Skip to main content
Download PDF

Toxoplasma gondii infection as a risk factor for osteoporosis: a case–control study

Parasites & Vectors volume 15, Article number: 151 (2022) Cite this article

Abstract

Background

More than one-third of the total world population is infected by Toxoplasma gondii (T. gondii). T. gondii has been linked to various diseases, such as cancer, mental disorders, type 2 diabetes mellitus (T2DM), etc. However, the effects of T. gondii infection on the risk of osteoporosis are unclear. Our study aimed to uncover evidence to determine whether patients exposed to T. gondii have an increased or decreased risk of osteoporosis in people with abnormal bone mineral density (BMD) by using case–control study.

Methods

A total of 729 patients, including 316 osteopenia and 413 osteoporosis patients of Han Chinese ancestry were selected in the study. Their blood samples were collected and the levels of specific IgG antibodies against T. gondii were measured using ELISA assay. We obtained some information about the patients from the medical record that included demographic indexes and clinical data. A logistic regression analysis was used to evaluate the effects of T. gondii infection on femur osteoporosis, lumbar osteoporosis and compound osteoporosis. Potential interaction was analyzed using multifactor dimensionality reduction software 1.0.0 (MDR 1.0.0).

Results

113 positive patients with T. gondii infections have been detected, including 80 cases of osteoporosis and 33 cases of osteopenia, the infection rates of T. gondii were 19.37% (80/413) and 10.44% (33/316), respectively. The patients with T.gondii infections were at a 2.60 times higher risk of suffering from compound osteoporosis than those without T. gondii infections (OR = 2.60, 95% CI 1.54–4.39, P < 0.001), but not associated with femur osteoporosis (OR = 1.01, 95% CI 0.43–2.34, P = 0.989) and lumbar osteoporosis (OR = 0.84, 95% CI 0.34–2.07, P = 0.705) after adjusting for the covariates. Moreover, a significantly higher risk of compound osteoporosis in the individuals with all two factors (T. gondii infection, Female) was observed compared with reference group (without T. gondii infection, male) under the interaction model (OR = 11.44, 95%CI = 5.44–24.05, P < 0.001). And the individuals with all two factors (T. gondii infection, over 70 years) exhibited a 8.14-fold higher possibility of developing compound osteoporosis compared with reference group (without T. gondii infection, under 70 years) (OR = 8.14, 95% CI 3.91–16.93, P < 0.001). We further stratified by age and sex, and found that women with T. gondii infection was more likely to develop compound osteoporosis than those without infection(OR = 3.12, 95% CI  1.67–5.81, P < 0.001), but we not found the association between T. gondii infection and compound osteoporosis in males (OR = 1.36, 95% CI 0.37–4.94, P = 0.645).

Conclusions

T. gondii infection is a risk factor for osteoporosis, especially compound osteoporosis. Meanwhile, it is very necessary for patients with osteoporosis to further diagnose and treat T. gondii infection, especially women.

Graphical Abstract

Background

Osteoporosis, characterized by the degeneration the microstructure of bone tissue and the decrease of bone mass, has become a public health problem affecting more than 200 million people worldwide [1, 2]. Clinically, osteoporosis will increase the fragility and susceptibility to fracture and osteoporosis-related fractures are common causes of morbidity and death in older adults [2,3,4]. Among the Chinese population aged 50 years or older, 65 million people are diagnosed with osteoporosis, while an additional 213 million were estimated to have osteopenia [5]. Zhang et al. reported that the prevalence of osteoporosis in Chinese women after menopause reach up more than 60% [6]. It brings great health and economic burden to old women [7].

Osteopenia refers to the bone mineral density (BMD) lower than the normal population but higher than the bone density of the osteoporotic population. Although the people with osteopenia had an increased fracture risk compared with the healthy, it was not severe enough to be considered a diseased state in the absence of a fragility fracture, if left untreated, they can eventually lead to osteoporosis and future fractures [6, 8, 9]. Most osteoporosis are asymptomatic, which makes epidemiological research especially difficult [10].

Gender, age, history of fractures, drinking, smoking, bone diseases and lack of physical activity are well-known risk factors for osteoporosis, particularly calcium deficiency, inadequate Vitamin D intake, and deficiencies in certain hormones, such as estrogen [11,12,13,14]. Furthermore, genetic polymorphisms also play a role in the development of osteoporosis [15]. Interestingly, it has been found that schistosome infection promotes osteoclast-mediated bone loss in mice [16]. However, the relationship between Toxoplasma gondii infection and osteoporosis is still unclear.

Toxoplasma gondii (T. gondii) belongs to apical complex protozoa, an important opportunistic pathogenic protozoan that infects almost all endotherms, including mammals, birds, and humans [17]. T. gondii can replicate and invade almost any nucleated cell in humans [18,19,20]. As an obligate intracellular parasite, It forms vacuoles in cells during infection, parasitizes in vacuoles and secretes effector molecules to regulate host cell biological processes such as energy metabolism, immune response, cell signaling, and lead to cell lysis to death along with the reproduction of T. gondii [21]. About 2 billion people worldwide are chronically infected with T. gondii, affecting approximately 30–50% of the world's population [22,23,24]. In a total of 49,784 Chinese blood donors from 1986 to 2017, the infection rate of T. gondii was detected at 6.26% [25]. Clinically, most infections are asymptomatic or taken in a mild, self-limiting form characterized by fever, malaise and lymphadenopathy [26]. T. gondii can lead to serious illnesses and even death of immunodeficiency patients [27]. Primary infection in pregnant women is a matter of great concern, the women in the first and second trimesters, infection with T. gondii may cause severe congenital toxoplasmosis, and can result in intrauterine fetal death and spontaneous abortion [28].

