Toxicity from chemotherapy is a common and unfortunate side effect of treatment that can occur even at standard doses. Oral mucositis is a common consequence in patients who have undergone high-dose chemotherapy and after hematopoietic stem cell transplantation (HSCT). Oral mucositis is frequently accompanied by pain, odynophagia, xerostomia, and dysgeusia, and it can lead to malnutrition, dehydration, and lowers the patients’ quality of life significantly (QoL) [5]. Polaprezinc (PZ), a chelated form of zinc and L-carnosine, inhibits the production of inflammatory cytokines such as tumour necrosis factor-alpha (TNF-$\alpha$), interleukin-1 (IL-1), interleukin-6 (IL-6) and matrix metalloproteinase-2 (MMP-2) and induces an anti-inflammatory effect and immune responses via inhibition of nuclear factor-kappa-light-chain-enhancer of activated B cells (NF-κB) [5, 6].

Chemotherapy-induced peripheral neuropathy (CIPN) is a typical side effect of neurotoxic chemotherapeutic drugs used to treat cancer patients. It is characterized by inflammation, damage, or degeneration of the peripheral nerve fibres. As a commonly used third-generation platinum analogue, oxaliplatin is responsible for more than 70% of symptomatic neurotoxicity of any severity, which frequently leads to treatment discontinuation [7, 8].

The oxidative stress, inflammatory, and apoptotic pathways are the responsible pathophysiological factors for Oxaliplatin-induced peripheral neuropathy (OPIN). The inflammatory cascade includes the up-regulation of the transcriptional factor NF-κB and its downstream molecule TNF-$\alpha$, while the redox pathway is associated with the elevation of malondialdehyde and the suppression of nuclear factor-2 erythroid related factor-2 (Nrf-2). Furthermore, elevated apoptotic markers such as caspase-3 can be used to assess the apoptotic signalling pathway [9, 10]. By scavenging free radicals and suppressing the inflammatory cascade, L-carnosine has an antioxidant and anti-inflammation effect on OPIN pathways that have been widely studied [11].

Pro-inflammatory cytokines, such as IL-6, and acute-phase proteins, such as C-reactive protein (CRP) are elevated in individuals with myocardial infarction (MI). The role of inflammation in the onset of MI is regarded to be significant [12]. L-carnosine has been shown to reduce the production of IL-6, and thereby it helps in the management of MI [13, 14].

Despite breakthroughs in pharmacological therapy and the introduction of novel devices, patients with heart failure continue to have a poor QoL and a lower exercise tolerance. Several factors contribute to the decline in factional capacity and exercise tolerance, including changes in endothelial and vasodilatory function, abnormalities in skeletal muscle metabolism, and reduction in muscle blood flow during exercise [15]. L-carnosine is a key antioxidant that protects against oxidative damage caused by anaerobic exercise. Lactic acid production increases during exercise, followed by dissociation into lactate and H${}^{+}$, lowering pH levels [16]. L-carnosine has an excellent buffering activity because the imidazole group of histidine binds a proton and lowers the pH value. As carnosine’s pKa is closer to that of physiological pH, it could be used as a buffer more quickly during exercise [17, 18]. Increased L-carnosine levels in the muscles may help to improve contractility and reduce fatigue [19]. Other mechanisms include regulating myocardial calcium levels, increasing the sensitivity of calcium-release channels and the contractile machinery, and improving cardiac contractility and function [20, 21].

Type 2 diabetes mellitus (T2DM) accounts for 90% of all diabetes cases. Insulin resistance is a condition in which the body does not fully respond to insulin, causing blood glucose levels to rise. Obesity, hypertension, and dyslipidemia are all common co-morbidities of T2DM [22]. Advanced glycation end products (AGEs) are a group of heterogeneous compounds that form in greater quantities in hyperglycemic conditions. The formation of covalent cross-links with proteins, increased oxidative stress, and up-regulation of inflammation are biological processes for AGEs’ detrimental effects. Increased reactive oxygen species formation and NF-κB targets-gene transcription is caused by AGEs interacting with the receptor for advanced glycation end products (RAGE), resulting in low-grade inflammation, endothelial dysfunction, platelet activation, and insulin resistance [23]. The identification of AGEs and their binding to RAGE contribute to diabetes’ micro- and macro-vascular complications [24]. L-carnosine has antioxidant properties and the ability to protect against the production of AGEs, making it useful in the treatment of T2DM [25, 26, 27].

