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Article

Altered Amino Acid Metabolism in Patients with Cardiorenal Syndrome Type 2: Is It a Problem for Protein and Exercise Prescriptions?

by
Roberto Aquilani
1,
Roberto Maestri
2,
Maurizia Dossena
1,
Maria Teresa La Rovere
3,
Daniela Buonocore
1,
Federica Boschi
4 and
Manuela Verri
1,*
1
Department of Biology and Biotechnology “Lazzaro Spallanzani”, University of Pavia, 27100 Pavia, Italy
2
Department of Biomedical Engineering of the Montescano Institute, Istituti Clinici Scientifici Maugeri IRCCS, 27040 Montescano, Italy
3
Department of Cardiac Rehabilitation of the Montescano Institute, Istituti Clinici Scientifici Maugeri IRCCS, 27040 Montescano, Italy
4
Department of Drug Sciences, University of Pavia, 27100 Pavia, Italy
*
Author to whom correspondence should be addressed.
Nutrients 2021, 13(5), 1632; https://doi.org/10.3390/nu13051632
Submission received: 14 April 2021 / Revised: 5 May 2021 / Accepted: 10 May 2021 / Published: 13 May 2021
(This article belongs to the Special Issue Aminoacid Loss and Deregulation in Chronic Renal Disease and New Protein Diet Strategies in Chronic Kidney Disease Patients)
Versions Notes

Abstract

:
The goal of this retrospective study was to document any alterations in plasma amino acids (AAs) in subjects with cardiorenal syndrome type 2 (CRS 2). We analyzed data from sixteen patients with CRS 2 and eight healthy subjects (control group, C), whose plasma arterial (A) and venous (V) AA concentrations had been measured. Compared to C, the group of CRS 2 patients showed significant reductions by more than 90% in A (p < 0.01) and V (p < 0.01) individual AAs, whereas negative A-V differences that indicated a net muscle AA release (muscle hypercatabolism) were found in 59% of CRS 2 patients (p < 0.03). No significant differences in plasma A and V AA concentrations nor in A-V differences were found between patients with mild kidney damage (N = 5; estimated glomerular filtration rate, eGFR ≥ 60 mL/min/1.73 m2) and patients with moderate-severe kidney damage (N = 11; eGFR < 60 mL/min/1.73 m2). Several plasma arterial AAs correlated with hemodynamic variables, but not with GFR. The study showed that patients with CRS 2 had very low concentrations of circulating AAs, independent of the degree of GFR damage.

1. Introduction

The complication of chronic heart failure (CHF) with chronic kidney disease (CKD) identifies the cardiorenal syndrome (CRS) which is classified as CRS type 2 (CRS 2) [1,2]. The prevalence of CRS 2 is estimated to be 25–63% [3,4,5]. The development of CKD in the CHF setting amplifies the clinical difficulties in managing volume overload, using mechanical circulatory support in a cardiac transplantation [6]. Anemia, cachexia and physical deconditioning, which are three independent risk factors of survival and functional prognosis in CHF [7,8,9], might be aggravated. The development of renal failure reduces survival, even in patients with preserved left ventricular ejection fraction (LVEF) [3].
We hypothesized that the development of renal dysfunction in patients with CHF may amplify the alterations of amino acid (AA)/protein metabolism, as reflected by plasma AA concentrations, already documented in CHF alone [10] and in primary CKD alone [11]. Firstly, CHF and CKD share similar pathogenic mechanisms, influencing the turnover of body/muscle nitrogen metabolism. These mechanisms include hemodynamic factors such as right ventricular overload [1,12], neurohormonal activation with sympathetic overdrive, activation of renin-angiotensin-aldosterone system (RAAS), inflammation, hormonal alterations and immune dysregulation [1,13]. Secondly, the kidney plays a major role on body AA homeostasis [14,15]. Thirdly, in CRS 2, both glomerular [16] and tubular [2,17,18,19] damages are described.
The presence of an abnormal plasma amino acid (PAA) profile in patients with CRS 2 may be clinically important given that it has the potential to impair the metabolic activities of all body districts, including the heart and the kidney themselves, thus acting as additive damage. Moreover, abnormal PAAs may lead the physician to two therapeutic dilemmas: (a) when patients are stable, how could their dietary protein intake be reduced in relation to glomerular filtration rate (GFR) damage [20] and, at the same time, how could it be increased in order to correct abnormal PAAs and provide patients with an adequate amount of nitrogen for their body’s metabolic requirements? (b) During an acute event, would normal or artificial nutrition be adequate to support the body’s increased nitrogen needs?
Using the data from a previous study where we had analyzed arterial and venous PAA profile in CHF patients [10], we performed a secondary analysis on the collected data. The aim of the analysis was to investigate whether GFR damage could be associated with abnormal PAA concentrations, even though we were aware that proximal tubules are the main structure deputed to AA reabsorption from filtered plasma.

2. Materials and Methods

We re-analyzed the data from chronic heart failure (CHF) patients who had participated in a previous study on Plasma Amino Acid Abnormalities [10]. These patients were admitted to the Heart Failure Unit of the Scientific Institute of Montescano to undergo right cardiac catheterization for heart transplantation evaluation. We only selected CRS 2 patients whose arterial and venous AAs had been measured after overnight fasting.
The diagnosis of CRS 2 was established following the indication of the American Heart Association Statement [1]. In addition to PAA measurements, the inclusion criteria were the following: clinical stability (no changes in drugs over the previous three weeks, and no clinical evidence of body water retention), stable normal body weight (body mass index, BMI, > 22 kg/m2) for the previous three months, absence of hypoglycemic agents, normal liver function (total bilirubin < 1.1 mg/dL; serum alanine aminotransferase < 39 U/L; serum oxaloacetic aminotransferase < 25 U/L), absence of kidney dysfunction preceding the diagnosis of CHF, absence of primary endocrine disturbances.
Following the routine protocol of the Institute, 2D-echocardiography and cardiopulmonary exercise testing was performed on CHF patients, and their venous N-terminal pro-B-type natriuretic peptide (NT-pro-BNP) concentrations were measured.
In the selected patients, CKD was diagnosed after transforming serum creatinine concentrations into GFR (estimated GFR, eGFR) (mL/min/1.73 m2) [21]. The eGFR values were then categorized according to the classification of Kidney Disease: Improving Global Outcomes (KDIGO) [22]. According to KDIGO, we identified 16 patients with CRS 2: 11 (68.8%) had eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD) (range 59–26) and 5 (31.2%) had eGFR ≥ 60 mL/min/1.73 m2 (range 60–88) (mild reduction: M-CKD). The patient characteristics have been reported in Table 1.
In the patients, the PAAs had been determined as described elsewhere [23], and expressed in µmol/L.
We used arterial (A) and venous (V) concentrations to calculate the AA (A-V) differences. A positive value indicated net muscle AA uptake (prevalence of anabolic activity); a negative value indicated a net muscle AA release (prevalence of catabolic activity); no positive–no negative (A-V) value indicated no AA net uptake, no net release (balanced muscle AA metabolism).
PAA concentrations were determined in a group of healthy subjects (controls: C; N = 8, 6 of whom males). The controls were selected for similar BMI (27.1 ± 2.2 kg/m2) and age (51 ± 9 years) and for absence of discretionary physical activity. The healthy subjects reported no significant past medical history. Examination of the control subjects confirmed that they were in good health. In healthy C, in the current study, we also considered the AA ornithine, which had not been considered in the previous study [10], as this AA is a by-product of the urea cycle; however, we did not consider the AA taurine [10] because it was not available in CRS 2 patients’ venous blood samples.

Statistical Analysis

The central tendency and dispersion of continuous variables were reported as mean ± SD. Due to violations to the normality assumption (Shapiro–Wilk statistic), hypothesis testing was based on non-parametric statistics. Descriptive statistics for categorical variables were reported as N (percent frequency). Between-group comparisons were carried out by the Mann–Whitney U-test (two groups), or by the Kruskal–Wallis test (three groups) and by the Chi-square test for continuous and categorical variables, respectively. When the Kruskal–Wallis test was significant, post hoc analysis was carried out (Dunn–Sidak adjustment). The association between couples of variables was assessed by the Spearman’s correlation coefficient.
A p-value < 0.05 was considered statistically significant. All analyses were carried out using the SAS/STAT statistical package, release 9.4 (SAS Institute Inc., Cary, NC, USA).

3. Results

3.1. Comparison between Healthy Controls and the Entire Population with CRS 2

The study found significant differences in PAAs between the entire population with CRS 2 and C. In CRS 2, more than 90% of both arterial (Table 2) and venous (Table 3) individual AAs, and 71.4% of (A-V) differences (Table 4) were lower than in C. In CRS 2, total arterial and venous AAs (TAAs) were lower: −73% and −56.4%, respectively. In contrast, the muscle release of TAAs was higher (+453%, p = 0.027) in CRS 2 than in C. Moreover, in CRS 2, significantly lower arterial and venous essential amino acid (EAA) and branched chain amino acid (BCAA) concentrations were found (p = 0.0001 for all AAs), whereas their muscle releases (Table 4) were higher than in C. Compared to C, CRS 2 had arterial/venous AA ratios < 1 (Table 5).
To sum up, the study found that in comparison to controls, patients with CRS 2 had low PAAs even though their skeletal muscle tissue released a larger amount of these substrates.

3.2. Comparisons between C, M-CKD, MS-CKD

Compared to C, M-CKD patients (eGFR ≥ 60 mL/min/1.73 m2) had lower concentrations of arterial (Table 6) and venous (Table 7) TAAs, EAAs, BCAAs and all the single AAs, with the exception of venous threonine, which was similar in C and M-CKD. Skeletal muscle tissue in M-CKD (Table 8) released larger amounts of leucine, BCAAs and EAAs.
Compared to C, MS-CKD (eGFR < 60 mL/min/1.73 m2) patients had lower arterial (Table 6) and venous (Table 7) concentrations of all individual AAs, except for venous ornithine, which was higher. With respect to muscle AA (A-V) differences (Table 8), MS-CKD released larger amounts of leucine, EAAs, BCAAs, glycine, tyrosine, tryptophan and phenylalanine.
M-CKD and MS-CKD patients had similar concentrations of arterial and venous AAs as well as muscle AA releases.

3.3. Comparison of Non-Amino Acid Variables between M-CKD and MS-CKD Patients

Table 9 shows that the two subgroups of CKD had similar concentrations of all the variables, with the exception of creatinine, which was lower in M-CKD than in MS-CKD patients.

