Immunosuppressive Therapy and Nutritional Diseases of Patients after Kidney Transplantation: A Systematic Review

doi:10.21203/rs.3.rs-4830927/v1

Download PDF

Research Article

Immunosuppressive Therapy and Nutritional Diseases of Patients after Kidney Transplantation: A Systematic Review

https://doi.org/10.21203/rs.3.rs-4830927/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background: Kidney transplantation (kTx) is by far the most effective method of treating end-stage renal disease, with immunosuppressive therapy being obligatory for all, except identical twins. Despite kTx being the most effective treatment for end-stage renal disease, the patients face significant morbidity. They are often burdened with diabetes, anemia, lipid disorders, all of which pose heightened risks for cardiovascular disease. Knowing that nutritional status plays a significant role in post-transplant results including graft survival, we conducted this systematic review with the aim to summarize the evidence of nutritional diseases following exposure to immunosuppressive therapy among patients after kTx.

Methods: This systematic review is reported according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist. Our search encompasses observational studies (cohort, case-control, cross-sectional) and randomized controlled trials (RCTs), published and unpublished, completed, and ongoing, written in English from the last 10 years (up to 17^th February 2023) in the following databases: MEDLINE (via PubMed), EMBASE (Elsevier), Scopus and Web of Science. Any settings were eligible for inclusion. Quality assessments were done using ROBINS-I and RoB2 tools. Results were summarized in a narrative synthesis. Quantitative analysis was conducted where feasible. The protocol for proposed systematic review was published elsewhere.

Results: A total of 24 studies were included (participants n=9,536) in the review. The majority of studies were cohort (n=16), with moderate or low quality. Most of the studies (n=16) were conducted in hospital settings. All studies had a higher proportion of male participants compared to female participants, except for one. Diabetes emerged as the most frequent disease assessed (n=14), while tacrolimus (Tac) was the most commonly evaluated immunosuppressive medication used (n=16). As a result, Tac presented a higher risk factor for the development of diabetes compared to cyclosporine (CsA). In addition, Tac was linked to weight gain in post-transplant recipients. In contrary, no relationship was found between steroids and weight gain. Regarding other immunosuppressants, everolimus was found to be associated with lipid abnormalities. Though, the relationship between lipid abnormalities and steroid use yielded inconsistent results. Calcineurin inhibitors (CNIs) were studied in various research articles. Consequently, patients who were not using CNIs had a lower prevalence of hypomagnesemia, hyperkaliemia, and metabolic acidosis compared to those treated with CNIs. Also, CNIs were found to have a negative impact on 25-hydroxyvitamin D (25(OH)D) levels. Another aspect was the use of slow and fast Tacrolimus metabolizers. There was no difference observed in phase angle, visceral fat area, lean body mass index, and the proportion of lean mass as a percentage of total body mass between them. Finally, mTOR inhibitors were associated with bone status and mycophenolate mofetil was linked to Vitamin B12 deficiencies.

Conclusions: To the best of our knowledge, this systematic review represents the first comprehensive overview of the evidence regarding immunosuppressive therapy and nutritional diseases in kTx patients. Our findings indicate an association between immunosuppressive therapy and nutritional diseases in this population. However, there is high heterogeneity and suboptimal quality of the included studies. Future researchers should prioritize high-quality, prospective randomized controlled trials to further elucidate these relationships.

Systematic review registration: PROSPERO (CRD42023396773), dated 12 April 2023.

Protocol publication: https://doi.org/10.3390/jcm12216955

kidney transplantation

immunosuppressive therapy

nutrition

diet

The kidney is the most transplanted organ followed by the liver and the heart. In 2022, there were a total of 157,494 organ transplants worldwide of which kidney accounted for 65% (102,090) [1]. Despite kidney transplantation (kTx) being the most effective treatment for end-stage renal disease (ESRD), offering extended lifespan and significantly enhanced quality of life compared to dialysis, these patients face significant morbidity [3–4]. They frequently contend with comorbidities such as hypertension, diabetes, anemia, lipid disorders, overweight and obesity. Each of these conditions pose heightened risks for cardiovascular diseases (CVD) which stands as one of the leading causes for kidney transplant recipients [5]. In addition, osteoporosis and cancers are also prevalent among this population [6].

Immunosuppressive therapy among kidney transplant recepients is obligatory for all, except identical twins. The standard scheme includes the use of immunosuppressive medication and steroids, that are delineated as follows, (1) Calcineurin inhibitors (CNIs) – cyclosporine (CsA) and tacrolimus (Tac), (2) Mammalian target of rapamycin (mTOR) inhibitors (sirolimus and everolimus), (3) Antiproliferatives like azathioprine and mycophenolic acid derivatives, (4) Glucocorticosteroids, and (5) Biological immunosuppressive agents [7, 8]. Contemporary immunosuppressive protocols typically involve triple-drug therapy, including CNIs, corticosteroids, and antiproliferative drugs. Chronic immunosuppressive therapy exacerbates pre-existing metabolic disorders and instigates new ones. For instance, steroids like prednisone can lead to osteoporosis, fluid retention, hypertension, dyslipidemia, NODAT increased appetite, and weight gain. Dyslipidemia can also result from calcineurin inhibitors (e.g., tacrolimus and cyclosporine) and mTOR inhibitors (e.g., everolimus and sirolimus). Hypomagnesemia may occur with cyclosporine, everolimus, and tacrolimus, while hyperkaliemia is linked to cyclosporine and tacrolimus. Furthermore, both CNIs are known to increase the incidence of hyperuricemia compared to mycophenolate or mTOR inhibitors [9].

