Abstract
In end-stage kidney disease requiring hemodialysis, patients at nutritional risk have a poor prognosis. The gut microbiota is important for maintaining the nutritional status of patients. However, it remains unclear whether an altered gut microbiota correlates with increased nutritional risk in patients undergoing hemodialysis. Therefore, we retrospectively analyzed patients who underwent hemodialysis at our hospital between April and December 2022. Nutritional risk was evaluated using the Geriatric Nutritional Risk Index (GNRI), and patients were divided into low- and high-GNRI groups. Patients’ clinical conditions and alterations in the gut microbiota were compared between the two groups. The study included a total of 38 patients with moderate to severe frailty. The low-GNRI group had 18 patients, and the high-GNRI group had 20 patients. The low-GNRI group had more severely frail patients. Serum transthyretin, cholinesterase, total cholesterol, and β2-microglobulin were significantly lower in the low-GNRI group than in the high-GNRI group. Significant differences in the relative abundances of the Actinobacteria and Proteobacteria phyla were observed between the two groups. The genus Bifidobacterium was significantly less abundant in the high-GNRI group than in the low-GNRI group. At the species level, Bifidobacterium adolescentis and Bifidobacterium bifidum were significantly lower in the low-GNRI group. Our results indicated that GNRI can be a useful nutritional risk index that accurately reflects the comprehensive differences in clinical condition in patients undergoing hemodialysis. The deficiency of B. adolescentis and B. bifidum was strongly associated with an increased nutritional risk in patients undergoing hemodialysis.
Keywords: gut microbiota, nutrition, frailty, hemodialysis, chronic kidney disease
INTRODUCTION
The lumen of the gastrointestinal tract hosts trillions of microbes that coexist and form the microbiota [1]. Multiple barrier mechanisms exist in the intestinal tract to prevent harmful microbes from entering the body through the lumen [2, 3]. The gut microbiota produces various metabolites through symbiosis with the host and can communicate with the host immune system [4]. It can alter the metabolism, contributing to the pathogenesis of various diseases [5,6,7], such as chronic kidney disease (CKD) [8]. CKD causes a state of dysbiosis, disturbing the composition of the gut microbiota [9]. Gut microbial dysbiosis is associated with increased mortality in patients undergoing hemodialysis [10]. Changes in the gut microbiota modify the pathology of CKD through uremic, chronic systemic inflammation, and immunoregulatory mechanisms [11, 12].
The number of patients with end-stage kidney disease (ESKD) needing dialysis is increasing worldwide [13, 14]. As the patients on dialysis become more aged, the prevalence of frailty in them increases [15]. More than 50% of patients with ESKD have malnutrition, which could cause frailty [15,16,17]. Nutrition and the gut microbiota are closely related, and the gut microbiota influences human energy metabolism [18]. Nutrient absorption efficiency in individuals varies based on the gut microbial composition [19]. Further, the diversity of the gut microbiota is reduced in malnourished frail patients [20]. Therefore, changes in nutritional status, frailty, and gut microbiota could be interrelated.
Malnutrition is one of the risk factors for mortality in patients undergoing dialysis [21, 22]. Various composite nutritional risk indices are useful for predicting the prognosis of patients undergoing dialysis [23, 24]. The geriatric nutritional risk index (GNRI) is based on serum albumin and body weight measurements and was originally developed to identify elderly patients at risk of malnutrition in hospitals [25]. Several studies have shown that the GNRI can predict mortality in patients undergoing hemodialysis [15, 26]. Therefore, GNRI can be a valuable nutritional risk indicator for the outcomes of patients undergoing hemodialysis.
Our previous report showed that probiotics affect nutrition and immunity by modulating the gut microbiota in patients undergoing hemodialysis [27]. However, the relationship between altered gut microbiota and increased nutritional risk in hemodialysis patients is unclear. Therefore, we evaluated nutritional risk in patients using the GNRI and investigated the gut microbial alteration in patients undergoing hemodialysis according to their nutritional risk.
MATERIALS AND METHODS
Participants
This study evaluated the medical records of patients who underwent maintenance hemodialysis at the National Hospital Organization Yanai Medical Center between April and December 2022. Eligible patients had vascular access through an arteriovenous fistula or prosthesis and had been on maintenance hemodialysis for at least 6 months for ESRD. Patients with concurrent infections, steroid use, or ileostomies were excluded from the study. The patients were divided into low-GNRI and high-GNRI groups, and we compared the gut microbial diversity between the two groups. The study protocol was approved by the ethics committee of the National Hospital Organization Yanai Medical Center (permit number: Y-4-1) and complied with the ethical standards of the Declaration of Helsinki (revised in Brazil, 2013). All patients provided informed consent for the procedures and use of their data for this study.
