dysregulations. However, most research has been limited to specific disorder pairs, leaving a significant gap in our understanding of the broader psycho-metabolic nexus.

METHODS

This study leveraged large-scale cohort data and genome-wide association study (GWAS) summary statistics, covering 8 common psychiatric disorders and 43 metabolic traits. We introduced a comprehensive analytical strategy to identify shared genetic bases sequentially, from key genetic correlation regions to local pleiotropy and pleiotropic genes. Finally, we developed polygenic risk score (PRS) models to translate these findings into clinical applications.

FINDINGS

We identified significant bidirectional clinical risks between psychiatric disorders and metabolic dysregulations among 310,848 participants from the UK Biobank. Genetic correlation analysis confirmed 104 robust trait pairs, revealing 1088 key genomic regions, including critical hotspots such as chr3: 47588462-50387742. Cross-trait meta-analysis uncovered 388 pleiotropic single nucleotide variants (SNVs) and 126 shared causal variants. Among variants, 45 novel SNVs were associated with psychiatric disorders and 75 novel SNVs were associated with metabolic traits, shedding light on new targets to unravel the mechanism of comorbidity. Notably, RBM6, a gene involved in alternative splicing and cellular stress response regulation, emerged as a key pleiotropic gene. When psychiatric and metabolic genetic information were integrated, PRS models demonstrated enhanced predictive power.

INTERPRETATION

The study highlights the intertwined genetic and clinical relationships between psychiatric disorders and metabolic dysregulations, emphasising the need for integrated approaches in diagnosis and treatment.

FUNDING

The National Key Research and Development Program of China (2023YFC2506200, SHH). The National Natural Science Foundation of China (82273741, SY).

Polygenic scores and their applications in kidney disease

Genome-wide association studies (GWAS) have uncovered thousands of risk variants that individually have small effects on the risk of human diseases, including chronic kidney disease, type 2 diabetes, heart diseases and inflammatory disorders, but cumulatively explain a substantial fraction of disease risk, underscoring the complexity and pervasive polygenicity of common disorders. This complexity poses unique challenges to the clinical translation of GWAS findings. Polygenic scores combine small effects of individual GWAS risk variants across the genome to improve personalized risk prediction. Several polygenic scores have now been developed that exhibit sufficiently large effects to be considered clinically actionable. However, their clinical use is limited by their partial transferability across ancestries and a lack of validated models that combine polygenic, monogenic, family history and clinical risk factors. Moreover, prospective studies are still needed to demonstrate the clinical utility and cost-effectiveness of polygenic scores in clinical practice. Here, we discuss evolving methods for developing polygenic scores, best practices for validating and reporting their performance, and the study designs that will empower their clinical implementation. We specifically focus on the polygenic scores relevant to nephrology and other chronic, complex diseases and review their key limitations, necessary refinements and potential clinical applications.

The impact of common and rare genetic variants on bradyarrhythmia development

To broaden our understanding of bradyarrhythmias and conduction disease, we performed common variant genome-wide association analyses in up to 1.3 million individuals and rare variant burden testing in 460,000 individuals for sinus node dysfunction (SND), distal conduction disease (DCD) and pacemaker (PM) implantation. We identified 13, 31 and 21 common variant loci for SND, DCD and PM, respectively. Four well-known loci (SCN5A/SCN10A, CCDC141, TBX20 and CAMK2D) were shared for SND and DCD, while others were more specific for SND or DCD. SND and DCD showed a moderate genetic correlation (rg = 0.63). Cardiomyocyte-expressed genes were enriched for contributions to DCD heritability. Rare-variant analyses implicated LMNA for all bradyarrhythmia phenotypes, SMAD6 and SCN5A for DCD and TTN, MYBPC3 and SCN5A for PM. These results show that variation in multiple genetic pathways (for example, ion channel function, cardiac developmental programs, sarcomeric structure and cellular homeostasis) appear critical to the development of bradyarrhythmias.