Nutrition plays a significant role for patients following kTx [9]. In the early post-transplant period, proper nutrition aids at facilitating wound healing, preventing infections, and addressing electrolyte and metabolic imbalances resulting from kidney function restoration and immunosuppressive medications. Over the long term however, maintaining proper nutrition is essential for stabilizing renal function and preventing various complications such as obesity, dyslipidemia, anemia, diabetes/hyperglycemia, hypertension, and bone disease. Nutritional habits can significantly impact the health and functioning of these patients [10]. The nutritional approach for patients after kidney transplantation was presented on Fig. 1.

Immunosuppressive therapy, while crucial for preventing rejection, can also induce side effects that may be influenced by dietary choices. Therefore, a tailored nutritional plan, possibly supervised by a dietitian or healthcare professional, is crucial for managing these side effects and promoting overall health and well-being post-transplantation.

Knowing that the relationship between immunosuppressive therapy and nutritional diseases among kTx patients is complex and influenced by multiple factors, the aim of this systematic review is to address this gap [11]. Specifically, this review seeks to summarize the evidence on nutritional outcomes following exposure to immunosuppressive therapy among kTx patients. By synthesizing the findings from relevant studies, the aim is to provide insights into the potential impact of immunosuppressive therapy on the nutritional diseases among post-transplant patients.

2.1. Protocol and Registration

This systematic review is reported according to the Preferred Reporting Items for a Systematic Reviews and Meta-Analyses (PRISMA) 2020 checklist [Supplementary File 1] [12]. The Protocol was registered at the International Prospective Register for Systematic Reviews (PROSPERO) [CRD42023396773] (registration date: 12 April 2023) [13]. The protocol for the proposed systematic review was published elsewhere [14].

2.2. Eligibility Criteria

2.2.1. Types of participants

We included studies on adult patients (18 years of age or older). Studies based on children, adults younger than 18 years of age, and pregnant women were excluded.

2.2.2. Intervention

Studies with single kidney transplantation were included. Studies on multiple organ transplantation were excluded.

2.2.3. Exposure(s)

Exposure included different schemes of immunosuppressive therapy, such as types and doses of immunosuppressives used. Studies were included where the scheme of immunosuppression was stated in the protocol. We excluded studies in which the immunosuppressive regimen was not clearly specified.

2.2.4. Outcome(s)

Eligible outcomes included anthropometric measurements and biochemical markers, such as body composition, body weight, body mass index (BMI), vitamins (i.e., Vitamin B₆, Vitamin B₁₂, Vitamin D and Folic Acid) and minerals levels (i.e., Iron (Fe), Magnesium (Mg), Phosphorus (P), and Potassium (K)). As body composition we considered all relevant parameters such as i.e. waist and hip circumferences, waist-to-hip ratio, body fat percentage, and percentage changes in hip circumferences. As body weight, we specifically addressed weight gain, body mass index (BMI), and obesity, all of which emerged as notable outcomes in the studies referenced. In our review, we outlined PTDM, NODAT, and hyperglycemia as key facets of diabetes under consideration. Post-transplant diabetes mellitus (PTDM) and new-onset diabetes after transplantation (NODAT) were considered based on glycemic parameters (serum glucose levels). Lipid abnormalities were evaluated, taking into consideration factors such as HDL-cholesterol, LDL-cholesterol, and triglycerides. In addition, bioimpedance (BIA) analysis components such as i.e., per cent body fat, mass of body fat, lean body mass, total body water, body cell mass, skeletal muscle mass was considered. The outcomes and outcomes measures for each study included in the review are presented in Table 1.

2.2.5. Setting and Design

We included observational studies (cohort, case-control and cross-sectional) and RCTs, both published and unpublished, completed, and ongoing, written in English from the last 10 years (up to 17th February 2023). Qualitative studies, case studies, conference reports and literature reviews were excluded. Any settings were eligible for inclusion. The reference lists of the articles were searched additionally. For missing data authors were contacted.

2.3. Information Sources and Search Strategu

We searched following databases: MEDLINE (via PubMed), EMBASE (Elsevier), Scopus and Web of Science. A search strategy was developed in collaboration with an experienced research librarian [Supplementary file 2]. To construct accurate search terms, we used subject headings and subheading as well as text words that will be used to describe words and phrases. For example, in MEDLINE (via PubMed) database for ‘kidney transplantation’ we used term “kidney transplantation” found in [All fields] as well as “organ transplantation”, “Renal Replacement Therapy” and “Transplants” all found as MeSH terms; for ‘immunosuppression therapy’: “immunosuppression therapy” [MeSH Terms], (("Immunosuppressive Agents"), “Immunosuppressive Agents” [MeSH Terms], “Immunosuppressive scheme”, “immunocompromised host” [MeSH Terms]; and for nutritional status "nutritional status", “body composition", “body composition” [MeSH Terms], "body mass index", "body mass index"[MeSH Terms] etc. Each group has been combined using operators AND, OR and NOT. According to each database guidelines: EMBASE (Elsevier); Scopus and Web of Science we applied all the rules in our search strategy. The search was revised and approved by all authors.