Hyperglycemia causes aberrant glucose-dependent pathway activation, i.e., the polyol pathway, hexosamine pathway and protein kinase C pathway. Multiple components, such as transforming growth factor-beta (TGF-$\beta$), vascular endothelial growth factor (VEGF), IL-1, IL-6, and TNF, are produced by these pathways [28, 29]. Increased urine TGF-$\beta$ activates both the canonical (ALK 5, Smad 2/3) and alternative (ALK 1, Smad 1/5) pathways in diabetic individuals. Extracellular matrix accumulates at the glomerular basement membrane (GBM) and mesangium when the canonical pathway is activated. In addition, activation of the alternative pathway induces podocyte damage, which results in the effacement of the foot process. As a result, TGF-$\beta$ and metabolic pathway activation are essential determinants in the development of diabetic nephropathy [30, 31]. One of the proposed mechanisms is that L-carnosine inhibits the synthesis of TGF-$\beta$ [32].

Skin complications are common in diabetic patients, with over 30% of individuals developing some form of skin involvement during the course of their condition [33]. Xerosis of the skin is found in up to 40% of diabetic patients [34]. In T2DM, topical use of urea 5% combined with arginine and carnosine increases skin hydration and alleviates skin dryness [33].

Individuals aged 55 and up will soon make up a quarter or more of the total population of schizophrenia patients globally. Glutamate dysfunction and dysregulation of the N-methyl-d-aspartate (NMDA) receptor (glutamatergic receptor) are thought to be linked to the pathogenesis of cognitive deficits of schizophrenia [35, 36]. L-carnosine is a known antioxidant that is co-localized at glutamatergic synapses, and it helps people with schizophrenia with their deficient cellular antioxidant defences [37, 38, 39]. Furthermore, L-carnosine has been shown to modulate NMDA receptor activity, lower glutamate levels, and limit glutamate release [40, 41].

Alzheimer’s disease (AD) is the most common type of dementia, accounting for 60 to 70% of all cases. According to Hipkiss’s [42] study, certain areas of the brain are the most sensitive to damage associated with AD when carnosine levels decline with age. Furthermore, heavy metal ions can be found in the brains of people with AD, which is defined by the presence of a pathogenic form of amyloid beta protein and intracellular lesions made up primarily of the cytoskeletal protein tau [43]. L-carnosine binds to metal ions and inhibits amyloid beta formation while also acting as a “scavenger” of free radicals [44].

Given this background, we aimed to find out the efficacy of L-carnosine versus placebo, or usual treatment, or other pharmacological/non-pharmacological interventions in patients with age-related diseases such as cancer, cardiovascular disease, diabetes, and neurodegenerative disorders. We, therefore, conducted a systematic review and meta-analysis of clinical studies, which will raise awareness of the clinical usage of L-carnosine for the aforementioned disorders among healthcare professionals, researchers, patients, and the general public.

The population, intervention, comparison, outcomes, and study design (PICOS) approach was used to rate studies for eligibility [46]. Table 1 shows the PICOS criteria for inclusion and exclusion. Papers published before 2011 and articles written in languages other than English were excluded from the study.

Before defining our research question, we ran a preliminary search in PROSPERO to see if there were any current systematic reviews or meta-analyses on the same topic. PubMed, Science Direct, Proquest, Scopus, Cochrane Library, Google Scholar, Clinical Trials Registry India (CTRI), and clinical trials.org were used by two investigators (KSur and KSri) to perform an independent literature search. Various combinations and phrases of major Medical Subject Heading (MeSH) terms and non-MeSH terms, such as L-carnosine, Carnosine, $\beta$-alanine-l-histidine, L-carnosine, randomized controlled trial (RCT), ageing, cancer, cardiovascular diseases, diabetes, and neurodegenerative disorders were used in search strategies.

The EndNote reference manager was used to remove duplicates, and a final duplicate removal was done. Disagreements over the study selection were settled through discussion among the reviewers. To validate eligibility, the full texts of the selected publications were extracted and independently examined by the three reviewers (KSri, KSur, MD). In the literature search, lists of references to important articles were also checked for intelligibility. Any discrepancies were handled through consensus; with the help of a third author (KU).