T. gondii has been linked to a various diseases.T. gondii infection is a serious problem in cancer patients in a case–control study [29]. And some studies have found that T. gondii might be a factor associated with hypertension in type 2 diabetes mellitus (T2DM) patients [30]. Moreover, T. gondii has been linked to a variety of mental disorders, such as schizophrenia, Alzheimer diseases, obsessive–compulsive disorder, recurrent migraines and even suicidal behavior [31,32,33,34,35]. Furthermore, T. gondii infection leads to deficits in goal-directed behavior in healthy elderly by altering dopaminergic neural transmission [36]. However, the chronic long-term damage to human health caused by latent T. gondii infection is not entirely clear, especially osteoporosis.

Until now, there is a lack of research supporting the relationship between T. gondii infections and osteoporosis in human. Therefore, our study aimed to uncover evidence to determine whether patients exposed to T. gondii have an increased or decreased risk of osteoporosis in people with abnormal bone mineral density (BMD) by using case–control study.

Method

Patients

A total of 729 osteopenia and osteoporosis patients of Chinese ancestry were included in our study, there were 316 osteopenia and 413 osteoporosis cases. All of these were inpatients at the Guangzhou Overseas Chinese Hospital from 2015 to 2019. And 5 ml peripheral venous blood sample from each patient was collected with the EDTA vacuum blood collection tubes and saved at 4℃, then transported to laboratory. Our study was approved by the Ethics Committee of the School of Medicine of Jinan University, Guangzhou, China, and performed strictly in accordance with the Declaration of Helsinki.

Data collection

We obtained some information about the patients from the medical record that included demographic indexes (age, gender, marriage, education, job, smoking, drinking), clinical data including, bone mineral density (BMD) of whole-body, lumbar and femur, diabetes, hypertension and cardiovascular disease (CVD), and current osteoporosis treatment. This information and dual-energy densitometry (DXA) report were led together by date.

The diagnosis of osteopenia and osteoporosis

Clinically, osteoporosis can be screened by physical examination. However, BMD measured by DXA is needed to confirm such a diagnosis, DXA is the gold standard for diagnosing osteoporosis [37]. Before DXA inspection, patients were instructed to rest at least 8 h during the previous night and to avoid strenuous exercise and alcohol consumption for 24 h, and during the measurement, subjects were in light clothing. The radiologist asked the patient to lie flat on the machine bed, the legs were fully extended, and the lower extremities were internally rotated (45 degrees), and if necessary, the lower limbs were fixed to expose the femoral neck as much as possible. When testing the whole body and lumbar spine, the patient just needs to lie down. In general, the entire inspection is maintained for 15 to 20 min.

The BMD value of an individual patient is expressed in terms of the number of standard deviations (SD) from the mean BMD of a healthy young-adult reference population, commonly referred to as the T-score [38]. Patients whose DXA showed low BMD by World Health Organization (WHO) guidelines were identified: individuals were considered to be osteoporosis when the T-score was below − 2.5 (T-score ≤ − 2.5) and were considered to be normal when the T-score was above − 1.0 (T-score > − 1.0), the BMD value of osteopenia is less than − 1.0 but above − 2.5 (T-score ≤ − 1.0 and > − 2.5) [39,40,41,42,43].

Serological analysis

Approximately 5 ml of venous blood was drawn from each patient and then centrifuged at 1000 ×g for 10 min. Serums were separated from the blood sample and stored at – 80 ℃. Seroprevalence of T. gondii infection was assessed by enzyme-linked immunosorbent assay (ELISA) Kit by Haitai Biological Pharmaceuticals (registration number: 20153400072). Positive, negative serum controls, and three critical control were included in each plate. The results (A value) were read by a microplate reader (TZCAN-SAFIRZ-Z) and Magellan software at the dual wavelength of 450/630 nm. Follow the manufacturer instructions, each experiment needed to fulfill the following three conditions: (1) the mean value of A in the positive control was ≥ 0.50; (2) the mean value of A in the negative control was ≤ 0.10; (3) the A values in the critical control range from 0.12 to 0.35. When A value of the sample is greater than the average value of the critical control group, it is judged as positive, otherwise negative.

Statistical analysis

Statistical analysis was performed using the statistical software SPSS (version 13.0). For the continuous variables were compared using Student’s t test. For categorical variables, the Chi-square test was used to determine associations between osteoporosis and potential risk factors, the strength of the associations was assessed by odds ratios (OR) and 95% confidence intervals (CI) were calculated. The continuous variables were reported as the means ± standard deviation. The frequency and proportion were reported for the categorical variables. Multivariate logistic regression models were used to adjust for potential confounders. Additionally, potential interaction was analyzed using multifactor dimensionality reduction software 1.0.0 (MDR 1.0.0). Results were considered significant at P < 0.05.

