Plasma branched-chain amino acids in chronic kidney disease: Associations with atherogenic lipids and mortality

doi:10.21203/rs.3.rs-7849136/v1

Background

Branched-chain amino acids (BCAAs) are essential nutrients that promote muscle protein anabolism but also associate with cardiometabolic diseases; however, their role in chronic kidney disease (CKD) remains unclear. We investigated plasma BCAA levels and their associations with metabolic parameters and survival in CKD patients.

Methods

Plasma BCAA levels, along with clinical and laboratory parameters, were measured in 328 patients with CKD stage 5 (median age 54 years, 60% males). BCAA concentrations in 83 healthy individuals (median age 51 years, 66% males) served as comparators. Multivariate linear regression analysis was employed to identify predictors of BCAA levels. Competing risk regression analysis was conducted to assess 5-year risk of all-cause and cardiovascular mortality in relation to total and individual BCAAs (valine, isoleucine, and leucine).

Results

Plasma BCAA levels were lower compared to healthy individuals (P < 0.0001) and positively associated with triglycerides and the atherogenic index of plasma, while inversely associated with high density lipoprotein-cholesterol (HDL-C), Apo-A, and Lp (a). After adjustments for confounders, low vs. high tertile of total BCAAs associated with increased risk of cardiovascular mortality (sub-hazard ratio [sHR] 2.37, 95% confidence interval [CI], 1.08–5.21) and low tertile of valine associated with higher risk of both all-cause mortality (sHR 2.05, 95% CI 1.10–3.79) and cardiovascular mortality (sHR 2.46, 95% CI 1.15–5.26).

Conclusion

In CKD, higher levels of BCAAs associated with an atherogenic lipid profile while lower BCAAs levels associated with increased cardiovascular mortality risk, and low valine was associated with higher both all-cause and cardiovascular mortality risk. Monitoring and potentially modulating BCAA levels could have prognostic or therapeutic implications in advanced CKD.

Branched-chain amino acids

lipid profile

inflammation

chronic kidney disease

mortality

Branched-chain amino acids (BCAAs), which include leucine (Leu), isoleucine (Ile), and valine (Val), are essential amino acids that play a crucial role in muscle protein synthesis and energy production. Beyond serving as substrates for protein synthesis, BCAAs act as signaling molecules, stimulating protein synthesis and regulating glucose and lipid metabolism, neurotransmitter and hormone synthesis, and mitochondrial biogenesis, and they have key roles for intestinal health and immunity ^{1, 2}.

On the other hand, high plasma BCAAs concentrations are closely associated with presence and severity of cardiometabolic alterations such as insulin resistance, metabolic syndrome, diabetes mellitus (DM), and obesity, as well as cardiovascular disease (CVD) ³. Adipose tissue, a dynamic organ essential for glucose and lipid metabolism, also influences BCAA balance through nutrient storage and lipolysis ⁴. Moreover, associations between BCAAs and metabolic dyslipidemia have been reported and several studies have explored the connections between BCAAs and the lipid profile ^5–10. Indeed, recent studies in the general population show that high levels of BCAAs are associated with elevated triglycerides (TG) and reduced high density lipoprotein-cholesterol (HDL-C) levels ^5–8. Whereas the connection between BCAAs and the lipid profile is not completely clear, it has been suggested that it is partially mediated by insulin resistance, a common feature in individuals with elevated BCAAs levels, which associates with increased lipolysis and reduced clearance of circulating lipids, contributing to dyslipidemia ¹¹. The finding of a significant association between BCAAs and insulin resistance suggests that BCAAs may play a major role in the modulation of insulin action ¹². Circulating levels of the BCAAs are significantly higher in obese individuals compared to lean ones ¹³ and BCAAs have been established as some of the most robust biomarkers for a range of cardiometabolic conditions, including obesity, insulin resistance, type 2 DM, and CVD ¹⁴. Furthermore, genetic variants linked to dyslipidemia and insulin resistance have been associated with increased concentrations of circulating BCAAs, suggesting that obesity and insulin resistance may drive the obesity-related rise in BCAAs ¹⁵.

Chronic kidney disease (CKD) patients often exhibit insulin resistance and dyslipidemia, along with disturbances in amino acid metabolism, particularly involving BCAAs ¹⁶. Patients with advanced CKD show decreased levels of plasma and intracellular BCAAs ^16–21, likely due to impaired kidney amino acid metabolism and metabolic changes such as acidosis, and malnutrition ^{16, 22} and often present with elevated levels of TG and low-density lipoprotein cholesterol (LDL-C), decreased HDL-C levels, and altered lipoprotein composition.