2.4. Study Selection

The selection of studies was done in Covidence, which is a web-based systematic review management tool [15]. After removing duplicates, two authors (A.A.K., A.K.N.) blindly screened titles and abstracts for exclusion followed by full-text screening that was also conducted by two reviewers (A.A.K., A.K.N.). Disagreements were solved through discussion or with the help of the third reviewers (D.S.L.). The selection of studies is illustrated in the PRISMA flow chart 2020, which is presented on Fig. 2.

2.5. Data Extraction

Data extraction and management of data were done by two reviewers (A.A.K., A.K.N.). Data were exported to the standardized MS Excel template. Disagreements were solved through discussion or with the assistance of a third reviewer (D.S.L.). The following data was extracted: 1) study reference (first author and year of publication), 2) study design, 3) country where the study was conducted, 4) settings, 5) sample size, 6) mean age of participants, 7) the number of males and females, 8) description of exposure, 9) description of outcome, 10) measures of effects and tools of measurements, and, 11) how the data was

2.6. Quality Assessment

Two investigators (A.A.K., M.K.) assessed the risk of bias of eligible studies. The quality of observational studies was assessed using the Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tool, including: bias due to confounding, bias in the selection of participants into the study, bias in classification of interventions, bias due to deviations from intended interventions, bias due to missing data, bias in the measurement of outcomes, and bias in selection of the reported result [16, Supplementary file 3]. For RCTs the Cochrane Risk of Bias tool (RoB2, August 2019) was used, considering five domains: risk of bias arising from the randomization process, risk of bias due to deviations from the intended interventions, missing outcome data, risk of bias in measurement of the outcome, and the risk of bias in the selection of the reported result [17, Supplementary file 4]. Risk-of-bias plots were generated using the web application Robvis [18].

2.7 Data Analysis

Data from eligible studies was extracted and presented in a narrative synthesis. We grouped studies based on the exposures and outcomes assessed. We discussed how potential confounders were addressed and controlled in each study. In order to present quantitative data, we developed a forest plot that summarizes the evidence of the effect of various immunosuppressants on NODAT among kTx patients (Fig. 5). Statistica 13.1 was used for data analysis. The studies were too heterogeneous to perform subgroup analysis.

3.1 Description of Search Results

Our search yielded a total of 2682 results. After eliminating duplicates, 2322 results were screened for title and abstract. Of these, 2245 were excluded for not being relevant, with a total of 77 studies included. After further screening, 77 articles were accessed for eligibility and full texts were screened. Out of these, 53 were excluded for specific reasons. Our final number of included studies was 24 [19–42] (Fig. 1).

3.2 Description of Study Characteristics

As presented in Table 2 most of the studies included in the review were cohort studies (n = 16). Further, two RCTs were included, and six cross-sectional studies. There was a total of 9,536 participants in the included studies, with a minimum and maximum sample size of 56 and 3342, respectively. The majority of studies were conducted in hospital settings (n = 16). In all studies the percentage of male participants was higher than female, except one [35]. Studies were conducted in different parts of the world, from Saudi Arabia to Australia, with the highest number coming from China (n = 5), Brazil (n = 3), and Poland (n = 2). The most common outcome assessed was diabetes (n = 14). The other following outcomes considered body weight (n = 3), lipid profile (n = 2), body composition (n = 1), electrolyte disorders (n = 1), bone status (n = 1), Vitamin D (n = 1), and Vitamin B₁₂ (n = 1). The most common immunosuppressant assessed was tacrolimus (n = 16). The time of participants after kTx being included in the studies varied from 0 to 8.4 years. The majority of studies were conducted 1 year after kTx (n = 9). There were only five studies conducted within the 1-year post-transplant, and the majority of studies (n = 10) were conducted long-term which means both within the 1 year after kTx and one-year post-transplant (Graph 1).

3.3 Quality Assessment

Figures 3 and 4 shows quality ratings of the included studies for observational and RCTs, respectively. The twenty-two observational studies included present moderate (n = 13), serious (n = 7), or critical risk of bias (n = 2). Two RCTs included in the review present ‘some concerns’ assessment and low risk of bias.

3.4 The summary of results

In the summary, seven main nutritional outcomes were assessed, described as follows: body composition, body weight, diabetes, lipid profile, bone status, vitamin D, vitamin B₁₂ and electrolyte disorders. The summary of results is presented in Table 3.

3.4.1 Body composition

In our review, one study assessed the body composition among kidney transplant recepients [32]. In this cohort study, significant increases were observed in various anthropometric measurements in both CsA and Tac groups. These included waist and hip circumferences between the 1st and 48th months, waist-to-hip ratio between the 1st and 3rd or 6th months, and neck circumference between the 1st and 12th or 24th months. Additionally, a significant increase in post-transplant body fat percentage values was noted for the 3rd to 24th months in the CsA group and for the 24th to 48th months in both CsA and Tac groups. Moreover, percentage changes in hip circumferences from the pre-transplant period to the 1st, 12th, and 24th months were significantly higher in the CsA group compared to the Tac group. However, there were no significant differences in percentage changes for other anthropometric parameters between the CsA and Tac groups at each time point [35]. Acknowledging the integral role that body weight and BMI play in the care of patients following kidney transplantation, it merits a separate paragraph given its significance for their post-transplant health and well-being.

