Open Access
Issue
Parasite
Volume 31, 2024
Article Number 9
Number of page(s) 13
DOI https://doi.org/10.1051/parasite/2024007
Published online 09 February 2024

© Y. Wang et al., published by EDP Sciences, 2024

Licence Creative CommonsThis is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Introduction

The Microsporidia, infecting a broad range of both vertebrate and invertebrate hosts, live exclusively within host cells [30]. This group of parasites currently comprises more than 200 genera and 1,600 species, including relatively common species, such as Encephalitozoon cuniculi, Enterocytozoon bieneusi, Encephalitozoon intestinalis, and Encephalitozoon hellem [5, 75]. Enterocytozoon bieneusi is the most important zoonotic microsporidian species worldwide and is transmitted predominantly through the fecal-oral route because it is capable of infecting a broad range of hosts, including humans, domestic animals, poultry, companion animals, birds, and wildlife [14, 63].

Enterocytozoon bieneusi was first identified in human immunodeficiency virus (HIV) patients in 1985, and with the expansion of the HIV epidemic, the number of cases of E. bieneusi infections in humans has increased [29]. To date, more than 200 genotypes have been identified and classified into 11 groups (groups 1–11) [40]. The genotypes identified in Group 1 are predominantly present in the human population, with the most frequently occurring ones being A, D, EbpC, and Type IV [40]. Although genotypes from other groups can also infect humans, they are relatively rare and are generally considered to have little public health significance [42].

Enterocytozoon bieneusi infection is associated with persistent diarrhea, malabsorption, and wasting diathesis in individuals with compromised immune systems, particularly those diagnosed with acquired immunodeficiency syndrome (AIDS) and can lead to life-threatening chronic diarrhea [6, 51, 87]. Patients with normal immune function can also develop self-limited diarrhea lasting up to one month [70]. Unfortunately, there are no currently effective treatments available for E. bieneusi infection [41]. Due to its importance and potential threat to public health, E. bieneusi has been classified as a Category B agent by the National Institutes of Health (NIH, https://www.niaid.nih.gov/research/emerging-infectious-diseases-pathogen), making it a second-highest priority organism/biological agent [97]. In addition, many public health organizations and academic institutions in various countries and regions have included E. bieneusi in their monitoring and control plans for infectious pathogens to ensure public health and safety.

Here, we present a systematic review and meta-analysis that evaluates the prevalence of human E. bieneusi infection in endemic regions. Our analysis considered various potential risk factors, such as gender, age, season, and geographic location.

Material and methods

Search strategy

We searched for all studies on the prevalence of E. bieneusi infection in humans around the world up to July 2022 from six databases, i.e., China National Knowledge Infrastructure (CNKI), VIP Chinese Journal Database (VIP), Wanfang Data, PubMed, Web of Science, and ScienceDirect. The retrieval strategy for the three Chinese databases was to use the search keywords “humans (in Chinese)” and “Microsporidia (in Chinese)”, in advanced retrieval. The three English-language databases were searched using search formulas, as follows: Web of Science: (TI=(Humans) OR TI=(Man) OR TI=(Homo sapiens)) AND (TI=(Microsporidia) OR TI=(Microsporidium) OR TI=(Microsporidiums)); ScienceDirect: (Human OR “Homo sapiens” OR Man) AND (Microsporidia OR Microsporidiums OR Microsporidium); PubMed: ((“Humans”[Mesh]) OR (Homo sapiens[Title/Abstract]) OR (Man[Title/Abstract]) OR (Man, Modern[Title/Abstract]) OR (Modern Man[Title/Abstract]) OR (Human[Title/Abstract])) AND (“Microsporidia”[Mesh]) OR (Microsporidias[Title/Abstract]) OR (Microspora[Title/Abstract]) OR (Microsporidians[Title/Abstract]) OR (Microsporidian[Title/Abstract]) AND (“epidemiology” [MeSH]) OR (epidemics[Title/Abstract])) OR (prevalence[Title/Abstract])) OR (frequency[Title/Abstract])) OR (surveillance[Title/Abstract])) OR (incidence[Title/Abstract])) OR (occurrence[Title/Abstract])).

Inclusion and exclusion criteria

The literature aggregation software used was Endnote X9.3.2 [15]. The inclusion criteria for this meta-analysis were as follows: (1) study on the prevalence of E. bieneusi in humans; (2) data must include a clear total number of surveyed humans and the number of positives; (3) the articles must have full text; and (4) the research must be designed to scale out. The exclusion criteria for this meta-analysis were as follows: (1) not Chinese or English literature; (2) data error, no data or data duplication in studies; (3) the research subject is not E. bieneusi and humans; (4) conference report or summary; and (5) no detailed positivity rate.