Data collection
Blood samples were collected at the beginning of each dialysis session. Blood cell counts (total neutrophils and lymphocytes), total protein (TP), serum albumin (ALB), total cholesterol (T-Chol), cholinesterase (CHE), triglyceride (TG), high-density lipoprotein (HDL), and low-density lipoprotein (LDL) levels were determined by standard laboratory techniques using auto analyzers. Transthyretin (TTR) was measured using a turbidimetric immunoassay. Transferrin levels were measured by the Nitro PSAP reagent. Beta2 microglobulin (β2MG) and retinol-binding protein (RBP) were measured using a latex agglutination method. Natural killer (NK) cell activity was measured as previously reported [28]. Serum interleukin (IL)-6 levels were measured by Quantikine ELISA (R&D Systems, Inc., Minneapolis, MO, USA). A single-pool kinetic model was used to calculate Kt/V [29].
Frailty was evaluated using the Clinical Frailty Scale (CFS) [30]. The CFS assesses comorbidities, function, and cognition to generate a frailty score ranging from 1 (very fit) to 9 (terminally ill).
Assessment of nutritional risks
GNRI was calculated as follows: GNRI = (14.89 × albumin [g/dL]) + (41.7 × dry/ideal body weight) [25]. Ideal body weight was calculated from the patient’s height using a body mass index (BMI) of 22.0 kg/m2. The dry/ideal BW ratio was identical to 1.0 when the dry weight exceeded the ideal weight. Patients were evaluated for nutritional risk using GNRI and divided into two groups, namely, low-GNRI and high-GNRI groups. The low-GNRI group included patients with high nutritional risk, and the high-GNRI group included patients with low nutritional risk. The cut-off value for the groups was a median GNRI value of 82.
Fecal sampling and DNA extraction
Fecal sampling and DNA extraction were conducted according to previously described methods [31]. Fresh fecal samples were collected from each patient and immediately frozen at −80°C. DNA was extracted using an automated DNA isolation system (GENE PREP STAR PI-480; Kurabo, Osaka, Japan).
16S sequencing
The V3–V4 regions of bacterial and archaeal 16S rRNA were amplified using the Pro341F/Pro805R primers and the dual-index method [31, 32]. Barcoded amplicons were paired-end sequenced on a 2×301-bp cycle using a MiSeq system with MiSeq Reagent Kit version 3 (600 cycles) chemistry.
Bioinformatics analysis
Using default settings, the primer sequences on paired-end sequencing reads were trimmed using Cutadapt (ver. 1.18) [33]. Paired-end sequencing reads were merged with the Fastq-join program using the default settings [34]. The joined amplicon sequence reads were processed through QIIME 2 (ver. 2020.6) [35]. The chimeric sequences underwent filtration for quality and deletion, and then representative sequences were created using DADA2 (Divisive Amplicon Denoising Algorithm 2), a denoise-single plugin, using the default settings [36]. Taxonomy of representative sequences was assigned using the Greengenes database (ver. 13.8) by training a Naive Bayes classifier using the q2-feature-classifier plugin [37].
Statistical analysis
Categorical variables were represented as numbers and percentages, and continuous variables were represented as medians and interquartile ranges. Pearson’s χ2 test was used to assess categorical variables, and the Mann–Whitney U test was used to evaluate continuous variables. The QIIME2 package was used to perform principal component analysis (PCA). The R package was used to generate the figures. The significance level was set at p≤0.05 for all analyses. Statistical analyses were performed using the JMP version 14 statistical analysis software (SAS Institute, Cary, NC, USA).
RESULTS
Participants
A total of 38 patients who underwent maintenance hemodialysis for ESRD were eligible for the study. The patients were divided into the low-GNRI (20 patients) and high-GNRI (18 patients) groups.
Baseline characteristics
The baseline characteristics of the patients are shown in Table 1. No significant differences were observed between the two groups for age (p=0.197), sex (p=0.564), hypertension (p=0.208), diabetes (p=0.054), Kt/V (p=0.579), TP (p=0.067), RBP (p=0.796), transferrin (p=0.132), TG (p=0.953), HDL (p=0.057), white blood cell count (p=0.965), lymphocyte proportion (p=0.619), hemoglobin (p=0.208), effector/target cell (ET) ratio 10:1 (p=0.357), ET ratio 20:1 (p=0.279) and IL-6 (p=0.118). In renal function, β2-MG was significantly higher in the low-GNRI group than in the high-GNRI group (p=0.046). The factors related with nutrition were significantly lower in the low-GNRI group than in the high-GNRI group: BMI (p<0.001), ALB (p<0.001), TTR (p=0.011), ChE (p=0.018), T-Chol (p=0.041).