3.4.2 Body weight

Three studies analyzed the effect of immunosuppressive therapy on body weight, of which two were cohort studies and one cross-sectional [27, 33, 34]. According to Ruangkanchanasetr et al., the prevalence of obesity stood at 12.6% during the initial year, escalated to 28.6% within the first three years, and surged to 39.7% beyond the third-year post-transplantation. mTOR inhibitor was administered more frequently to obese patients compared to those with normal BMI (16.1% vs 7%; P = .056). Conversely, obese recepients showed significantly lower usage of tacrolimus compared to those with normal BMI [8]. In contrast, Sayilar et al. observed notable rises in body weight and body mass index across both CsA and Tac groups. Following a successful kidney transplant, anthropometric measurements typically increase in most recipients. While the impact of calcineurin inhibitor type on weight gain remains unclear, regression analysis indicated that CNI type wasn't identified as a risk factor for obesity development by the 48th month. However, it's prudent to exercise caution regarding its dyslipidemic effects in patients using CsA and the potential risks associated with Tac use in patients with a predisposition to diabetes [35]. In another study, assessing the prevalence and the influence of steroid-free therapy on obesity de Oliveira et al. found that on average, the percentage of weight gain reached 9% after 36 months post-transplantation, coinciding with a significant increase in the prevalence of overweight and obesity during this period. Interestingly, steroid therapy showed no influence on the percentage of weight gain post-transplantation. Instead, associations were found between younger recipient age, female gender, younger donor age, and higher creatinine levels with the most substantial weight gain following transplantation [27]. All studies were conducted long-term which means within 1-year post-transplant and 1 year after.

3.4.3 Diabetes

In total, fourteen studies assessed the effect of immunosuppressive therapy on the occurrence of diabetes following kidney transplantation [19–21, 24–26, 31, 36–42]. Among these, seven studies examined NODAT (n = 7), six investigated PTDM (n = 6), and one study focused on hyperglycemia (n = 1). In general, the immunosuppressive regimens under consideration predominantly included combinations involving calcineurin inhibitors, such as: i) Tac vs. CsA (n = 8); ii) Tac alone (n = 4), and CsA alone (n = 1). Additionally, one study examined the transition from CNIs to belatacept. Overall, with the exception of two studies [73,91], all concluded that CNIs pose a risk factor for the development of diabetes. NODAT occurrence within the first year after kTx was investigated in three studies; however, comparing the findings proved challenging due to variations in the assessment of immunosuppressive regimens [36, 41–42]. According to Xue et al., the incidence of NODAT stood at 20.3%, with the type of immunosuppressive regimen demonstrating a consistent protective effect against its onset. On the contrary, Yu et al. discovered an association between the use of tacrolimus and the onset of NODAT. Finally, Terrec et al. concluded that a late transition from CNIs to Belacept proved to be a beneficial therapeutic strategy, significantly enhancing glycemic parameters. NODAT incidence among patients beyond the first year post-kTx was delineated in four studies, all of which examined the impact of tacrolimus or cyclosporine (Tac vs. CsA) [Borda, Chen, Tillman, Wang]. Three of them identified tacrolimus as posing a higher risk for the development of NODAT compared to cyclosporine [20, 25, 37]. One of them found no difference in the occurrence of NODAT between tacrolimus and cyclosporine [39]. The forest plot showing the relationship between tacrolimus and development of NODAT among kTx patients is described on Fig. 4. Eight studies explored the relationship between developing NODAT and the use of tacrolimus. Six of the studies showed an increased risk of NODAT (OR > 1, p < 0.05). The studies were too heterogeneous to perform subgroup analysis. Torres et al. described PTDM within the first year post-kTx, concluding that in high-risk patients, employing tacrolimus-based immunosuppression with steroid minimization provides the optimal balance between the incidence of PTDM [70]. Two studies examined PTDM incidence among patients beyond the first year post-kTx [24, 38]. Brzezinska et al. found no difference between tacrolimus and cyclosporine concerning the incidence of PTDM after kTx. However, van der Burgh et al. discovered that tacrolimus use posed a risk factor for PTDM development. Three studies examined the long-term incidence of PTDM [19, 26, 40]. In them, tacrolimus has been identified as a risk factor for developing PTDM. Finally, cyclosporine was identified as the higher risk factor for hyperglycemia [31].

3.4.4 Lipid profile

Two studies investigated the relationship between immunosuppressives and lipid profile among kidney transplant recepients [23, 30]. One study was conducted within 1 year after kTx and one was conducted long-term. The results were inconsistent. Bergmann et al. reported no statistically significant correlation between total or free prednisolone exposure (tAUC0–6 h or fAUC0–12 h) and serum levels of HDL-cholesterol, LDL-cholesterol, and triglycerides [23]. However, Ichimaru et al. found that everolimus and corticosteroid use were significant risk factors for lipid abnormalities. In the same study, cyclosporine was not identified as a significant risk factor for the development of lipid abnormalities [30].

3.4.5 Bone status

One study explored the relationship between immunosuppressive therapy and bone status among kidney transplant patients [29]. Gregorini et al. found that there is a significant correlation (p < 0.05) for both osteopenia and osteoporosis with mammalian target of rapamycin (mTOR) inhibitors treatment (imTOR) among kTx patients. The study was conducted above 1-year post-transplant.

3.4.6 Vitamin D

The relationship between immunosuppressive therapy and serum 25(OH)D level among kTx patients in our review was described in one study [28]. CNIs were found to negatively affect serum 25(OH)D level by Filipov et. al. In addition, there was a negative association between the concentration of 25(OH)D and female gender, presence of DM and BMI. The study was conducted long-term.