One reviewer (KSur) conducted the primary literature search. The identified papers’ titles, abstracts, keywords, authors, author affiliations, year of publication, volume, issue, and DOI were exported to Microsoft Office Excel ver. 2019 (Redmond, Washington, United States). Furthermore, two reviewers (RMG and VTM) independently examined the titles and abstracts of the retrieved records to find studies that would fit the aforementioned inclusion criteria. Full-text screening was performed on an article with confusing qualifying criteria. The authors of the papers that might have an impact on the review but whose full text couldn’t be found were contacted via email and asked for the full-text article. Following that, two review team members (RMG and VTM) independently reviewed the complete texts of these possibly eligible papers for eligibility. Any differences between the RMG and VTM over the eligibility of certain studies were resolved by discussion and consensus with a third reviewer (KU). After a month, the searches were conducted again.

In a specially designed data extraction form, two independent investigators (KSri and KSur) extracted key data from all of the included publications. A discussion with the third independent investigator (MD) addressed the discrepancy amongst the reviewers, and data accuracy was validated. For each article, we extracted data on authors, year of publication, a number of participants, age, gender, history of diseases, comorbidities, clinical parameters, route of administration, dose and therapeutic regimen of the intervention and control groups, study follow-up time, randomization, concealment of allocation, blindness scheme, presence of an intention-to-treat analysis, loss of follow-up, early termination, expected results and results.

Two independent reviewers (MD and KSur) assessed the risk of bias (RoB) in the included papers using the revised Cochrane tool to assess the risk of bias, consisting of five domains: randomization procedure, deviation from intended intervention, missing outcome data, measurement of the outcome and selection of the reported result [47]. Finally, any discrepancies were resolved through discussion until an agreement was reached or by consulting a third reviewer (KS).

Among the studies that reported similar outcomes, the meta-analysis was conducted using RevMan 5.4 software (Cochrane Training, New York, NY, USA). If continuous data had baseline and endpoint scores, we looked at the change from baseline to endpoint and estimated mean difference and standard error for continuous exposure. The mean difference (MD) and 95% CI were provided as the final pooled result. A forest plot was used to show the results and study level estimations. A p-value of 0.05 was used to determine statistical significance. In each of the included studies’ analyses, the I${}^2$ statistic was utilised to assess heterogeneity. Due to the insufficient number of papers, we were unable to perform a funnel plot, hence publication bias could not be detected. When the study’s heterogeneity (I${}^2$) was less than 50%, a fixed-effects model was used for all analyses, and when the study’s heterogeneity was greater than 50%, a random-effects model was employed.

An electronic database search yielded a total of 116 studies. The titles and abstracts of 105 potentially relevant articles were evaluated after duplicate studies were removed. Based on title and abstract screening, 86 articles were eliminated. The full-text screening included the remaining 21 studies. As shown in the PRISMA flow diagram (Fig. 1), 5 studies were excluded for the following reasons: unavailable data, inappropriate study design, and unrelated outcomes. At the end of the selection process, 14 studies [5, 22, 33, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58] meeting the inclusion criteria were eventually selected for systematic review and meta-analysis. The PRISMA checklist is presented as a Supplementary File.

Fig. 1.

PRISMA flow chart illustrating the selection process for all included and excluded studies.

Table 2 (Ref. [5, 22, 33, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]) and Supplementary Table 1 list the basic characteristics of the studies that were included. These studies were published between 2011 and 2022. Studies in neurodegenerative disorders were found in 43% (6 out of 14) of the included studies [48, 49, 50, 51, 53, 56]. Diabetes mellitus was found in 29% (4 out of 14) of the studies [22, 33, 52, 57]. Two of the remaining four studies were on cancer [5, 55], while the other two were on cardiovascular diseases [54, 58]. Both genders were included in the majority of the studies. In 8 of the 14 studies, researchers looked at safety measures and reported on adverse drug reactions [5, 33, 49, 50, 52, 54, 56, 57]. Five of the studies included were from Japan [5, 51, 53, 56, 58], two from Iran [22, 50] and Italy [33, 54] and one from Poland [48], USA [49], Greece [52], Egypt [55], and Thailand [57].