Whereas links between BCAAs and lipoproteins have been reported in the general population, the existence of such a linkage in CKD patients has to the best of our knowledge not yet been explored. Therefore, in the present study, we evaluated associations between plasma BCAA concentrations and serum cholesterol, TG, HDL-C, and LDL-C, and estimated the risk of atherogenic dyslipidemia in relation to plasma BCAA levels, in patients with advanced CKD. We used the atherogenic index of plasma (AIP), reflecting the TG to HDL-C ratio, as a biomarker for atherogenic dyslipidemia ²³. By considering two atherogenic lipid parameters, AIP provides insights into an individual's risk of atherosclerosis.

While high plasma concentrations of BCAAs may be linked to cardiometabolic diseases, low circulating levels of essential nutrients such as BCAAs could potentially have a negative effect on survival. However, the association between BCAAs and mortality risk in CKD remains unclear and has not been conclusively determined. Therefore, we investigated these associations to gain a better understanding of possible links between plasma BCAA concentrations, atherogenic lipids, and clinical outcomes in CKD patients.

Study populations

This is a post hoc analysis of a cross-sectional study with follow-up data of mortality in a cohort of patients with CKD stage 5 ²⁴ (Figure S1). The study conformed to and was conducted in accordance with the STROBE (Strengthening the Reporting of Observational Studies in Epidemiology) guidelines ²⁵. The patients, who were recruited between December 1994 and April 2014, were investigated close to the start of dialysis treatment and were followed for up to five years. Exclusion criteria included age younger than 18 or older than 70 years, signs of overt infection, acute vasculitis, unwillingness to participate, and, for this study, missing BCAA measurement. Of 560 patients included in the cohort, 328 patients (198 (60%) males, median age 54 years, and median estimated glomerular filtration rate (eGFR) 6.3 ml/min per 1.73 m²) met the study criteria and were included in the current analyses, see Table 1. The causes of CKD were diabetic nephropathy (26%), hypertension and kidney vascular disease (21%), chronic glomerulonephritis (25%), and other causes (28%). Most patients (85%) were on antihypertensive medications, 59 (18%) patients were prescribed statins and other commonly used drugs in kidney failure such as erythropoietin, phosphate binders and potassium binders, and 61 (19%) patients received an oral amino acid supplementation.

Data on BCAAs of 83 healthy subjects (66% males, median age 51 (range 21-80) years) served as comparator for BCAAs in the patient cohort (Supplementary material, Table S1).

Informed written consent was obtained from each patient and control subject. The protocol of this study was approved by the Ethics Committee of the Karolinska Institute (EPN) at the Karolinska University Hospital Huddinge, Stockholm, Sweden. The study was conducted in adherence to the Declaration of Helsinki.

Methods

After an overnight fast, venous blood samples were taken for analysis. Plasma and serum were separated and kept frozen at −70^◦C if not analyzed immediately. Plasma amino acids including BCAAs (Leu, Ile and Val) were measured by reversed-phase high-performance liquid chromatography (HPLC) with fluorometric detection as previously described ²⁶.

Serum cholesterol, HDL-C and TG were analyzed by standard enzymatic procedures (Boehringer Mannheim, Mannheim, Germany). High-sensitivity C-reactive protein (hsCRP) was measured by the nephelometry method. Interleukin-6 (IL-6) was measured with ELISA commercial kits (Roche Diagnostics GmbH, Penzberg, Germany). The remaining biochemical analyses were done using routine methods at Karolinska University Hospital at Huddinge. Glomerular filtration rate (GFR) was assessed in the CKD patients as an estimated GFR (eGFR) from serum creatinine levels. Atherogenic index of plasma (AIP) was calculated as the logarithmically transformed ratio of the serum TG to high-density lipoprotein cholesterol (HDL-C) as described in ²⁷: . Homeostatic Model Assessment of Insulin Resistance (HOMA-IR) was calculated based on the following equation: Fasting insulin in μU/mL)×fasting glucose in mmol/L) / 22.5. Body mass index (BMI) was calculated as the subject’s body weight in kilograms divided by the square of the subject’s height in meters (kg/m²).

Outcome ascertainment

Survival among the 328 CKD stage 5 patients was measured from the day of examination until death or censoring for kidney transplantation or when they completed the 5-year follow-up period. No patients were lost to follow-up. The median follow-up period was 29.4 (range 0.9–60) months. Within the 5-year follow-up period, 82 patients (25%) died, of which 52 (63%) were cardiovascular deaths, and 166 patients (51%) underwent transplantation. Cardiovascular deaths were attributed to ischemic heart disease, heart failure, ischemic stroke, peripheral vascular disease, or hemorrhagic stroke.