3.4.7 Vitamin B₁₂

The association between the immunosuppressive medication and vitamin B12 deficiency was described in one study [33]. Pontes et al, found that among individuals with adequate intake of B₁₂, the deficiency of this vitamin was more frequently seen in those using MMF) (17%) vs. azathioprine (2%), p = 0.01. In conclusion, the prevalence of B₁₂ deficiency in kTx was estimated as 14% and was associated with reduced intake of B₁₂ as well as higher adiposity, especially in women, and with the use of MMF.

3.4.8 Electrolyte disorders

Electrolyte disorders in our review were described in one study [22]. Patients without any CNI therapy (n = 50) had a lower prevalence of hypomagnesaemia, hyperkaliemia and metabolic acidosis compared with calcineurin inhibitor treatment (4% vs 26%; 2% vs 14.1% and 2% vs 11.4%; p < 0.01). The study was conducted above 1-year post-transplant.

The aim of this systematic review was to summarize the evidence of nutritional diseases following exposure to immunosuppressive therapy among patients following kidney transplantation (kTx). A total of 24 studies met our inclusion criteria [19–42]. The assessed outcomes encompassed diabetes, body weight, lipid abnormalities, body composition, electrolyte disorders, bone status, and serum of the vitamin D and the vitamin B₁₂ levels. The immunosuppressive medications comprised calcineurin inhibitors (CNIs) (tacrolimus (Tac), cyclosporine (CsA), mTOR inhibitors, antiproliferative, and glucocorticosteroids. Our findings indicate that, overall, immunosuppressive therapy has an effect on nutritional diseases among kTx patients. Furthermore, certain immunosuppressants demonstrate a stronger association than the others. Half of the studies regarding diabetes included in our review described Tac as a stronger risk factor for developing this disease compared to CsA. Our findings are in line with a systematic review conducted by Heisel et al., which examined diabetes and CNIs among solid organ transplant patients. Heisel et al. concluded that patients receiving Tac exhibited a higher incidence of post-transplant diabetes compared to those receiving cyclosporine [43]. Additionally, other studies have linked diabetes to the use of immunosuppressive medications, which may be reversible after modifying the immunosuppressive treatment. This includes reducing the doses of steroid drugs and replacing Tac with CsA [45]. However, in two RCTs studies concerning diabetes and immunosuppressive medications, the results from Torres and Borda were inconsistent. This underscores the necessity for further research in this area, emphasizing the importance of conducting studies of the highest quality. The causes of increased body fat mass in patients after transplantation include factors such as improved appetite, enhanced sense of taste, lack of necessity to adhere to a restrictive diet, and the use of steroid medications [45]. In proposed systematic review, three studies analyzed the effect of immunosuppressive medications on body weight, of which two were cohort studies and one cross-sectional. It was observed that obese patients more frequently used mTOR inhibitors and less often Tac [34]. In contrast, another study. noted significant increases in body weight and body mass index across both CsA and Tac groups [35]. Our findings are consistent with a scoping review that emphasized the limited evidence on this topic in the scientific literature, as well as the lack of high-quality evidence from intervention studies [46]. One of the complications associated with chronic steroid therapy is Cushing's syndrome, characterized by abdominal obesity and sarcopenia. Interestingly, steroid therapy did not demonstrate any influence on the percentage of weight gain post-transplantation in our review [27]. Dyslipidemia represents a significant and frequently encountered burden post-transplant. In our review, two studies investigated the association between immunosuppressive medications and lipid profile. Everolimus emerged as a significant risk factor for lipid abnormalities, while CsA did not show the same association. However, the results regarding the use of steroids were inconsistent. Our findings contradict the existing literature, which suggests that components contributing to lipid abnormalities include immunosuppressive medications such as steroid drugs, calcineurin inhibitors like CsA rather than Tac, and mTOR inhibitors such as sirolimus or everolimus [44]. One study assessed the effect of fast and slow Tac metabolizers on body composition [32]. As a result, there was no difference in phase angle, visceral fat area, lean body mass index (LBMI) and the proportion of lean mass as a percentage of total body mass between the subgroups of slow and fast metabolizers. In our review, mTOR inhibitors were found to be associated with the bone status post-transplant. Gregorini et al. concluded that there is a significant correlation for both osteopenia and osteoporosis with mammalian target of rapamycin (mTOR) inhibitors treatment (imTOR) among kTx patients [29]. What is more, CNIs were found to negatively affect serum 25(OH)D level [28]. The association between the immunosuppressive medication and vitamin B₁₂ deficiency was described in one study [33]. Pontes et al. established the B₁₂ deficiency was linked to the use of MMF. Our findings are in line with the literature which states that immunosuppressive medications contribute to development of anemia (mycophenolate mofetil/Na, Tac, azathioprine, mTOR inhibitors), blockers of the renin-angiotensin-aldosterone (RAA) system (angiotensin-converting enzyme inhibitors and angiotensin receptor antagonists), allopurinol, trimethoprim [44]. Patients without using CNIs had a lower prevalence of hypomagnesaemia, hyperkaliemia and metabolic acidosis compared with calcineurin inhibitor treatment. There was no difference in phase angle, visceral fat area, LBMI and the proportion of lean mass as a percentage of total body mass between the subgroups of slow and fast Tac metabolizers. Only one study assessed this relationship which found that patients without any CNI therapy had a lower prevalence of hypomagnesaemia, hyperkaliemia and metabolic acidosis compared with calcineurin inhibitor treatment. Our findings are in line with the existing literature [44]. It is necessary to monitor magnesium concentrations and in case of deficiency - depending on its severity - supplementation of this element via intravenous infusions (in the early period after transplantation) or in the form of tablets [38]. None of the studies examined an important aspects which are serum potassium and calcium levels. Among patients following kTx, variations in serum potassium concentrations are evident, encompassing both hypo- and hyperkalemia [20]. Furthermore, the distribution of studies across different outcomes may not accurately represent the prevalence or clinical significance of those outcomes post-transplant. While our review highlighted 14 studies on post-transplant diabetes, it's crucial to acknowledge that certain outcomes may garner more attention due to their clinical relevance, existing literature, or research priorities. For instance, lipid abnormalities are more prevalent than diabetes among kTx patients. The relatively low number of studies examining body weight may be due to various factors such as methodological challenges, limited resources, or research priorities. While it's important to acknowledge the discrepancies in the distribution of studied outcomes, it's also crucial to interpret the findings in the context of available evidence and research limitations. Future research efforts may benefit from addressing gaps in the literature and prioritizing areas with significant clinical implications for kTx patients.

