HDL Cholesterol, LDL Cholesterol, and Triglycerides as Risk Factors for CKD: A Mendelian Randomization Study

Recent advances in the application of Mendelian randomization to chronic kidney disease

OBJECTIVE

Chronic kidney disease (CKD) is a condition influenced by both genetic and environmental factors and has been a focus of extensive research. Utilizing Mendelian randomization, researchers have begun to untangle the complex causal relationships underlying CKD. This review delves into the advances and challenges in the application of MR in the field of nephrology, shifting from a mere summary of its principles and limitations to a more nuanced exploration of its contributions to our understanding of CKD.

METHODS

Key findings from recent studies have been pivotal in reshaping our comprehension of CKD. Notably, evidence indicates that elevated testosterone levels may impair renal function, while higher sex hormone-binding globulin (SHBG) levels appear to be protective, predominantly in men. Surprisingly, variations in plasma glucose and glycated hemoglobin levels seem unaffected by genetically induced changes in the estimated glomerular filtration rate (eGFR), suggesting an independent pathway for renal function impairment.

RESULTS

Furthermore, lifestyle factors such as physical activity and socioeconomic status emerge as significant influencers of CKD risk and kidney health. The relationship between sleep duration and CKD is nuanced; short sleep duration is linked to increased risk, while long sleep duration does not exhibit a clear causal effect. Additionally, lifestyle factors, including diet, exercise, and mental wellness activities, play a crucial role in kidney health. New insights also reveal a substantial causal connection between both central and general obesity and CKD onset, while no significant links were found between genetically modified LDL cholesterol or triglyceride levels and kidney function.

CONCLUSION

This review not only presents the recent achievements of MR in CKD research but also illuminates the path forwards, underscoring critical unanswered questions and proposing future research directions in this dynamic field.

Remnant cholesterol, preinflammatory state and chronic kidney disease: association and mediation analyses

Blood lipid management is a key approach in the prevention of chronic kidney disease (CKD). Remnant cholesterol (RC) plays an important role in the development of multiple diseases via chronic inflammation. The aim of our study was to determine the relationship between RC and CKD and explore the role of inflammation in this relationship. The 7696 subjects from the Chinese Health and Nutrition Survey were divided into four subgroups according to the quartile of RC. The estimated glomerular filtration rate was calculated using the CKD Epidemiology Collaboration equation. Fasting RC was calculated as total cholesterol minus low-density lipoprotein cholesterol and high-density lipoprotein cholesterol. Logistic regression analysis was employed to evaluate the relationships between RC and CKD. Mediation analysis was undertaken to identify potential mediators of high-sensitivity C-reactive protein (hs-CRP) and white blood cells (WBCs). Of all participants, the mean age was 51 years, and the male accounted for 47.8%. The multivariable-adjusted odds ratios (95% CIs) for the highest versus lowest quartile of remnant cholesterol were 1.40 (1.10-1.78, p for trend = 0.006) for CKD. RC and preinflammatory markers have combined effect on CKD. The preinflammatory state, presented by increased hs-CRP or WBCs, partially mediated the association between RC and CKD with proportion of 10.14% (p = 0.002) and 11.65% (p = 0.012), respectively. In conclusion, this study suggested a positive relationship between RC and CKD, which was partially mediated by preinflammatory state. These findings highlight the importance of RC and inflammation in renal dysfunction.IMPACT STATEMENTWhat is already known on this subject?: Dyslipidemia plays an important role in the development of chronic kidney disease (CKD). Remnant cholesterol (RC), as a triglyceride-rich particle, can contribute to target organ damage, primarily through inflammatory pathways. However, the relationship between RC and CKD in the community-dwelling population, particularly the role of inflammation, is not yet fully understood.What do the results of this study add?: This study shows that RC was significantly associated with CKD. RC and preinflammatory status exhibit a combined effect on CKD. Preinflammatory state, presented by increased high-sensitivity C-reactive protein or white blood cells, partially mediated the association between RC and CKD.What are the implications of these findings for clinical practice and/or further research?: The study provides us with a better understanding of the role of RC and inflammation in kidney dysfunction and raises the awareness of RC in the management of CKD.

Predictive value of total cholesterol to high-density lipoprotein cholesterol ratio for chronic kidney disease among adult male and female in Northwest China

Background

Studies have found that the ratio of total cholesterol to high-density lipoprotein cholesterol (TC/HDL-C) was associated with the development of chronic kidney disease (CKD). However, the relationship in different genders was rarely discussed. The aim of this study was to explore this relationship and assess its predictive power for both males and females.

Methods

Based on a prospective cohort platform in northwest China, 32,351 participants without CKD were collected in the baseline and followed up for approximately 5 years. Cox proportional hazard model and restricted cubic spline regression analysis were performed to investigate the association between TC, HDL-C, TC/HDL-C and CKD in adult female and male. The clinical application value of the indicators in predicting CKD was evaluated by the receiver operator characteristic curve.

Results

During a mean follow-up of 2.2 years, 484 males and 164 females developed CKD. After adjusted for relevant confounders, for every one standard deviation increase in TC, HDL-C and TC/HDL-C, the hazard ratios (HRs) and 95% confidence intervals (95% CIs) for CKD were 1.17 (1.05-1.31), 0.84 (0.71-0.99), and 1.15 (1.06-1.25) for males, 0.94 (0.78-1.13), 0.58 (0.35-0.95), and 1.19 (1.01-1.40) for females, respectively. The results also showed that TC, HDL-C, and TC/HDL-C were associated with CKD in a linear dose-response relationship. The TC/HDL-C had the largest area under the curve (AUC) compared to TC and HDL-C, and the AUC among the females was larger than that among males.

Conclusions

The TC/HDL-C was significantly associated with CKD in adult males and females and has better clinical value in predicting CKD than TC and HDL-C, especially in females.

The causal relationship between 5 serum lipid parameters and diabetic nephropathy: a Mendelian randomization study

Background

Serum lipids were found to be correlated with chronic kidney disease and cardiovascular disease. Here, we aimed to research the potential causal associations between five serum lipid parameters and the risk of diabetic nephropathy using several Mendelian Randomization methods.

Methods

Genetic data was obtained from the UK Biobank datasets. Causal effects were estimated using multiple MR methods. Heterogeneity and pleiotropy tests were performed.

Results

MR analysis revealed that HDL-C and TG exhibited causal associations with diabetic nephropathy (P<0.05). Similar trends were not observed for other lipid parameters.

Conclusions

Our research has suggested links between HDL-C, TG and diabetic nephropathy. The findings could contribute to further elucidation of the disease etiology.

Strengths and limitations of this study

This article only uses Mendel randomization method to analyze the relationship between blood lipids and diabetes nephropathy, which is more convincing when combined with population data.

Metabolomics Characterization of Disease Markers in Diabetes and Its Associated Pathologies

With the change in lifestyle of people, there has been a considerable increase in diabetes, which brings with it certain follow-up pathological conditions, which lead to a substantial medical burden. Identifying biomarkers that aid in screening, diagnosis, and prognosis of diabetes and its associated pathologies would help better patient management and facilitate a personalized treatment approach for prevention and treatment. With the advancement in techniques and technologies, metabolomics has emerged as an omics approach capable of large-scale high throughput data analysis and identifying and quantifying metabolites that provide an insight into the underlying mechanism of the disease and its progression. Diabetes and metabolomics keywords were searched in correspondence with the assigned keywords, including kidney, cardiovascular diseases and critical illness from PubMed and Scopus, from its inception to Dec 2023. The relevant studies from this search were extracted and included in the study. This review is focused on the biomarkers identified in diabetes, diabetic kidney disease, diabetes-related development of CVD, and its role in critical illness.

Causality of Genetically Determined Metabolites on Chronic Kidney Disease: A Two-Sample Mendelian Randomization Study In Silico

Introduction: Chronic kidney disease (CKD) is associated with metabolic disorders. However, the evidence for the causality of circulating metabolites to promote or prevent CKD is still lacking. Methods: The two-sample Mendelian randomization (MR) analysis was conducted to evaluate the latent causal relationship between the genetically proxied 486 blood metabolites and CKD. Genome-wide association study (GWAS) data for exposures were derived from 7824 European GWAS on metabolite levels, which have been extensively utilized in the medical field to elucidate the mechanisms underlying disease onset and progression. The random inverse variance weighted (IVW) is the primary analysis for causality analysis while MR-Egger and weighted median as complementary analyses. For the further identification of metabolites, reverse MR and linkage disequilibrium score regression were performed for further evaluation. The drug target for N-acetylornithine was subsequently supplemented into the analysis, with MR and colocalization analysis being utilized. Key metabolic pathways were identified via MetaboAnalyst 4.0 (https://www.metaboanalyst.ca/) online website. Results: N-acetylornithine was identified as a reliable metabolite that increases the susceptibility to estimated glomerular filtration rate (eGFR) decrease (β = 0.047; 95% confidence interval: -0.068 to -0.026; PIVW = 1.5E-5). The "glyoxylate and dicarboxylate metabolism" pathway showed significant relevance to CKD development (P = 6E-4), whereas the "glycine, serine, and threonine metabolism" pathway was also recognized as associated with CKD by general practitioners (P = 7E-4). Colocalization analysis revealed a robust genetic link between N-acetylornithine and both CKD and eGFR, with 85.1% and 99.4% colocalization rates, respectively. IVW-MR analysis substantiated these findings with a significant positive association for CKD (odds ratio = 1.43, P = 4.7E-5) and a negative correlation with eGFR (b = -0.04, P = 1.13E-31). Conclusions: MR was utilized to explore the potential causal links between 61 genetic serum metabolites and CKD. N-acetylornithine and NAT8 were further explored as a potential therapeutic target for CKD treatment.