Statistical analysis

Data are expressed as number (percentage) or median (interquartile range, IQR). Statistical significance was set at the level of P < 0.05. Comparisons between two groups were assessed with the non-parametric Wilcoxon test for continuous variables and Chi-square test (χ²) for nominal variables. When comparing more than two groups we applied the non-parametric Kruskal-Walli’s test for continuous variables and χ²test for nominal variables. Non-parametric Spearman rank correlation analysis was used to determine associations between variables. Multivariate linear regression analysis with stepwise backward selection of variables was used to determine the predictors of total and individual BCAAs.

Restricted cubic spline curve analysis was performed to assess the associations between total BCAA and valine concentrations (as continuous variables) and the risk of all-cause mortality and cardiovascular mortality. Fine-Gray competing-risk regression analysis models with kidney transplantation as a competing risk were used to estimate the sub-distribution hazard ratio (sHR) with 95% confidence interval (95% CI) to quantify the association of total and individual BCAAs, expressed as tertiles, with mortality risk. Statistical analyses were performed using statistical software Stata Now 18.5 (Stata Corporation, College Station, TX, USA) and Statistical Analysis Systems (SAS) SAS 9.4 level 1 M8 (SAS Campus Drive, Cary, NC, USA).

Characteristics of the CKD patients

A total of 328 CKD patients (198 males and 130 females) with a median (IQR) age of 54 (43 – 63) years were included in the study (Table 1). Their median eGFR was 6.3 (4.9 – 7.9) ml/min/1.73 m², 104 (32%) had DM and 111 (34%) had CVD. Moreover, Table 1 shows glucose-related parameters, plasma lipid profile including AIP, and total and individual BCAAs, for all patients and when patients are divided into tertiles of total BCAAs.

BCAAs in patients and controls

Plasma concentrations of total (T-BCAA) and individual BCAAs were significantly lower in CKD patients compared to healthy controls (Fig. 1 and Table S1), except for Ile, for which the difference did not reach statistical significance.

BCAAs in different CKD patient groups

The plasma concentrations of T-BCAA (Fig. S2) and the three individual BCAAs (Table S2) were higher (all p<0.0001) in male patients compared to female patients. Similarly, plasma concentrations of total BCAAs (T-BCAA) and the three individual BCAAs were significantly higher in healthy males compared to healthy females (Fig. S3). However, the plasma BCAA concentrations did not differ significantly between CKD patients with and without DM, CVD, and statin treatment, respectively (Fig. S2). Moreover, the concentrations of BCAAs did not differ significantly between 61 patients (19%) who received amino acid supplementation and those who did not (Table S3).

Associations of BCAAs with lipid profile

The individual BCAAs were strongly correlated with each other and with lipid components (Table 2). TG was positively and significantly correlated with T-BCAA and Val. Moreover, HDL-C was negatively and significantly correlated with T-BCAA, Val, Ile, and Leu. Similarly, AIP, Lp(a), and Apo-A were negatively and significantly correlated with T-BCAA, Val, and Ile, but not with Leu. Serum cholesterol, LDL-C, and Apo-B did not show significant associations with T-BCAA or individual BCAAs.

To further explore links between AIP and BCAAs, we divided the patients into AIP tertiles and compared the concentration of T-BCAA and individual BCAAs between the AIP tertiles. The high AIP tertile had significantly higher levels of T-BCAA, Val and Ile, but not Leu, compared to the low tertile (Fig. 2).

The association between BCAAs and atherogenic lipids was further investigated by multivariate linear regression analysis to determine variables independently associated with BCAAs (Table 3). In a model including age, sex, DM, CVD, BMI, AIP and plasma insulin, higher AIP, higher plasma insulin and male sex emerged as independent predictors of plasma T-BCAA concentration, whereas age, DM and BMI were not significantly associated with T-BCAA.

Associations of BCAA with glucose-related factors and inflammatory biomarkers

As shown in Table 4, blood glucose, plasma insulin and HOMA-IR were positively and significantly correlated with T-BCAA and Val, and HbA1c was inversely and significantly correlated with Leu.

TNF-α correlated inversely with T-BCAA, Val, and Leu (Table 4). Other inflammatory markers such as WBC, hsCRP, IL-6, IL-10, IL-18, ICAM-1, VCAM-1, and 8-OHdG were not significantly correlated with the concentrations of BCAAs.