3.4. Correlations between Arterial Plasma AAs, Renal and Cardiac Functions

eGFR was positively associated with arterial systolic and diastolic blood pressures (r = +0.51, p = 0.055 and r = 0.72, p = 0.002, respectively). Several plasma AAs correlated with LVEF and other hemodynamic variables, but not with eGFR (Table 10).

4. Discussion

The study found that patients with CRS 2 had low arterial and venous PAA concentrations, even though these metabolic substrates were excessively released by skeletal muscle tissue. The rate of PAA deterioration was independent of the renal filtration damage.
PAA deterioration was worse in CHF and CKD patients when the two diseases were considered together than when they were considered separately. When CHF patients were considered alone, only aspartic acid, methionine, taurine (NYHA II and III) and glutamic acid, and cysteine (NYHA III) were low [10]. Notably, in patients with M-CKD, altered PAAs were similar to those observed in the CHF IV NYHA class [10]. In the early stages of CKD (stage I and II), only valine and leucine concentrations were lower than in controls [24], whereas in severe CKD (GFR of 7 mL/min) [25] there were increases in several non-essential AAs and decreases in five essential AAs (threonine, tryptophan, histidine, valine, leucine). Notably, PAA alterations in CRS 2 patients were greater than those observed in long-term hemodialyzed patients in whom 70% of arterial AAs were altered [26]. Higher concentrations of ornithine in MS-CKD patients than in normal subjects suggests overactivity of the urea cycle.
The study results clearly indicate that it is clinically and metabolically important in every patient with CHF to convert the serum creatinine levels into eGFR.
The non-dependence of AA alterations on the degree of GFR reduction clearly indicates that tubular dysfunction contributes to altered PAA concentrations. Under physiological conditions, proximal tubule cells reabsorb 80% of the filtrated AAs [27]. In CHF, a tubulo-interstitial injury may coexist with normal glomerular filtration [28] and is more evident during acute decompensation of heart failure [17,19]. Urinary levels of tubular markers are increased in clinically stable CHF [28] and may indicate impaired GFR even before GFR reduction [28]. Therefore, tubular injuries may bring about increased urinary AA loss [2,29].
The complex interplay of several factors shared by CHF and CKD likely provides an explanation of the results of this study. These factors include neurohormonal activation [30], consisting of hyperactivities of hypothalamic-pituitary-adrenal axis, adrenergic system, renin-angiotensin-aldosterone system (RAAS), hormonal imbalances [11,31,32], systemic inflammation [13,25,30,33,34], body/muscle AA overconsumption [10] and abnormal skeletal muscle intermediate metabolism [30,35,36,37]. All these factors alter body hemodynamic and rheologic conditions, and metabolic homeostasis and lead to changes in body AA/protein metabolism.
The main contributions of these factors to abnormal PAAs in CRS will be discussed separately for arterial AA concentrations and A-V differences.

4.1. Potential Mechanisms Underlying Low Arterial AAs

AA concentrations in arterial plasma reflect body protein metabolism better than venous plasma [38].
Under physiological conditions, arterial AA concentrations depend on both dietary protein intake and body protein metabolism [39].
Due to the lack of information about patients’ nutritional intakes, the role of nutrition in deteriorating PAAs cannot be delineated. However, it would be reasonable to assume that even if the patients’ nutrition had been normal, it would have been inadequate to meet the body’s nitrogen requirements, as inferred by the reduction in circulating essential AAs (EAAs): substances which must be provided by exogenous sources.
The combination of hemodynamic alterations, body AA overconsumption and intracellular metabolic acidosis (not determined in the study patients) may be responsible for the altered PAAs.
Both in CHF and CKD, volume overload leads to intestinal wall congestion [40,41], thus favoring the development of pathogenic gut flora [40,42]. Intestinal dysbiosis, in turn, may decrease the retrieval of non-absorbed protein [43] and, at the same time, may induce endoluminal proteolytic over-activity and urea formation. In addition, intestinal edema and gut dysbiosis are directly responsible for translocation of bacteria and/or their toxic products into the blood stream [42], causing/enhancing systemic inflammation. Low circulating citrulline suggests that the study patients may have had a dysfunctional small bowel mucosa. This amino acid is not incorporated in proteins, and is almost exclusively formed by enterocytes [44] and 80% of its concentration is converted into arginine in proximal convoluted kidney tubules [45]. Therefore, low citrulline reflects low intestinal production and/or increased intestinal ureagenesis.
The heart, the lungs, the kidney and skeletal muscle are body districts with high AA consumption. In heart failure, there is AA overconsumption to sustain myocardium remodeling, a process requiring a high rate of protein synthesis and oxidative metabolism [10,46,47]. Renal dysfunction itself increases the heart remodeling rate, given that on one hand renal disfunction (eGFR 60 mL/min/1.73 m2) is associated with left ventricular remodeling [48] and on the other hand, the accompanying increase in extracellular water induces left ventricular hypertrophy at a very early stage of chronic kidney disease [48].
In CHF, there is also AA overconsumption in the lungs [49], in particular in subjects without β-blocker therapy [50]. Renal dysfunction per se causes AA overconsumption due to gluconeogenesis, ureagenesis and structural remodeling because of tubular hypertrophy that is caused by the concentration of ammonia in the tubule cells [51].
Metabolic acidosis lowers PAA concentrations by increasing renal AA uptake and, at the same time, suppressing renal proteolysis [52]. Measures of acid-base balance were not available in the study patients, however intracellular metabolic acidosis could be suspected given the low arterial histidine concentration, an important intracellular buffer [53].
Skeletal muscle AA utilization, particularly in mitochondria, occurs both in CHF and CKD as documented in bioptic specimens from the quadriceps muscle of CHF [35] and CKD [36], showing exalted mitochondrial aminotransferase activities.
At first glance, low arterial AAs could be due to low venous AA concentrations; however, this is not a major mechanism as the patients, unlike controls, had low arterial/venous AA ratios, indicating that muscle release of AAs, although in excess, was not enough to balance AA uptake by extramuscular body districts.
In summary, the study suggests that in CRS 2 patients, the body’s AA requirements are greater than the amount of AAs provided by the skeletal muscle, which is the main store of AAs in the body.

4.2. Muscle AA (A-V) Differences and AA Plasma Venous Concentrations

The net muscle AA releases, in particular phenylalanine, indirectly indicate the presence of muscle protein hypercatabolism [54], whose pathophysiological mechanisms are shared by both CHF and CKD, and include inflammation [30,33,55,56] and hemodynamic factors such as venous congestion and hypertension, metabolic acidosis, insulin, and growth hormone resistances.
Inflammation is a potent condition causing muscle AA depletion. The overproduction of proinflammatory cytokines increases muscle protein degradation, inhibits both muscle protein synthesis and repair [57,58,59,60,61,62,63] and increases production of catabolic hormones such as glucagon, catecholamines and cortisol [64,65].
Both in CHF and CKD, one source of cytokine production is venous hypertension [66].
In CKD, metabolic acidosis leads to muscle AA overconsumption by accelerating protein degradation [67].
Insulin and growth hormone (GH) resistances reduce anabolic activities both in CHF [68] and CKD [11,69] as insulin resistance depresses the antiproteolytic activity of the insulin [70], in particular during overnight fasting, and GH resistance causes muscle proteolysis given that the physiologic GH activity is to increase AA uptake into skeletal muscle.

4.3. Correlations between Cardiac Function, Renal Function and PAAs in CRS 2

The study confirms the positive correlations existing between most PAAs and cardiac function [10]. On the contrary, no significant correlations were found between PAAs and renal filtration rate (GFR), suggesting that renal glomeruli have no role in body AA metabolic homeostasis.
Regarding the heart/kidney relationship, the positive association between renal filtration rate and arterial blood pressure (both systolic and diastolic pressures) indicates that an important determinant of GFR is the peripheral arterial pressure and consequently the renal perfusion pressure [71] and not the cardiac output as also documented by a previous study [72].
The lack of information about patient nutritional intake does not allow us to understand the contribution of ingested salt and water intakes to the hyponatremia found in MS-CKD. Given that sodium is the most important osmotic solute of extracellular fluid, it would be reasonable to assume that serum osmolarity was low in MS-CKD, and low concentrations of circulating AAs likely contributed to reduce osmolarity. Notably, increased blood glucose and urea may help to maintain renal perfusion pressure, mitigate sodium-induced hypoosmolality, and limit the extravasation of intravascular hypotonic fluid towards the intracellular and interstitial spaces.
The higher serum albumin in MS-CKD could be due to higher protein-calorie intakes [73] and/or a hypovolemic state associated with hypotonic hyponatremia. This latter mechanism may be plausible given that the patients were not on hypertonic infusions, nor did they have serious hyperglycemia, hyperlipidemia or hyperproteinemia.
The similar PAA alterations in M-CKD and MS-CKD indicate that the renal contribution to altered AA/protein metabolism starts in the early stages of renal damage in subjects with CHF.

4.4. Relevance of Altered PAAs for Patients with CRS 2. Potential Practical Implications

In CRS 2 patients, the alterations of AA/protein metabolism may potentially contribute to and accentuate the metabolic and functional alterations of several body districts (Table 11).
The hypoaminoacidemia in hyperazotemic CRS 2 patients raises the question of whether it is appropriate to prescribe a hypoproteic diet before improving circulating AAs. The authors’ opinion is that a hypoproteic diet should be prescribed in association with EAA supplementation for the following reasons. Firstly, a hypoproteic diet alone may further impair circulating AAs. Secondly, a bolus of oral 8 g EAAs has shown to increase EAA plasma concentrations in healthy subjects [81]. Chronic EAA supplementation has been shown to improve body weight, anthropometric measures, insulin resistance and exercise tolerance in stable CHF on rehabilitative treatment [82,83]. Interestingly, in CKD patients, physical exercise can improve protein energy wasting [84,85,86]. Thirdly, 8 g free EAAs, by providing 1.28 g nitrogen vs. 3.28 g nitrogen from 100 g lean beef meat with a similar quantity of EAAs, can save nitrogen and at the same time ensure/enhance anabolic activities. Lastly, CHF patients release a large amount of AAs during light exercise that mimics the physical activities of daily life [87]. Future research should address whether the association of EAA supplementation and physical training could benefit hyperazotemic CRS 2 in terms of improvements in the PAA profile and body/muscle anabolic activity.
It would be prudent to improve plasma AA concentrations when the patients are clinically stable in order to limit metabolic damage following periods of acute events requiring continuous renal replacement therapy or during hemodynamic instability [88].
This study suggests the importance of calculating nutritional intakes of patients with CHF as soon as CHF is first diagnosed, given the high prevalence of the development of renal damage.