Causal association of plasma circulating metabolites with nephritis: a Mendelian randomization study

Background

Nephritis is a pivotal catalyst in chronic kidney disease (CKD) progression. Although epidemiological studies have explored the impact of plasma circulating metabolites and drugs on nephritis, few have harnessed genetic methodologies to establish causal relationships.

Methods

Through Mendelian randomization (MR) in two substantial cohorts, spanning large sample sizes, we evaluated over 100 plasma circulating metabolites and 263 drugs to discern their causal effects on nephritis risk. The primary analytical tool was the inverse variance weighted (IVW) analysis. Our bioinformatic scrutiny of GSE115857 (IgA nephropathy, 86 samples) and GSE72326 (lupus nephritis, 238 samples) unveiled anomalies in lipid metabolism and immunological characteristics in nephritis. Thorough sensitivity analyses (MR-Egger, MR-PRESSO, leave-one-out analysis) were undertaken to verify the instrumental variables' (IVs) assumptions.

Results

Unique lipoprotein-related molecules established causal links with diverse nephritis subtypes. Notably, docosahexaenoic acid (DHA) emerged as a protective factor for acute tubulointerstitial nephritis (ATIN) (OR1 = 0.84, [95% CI 0.78-0.90], p1 = 0.013; OR2 = 0.89, [95% CI 0.82-0.97], p2 = 0.007). Conversely, multivitamin supplementation minus minerals notably increased the risk of ATIN (OR = 31.25, [95% CI 9.23-105.85], p = 0.004). Reduced α-linolenic acid (ALA) levels due to lipid-lowering drugs were linked to both ATIN (OR = 4.88, [95% CI 3.52-6.77], p < 0.001) and tubulointerstitial nephritis (TIN) (OR = 7.52, [95% CI 2.78-20.30], p = 0.042). While the non-renal drug indivina showed promise for TIN treatment, the use of digoxin, hydroxocobalamin, and liothyronine elevated the risk of chronic tubulointerstitial nephritis (CTIN). Transcriptome analysis affirmed that anomalous lipid metabolism and immune infiltration are characteristic of IgA nephropathy and lupus nephritis. The robustness of these causal links was reinforced by sensitivity analyses and leave-one-out tests, indicating no signs of pleiotropy.

Conclusion

Dyslipidemia significantly contributes to nephritis development. Strategies aimed at reducing plasma low-density lipoprotein levels or ALA supplementation may enhance the efficacy of existing lipid-lowering drug regimens for nephritis treatment. Renal functional status should also be judiciously considered with regard to the use of nonrenal medications.

Analyzing Longitudinal Health Screening Data with Feature Ensemble and Machine Learning Techniques: Investigating Diagnostic Risk Factors of Metabolic Syndrome for Chronic Kidney Disease Stages 3a to 3b

Longitudinal data, while often limited, contain valuable insights into features impacting clinical outcomes. To predict the progression of chronic kidney disease (CKD) in patients with metabolic syndrome, particularly those transitioning from stage 3a to 3b, where data are scarce, utilizing feature ensemble techniques can be advantageous. It can effectively identify crucial risk factors, influencing CKD progression, thereby enhancing model performance. Machine learning (ML) methods have gained popularity due to their ability to perform feature selection and handle complex feature interactions more effectively than traditional approaches. However, different ML methods yield varying feature importance information. This study proposes a multiphase hybrid risk factor evaluation scheme to consider the diverse feature information generated by ML methods. The scheme incorporates variable ensemble rules (VERs) to combine feature importance information, thereby aiding in the identification of important features influencing CKD progression and supporting clinical decision making. In the proposed scheme, we employ six ML models-Lasso, RF, MARS, LightGBM, XGBoost, and CatBoost-each renowned for its distinct feature selection mechanisms and widespread usage in clinical studies. By implementing our proposed scheme, thirteen features affecting CKD progression are identified, and a promising AUC score of 0.883 can be achieved when constructing a model with them.

Hypothesis-free discovery of novel cancer predictors using machine learning

BACKGROUND

Cancer is a leading cause of morbidity and mortality worldwide, and better understanding of the risk factors could enhance prevention.

METHODS

We conducted a hypothesis-free analysis combining machine learning and statistical approaches to identify cancer risk factors from 2828 potential predictors captured at baseline. There were 459,169 UK Biobank participants free from cancer at baseline and 48,671 new cancer cases during the 10-year follow-up. Logistic regression models adjusted for age, sex, ethnicity, education, material deprivation, smoking, alcohol intake, body mass index and skin colour (as a proxy for sun sensitivity) were used for obtaining adjusted odds ratios, with continuous predictors presented using quintiles (Q).

RESULTS

In addition to smoking, older age and male sex, positively associating features included several anthropometric characteristics, whole body water mass, pulse, hypertension and biomarkers such as urinary microalbumin (Q5 vs. Q1 OR 1.16, 95% CI = 1.13-1.19), C-reactive protein (Q5 vs. Q1 OR 1.20, 95% CI = 1.16-1.24) and red blood cell distribution width (Q5 vs. Q1 OR 1.18, 95% CI = 1.14-1.21), among others. High-density lipoprotein cholesterol (Q5 vs. Q1 OR 0.84, 95% CI = 0.81-0.87) and albumin (Q5 vs. Q1 OR 0.84, 95% CI = 0.81-0.87) were inversely associated with cancer. In sex-stratified analyses, higher testosterone increased the risk in females but not in males (Q5 vs. Q1 ORfemales 1.23, 95% CI = 1.17-1.30). Phosphate was associated with a lower risk in females but a higher risk in males (Q5 vs. Q1 ORfemales 0.94, 95% CI = 0.90-0.99 vs. ORmales 1.09, 95% CI 1.04-1.15).

CONCLUSIONS

This hypothesis-free analysis suggests personal characteristics, metabolic biomarkers, physical measures and smoking as important predictors of cancer risk, with further studies needed to confirm causality and clinical relevance.

Understanding the relationship between circulating lipids and risk of chronic kidney disease: a prospective cohort study and large-scale genetic analyses

BACKGROUND

This study aims to comprehensively investigate the phenotypic and genetic relationships between four common lipids (high-density lipoprotein cholesterol, HDL-C; low-density lipoprotein cholesterol, LDL-C; total cholesterol, TC; and triglycerides, TG), chronic kidney disease (CKD), and estimated glomerular filtration rate (eGFR).

METHODS

We first investigated the observational association of lipids (exposures) with CKD (primary outcome) and eGFR (secondary outcome) using data from UK Biobank. We then explored the genetic relationship using summary statistics from the largest genome-wide association study of four lipids (N = 1,320,016), CKD (Ncase = 41,395, Ncontrol = 439,303), and eGFR(N = 567,460).

RESULTS

There were significant phenotypic associations (HDL-C: hazard ratio (HR) = 0.76, 95%CI = 0.60-0.95; TG: HR = 1.08, 95%CI = 1.02-1.13) and global genetic correlations (HDL-C: [Formula: see text] = - 0.132, P = 1.00 × 10-4; TG: [Formula: see text] = 0.176; P = 2.66 × 10-5) between HDL-C, TG, and CKD risk. Partitioning the whole genome into 2353 LD-independent regions, twelve significant regions were observed for four lipids and CKD. The shared genetic basis was largely explained by 29 pleiotropic loci and 36 shared gene-tissue pairs. Mendelian randomization revealed an independent causal relationship of genetically predicted HDL-C (odds ratio = 0.91, 95%CI = 0.85-0.98), but not for LDL-C, TC, or TG, with the risk of CKD. Regarding eGFR, a similar pattern of correlation and pleiotropy was observed.

CONCLUSIONS

Our work demonstrates a putative causal role of HDL-C in CKD and a significant biological pleiotropy underlying lipids and CKD in populations of European ancestry. Management of low HDL-C levels could potentially benefit in reducing the long-term risk of CKD.