BCAAs and mortality

The associations of low and middle tertiles vs. high tertile of T-BCAA and individual BCAAs with cardiovascular and all-cause mortality were investigated using competing-risk regression analysis models, adjusted for age, sex, DM, CVD, eGFR, BMI, AIP, serum albumin and plasma insulin (Fig 3 and Table S4). The low T-BCAA tertile was associated with increased risk of cardiovascular mortality (sub-hazard ratio [sHR] 2.37, 95% confidence interval [CI], 1.08 - 5.21) and the low tertile of valine was associated with higher risk of both all-cause mortality (sHR 2.05, 95% CI 1.10–3.79) and cardiovascular mortality (sHR 2.46, 95% CI 1.15–5.26).

Restricted cubic spline curve analysis showed that lower plasma concentrations of T-BCAA and Val, as continuous variables, were associated with increased 5-year all-cause and cardiovascular mortality risk (Fig. 4).

Our study provides several important insights into the complex relationship between BCAAs, atherogenic lipids and mortality risk in patients with advanced CKD. Their plasma concentrations of BCAAs, which were lower than in healthy individuals, were inversely associated with increased cardiovascular mortality, and lower Val concentration was associated with increased both all-cause and cardiovascular mortality risk. Finally, higher plasma BCAA levels were positively associated with TG and AIP, and inversely associated with HDL-C, Apo-A, and Lp(a).

BCAAs in different CKD groups

During CKD, abnormalities in BCAA metabolism occur due to the reduced kidney contribution to amino acid metabolism, compounded by declining kidney function and the accumulation of uremic toxins, which disrupt whole body nitrogen metabolism. Previous studies have demonstrated that patients with advanced CKD, including those undergoing hemodialysis (HD) or peritoneal dialysis, exhibit reduced levels of essential amino acids, including BCAAs ^{18, 19, 21, 28}. In our study, BCAA levels were significantly lower in the CKD patients compared to a group of healthy individuals. The precise cause of lower BCAA levels in CKD remains unclear. It is plausible that the combination of impaired kidney amino acid metabolism, effects of uremic toxins, nutritional deficits, muscle wasting, metabolic stress, inflammation, and the process of adapting to kidney failure all contribute to the lower plasma amino acid concentrations.

Our findings also revealed strong intercorrelations among plasma concentrations of BCAAs in CKD patients, consistent with findings by Ikeda et al. ²⁸ in both HD patients and healthy older individuals and by Luo et al. ²⁹ in patients with hypertension-attributed CKD. These observations support previous explanations that attributed the strong correlation among BCAAs to shared metabolic enzymes ³⁰.

Furthermore, in CKD patients and in healthy controls, BCAA concentrations were significantly higher in males compared to females, consistent with previous findings in HD patients and healthy individuals ²⁸. The higher levels of BCAAs in males may be attributed to differences in muscle mass, hormone status, and body fat distribution, all of which affect amino acid metabolism differently between sexes.

Many studies have reported a close association between elevated BCAA levels and the development of insulin resistance, DM, and hypertension ^31–33. However, the concentrations of BCAAs in CKD patients with DM or hypertension in our study did not significantly differ from those without these conditions. We did observe, however, significant associations between BCAA levels and both blood glucose and plasma insulin concentrations, suggesting a link between BCAAs and glucose regulation.. Although there was a trend towards a positive association with HbA1c, it did not reach statistical significance, except for leucine, which showed a significant association with HbA1c. This suggests that BCAAs may play a role in metabolic processes related to glucose and insulin regulation, although the precise nature of these relationships requires further investigation.

Associations BCAAs with lipid profile

A novel and intriguing finding in our study is the specific correlation between BCAA levels and lipid profiles. To our knowledge, this is the first study to examine the association between plasma BCAA concentrations and the circulating lipid profile in CKD patients. Although BCAA levels in our cohort were lower than those typically observed in healthy individuals, they were still positively associated with atherogenic lipids, as indicated by the Atherogenic Index of Plasma (AIP), a composite biomarker derived from the ratio of TG to HDL-C. Consistent with previous studies in non-kidney disease populations ^5–8, we found that BCAA concentrations were significantly positively correlated with TG and AIP, and negatively correlated with HDL-C, Apo-A, and Lp (a). Interestingly, no significant correlation was observed between BCAA levels and total cholesterol or LDL-C concentrations.