4.5. Limitations of the Study

The study has several limitations that should be addressed by future research. The results of the study should be confirmed by a prospective investigation with a larger patient population.
Patients’ nutritional intakes and body tissue composition were not available. The knowledge of nutritional intakes would have allowed us to better understand the contribution of diet to circulating AAs. Body composition analysis would have allowed us to diagnose a state of sarcopenia or cachexia. However, a depletion of skeletal muscle mass in the study patients may be likely, given their muscle hypercatabolism [89].
A population of subjects with CHF alone was not considered in this study. For comparison aims, we referred to the abnormal plasma AA profile of subjects with CHF described in a previous investigation [10]. Similarly, the study did not compare AA concentrations in CRS 2 patients with those in CKD patients alone.
Renal biomarkers [90] including plasma beta 2-microglobulin [91], N-acetyl-beta-glucosaminidase (NAG) [92] and urinary kidney injury molecule-1 (KIM-1) [93] were not available in this study. Thus, a prospective investigation is necessary to address the relationship between levels of kidney injury markers and plasma AA levels.
Another limitation of the study is the lack of information about urine AA losses. This information would have strengthened the discussion. A future prospective study will address the balance between urine and plasma amino acid levels.
The knowledge of patients’ acid-base state would have allowed us to better understand its contribution to muscle net AA releases. In addition, the determination of urinary AA losses would have suggested the role played by proximal tubular dysfunction in contributing to altered PAAs.

5. Conclusions

The study shows that patients with cardiorenal syndrome type 2 had very low concentrations of circulating AAs, the rates of which were independent of the degree of GFR reduction.

Author Contributions

Conceptualization, R.A.; methodology, M.V., F.B. and D.B.; software, R.M.; validation, R.A., R.M. and M.V.; formal analysis, R.M.; investigation, M.T.L.R. and M.D.; data curation, R.M.; writing—original draft preparation, R.A.; writing—review and editing, M.V.; visualization, F.B., D.B.; supervision, R.A. and M.T.L.R.; project administration, R.A.; funding acquisition, M.D. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted according to the guidelines of the Declaration of Helsinki. We re-analyzed the data from chronic heart failure (CHF) patients who had participated in a previous study on Plasma Amino Acid Abnormalities [Aquilani, R.; La Rovere, M.T.; Corbellini, D.; Pasini, E.; Verri, M.; Barbieri, A.; Condino, A.M.; Boschi, F. Plasma amino acid abnormalities in chronic heart failure. Mechanisms, potential risks and targets in human myocardium metabolism. Nutrients 2017, 9, 1251, doi:10.3390/nu9111251]. These patients were admitted to the Heart Failure Unit of the Scientific Institute of Montescano to undergo right cardiac catheterization for heart transplantation evaluation.

Informed Consent Statement

Informed written consent was obtained from each patient before the original study.

Data Availability Statement

Data supporting the reported results were confidential. The datasets that were used and/or analyzed during the current study, but not shown in the paper, are available from the corresponding author, on reasonable request.

Acknowledgments

This research was supported by the Italian Ministry of Education, University and Research (MIUR), Dipartimenti di Eccellenza Program (2018–2022)-Dept. of Biology and Biotechnology “L. Spallanzani”, University of Pavia (to R.A., M.D., D.B. and M.V.) and by the Ricerca Corrente funding scheme of the Ministry of Health (to R.M. and M.T.L.R.).

Conflicts of Interest

The author Roberto Aquilani is a scientific consultant at Professional Dietetics (Milano, Italy). This company had no role in the design, execution, interpretation, or writing of the study. The other authors declare no conflict of interest.