Results

Demographic characteristics

A total of 729 patients with abnormal BMD of Chinese ancestry were included in our study, 56.65% with osteopenia and 43.35% with osteoporosis. The mean ages of people with osteopenia, and osteoporosis were 67.28 ± 9.64 years, and 71.89 ± 9.60 years, and there was significant difference in age (t = − 6.41, df = 727, P < 0.001). The proportion of female in the osteoporosis group (83.05%) was higher than that in the osteopenia group (65.51%) (χ2 = 29.75, df = 1, P < 0.001). The proportion of high triglyceride (TG > 1.5 mmol/L) in the osteopenia group (42.46%) was higher than that in the osteoporosis group (31.69%) (χ2 = 8.22, df = 1, P = 0.004). In this study, 113 cases of T. gondii infections have been detected, and the T. gondii infection rates of osteoporosis and osteopenia were 19.37% and 10.44%, respectively, and there was significant difference (χ2 = 10.89, df = 1, P = 0.001). No differences were observed between the groups in smoking, drinking, hormone taking, job, total cholesterol level (TC), and the number of comorbidities including hypertension, diabetes and cardiovascular disease (CVD) (Table 1).

Table 1 Characteristics among the population with abnormal BMD (% within group)
Full size table

Risk of osteoporosis associated with T. gondii infection

Among the 413 patients with osteoporosis, according to the different sites of osteoporosis, we divided them into three groups: femur osteoporosis, lumbar osteoporosis and compound osteoporosis (including both femoral and lumbar osteoporosis or whole-body osteoporosis), and the osteopenia was regarded as the control group. A logistic regression analysis showed that patients with T.gondii infections were at a 2.60 times higher risk of suffering from compound osteoporosis than those without T. gondii infections (OR = 2.60, 95% CI 1.54–4.39, P < 0.001) (Table 2) after adjusting age, sex, job, smoking, drinking, hormone taking, TG, TC, number of comorbidities. There were no statistically significant differences among the femur osteoporosis and lumbar osteoporosis (Fig. 1).

Table 2 Risk of osteoporosis associated with T. gondii infection
Full size table
Fig. 1
figure 1

Logistic regression model of the associations between three different types of osteoporosis and T. gondii infection. Note: *P < 0.05, **P < 0.01, ***P < 0.001, Model 1: unadjusted model; Model 2: adjusted for age, sex, job, smoking, drinking, hormone, TG, TC, number of comorbiditie

Full size image

The interaction models of compound osteoporosis

We summarized the best interaction models for different types of osteoporosis by MDR, the best model was determined by the testing balanced accuracy (TBA) and cross-validation consistency (CVC) indices. P values obtained from the MDR analysis among three groups. Our results revealed that age and sex have an interactive effect on compound osteoporosis (P = 0.039) (Table 3).

Table 3 Best MDR interaction models for osteoporosis
Full size table

We further analyzed the interactive effects of T. gondii infection with age or sex on compound osteoporosis. In comparison with the reference group (without T. gondii infection, male), the individuals with all two factors (T. gondii infection, Female) exhibited a 11.44-fold higher possibility of developing compound osteoporosis (OR = 11.44, 95% CI 5.44–24.05, P < 0.001) (Table 4). In the interaction of T. gondii infection and age, the individuals with all two factors (T. gondii infection, over 70 years) were 8.14 times more likely to suffer from compound osteoporosis when compared with reference group (without T. gondii infection, under 70 years) (OR = 8.14, 95% CI 3.91–16.93, P < 0.001) (Table 5). We further stratified the population by age and sex, and found that women with T. gondii infection was more likely to develop compound osteoporosis than those without infection (OR = 3.12, 95% CI 1.67–5.81, P < 0.001), but we not found the association between T. gondii infection and compound osteoporosis in males (OR = 1.36, 95% CI  0.37–4.94, P = 0.645) (Additional file 1: Table S1). Furthermore, T. gondii infection was associated with compound osteoporosis in women under 70 years (OR = 4.35, 95%CI = 1.79–10.57, P = 0.001) and over 70 years (OR = 2.48, 95% CI 1.03–6.01, P = 0.044) (Additional file 2: Table S2).

Table 4 Different interaction models (with sex) for compound osteoporosis
Full size table
Table 5 Different interaction models (with age) for compound osteoporosis
Full size table

Discussion

In order to find out whether T. gondii infection is related to the occurrence of osteoporosis in patients with abnormal BMD, we collected a total of 729 blood samples with osteoporosis and osteopenia between 2015 and 2019, and collected corresponding demographic and clinical information. The IgG antibody against T. gondii was measured by ELISA, and 113 (113/729, 15.50%) cases of T. gondii infection were found, is obviously higher than the average level in China (10%) [44]. In this study, women account for a much larger proportion in osteoporosis (83.05%) than the group of osteopenia (65.51%). This is consistent with the results of other studies that women are more likely to suffer from osteoporosis, especially postmenopausal women [45, 46]. This is because estrogen deficiency in postmenopausal women leads to reduce bone mass by approximately 10%, and it can be as high as 20% in those 5–6 years around menopause [47]. We found that the osteopenia group had more people with high TG (> 1.5 mmol/L) and our results was consistent with Dennison et al. research in which a significant positive correlation between fasting TG levels and lumbar spine BMD by cohort study was observed [48].