BCAAs are crucial in protein synthesis and energy metabolism and have been shown to regulate both glucose and lipid metabolism ¹. The interaction between BCAAs and lipids involves complex metabolic pathways, where BCAAs influence enzymes and signalling pathways critical for lipid synthesis and breakdown ^{1, 34}. Although BCAAs are primarily metabolized in skeletal muscle, their catabolism is linked to the production of acyl-CoA intermediates that can enter lipid synthesis pathways ³⁵, potentially leading to increased production of specific lipids. Low BCAA levels, as in CKD, may impair the regulation of these pathways, resulting in lipid accumulation in the bloodstream. Additionally, BCAAs may influence lipid transport by affecting lipoprotein levels, including those responsible for carrying cholesterol and triglycerides ³⁶. This interaction may contribute to dyslipidemia, further highlighting the complex role of BCAAs in lipid metabolism and cardiovascular risk. In CKD patients, the combination of dysregulated lipid metabolism and low BCAA levels may create a perfect storm for increased cardiovascular risk. This occurs through mechanisms including the promotion of atherogenesis, enhanced insulin resistance, chronic inflammation, oxidative stress, muscle wasting, and endothelial dysfunction ³⁷.

Associations of BCAAs with glucose-related factors

Many studies have reported a close association between elevated BCAA levels and the development of insulin resistance, DM, and hypertension ^31–33. However, in our study, BCAA concentrations in CKD patients with DM or hypertension did not significantly differ from those without these conditions. Insulin resistance is a common and early feature of kidney failure, regardless of diabetes status. In this study, we observed significant associations between BCAA levels and both blood glucose and plasma insulin concentrations, suggesting a potential link between BCAAs and glucose regulation. Moreover, the HOMA-IR was positively and significantly correlated with T-BCAA and valine concentrations. These findings imply that BCAAs may play a role in metabolic processes related to glucose and insulin regulation, although the precise nature of these relationships warrants further investigation. It is important to consider that the nature and direction of these associations may differ in individuals with CKD compared to those without. Notably, metabolomics work by Newgard et al. ^{11, 13, 14} reported strong associations between elevated circulating BCAA levels and the development of insulin resistance, type 2 diabetes mellitus, and related metabolic disorders. Their study demonstrated that a metabolic signature characterized by increased BCAAs and related metabolites was closely linked to insulin resistance and impaired glucose metabolism, suggesting a contributory role of BCAAs in the pathogenesis of metabolic disease. Further research is needed to elucidate the mechanisms through which BCAAs influence glucose homeostasis in CKD and to determine how these pathways may differ from those established in non-CKD populations.

Associations of BCAAs with inflammatory markers

Our study did not find significant associations between total or individual BCAAs and inflammatory markers such as CRP or IL-6. However, there was a significant negative association between TNF-α and total BCAAs, Val, and Ile, but not Leu. Inflammatory cytokines like TNF-α and IL-6 modulate BCAA metabolism and are key mediators of muscle protein breakdown, altering circulating amino acid levels, including BCAAs. TNF-α, in particular, promotes muscle protein catabolism via the ubiquitin-proteasome pathway, contributing to elevated BCAA levels and systemic metabolic disturbances ³⁸. TNF-α, IL-1β, and IL-6 are central pro-inflammatory cytokines that drive myofibrillar protein degradation, inhibit protein synthesis, and lead to muscle atrophy. TNF-α also stimulates reactive oxygen species (ROS) production via the mitochondrial electron transport chain, activating NF-κB, which further enhances the ubiquitin-proteasome system, accelerating muscle protein breakdown and atrophy ³⁹. TNF-α is produced by various cells, including macrophages, lymphocytes, and skeletal muscle cells, and contributes to local and systemic inflammation upon binding to its receptors ⁴⁰. In CKD patients and those on hemodialysis, persistent activation of innate and adaptive immunity results in "inflammaging," a state of chronic low-grade inflammation ^{41, 42}. Simultaneously, BCAAs may exacerbate inflammation by directly activating NF-κB in inflammatory cells, leading to increased production of IL-6 and TNF-α ⁴³. Thus, TNF-α contributes to muscle wasting and altered amino acid levels, while BCAAs may further promote inflammation by enhancing cytokine production.

BCAAs and mortality

In our study, we observed that individuals in the low tertile of Val levels, compared to those in the high tertile, had an increased risk of cardiovascular and all-cause mortality. Additionally, lower levels of total BCAAs were linked to higher cardiovascular mortality risk but not to all-cause mortality risk. While in our study, no significant associations were found between Ile or Leu and neither cardiovascular nor all-cause mortality, a recent study by Luo et al. ²⁹ reported that in hypertensive individuals with advanced non-diabetic CKD, higher levels of Val, Leu, and Ile were associated with reduced cardiovascular mortality, with higher levels of Leu and Ile, but not Val, also being linked to lower all-cause mortality.