To the best of our knowledge, this is the first systematic review that summarizes the evidence of immunosuppressive therapy and nutritional diseases of patients following kidney transplantation. A strength of our review is that we report on a large number of studies, including data from various populations. The limitations include high heterogeneity, and the low quality of studies incorporated in the review. Despite the above limitations, our findings carry significant clinical implications: i) Immunosuppressive therapy affects various nutritional diseases among post-kidney transplant patients; ii) Tac emerged as a higher potent risk factor for disease development compared to CsA; iii) Diabetes garnered the most attention in this research area. Given the heterogeneity and suboptimal quality of the studies included in our review, it is imperative that future research endeavors prioritize high-quality, prospective randomized controlled studies. These rigorous study designs can provide more reliable evidence regarding the association between immunosuppressive therapy and the nutritional status of kidney transplant recepients. Furthermore, additional longitudinal studies focusing on nutritional outcomes are warranted to enhance our understanding of the long-term effects of immunosuppressive therapy among this population. By conducting well-designed RCTs and longitudinal studies, researchers can contribute to filling the existing gaps in the literature and ultimately improve clinical management strategies for kTx patients, thereby enhancing their overall health and well-being. Finally, for a conclusive attribution of the increase in the mentioned diseases to immunosuppressive medication, forthcoming researchers ought to delve into the dietary habits of kidney transplant patients. This exploration will afford a more profound comprehension of the subject matter under study.

95%CI

95% confidence interval

CsA

cyclosporine

CVD

cardiovascular diseases

DASH

Dietary Approaches to Stop Hypertension

ESRD

end stage renal disease

HDL

high-density lipoprotein

LDL

low-density lipoprotein

kTx

kidney transplantation/ kidney transplant

LBMI

lean body mass index

MMF

mycophenolate mofetil

NODAT

new-onset diabetes after transplantation

odds ratio

p-value

PTA

post transplantation anemia

PTDM

post-transplant diabetes mellitus

PRISMA

Preferred Reporting Items for Systematic Reviews and Meta-Analyses

PROSPERO

International Prospective Register for Systematic Reviews

RCTs

randomized controlled trials

RoB 2

the Cochrane Risk of Bias tool

ROBINS-I

Risk of Bias in Non-randomized Studies of Interventions

Tac

tacrolimus

total cholesterols

Ethical approval and consent to participate: Not applicable

Availability of data and materials: The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request.

Competing Interest: The authors declare that they have no competing interests.

Funding: The research received no external funding.

Author Contributions’: Conceptualization: A.A.K and D.S.L.; Methodology: D.S.L. and A.A.K.; Data Curation: M.K., A.K.N.N, and A.A.K; Data Analysis: K.K.; Narrative synthesis: A.K.K; Writing – original draft: A.A.K.; Review and Editing: All authors ; Supervision: D.S.W and D.S.L. All authors have read and agreed to the published version of the manuscript.

Acknowledgments: Special thanks to the Medical University of Warsaw’s research librarian – Mr. Maciej Głowalski, for assisting in developing the data search strings.

Institutional Review Board Statement: Not applicable.