Osteopenia is the disease progression process of osteoporosis, in other words, osteopenia is a necessary condition for osteoporosis [49]. Interestingly, we found that patients with osteoporosis have a higher proportion of T. gondii infection (19.37%) than osteopenia group (10.44%). T. gondii can infect all nucleated cells (including bone marrow cells), in animal studies, Brazilian T. gondii Laboratory (LabTXOP) extracts high concentrations of T. gondii DNA from the bones sample (vertebrae and ribs) of mice [50], and some studies have shown that T. gondii may present serious effects on bone marrow cells in human bone marrow transplantation [51, 52]. At the cellular level, osteoblast and osteoclast are two main types of cells that maintain bone mass [53]. In normal circumstances, osteoblasts and osteoclasts maintain a certain number and constrain each other, the bone formation and bone resorption mediated by them are in balance [14]. However, the decreased bone marrow cells and decreased osteogenesis are important factors leading to osteoporosis, and it has been proved that chronic inflammatory response or inflammation caused by acute infection will increase the activity of osteoclasts, osteocytes are decomposed and absorbed, and eventually lead to the loss of bone mass[54]. And many inflammatory mediators have been implicated in driving osteoclast-mediated bone destruction [55, 56]. Indeed, TNF is a potent osteoclastogenic agent [57]. IL-12, TNF-α and IFN-γ are important cytokines produced after T. gondii infection [58]. Therefore, we propose that T. gondii infection may be a risk factor for osteoporosis. The possible mechanism is that the immune response to T. gondii infection activates osteoclasts, resulting in bone resorption over bone formation, which needs to be proved by further experiments.

In order to further analyze the type of bone that T. gondii affects osteoporosis, we divided osteoporosis into three different types of osteoporosis (femur, lumbar and compound), logistic regression showed that T. gondii infections were at a 2.60 times higher risk of compound osteoporosis than those without T. gondii infections (OR = 2.60, 95% CI 1.54–4.39, P < 0.001), but there is no significant difference from other types of osteoporosis (femur and lumbar). Obviously, T. gondii infection is a risk factor for osteoporosis, especially compound osteoporosis. On the one hand, the BMD in this study was measured by iDAX, and the precision of the BMD of the compound (0.7%) is higher than lumbar and femur (0.8%) measured by iDAX [59]. This may make compound osteoporosis caused by T. gondii easier to detected. On the other hand, compound osteoporosis includes osteoporosis of lumbar, femur, skull, ribs, etc. This may be that T. gondii is more likely to affect more active, rich blood vessels, and more vulnerable bone parts, such as skull, ribs, etc. But it needs to be confirmed by more detailed epidemiological data.

Some studies have shown that age and gender have an interactive effect on bone microstructure [60]. We also considered whether the T. gondii infection has an interaction effect with age and sex on compound osteoporosis, and found that women infected with T. gondii and people over 70 years infected with T. gondii have a higher risk of compound osteoporosis than other people. The results of the stratified analysis suggest that T. gondii infection needs to be monitored in women to prevent compound osteoporosis.

Our research has a potential limitation. Worldwide genotypic analysis of T. gondii isolates has identified a population structure consisting of three widespread clonal lineages, termed type I, II, and III [61], and each displays are distinct biological traits, such as virulence. In the existing article shows that the genotype Chinese 1 (ToxoDB#9) type II strain is very popular in southern China [62]. Therefore, the type II strain may be the main type affecting whole-body bone mineral density values in patients with osteoporosis. Selection bias from one hospital cannot be avoided completely and this is one limitation. In the future research, a large sample size from multiple hospitals is needed to confirm the relationship between T. gondii infection and osteoporosis risk. In addition, this was a hospital-based case–control study and we want to explore the relationship between T. gondii infection and osteoporosis progression. Since the blood samples are collected in the orthopedics department in the hospital, it is difficult for us to obtain blood sample with normal BMD. Obviously, using osteopenia as a control group would greatly underestimate the risk of T. gondii on osteoporosis. Although the use of osteopenia as a control might underestimate the risk, the results will provide the important clues for the future research. Next we will conduct community-based case–control study using a health control. In this study, we found positive association between T. gondii infection and osteoporosis..

In conclusion, our study shows that T. gondii infection is a risk factor for osteoporosis, especially compound osteoporosis. Meanwhile, it is very necessary for patients with osteoporosis to further diagnose and treat T. gondii infection, especially women.

Availability of data and materials

Not applicable.

Abbreviations

TG:

Triglyceride

TC:

Total cholesterol

SD:

Standard deviation

BMD:

Bone mineral density

T. gondii :

Toxoplasma gondii

MDR:

Multifactor dimensionality reduction

CVC:

Cross-validation consistency

References

  1. Siris ES, Adler R, Bilezikian J, Bolognese M, Dawson-Hughes B, Favus MJ, et al. The clinical diagnosis of osteoporosis: a position statement from the National Bone Health Alliance Working Group. Osteoporos Int. 2014;25:1439–43. https://doi.org/10.1007/s00198-014-2655-z.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  2. Yang TL, Shen H, Liu A, Dong SS, Zhang L, Deng FY, et al. A road map for understanding molecular and genetic determinants of osteoporosis. Nat Rev Endocrinol. 2020;16:91–103. https://doi.org/10.1038/s41574-019-0282-7.