A Nomogram for Predicting the Risk of CKD Based on Cardiometabolic Risk Factors

Background

In China, the spectrum of causes for CKD has been changing in recent years, and the proportion of CKD caused by cardiometabolic diseases, such as diabetes and hypertension continues to increase. Thus, predicting CKD based on cardiometabolic risk factors can to a large extent help identify those at increased risk and facilitate the prevention of CKD. In this study, we aimed to develop a nomogram for predicting CKD risk based on cardiometabolic risk factors.

Methods

We developed a nomogram for predicting CKD risk by using a subcohort population of the 4C study, which was located in central China. The prediction model was designed by using a logistic regression model, and a backwards procedure based on the Akaike information criterion was applied for variable selection. The performance of the model was evaluated by the concordance index (C-index), and Hosmer‒Lemeshow goodness-of-fit test. The bootstrapping method was applied for internal validation.

Results

During the 3-years follow-up, 167 cases of CKD developed. By using univariate and multivariate logistic regression models, the following factors were identified as predictors in the nomogram: age, sex, HbA1c, baseline eGFR, low HDL-C levels, high TC levels and SBP. The bootstrap-corrected C-index for the model was 0.84, which indicated good discrimination ability. The Hosmer‒Lemeshow goodness-of-fit tests yielded chi-square of 13.61 (P=0.192), and the calibration curves demonstrated good consistency between the predicted and observed probabilities, which indicated satisfactory calibration ability.

Conclusion

We developed a convenient and practicable nomogram for the 3‑year risk of incident CKD among a population in central China, which may help to identify high-risk individuals for CKD and contribute to the prevention of CKD.

High-Density Lipoprotein in Metabolic Disorders and Beyond: An Exciting New World Full of Challenges and Opportunities

High-density lipoprotein (HDL) is an enigmatic member of the plasma lipid and lipoprotein transport system, best known for its ability to promote the reverse cholesterol efflux and the unloading of excess cholesterol from peripheral tissues. More recently, data in experimental mice and humans suggest that HDL may play important novel roles in other physiological processes associated with various metabolic disorders. Important parameters in the HDL functions are its apolipoprotein and lipid content, further reinforcing the principle that HDL structure defines its functionality. Thus, based on current evidence, low levels of HDL-cholesterol (HDL-C) or dysfunctional HDL particles contribute to the development of metabolic diseases such as morbid obesity, type 2 diabetes mellitus, and nonalcoholic fatty liver disease. Interestingly, low levels of HDL-C and dysfunctional HDL particles are observed in patients with multiple myeloma and other types of cancer. Therefore, adjusting HDL-C levels within the optimal range and improving HDL particle functionality is expected to benefit such pathological conditions. The failure of previous clinical trials testing various HDL-C-raising pharmaceuticals does not preclude a significant role for HDL in the treatment of atherosclerosis and related metabolic disorders. Those trials were designed on the principle of "the more the better", ignoring the U-shape relationship between HDL-C levels and morbidity and mortality. Thus, many of these pharmaceuticals should be retested in appropriately designed clinical trials. Novel gene-editing-based pharmaceuticals aiming at altering the apolipoprotein composition of HDL are expected to revolutionize the treatment strategies, improving the functionality of dysfunctional HDL.

The causal effects of lipid traits on kidney function in Africans: bidirectional and multivariable Mendelian-randomization study

BACKGROUND

Observational studies have investigated the effect of serum lipids on kidney function, but these findings are limited by confounding, reverse causation and have reported conflicting results. Mendelian randomization (MR) studies address this confounding problem. However, they have been conducted mostly in European ancestry individuals. We, therefore, set out to investigate the effect of lipid traits on the estimated glomerular filtration rate (eGFR) based on serum creatinine in individuals of African ancestry.

METHODS

We used the two-sample and multivariable Mendelian randomization (MVMR) approaches; in which instrument variables (IV's) for the predictor (lipid traits) were derived from summary-level data of a meta-analyzed African lipid GWAS (MALG, n = 24,215) from the African Partnership for Chronic Disease Research (APCDR) (n = 13,612) & the Africa Wits-IN-DEPTH partnership for Genomics studies (AWI-Gen) dataset (n = 10,603). The outcome IV's were computed from the eGFR summary-level data of African-ancestry individuals within the Million Veteran Program (n = 57,336). A random-effects inverse variance method was used in our primary analysis, and pleiotropy was adjusted for using robust and penalized sensitivity testing. The lipid predictors for the MVMR were high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, and triglycerides (TG).

FINDINGS

We found a significant causal association between genetically predicted low-density lipoprotein (LDL) cholesterol and eGFR in African ancestry individuals β = 1.1 (95% CI [0.411-1.788]; p = 0.002). Similarly, total cholesterol (TC) showed a significant causal effect on eGFR β = 1.619 (95% CI [0.412-2.826]; p = 0.009). However, the IVW estimate showed that genetically predicted HDL-C β = -0.164, (95% CI = [-1.329 to 1.00]; p = 0.782), and TG β = -0.934 (CI = [-2.815 to 0.947]; p = 0.33) were not significantly causally associated with the risk of eGFR. In the multivariable analysis inverse-variance weighted (MVIVW) method, there was evidence for a causal association between LDL and eGFR β = 1.228 (CI = [0.477-1.979]; p = 0.001). A significant causal effect of Triglycerides (TG) on eGFR in the MVIVW analysis β = -1.3 ([-2.533 to -0.067]; p = 0.039) was observed as well. All the causal estimates reported reflect a unit change in the outcome per a 1 SD increase in the exposure. HDL showed no evidence of a significant causal association with eGFR in the MVIVW method (β = -0.117 (95% CI [-1.252 to 0.018]; p = 0.840)). We found no evidence of a reverse causal impact of eGFR on serum lipids. All our sensitivity analyses indicated no strong evidence of pleiotropy or heterogeneity between our instrumental variables for both the forward and reverse MR analysis.

INTERPRETATION

In this African ancestry population, genetically predicted higher LDL-C and TC are causally associated with higher eGFR levels, which may suggest that the relationship between LDL, TC and kidney function may be U-shaped. And as such, lowering LDL_C does not necessarily improve risk of kidney disease. This may also imply the reason why LDL_C is seen to be a poorer predictor of kidney function compared to HDL. In addition, this further supports that more work is warranted to confirm the potential association between lipid traits and risk of kidney disease in individuals of African Ancestry.

FUNDING

Wellcome (220740/Z/20/Z).

Serum Urate and Risk of Chronic Kidney Disease: A Mendelian Randomization Study Using Taiwan Biobank

OBJECTIVE

To evaluate the association between serum urate and risk of incident chronic kidney disease (CKD) and to assess whether serum urate plays a causal role in CKD.

PATIENTS AND METHODS

We conducted a prospective cohort study and Mendelian randomization analysis that analyzed longitudinal data from the Taiwan Biobank between January 1, 2012, and December 31, 2021.

RESULTS

A total of 34,831 individuals met the inclusion criteria, of which 4697 (13.5%) had hyperuricemia. After a median (interquartile range) follow-up of 4.1 (3.1-4.9) years, 429 participants developed CKD. After adjustment for age, sex, and comorbid conditions, each mg/dL increase in serum urate was associated with a 15% higher risk of incident CKD (HR, 1.15; 95% CI, 1.08 to 1.24; P<.001). The genetic risk score and seven Mendelian randomization methods revealed no significant association between serum urate levels and the risk of incident CKD (HR, 1.03; 95% CI, 0.72 to 1.46; P=0.89; all P>.05 for 7 Mendelian randomization methods).

CONCLUSION

This prospective, population-based cohort study showed that elevated serum urate is a significant risk factor for incident CKD; however, Mendelian randomization analyses failed to provide evidence that serum urate had a causal effect on CKD in the East Asian population.

Protective effect of natural products in the metabolic-associated kidney diseases via regulating mitochondrial dysfunction

Metabolic syndrome (MS) is a complex group of metabolic disorders syndrome with hypertension, hyperuricemia and disorders of glucose or lipid metabolism. As an important organ involved in metabolism, the kidney is inevitably attacked by various metabolic disorders, leading to abnormalities in kidney structure and function. Recently, an increasing number of studies have shown that mitochondrial dysfunction is actively involved in the development of metabolic-associated kidney diseases. Mitochondrial dysfunction can be used as a potential therapeutic strategy for the treatment of metabolic-associated kidney diseases. Many natural products have been widely used to improve the treatment of metabolic-associated kidney diseases by inhibiting mitochondrial dysfunction. In this paper, by searching several authoritative databases such as PubMed, Web of Science, Wiley Online Library, and Springer Link. We summarize the Natural Products Protect Against Metabolic-Associated Kidney Diseases by Regulating Mitochondrial Dysfunction. In this review, we sought to provide an overview of the mechanisms by which mitochondrial dysfunction impaired metabolic-associated kidney diseases, with particular attention to the role of mitochondrial dysfunction in diabetic nephropathy, gouty nephropathy, hypertensive kidney disease, and obesity-related nephropathy, and then the protective role of natural products in the kidney through inhibition of mitochondrial disorders, thus providing a systematic understanding of the targets of mitochondrial dysfunction in metabolic-associated kidney diseases, and finally a review of promising therapeutic targets and herbal candidates for metabolic-associated kidney diseases through inhibition of mitochondrial dysfunction.