References

  1. Rangaswami, J.; Bhalla, V.; Blair, J.E.; Chang, T.I.; Costa, S.; Lentine, K.L.; Lerma, E.V.; Mezue, K.; Molitch, M.; Mullens, W.; et al. Cardiorenal Syndrome: Classification, Pathophysiology, Diagnosis, and Treatment Strategies: A Scientific Statement From the American Heart Association. Circulation 2019, 139, e840–e878. [Google Scholar] [CrossRef]
  2. Cruz, D.N.; Schmidt-Ott, K.M.; Vescovo, G.; House, A.A.; Kellum, J.A.; Ronco, C.; McCullough, P.A. Pathophysiology of Cardiorenal Syndrome Type 2 in Stable Chronic Heart Failure: Workgroup Statements from the Eleventh Consensus Conference of the Acute Dialysis Quality Initiative (ADQI). Contrib. Nephrol. 2013, 182, 117–136. [Google Scholar] [CrossRef]
  3. Hillege, H.L.; Nitsch, D.; Pfeffer, M.A.; Swedberg, K.; McMurray, J.J.; Yusuf, S.; Granger, C.B.; Michelson, E.L.; O’stergren, J.; Cornel, J.H.; et al. Renal Function as a Predictor of Outcome in a Broad Spectrum of Patients with Heart Failure. Circulation 2006, 113, 671–678. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  4. De Silva, R.; Nikitin, N.P.; Witte, K.K.; Rigby, A.S.; Goode, K.; Bhandari, S.; Clark, A.L.; Cleland, J.G. Incidence of renal dysfunction over 6 months in patients with chronic heart failure due to left ventricular systolic dysfunction: Contributing factors and relationship to prognosis. Eur. Hear. J. 2006, 27, 569–581. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Ronco, C.; McCullough, P.; Anker, S.D.; Anand, I.; Aspromonte, N.; Bagshaw, S.M.; Bellomo, R.; Berl, T.; Bobek, I.; Cruz, D.N.; et al. Cardio-renal syndromes: Report from the consensus conference of the Acute Dialysis Quality Initiative. Eur. Heart J. 2010, 31, 703–711. [Google Scholar] [CrossRef]
  6. Zannad, F.; Rossignol, P. Cardiorenal Syndrome Revisited. Circulation 2018, 138, 929–944. [Google Scholar] [CrossRef]
  7. Jankowska, E.A.; Von Haehling, S.; Anker, S.D.; MacDougall, I.C.; Ponikowski, P. Iron deficiency and heart failure: Diagnostic dilemmas and therapeutic perspectives. Eur. Hear. J. 2013, 34, 816–829. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  8. Sato, Y.; Yoshihisa, A.; Kimishima, Y.; Yokokawa, T.; Abe, S.; Shimizu, T.; Misaka, T.; Yamada, S.; Sato, T.; Kaneshiro, T.; et al. Prognostic factors in heart failure patients with cardiac cachexia. J. Geriatr. Cardiol. 2020, 17, 26–34. [Google Scholar] [PubMed]
  9. Prescott, E.; Hjardem-Hansen, R.; Dela, F.; Ørkild, B.; Teisner, A.S.; Nielsen, H. Effects of a 14-month low-cost maintenance training program in patients with chronic systolic heart failure: A randomized study. Eur. J. Cardiovasc. Prev. Rehabil. 2009, 16, 430–437. [Google Scholar] [CrossRef]
  10. Aquilani, R.; La Rovere, M.T.; Corbellini, D.; Pasini, E.; Verri, M.; Barbieri, A.; Condino, A.M.; Boschi, F. Plasma Amino Acid Abnormalities in Chronic Heart Failure. Mechanisms, Potential Risks and Targets in Human Myocardium Metabolism. Nutrients 2017, 9, 1251. [Google Scholar] [CrossRef] [Green Version]
  11. Garibotto, G.; Sofia, A.; Russo, R.; Paoletti, E.; Bonanni, A.; Parodi, E.L.; Viazzi, F.; Verzola, D. Insulin sensitivity of muscle protein metabolism is altered in patients with chronic kidney disease and metabolic acidosis. Kidney Int. 2015, 88, 1419–1426. [Google Scholar] [CrossRef] [Green Version]
  12. Kanjanahattakij, N.; Sirinvaravong, N.; Aguilar, F.; Agrawal, A.; Krishnamoorthy, P.; Gupta, S. High Right Ventricular Stroke Work Index Is Associated with Worse Kidney Function in Patients with Heart Failure with Preserved Ejection Fraction. Cardiorenal Med. 2018, 8, 123–129. [Google Scholar] [CrossRef] [PubMed]
  13. Clementi, A.; Virzì, G.M.; Battaglia, G.G.; Ronco, C. Neurohormonal, Endocrine, and Immune Dysregulation and Inflammation in Cardiorenal Syndrome. Cardiorenal Med. 2019, 9, 265–273. [Google Scholar] [CrossRef]
  14. Young, G.A. Amino acids and the kidney. Amino Acids 1991, 1, 183–192. [Google Scholar] [CrossRef] [PubMed]
  15. Garibotto, G.; Sofia, A.; Saffioti, S.; Bonanni, A.; Mannucci, I.; Verzola, D. Amino acid and protein metabolism in the human kidney and in patients with chronic kidney disease. Clin. Nutr. 2010, 29, 424–433. [Google Scholar] [CrossRef]
  16. Le Jemtel, T.H.; Rajapreyar, I.; Selby, M.G.; Payne, B.; Barnidge, D.R.; Milic, N.; Garovic, V.D. Direct Evidence of Podocyte Damage in Cardiorenal Syndrome Type 2: Preliminary Evidence. Cardiorenal Med. 2015, 5, 125–134. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  17. Aghel, A.; Shrestha, K.; Mullens, W.; Borowski, A.; Tang, W.H.W. Serum Neutrophil Gelatinase-Associated Lipocalin (NGAL) in Predicting Worsening Renal Function in Acute Decompensated Heart Failure. J. Card. Fail. 2010, 16, 49–54. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  18. Brezis, M.; Rosen, S. Hypoxia of the Renal Medulla–Its Implications for Disease. N. Engl. J. Med. 1995, 332, 647–655. [Google Scholar] [CrossRef]
  19. Shrestha, K.; Shao, Z.; Singh, D.; Dupont, M.; Tang, W.H.W. Relation of Systemic and Urinary Neutrophil Gelatinase-Associated Lipocalin Levels to Different Aspects of Impaired Renal Function in Patients with Acute Decompensated Heart Failure. Am. J. Cardiol. 2012, 110, 1329–1335. [Google Scholar] [CrossRef] [Green Version]
  20. Kalista-Richards, M. Invited Review: The Kidney: Medical Nutrition Therapy—Yesterday and Today. Nutr. Clin. Pr. 2011, 26, 143–150. [Google Scholar] [CrossRef]
  21. Levey, A.S.; Greene, T.; Beck, G.J.; Caggiula, A.W.; Kusek, J.W.; Hunsicker, L.G.; Klahr, S. Dietary protein restriction and the progression of chronic renal disease: What have all of the results of the MDRD study shown? Modification of Diet in Renal Disease Study group. J. Am. Soc. Nephrol. 1999, 10, 2426–2439. [Google Scholar] [CrossRef] [PubMed]
  22. Eckardt, K.-U.; Kasiske, B.L. Foreword. Kidney Int. 2009, 76, S1–S2. [Google Scholar] [CrossRef] [PubMed]
  23. Aquilani, R.; Brugnatelli, S.; Dossena, M.; Maestri, R.; Delfanti, S.; Buonocore, D.; Boschi, F.; Simeti, E.; Condino, A.M.; Verri, M. Oxaliplatin-Fluoropyrimidine Combination (XELOX) Therapy Does Not Affect Plasma Amino Acid Levels and Plasma Markers of Oxidative Stress in Colorectal Cancer Surgery Patients: A Pilot Study. Nutrients 2019, 11, 2667. [Google Scholar] [CrossRef] [Green Version]
  24. Kumar, M.A.; Bitla, A.R.R.; Raju, K.V.N.; Manohar, S.M.; Kumar, V.S.; Narasimha, S.R.P.V.L. Branched chain amino acid profile in early chronic kidney disease. Saudi J. Kidney Dis. Transplant. 2012, 23, 1202–1207. [Google Scholar]
  25. Suliman, M.E.; Qureshi, A.R.; Stenvinkel, P.; Pecoits-Filho, R.; Bárány, P.; Heimburger, O.; Anderstam, B.; Ayala, E.R.; Filho, J.C.D.; Alvestrand, A.; et al. Inflammation contributes to low plasma amino acid concentrations in patients with chronic kidney disease. Am. J. Clin. Nutr. 2005, 82, 342–349. [Google Scholar] [CrossRef] [PubMed]
  26. Murtas, S.; Aquilani, R.; Iadarola, P.; Deiana, M.; Secci, R.; Cadeddu, M.; Bolasco, P. Differences and Effects of Metabolic Fate of Individual Amino Acid Loss in High-Efficiency Hemodialysis and Hemodiafiltration. J. Ren. Nutr. 2020, 30, 440–451. [Google Scholar] [CrossRef]
  27. Bhargava, P.; Schnellmann, R.G. Mitochondrial energetics in the kidney. Nat. Rev. Nephrol. 2017, 13, 629–646. [Google Scholar] [CrossRef]
  28. Damman, K.; Masson, S.; Hillege, H.L.; Maggioni, A.P.; Voors, A.A.; Opasich, C.; Van Veldhuisen, D.J.; Montagna, L.; Cosmi, F.; Tognoni, G.; et al. Clinical outcome of renal tubular damage in chronic heart failure. Eur. Hear. J. 2011, 32, 2705–2712. [Google Scholar] [CrossRef] [Green Version]
  29. Duranton, F.; Lundin, U.; Gayrard, N.; Mischak, H.; Aparicio, M.; Mourad, G.; Daurès, J.-P.; Weinberger, K.M.; Argilés, À. Plasma and Urinary Amino Acid Metabolomic Profiling in Patients with Different Levels of Kidney Function. Clin. J. Am. Soc. Nephrol. 2014, 9, 37–45. [Google Scholar] [CrossRef] [Green Version]
  30. Anker, S.; Ponikowski, P.; Clark, A.; Leyva, F.; Rauchhaus, M.; Kemp, M.; Teixeira, M.; Hellewell, P.; Hooper, J.; Poole-Wilson, P.; et al. Cytokines and neurohormones relating to body composition alterations in the wasting syndrome of chronic heart failure. Eur. Hear. J. 1999, 20, 683–693. [Google Scholar] [CrossRef]
  31. Tessari, P.; Cecchet, D.; Cosma, A.; Puricelli, L.; Millioni, R.; Vedovato, M.; Tiengo, A. Insulin resistance of amino acid and protein metabolism in type 2 diabetes. Clin. Nutr. 2011, 30, 267–272. [Google Scholar] [CrossRef] [PubMed]
  32. Siew, E.; Pupim, L.; Majchrzak, K.; Shintani, A.; Flakoll, P.; Ikizler, T. Insulin resistance is associated with skeletal muscle protein breakdown in non-diabetic chronic hemodialysis patients. Kidney Int. 2007, 71, 146–152. [Google Scholar] [CrossRef] [Green Version]