All of the studies are RCT that provide clinical evidence for the efficacy of L-carnosine as an individual supplement or in combination with other supplements. Of 14 studies, 4 studies used anserine as an add-on supplement with L-carnosine in neurodegenerative disorders [48, 51, 53, 56], 2 studies used zinc as an additional supplement with L-carnosine [5, 58], and 6 studies did not use any supplements with L-carnosine [22, 49, 50, 54, 55, 57]. Federici et al. [33], study used urea and arginine as supplements along with L-carnosine. Karkabounas et al. [52], study used α-Linolenic acid (ALA) and thiamine as a supplement to L-carnosine for diabetes mellitus. As an intervention group regimen for L-carnosine supplementation, one of the included studies used chicken meat extract (CME) containing 40% carnosine related compounds (CRC) [48]. The dose and mode of administration, on the other hand, differed significantly between the included studies.

Across the studies that were considered, a wide range of outcome measures were observed. L-carnosine has been shown in cancer studies to minimize treatment-related toxicities [5, 55]. In addition, Magdy et al. [55], examined neuropathy grade and rated it using the National Cancer Institute Common Terminology Criteria for Adverse Events-version 4 (NCI-CTCAE-v4) system, revealing that L-carnosine improved OIPN by reducing the pathogenic triad of inflammation, oxidative stress, and apoptosis. The Kitagawa et al. [5], study looked at the incidence of Grade $\ge$3 oral mucositis and concluded that the PZ lozenge could be helpful in preventing oral mucositis associated with chemotherapy in HSCT patients.

Lombardi et al. [54], study had the primary outcome measure to evaluate the exercise parameters [distance at 6-minute walk test (6-MWT)] and cardiopulmonary exercise test) and the effects on QoL [EuroQol-5D (EQ-5D) and visual analogue scale (VAS)] among congestive heart failure (CHF) patients and concluded that L-carnosine added to conventional therapy may improve exercise performance and QoL. The zinc concentration, cardiac enzymes, and the level of inflammation markers in blood and urine samples were analysed in the Yoshikawa et al. [58], study, and it was found that it improves cardiac function post-acute myocardial infarction (AMI), and that this effect may be due to anti-inflammatory processes through the suppression of IL-6. Ejection fraction was a common outcome in cardiovascular diseases between these 2 studies [54, 58].

Federici et al. [33], study examined the evolution of a 9-point grading xerosis assessment scale (XAS) score and a 4-point grading overall cutaneous score (OCS) score in T2DM patients, which enhances skin hydration and alleviates the state of severe skin dryness. Fasting blood sugar (FBS), total cholestrol (TC), high- density lipoprotein cholesterol (HDL-c), low-density lipoprotein cholesterol (LDL-c), Glycated hemoglobin (HbA1c), fasting insulin, homeostatic model assessment of insulin resistance (HOMA-IR), homeostatic model assessment of insulin secretion (HOMA-$\beta$), triglycerides (TG) and serum levels of pentosidine Carboxymethyl lysine (CML), soluble receptor of advanced glycation end products (sRAGE), TNF-$\alpha$, interleukin-1ß (IL-1ß), IL-6 were examined in Houjeghani et al. [22], study. They found that L-carnosine improved glycemic control, lipid profile, AGEs, and low-grade inflammation without changing soluble receptor of AGEs, IL-6 and IL-1ß.

The glycemic profile, lipid profile, kidney function, liver function, tissue damage, thyroid function, cancer markers, electrolytes, minerals, oxidative stress, platelet activating factor (PAF), arachidonic acid, epinephrine, thrombin, and collagen were all examined in the Karkabounas et al. [52], study, which found that L-carnosine as an added supplement reduced glucose concentration in T2DM patients by potentially increasing insulin production from the pancreas.

Siriwattanasit et al. [57], looked at the change in urine TGF-$\beta$ levels in T2DM patients with diabetic nephropathy and showed lower urinary TGF-$\beta$ levels. HbA1c, FBS, LDL-c, HDL-c, TG, and TC are typical laboratory variables examined in the included diabetic studies [22, 52, 57]. A comparable analysis of serum creatinine (serum Cr.) was found in [52, 57] study.