Obesity and chronic kidney disease

The prevalence of obesity has increased dramatically during the past decades, which has been a major health problem. Since 1975, the number of people with obesity worldwide has nearly tripled. An increasing number of studies find obesity as a driver of chronic kidney disease (CKD) progression, and the mechanisms are complex and include hemodynamic changes, inflammation, oxidative stress, and activation of the renin-angiotensin-aldosterone system (RAAS). Obesity-related kidney disease is characterized by glomerulomegaly, which is often accompanied by localized and segmental glomerulosclerosis lesions. In these patients, the early symptoms are atypical, with microproteinuria being the main clinical manifestation and nephrotic syndrome being rare. Weight loss and RAAS blockers have a protective effect on obesity-related CKD, but even so, a significant proportion of patients eventually progress to end-stage renal disease despite treatment. Thus, it is critical to comprehend the mechanisms underlying obesity-related CKD to create new tactics for slowing or stopping disease progression. In this review, we summarize current knowledge on the mechanisms of obesity-related kidney disease, its pathological changes, and future perspectives on its treatment.

Association between serum uric acid/HDL-cholesterol ratio and chronic kidney disease: a cross-sectional study based on a health check-up population

OBJECTIVE

Evidence suggests that both serum uric acid (SUA) and high-density lipoprotein cholesterol (HDL-C) are risk factors for chronic kidney disease (CKD). The SUA-to-HDL-C ratio (UHR) has recently attracted attention as a new biomarker to evaluate the role between inflammatory and anti-inflammatory substances. Thus, we explored the association between UHR and CKD in a large Chinese population.

DESIGN

A cross-sectional study.

SETTING

Annual health check-up population in Nanjing.

PARTICIPANTS

19 458 individuals who underwent an annual health check-up in 2019 were included in our study.

MAIN OUTCOME MEASURE

CKD was diagnosed according to an estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m².

RESULTS

Correlation analysis showed that UHR was negatively associated with eGFR after adjusting for confounding factors (r=-0.34). In addition, participants in the highest quartile of UHR had a higher risk of CKD than those in the lowest quartiles (OR=9.28, p<0.001).

CONCLUSION

We found that high UHR values were positively associated with CKD risk in health check-up population. An increased UHR may be a useful measure by which to assess CKD risk in the preclinical stage.

Lipid Parameters and the Development of Chronic Kidney Disease: A Prospective Cohort Study in Middle-Aged and Elderly Chinese Individuals

Epidemiological evidence suggests that lipid parameters are related to the progression of chronic kidney disease (CKD). Nevertheless, prospective studies that comprehensively assess the effect of routinely available lipid measures on the development of CKD are lacking. The aim of this study was to longitudinally assess the influence of lipid metabolism indicators on the presence of CKD in a large community-based population. We conducted a prospective cohort study at Sun Yat-sen Memorial Hospital, China, with 5345 patients of 40 years or older. Cox regression models were conducted, and hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated to assess lipid parameters and their relationship with the incidence of CKD. During the follow-up period, 340 (6.4%) subjects developed CKD. The incidence of CKD increased progressively with quartile values of triglyceride (TG), the ratio of non-high-density lipoprotein cholesterol to high-density lipoprotein cholesterol (non-HDL-C/HDL-C) and the ratio of TG to HDL-C, but decreased with HDL-C quartiles (p < 0.0001 for all trends). Pearson’s correlation analysis and multiple regression analyses indicated that these parameters were also associated with various indicators of kidney function. Moreover, we found that among all the lipid parameters, TG/HDL-C emerged as the most effective predictor of CKD. In conclusion, our findings suggest that TG/HDL-C better predicts the incidence of CKD in middle-aged and elderly Chinese individuals than other lipid parameters tested in the study.

Vascular endothelial growth factor and the risk of venous thromboembolism: a genetic correlation and two-sample Mendelian randomization study

Background

The relationship between vascular endothelial growth factor (VEGF) and the risk of venous thromboembolism (VTE) has always been one of the concerns in the medical field. However, the causal inferences from published observational studies on this issue may be affected by confounders or reverse causality. We performed a two-sample bidirectional Mendelian randomization (MR) to infer the associations between VEGF and VTE.

Methods

Summary statistics from genome-wide association studies (GWAS) for VEGF and VTE were obtained from published meta-analysis studies and the FinnGen consortium, respectively. Independent genetic variables significantly associated with exposure were selected as instrumental variables. Linkage disequilibrium score regression (LDSC) and five robust MR analytical approaches were conducted to estimate the genetic correlations and causal inference. The MR-Egger intercept, Cochran’s Q, and MR pleiotropy residual sum and outlier (MR-PRESSO) were performed to evaluate the horizontal pleiotropy, heterogeneities, and stability of these genetic variants on outcomes. Notably, replication analyses were performed using different subgroups of VTE.

Results

LDSC failed to identify genetic correlations between VEGF and VTE. Based on 9 SNPs, the circulating VEGF level was positively related to the risk of VTE using inverse variance weighting (IVW) method (odds ratio (OR) = 1.064, 95% confidence interval (CI), 1.009–1.122). Reverse MR analyses showed that genetic liability for VTE was not associated with increased VEGF level (β = -0.021, 95% CI, -0.087-0.045). Pleiotropy-robust methods indicated no bias in any estimates.

Conclusions

Our findings failed to detect coheritability between VEGF and VTE. The suggestive positive effect of the higher VEGF level on the VTE risk may have clinical implications, suggesting that VEGF as a possible predictor and therapeutic target for VTE prevention need to be further warranted.

High-density lipoprotein revisited: biological functions and clinical relevance

Previous interest in high-density lipoproteins (HDLs) focused on their possible protective role in atherosclerotic cardiovascular disease (ASCVD). Evidence from genetic studies and randomized trials, however, questioned that the inverse association of HDL-cholesterol (HDL-C) is causal. This review aims to provide an update on the role of HDL in health and disease, also beyond ASCVD. Through evolution from invertebrates, HDLs are the principal lipoproteins, while apolipoprotein B-containing lipoproteins first developed in vertebrates. HDLs transport cholesterol and other lipids between different cells like a reusable ferry, but serve many other functions including communication with cells and the inactivation of biohazards like bacterial lipopolysaccharides. These functions are exerted by entire HDL particles or distinct proteins or lipids carried by HDL rather than by its cholesterol cargo measured as HDL-C. Neither does HDL-C measurement reflect the efficiency of reverse cholesterol transport. Recent studies indicate that functional measures of HDL, notably cholesterol efflux capacity, numbers of HDL particles, or distinct HDL proteins are better predictors of ASCVD events than HDL-C. Low HDL-C levels are related observationally, but also genetically, to increased risks of infectious diseases, death during sepsis, diabetes mellitus, and chronic kidney disease. Additional, but only observational, data indicate associations of low HDL-C with various autoimmune diseases, and cancers, as well as all-cause mortality. Conversely, extremely high HDL-C levels are associated with an increased risk of age-related macular degeneration (also genetically), infectious disease, and all-cause mortality. HDL encompasses dynamic multimolecular and multifunctional lipoproteins that likely emerged during evolution to serve several physiological roles and prevent or heal pathologies beyond ASCVD. For any clinical exploitation of HDL, the indirect marker HDL-C must be replaced by direct biomarkers reflecting the causal role of HDL in the respective disease.

Elevated triglycerides and reduced high-density lipoprotein cholesterol are independently associated with the onset of advanced chronic kidney disease: a cohort study of 911,360 individuals from the United Kingdom

Background

Increased total cholesterol (TC), triglycerides (TG), low-density lipoprotein cholesterol (LDL-C), and decreased high-density lipoprotein cholesterol (HDL-C) concentrations, are established risk factors for cardiovascular morbidity and mortality; but their impact on the risk of advanced chronic kidney disease (CKD) is unclear. This study evaluates the association between the different lipid profiles and the onset of advanced CKD using a general population sample.

Methods

This observational study used records of 911,360 individuals from the English Clinical Practice Research Datalink (from 2000 to 2014), linked to coded hospital discharges and mortality registrations. Cox models were used to examine the independent association between the equal quarters of TC, TG, LDL-C, and HDL-C and the risk of advanced CKD, after adjustment for sex and age, and potential effect mediators.