Previous studies in non-kidney disease populations have yielded inconsistent results. For instance, a meta-analysis by Teymoori et al. ⁴⁴, which included nine cohort studies and one case–control study, found no association between total or individual BCAAs and the risk of all-cause mortality. On the other hand, Fung et al. ⁴⁵ demonstrated a U-shaped relationship between BCAA levels and mortality in older individuals with hypertension and/or diabetes mellitus, with both high and low BCAA levels being associated with increased mortality. In contrast, among individuals without these conditions ⁴⁵, higher BCAA levels were associated with improved survival. Moreover, the LURIC study ⁴⁶ found that elevated BCAA levels in a Caucasian population were associated with a reduced long-term risk of both all-cause and cardiovascular mortality, with this relationship persisting regardless of obesity and/or diabetes status. The study by Deelen et al. ⁴⁷ further supported these findings, showing that higher levels of Val and Ile were associated with decreased mortality. Moreover, in a recent study Li et al ⁴⁸ reported that lower total BCAA levels were associated with increased all-cause mortality in patients with liver cirrhosis.

Our study is so far the most comprehensive exploration of the relationship between BCAAs, lipid profiles, and mortality risk among individuals with advanced CKD, with a relatively large sample size, detailed phenotyping and inclusion of age- and sex-matched controls for comparative analysis of BCAA concentrations. Additionally, no patients were lost to follow-up. However, some limitations should be considered when interpreting our findings. First, as this is an observational study, causality cannot be established. Second, BCAAs were measured only at the study's outset. Third, unmeasured confounders may have influenced the results, despite our efforts to account for potential confounders such as age, sex, BMI, DM, CVD, eGFR, plasma insulin, atherogenic lipids, and inflammation. Finally, the lack of detailed dietary information for CKD patients that potentially may influence circulating BCAA levels limits our ability to fully account for dietary contributions. However, previous studies suggest that metabolic alterations in CKD often outweigh the effects of diet, indicating that the observed changes in BCAA levels are likely driven primarily by the disease itself.

In patients with CKD stage 5, plasma concentrations of total and individual BCAAs were lower than in age- and sex matched healthy controls, lower in females than in males, and inversely correlated with TNF-α. Whereas higher levels of BCAAs were associated with an atherogenic lipid profile including higher AIP and glucose-related factors including HOMA-IR, competing risk regression analysis showed that lower levels of total BCAAs and valine were associated with increased cardiovascular mortality risk and lower plasma valine concentration was associated also with higher all-cause mortality risk.

These results provide insights into the intricate relationships between BCAA levels, lipid profiles, glucose-related compounds, inflammatory markers, and mortality in CKD patients and underscore the role of BCAAs in modulating cardiovascular risk and mortality in the context of CKD. While our study highlights significant associations, it also raises questions about the causality and clinical implications of these findings, and the underlying mechanisms remain complex and warrant further investigation. Further research, particularly longitudinal studies and interventional trials is needed to clarify the role of BCAAs in CKD in relation to metabolic alterations, progression of underlying disease and patient outcomes. Understanding these relationships could potentially contribute to new therapeutic strategies aimed at improving the prognosis for CKD patients.

Acknowledgements

We thank all patients and healthy subjects who participated in present study, and those who carried out the extensive clinical and laboratory work at the clinical investigational unit and the Renal Laboratory at Department of Renal Medicine, Karolinska University Hospital Huddinge. Baxter Novum is the result of a grant from Baxter Healthcare to Karolinska Institutet. The study also benefited from support from Martin Rind Foundation, Heart and Lung Foundation, Njurfonden, and Westmans Foundation.

Conflict of interest

Bengt Lindholm has been affiliated with Baxter Healthcare Corporation. Peter Stenvinkel is or has been on scientific advisory boards of REATA, Baxter, GSK, Astra Zeneca, Invizius, Behring, and Vifor and educational advisory boards for Astellas and FMC. Other authors do not declare any conflict of interest.

Credit Authorship Contribution Statement

Mohamed E Suliman: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Visualization, and Writing – original draft, Writing - review & editing

Abdul Rashid Qureshi: Conceptualization, Data curation, Formal analysis, Investigation, Methodology, Resources, Visualization, and Writing – original draft.

Dario Troise: Formal analysis and Writing – original draft and review & editing

Qianying Zhang: Formal analysis and Writing – original draft and review & editing

Peter Barany: Patient recruitment, Investigation, Methodology, Writing - review & editing

Olof Heimbürger: Patient recruitment, Investigation, Methodology, Writing - review & editing

Peter Stenvinkel: Investigation, Methodology, Funding acquisition, Project administration, Resources, Writing - review & editing

Bengt Lindholm: Conceptualization, Funding acquisition, Project administration, Resources,

Supervision, and Writing – review & editing.