    Article  PubMed  Google Scholar 

  3. Clynes MA, Harvey NC, Curtis EM, Fuggle NR, Dennison EM, Cooper C. The epidemiology of osteoporosis. Br Med Bull. 2020;133:105–17. https://doi.org/10.1093/bmb/ldaa005.

    Article  PubMed  Google Scholar 

  4. Bouvard B, Annweiler C, Legrand E. Osteoporosis in older adults. Joint Bone Spine. 2021;88:105135. https://doi.org/10.1016/j.jbspin.2021.105135.

    Article  PubMed  Google Scholar 

  5. Harvey NC, Glüer CC, Binkley N, McCloskey EV, Brandi ML, Cooper C, et al. Trabecular bone score (TBS) as a new complementary approach for osteoporosis evaluation in clinical practice. Bone. 2015;78:216–24. https://doi.org/10.1016/j.bone.2015.05.016.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Zhang J, Morgan SL, Saag KG. Osteopenia: debates and dilemmas. Curr Rheumatol Rep. 2013;15:384. https://doi.org/10.1007/s11926-013-0384-5.

    Article  PubMed  Google Scholar 

  7. Hernlund E, Svedbom A, Ivergård M, Compston J, Cooper C, Stenmark J, et al. Osteoporosis in the European Union: medical management, epidemiology and economic burden. A report prepared in collaboration with the International Osteoporosis Foundation (IOF) and the European Federation of Pharmaceutical Industry Associations (EFPIA). Arch Osteoporos. 2013;8:136. https://doi.org/10.1007/s11657-013-0136-1.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Karaguzel G, Holick MF. Diagnosis and treatment of osteopenia. Rev Endocr Metab Disord. 2010;11:237–51. https://doi.org/10.1007/s11154-010-9154-0.

    Article  CAS  PubMed  Google Scholar 

  9. Maria S, Witt-Enderby PA. Melatonin effects on bone: potential use for the prevention and treatment for osteopenia, osteoporosis, and periodontal disease and for use in bone-grafting procedures. J Pineal Res. 2014;56:115–25. https://doi.org/10.1111/jpi.12116.

    Article  CAS  PubMed  Google Scholar 

  10. Baccaro LF, Conde DM, Costa-Paiva L, Pinto-Neto AM. The epidemiology and management of postmenopausal osteoporosis: a viewpoint from Brazil. Clin Interv Aging. 2015;10:583–91. https://doi.org/10.2147/cia.S54614.

    Article  PubMed  PubMed Central  Google Scholar 

  11. Anagnostis P, Karagiannis A, Kakafika AI, Tziomalos K, Athyros VG, Mikhailidis DP. Atherosclerosis and osteoporosis: age-dependent degenerative processes or related entities? Osteoporos Int. 2009;20:197–207. https://doi.org/10.1007/s00198-008-0648-5.

    Article  CAS  PubMed  Google Scholar 

  12. Bischoff-Ferrari HA, Willett WC, Wong JB, Giovannucci E, Dietrich T, Dawson-Hughes B. Fracture prevention with vitamin D supplementation: a meta-analysis of randomized controlled trials. JAMA. 2005;293:2257–64. https://doi.org/10.1001/jama.293.18.2257.

    Article  CAS  PubMed  Google Scholar 

  13. Wong PK, Christie JJ, Wark JD. The effects of smoking on bone health. Clin Sci (Lond). 2007;113:233–41. https://doi.org/10.1042/cs20060173.

    Article  CAS  Google Scholar 

  14. Raisz LG. Pathogenesis of osteoporosis: concepts, conflicts, and prospects. J Clin Invest. 2005;115:3318–25. https://doi.org/10.1172/jci27071.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Ioannidis JP, Ralston SH, Bennett ST, Brandi ML, Grinberg D, Karassa FB, et al. Differential genetic effects of ESR1 gene polymorphisms on osteoporosis outcomes. JAMA. 2004;292:2105–14. https://doi.org/10.1001/jama.292.17.2105.

    Article  CAS  PubMed  Google Scholar 

  16. Li W, Wei C, Xu L, Yu B, Chen Y, Lu D, et al. Schistosome infection promotes osteoclast-mediated bone loss. PLoS Pathog. 2021;17:e1009462. https://doi.org/10.1371/journal.ppat.1009462.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Dubey JP. The history of Toxoplasma gondii–the first 100 years. J Eukaryot Microbiol. 2008;55:467–75. https://doi.org/10.1111/j.1550-7408.2008.00345.x.

    Article  PubMed  Google Scholar 

  18. Coppens I. Toxoplasma, or the discovery of a heterophage. Trends Parasitol. 2014;30:467–9. https://doi.org/10.1016/j.pt.2014.08.005.

    Article  CAS  PubMed  Google Scholar 

  19. Xiao J, Yolken RH. Strain hypothesis of Toxoplasma gondii infection on the outcome of human diseases. Acta Physiol (Oxf). 2015;213:828–45. https://doi.org/10.1111/apha.12458.