Table 1. Patients baseline characteristics.
| Low-GNRI group | High-GNRI group | p | |
|---|---|---|---|
| Age (years)a | 79 (74–84) | 75 (72–79) | 0.197 |
| Male/Femaleb | 6 (30.0)/14 (70.0) | 7 (38.9)/11 (61.1) | 0.564 |
| BMI (kg/m2)a | 17.6 (15.8–19.5) | 21.1 (19.2–22.3) | <0.001 |
| Hypertensionb | 6 (30.0) | 9 (50.0) | 0.208 |
| Diabetesb | 5 (25.0) | 10 (55.6) | 0.054 |
| Kt/Va | 2.2 (2.1–2.4) | 2.3 (1.9–2.8) | 0.579 |
| β2-MG (mg/dL)a | 29.9 (26.6–35.9) | 25.9 (23.7–31.7) | 0.046 |
| TP (g/dL)a | 5.7 (5.3–6.1) | 6.1 (5.6–6.6) | 0.067 |
| ALB (g/dL)a | 2.8 (2.6–2.9) | 3.2 (3.0–3.5) | <0.001 |
| TTR (mg/dL)a | 19.3 (15.4–23.5) | 23.9 (19.5–26.8) | 0.011 |
| RBP (mg/dL)a | 10.2 (7.3–12) | 9.7 (8.0–11.6) | 0.796 |
| Transferrin (mg/dL)a | 143 (118–158) | 148 (140–178) | 0.132 |
| ChE (mg/dL)a | 139 (121–224) | 239 (174–279) | 0.018 |
| T-Chol (mg/dL)a | 139 (110–161) | 166 (145–193) | 0.041 |
| TG (mg/dL)a | 115 (86–141) | 123 (79–139) | 0.953 |
| HDL (mg/dL)a | 43 (30–54) | 49 (42–63) | 0.057 |
| LDL (mg/dL)a | 68 (49–95) | 96 (66–109) | 0.044 |
| WBC (/μL)a | 5,750 (3,975–7,075) | 5,650 (4,625–6,800) | 0.965 |
| Hb (g/dL)a | 10.4 (8.7–11.3) | 10.8 (9.9–11.1) | 0.208 |
| Lymphocyte (%)a | 17.5 (14.1–23.5) | 18.3 (16.3–22.2) | 0.619 |
| E/T ratio 10:1a | 8.1 (4.6–16.3) | 11.6 (6.0–17.6) | 0.357 |
| E/T ratio 20:1a | 12.4 (7.2–25.3) | 18.3 (10.2–33.1) | 0.279 |
| IL-6 (pg/mL)a | 12.0 (6.3–30.8) | 8.6 (4.6–15.3) | 0.118 |
aValues are expressed as median (interquartile range).
bValues are expressed as number (percentage).
GNRI: Geriatric nutritional risk index; BMI: body mass index; β2-MG: beta-2 microglobulin; TTR: transthyretin; RBP: retinol binding protein; ChE: cholinesterase; T-Chol: total cholesterol; TG: triglyceride; HDL: high density lipoprotein; LDL: low density lipoprotein; WBC: white blood cell; Hb: hemoglobin; ET: effector/target cell; IL: interleukin.
Frailty
All participants were in patients undergoing dialysis and unable to attend outpatient clinics. As shown in Table 2, all the patients presented with moderate-to-severe frailty. Additionally, there were more patients with CFS ≥7 in the low-GNRI group than in the high-GNRI group (p=0.021).
Table 2. Clinical Frailty Scale in patients with hemodialysis.
| CFS | Low-GNRI group | High-GNRI group | p |
|---|---|---|---|
| 1–4 | 0 (0.0) | 0 (0.0) | |
| 5 (mild frailty) | 0 (0.0) | 0 (0.0) | |
| 6 (moderate frailty) | 11 (55.0) | 16 (88.9) | |
| 7 (severe frailty) | 7 (35.0) | 2 (11.1) | |
| 8 (very severe frailty) | 2 (10.0) | 0 (0.0) | |
| 9 (terminal ill) | 0 (0.0) | 0 (0.0) | |
| CFS ≥7 | 9 (45.0) | 2 (11.1) | 0.021 |
Values are expressed as number (percentage).