Budzen et al. [48], study investigated cognitive function, the existence of depressive symptoms, physical capacity, body measures, blood pressure (BP), and heart rate (HR) in neurodegenerative disorder patients. They also looked at the mini mental state examination (MMSE) and short test of mental status (STMS) to test cognitive functions, the geriatric depression scale (GDS) to examine the presence of depressive symptoms, and the clinical dementia rating (CDR) to assess dementia severity, and found that L-carnosine supplementation in the elderly could have positive effects on cognitive functioning and physical capacity.

Based on the results of a neurocognition set-shifting test and a strategic target detection test, L-carnosine was found to be an additional treatment to ameliorate executive dysfunction in people with schizophrenia [49]. The difference in positive and negative syndrome scale (PANSS) negative subscale score reduction and hamliton depression rating scale (HDRS) was used to assess changes in depressive symptoms, and L-carnosine as an add-on to risperidone was found to have good tolerability and considerable favourable effects on negative symptoms in individuals with chronic stable schizophrenia [50].

The outcome measured in the Hisatsune et al. [51], study included a semi-quantitative dietary survey; cognitive testing: Wechsler memory scale-revised logical memory immediate recall (WMS-LM1), Wechsler memory scale-revised logical memory delayed recall (WMS-LM2), Alzheimer’s disease assessment scale (ADAScog), beck depression inventory (BDI), study, 36-item d physical health component summary (SF-36 MCS), and study, 36-item d physical health component summary (SF-36 PCS); blood samples and immunoassays; microarray analysis and acquisition of human Magnetic Resonance Imaging (MRI) data and MRI data analysis; and microarray analysis and acquisition of human MRI data. The Anserine and Carnosine (ACS) and placebo groups in this trial consumed the same amount of anserine and carnosine from their diets, according to the survey results.

Katakura et al. [53], evaluated dietary survey outcome measures using a semi-quantitative method; cognitive testing: WMS-LM1, WMS-LM2, ADAScog, BDI, SF-36 MCS and SF-36 PCS; microarray analysis and real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR), which found that ACS may preserve verbal episodic memory, likely due to CCL24 suppression in the blood, especially in elderly participants.

Inventory of anserine and carnosine in the Normal Diet; Blood Analysis; Cognitive Testing: MMSE, gloCDR, CDRsob, WMS-1, WMS-2, ADAS and GDS; and electroencephalogram (EEG) recording were used in the Masuoka et al. [56], study, which showed that the results did not indicate that ACS has significant efficacy on cognitive change in mild cognitive impairment (MCI) subjects but might suggest that ACS has a beneficial effect in APOE4 (+) MCI subjects exists, and thereby, ACS might help to prevent a transition from MCI to AD as a secondary effect in APOE4 (+) MCI subjects.

WMS-1, WMS-2, and ADAS [51, 53, 56] were the most commonly used outcome measures in neurodegenerative disorder studies, followed by BDI, SF-36 MCS, and SF-36 PCS [51, 53], GDS [48, 51, 56] and MMSE [48, 56].

Supplementary Table 2 shows the RoB assessment for each of the studies. All reports were critically examined using the standard checklist for the revised Cochrane RoB tool. The method of randomization is rarely described, despite the fact that randomization is an important tool to reduce bias. The method of randomization was not reported in any of the included trials, or there was insufficient information. Fourteen RCTs were analyzed for the effect of L-carnosine in various age-related diseases such as cancer [5, 55], cardiovascular disease [54, 58], diabetes mellitus [22, 33, 52, 57] and neurodegenerative disorder [48, 49, 50, 51, 53, 56].

The bias arising from randomization technique was “low risk” for all 14 included studies in a quality assessment using the Revised Cochrane Risk of Bias Tool for RCT, whereas bias due to deviation from intended intervention had “some concerns” for 5 studies [5, 33, 54, 55, 58] and low risk for the other 9 [22, 48, 49, 50, 51, 52, 53, 56, 57].

Bias for missing outcome data was found to be “low risk” in all of the included studies. Only one study [33] found a “low risk” of bias in outcome measurement, whereas the remaining 13 studies had “some concerns” about outcome measuring. All of the studies that were considered demonstrated a “low risk” of selecting the reported result. All of the studies were evaluated separately, and the aggregate assessment had a “low risk” of bias (Supplementary Table 2).