Data extraction

Two authors independently extracted and recorded the data. The lead author of this meta-analysis further evaluated any differences or uncertainties regarding research qualifications. The extracted data included the article title, testing method, residence, HIV or diarrhea, article quality, age and gender of the patient, country, longitude and latitude, altitude and climate, and the total and positive numbers. The geographic data (longitude, latitude, and altitude) collected were from the National Oceanic and Atmospheric Administration (NOAA; https://www.ncei.noaa.gov/maps/monthly/). We also considered various socioeconomic variables (World Bank–income category, National population in 2021, and the human development index (HDI): https://data.worldbank.org/, https://population.un.org/, and https://hdr.undp.org/).

Statistical analyses

This meta-analysis was performed according to the PRISMA statement [67]. The “meta” package (version 6.0-0) in RStudio (version 4.0.5) was employed to analyze the data. Before performing the meta-analysis, we tested five transformation methods (Table S1). The W-value close to 1 and the p-value > 0.05 were close to the normal distribution criterion. We used Cochran-Q, I2 statistics, and χ2 tests to calculate the heterogeneity between studies. When p-value < 0.05 and I2 > 50%, this indicates the existence of heterogeneity, and the random effect model was adopted; when p-value > 0.05, I2 < 50%, this indicates that there is no heterogeneity, and the fixed effect model was adopted. A forest plot was used to visualize the statistical results of the meta-analysis; a funnel plot and Egger test detected the publication bias of the research; the sensitivity analysis evaluated the stability of the meta-analysis model and the reliability of the results; and subgroup analysis and univariate regression analysis verified the potential source of heterogeneity.

Results

Search results

A total of 1,485 publications were identified, and after the titles and abstracts were reviewed, 1,326 papers were selected for full-text reading. According to the inclusion and exclusion criteria, 75 studies were finally included after screening (Fig. 1 and Table S2). Among them, 40 publications had 4 points, 26 publications had 3 points, and 9 publications had 2 points (Table S2).

thumbnail Figure 1

Flow diagram of literature search and selection.

Qualification research and publication bias

This study used PLOGIT for data transformation (Table S1; W = 0.98608, p = 0.5848). The forest plot of global human infection with E. bieneusi showed high heterogeneity (χ2 = 1.6138, I2 = 96.0%, p < 0.01), so a random effects model was used (Fig. 2). According to the funnel plot and Egger test, there was publication bias in this study (p = 0.0001; Table S3, Figs. S1, and S2). There were 24 supplementary articles shown in the trim and fill analysis (Fig. S3). Based on the sensitivity test, the data after restructuring were not significantly affected (Fig. S4). Figure 3 shows the distribution of human E. bieneusi prevalence. Distribution is essentially worldwide, but there are few reports from North America.

thumbnail Figure 2

Forest map of global human infection in E. bieneusi.

thumbnail Figure 3

Map of E. bieneusi prevalence in human worldwide.

Meta-analysis of E. bieneusi prevalence in humans worldwide

Detailed data on global human E. bieneusi prevalence are summarized in Tables 1 and 2. The global prevalence of E. bieneusi infection in humans was 6.59% (95% CI: 4.97–8.68). The highest prevalence of E. bieneusi in the male population was 5.50% (95% CI: 3.54–8.45). Concerning the environment of residence, rural areas had the highest rate at 7.58% (95% CI: 4.22–13.25). The prevalence of E. bieneusi in teenagers was 10.97% (95% CI: 5.90–17.36). The infection rate was 16.5% (95% CI: 11.47–22.18) in patients with diarrhea, and 10.54% (95% CI: 5.79–16.44) in patients without diarrhea. The rate of infection in patients with cancer was 69.89% (95% CI: 60.13–78.84), and the rate of infection in other patients was also high, i.e., 39.00% (95% CI: 32.34–45.87) in bone marrow transplant patients, 14.4% (95% CI: 9.84–19.62) in patients with HIV, etc. Concerning the analyzed geographic factors, the positive rate of E. bieneusi was the highest in humans living at altitudes <10 m (6.42%; 95% CI: 4.02–10.08). According to the analysis of climatic factors, we found that the temperate zone marine climate had the highest positive rate of human E. bieneusi (13.55%; 95% CI: 3.19–42.73; Table 1).

Table 1

Summary of global E. bieneusi human infection rates and relevant characteristics.

Table 2

Prevalence estimates of E. bieneusi infection, and estimated numbers of infected people in 34 countries.