    Article  CAS  Google Scholar 

  20. Liu Q, Wang ZD, Huang SY, Zhu XQ. Diagnosis of toxoplasmosis and typing of Toxoplasma gondii. Parasit Vectors. 2015;8:292. https://doi.org/10.1186/s13071-015-0902-6.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Hakimi MA, Olias P, Sibley LD. Toxoplasma effectors targeting host signaling and transcription. Clin Microbiol Rev. 2017;30:615–45. https://doi.org/10.1128/cmr.00005-17.

    Article  PubMed  PubMed Central  Google Scholar 

  22. Gulinello M, Acquarone M, Kim JH, Spray DC, Barbosa HS, Sellers R, et al. Acquired infection with Toxoplasma gondii in adult mice results in sensorimotor deficits but normal cognitive behavior despite widespread brain pathology. Microbes Infect. 2010;12:528–37. https://doi.org/10.1016/j.micinf.2010.03.009.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Wang ZD, Wang SC, Liu HH, Ma HY, Li ZY, Wei F, et al. Prevalence and burden of Toxoplasma gondii infection in HIV-infected people: a systematic review and meta-analysis. Lancet HIV. 2017;4:e177–88. https://doi.org/10.1016/s2352-3018(17)30005-x.

    Article  PubMed  Google Scholar 

  24. Zheng J, Jia H, Zheng Y. Knockout of leucine aminopeptidase in Toxoplasma gondii using CRISPR/Cas9. Int J Parasitol. 2015;45:141–8. https://doi.org/10.1016/j.ijpara.2014.09.003.

    Article  CAS  PubMed  Google Scholar 

  25. Wang T, Han Y, Pan Z, Wang H, Yuan M, Lin H. Seroprevalence of Toxoplasma gondii infection in blood donors in mainland China: a systematic review and meta-analysis. Parasite. 2018;25:36. https://doi.org/10.1051/parasite/2018037.

    Article  PubMed  PubMed Central  Google Scholar 

  26. Harker KS, Ueno N, Lodoen MB. Toxoplasma gondii dissemination: a parasite’s journey through the infected host. Parasite Immunol. 2015;37:141–9. https://doi.org/10.1111/pim.12163.

    Article  CAS  PubMed  Google Scholar 

  27. Bougdour A, Tardieux I, Hakimi MA. Toxoplasma exports dense granule proteins beyond the vacuole to the host cell nucleus and rewires the host genome expression. Cell Microbiol. 2014;16:334–43. https://doi.org/10.1111/cmi.12255.

    Article  CAS  PubMed  Google Scholar 

  28. Liu Q, Wei F, Gao S, Jiang L, Lian H, Yuan B, et al. Toxoplasma gondii infection in pregnant women in China. Trans R Soc Trop Med Hyg. 2009;103:162–6. https://doi.org/10.1016/j.trstmh.2008.07.008.

    Article  PubMed  Google Scholar 

  29. Cong W, Liu GH, Meng QF, Dong W, Qin SY, Zhang FK, et al. Toxoplasma gondii infection in cancer patients: prevalence, risk factors, genotypes and association with clinical diagnosis. Cancer Lett. 2015;359:307–13. https://doi.org/10.1016/j.canlet.2015.01.036.

    Article  CAS  PubMed  Google Scholar 

  30. Han Y, Nie L, Ye X, Zhou Z, Huang S, Zeng C, et al. The association between Toxoplasma gondii infection and hypertensive disorders in T2DM patients: a case-control study in the Han Chinese population. Parasitol Res. 2018;117:689–95. https://doi.org/10.1007/s00436-017-5737-y.

    Article  PubMed  Google Scholar 

  31. Miman O, Mutlu EA, Ozcan O, Atambay M, Karlidag R, Unal S. Is there any role of Toxoplasma gondii in the etiology of obsessive-compulsive disorder? Psychiatry Res. 2010;177:263–5. https://doi.org/10.1016/j.psychres.2009.12.013.

    Article  PubMed  Google Scholar 

  32. Sutterland AL, Fond G, Kuin A, Koeter MW, Lutter R, van Gool T, et al. Beyond the association. Toxoplasma gondii in schizophrenia, bipolar disorder, and addiction: systematic review and meta-analysis. Acta Psychiatr Scand. 2015;132:161–79. https://doi.org/10.1111/acps.12423.

    Article  CAS  PubMed  Google Scholar 

  33. Bayani M, Riahi SM, Bazrafshan N, Ray Gamble H, Rostami A. Toxoplasma gondii infection and risk of Parkinson and Alzheimer diseases: a systematic review and meta-analysis on observational studies. Acta Trop. 2019;196:165–71. https://doi.org/10.1016/j.actatropica.2019.05.015.

    Article  PubMed  Google Scholar 

  34. Koseoglu E, Yazar S, Koc I. Is Toxoplasma gondii a causal agent in migraine? Am J Med Sci. 2009;338:120–2. https://doi.org/10.1097/MAJ.0b013e31819f8cac.

    Article  PubMed  Google Scholar 

  35. Kamal AM, Kamal AM, Abd El-Fatah AS, Rizk MM, Hassan EE. Latent toxoplasmosis is associated with depression and suicidal behavior. Arch Suicide Res. 2020. https://doi.org/10.1080/13811118.2020.1838368.

