Seven Lakes High School, 9251 S Fry Rd, Katy, TX 77494, USA

Corresponding Author: Elizabeth Wu, Seven Lakes High School, 9251 S Fry Rd, Katy, TX 77494, USA. E-mail: elizabethwu38@gmail.com.

Running title: META-ANALYSIS OF CURCUMIN-LOADED NANOPARTICLES FOR AD TREATMENT

	ABSTRACT
	INTRODUCTION
	METHODS
	RESULTS
	DISCUSSION
	ACKNOWLEDGEMENTS
	ABBREVIATIONS
	CONFLICTS OF INTEREST
	REFERENCES

	ABSTRACT

Alzheimer’s Disease (AD) is a progressive disorder that affects millions of people, and that number continues to grow each year. Currently, the exact causes of AD are not fully understood, and there are no cures are available. Recently, many studies have shown that curcumin treatment may be beneficial to AD. Nevertheless, the efficacy of curcumin is significantly limited by its low aqueous solubility and poor capacity to cross the blood-brain barrier. To address this challenge, curcumin-loaded nanoparticles have been extensively studied, showing improved efficacy for AD treatment. However, to date, comparative studies for the efficacy of curcumin delivered by different nanoparticle types for the AD treatment are lacking. In this article, I review two types of curcumin-loaded nanoparticles, polymer nanoparticles and lipid nanoparticles, and conduct a meta-analysis to compare their efficacies for the treatment of AD. The meta-analysis result indicates that there is no statistical significance in the efficacy of these two types of curcumin-loaded nanoparticles for the AD though each type of curcumin-loaded nanoparticles shows favorable outcomes in comparison to the control groups, suggesting that either polymer nanoparticles or lipid nanoparticles for curcumin delivery would be equally effective for AD treatment.

	INTRODUCTION

   Alzheimer’s Disease (AD) is a neurodegenerative disorder that impairs memory, cognition, and behavior. It is the most common cause of dementia and the sixth leading cause of death in the United States, affecting approximately 5.8 million people, usually at the age of 65 years and older (1). The exact causes of AD are not fully understood, but it is believed that a combination of genetic, environmental, and lifestyle factors contribute to AD origination (2). To date, there are no cures available for AD, but doctors are continuously finding and testing potential treatments (3). In the past few decades, amyloid plaques and neurofibrillary tangles of tau protein have been identified as two likely culprits and have been the focus of major AD research (4-7).

   Curcumin, a chemical compound isolated from the plants of the Curcuma longa species, has been studied for the treatment of AD (8-11). Nevertheless, the efficacy of curcumin used for such purposes is significantly limited by its low aqueous solubility and poor capacity to cross the blood-brain-barrier (BBB). To address this challenge, nanoparticles have been explored as a drug delivery system for curcumin to treat AD (12-21). For instance, Tiwari et al. reported that curcumin encapsulated poly lactic-co-glycolic acid (PLGA) nanoparticles potently induced neuron stem cell proliferation and neuronal differentiation in vitro, and, and reversed learning and memory impairments in the hippocampus and subventricular zone of adult rats by inducing stem cell neurogenesis in an AD rat model (14) . In another study, Huang et al. administrated the nanoparticles to AD mice, showing that the PLGA nanoparticles significantly improved the spatial memory and recognition in transgenic AD mice, remarkably decreased the level of amyloid-β plaques, reactive oxygen species and enhanced synapse numbers in the AD mouse brains (15). In addition, lipid-based nanoparticles are another commonly used nanoparticles in AD treatment. Kakkar et al. reported that curcumin-solid lipid nanoparticles (SLNs) enhanced curcumin bioavailability by 32-155 times in mice and alleviated behavioral, biochemical, and histochemical changes in AD-like mice, highlighting the potential of curcumin-SLNs for treatment of AD (16) . Maiti et al. discovered that curcumin-SLNs prevented the increase of phosphorylated tau after exposure to amyloid-β 42 and ultimately decreased the tau as well (17).

   Although curcumin-loaded nanoparticles for AD treatment have been examined in many studies, comparative studies for the efficacy of curcumin delivered by different nanoparticle types are lacking. In this article, I compare two types of curcumin-loaded nanoparticles, polymer nanoparticles and lipid nanoparticles by a meta-analysis to identify which type of nanoparticle would be more efficacious for AD treatment.