Results

During a median follow-up of 7.5 years, 11,825 individuals developed CKD stages 4–5. After adjustment for sex and age, the hazard ratios (HRs) and confidence intervals (CIs) for CKD stages 4–5 comparing the 4th vs. 1st quarters of TG and 1st vs. 4th quarters of HDL-C were 2.69 (95% CI, 2.49–2.90) and 2.61 (95% CI, 2.42–2.80), respectively. Additional adjustment for potential effect mediators reduced the HRs to 1.28 (95% CI, 1.15–1.43), and 1.27 (95% CI, 1.14–1.41), respectively. There was no evidence of fully adjusted associations with CKD stages 4–5 for levels of either TC or LDL-C.

Conclusions

Elevated TG and reduced HDL-C levels are independently associated with the onset of advanced CKD. Future studies, such as in basic science and randomized trials, are needed to understand whether associations between TG and HDL-C and the development of CKD are causal.

Mendelian randomization reveals causal effects of kidney function on various biochemical parameters

The kidney is a vital organ with diverse biological effects and the burden of kidney function impairment is increasing in modern medicine. As the effects from kidney function on diverse biochemical parameters are yet fully understood, additional investigation to reveal the causal effects is warranted. Here we show the causal estimates from kidney function parameter, estimated glomerular filtration rate (eGFR), on 60 biochemical parameters by performing two-sample Mendelian randomization (MR) study in 337,138 white British UK Biobank participants. A higher genetically predicted eGFR was significantly associated with higher lymphocyte percentage, HDL cholesterol, and alanine aminotransferase. The causal estimates indicated that a higher genetically predicted eGFR was associated with lower urea, urate, insulin growth factor-1, and triglycerides levels. The parameters with significant but non-linear causal estimates were hemoglobin concentration, calcium, vitamin D, and urine creatinine values, identified by non-linear MR. Healthcare providers should understand that changes in eGFR may affect the identified biochemical parameters in diverse patterns. Future study is warranted to expand the knowledge of the mechanisms and clinical implications of the causal effects of eGFR on various biochemical parameters.

ACLY and CKD: A Mendelian Randomization Analysis

Introduction

Adenosine triphosphate-citrate lyase (ACLY) inhibition is a therapeutic strategy under investigation for atherosclerotic cardiovascular disease, nonalcoholic steatohepatitis, and metabolic syndrome. Mouse models suggest that ACLY inhibition could reduce inflammation and kidney fibrosis. Genetic analysis of ACLY in chronic kidney disease (CKD) has not been performed.

Methods

We constructed a genetic instrument by selecting variants associated with ACLY expression in the expression quantitative trait loci genetics consortium (eQTLGen) from blood samples from 31,684 participants. In a 2-sample Mendelian randomization analysis, we evaluated the effect of genetically predicted ACLY expression on the risk of CKD, estimated glomerular filtration rate (eGFR), and albumin-to-creatinine ratio (ACR) using the CKD Genetics (CKDGen) consortium, UK Biobank, and the Finnish Genetics (FinnGen) consortium totaling 66,396 CKD cases and 958,517 controls.

Results

ACLY is constitutively expressed in all cell types including in whole blood. The genetic instrument included 13 variants and explained 1.5% of the variation in whole blood ACLY gene expression. A 34% reduction in ACLY expression score was associated with a 0.04 mmol/l reduced low-density lipoprotein (LDL) cholesterol (P = 3.4 × 10^-4) and a 9% reduced risk of CKD (stages 3, 4, 5, dialysis, or eGFR < 60 ml/min per 1.73 m²) (odds ratio [OR] = 0.91, 95% CI: 0.85-0.98, P = 0.008), but no association was observed with either eGFR or ACR.

Conclusion

Mendelian randomization analyses revealed that genetically reduced ACLY expression was associated with reduced risk of CKD but had no effect on either eGFR or ACR. Further evaluation of ACLY in kidney disease is warranted.

Increased LDL cholesterol level is associated with deterioration of renal function in males

Background

Relationships between levels of serum lipid fractions and the time course of renal function are discrepant in the literature. Here we examined this issue by analyses of healthy subjects in a cohort.

Methods

Of all subjects who received health examinations at Keijinkai Maruyama Clinic, Sapporo in 2006, subjects with hypertension, diabetes mellitus or chronic kidney disease (CKD) and those taking medication for dyslipidemia were excluded, and a total of 5,586 subjects (male/female: 3,563/2,023, mean age: 43 ± 8 years) were followed for 10 years.

Results

Linear mixed effect models showed that baseline low-density lipoprotein (LDL)-cholesterol level was negatively associated with estimated glomerular filtration rate (eGFR) during the 10-year follow-up period after adjustment of confounders. Interactions between the follow-up year and baseline level of LDL-cholesterol or high-density lipoprotein (HDL)-cholesterol for eGFR values during the follow-up period were significant in males but not in females. There were no significant interactions for eGFR between the follow-up year and baseline levels of total cholesterol, triglycerides, or HDL-cholesterol/triglycerides ratio. During the follow-up period, 346 males and 223 females developed CKD. When male subjects were divided into subgroups according to tertiles of baseline levels of LDL-cholesterol, the adjusted risk for CKD in the third tertial group was significantly higher than that in the first tertile group as a reference (hazard ratio [95% confidence interval]: 1.39 [1.02-1.90], p = 0.035). Such a difference was not observed for LDL-cholesterol tertiles in females or HDL-cholesterol tertiles in both sexes.

Conclusions

A high LDL-cholesterol level may be a risk factor of new-onset CKD in apparently healthy males.

Prognostic value of metabolic syndrome in renal structural changes in type 2 diabetes

PURPOSE

To investigate the prognostic value of metabolic syndrome (MetS) and its relationship with renal structure changes in patients with type 2 diabetes and associated diabetic nephropathy (DN).

METHODS

411 Chinese patients with type 2 diabetes and biopsy-confirmed DN were enrolled in this retrospective study. MetS was defined according to the modified criteria of the 2005 International Diabetes Federation. Baseline demographics and clinical information at the time of renal biopsy were extracted from the hospital's electronic medical records system. Renal pathological findings were assessed according to Renal Pathology Society system. Univariate and multivariate logistic regression analyses were performed to define the pathological covariates associated with MetS. A competing risk model, with death as the competing risk, was used to estimate the sub-distribution hazard ratio (SHR) of MetS for end-stage kidney disease (ESKD).

RESULTS

224 (55%) patients had MetS. Patients with MetS had poor renal function and more severe interstitial fibrosis tubular atrophy scores (IFTA) than those without MetS. Multivariate logistic regression analysis revealed that IFTA was significantly associated with MetS (odds ratio per score increase 1.45, 95% confidence interval [CI] 1.02-2.05). Of the patients with DN at risk, 40% of patients progressed to ESKD. After adjusting for renal function and pathological parameters, the presence of MetS was an independent predictor for progression to ESKD (SHR 1.93, 95% CI 1.34-2.79). The SHRs for progression to ESKD also increased as the number of MetS components increased. Additionally, adding the IFTA scores improved the prognostic power of a model that only contained MetS and clinical covariates for predicting future ESKD.

CONCLUSION

MetS is an independent prognostic predictor of ESKD in patients with T2D and DN, while adding the IFTA scores increased the prognostic value of MetS for renal outcome.

Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease

BACKGROUND

This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization.

METHODS

A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included.

RESULTS

Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2.

CONCLUSIONS

Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.

Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies

The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.

Mendelian Randomization Analysis as a Tool to Gain Insights into Causes of Diseases: A Primer

Many Mendelian randomization (MR) studies have been published recently, with inferences on the causal relationships between risk factors and diseases that have potential implications for clinical research. In nephrology, MR methods have been applied to investigate potential causal relationships of traditional risk factors, lifestyle factors, and biomarkers from omics technologies with kidney function or CKD. This primer summarizes the basic concepts of MR studies, highlighting methods used in recent applications, and emphasizes key elements in conducting and reporting of MR studies that are important for interpreting the results.

Inflammation Alters Relationship Between High-Density Lipoprotein Cholesterol and Cardiovascular Risk in Patients With Chronic Kidney Disease: Results From KNOW-CKD

Background

The function of high‐density lipoprotein can change from protective to proatherosclerotic under inflammatory conditions. Herein, we studied whether inflammation could modify the relationship between high‐density lipoprotein level and risk of adverse outcomes in patients with chronic kidney disease .

Methods and Results

In total, 1864 patients from the prospective KNOW‐CKD (Korean Cohort Study for Outcome in Patients With Chronic Kidney Disease) were enrolled. The main predictor was high‐density lipoprotein cholesterol (HDL‐C) level. Presence of inflammation was defined by hs‐CRP (high‐sensitivity C‐reactive protein) level of ≥1.0 mg/L. The primary outcome was extended major adverse cardiovascular events. During 9231.2 person‐years of follow‐up, overall incidence of the primary outcome was 15.8 per 1000 person‐years. In multivariable Cox analysis after adjusting for confounders, HDL‐C level was not associated with the primary outcome. There was a significant interaction between the inflammatory status and HDL‐C for risk of extended major adverse cardiovascular events (P=0.003). In patients without inflammation, the hazard ratios (HRs) (95% CIs) for HDL‐C levels <40, 50 to 59, and ≥60 mg/dL were 1.10 (0.50–1.82), 0.95 (0.50–1.82), and 0.42 (0.19–0.95), respectively, compared with HDL‐C of 40 to 49 mg/dL. However, the significant association for HDL‐C ≥60 mg/dL was not seen after Bonferroni correction. In patients with inflammation, we observed a trend toward increased risk of extended major adverse cardiovascular events in higher HDL‐C groups (HRs [95% CIs], 0.73 [0.37–1.43], 1.24 [0.59–2.61], and 1.56 [0.71–3.45], respectively), but without statistical significance.