  33. Kalantar-Zadeh, K.; Ikizler, T.; Block, G.; Avram, M.M.; Kopple, J.D. Malnutrition-inflammation complex syndrome in dialysis patients: Causes and consequences. Am. J. Kidney Dis. 2003, 42, 864–881. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  34. Colombo, P.C.; Ganda, A.; Lin, J.; Onat, D.; Harxhi, A.; Iyasere, J.E.; Uriel, N.; Cotter, G. Inflammatory activation: Cardiac, renal, and cardio-renal interactions in patients with the cardiorenal syndrome. Hear. Fail. Rev. 2012, 17, 177–190. [Google Scholar] [CrossRef] [PubMed]
  35. Opasich, C.; Aquilani, R.; Dossena, M.; Foppa, P.; Catapano, M.; Pagani, S.; Pasini, E.; Ferrari, R.; Tavazzi, L.; Pastoris, O. Biochemical analysis of muscle biopsy in overnight fasting patients with severe chronic heart failure. Eur. Hear. J. 1996, 17, 1686–1693. [Google Scholar] [CrossRef] [PubMed]
  36. Pastoris, O.; Aquilani, R.; Foppa, P.; Bovio, G.; Segagni, S.; Baiardi, P.; Catapano, M.; Maccario, M.; Salvadeo, A.; Dossena, M. Altered muscle energy metabolism in post-absorptive patients with chronic renal failure. Scand. J. Urol. Nephrol. 1997, 31, 281–287. [Google Scholar] [CrossRef] [PubMed]
  37. Cicoira, M.; Bolger, A.P.; Doehnera, W.; Rauchhausac, M.; Davos, C.H.; Sharmaa, R.; Al-Nasser, F.O.; Coats, A.J.; D’Ankerad, S. High Tumour Necrosis Factor-Α Levels Are Associated with Exercise Intolerance And Neurohormonal Activation In Chronic Heart Failure Patients. Cytokine 2001, 15, 80–86. [Google Scholar] [CrossRef]
  38. Cynober, L.A. Plasma amino acid levels with a note on membrane transport: Characteristics, regulation, and metabolic significance. Nutrients 2002, 18, 761–766. [Google Scholar] [CrossRef]
  39. Luo, Y.; Yoneda, J.; Ohmori, H.; Sasaki, T.; Shimbo, K.; Eto, S.; Kato, Y.; Miyano, H.; Kobayashi, T.; Sasahira, T.; et al. Cancer Usurps Skeletal Muscle as an Energy Repository. Cancer Res. 2014, 74, 330–340. [Google Scholar] [CrossRef] [Green Version]
  40. Pasini, E.; Aquilani, R.; Testa, C.; Baiardi, P.; Angioletti, S.; Boschi, F.; Verri, M.; Dioguardi, F. Pathogenic Gut Flora in Patients with Chronic Heart Failure. JACC: Heart Fail. 2016, 4, 220–227. [Google Scholar] [CrossRef]
  41. Koppe, L.; Mafra, D.; Fouque, D. Probiotics and chronic kidney disease. Kidney Int. 2015, 88, 958–966. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  42. Vaziri, N.D.; Yuan, J.; Norris, K. Role of Urea in Intestinal Barrier Dysfunction and Disruption of Epithelial Tight Junction in Chronic Kidney Disease. Am. J. Nephrol. 2013, 37, 1–6. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Chacko, A.; Cummings, J.H. Nitrogen losses from the human small bowel: Obligatory losses and the effect of physical form of food. Gut 1988, 29, 809–815. [Google Scholar] [CrossRef] [Green Version]
  44. Crenn, P.; Messing, B.; Cynober, L. Citrulline as a biomarker of intestinal failure due to enterocyte mass reduction. Clin. Nutr. 2008, 27, 328–339. [Google Scholar] [CrossRef] [PubMed]
  45. Levillain, O.; Hus-Citharel, A.; Morel, F.; Bankir, L. Localization of arginine synthesis along rat nephron. Am. J. Physiol. Physiol. 1990, 259, F916–F923. [Google Scholar] [CrossRef] [PubMed]
  46. Azuma, J.; Sawamura, A.; Awata, N.; Ohta, H.; Hamaguchi, T.; Harada, H.; Takihara, K.; Hasegawa, H.; Yamagami, T.; Ishiyama, T.; et al. Therapeutic effect of taurine in congestive heart failure: A double-blind crossover trial. Clin. Cardiol. 1985, 8, 276–282. [Google Scholar] [CrossRef]
  47. Aquilani, R.; La Rovere, M.T.; Febo, O.; Boschi, F.; Iadarola, P.; Corbellini, D.; Viglio, S.; Bongiorno, A.I.; Pastoris, O.; Verri, M. Preserved muscle protein metabolism in obese patients with chronic heart failure. Int. J. Cardiol. 2012, 160, 102–108. [Google Scholar] [CrossRef]
  48. Essig, M.; Escoubet, B.; De Zuttere, D.; Blanchet, F.; Arnoult, F.; Dupuis, E.; Michel, C.; Mignon, F.; Mentre, F.; Clerici, C.; et al. Cardiovascular remodelling and extracellular fluid excess in early stages of chronic kidney disease. Nephrol. Dial. Transplant. 2008, 23, 239–248. [Google Scholar] [CrossRef] [Green Version]
  49. Plumley, D.A.; Austgen, T.R.; Salloum, R.M.; Souba, W.W. Role of the Lungs in Maintaining Amino Acid Homeostasis. J. Parenter. Enter. Nutr. 1990, 14, 569–573. [Google Scholar] [CrossRef]
  50. Aquilani, R.; La Rovere, M.T.; Febo, O.; Baiardi, P.; Boschi, F.; Iadarola, P.; Viglio, S.; Dossena, M.; Bongiorno, A.I.; Pastoris, O.; et al. Lung anabolic activity in patients with chronic heart failure: Potential implications for clinical practice. Nutrients 2012, 28, 1002–1007. [Google Scholar] [CrossRef]
  51. Griffin, S.V.; Shankland, S.J. Renal hyperplasia and hypertrophy. In Seldin and Giebisch’s The Kidney: Physiology and Pathophysiology, 4th ed.; Alpern, R.J., Hebert, S.C., Eds.; Academic Press: Cambridge, MA, USA, 2008; Volume 1, pp. 723–742. [Google Scholar]
  52. Garibotto, G. Kidney Protein Dynamics and Ammoniagenesis in Humans with Chronic Metabolic Acidosis. J. Am. Soc. Nephrol. 2004, 15, 1606–1615. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  53. Dolan, E.; Saunders, B.; Harris, R.C.; Bicudo, J.E.P.W.; Bishop, D.J.; Sale, C.; Gualano, B. Comparative physiology investigations support a role for histidine-containing dipeptides in intracellular acid–base regulation of skeletal muscle. Comp. Biochem. Physiol. Part. A Mol. Integr. Physiol. 2019, 234, 77–86. [Google Scholar] [CrossRef] [PubMed]
  54. Liu, Z.; Barrett, E.J. Human protein metabolism: Its measurement and regulation. Am. J. Physiol. Metab. 2002, 283, E1105–E1112. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Levine, B.; Kalman, J.; Mayer, L.; Fillit, H.M.; Packer, M. Elevated Circulating Levels of Tumor Necrosis Factor in Severe Chronic Heart Failure. N. Engl. J. Med. 1990, 323, 236–241. [Google Scholar] [CrossRef]
  56. Rao, M.; Wong, C.; Kanetsky, P.A.; Girndt, M.; Stenvinkel, P.; Reilly, M.P.; Raj, D.S.C. Cytokine gene polymorphism and progression of renal and cardiovascular diseases. Kidney Int. 2007, 72, 549–556. [Google Scholar] [CrossRef] [Green Version]
  57. Zoico, E.; Roubenoff, R. The Role of Cytokines in Regulating Protein Metabolism and Muscle Function. Nutr. Rev. 2002, 60, 39–51. [Google Scholar] [CrossRef]
  58. Li, Y.-P.; Schwartz, R.J.; Waddell, I.D.; Holloway, B.R.; Reid, M.B. Skeletal muscle myocytes undergo protein loss and reactive oxygen-mediated NF-κB activation in response to tumor necrosis factor α. FASEB J. 1998, 12, 871–880. [Google Scholar] [CrossRef]
  59. Vary, T.C.; Owens, E.L.; Beers, J.K.; Verner, K.; Cooney, R.N. Sepsis Inhibits Synthesis of Myofibrillar And Sarcoplasmic Proteins. Shock 1996, 6, 13–18. [Google Scholar] [CrossRef]
  60. Guttridge, D.C.; Mayo, M.W.; Madrid, L.V.; Wang, C.-Y., Jr. NF-kappa B-Induced Loss of MyoD Messenger RNA: Possible Role in Muscle Decay and Cachexia. Science 2000, 289, 2363–2366. [Google Scholar] [CrossRef] [Green Version]
  61. Li, X.; Moody, M.R.; Engel, D.J.; Walker, S.; Clubb, F.J.; Sivasubramanian, N.; Mann, D.L.; Reid, M.B. Cardiac-Specific Overexpression of Tumor Necrosis Factor-α Causes Oxidative Stress and Contractile Dysfunction in Mouse Diaphragm. Circulation 2000, 102, 1690–1696. [Google Scholar] [CrossRef] [Green Version]
  62. Ebisui, C.; Tsujinaka, T.; Morimoto, T.; Kan, K.; Iijima, S.; Yano, M.; Kominami, E.; Tanaka, K.; Monden, M. Interleukin-6 Induces Proteolysis by Activating Intracellular Proteases (Cathepsins B and L, Proteasome) in C2C12 Myotubes. Clin. Sci. 1995, 89, 431–439. [Google Scholar] [CrossRef]
  63. Ritz, E. Intestinal-Renal Syndrome: Mirage or Reality? Blood Purif. 2011, 31, 70–76. [Google Scholar] [CrossRef]
  64. Adey, D.; Kumar, R.; McCarthy, J.T.; Nair, K.S. Reduced synthesis of muscle proteins in chronic renal failure. Am. J. Physiol. Metab. 2000, 278, E219–E225. [Google Scholar] [CrossRef] [Green Version]
  65. Sharma, K.; Mogensen, K.M.; Robinson, M.K. Pathophysiology of Critical Illness and Role of Nutrition. Nutr. Clin. Pract. 2019, 34, 12–22. [Google Scholar] [CrossRef] [Green Version]
  66. Jünger, M.; Steins, A.; Hahn, M.; Häfner, H.-M. Microcirculatory Dysfunction in Chronic Venous Insufficiency (CVI). Microcirculation 2000, 7, 3–12. [Google Scholar] [CrossRef]
  67. Garibotto, G.; Russo, R.; Sofia, A.; Sala, M.R.; Robaudo, C.; Moscatelli, P.; Deferrari, G.; Tizianello, A. Skeletal muscle protein synthesis and degradation in patients with chronic renal failure. Kidney Int. 1994, 45, 1432–1439. [Google Scholar] [CrossRef] [Green Version]
  68. Cicoira, M.; Kalra, P.R.; Anker, S.D. Growth hormone resistance in chronic heart failure and its therapeutic implications. J. Card. Fail. 2003, 9, 219–226. [Google Scholar] [CrossRef]
  69. Kobayashi, S.; Maesato, K.; Moriya, H.; Ohtake, T.; Ikeda, T. Insulin resistance in patients with chronic kidney disease. Am. J. Kidney Dis. 2005, 45, 275–280. [Google Scholar] [CrossRef] [PubMed]
  70. Liu, Z.; Long, W.; Fryburg, D.A.; Barrett, E.J. The Regulation of Body and Skeletal Muscle Protein Metabolism by Hormones and Amino Acids. J. Nutr. 2006, 136, 212S–217S. [Google Scholar] [CrossRef] [Green Version]