    Article  PubMed  Google Scholar 

  36. Beste C, Getzmann S, Gajewski PD, Golka K, Falkenstein M. Latent Toxoplasma gondii infection leads to deficits in goal-directed behavior in healthy elderly. Neurobiol Aging. 2014;35:1037–44. https://doi.org/10.1016/j.neurobiolaging.2013.11.012.

    Article  PubMed  Google Scholar 

  37. Hwang JS, Chan DC, Chen JF, Cheng TT, Wu CH, Soong YK, et al. Clinical practice guidelines for the prevention and treatment of osteoporosis in Taiwan: summary. J Bone Miner Metab. 2014;32:10–6. https://doi.org/10.1007/s00774-013-0495-0.

    Article  PubMed  Google Scholar 

  38. Sözen T, Özışık L, Başaran N. An overview and management of osteoporosis. Eur J Rheumatol. 2017;4:46–56. https://doi.org/10.5152/eurjrheum.2016.048.

    Article  PubMed  Google Scholar 

  39. Carlos F, Clark P, Galindo-Suárez RM, Chico-Barba LG. Health care costs of osteopenia, osteoporosis, and fragility fractures in Mexico. Arch Osteoporos. 2013;8:125. https://doi.org/10.1007/s11657-013-0125-4.

    Article  PubMed  Google Scholar 

  40. Hamrick I, Cao Q, Agbafe-Mosley D, Cummings DM. Osteoporosis healthcare disparities in postmenopausal women. J Womens Health (Larchmt). 2012;21:1232–6. https://doi.org/10.1089/jwh.2012.3812.

    Article  Google Scholar 

  41. Kanis JA, McCloskey EV, Johansson H, Oden A, Melton LJ 3rd, Khaltaev N. A reference standard for the description of osteoporosis. Bone. 2008;42:467–75. https://doi.org/10.1016/j.bone.2007.11.001.

    Article  CAS  PubMed  Google Scholar 

  42. Laster AJ. Dual-energy x-ray absorptiometry: overused, neglected, or just misunderstood? N C Med J. 2014;75:132–6. https://doi.org/10.18043/ncm.75.2.132.

    Article  PubMed  Google Scholar 

  43. Consensus development conference. diagnosis, prophylaxis, and treatment of osteoporosis. Am J Med. 1993;94:646–50. https://doi.org/10.1016/0002-9343(93)90218-e.

    Article  Google Scholar 

  44. Pan M, Lyu C, Zhao J, Shen B. Sixty years (1957–2017) of research on toxoplasmosis in China—an overview. Front Microbiol. 2017;8:1825. https://doi.org/10.3389/fmicb.2017.01825.

    Article  PubMed  PubMed Central  Google Scholar 

  45. Wang Y, Ding H, Wang X, Wei Z, Feng S. Associated Factors for Osteoporosis and Fracture in Chinese Elderly. Med Sci Monit. 2019;25:5580–8. https://doi.org/10.12659/msm.914182.

    Article  PubMed  PubMed Central  Google Scholar 

  46. Mo X, Zhao S, Wen Z, Lin W, Chen Z, Wang Z, et al. High prevalence of osteoporosis in patients undergoing spine surgery in China. BMC Geriatr. 2021;21:361. https://doi.org/10.1186/s12877-021-02313-8.

    Article  PubMed  PubMed Central  Google Scholar 

  47. Ji MX, Yu Q. Primary osteoporosis in postmenopausal women. Chronic Dis Transl Med. 2015;1:9–13. https://doi.org/10.1016/j.cdtm.2015.02.006.

    Article  PubMed  PubMed Central  Google Scholar 

  48. Dennison EM, Syddall HE, Aihie Sayer A, Martin HJ, Cooper C. Lipid profile, obesity and bone mineral density: the Hertfordshire Cohort Study. QJM. 2007;100:297–303. https://doi.org/10.1093/qjmed/hcm023.

    Article  CAS  PubMed  Google Scholar 

  49. Kanis JA. Osteoporosis and osteopenia. J Bone Miner Res. 1990;5:209–11. https://doi.org/10.1002/jbmr.5650050302.

    Article  CAS  PubMed  Google Scholar 

  50. Leles D, Lobo A, Rhodes T, Millar PR, Amendoeira MR, Araújo A. Recovery of Toxoplasma gondii DNA in experimentally mummified skin and bones: prospects for paleoparasitological studies to unveil the origin of toxoplasmosis. Exp Parasitol. 2016;168:51–5. https://doi.org/10.1016/j.exppara.2016.06.003.

    Article  CAS  PubMed  Google Scholar 

  51. Lopes CS, Silva TL, de Almeida JCN, Costa LVS, Mineo TWP, Mineo JR. Transmission of Toxoplasma gondii infection due to bone marrow transplantation: validation by an experimental model. Front Med (Lausanne). 2019;6:227. https://doi.org/10.3389/fmed.2019.00227.

    Article  Google Scholar 

  52. Portes J, Barrias E, Travassos R, Attias M, de Souza W. Toxoplasma gondii mechanisms of entry into host cells. Front Cell Infect Microbiol. 2020;10:294. https://doi.org/10.3389/fcimb.2020.00294.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  53. Robling AG, Bonewald LF. The osteocyte: new insights. Annu Rev Physiol. 2020;82:485–506. https://doi.org/10.1146/annurev-physiol-021119-034332.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Place DE, Malireddi RKS, Kim J, Vogel P, Yamamoto M, Kanneganti TD. Osteoclast fusion and bone loss are restricted by interferon inducible guanylate binding proteins. Nat Commun. 2021;12:496. https://doi.org/10.1038/s41467-020-20807-8.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Amarasekara DS, Yun H, Kim S, Lee N, Kim H, Rho J. Regulation of osteoclast differentiation by cytokine networks. Immune Netw. 2018;18:e8. https://doi.org/10.4110/in.2018.18.e8.