All authors have read and approved the final manuscript.

Data Availability: Data described in the manuscript, code book, and analytic code will be made available upon request pending application to the corresponding author.

Supplementary Data: Supplementary data to this article can be found online at

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Table 1. Baseline characteristics of all CKD stage 5 patients and when divided into tertiles based on plasma concentration of total branched-chain amino acids (BCAAs).

Patient characteristics	Total	BCAAs First tertile	BCAAs Middle tertile	BCAAs Third tertile	P-value
Number	328	108	109	111
Age, years	54 (43 – 63)	56 (47-63)	53 (44-63.)	52 (42-64)	0.67
Males, n (%)	198 (60%)	49 (45%)	69 (63%)	80 (72%)	<0.001
DM, n (%)	104 (32%)	32 (30%)	37 (34%)	35 (32%)	0.79
CVD, n (%)	111 (34%)	38 (35%)	36 (33%)	37 (33%)	0.94
BMI, kg/m²	24 (22- 27)	24 (22-27)	24 (22-28)	24 (22-28)	0.74
eGFR, ml/min/1.73m²	6.4 (5.0-8.2)	6.3 (5.0-8.2)	6.6 (5.1-7.9)	6.5 (5.0-8.7)	0.60
CRP, mg/L	5.0 (2.0-15.0)	4.0 (1.6-15.0)	4.8 (2.0-15.0)	5.7 (2.6-14.0)	0.71
Glucose-related parameters
HbA1c, %	5.1 (4.5 – 6.1)	5.0 (4.4-5.8)	5.1 (4.4-6.4)	5.1 (4.6-6.2)	0.83
Blood glucose, mmol/L	5.4 (4.8-6.6)	5.3 (4.7-5.9)	5.3 (4.8-7.4)	5.5 (5.0-7.3)	0.08
Plasma insulin, mU/L	16 (11 – 29)	14 (11-22)	16 (10-27)	18 (11-29)	0.20
HOMA-IR	3.9 (2.5-7.1)	3.3 (2.4-5.4)	4.7 (2.4-7.9)	4.4 (2.9-9.1)	0.02
Plasma lipid profile
Triglycerides, mmol/L	1.9 (1.3-2.5)	1.8 (1.2-2.3)	1.9 (1.4-2.5)	2.0 (1.4-2.9)	0.23
Total cholesterol, mmol/L	5.2 (4.4-6.3)	5.5 (4.5-6.5)	5.3 (4.4-6.4)	4.9 (4.1-6.2)	0.21
HDL-C, mmol/L	1.2 (0.9-1.5)	1.4 (1.0-1.9)	1.1 (0.9-1.4)	1.1 (0.8-1.4)	<0.001
LDL-C, mmol/L	3.1 (2.2-4.0)	3.0 (2.2-4.0)	3.2 (2.3-4.2)	2.9 (2.0-4.0)	0.31
AIP, ratio	0.4 (0.0-1.0)	0.2 (-0.2-0.7)	0.5 (0.0-1.0)	0.5 (0.1-1.2)	0.003
Lipoprotein(a), nmol/L	213 (91-499)	212 (85-596)	271 (113-562)	180 (64-381)	0.02
Apolipoprotein-A, g/L	1.3 (1.1-1.5)	1.4 (1.2-1.6)	1.2 (1.1-1.4)	1.2 (1.0-1.4)	<0.001
Apolipoprotein-B, g/L	1.0 (0.8-1.3)	1.1 (0.8-1.2)	1.1 (0.8-1.3)	1.0 (0.8-1.3)	0.60
Plasma BCAAs
Total BCAAs, mmol/L	281 (232-329)	219 (191-232)	281 (263-291)	356 (328-397)	<0.001
Valine, mmol/L	152 (126 – 179)	112 (96-129)	152 (140-163)	195 (174-231)	<0.001
Isoleucine, mmol/L	56 (43-68)	41 (35-50)	57 (49-65)	69 (58-85)	<0.001
Leucine, mmol/L	67 (54-84)	54 (46-62)	72 (58-81)	88 (68-108)	<0.001

Data presented as median (IQR, interquartile range). Abbreviations: DM, diabetes mellitus; CVD, cardiovascular disease; BMI, body mass index; eGFR, estimated glomerular filtration rate; CRP, C-reactive protein; HbA1c, glycated hemoglobin; HDL-C, high-density lipoprotein-cholesterol; LDL-C, low-density lipoprotein-cholesterol; AIP, atherogenic index of plasma; BCAAs, branched-chain amino acids.