CFS: Clinical Frailty Scale; GNRI: Geriatric nutritional risk index.
Differences in gut microbial diversity based on nutritional status
The relative abundance of the bacterial community at the phylum level is listed in Supplementary Fig. 1. The four major phyla of the human gut microbiota are Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria. Table 3 shows the abundances of these phyla in the two groups. The abundances of Firmicutes (p=0.051) and Actinobacteria (p=0.023) were lower in the low-GNRI group than those in the high-GNRI group, whereas the abundance of Proteobacteria (p=0.031) was significantly higher in the low-GNRI group than in the high-GNRI group. The abundance of Bacteroidetes was not statistically significantly higher in the low GNRI group than in the high GNRI group (p=0.066).
Table 3. Relative abundances of four major phyla in patients with hemodialysis.
| Low-GNRI group | High-GNRI group | p | |
|---|---|---|---|
| The relative abundance of | |||
| the Firmicutes phylum (%) | 62.1 (56.2–76.3) | 75.4 (60.8–84.5) | 0.051 |
| the Actinobacteria phylum (%) | 4.1 (1.9–7.5) | 7.6 (4.3–13.6) | 0.023 |
| the Bacteroidates phylum (%) | 13.9 (4.2–20.3) | 5.8 (1.6–11.6) | 0.066 |
| the Proteobacteria phylum (%) | 4.9 (2.2–19.3) | 1.8 (0.9–9.3) | 0.031 |
Values are expressed as median (interquartile range).
GNRI: Geriatric nutritional risk index.
Table 4 shows the abundance of bacteria at the genus level for the phylum Actinobacteria. The two groups showed no significant differences in the abundances of the genera Actinomyces (p=0.838), Collinsella (p=0.659), and Eggerthella (p=0.198). However, Bifidobacterium was significantly less abundant in the low-GNRI group (p=0.011). We also determined the abundances of bacteria at the genus level for the phylum Firmicutes, which was the phylum with higher relative abundance (Supplementary Table 1). Regarding bacteria at the genus level for the phylum Firmicutes, some intestinal bacteria tended to differ between the two groups, but there were no significant differences.
Table 4. Relative abundances of intestinal bacteria at the genus level in patients with hemodialysis.
| Low-GNRI group | High-GNRI group | p | |
|---|---|---|---|
| The relative abundance of | |||
| the genus Bifidobacterium (%) | 1.3 (0.7–2.8) | 5.7 (1.3–10.0) | 0.011 |
| the genus Actinomyces (%) | 0.1 (0.0–0.3) | 0.1 (0.0–0.2) | 0.838 |
| the genus Collinsella (%) | 0.6 (0.1–2.0) | 2.1 (0.0–2.8) | 0.659 |
| the genus Eggerthella (%) | 0.5 (0.2–1.1) | 0.3 (0.1–0.8) | 0.198 |
Values are expressed as median (interquartile range).
GNRI: Geriatric nutritional risk index.
Table 5 shows the differences at the species level for the genus Bifidobacterium in two groups. The detection rates of Bifidobacterium adolescentis (p=0.007) and Bifidobacterium bifidum (p=0.049) were significantly lower in the low-GNRI group. No significant differences were observed between the two groups in detecting Bifidobacterium longum (p=0.194) and Bifidobacterium breve (p=0.758).
Table 5. Bifidobacterium species in patients with hemodialysis.
| Low-GNRI group | High-GNRI group | p | |
|---|---|---|---|
| Detection of | |||
| Bifidobacterium adolescentis | 2 (10.0) | 9 (50.0) | 0.007 |
| Bifidobacterium bifidum | 4 (20.0) | 9 (50.0) | 0.049 |
| Bifidobacterium longum | 8 (40.0) | 11 (61.1) | 0.194 |
| Bifidobacterium breve | 11 (55.0) | 9 (50.0) | 0.758 |
Values are expressed as number (percentage).
GNRI: Geriatric nutritional risk index.
The α-diversity indices revealed no significant differences in gut microbial diversity between the two groups (p=0.511; Supplementary Fig. 2).
DISCUSSION
This study examined gut microbial differences in patients undergoing maintenance hemodialysis according to their nutritional risk. The relative abundances of Actinobacteria and Proteobacteria varied significantly with different nutritional risks in patients with hemodialysis. Among the Actinobacteria phylum, the genus Bifidobacterium was significantly reduced in patients with high nutritional risk. At the species level, reduced numbers of the good microbes B. adolescentis and B. bifidum were significantly correlated with high nutritional risk.