    Article  PubMed  PubMed Central  Google Scholar 

  56. Bi H, Chen X, Gao S, Yu X, Xiao J, Zhang B, et al. Key triggers of osteoclast-related diseases and available strategies for targeted therapies: a review. Front Med (Lausanne). 2017;4:234. https://doi.org/10.3389/fmed.2017.00234.

    Article  Google Scholar 

  57. Teitelbaum SL. Bone resorption by osteoclasts. Science. 2000;289:1504–8. https://doi.org/10.1126/science.289.5484.1504.

    Article  CAS  PubMed  Google Scholar 

  58. Sasai M, Pradipta A, Yamamoto M. Host immune responses to Toxoplasma gondii. Int Immunol. 2018;30:113–9. https://doi.org/10.1093/intimm/dxy004.

    Article  CAS  PubMed  Google Scholar 

  59. Precision evaluation of dual X-ray absorptiometry (iDXA) measurements. 2009;43;12:1291–4. https://www.osti.gov/etdeweb/biblio/21404906. Accessed 18 Dec 2021

  60. Khosla S, Riggs BL, Atkinson EJ, Oberg AL, McDaniel LJ, Holets M, et al. Effects of sex and age on bone microstructure at the ultradistal radius: a population-based noninvasive in vivo assessment. J Bone Miner Res. 2006;21:124–31. https://doi.org/10.1359/jbmr.050916.

    Article  PubMed  Google Scholar 

  61. Barragan A, Sibley LD. Transepithelial migration of Toxoplasma gondii is linked to parasite motility and virulence. J Exp Med. 2002;195:1625–33. https://doi.org/10.1084/jem.20020258.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  62. Wang L, Chen H, Liu D, Huo X, Gao J, Song X, et al. Genotypes and mouse virulence of Toxoplasma gondii isolates from animals and humans in China. PLoS ONE. 2013;8: e53483. https://doi.org/10.1371/journal.pone.0053483.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

Not applicable.

Funding

This work was supported by National Key Research and Development Program of China (2021YFC2301500), the National Natural Science Foundation of China (Nos: 91543132), the Guangdong Natural Science Foundation (No: 2016A030313089).

Author information

Author notes

  1. Kehui Zhu, Kun Liu and Junsi Huang are contributed equally to this work.

Authors and Affiliations

  1. Department of Pathogen Biology, School of Medicine, Jinan University, Guangzhou, 510632, Guangdong, China

    Kehui Zhu, Kun Liu, Junsi Huang, Qiaoyun Chen, Tianyu Gao & Guang Yang

  2. Institute of Blood Transfusion, Chinese Academy of Medical Sciences and Peking Union Medical College, Chengdu, 610000, Sichuan, China

    Kehui Zhu

  3. Department of Epidemiology, School of Medicine, Jinan University, No.601 Huangpu Road West, Guangzhou, 510632, Guangdong, China

    Kun Liu, Junsi Huang, Xueqiong Weng, Qiaoyun Chen, Tianyu Gao & Chunxia Jing

  4. Department of Orthopedics, The First Affiliated Hospital of Jinan University, Guangzhou, 510630, China

    Jing Wang

  5. Department of Spine Surgery, Center for Orthopaedic Surgery, The Sixth Affiliated Hospital of Sun Yat-Sen University, Guangzhou, 510655, China

    Kebing Chen

Authors
  1. Kehui Zhu
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Kun Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Junsi Huang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Xueqiong Weng
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qiaoyun Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Tianyu Gao
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Kebing Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Chunxia Jing
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Jing Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Guang Yang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

KZ, KL and JH: conceptualization, writing-original draft, writing-review and editing, resources. XW: data curation. QC, TG: investigation, resources. KC, CJ: software, validation, writing-review and editing. JW, GY: conceptualization, validation, supervision, writing-review and editing, project administration. All the authors have read and approved the final manuscript.

Corresponding authors

Correspondence to Jing Wang or Guang Yang.

Ethics declarations

Ethics approval and consent to participate

Approved by the Ethics Committee of the School of Medicine of Jinan University, Guangzhou, China, and performed strictly in accordance with the Declaration of Helsinki.

Consent for publication

All participants provided written informed consent.

Competing interests

The authors declare that they have no conflict of interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1:

Table S1. Risk of T. gondii for compound osteoporosis under different stratification factors.

Additional file 2:

Table S2. Risk of T. gondii for compound osteoporosis in women stratified by age.

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and Permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhu, K., Liu, K., Huang, J. et al. Toxoplasma gondii infection as a risk factor for osteoporosis: a case–control study. Parasites Vectors 15, 151 (2022). https://doi.org/10.1186/s13071-022-05257-z

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s13071-022-05257-z

Keyword

Parasites & Vectors

ISSN: 1756-3305

Contact us