According to income level, the highest prevalence rates of E. bieneusi infection was in countries with high (9.53%; 95% CI: 5.01–17.37) and lower-middle (7.31%; 95% CI: 5.17–10.24) income levels, with the lowest prevalence estimated for upper-middle income countries (5.07%; 95% CI: 3.24–7.85). According to HDI, the level subgroup analysis indicated that the highest prevalence rates were estimated for countries with extremely high HDI levels (7.93%; 95% CI: 4.94–12.48%) (Table 2). Countries with high prevalence rates included Germany (41.66%), South Africa (32.94%), Czechia (31.08%), and Russia (18.87%). The highest positive rate of human E. bieneusi infection was 14.70% (95% CI: 8.21–22.68) in Europe, which indicates that 109,540,000 (range: 61,178,000–169,005,000) people will be infected in Europe in 2021. An extrapolation to the 2021 world population indicated that 521,222,000 (range: 393,092,000–686,526,000) people harbored E. bieneusi infection. More detail on the global and regional E. bieneusi infection prevalence is given in Table 2.

A total of 70 E. bieneusi genotypes were included in this study, of which Group 1 was the most common in human infections (n = 40, 57.14%), followed by Group 2 (n = 5, 7.14%) (Table 3 and Fig. 4). According to the genotypes of E. bieneusi in different countries, China had the most E. bieneusi genotypes (n = 52; 48%). China shares three genotypes with Brazil and Thailand, four with Bangladesh, and one with Myanmar (Fig. 5).

thumbnail Figure 4

Evolutionary tree of E. bieneusi prevalence in human worldwide.

thumbnail Figure 5

Prevalence of E. bieneusi genotype in different countries.

Table 3

Prevalence of E. bieneusi genotype grouping.

Discussion

Microsporidia specializing in intracellular parasitism [5] are a type of single-celled eukaryotic organism [29, 76]. As we know, more than 90% of human microsporidiosis cases are caused by E. bieneusi as the most important species of microsporidiosis, with worldwide distribution of infected cases [37, 65, 83, 94]. We have estimated that of the world population of 7.9 billion people, over 520 million people may be infected with E. bieneusi in 2021 [10].

In this study, the results showed that the infection rate in men was higher than that in women, but the difference was not statistically significant. A similar phenomenon was also found in the meta-analysis of the prevalence of microsporidia in China by Qiu et al. [65]. For people, the high male infection rate may be related to poor living habits and higher engagement in animal husbandry. At the same time, the high positive rate of the population in rural areas may also be related to high engagement in animal husbandry [55]. In rural areas, it is customary to raise poultry, livestock and pets, and most of them are raised in a way that combines free range breeding with captive breeding. Close contact between people and animals, poor living conditions, pollution of drinking water by animal feces, and low awareness of prevention methods all increase the probability of E. bieneusi infection [41].

There are currently more than 500 genotypes of E. bieneusi identified based on ITS nucleic acid sequences, and these existing genotypes can be divided into different genetic groups, totaling 11 groups (Groups 1–11). The results of this study showed that 82.05% of genotypes belonged to Group 1. Group 1 has the largest number of species and is found in both domestic and wild animals worldwide [42], and is also the genotype group of E. bieneusi that mainly infects humans [31, 32]. However, genotypes in other groups causing zoonotic disease cannot be ignored, such as J and BEBE4 in group 2, CAF4 and KIM3 in group 5, Nig3 and Nig4 in group 6, and S7 in group 10 [31, 40, 53, 63]. These genotypes with the potential for zoonotic co-infection, can infect both animal hosts and humans, establishing a pathway of transmission between humans and animals [41, 104, 105]. This is therefore of high public health significance. Findings also further demonstrate that human E. bieneusi infection is mainly related to animals [31, 32].

Enterocytozoon bieneusi is one of the common pathogens that causes chronic diarrhea in the human body, especially in people with immunodeficiency or low immunity (such as people with HIV, organ transplant recipients, bone marrow transplant recipients, patients with tumors, elderly people, and children) [83, 94, 100]. In the statistical analysis of people at different ages, compared with other groups, the infection rates of young people and the elderly were higher. Previous studies have shown that young and older age are risk factors for E. bieneusi infection [29]. The prevalence of E. bieneusi in diarrhea patients 16.50% (11.47–22.18) was significantly higher than that in non-diarrhea patients 10.54% (5.79–16.44). Several studies have shown similar results, indicating that patients with diarrhea have significantly higher rates of E. bieneusi infection than those without diarrhea. People with diarrhea are more susceptible to infection [99, 102]. Meanwhile, E. bieneusi infection is widespread and infectious for people with HIV, as well as for others with compromised immunity [29]. This study found that E. bieneusi had the highest infection rate among patients with cancer, followed by organ transplant recipients. However, the mechanism of infection and pathogenicity established by the entry of E. bieneusi into host cells is not yet clear, and there may be a certain balance between it and the host, causing the host to be in a subclinical state for a long period of time [74]. Once the host’s immune function is compromised, obvious clinical symptoms will appear, such as persons with ≤200 CD4+ T cells per microliter blood [16, 26]. Moreover, the infection rate of E. bieneusi in persons with <200 (25.97%) CD4+ T cells was higher than that in those with >200 CD4+ T cells (21.76%). Therefore, it is recommended that patients with low immunity should maintain good hygiene habits and seek medical attention in good time when symptoms such as diarrhea occur [101, 106].