  71. Guazzi, M.; Gatto, P.; Giusti, G.; Pizzamiglio, F.; Previtali, I.; Vignati, C.; Arena, R. Pathophysiology of cardiorenal syndrome in decompensated heart failure: Role of lung–right heart–kidney interaction. Int. J. Cardiol. 2013, 169, 379–384. [Google Scholar] [CrossRef] [PubMed]
  72. Hanberg, J.S.; Sury, K.; Wilson, F.P.; Brisco, M.A.; Ahmad, T.; Ter Maaten, J.M.; Broughton, J.S.; Assefa, M.; Tang, W.W.; Parikh, C.R.; et al. Reduced Cardiac Index Is Not the Dominant Driver of Renal Dysfunction in Heart Failure. J. Am. Coll. Cardiol. 2016, 67, 2199–2208. [Google Scholar] [CrossRef] [PubMed]
  73. Aquilani, R.; Maestri, R.; Boselli, M.; Achilli, M.P.; Arrigoni, N.; Bruni, M.; Dossena, M.; Verri, M.; Buonocore, D.; Pasini, E.; et al. The relationship between plasma amino acids and circulating albumin and haemoglobin in postabsorptive stroke patients. PLoS ONE 2019, 14, e0219756. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  74. Anagnostou, A.; Schade, S.; Ashkinaz, M.; Barone, J.; Fried, W. Effect of protein deprivation on erythropoiesis. Blood 1977, 50, 1093–1097. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  75. Calder, P.C. Branched-Chain Amino Acids and Immunity. J. Nutr. 2006, 136, 288S–293S. [Google Scholar] [CrossRef] [PubMed]
  76. Li, P.; Yin, Y.-L.; Li, D.; Kim, S.W.; Wu, G. Amino acids and immune function. Br. J. Nutr. 2007, 98, 237–252. [Google Scholar] [CrossRef] [Green Version]
  77. Rennie, M.J.; Bohé, J.; Smith, K.; Wackerhage, H.; Greenhaff, P. Branched-Chain Amino Acids as Fuels and Anabolic Signals in Human Muscle. J. Nutr. 2006, 136, 264S–268S. [Google Scholar] [CrossRef]
  78. Cano, N.J.M.; Fouque, D.; Leverve, X.M. Application of Branched-Chain Amino Acids in Human Pathological States: Renal Failure. J. Nutr. 2006, 136, 299S–307S. [Google Scholar] [CrossRef] [Green Version]
  79. Krajmalnik-Brown, R.; Ilhan, Z.-E.; Kang, D.-W.; DiBaise, J.K. Effects of Gut Microbes on Nutrient Absorption and Energy Regulation. Nutr. Clin. Pr. 2012, 27, 201–214. [Google Scholar] [CrossRef] [Green Version]
  80. Cohen, J.J. Disorders of Hydrogen Ion Metabolism. In Strauss and Welt’s Diseases of the Kidney, 3rd ed.; Early, L.E., Gottschalk, C.W., Eds.; Little Brown: Boston, MA, USA, 1979; pp. 1543–1579. [Google Scholar]
  81. Condino, A.M.; Aquilani, R.; Pasini, E.; Iadarola, P.; Viglio, S.; Verri, M.; D’Agostino, L.; Boschi, F. Plasma kinetic of ingested essential amino acids in healthy elderly people. Aging Clin. Exp. Res. 2013, 25, 711–714. [Google Scholar] [CrossRef]
  82. Aquilani, R.; Opasich, C.; Gualco, A.; Verri, M.; Testa, A.; Pasini, E.; Viglio, S.; Iadarola, P.; Pastoris, O.; Dossena, M.; et al. Adequate energy-protein intake is not enough to improve nutritional and metabolic status in muscle-depleted patients with chronic heart failure. Eur. J. Hear. Fail. 2008, 10, 1127–1135. [Google Scholar] [CrossRef]
  83. Aquilani, R.; D’Antona, G.; Baiardi, P.; Gambino, A.; Iadarola, P.; Viglio, S.; Pasini, E.; Verri, M.; Barbieri, A.; Boschi, F. Essential Amino Acids and Exercise Tolerance in Elderly Muscle-Depleted Subjects with Chronic Diseases: A Rehabilitation without Rehabilitation? BioMed Res. Int. 2014, 2014, 1–8. [Google Scholar] [CrossRef]
  84. Ikizler, T.A.; Cano, N.J.; Franch, H.; Fouque, D.; Himmelfarb, J.; Kalantar-Zadeh, K.; Kuhlmann, M.K.; Stenvinkel, P.; TerWee, P.; Teta, D.; et al. Prevention and treatment of protein energy wasting in chronic kidney disease patients: A consensus statement by the International Society of Renal Nutrition and Metabolism. Kidney Int. 2013, 84, 1096–1107. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  85. Wilkinson, T.J.; Shur, N.F.; Smith, A.C. “Exercise as medicine” in chronic kidney disease. Scand. J. Med. Sci. Sports 2016, 26, 985–988. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  86. Müller-Ortiz, H.; Pedreros-Rosales, C.; Vera-Calzaretta, A.; González-Burboa, A.; Martín, C.Z.-S.; Oliveros-Romero, M.S. Exercise training in advanced chronic kidney disease. Revista Médica De Chile 2019, 147, 1443–1448. [Google Scholar] [CrossRef]
  87. Aquilani, R.; Opasich, C.; Dossena, M.; Iadarola, P.; Gualco, A.; Arcidiaco, P.; Viglio, S.; Boschi, F.; Verri, M.; Pasini, E. Increased skeletal muscle amino acid release with light exercise in deconditioned patients with heart failure. J. Am. Coll. Cardiol. 2005, 45, 158–160. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  88. Nystrom, E.M.; Nei, A.M. Metabolic Support of the Patient on Continuous Renal Replacement Therapy. Nutr. Clin. Pract. 2018, 33, 754–766. [Google Scholar] [CrossRef] [PubMed]
  89. Cicoira, M.; Anker, S.D.; Ronco, C. Cardio-renal cachexia syndromes (CRCS): Pathophysiological foundations of a vicious pathological circle. J. Cachex Sarcopenia Muscle 2011, 2, 135–142. [Google Scholar] [CrossRef] [Green Version]
  90. Petra, E.; Zoidakis, J.; Vlahou, A. Protein biomarkers for cardiorenal syndrome. Expert Rev. Proteom. 2019, 16, 325–336. [Google Scholar] [CrossRef]
  91. Vianello, A.; Caponi, L.; Galetta, F.; Franzoni, F.; Taddei, M.; Rossi, M.; Pietrini, P.; Santoro, G. β2-Microglobulin and TIMP1 Are Linked Together in Cardiorenal Remodeling and Failure. Cardiorenal Med. 2015, 5, 1–11. [Google Scholar] [CrossRef] [Green Version]
  92. Jungbauer, C.G.; Uecer, E.; Stadler, S.; Birner, C.; Buchner, S.; Maier, L.S.; Luchner, A. N-acteyl-ß-D-glucosaminidase and kidney injury molecule-1: New predictors for long-term progression of chronic kidney disease in patients with heart failure. Nephrology 2016, 21, 490–498. [Google Scholar] [CrossRef] [PubMed]
  93. Bonventre, J.V. Kidney injury molecule-1 (KIM-1): A urinary biomarker and much more. Nephrol. Dial. Transplant. 2009, 24, 3265–3268. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Table
Table 1. Demographic, anthropometric and clinical characteristics, functional class, etiology, biohumoral variables, cardiac hemodynamic variables and renal function tests of the studied cardiorenal syndrome type 2 (CRS 2) patients.
Table 1. Demographic, anthropometric and clinical characteristics, functional class, etiology, biohumoral variables, cardiac hemodynamic variables and renal function tests of the studied cardiorenal syndrome type 2 (CRS 2) patients.
VariablesAll-CRS 2 (N = 16)
Demographics
Age (years)56.5 ± 8.5
Sex (male/female)11/5
Anthropometrics
Body weight (kg)76.0 ± 15.2
BMI (kg/m2)26.3 ± 3.9
Blood
Glucose (mg/dL; NV = 80–110)96.3 ± 14.1
Albumin (g/dL; NV = 3.5–5)4.3 ± 0.4
Hemoglobin (g/dL; NV = 12–15)13.0 ± 2.2
Sodium (mEq/L; NV = 135–145)136.4 ± 3.5
Potassium (mEq/L; NV = 3.5–5.0)4.1 ± 0.6
NT-pro-BNP2940.9 ± 1865.4
(pg/mL; NV < 125 for age < 75 years)
Clinical characteristics
Medication
β blockers16 pts (100%)
Diuretics16 pts (100%)
ACE inhibition14 pts (87.5%)
Digoxin7 pts (43.7%)
Functional class
NYHA3.2 ± 0.5
Etiology
Ischemic10 pts (62.5%)
Idiopathic dilated cardiomyopathy4 pts (25%)
Valvular2 pts (12.5%)
Arterial blood pressure
Systolic blood pressure (mm Hg)108.4 ± 12.3
Diastolic blood pressure (mm Hg)65.5 ± 11.4
Hemodynamic variables
CI (L/min/m2)2.1 ± 0.4
SV (mL/beat)61.5 ± 13.7
SVI (mL/beat/m2)32.8 ± 7.5
LVEF (%; NV > 55)29.3 ± 12.0
Physical performance
VO2 rest (mL O2/kg/min)3.5 ± 0.8
VO2 peak (mL O2/kg/min)11.8 ± 2.9
RER peak1.10 ± 0.03
Renal function tests
Creatinine (mg/dL; NV = 0.6–1.2)1.42 ± 0.18
eGFR (mL/min/1.73 m2)54.9 ± 19.3
Urea (mg/dL; NV = 20–40)68.2 ± 46.2
Data are given as mean ± SD, except for gender. Abbreviations: CRS 2, cardiorenal syndrome type 2; BMI, body mass index; NT-pro-BNP, N-terminal pro-B-type natriuretic peptide; NYHA, New York Heart Association; CI, cardiac index; SV, stroke volume; SVI, stroke volume index; LVEF, left ventricular ejection fraction; NV, normal value; VO2, oxygen consumption; RER, respiratory exchange ratio; eGFR, estimated glomerular filtration rate.
Table
Table 2. Plasma arterial AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
Table 2. Plasma arterial AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
VariableC (N = 8)CRS 2 (N = 16)p-Value
Aspartic acid112.1 ± 8.85829.83 ± 14.23<0.0001
Glutamic acid198.63 ± 10.6184.97 ± 26.72<0.0001
Asparagine61.04 ± 1.9923.60 ± 11.17<0.0001
Serine88.39 ± 4.2523.17 ± 8.01<0.0001
Glutamine464.88 ± 13.98100.64 ± 43.78<0.0001
Histidine58.00 ± 5.1523.02 ± 33.440.014
Glycine268.25 ± 11.9749.08 ± 16.79<0.0001
Threonine111.6 ± 7.320.62 ± 10.00<0.0001
Citrulline24.57 ± 3.666.42 ± 1.73<0.0001
Alanine312.63 ± 15.6772.28 ± 20.20<0.0001
Arginine59.27 ± 7.6127.23 ± 11.360.00019
Tyrosine56.25 ± 6.1116.12 ± 3.90<0.0001
Cysteine77.13 ± 5.1415.47 ± 6.37<0.0001
Valine160.0 ± 15.849.84 ± 12.79<0.0001
Methionine9.7 ± 2.83.22 ± 1.49<0.0001
Tryptophan50.1 ± 4.915.64 ± 7.93<0.0001
Phenylalanine51.3 ± 5.111.61 ± 3.17<0.0001
Isoleucine47.4 ± 4.110.61 ± 3.35<0.0001
Leucine79.1 ± 8.521.03 ± 6.93<0.0001
Lysine107 ± 11.437.65 ± 12.95<0.0001
Ornithine56.38 ± 6.3963.88 ± 20.730.36
TAAs2453.78 ± 49.54626.56 ± 176.22<0.0001