Elflein J. (2023) Global number of organ transplantations 2022, Statista. https://www.statista.com/statistics/398645/global-estimation-of-organ-transplantations/#:~:text=The%20kidney%20is%20the%20most,can%20be%20challenging%20and%20complex. (Accessed: 19 February 2024).
Data (charts and tables) (2020) Global Observatory on Donation and Transplantation (GODT). https://www.transplant-observatory.org/data-charts-and-tables/ (Accessed: 19 February 2024).
Daugirdas JT, Rocco MV, Depner TA, Inrig J, Mehrotra R, Suri RS, Weiner DE, Greer N, Ishani A, MacDonald R, et al. KDOQI clinical practice guideline for hemodialysis adequacy: 2015 update. Am J Kidney Dis. 2015;66:884–930.
Europe PMC, Abramyan S, Matthew H, Kidney Transplantation, Europe PMC. 2023. Available online: https://europepmc.org/article/nbk/nbk567755#free-full-text (accessed on 14 March 2023).
Osté MCJ, et al. Dietary approach to stop hypertension (DASH) diet and risk of renal function decline and all-cause mortality in renal transplant recipients. Am J Transplant. 2018;18(10):2523–33. 10.1111/ajt.14707.
Segaud N, et al. Changes in bone mineral density after kidney transplantation: 2-year assessment of a French cohort. Osteoporos Int. 2018;29(5):1165–75. 10.1007/s00198-018-4383-2.
Szumilas K, Wilk A, Wis ́niewski P, Gimpel A, Dziedziejko V, Kipp M, Pawlik A. Current status regarding immunosuppressive treatment in patients after renal transplantation. Int J Mol Sci. 2023;24:10301.
Bauer AC, Franco RF, Manfro RC. Immunosuppression in kidney transplantation: State of the art and current protocols. Curr Pharm Des. 2020;26:3440–50.
Mlinšek G. Nutrition after Kidney Transplantation. Clin Nutr ESPEN. 2016;14:47–8. 10.1016/j.clnesp.2016.04.012.
Kluch M et al. (2020) ‘Nutrition trends in patients over the long term after kidney transplantation’, Transplantation Proceedings, 52(8), pp. 2357–2362. 10.1016/j.transproceed.2019.12.055
Porrini EL, Díaz JM, Moreso F, et al. Clinical evolution of post-transplant diabetes mellitus. Nephrol Dial Transpl. 2016;31:495–505.
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, et al. The Prisma 2020 statement: An updated guideline for reporting systematic reviews. BMJ. 2021;372:71.
Kajdas A et al. (2023) Immunosuppressive therapy and nutritional status of patients after kidney transplantation – a systematic review, Prospero. https://www.crd.york.ac.uk/prospero/export_details_pdf.php (Accessed: 29 August 2023).
Kajdas AA, et al. Immunosuppressive therapy and nutritional status of patients after kidney transplantation: A Protocol for a systematic review. J Clin Med. 2023a;12(21):6955. 10.3390/jcm12216955.
Better Systematic Review Management. Covidence. 2023. Available online: https://www.covidence.org/ (accessed on 29 August 2023).
Sterne JAC, Hernan MA, Reeves BC, Savovic ́ J, Berkman ND, Viswanathan M, Henry D, Altman DG, Ansari MT, Boutron I, et al. ROBINS-I: A tool for assessing risk of bias in non-randomised studies of interventions. BMJ Br Med J. 2016;355:i4919.
Higgins JP, Altman DG, Gøtzsche PC, Jüni P, Moher D, Oxman AD, Savovic ́ J, Schulz KF, Weeks L, Sterne JAC, et al. The Cochrane Collaboration’s tool for assessing risk of bias in randomised trials. BMJ. 2011;343:d5928.
McGuinness LA, Higgins JPT. Risk-of-bias visualization (robvis): An R package and Shiny web app for visualizing risk-of-bias assessments. Res Synth Methods. 2021;12:55–61.
Ajabnoor A et al. (2020) ‘Evaluation of tacrolimus trough level in patients who developed post-transplant diabetes mellitus after kidney transplantation: A retrospective single-center study in Saudi Arabia’, Transplantation Proceedings, 52(10), pp. 3160–3167. 10.1016/j.transproceed.2020.05.014
Borda B, et al. Side effects of the calcineurin inhibitor, such as new-onset diabetes after kidney transplantation. Acta Physiol Hung. 2014;101(3):388–94. 10.1556/aphysiol.101.2014.3.13.
Torres A, et al. Randomized controlled trial assessing the impact of tacrolimus versus cyclosporine on the incidence of posttransplant diabetes mellitus. Kidney Int Rep. 2018;3(6):1304–15. 10.1016/j.ekir.2018.07.009.
Beilhack G, et al. Electrolyte disorders in stable renal allograft recipients. Swiss Med Wkly. 2020;150(4344). 10.4414/smw.2020.20366.
Bergmann TK, et al. Exploratory study of total and free prednisolone plasma exposure and cushingoid appearance, quality of life and biochemical toxicity in adult male kidney transplant recipients. Clin Drug Investig. 2015;35(11):743–50. 10.1007/s40261-015-0334-2.
Brzezinska B et al. (2013) ‘Factors associated with glucose metabolism disorders after kidney transplantation’. Pol Endocrinol, 64(1).
Chen Q-J, et al. Tacrolimus decreases insulin sensitivity without reducing fasting insulin concentration: A 2-year follow-up study in kidney transplant recipients. Ren Fail. 2015;37(4):601–6. 10.3109/0886022x.2015.1007833.
de Lucena DD et al. (2020) ‘Modifiable variables are major risk factors for posttransplant diabetes mellitus in a time-dependent manner in kidney transplant: An observational cohort study’, Journal of Diabetes Research, 2020, pp. 1–10. 10.1155/2020/1938703
de Oliveira CMC et al. (2014) ‘Post-transplantation weight gain: Prevalence and the impact of steroid-free therapy’, Transplantation Proceedings, 46(6), pp. 1735–1740. 10.1016/j.transproceed.2014.05.027
Filipov JJ, et al. Relationship between vitamin D status and immunosuppressive therapy in kidney transplant recipients. Biotechnol Biotechnol Equip. 2015;29(2):331–5. 10.1080/13102818.2014.995415.
Gregorini M et al. (2017) ‘Understanding bone damage after Kidney Transplantation: A retrospective monocentric cross sectional analysis’, Transplantation Proceedings, 49(4), pp. 650–657. 10.1016/j.transproceed.2017.02.023
Ichimaru N et al. (2015) ‘Risk factors and incidence for lipid abnormalities in kidney transplant patients’, Transplantation Proceedings, 47(3), pp. 672–674. 10.1016/j.transproceed.2014.12.029
Khalili N, et al. Hyperglycemia after renal transplantation: Frequency and risk factors. Nephro-Urology Monthly. 2013;5(2):753–7. 10.5812/numonthly.10773.
Kolonko A, et al. The relationship between initial tacrolimus metabolism rate and recipients body composition in Kidney Transplantation. J Clin Med. 2021;10(24):5793. 10.3390/jcm10245793.
Pontes KS, et al. Vitamin B12 status in kidney transplant recipients: Association with dietary intake, body adiposity and immunosuppression. Br J Nutr. 2019;122(04):450–8. 10.1017/s0007114519001417.
Ruangkanchanasetr P et al. (2014) ‘High prevalence of obesity in Thai renal transplant recipients: A multicenter study’, Transplantation Proceedings, 46(2), pp. 546–551. 10.1016/j.transproceed.2013.11.057
Sayilar EI, et al. The effect of calcineurin inhibitors on anthropometric measurements in kidney transplant recipients. BMC Nephrol. 2022;23(1). 10.1186/s12882-022-03004-1.
Terrec F, et al. Late conversion from calcineurin inhibitors to belatacept in kidney-transplant recipients has a significant beneficial impact on glycemic parameters. Transplantation Direct. 2019;6(1). 10.1097/txd.0000000000000964.
Tillmann FP, et al. Impact of low-dose steroids on hba1c levels and development of pre-diabetes and Nodat in non-diabetic renal transplant recipients on long-term follow-up. Int Urol Nephrol. 2017;50(4):771–7. 10.1007/s11255-017-1754-0.
van der Burgh AC, et al. Serum magnesium, hepatocyte nuclear factor 1β genotype and post-transplant diabetes mellitus: A prospective study. Nephrol Dialysis Transplantation. 2019. 10.1093/ndt/gfz145. [Preprint].
Wang Q, et al. Risk Factors of New-onset Diabetes After Renal Transplantation and Prognostic Analysis. Altern Ther. 2023;29(1):230–5.
Xu J et al. (2018) ‘Incidence and risk factors of posttransplantation diabetes mellitus in living donor kidney transplantation: A single-center retrospective study in China’, Transplantation Proceedings, 50(10), pp. 3381–3385. 10.1016/j.transproceed.2018.08.007
Xue M, et al. Interleukin-2 receptor antagonists: Protective factors against new‐onset diabetes after Renal Transplantation. J Diabetes. 2018;10(11):857–65. 10.1111/1753-0407.12663.
Yu H, et al. Risk factors for new-onset diabetes mellitus after living donor kidney transplantation in Korea - A retrospective single center study. BMC Nephrol. 2016b;17(1). 10.1186/s12882-016-0321-8.
Heisel O, et al. New onset diabetes mellitus in patients receiving calcineurin inhibitors: A systematic review and meta-analysis. Am J Transplant. 2004;4(4):583–95. 10.1046/j.1600-6143.2003.00372.x.
Małgorzewicz S, Ciechanowski K, Kozłowska L. Principles of nutrition in chronic kidney disease—Position of the Working Group of the Polish Society of Nephrology. Nephrol Forum. 2019;12:240–78.
Kluch M et al. (2020) ‘Nutrition trends in patients over the long term after kidney transplantation’, Transplantation Proceedings, 52(8), pp. 2357–2362. 10.1016/j.transproceed.2019.12.055
Pedrollo EF, et al. What is known about dietary interventions and body weight management after kidney transplantation? A scoping review. J Ren Nutr. 2023;33(1):4–11. 10.1053/j.jrn.2022.07.003.