Conclusions

The association between HDL‐C level and adverse cardiovascular outcomes showed reverse trends based on inflammation status in Korean patients with chronic kidney disease.

Registration

URL: https://www.clinicaltrials.gov; Unique identifier: NCT01630486.

High-Density Lipoproteins in Kidney Disease

Decades of epidemiological studies have established the strong inverse relationship between high-density lipoprotein (HDL)-cholesterol concentration and cardiovascular disease. Recent evidence suggests that HDL particle functions, including anti-inflammatory and antioxidant functions, and cholesterol efflux capacity may be more strongly associated with cardiovascular disease protection than HDL cholesterol concentration. These HDL functions are also relevant in non-cardiovascular diseases, including acute and chronic kidney disease. This review examines our current understanding of the kidneys’ role in HDL metabolism and homeostasis, and the effect of kidney disease on HDL composition and functionality. Additionally, the roles of HDL particles, proteins, and small RNA cargo on kidney cell function and on the development and progression of both acute and chronic kidney disease are examined. The effect of HDL protein modification by reactive dicarbonyls, including malondialdehyde and isolevuglandin, which form adducts with apolipoprotein A-I and impair proper HDL function in kidney disease, is also explored. Finally, the potential to develop targeted therapies that increase HDL concentration or functionality to improve acute or chronic kidney disease outcomes is discussed.

LDL-Cholesterol versus Glucose in Microvascular and Macrovascular Disease

BACKGROUND

The causal relationships between increased concentrations of low density lipoprotein (LDL)-cholesterol and glucose and risk of ischemic heart disease are well established. The causal contributions of LDL-cholesterol and glucose to risk of peripheral micro- and macrovascular diseases are less studied, especially in prediabetic stages and in a general population setting.

CONTENT

This review summarizes the current evidence for a causal contribution of LDL-cholesterol and glucose to risk of a spectrum of peripheral micro- and macrovascular diseases and reviews possible underlying disease mechanisms, including differences between vascular compartments, and finally discusses the clinical implications of these findings, including strategies for prevention and treatment.

SUMMARY

Combined lines of evidence suggest that LDL-cholesterol has a causal effect on risk of peripheral arterial disease and chronic kidney disease, both of which represent manifestations of macrovascular disease due to atherosclerosis and accumulation of LDL particles in the arterial wall. In contrast, there is limited evidence for a causal effect on risk of microvascular disease. Glucose has a causal effect on risk of both micro- and macrovascular disease. However, most evidence is derived from studies of individuals with diabetes. Further studies in normoglycemic and prediabetic individuals are warranted. Overall, LDL-cholesterol-lowering reduces risk of macrovascular disease, while evidence for a reduction in risk of microvascular disease is inconsistent. Glucose-lowering has a beneficial effect on risk of microvascular diseases and on risk of chronic kidney disease and estimated glomerular filtration rate (eGFR) in some studies, while results on risk of peripheral arterial disease are conflicting.

Lipoproteins in chronic kidney disease: from bench to bedside

Chronic kidney disease (CKD) is associated with high cardiovascular risk. CKD patients exhibit a specific lipoprotein pattern termed 'uraemic dyslipidaemia', which is characterized by rather normal low-density lipoprotein cholesterol, low high-density lipoprotein cholesterol, and high triglyceride plasma levels. All three lipoprotein classes are involved in the pathogenesis of CKD-associated cardiovascular diseases (CVDs). Uraemia leads to several modifications of the structure of lipoproteins such as changes of the proteome and the lipidome, post-translational protein modifications (e.g. carbamylation) and accumulation of small-molecular substances within the lipoprotein moieties, which affect their functionality. Lipoproteins from CKD patients interfere with lipid transport and promote inflammation, oxidative stress, endothelial dysfunction as well as other features of atherogenesis, thus contributing to the development of CKD-associated CVD. While, lipid-modifying therapies play an important role in the management of CKD patients, their efficacy is modulated by kidney function. Novel therapeutic agents to prevent the adverse remodelling of lipoproteins in CKD and to improve their functional properties are highly desirable and partially under development.

Association between monocyte count to high-density lipoprotein cholesterol ratio and mortality in patients undergoing peritoneal dialysis

BACKGROUND AND AIMS

Previous studies had demonstrated that elevated monocyte count to high-density lipoprotein cholesterol ratio (MHR), a novel marker of inflammation, was associated with higher cardiovascular events and mortality in patients with pre-dialysis chronic kidney disease, diabetes, and coronary heart disease. However, the association between MHR and mortality in patients undergoing peritoneal dialysis (PD) has received little attention. The aim of this study was to investigate the association between MHR and all-cause and cardiovascular mortality in PD patients.

METHODS AND RESULTS

In this single center retrospective cohort study, PD patients who had catheter insertion in our PD center from January 1, 2006 to December 31, 2016 were enrolled. All patients were divided into three groups according to the tertiles of baseline MHR levels and followed up until December 31, 2018. The associations of MHR levels with all-cause and cardiovascular mortality were assessed by using Cox proportional hazards models. Of 1584 patients, mean age was 46.02 ± 14.65 years, 60.1% were male, and 24.2% had diabetes. The mean MHR level was 0.39 ± 0.23. During a median follow up time of 45.6 (24.6-71.8) months, 349 patients died, and 181 deaths were caused by cardiovascular disease. After adjusting for confounders, the highest MHR tertile was significantly associated with all-cause and cardiovascular mortality with a hazard ratio of 1.43 (95%CI = 1.06-1.93, P = 0.019), 1.54 (95%CI = 1.01-2.35, P = 0.046), respectively.

CONCLUSION

Higher MHR level was an independent risk factor for all-cause and cardiovascular mortality in PD patients.

The causal effects of serum lipids and apolipoproteins on kidney function: multivariable and bidirectional Mendelian-randomization analyses

Background

The causal nature of the observed associations between serum lipids and apolipoproteins and kidney function are unclear.

Methods

Using two-sample and multivariable Mendelian randomization (MR), we examined the causal effects of serum lipids and apolipoproteins on kidney function, indicated by the glomerular-filtration rate estimated using creatinine (eGFRcrea) or cystatin C (eGFRcys) and the urinary albumin-to-creatinine ratio (UACR). We obtained lipid- and apolipoprotein-associated genetic variants from the Global Lipids Genetics Consortium (n = 331 368) and UK Biobank (n = 441 016), respectively, and kidney-function markers from the Trøndelag Health Study (HUNT; n = 69 736) and UK Biobank (n = 464 207). The reverse causal direction was examined using variants associated with kidney-function markers selected from recent genome-wide association studies.

Results

There were no strong associations between genetically predicted lipid and apolipoprotein levels with kidney-function markers. Some, but inconsistent, evidence suggested a weak association of higher genetically predicted atherogenic lipid levels [indicated by low-density lipoprotein cholesterol (LDL-C), triglycerides and apolipoprotein B] with increased eGFR and UACR. For high-density lipoprotein cholesterol (HDL-C), results differed between eGFRcrea and eGFRcys, but neither analysis suggested substantial effects. We found no clear evidence of a reverse causal effect of eGFR on lipid or apolipoprotein traits, but higher UACR was associated with higher LDL-C, triglyceride and apolipoprotein B levels.

Conclusion

Our MR estimates suggest that serum lipid and apolipoprotein levels do not cause substantial changes in kidney function. A possible weak effect of higher atherogenic lipids on increased eGFR and UACR warrants further investigation. Processes leading to higher UACR may lead to more atherogenic lipid levels.

A UGT1A1 variant is associated with serum total bilirubin levels, which are causal for hypertension in African-ancestry individuals

Serum bilirubin is associated with several clinical outcomes, including hypertension, type 2 diabetes (T2D), and drug metabolism. Here, we describe findings from our genome-wide association studies (GWAS) of serum (TBIL) using a generalized linear mixed model in West Africans (n = 1127), with adjustment for age, sex, body mass index, T2D, significant principal components of population structure, and cryptic relatedness. Genome-wide conditional analysis and CAVIARBF were used to fine map significant loci. The causal effect of TBIL on hypertension was assessed by Mendelian randomization (MR) using the GWAS findings as instrumental variables (IVs) in African Americans (n = 3,067). The SNP rs887829 (UGT1A1) was significantly associated with TBIL levels (effect allele (T) frequency = 0.49, β (SE) = 0.59 (0.04), p = 9.13 × 10^-54). Genome-wide conditional analysis and regional fine mapping pointed to rs887829 as a possible causal variant with a posterior inclusion probability of 0.99. The T allele of rs887829 is associated with lower hepatic expression of UGT1A1. Using rs887829 as an IV, two-stage least-squares MR showed a causal effect of bilirubin on hypertension (β = -0.76, 95% CI [-1.52, -0.01], p = 0.0459). Our finding confirms that UGT1A1 influences bilirubin levels. Notably, lower TBIL is causally associated with the increased risk of hypertension.