BCAAs286.5 ± 13.5781.47 ± 22.41<0.0001
EAAs612.2 ± 20.3170.21 ± 48.64<0.0001
Data are given as mean ± SD. Reported p-values are from Mann–Whitney U-test. AA, amino acid; C, controls; CRS 2, cardiorenal syndrome type 2; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 3. Plasma venous AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
Table 3. Plasma venous AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
VariableC (N = 8)CRS 2 (N = 16)p-Value
Aspartic acid111.83 ± 10.4843.48 ± 15.53<0.0001
Glutamic acid206.13 ± 11.15154.01 ± 52.320.004
Asparagine112.65 ± 157.3941.27 ± 10.380.001
Serine90.83 ± 4.2142.10 ± 14.69<0.0001
Glutamine467.25 ± 11.67128.17 ± 31.67<0.0001
Histidine58.38 ± 6.0237.92 ± 27.400.043
Glycine258.38 ± 27.5490.67 ± 38.11<0.0001
Threonine106.63 ± 11.1028.83 ± 8.42<0.0001
Citrulline25.07 ± 2.909.77 ± 3.26<0.0001
Alanine327.63 ± 15.60125.82 ± 37.67<0.0001
Arginine59.44 ± 5.8536.21 ± 16.750.001
Tyrosine51.75 ± 5.7036.04 ± 12.970.003
Cysteine79.38 ± 7.7626.00 ± 27.580.0006
Valine153.88 ± 13.4879.44 ± 26.50<0.0001
Methionine10.75 ± 1.756.61 ± 3.470.003
Tryptophan51.13 ± 4.6435.09 ± 15.890.003
Phenylalanine46.25 ± 5.6822.99 ± 7.37<0.0001
Isoleucine45.75 ± 5.0119.27 ± 5.27<0.0001
Leucine78.13 ± 6.3643.50 ± 12.10<0.0001
Lysine115.75 ± 11.0359.02 ± 17.97<0.0001
Ornithine55.38 ± 6.7298.37 ± 30.200.0009
TAAs2377.56 ± 151.781040.19 ± 210.78<0.0001
BCAAs277.75 ± 12.96142.21 ± 42.71<0.0001
EAAs608.25 ± 19.95294.75 ± 71.74<0.0001
Data are given as mean ± SD. Reported p-values are from Mann–Whitney U-test. AA, amino acid; C, controls; CRS 2, cardiorenal syndrome type 2; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 4. (A-V) AA differences (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
Table 4. (A-V) AA differences (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
Variable(A-V) C (N = 8)(A-V) CRS 2 (N = 16)p-Value
Aspartic acid0.27 ± 14.35−13.65 ± 20.730.10
Glutamic acid−7.50 ± 21.05−69.04 ± 70.600.027
Asparagine−51.61 ± 157.21−17.67 ± 16.030.023
Serine−2.44 ± 6.45−18.93 ± 18.590.032
Glutamine−2.38 ± 23.05−27.53 ± 54.470.08
Histidine−0.38 ± 5.04−14.90 ± 48.430.023
Glycine9.88 ± 29.98−41.60 ± 32.730.001
Threonine4.97 ± 14.84−8.21 ± 10.400.11
Citrulline−0.50 ± 5.65−3.35 ± 2.670.14
Alanine−15.00 ± 20.54−53.53 ± 38.400.012
Arginine−0.16 ± 10.21−8.98 ± 14.610.14
Tyrosine4.50 ± 9.10−19.92 ± 13.230.0006
Cysteine−2.25 ± 8.10−10.53 ± 27.130.95
Valine6.12 ± 19.39−29.60 ± 25.150.017
Methionine−1.05 ± 1.93−3.39 ± 4.450.037
Tryptophan−1.03 ± 7.65−19.45 ± 18.860.008
Phenylalanine5.05 ± 6.56−11.38 ± 7.940.006
Isoleucine1.65 ± 5.72−8.66 ± 5.960.023
Leucine0.97 ± 7.25−22.47 ± 14.060.002
Lysine−8.75 ± 16.73−21.37 ± 21.050.020
Ornithine1.00 ± 10.49−34.50 ± 32.730.004
TAAs76.22 ± 138.9−413.63 ± 333.210.020
BCAAs8.75 ± 23.87−60.74 ± 43.950.006
EAAs7.95 ± 24.07−124.54 ± 92.020.004
Data are given as mean ± SD. Reported p-values are from Mann–Whitney U-test. AA, amino acid; A, arterial AA concentration; V, venous AA concentration; C, controls; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 5. Plasma arterial/venous ratios (%) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
Table 5. Plasma arterial/venous ratios (%) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients.
VariableRatio C (N = 8)Ratio CRS 2 (N = 16)p-Value
Aspartic acid1.00 ± 0.130.77 ± 0.480.09
Glutamic acid0.97 ± 0.100.87 ± 1.220.027
Asparagine0.96 ± 0.350.62 ± 0.330.032
Serine0.98 ± 0.070.63 ± 0.330.017
Glutamine1.00 ± 0.050.84 ± 0.440.10
Histidine1.00 ± 0.090.61 ± 0.110.014
Glycine1.05 ± 0.130.97 ± 1.710.0006
Threonine1.05 ± 0.140.75 ± 0.370.014
Citrulline1.00 ± 0.240.70 ± 0.210.010
Alanine0.96 ± 0.060.61 ± 0.230.003
Arginine1.01 ± 0.170.83 ± 0.340.09
Tyrosine1.10 ± 0.170.53 ± 0.330.002
Cysteine0.98 ± 0.110.93 ± 0.450.54
Valine1.04 ± 0.120.68 ± 0.260.008
Methionine0.90 ± 0.170.78 ± 0.900.017
Tryptophan0.98 ± 0.150.56 ± 0.470.020
Phenylalanine1.11 ± 0.150.56 ± 0.280.002
Isoleucine1.04 ± 0.130.59 ± 0.260.002
Leucine1.01 ± 0.090.53 ± 0.280.002
Lysine0.92 ± 0.140.68 ± 0.280.007
Ornithine1.03 ± 0.190.70 ± 0.270.007
TAAs1.03 ± 0.060.65 ± 0.290.008
BCAAs1.03 ± 0.090.62 ± 0.260.003
EAAs1.00 ± 0.040.62 ± 0.280.003
Data are given as mean ± SD. Reported p-values are from Mann–Whitney U-test. C, controls; CRS 2, cardiorenal syndrome type 2; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 6. Plasma arterial AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
Table 6. Plasma arterial AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
VariableC (N = 8)M-CKD eGFR ≥ 60 mL/min/1.73 m2 (N = 5)MS-CKD eGFR < 60 mL/min/1.73 m2 (N = 11)p-Valuep-Value C vs. M-CKDp-Value C vs. MS-CKDp-Value M-CKD vs. MS-CKD
Aspartic acid112.1 ± 8.85830.49 ± 19.7629.53 ± 12.130.000460.0090.00071.00
Glutamic acid198.63 ± 10.6180.48 ± 29.0887.01 ± 26.800.000450.0050.0010.99
Asparagine61.04 ± 1.9920.21 ± 9.2025.13 ± 12.040.000400.0030.0020.94
Serine88.39 ± 4.2521.80 ± 8.9723.79 ± 7.920.000460.0070.00091.00
Glutamine464.88 ± 13.98100.16 ± 33.41100.86 ± 49.280.000450.0130.00061.00
Histidine58.00 ± 5.1521.52 ± 32.0223.71 ± 35.570.0500.180.0661.00
Glycine268.25 ± 11.9747.53 ± 18.6649.78 ± 16.790.000460.0090.00071.00
Threonine111.6 ± 7.321.63 ± 8.8820.16 ± 10.850.000450.0150.00050.99
Citrulline24.57 ± 3.665.98 ± 2.486.62 ± 1.370.000440.0040.0010.98
Alanine312.63 ± 15.6767.30 ± 7.5874.55 ± 23.890.000460.0070.00091.00
Arginine59.27 ± 7.6128.52 ± 17.0226.64 ± 8.750.00090.0110.0021.00
Tyrosine56.25 ± 6.1114.81 ± 3.7416.72 ± 3.990.000350.0020.0020.85
Cysteine77.13 ± 5.1412.73 ± 6.3216.72 ± 6.270.000370.0020.0020.89
Valine160.0 ± 15.847.73 ± 12.9550.80 ± 13.240.000440.0050.0010.99
Methionine9.7 ± 2.83.12 ± 1.273.26 ± 1.640.000430.0040.0010.98
Tryptophan50.1 ± 4.917.44 ± 11.5314.82 ± 6.220.000460.0080.00081.00
Phenylalanine51.3 ± 5.19.99 ± 2.4112.35 ± 3.300.000330.0010.0020.81
Isoleucine47.4 ± 4.110.41 ± 2.5310.70 ± 3.780.000450.0060.0011.00
Leucine79.1 ± 8.519.98 ± 6.2821.50 ± 7.450.000430.0040.0010.98
Lysine107 ± 11.432.37 ± 7.3440.05 ± 14.480.000370.0020.0020.89
Ornithine56.38 ± 6.3960.34 ± 28.5465.48 ± 17.590.43---
TAAs2453.78 ± 49.54601.46 ± 166.72637.97 ± 187.100.000460.0070.00091.00
BCAAs286.5 ± 13.5778.12 ± 20.7583.00 ± 23.940.000450.0050.0010.99
EAAs612.2 ± 20.3162.67 ± 45.03173.63 ± 51.920.000460.0070.00091.00
Data are given as mean ± SD. Reported p-values are from Kruskal–Wallis test. Post hoc p-values (Dunn–Sidak adjustment) are reported for the following comparisons: controls vs. mild chronic kidney disease (C vs. M-CKD), controls vs. moderate-severe chronic kidney disease (C vs. MS-CKD) and mild chronic kidney disease vs. moderate-severe chronic kidney disease (M-CKD vs. MS-CKD). AA, amino acid; C, controls; CRS 2, cardiorenal syndrome type 2; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; M-CKD, mild CKD; MS-CKD, moderate-severe CKD; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 7. Plasma venous AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
Table 7. Plasma venous AA concentrations (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
VariableC (N = 8)M-CKD eGFR ≥ 60 mL/min/1.73 m2 (N = 5)MS-CKD eGFR < 60 mL/min/1.73 m2 (N = 11)p-Valuep-Value C vs. M-CKDp-Value C vs. MS-CKDp-Value M-CKD vs. MS-CKD
Aspartic acid111.83 ± 10.4836.54 ± 15.1046.63 ± 15.350.000290.00100.0030.71
Glutamic acid206.13 ± 11.15155.13 ± 34.08153.49 ± 60.340.0140.0340.0370.94
Asparagine112.65 ± 157.3939.04 ± 11.2342.2 8 ± 10.370.0050.0170.0130.96
Serine90.83 ± 4.2143.43 ± 20.0941.49 ± 12.690.000450.0060.0011.00
Glutamine467.25 ± 11.67130.22 ± 28.59127.24 ± 34.270.000440.0150.00050.99
Histidine58.38 ± 6.0238.37 ± 27.6337.72 ± 28.640.12---
Glycine258.38 ± 27.5496.28 ± 51.7988.13 ± 32.900.000440.0180.000480.98
Threonine106.63 ± 11.1033.64 ± 6.9826.64 ± 8.370.000310.0480.000210.76
Citrulline25.07 ± 2.908.27 ± 3.6510.45 ± 2.990.000340.0010.0020.81
Alanine327.63 ± 15.60126.17 ± 48.59125.65 ± 34.400.000440.0050.0010.99
Arginine59.44 ± 5.8532.47 ± 8.9137.91 ± 19.470.0050.0170.0130.96
Tyrosine51.75 ± 5.7032.30 ± 9.9637.74 ± 14.230.0080.0140.0380.78
Cysteine79.38 ± 7.7611.81 ± 5.8332.45 ± 31.320.00100.0010.0230.38
Valine153.88 ± 13.4878.79 ± 32.2579.74 ± 25.250.000460.0070.00091.00
Methionine10.75 ± 1.756.45 ± 3.296.68 ± 3.700.0130.0620.0211.00
Tryptophan51.13 ± 4.6431.57 ± 10.1936.69 ± 18.120.0130.0420.0270.98
Phenylalanine46.25 ± 5.6820.59 ± 8.9124.08 ± 6.750.000400.0030.0020.94
Isoleucine45.75 ± 5.0119.25 ± 6.3119.28 ± 5.070.000460.0070.00091.00
Leucine78.13 ± 6.3643.58 ± 13.9943.46 ± 11.890.000460.0090.00071.00
Lysine115.75 ± 11.0362.10 ± 23.1457.62 ± 16.230.000460.0090.00071.00
Ornithine55.38 ± 6.7299.14 ± 35.4798.02 ± 29.400.0040.0280.0071.00
TAAs2377.56 ± 151.781034.19 ± 248.631042.92 ± 204.670.000460.0080.00081.00
BCAAs277.75 ± 12.96141.62 ± 51.16142.48 ± 41.100.000450.0060.0011.00
EAAs608.25 ± 19.95295.97 ± 86.42294.19 ± 68.790.000460.0080.00081.00