	METHODS

   Data Collection

   I performed systematic literature searches in PubMed (MEDLINE), EBSCO, and Google Scholar by using the keywords: ((polymer nanoparticles) OR (lipid nanoparticles)) AND (Alzheimer) AND (Morris Water Maze) AND (curcumin). The Morris Water Maze was used as one search keyword because it is a common test to study AD in rodents by assessing spatial learning and memory of rodents that rely on distal cues to navigate from start locations around the perimeter of an open swimming arena to a submerged escape platform at the end (22). Only the articles that were published between January 1st, 2010 and February 28th, 2021 were examined to eliminate outdated research results.

   Once all the relevant articles were collected, their full texts were reviewed for the quantitative data needed for the study including escape latency, standard deviation/standard error, and sample size. Since the explicit numbers associated with the reported graphs in the studies were unavailable, attempts were made to contact the authors of the articles by email to request the data from their graphs, but none of them replied. Next, the Page Ruler Redux Google Chrome Extension was used to measure the pixels on the graph with the page at maximum zoom. This tool is extremely precise as it measures the pixels on the graph and should be very close to the exact numbers. I started from the origin of the graph and measured until the next interval, entering the data to a Microsoft Excel spreadsheet afterwards. A scatter plot graph was created for each study, and the escape latency was plotted on the x-axis and the number of pixels from the origin as the y-axis. Using the line of best fit, I was able to plug in the number of pixels and find the mean escape latency as well as the standard deviation/standard error. Finally, all the gathered data was inputted into the RevMan5 software for analysis.

   Meta-analysis

   Meta-analyses were performed using RevMan5 software (the Cochrane Collaboration, Copenhagen, Denmark) and reported in accordance with the reporting guidance provided in the PRISMA statement (23). A continuous data type was used since the escape latency was given with the mean and standard deviation, and the number of mice or rats used in the experiment (the sample size). To compare the effects of lipid with those of polymer nanoparticles to determine if there was a significant difference, a subgroup analysis was used. The experimental data and control data within each group (lipid nanoparticles or polymer nanoparticles) were first compared, and then the subgroup analysis function compared the two groups to one another. Zhang et al. has demonstrated that this subgroup analysis method with RevMan5 was effective for comparing neuroprotective effects of Quercetin in different AD models (24). An inverse variance statistical method and the random effects analysis model were used. The effect measure chosen was the standardized mean difference, meaning that each study may have conducted their tests slightly differently and reached the results in a slightly different way. Since some studies used mice and others used rats, the standardized mean difference was the best effect measure. The standard 95% confidence interval was used with a p value equal to 0.05, and a forest plot was produced with the data.

	RESULTS

   Literature Search

   The keywords, ((polymer nanoparticles) OR (lipid nanoparticles)) AND (Alzheimer) AND (Morris Water Maze) AND (curcumin), were used for literature search in PubMed (MEDLINE), EBSCO and Google Scholar. The search yielded 81 articles from the EBSCO database, and 72 articles from other resources (Google Scholar and PUBMED) during 2010- 2021. After removing 14 duplicate articles that overlapped between EBSCO, Google Scholar, and PUBMED, a total of 139 articles were finally obtained, and their full texts were assessed carefully. Among them, 133 were excluded as they do not have the essential Morris Water Maze test or in vivo data required for the meta-analysis. Finally, six articles were found to meet the criteria outlined in the Methods section, and they were reviewed in full, and their reported data was extracted for the meta-analysis (Table 1). The article selection process is summarized in Figure 1.

   Implementing the statistical analysis described in the Methodology, a forest plot was generated using the six selected studies based on the selection criteria. There were 60 mice and rats studied altogether: 36 treated with curcumin-loaded polymer nanoparticles and 24 treated with curcumin-loaded lipid nanoparticles. The forest plot displays the estimated data for each study, the total number of animals, the weight of each study, and the standard mean difference with the 95% confidence interval. The point estimate is -6.27 for the difference between standard means (Figure 2). The p-value for the polymer nanoparticles is 0.02, and the p-value for the lipid nanoparticles is 0.003 (Figure 2).

   The meta-analysis shows that in comparing the control group (saline) and the experimental group (curcumin nanoparticle), there was a significant efficacious difference between these two groups. The experimental group statistically significantly improved the memory and cognitive behavior of the mice compared to the saline. There was a p-value of 0.02 for the curcumin-loaded polymer nanoparticles and a p-value of 0.003 for the curcumin-loaded lipid nanoparticles, indicating that the results were statistically significant.

   However, the meta-analysis results indicate that the p-value for the “test for subgroup differences” is 0.11, suggesting that there is no statistically significant difference between the effects of the curcumin-loaded polymer and the curcumin-loaded lipid nanoparticles treating the cognitive behavior and memory of AD rodent models (Figure 2). In summary, the meta-analysis of the published studies of the curcumin-loaded polymer and the curcumin-loaded lipid nanoparticles in the rodent AD models shows that both types of curcumin-loaded nanoparticles may be equally effective in the treatment of Alzheimer’s Disease.