Only four studies [5, 33, 55, 57] identified a “high risk” of allocation concealment in the selection bias (Fig. 2), and one study identified an “unclear risk” of allocation concealment in the selection bias [54]. Only six studies had a “high risk” of performance bias due to participant and personnel blinding [5, 33, 54, 55, 57, 58]. However, in one trial, the outcome assessors were blinded [33]. The random sequence generation in selection bias was addressed in all of the studies. All of the papers were evaluated to see if the research question, study population, and L-carnosine indices were well described. Other causes of bias, such as medication pooling, dropouts, unit-of-analysis mistakes, design-specific bias, and conflicts of interest, were not mentioned in these studies.

Fig. 2.

Methodological quality of the included studies based on the revised Cochrane risk of bias tool for randomized trials. (A) Overall risk of bias. Each item is presented as a percentage based on all included studies. (B) Individual risk of bias. Each item is scored as ‘weak’, ‘moderate’, or ‘strong’.

Primarily, we analysed whether or not L-carnosine supplementation had a positive impact on age-related diseases such as cancer, cardiovascular disease, diabetes mellitus, and neurodegenerative disorders. We used 14 studies in our qualitative analysis [5, 22, 33, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 58]. Five studies were excluded from the quantitative synthesis [5, 33, 49, 50, 55] because they did not correlate with the outcome variables and did not report any data with the other included studies under each age-related disease.

3.6.1 Effect of L-Carnosine in Cardiovascular Disease Patients

Two studies [54, 58] looked at the effects of L-carnosine on patients with cardiovascular disease. On the ejection fraction, there was no statistically significant difference between the L-carnosine and control groups [MD 95% CI = 0.82 (–2.38, 4.01); p = 0.62; p = 0.56; I${}^2$ = 0%] (Fig. 3).

Fig. 3.

Effect of L-carnosine in cardiovascular disease patients. Effect of L-carnosine treated versus control on measures of ejection fraction in patients with cardiovascular disorders. CI, confidence interval; df, degrees of freedom; IV, inverse variance; SE, standard error.

3.6.2. Effect of L-Carnosine in Diabetes Mellitus Patients

HbA1c, FBS, LDL-c, HDL-c, TGs, TCs, and serum Cr. were used to study the effect of L-carnosine in diabetes mellitus patients. Three studies (n = 248) [22, 52, 57] showed a statistically significant difference between the L-carnosine group and the control group on HbA1c [MD 95% CI = –1.25 (–2.49, –0.022); p = 0.05; p = 0.001; I${}^2$ = 85%] (Fig. 4A) and FBS [MD 95% CI = –12.44 (–22.44, –2.44); p = 0.01; p = 0.40; I${}^2$ = 0%] (Fig. 4B), favouring the L-carnosine group.

Fig. 4.

Effect of L-carnosine in diabetes mellitus patients. (A) Effect of L-carnosine treated versus control on measures of HbA1c in patients with diabetes mellitus. (B) Effect of L-carnosine treated versus control on measures of FBS in patients with diabetes mellitus. (C) Effect of L-carnosine treated versus control on measures of LDL-c in patients with diabetes mellitus. (D) Effect of L-carnosine treated versus control on measures of HDL-c in patients with diabetes mellitus. (E) Effect of L-carnosine treated versus control on measures of TGs in patients with diabetes mellitus. (F) Effect of L-carnosine treated versus control on measures of TCs in patients with diabetes mellitus. (G) Effect of L-carnosine treated versus control on measures of serum Cr. in patients with diabetes mellitus. HbA1c, glycated hemoglobin; FBS, fasting blood sugar; LDL-c, low-density lipoprotein cholesterol; HDL-c, high-density lipoprotein cholesterol; TGs, triglycerides; TCs, total cholesterol; Cr, creatinine; CI, confidence interval; df, degrees of freedom; IV, inverse variance; SE standard error.

On the other hand, there was no statistically significant difference between the L-carnosine and control groups on the LDL-c [MD 95% CI = –4.70 (–13.33, 3.94); p = 0.29; p = 0.36; I${}^2$ = 2%] (Fig. 4C), HDL-c [MD 95% CI = –0.50 (–3.82, 2.82); p = 0.77; p = 0.77; I${}^2$ = 0%] (Fig. 4D), TGs [MD 95% CI = –0.42 (–6.02, 5.19); p = 0.88; p = 0.44; I${}^2$ = 0%] (Fig. 4E) and TCs [MD 95% CI = –5.09 (–11.81, 1.63); p = 0.14; p = 0.60; I${}^2$ = 0%] (Fig. 4F) in three studies (n = 248) [22, 52, 57]. L-carnosine does not alter the levels of serum creatinine [MD 95% CI = 0.06 (–0.12, 0.24); p = 0.51; p = 0.27; I${}^2$ = 19%] in two studies (n = 204) [52, 57] (Fig. 4G).