More than 99% of the human gut microbiota belongs to four phyla: Firmicutes, Actinobacteria, Bacteroidetes, and Proteobacteria [38]. Among the genus Bifidobacterium present in primates, B. adolescentis is common in adults [39]. In this study, patients with a high nutritional risk had low numbers of B. adolescentis and B. bifidum. B. adolescentis stimulates the anti-inflammatory cytokines and induces a protective Treg/Th2 response and gut microbiota remodeling in patients with chronic colitis [40]. A previous study has reported that the fecal level of B. adolescentis in patients with inflammatory bowel disease was lower than in normal individuals and that administration of B. adolescentis decreased proinflammatory cytokines and increased anti-inflammatory cytokines [40]. Conversely, B. bifidum is more commonly observed in breastfed infants [39]; however, it is present in low numbers in adults [41]. B. bifidum contributes to antibacterial activity, modulation of the host immune system, and alleviation of inflammatory activity in chronic gastrointestinal dysfunction [39, 42,43,44]. Therefore, it is suggested that B. adolescentis and B. bifidum are intestinal bacteria that affect inflammation. Also in patients undergoing hemodialysis, Bifidobacterium levels were reported to be negatively correlated with inflammatory markers such as interleukin-6 and tumor necrosis factor α [45]. Because inflammation is a contributing factor that affects nutritional status [46], we speculate that differences in Bifidobacterium levels, which are related to the regulation of inflammation, may have been observed between patients with high and low nutritional risk in this study. In optimal numbers, the Bifidobacterium species bacteria might play an important role in reducing the nutritional risk in patients undergoing hemodialysis by modulating the activity of the intestinal immune system and inflammation.
Changes in gut microbiota in CKD form an entero-renal linkage that further modifies CKD pathology [11, 12]. Reduced gut microbial diversity is associated with mortality in patients with ESRD [10]. In addition, malnutrition is significantly correlated with decreased gut microbial diversity in patients with ESRD [10, 47]. Frailty and gut microbial diversity have been shown to have a significant negative correlation [20]. In this study, all participants were moderately to severely frail. Therefore, it is possible that the patients included in this study did not have a diverse gut microbial population. Differences in the abundance of the Bifidobacterium species according to nutritional risk may have limited the findings in patients with ESKD with frailty.
The GNRI is a nutritional risk index that has been shown to correlate with the prognosis and postoperative outcomes of various diseases [48,49,50]. In patients undergoing hemodialysis, the GNRI has been shown to strongly impact infection-related mortality [50]. In this study, the GNRI was correlated with general factors related with nutrition (ALB, TTR, ChE, and T-Chol values) and patient renal function (as studied using β2-MG). Previous studies have shown that a low GNRI is a risk factor for progression to end-stage CKD [26]. Furthermore, the GNRI was significantly associated with frailty severity and reduced microbial diversity in patients on hemodialysis. Therefore, the GNRI reflects clinical conditions such as nutritional deficiency, frailty, renal function, and the distribution of gut microbiota. These findings indicate that GNRI is a valuable indicator for a comprehensive evaluation of the clinical condition of patients on hemodialysis.
This study has certain limitations. This was a retrospective cohort study, and the small sample size may have limited the power of the analysis. Eligible patients were limited to those who had declined ADL and were managed in the hospital. A prospective trial with a large sample size is needed to examine the relationship between nutritional risk and gut microbial diversity in patients on hemodialysis. This study did not examine differences in gut microbiota or nutritional risk assessment over time with multiple examinations. Therefore, future studies should examine the association between Bifidobacterium levels and nutritional risk in more detail by testing at multiple time points. In addition, this study could not determine which is the cause or the result in the relationship between B. adolescentis and B. bifidum and nutritional risk. Nevertheless, we expect that the results of this study will help to elucidate the intestinal bacteria that are associated with nutritional risk in patients undergoing hemodialysis.
We discussed differences in the gut microbiota depending on the degree of nutritional risk. Our results suggest that depletion of B. adolescentis and B. bifidum is associated with increased nutritional risk in patients on hemodialysis. GNRI is an important nutritional risk index that effectively reflects the comprehensive clinical condition of patients on hemodialysis.
FUNDING
This study was supported by a Grant-in-Aid for Clinical Research from the National Hospital Organization.
CONFLICT OF INTEREST
The authors declare they have no conflicts of interest.
Supplementary Material
Acknowledgments
We would like to thank TechnoSuruga Laboratory Co., Ltd. for their cooperation in collecting the data.
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