Health improvement framework for actionable treatment planning using a surrogate Bayesian model

Clinical decision-making regarding treatments based on personal characteristics leads to effective health improvements. Machine learning (ML) has been the primary concern of diagnosis support according to comprehensive patient information. A prominent issue is the development of objective treatment processes in clinical situations. This study proposes a framework to plan treatment processes in a data-driven manner. A key point of the framework is the evaluation of the actionability for personal health improvements by using a surrogate Bayesian model in addition to a high-performance nonlinear ML model. We first evaluate the framework from the viewpoint of its methodology using a synthetic dataset. Subsequently, the framework is applied to an actual health checkup dataset comprising data from 3132 participants, to lower systolic blood pressure and risk of chronic kidney disease at the individual level. We confirm that the computed treatment processes are actionable and consistent with clinical knowledge for improving these values. We also show that the improvement processes presented by the framework can be clinically informative. These results demonstrate that our framework can contribute toward decision-making in the medical field, providing clinicians with deeper insights.

Association of High-Density Lipoprotein Cholesterol With GFR Decline in a General Nondiabetic Population

Introduction

Although lower high-density lipoprotein cholesterol (HDL-C) levels are considered a risk factor for cardiovascular disease (CVD), experimental evidence suggest that aging, inflammation, and oxidative stress may remodel HDL-C, leading to dysfunctional HDL-C. Population studies on HDL-C and loss of the glomerular filtration rate (GFR) reported inconsistent results, but they used inaccurate estimates of the GFR and may have been confounded by comorbidity.

Methods

We investigated the association of HDL-C levels with risk of GFR loss in a general population cohort; the participants were aged 50-62 years and did not have diabetes, CVD, or chronic kidney disease (CKD) at baseline. The GFR was measured using iohexol-clearance at baseline (n=1627) and at the follow-up (n=1324) after a median of 5.6 years. We also investigated any possible effect modification by low-grade inflammation, physical activity, and sex.

Results

Higher HDL-C levels were associated with steeper GFR decline rates and increased risk of rapid GFR decline (>3 ml/min per 1.73 m² per year) in multivariable adjusted linear mixed models and logistic regression (-0.64 ml/min per 1.73 m² per year [95% CI -0.99, -0.29; P < 0.001] and odds ratio 2.7 [95% CI 1.4, 5.2; P < 0.001] per doubling in HDL-C). Effect modifications indicated a stronger association between high HDL-C and GFR loss in physically inactive persons, those with low-grade inflammation, and men.

Conclusion

Higher HDL-C levels were independently associated with accelerated GFR loss in a general middle-aged nondiabetic population.

Factors predicting decline in renal function and kidney volume growth in autosomal dominant polycystic kidney disease: a prospective cohort study (Japanese Polycystic Kidney Disease registry: J-PKD)

BACKGROUND

Factors affecting decline in renal function and cyst growth in patients with autosomal polycystic kidney disease (ADPKD) are not fully described, particularly in Japan.

METHODS

This was the first multi-facility, prospective, observational cohort study conducted in ADPKD patients at 14 centers in Japan. Patients in the J-PKD registry were assessed from December 2009 to June 2012 (follow-up until June 2017). Patients' data including estimated glomerular filtration rate (eGFR) and total kidney volume (TKV) were assessed initially and a maximum of five times annually. Contributing factors to eGFR decline and TKV growth were identified using multiple linear regression analysis.

RESULTS

Of the 340 patients in the J-PKD registry, data analysis was performed for 192 patients in whom serial changes for both eGFR and TKV were obtained. eGFR slope, eGFR change, and TKV change values were as follows: - 2.7 (- 4.2 to - 1.5) (ml/min/1.73 m²/year), - 5.0 (- 9.6 to - 2.3) (%/year), and 4.78 (0.86-8.22) (%/year), respectively. Lower high-density lipoprotein (HDL) cholesterol was an independent predictor of eGFR decline, using both eGFR slope and change (P = 0.04, P = 0.02, respectively), whereas lower hemoglobin and higher uric acid were significantly associated with greater eGFR change only (P = 0.02, P = 0.002, respectively). Younger age and higher fasting blood sugar were independent predictors of greater TKV change (P = 0.01, P = 0.02, respectively).

CONCLUSIONS

This real-world study in Japan identified risk factors for renal function decline in ADPKD patients. These included lower HDL cholesterol, lower hemoglobin and higher uric acid for eGFR decline, and youth and higher blood sugar levels for TKV growth.

Curcumin analogue C66 attenuates obesity-induced renal injury by inhibiting chronic inflammation

Obesity has been recognized as a major risk factor for the development of chronic kidney disease, which is accompanied by increased renal inflammation, fibrosis, and apoptosis. C66 is a curcumin derivative that exerts anti-inflammatory effects by inhibiting the JNK pathway and prevents diabetic nephropathy. The present study investigates the possible protective effect of C66 on high-fat diet (HFD)-induced obesity-related glomerulopathy. Mice were fed with HFD for 8 weeks while some were treated with C66 every 2 days for 11 weeks. The HFD-fed mice developed renal dysfunction, as well as elevated triglyceride and cholesterol. Kidneys of the HFD-fed mice showed marked glomerular injuries, apoptosis, and inflammation with markedly increased cytokine production. Interestingly, treating HFD-fed mice with C66 remarkably reversed these pathological changes via inhibiting inflammation and NF-κB/JNK activation. In cultured mesangial cells, Palmitic Acid was able to activate the pro-fibrotic mechanisms, apoptosis, inflammatory response, and NF-κB and JNK signaling pathways, all of which could be attenuated by C66 treatment. In all, we demonstrated that curcumin analogue C66 attenuates obesity-induced renal injury by inhibiting chronic inflammation and apoptosis via targeting NF-κB and JNK. Our data suggest that C66 can be potentially used to prevent obesity-associated renal diseases warranting future investigations.

Causal effect between total cholesterol and HDL cholesterol as risk factors for chronic kidney disease: a mendelian randomization study

Background

While observational studies show an association between serum lipid levels and cardiovascular disease (CVD), intervention studies that examine the preventive effects of serum lipid levels on the development of CKD are lacking.

Methods

To estimate the role of serum lipid levels in the etiology of CKD, we conducted a two-sample mendelian randomization (MR) study on serum lipid levels. Single nucleotide polymorphisms (SNPs), which were significantly associated genome-wide with serum lipid levels from the GLGC and CKDGen consortium genome-wide association study (GWAS), including total cholesterol (TC, n = 187,365), triglyceride (TG, n = 177,861), HDL cholesterol (HDL-C, n = 187,167), LDL cholesterol (LDL-C, n = 173,082), apolipoprotein A1 (ApoA1, n = 20,687), apolipoprotein B (ApoB, n = 20,690) and CKD (n = 117,165), were used as instrumental variables. None of the lipid-related SNPs was associated with CKD (all P > 0.05).

Results

MR analysis genetically predicted the causal effect between TC/HDL-C and CKD. The odds ratio (OR) and 95% confidence interval (CI) of TC within CKD was 0.756 (0.579 to 0.933) (P = 0.002), and HDL-C was 0.85 (0.687 to 1.012) (P = 0.049). No causal effects between TG, LDL-C- ApoA1, ApoB and CKD were observed. Sensitivity analyses confirmed that TC and HDL-C were significantly associated with CKD.

Conclusions

The findings from this MR study indicate causal effects between TC, HDL-C and CKD. Decreased TC and elevated HDL-C may reduce the incidence of CKD but need to be further confirmed by using a genetic and environmental approach.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12882-020-02228-3.

Acute kidney injury leading to CKD is associated with a persistence of metabolic dysfunction and hypertriglyceridemia

Fibrosis is the pathophysiological hallmark of progressive chronic kidney disease (CKD). The kidney is a highly metabolically active organ, and it has been suggested that disruption in its metabolism leads to renal fibrosis. We developed a longitudinal mouse model of acute kidney injury leading to CKD and an in vitro model of epithelial to mesenchymal transition to study changes in metabolism, inflammation, and fibrosis. Using transcriptomics, metabolic modeling, and serum metabolomics, we observed sustained fatty acid metabolic dysfunction in the mouse model from early to late stages of CKD. Increased fatty acid biosynthesis and downregulation of catabolic pathways for triglycerides and diacylglycerides were associated with a marked increase in these lipids in the serum. We therefore suggest that the kidney may be the source of the abnormal lipid profile seen in patients with CKD, which may provide insights into the association between CKD and cardiovascular disease.