3.6.3. Effect of L-Carnosine in Neurodegenerative Disorder Patients

Variables such as WMS-1, WMS-2, ADAS, BDI, SF-36 MCS, SF-36 PCS, MMSE, and GDS were used to find the effect of L-carnosine in patients with neurodegenerative disorder. On WMS-1, the association between the three studies (n = 149) [51, 53, 56] revealed no statistically significant difference between the L-carnosine and control groups [MD 95% CI = 0.26 (–0.79, 0.26); p = 0.33; p = 0.75; I${}^2$ = 0%] (Fig. 5A), however the same studies showed the statistically significant difference between the groups on WMS-2 [MD 95% CI = 1.34 (0.83, 1.85); p 0.00001; p = 0.43; I${}^2$ = 0%] (Fig. 5B).

Fig. 5.

Effect of L-carnosine in neurodegenerative disorder patients. (A) Effect of L-carnosine treated versus control on measures of WMS-1 in patients with neurodegenerative disorder. (B) Effect of L-carnosine treated versus control on measures of WMS-2 in patients with neurodegenerative disorder. (C) Effect of L-carnosine treated versus control on measures of ADAS in patients with neurodegenerative disorder. (D) Effect of L-carnosine treated versus control on measures of BDI in patients with neurodegenerative disorder. (E) Effect of L-carnosine treated versus control on measures of SF-36 MCS in patients with neurodegenerative disorder. (F) Effect of L-carnosine treated versus control on measures of SF-36 PCS in patients with neurodegenerative disorder. (G) Effect of L-carnosine treated versus control on measures of MMSE in patients with neurodegenerative disorder. (H) Effect of L-carnosine treated versus control on measures of GDS in patients with neurodegenerative disorder. GDS, geriatric depression scale; WMS-1, wechsler memory scale-revised logical memory immediate recall; WMS-2, wechsler memory scale-revised logical memory delayed recall; ADAS, Alzheimer’s disease assessment scale; BDI, beck depression inventory; SF-36 MCS, 36-item short form survey for mental-health component summary scores; SF-36 PCS, 36-item short form survey for physical-health component summary scores; MMSE, mini mental state examination; CI, confidence interval; df, degrees of freedom; IV, inverse variance; SE, standard error.

On the ADAS, a statistically significant difference was observed between the L-carnosine and control groups of the three studies (n = 149) [51, 53, 56] [MD 95% CI = 0.98 (–1.55, –0.42); p = 0.0007; p = 0.86; I${}^2$ = 0%] favouring the control group over the L-carnosine group (Fig. 5C). Similarly, on BDI, a statistically significant difference was observed between the L-carnosine and control groups of the two studies (n = 99) [51, 53], favouring the control group over the L-carnosine group (Fig. 5D).

Pooling analysis of the SF-36 MCS [MD 95% CI = –0.25 (–1.29, 0.79); p = 0.64; p = 0.55; I${}^2$ = 0%] and SF-36 PCS [MD 95% CI = 0.53 (–0.47, 1.52); p = 0.30; p = 0.71; I${}^2$ = 0%], as shown in Fig. 5E,F, revealed that there was no statistically significant difference between the L-carnosine group and the control group in the two studies (n = 99) [51, 53].

Meta-analysis of data from three studies (n = 140) [48, 51, 53] showed no statistically significant difference in MMSE score between the L-carnosine and control groups [MD 95% CI = 0.50 (–0.60, 1.60); p = 0.37; p = 0.97; I${}^2$ = 0%] (Fig. 5G). Similarly, in GDI also no statistically significant difference between the L-carnosine and control groups in two studies (n = 101) [48, 53] [MD 95% CI = 0.01 (–1.73, 1.76); p = 0.99; p = 0.97; I${}^2$ = 0%] (Fig. 5H).