Disrupted uromodulin trafficking is rescued by targeting TMED cargo receptors

The trafficking dynamics of uromodulin (UMOD), the most abundant protein in human urine, play a critical role in the pathogenesis of kidney disease. Monoallelic mutations in the UMOD gene cause autosomal dominant tubulointerstitial kidney disease (ADTKD-UMOD), an incurable genetic disorder that leads to kidney failure. The disease is caused by the intracellular entrapment of mutant UMOD in kidney epithelial cells, but the precise mechanisms mediating disrupted UMOD trafficking remain elusive. Here, we report that transmembrane Emp24 protein transport domain-containing (TMED) cargo receptors TMED2, TMED9, and TMED10 bind UMOD and regulate its trafficking along the secretory pathway. Pharmacological targeting of TMEDs in cells, in human kidney organoids derived from patients with ADTKD-UMOD, and in mutant-UMOD-knockin mice reduced intracellular accumulation of mutant UMOD and restored trafficking and localization of UMOD to the apical plasma membrane. In vivo, the TMED-targeted small molecule also mitigated ER stress and markers of kidney damage and fibrosis. Our work reveals TMED-targeting small molecules as a promising therapeutic strategy for kidney proteinopathies.

Advances in uromodulin biology and potential clinical applications

Uromodulin (also known as Tamm-Horsfall protein) is a kidney-specific glycoprotein secreted bidirectionally into urine and into the circulation, and it is the most abundant protein in normal urine. Although the discovery of uromodulin predates modern medicine, its significance in health and disease has been rather enigmatic. Research studies have gradually revealed that uromodulin exists in multiple forms and has important roles in urinary and systemic homeostasis. Most uromodulin in urine is polymerized into highly organized filaments, whereas non-polymeric uromodulin is detected both in urine and in the circulation, and can have distinct roles. The interactions of uromodulin with the immune system, which were initially reported to be a key role of this protein, are now better understood. Moreover, the discovery that uromodulin is associated with a spectrum of kidney diseases, including acute kidney injury, chronic kidney disease and autosomal-dominant tubulointerstitial kidney disease, has further accelerated investigations into the role of this protein. These discoveries have prompted new questions and ushered in a new era in uromodulin research. Here, we delineate the latest discoveries in uromodulin biology and its emerging roles in modulating kidney and systemic diseases, and consider future directions, including its potential clinical applications.

Causal Association Between Sedentary Behaviors and Health Outcomes: A Systematic Review and Meta-Analysis of Mendelian Randomization Studies

BACKGROUND

Different types of sedentary behavior are associated with several health outcomes, but the causality of these associations remains unclear.

OBJECTIVES

To conduct a systematic review and meta-analysis of Mendelian randomization (MR) studies investigating the associations between sedentary behaviors and health outcomes.

METHODS

A systematic search on PubMed, Embase, Web of Science, Scopus, and PsycINFO up to August 2023 was conducted to identify eligible MR studies. We selected studies that assessed associations of genetically determined sedentary behaviors and health outcomes. A meta-analysis was conducted to examine the causal associations when two or more MR studies were available. We graded the evidence level of each MR association based on the results of the main method and sensitivity analyses in MR studies.

RESULTS

A total of 31 studies with 168 MR associations between six types of sedentary behavior and 47 health outcomes were included. Results from meta-analyses suggested a total of 47 significant causal associations between sedentary behaviors and health outcomes. Notably, more leisure TV watching is robustly correlated with increased risks of myocardial infarction, coronary artery disease, all-cause ischemic stroke, and type 2 diabetes. Conversely, robust inverse associations were observed between leisure computer use and risks of rheumatoid arthritis, Alzheimer's disease, and gastroesophageal reflux disease.

CONCLUSION

These findings suggest that different types of sedentary behavior have distinct causal effects on health outcomes. Therefore, interventions should focus not only on reducing sedentary time but also on promoting healthier types of sedentary behavior.

PROSPERO REGISTRATION

CRD42023453828.