Data are given as mean ± SD. Reported p-values are from Kruskal–Wallis test. Post hoc p-values (Dunn–Sidak adjustment) are reported for the following comparisons: controls vs. mild chronic kidney disease (C vs. M-CKD), controls vs. moderate-severe chronic kidney disease (C vs. MS-CKD) and mild chronic kidney disease vs. moderate-severe chronic kidney disease (M-CKD vs. MS-CKD). AA, amino acid; C, controls; CRS 2, cardiorenal syndrome type 2; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; M-CKD, mild CKD; MS-CKD, moderate-severe CKD; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 8. (A-V) AA differences (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
Table 8. (A-V) AA differences (µmol/L) in controls (C) and cardiorenal syndrome type 2 (CRS 2) patients after stratification for eGFR ≥ 60 mL/min/1.73 m2 (mild CKD: M-CKD) and eGFR < 60 mL/min/1.73 m2 (moderate-severe CKD: MS-CKD).
VariableC (N = 8)M-CKD eGFR ≥ 60 mL/min/1.73 m2 (N = 5)MS-CKD eGFR < 60 mL/min/1.73 m2 (N=11)p-Valuep-Value C vs. M-CKDp-Value C vs. MS-CKDp-Value M-CKD vs. MS-CKD
Aspartic acid0.27 ± 14.35−6.05 ± 21.62−17.10 ± 20.380.14---
Glutamic acid−7.50 ± 21.05−74.65 ± 56.04−66.48 ±7 8.730.09---
Asparagine−51.61 ± 157.21−18.83 ± 11.79−17.14 ± 18.130.067---
Serine−2.44 ± 6.45−21.63 ± 24.06−17.71 ± 16.770.10---
Glutamine−2.38 ± 23.05−30.06 ± 53.39−26.38 ± 57.490.19---
Histidine−0.38 ± 5.04−16.86 ± 29.60−14.01 ± 56.250.057---
Glycine9.88 ± 29.98−48.74 ± 45.88−38.35 ± 26.970.0060.0510.0081.00
Threonine4.97 ± 14.84−12.01 ± 9.50−6.48 ± 10.760.19---
Citrulline−0.50 ± 5.65−2.30 ± 1.98−3.83 ± 2.890.22---
Alanine−15.00 ± 20.54−58.87 ± 51.47−51.10 ± 33.640.0420.130.0641.00
Arginine−0.16 ± 10.21−3.94 ± 16.48−11.27 ± 13.900.25---
Tyrosine4.50 ± 9.10−17.49 ± 13.04−21.02 ± 13.800.0030.0540.0030.97
Cysteine−2.25 ± 8.100.92 ± 4.04−15.73 ± 31.660.56---
Valine6.12 ± 19.39−31.06 ± 25.46−28.94 ± 26.230.057---
Methionine−1.05 ± 1.93−3.33 ± 4.43−3.42 ± 4.680.11---
Tryptophan−1.03 ± 7.65−14.13 ± 17.42−21.87 ± 19.780.0260.290.0220.91
Phenylalanine5.05 ± 6.56−10.60 ± 7.40−11.73 ± 8.500.0220.160.0230.99
Isoleucine1.65 ± 5.72−8.84 ± 6.88−8.58 ± 5.860.08---
Leucine0.97 ± 7.25−23.60 ± 16.03−21.96 ± 13.880.0090.0300.0190.98
Lysine−8.75 ± 16.73−29.74 ± 26.63−17.57 ± 18.170.056---
Ornithine1.00 ± 10.49−38.80 ± 44.59−32.54 ± 28.250.0160.100.0201.00
TAAs76.22 ± 138.9−432.73 ± 384.01−404.95 ± 327.560.065---
BCAAs8.75 ± 23.87−63.50 ± 47.20−59.48 ± 44.730.0220.080.0371.00
EAAs7.95 ± 24.07−133.30 ± 100.00−120.56 ± 92.980.0140.0340.0370.94
Data are given as mean ± SD. Reported p-values are from Kruskal–Wallis test. Post hoc p-values (Dunn–Sidak adjustment) are reported for the following comparisons: controls vs. mild chronic kidney disease (C vs. M-CKD), controls vs. moderate-severe chronic kidney disease (C vs. MS-CKD) and mild chronic kidney disease vs. moderate-severe chronic kidney disease (M-CKD vs. MS-CKD). AA, amino acid; A, arterial AA concentration; V, venous AA concentration; C, controls; CRS 2, cardiorenal syndrome type 2; eGFR, estimated glomerular filtration rate; CKD, chronic kidney disease; M-CKD, mild CKD; MS-CKD, moderate-severe CKD; TAAs, total amino acids; BCAAs, branched chain amino acids; EAAs, essential amino acids.
Table
Table 9. Blood non-amino acid variables in mild CKD (M-CKD; eGFR ≥ 60 mL/min/1.73 m2) and moderate-severe CKD (MS-CKD; eGFR < 60 mL/min/1.73 m2) patients.
Table 9. Blood non-amino acid variables in mild CKD (M-CKD; eGFR ≥ 60 mL/min/1.73 m2) and moderate-severe CKD (MS-CKD; eGFR < 60 mL/min/1.73 m2) patients.
VariableM-CKD eGFR ≥ 60 mL/min/1.73 m2 (N = 5)MS-CKD eGFR < 60 mL/min/1.73 m2 (N = 11)p-Values
Serum osmolarity (mOsm/L; NV = 290–320)271.36 ± 5.35277.08 ± 16.380.78
Plasma bilirubin (mg/dL; NV = 0.5–1.0)0.80 ± 0.341.10 ± 0.530.28
Serum sodium (mEq/L; NV = 135–145)137.80 ± 3.11135.82 ± 3.630.31
Serum creatinine (mg/dL; NV = 0.6–1.2)1.02 ± 0.081.60 ± 0.440.002
Serum potassium (mEq/L; NV = 3.5–5.0)4.22 ± 0.594.10 ± 0.580.95
Plasma urea (mg/dL; NV = 20–40)50.80 ± 24.4576.09 ± 52.390.26
Plasma glucose (mg/dL; NV = 80–110)93.20 ± 10.1397.73 ± 15.840.61
Blood hemoglobin (g/dL; NV = 12–15)13.34 ± 2.5312.93 ± 2.180.67
Serum albumin (g/dL; NV = 3.5–5)4.07 ± 0.584.54 ± 0.310.08
Total cholesterol (mg/dL; NV < 200)146.40 ± 22.39162.09 ± 53.350.61
Plasma triglycerides (mg/dL; NV = 60–170)98.40 ± 33.40112.90 ± 71.051.00
Data are given as mean ± SD. Reported p-values are from Mann–Whitney U-test. CKD, chronic kidney disease; M-CKD, mild CKD; MS-CKD, moderate-severe CKD; eGFR, estimated glomerular filtration rate; NV, normal value.
Table
Table 10. Correlation coefficients (Spearman’s r) between plasma arterial concentrations of individual AAs (µmol/L), and renal function and hemodynamic variables.
Table 10. Correlation coefficients (Spearman’s r) between plasma arterial concentrations of individual AAs (µmol/L), and renal function and hemodynamic variables.
eGFR (mL/min/1.73 m2)RAP (mmHg)LVEF (%)LVEDD (mm)LVESD (mm)CI (L/min/m2)
Aspartic acid0.18−0.030.53 ^0.230.210.56 ^
Glutamic acid−0.04−0.080.420.320.290.51
Asparagine−0.110.460.49−0.03−0.040.14
Serine0.02−0.010.260.06−0.050.57 ^
Glutamine0.28−0.040.440.380.280.58 ^
Histidine−0.03−0.140.160.420.340.12
Glycine−0.23−0.12−0.370.050.04−0.06
Threonine0.20−0.330.350.240.140.18
Citrulline−0.29−0.61 ^−0.090.400.370.17
Alanine−0.21−0.51−0.030.59 ^0.490.30
Arginine−0.250.030.210.030.020.40
Tyrosine−0.14−0.060.57 ^−0.10−0.020.21
Cysteine−0.17−0.20.22−0.21−0.09−0.06
Valine0.17−0.300.57 ^0.110.020.22
Methionine−0.09−0.170.19−0.15−0.11−0.12
Tryptophan−0.01−0.170.220.400.380.62 ^
Phenylalanine−0.13−0.060.51 ^0.04−0.100.29
Isoleucine0.28−0.200.64 †0.090.040.41
Leucine0.15−0.410.61 ^0.070.060.34
Lysine−0.13−0.050.50 ^0.050.080.19
Ornithine−0.300.22−0.150.12−0.09−0.11
^: p < 0.05; †: p < 0.01; AA, amino acid; eGFR, estimated glomerular filtration rate; RAP, right atrial pressure; LVEF, left ventricular ejection fraction; LVEDD, left ventricular end-diastolic diameter; LVESD, left ventricular end-systolic diameter; CI, cardiac index.
Table
Table 11. Some examples of potential additive damage to altered physiology of CRS 2 patients from hypoaminoacidemia.
Table 11. Some examples of potential additive damage to altered physiology of CRS 2 patients from hypoaminoacidemia.
Metabolic CompartmentsEffectsMetabolic and Clinical Impacts
Protein synthesis
(a) visceral compartmentreduced albumin synthesis [73]
reduced erythropoietin synthesis [74]
reduced immune cell proliferation, differentiation, function [75,76]		hypoalbuminemia
anemia
impaired immune response
(b) somatic compartment (skeletal muscle tissue)reduced contractile myofibrils [77]sarcopenia, reduced muscle strength
Braindecreased fuel provision
decreased neurotransmitter synthesis [78]		altered cognition, behavior, mood, appetite
Intestine metabolismreduced energy metabolism
reduced protein synthesis [79]		small intestine injury:
mucosal barrier disruption
bacteria/toxins translocation
Kidney metabolismreduced renal mTOR complex signaling [27]increased tubuli mitochondria dysfunction
impaired mitochondria biogenesis
reduced protein synthesis
reduced nucleotide synthesis
increased oxidative stress
Heart metabolismmitochondrial dysfunction
altered myocardium remodeling
increased oxidative stress [10]		inadequate energy production
maladaptive remodeling
reduced left ventricular ejection fraction
Lung metabolismreduced activity of alveolar Na+/K+ pump [50]accumulation of intralveolar fluid
Acid-base balancereduced intracellular protein and AA buffers
alterations in intermediate metabolism [80]		exaltation of intracellular acidosis
reduced energy production
increased oxidative stress
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Aquilani, R.; Maestri, R.; Dossena, M.; La Rovere, M.T.; Buonocore, D.; Boschi, F.; Verri, M. Altered Amino Acid Metabolism in Patients with Cardiorenal Syndrome Type 2: Is It a Problem for Protein and Exercise Prescriptions? Nutrients 2021, 13, 1632. https://doi.org/10.3390/nu13051632

AMA Style

Aquilani R, Maestri R, Dossena M, La Rovere MT, Buonocore D, Boschi F, Verri M. Altered Amino Acid Metabolism in Patients with Cardiorenal Syndrome Type 2: Is It a Problem for Protein and Exercise Prescriptions? Nutrients. 2021; 13(5):1632. https://doi.org/10.3390/nu13051632

Chicago/Turabian Style

Aquilani, Roberto, Roberto Maestri, Maurizia Dossena, Maria Teresa La Rovere, Daniela Buonocore, Federica Boschi, and Manuela Verri. 2021. "Altered Amino Acid Metabolism in Patients with Cardiorenal Syndrome Type 2: Is It a Problem for Protein and Exercise Prescriptions?" Nutrients 13, no. 5: 1632. https://doi.org/10.3390/nu13051632

APA Style

Aquilani, R., Maestri, R., Dossena, M., La Rovere, M. T., Buonocore, D., Boschi, F., & Verri, M. (2021). Altered Amino Acid Metabolism in Patients with Cardiorenal Syndrome Type 2: Is It a Problem for Protein and Exercise Prescriptions? Nutrients, 13(5), 1632. https://doi.org/10.3390/nu13051632

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