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Following AKI, markers of fibrosis and inflammation go up simultaneously

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AKI is associated with reduced fatty acid oxidation and oxidative phosphorylation

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Changes in metabolism persist as chronic kidney disease develops

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Changes in metabolism are associated with increased serum levels of triglycerides

Combined Effects of Dyslipidemia and High Adiposity on the Estimated Glomerular Filtration Rate in a Middle-Aged Chinese Population

BACKGROUND

Some studies have reported that chronic kidney disease (CKD) or the estimated glomerular filtration rate (eGFR) is significantly associated with metabolic abnormalities.

METHODS

Six hundred forty-six community residents aged 45-60 years without overt renal dysfunction were recruited in this cross-sectional study. eGFR was estimated by serum creatinine measurement. The visceral fat area (VFA) and subcutaneous fat area (SFA) were assessed by magnetic resonance imaging (MRI). The body mass index (BMI) and waist-hip ratio (WHR) were also evaluated. Additionally, we tested the subjects' blood lipid levels to diagnose dyslipidemia.

RESULTS

Compared with the subjects with neither dyslipidemia nor obesity, men with both dyslipidemia and high obesity indices, such as BMI, WHR and VFA, showed a significantly lower mean eGFR; women with dyslipidemia with high WHR, VFA or SFA also showed a significantly lower mean eGFR. Although an independent association between the metabolic variables and eGFR was not found except for BMI, some of the combined effects of each variable were related to eGFR decline. Comorbidity of dyslipidemia and high WHR was significant risk factor for eGFR reduction (β -8.805, SD 4.116, p < 0.05). Additionally, comorbidity of dyslipidemia and high obesity indices such as BMI (β -12.942, SD 5.268, p < 0.05) and VFA (β -7.069, SD 3.394, p < 0.05) were significant risk factors for eGFR reduction in men.

CONCLUSION

The combined effect of dyslipidemia and high obesity indices is significantly related to the decline in eGFR. The association is more profound in men.

Novel Insights From Human Studies on the Role of High-Density Lipoprotein in Mortality and Noncardiovascular Disease

The vast majority of research about HDL (high-density lipoprotein) has for decades revolved around the possible role of HDL in atherosclerosis and its therapeutic potential within cardiovascular disease prevention; however, failures with therapies aimed at increasing HDL cholesterol has left questions as to what the role and function of HDL in human health and disease is. Recent observational studies have further shown that extreme high HDL cholesterol is associated with high mortality leading to speculations that HDL could in some instances be harmful. In addition, evidence from observational, and to a lesser extent genetic studies has emerged indicating that HDL might be associated with the development of other major noncardiovascular diseases, such as infectious disease, autoimmune disease, cancer, type 2 diabetes, kidney disease, and lung disease. In this review, we discuss (1) the association between extreme high HDL cholesterol and mortality and (2) the emerging human evidence linking HDL to several major diseases outside the realm of cardiovascular disease.

Usefulness of atherogenic index of plasma for estimating reduced eGFR risk: insights from the national health and nutrition examination survey

AIMS

Previous studies have identified Atherogenic index of plasma (AIP) as a simple measure of atherosclerosis. Because atherosclerosis plays a role in the development of renal damage, our study aims to evaluate the effect of AIP on the risk of reduced eGFR and assess its usefulness to refine the risk stratification of reduced estimated glomerular filtration rate (eGFR).

METHODS

Our study included 15,836 participants from the National Health and Nutritional Survey (NHANES) 2009-2016. Association was investigated by logistic regression. AIP was calculated as log (triglycerides/high-density lipoprotein cholesterol). Reduced eGFR was determined as eGFR < 60 ml/min per 1.73 m*2.

RESULTS

The prevalence of reduced eGFR was 8.01%. In the full model, each SD increase of AIP leaded to 27.4% additional risk for reduced eGFR. After dividing AIP into quartiles, the fourth quartile had a 1.649 times risk than the first quartile. Moreover, smooth curve fitting suggested that the risk of reduced eGFR elevated linearly with the increase of AIP. Subgroup analysis demonstrated that the association between AIP and reduced eGFR was robust in sex, body mass index, hypertension, and diabetes subpopulation, but the association was significantly stronger in black race and people aged less than 50 years old. Additionally, AUC displayed an advancement when introducing AIP into established risk factors (0.875 cs. 0.897, P < 0.001), category-free net reclassification index (0.249, 95% CI: 0.192-0.306, P < 0.001) and integrated discrimination index (0.007, 95% CI: 0.004-0.009, P < 0.001) also suggested the improvement from AIP.

CONCLUSION

The present work suggested a linear association between AIP and reduced eGFR. Furthermore, the results showed that the association was stronger in black race and people aged less than 50 years old. Most importantly, our work implicated the usefulness of AIP to refine the risk stratification of reduced eGFR.

Sex-specific associations of insulin resistance with chronic kidney disease and kidney function: a bi-directional Mendelian randomisation study

AIMS/HYPOTHESIS

Reasons for the sexual disparity in chronic kidney disease (CKD) are unclear. To provide insight we contextualised these differences within evolutionary biology, and explored sex-specific effects of insulin resistance because it may have sex-specific effects on the reproductive axis. Impaired kidney function may also cause insulin resistance. We assessed these possibilities using bi-directional, sex-specific, two-sample Mendelian randomisation (MR).

METHODS

Given that fasting insulin, fasting glucose and HbA_1c are related, we used MR-Bayesian model averaging (MR-BMA) to identify the best-fitting model and most influential exposure. Genetic associations with glycaemic traits were obtained from genome-wide association studies (GWAS) in Europeans without diabetes (n = 108,557 for fasting insulin, as a proxy for insulin resistance, and for fasting glucose, n = 123,665 for HbA_1c in the Meta-Analyses of Glucose and Insulin-related traits Consortium [MAGIC]), and applied to GWAS of 480,698 Europeans for overall associations with CKD (cases n = 41,395) and eGFR. We also used sex-specific individual information in white British (179,917 men, 6016 CKD cases; 212,079 women, 5958 CKD cases) from the UK Biobank. Univariable or multivariable MR was used to assess the role of glycaemic trait(s) selected by MR-BMA in CKD and kidney function. Genetic variants predicting eGFR were used to assess the role of kidney function in the most influential exposure(s).

RESULTS

Fasting insulin was selected as the most likely exposure by both overall and sex-specific MR-BMA. It increased CKD in men (OR 7.23 per pmol/l higher fasting insulin [95% CI 2.46, 21.2]) but not in women (OR 1.05 [95% CI 0.21, 5.21]), and reduced eGFR in men (-0.04 [95% CI -0.07, -0.01]) but not in women (0.01 [95% CI -0.02, 0.03]). Genetically predicted eGFR was unrelated to fasting insulin.

CONCLUSIONS/INTERPRETATION

Genetically predicted fasting insulin was sex-specifically associated with CKD and unhealthier kidney function but was not affected by kidney function. Graphical abstract.

Association Between Serum High-Density Lipoprotein Cholesterol Levels and Progression of Chronic Kidney Disease: Results From the KNOW-CKD

Background High-density lipoprotein cholesterol ( HDL -C) levels are generally decreased in patients with chronic kidney disease ( CKD ). However, studies on the relationship between HDL -C and CKD progression are scarce. Methods and Results We studied the association between serum HDL -C levels and the risk of CKD progression in 2168 participants of the KNOW - CKD (Korean Cohort Study for Outcome in Patients With Chronic Kidney Disease). The primary outcome was the composite of a 50% decline in estimated glomerular filtration rate from baseline or end-stage renal disease. The secondary outcome was the onset of end-stage renal disease. During a median follow-up of 3.1 (interquartile range, 1.6-4.5) years, the primary outcome occurred in 335 patients (15.5%). In a fully adjusted Cox model, the lowest category with HDL -C of <30 mg/dL (hazard ratio, 2.21; 95% CI, 1.30-3.77) and the highest category with HDL -C of ≥60 mg/dL (hazard ratio, 2.05; 95% CI , 1.35-3.10) were associated with a significantly higher risk of the composite renal outcome, compared with the reference category with HDL -C of 50 to 59 mg/dL. This association remained unaltered in a time-varying Cox analysis. In addition, a fully adjusted cubic spline model with HDL -C being treated as a continuous variable yielded similar results. Furthermore, consistent findings were obtained in a secondary outcome analysis for the development of end-stage renal disease. Conclusions A U-shaped association was observed between serum HDL -C levels and adverse renal outcomes in this large cohort of patients with CKD . Our findings suggest that both low and high serum HDL -C levels may be detrimental to patients with nondialysis CKD .