Tables 1 to 3 are available in the Supplementary Files section.

No competing interests reported.

Download PDF

Editor assigned by journal
02 Aug, 2024
Submission checks completed at journal
31 Jul, 2024
First submitted to journal
30 Jul, 2024

You are reading this latest preprint version

Immunosuppressive Therapy and Nutritional Diseases of Patients after Kidney Transplantation: A Systematic Review

Status:

Version 1

Abstract

Figures

1. Background

2. Material and Methods

2.1. Protocol and Registration

2.2. Eligibility Criteria

2.2.1. Types of participants

2.2.2. Intervention

2.2.3. Exposure(s)

2.2.4. Outcome(s)

2.2.5. Setting and Design

2.3. Information Sources and Search Strategu

2.4. Study Selection

2.5. Data Extraction

2.6. Quality Assessment

2.7 Data Analysis

3. Results

3.1 Description of Search Results

3.2 Description of Study Characteristics

3.3 Quality Assessment

3.4 The summary of results

3.4.1 Body composition

3.4.2 Body weight

3.4.3 Diabetes

3.4.4 Lipid profile

3.4.5 Bone status

3.4.6 Vitamin D

3.4.7 Vitamin B12

3.4.8 Electrolyte disorders

4. Conclusions

Abbreviations

Declarations

References

Tables

Additional Declarations

Supplementary Files

Status:

Version 1

3.4.7 Vitamin B₁₂