Table 2. Spearman rank correlation matrix of branched chain amino acids and lipid profile in 328 CKD stage 5 patients.

	BCAAs	Val	Ile	Leu	TG	HDL	AIP	Chol	LDL	Lp(a)	Apo-A
Val	0.93^d
Ile	0.73^d	0.59^d
Leu	0.63^d	0.40^d	0.29^d
TG	0.13^a	0.15^b	0.08	0.02
HDL	-0.26^d	-0.24^d	-0.24^d	-0.15^b	-0.45^d
AIP	0.22^c	0.22^c	0.17^b	0.10	0.89^d	-0.79^d
Chol	-0.08	-0.05	-0.05	-0.10	0.41^d	0.11	0.22^c
LDL	-0.02	-0.01	0.02	-0.05	0.29^d	-0.09	0.23^c	0.91^d
Lp(a)	-0.12^a	-0.13^a	-0.10	-0.05	-0.08	0.15^b	-0.13^a	0.12^a	0.11
Apo-A	-0.23^c	-0.24^d	-0.21^c	-0.07	-0.25^d	0.75^d	-0.53^d	0.26^d	0.09	0.12^a
Apo-B	0.02	0.01	0.04	-0.02	0.46^d	-0.18^b	0.39^d	0.84^d	0.87^d	0.12^a	0.08

Significance levels: a<0.05, b<0.01, c<0.001 and d<0.0001.

Abbreviations: BCAAs, branched-chain amino acids; Val, valine; Ile, isoleucine; Leu, leucine; TG, triglycerides; HDL, high-density lipoprotein-cholesterol; AIP, atherogenic index of plasma; Chol, cholesterol; LDL, low-density lipoprotein-cholesterol; Lp(a), lipoprotein (a); Apo-A, Apolipoprotein A; Apo-B, Apolipoprotein B.

Table 3. Predictors of 1-standard deviation (SD) increase of plasma concentrations of total (T-BCAAs) and individual branched-chain amino acids in 328 CKD 5 patients.

	T-BCAAs		Valine		Isoleucine		Leucine
	Beta	P-value	Beta	P-value	Beta	P-value	Beta	P-value
1-SD of age, years	-0.012	ns	-0.007	ns	-0.019	ns	-0.008	ns
Sex, F vs. M	-0.258	0.0001	-0.215	0.0001	-0.253	0.0001	0.163	0.004
Presence of DM	0.021	ns	-0.020	ns	0.010	ns	0.090	ns
Presence of CVD	-0.067	ns	-0.075	ns	-0.102	ns	0.189	ns
1-SD of BMI	0.050	ns	0.041	ns	0.003	ns	0.070	ns
1-SD of AIP	0.153	0.006	0.177	0.002	0.120	0.03	0.031	ns
1-SD of plasma insulin	0.127	0.02	0.099	0.07	0.097	0.07	0.113	0.04

Multivariate linear regression analysis with stepwise backward selection of variables. The model including sex, age, diabetes mellitus (DM), cardiovascular disease (CVD), body mass index (BMI), plasma insulin and atherogenic index of plasma (AIP). AIP is a ratio of the log of TG to HDL-C. ns= non-significant.

Table 4. Correlation between plasma concentrations of total (T-BCAA) and individual BCAAs with glucose-related parameters, estimated glomerular filtration rate (eGFR) and tumor necrosis factor-α (TNF-α) in 328 CKD 5 patients.

	T-BCAA	Val	Ile	Leu
HbA1c	0.10	0.06	0.03	0.17^***
Glucose	0.12^*	0.12^*	0.06	0.06
Insulin	0.12^*	0.14^**	0.06	0.02
HOMA-IR	0.17^**	0.20^***	0.10	0.05
eGFR	0.15^**	0.18^***	0.08	0.02
TNF-α	-0.15^**	-0.14^**	-0.18^***	0.01

Competing interest reported. Bengt Lindholm has been affiliated with Baxter Healthcare Corporation. Peter Stenvinkel is or has been on scientific advisory boards of REATA, Baxter, GSK, Astra Zeneca, Invizius, Behring, and Vifor and educational advisory boards for Astellas and FMC. Other authors do not declare any conflict of interest.

Supplementarymaterial.docx

Plasma branched-chain amino acids in chronic kidney disease: Associations with atherogenic lipids and mortality

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Abstract

Background

Methods

Results

Conclusion

Figures

Introduction

Material and Methods

Results

Discussion

BCAAs in different CKD groups

Associations BCAAs with lipid profile

Associations of BCAAs with glucose-related factors

Associations of BCAAs with inflammatory markers

BCAAs and mortality

Summary and conclusion

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

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