View larger version : [in a new window] Figure 1. Flow chart of the literature search strategy and the process of manuscript selection.

 

View larger version : [in a new window] Figure 2. The forest plot of the curcumin-loaded lipid nanoparticles and the curcumin-loaded polymer nanoparticles for the treatment of AD. Black diamond represents the standard mean difference, and the p-value, identifying the statistical significance, is displayed at the bottom of the figure.

	DISCUSSION

   Curcumin-loaded nanoparticles have shown improved efficacy for the AD treatment as they can overcome solubility and poor capacity to cross the blood-brain-barrier. However, to date, comparative studies for the efficacy of curcumin delivered by different nanoparticle types for the AD treatment are lacking. In this study, I performed a meta-analysis to compare two types of nanoparticles, lipid nanoparticles and polymer nanoparticles, which are encapsulated with curcumin for AD treatment. The result indicates that the difference between the standard means of the escape latency for the experimental group and the control group of curcumin-loaded polymer and lipid nanoparticles were -4.04 and -10.05, respectively (Figure 2). Since these standard mean differences are less than zero, the efficacy of curcumin-loaded nanoparticle treatment is favored over the control treatment. Furthermore, the difference between the standard means of the escape latency for the overall effect of the curcumin-loaded nanoparticles was -6.27, suggesting that both the curcumin-loaded polymer and lipid nanoparticles are favored, and there is no significant difference in AD treatment efficacy between the two types of curcumin-loaded nanoparticles. The p value (0.11) of the “test for subgroup differences,” further supports that there is no statistically significant difference for the AD treatment efficacy between curcumin loaded lipid and polymer nanoparticles. This finding may explain why polymeric nanoparticles and solid lipid nanoparticles make up 40% and 22% of all reported nanoparticle drug deliveries, respectively (25). On the other hand, the p-value for the curcumin-loaded polymer and lipid nanoparticles in comparison to saline are both lower than 0.05, confirming that polymer and lipid nanoparticles are effective for curcumin delivery to treat AD. This is consistent with the previous reports that a large improvement in cognitive terms in the rats treated with curcumin-loaded lipid nanoparticles compared to those treated with saline (26-28). Furthermore, due to the small number of studies, there is notable bias in the heterogeneity test, and it is not plausible to determine the cause of the heterogeneity or draw a conclusion from the I2 value. The 95% confidence intervals (CI) confirms that curcumin nanoparticles are beneficial in Alzheimer’s treatment, whether the material is polymer or lipid since it does not contain zero. In summary, both curcumin-loaded lipid and polymer nanoparticles effectively enhance the AD conditions in rodent models, and there is no statistical significance that one type of nanoparticles is better than the other type in the examined two types of nanoparticles.

   Given the broad range of curcumin-loaded nanoparticles and very few clinical trials, the meta-analysis may produce a result that is not generally applicable outside the scope of curcumin associated with lipid and polymer nanoparticles as there may be a significant difference with a different drug or other nanomaterials. Most of the studies regarding nanoparticles have a small sample size that cannot be generalized to the entire population, and more samples required to reach a reliable conclusion are lacking. Another main limitation to the meta-analysis is the risk of bias or error in each study, so it is important to interpret the results with caution. Even though the data included in the meta-analysis did not have the exact decimals, the numbers estimated using the Page ruler Redux, a tool that allows for precise pixel measurements on the web page. was the most accurate option and should not have a huge difference that impacts the validity of the results. Moreover, the inability to control the procedures of the study and the dissimilarity of the studies are drawbacks; however, when all of the studies are compiled together, the individual differences of each study can be balanced to generate a substantial result. Future research may compare different drugs in numerous types of nanoparticles with a variety of parameters in order to discover the best treatment in the pre-clinical studies and eventually clinical trials.

	ACKNOWLEDGEMENTS

   I would like to thank Parinaz Fathi at the NIH and Tiffany Zhang at the Weill Cornell Graduate School of Medical Sciences for my research guidance.

	ABBREVIATIONS

AD	Alzheimer’s Disease
PLGA	Poly lactic-co-glycolic acid
BBB	Blood-Brain Barrier
SLN	Solid Lipid Nanoparticles
NP	Nanoparticles
CI	Confidence Interval

	CONFLICTS OF INTEREST

   The authors declare that no conflicting interests exist.

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