Our analysis also showed that based on economic development, high infection rates are found in the extremely high HDI and high-income countries. On the one hand, this may be due to differences in testing technology, focus, and logistics development [69]. On the other, it may be due to climate. Our research showed that the prevalence rate of E. bieneusi in European countries was relatively high. The results of the climate subgroups showed that the prevalence in temperate zone marine climate was the highest. Studies have shown that extreme temperatures and precipitation are not conducive to the growth of E. bieneusi [43, 63]. The temperate zone marine climate has the characteristics of warm winters and cool summers, small annual temperature differences, and uniform precipitation distribution. This may be beneficial for the growth and transmission of E. bieneusi.

Although we conducted a comprehensive and detailed analysis of the risk factors for E. bieneusi infection in humans in this study, there were certain limitations. First, we may have missed some studies. Second, in some cases, our estimates might not be representative of national prevalence nor of all communities in a country. Third, some included studies lack infection rates based on gender, age, and living environment factors, and information on the different detection methods used, which may affect certain subgroup analyses.

Conclusions

This study revealed a global prevalence rate of 6.59% for human E. bieneusi infection, with 82.05% of the genotypes belonging to Group 1 and posing a risk of zoonotic disease. Not only people with low immunity (such as the elderly, children, patients with HIV, etc.), but also people in Europe living in temperate marine climates should exercise caution to prevent infection with E. bieneusi during contact with animals.

Supplementary material

Table S1: Normal distribution tests for normal rates and different transitions of articles hosted by humans. Access here

Table S2: Main characteristics of the included studies in humans. Access here

Table S3: Egger for publication bias. Access here

thumbnail Figure S1:

Funnel plot with pseudo 95% confidence interval for publication bias test.

thumbnail Figure S2:

Egger’s test for publication bias.

thumbnail Figure S3:

Shear complement graph and pseudo 95% confidence interval for publication bias test.

thumbnail Figure S4:

Figure S4: Sensitivity analysis of human infection with E. bieneusi.

Funding

This work was supported by the Jilin Provincial Education Department of Science and Technology Research Project (JJKH20210366KJ).

Conflict of interest

The authors declare that they have no conflicts of interest.

Data availability statement

The data used to support the findings of this study are available from the corresponding authors upon request.

Author contributions statement

Yanchun Wang, Hongwei Cao, and Jing Jiang designed the study. Yanan Cai acquired the funding. Xiao-Man Li, Xiang-Yu Wang, Yong-Jie Wei, and Hai-Long Yu extracted the data. Xiao-Man Li, Xiang-Yu Wang, Xing Yang, and Xin-Bo Yang analyzed the data. Yanchun Wang, Xiao-Man Li, and Xing Yang wrote the original draft. Xiang-Yu Wang, Yong-Jie Wei, Yanan Cai, Hong-Li Geng, and Jing Jiang reviewed the draft. All authors reviewed the final manuscript.

Ethics approval

Ethical approval was not required.

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Cite this article as: Wang Y, Li X-M, Yang X, Wang X-Y, Wei Y-J, Cai Y, Geng H-L, Yang X-B, Yu H-L, Jiang J & Cao H. 2024. Global prevalence and risk factors of Enterocytozoon bieneusi infection in humans: a systematic review and meta-analysis. Parasite 31, 9.

All Tables

Table 1

Summary of global E. bieneusi human infection rates and relevant characteristics.

Table 2

Prevalence estimates of E. bieneusi infection, and estimated numbers of infected people in 34 countries.

Table 3

Prevalence of E. bieneusi genotype grouping.

All Figures

thumbnail Figure 1

Flow diagram of literature search and selection.

In the text
thumbnail Figure 2

Forest map of global human infection in E. bieneusi.

In the text
thumbnail Figure 3

Map of E. bieneusi prevalence in human worldwide.

In the text
thumbnail Figure 4

Evolutionary tree of E. bieneusi prevalence in human worldwide.

In the text
thumbnail Figure 5

Prevalence of E. bieneusi genotype in different countries.

In the text
thumbnail Figure S1:

Funnel plot with pseudo 95% confidence interval for publication bias test.

In the text
thumbnail Figure S2:

Egger’s test for publication bias.

In the text
thumbnail Figure S3:

Shear complement graph and pseudo 95% confidence interval for publication bias test.

In the text
thumbnail Figure S4:

Figure S4: Sensitivity analysis of human infection with E. bieneusi.

In the text

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