Study design and settings

This was a cross-sectional analysis of baseline data from the Chronic Infections, Co-morbidities and Diabetes in Africa (CICADA) study, a cohort study investigating risk factors for diabetes among HIV-uninfected and HIV-infected adults in north-western Tanzania and registered at clinical.trials.gov as NCT03106480. During October 2016 to November 2017, CICADA recruited 1947 participants and those with both helminth (Schistosoma and geohelminth) and insulin data were eligible for inclusion in the current analysis.

Recruitment of participants

The study population and main methods have been reported recently [7]. Briefly, all surviving HIV-infected individuals from the Nutritional Support for African Adults Starting Antiretroviral Therapy (NUSTART) trial [18] and both HIV-infected and uninfected individuals from TB-NUT (Nutrition, Diabetes and Pulmonary Tuberculosis) study [19, 20] were invited for enrolment in CICADA study. HIV-infected participants from those studies had been on ART a median of 53 months (interquartile range 46; 102 months). In addition, a new cohort of HIV-infected people who visited antiretroviral therapy (ART) clinics in Mwanza City from October 2016 to November 2017, who were preparing to start ART and were not part of TB-NUT or NUSTART cohorts were also invited if they were aged ≥18 years and residents of Mwanza City. Using a computer-generated randomization list, we randomly selected half of the new HIV-infected participants and selected HIV-uninfected participants for frequency matching. Criteria for HIV-negative participants were: lived within the same neighbourhood as the HIV index participant (defined as living in the same street or sub-village), HIV-negative based on HIV rapid tests, had lived in Mwanza City for at least 3 months with no plans for relocating within the next 3 years, aged 18 years or above and age difference from the HIV-infected index participant not more than 5 years, same sex as the HIV-infected index participant, and willing to consent.

Data collection

Ethics

Ethical clearance was provided by the National Institute for Medical Research (NIMR) in Tanzania and the London School of Hygiene and Tropical Medicine in UK and a consultative approval was obtained from the National Committee on Health Research Ethics in Denmark. Participants were enrolled after completing a written informed consent and those with diabetes and other illnesses were referred to Sekou-Toure referral hospital for care. All data were fully anonymized.

Data management and statistics

Data were double entered in CSPro database and analysed in STATA version 13 (Station College, Texas, USA). Demographic characteristics, body composition, physical activity, smoking, alcohol drinking, CRP and HIV were presented as percentages, means, and geometric means. Comparison of these variables between participants without helminth infection vs those with Schistosoma or geohelminth infection were done using t-test (if variables were continuous or after log-transformation where data were presented as geometric means) and chi-squared test (if variables were categorical).

We investigated the role of Schistosoma and geohelminth infections on fasting insulin, 30, and 120 min insulin using generalized estimating equations (GEE) with gamma distribution and log link since data were skewed positively with an unstructured covariance matrix (to account for within-person correlations of these markers at the 3 time points) and robust standard errors. However, for correlated outcomes with normal distribution (fasting glucose, 30, and 120 min glucose) we applied GEE with Gaussian distribution and identity link. For derived markers of β-cell function (i.e. HOMA-β, insulinogenic index and overall insulin release index) and HOMA-IR, which were all positive skewed, we used generalized linear models with gamma distribution and log link to investigate the association of main exposures on these outcomes. Finally, linear regression with robust standard errors was used on to investigate the associations between exposures with HbA1c, fat mass and waist circumference. Analyses were initially adjusted for age and sex and in final models further adjustments for body mass index, physical activity, and CRP were done [31–33] as well as malaria infection and clinical TB co-morbidities which may cofound the hypothesized relationships [34, 35] However, in final models for fat mass and waist circumference we adjusted for alcohol intake [36] and smoking [37, 38] in addition to CRP and physical activity because these could be important confounders. Data on these associations were presented as marginal means with 95% confidence intervals. In all analyses a significance level of P<0.05 was used. Effect modification by HIV status was explored by fitting interaction terms where wald tests with p<0.05 indicated significant interactions existed.

Association of Schistosoma infection with β-cell function and insulin resistance

Table 2 presents associations of Schistosoma infection with markers of β-cell function and insulin resistance. Among the HIV-uninfected group, in final models, Schistosoma infection was associated with higher 30 min insulin (24.2 mU/L, 95% CI: 6.9, 41.6) and overall insulin release index (13.3 pmol/L/mmol/L, 95%CI: 3.7, 22.9) but there was no association with HOMA-IR. In contrast among the HIV-infected not yet on ART group, Schistosoma infection was associated with lower fasting insulin (-0.9 mU/L, 95%CI: -1.6, -0.2) and 120 min insulin (-12.0 (mU/L, 95% CI: 18.9, -5.1) as well as HOMA-IR (-0.3 mmol/L, 95%CI: -0.6, -0.05). Among HIV-infected participants on ART 30 min insulin, 120 min insulin, HOMA-β, insulinogenic index and overall insulin release index tended to be lower in participants with Schistosoma infection, but no differences were statistically significant.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 2. Analysis of association of Schistosoma infection with β-cell function and insulin resistance by HIV treatment status.

https://doi.org/10.1371/journal.pone.0262860.t002

Association of geohelminth infection with β-cell function and insulin resistance

Table 3 presents the association of geohelminth infection with markers of β-cell function and insulin resistance. In final adjusted models, we found that among the HIV-uninfected group, geohelminth infection was associated with lower insulinogenic index (-0.9(mU/L)/(mg/dL, 95% CI:—1.7, -0.1), but there was no association with insulin resistance. In addition, among HIV-infected participants not yet on ART, geohelminth infection was associated with lower fasting insulin (-0.9 mU/L, 95% CI: -1.6, -0.2), 120 min insulin (-9.1 mU/L, 95%CI: -17.3, -1.0), HOMA-β (-8.9 mU/L)/(mmol/L, 95% CI: -15.3, -2.6), and overall insulin release index (-5.1 pmol/L/mmol/L, 95%CI: -10.3, 0.02), although this was marginally significant. Among HIV-infected participants on ART we found no association with geohelminths.

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 3. Analysis of association of geohelminth infection with β-cell function and insulin resistance by HIV treatment status.

https://doi.org/10.1371/journal.pone.0262860.t003

Association of helminth infections with glucose, HbA1c and body composition

There was no association between Schistosoma infection with glucose, HbA1c, fat mass and waist circumference in either HIV-infected group (Table 4). However, among HIV-uninfected participants, geohelminth infection was associated with lower fat mass and waist circumference (P<0.005, all) and with HbA1c, although this was only marginally significant (P = 0.06) (Table 5)

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 4. Analysis of association of Schistosoma infection with glucose, HbA1c, fat mass, and waist circumference by HIV treatment status.

https://doi.org/10.1371/journal.pone.0262860.t004

Download:

• PPT
  PowerPoint slide
• PNG
  larger image
• TIFF
  original image

Table 5. Analysis of association of geohelminth infection with glucose, HbA1c, fat mass, and waist circumference by HIV treatment status.

https://doi.org/10.1371/journal.pone.0262860.t005

Beneficial effects of Schistosoma and geohelminth infections

Several studies have reported associations of Schistosoma and geohelminth infections with metabolic diseases. A recent study in Uganda found no association of helminths with insulin resistance or glucose [41], but in Ethiopia investigators found in a small study that S. mansoni infection was associated with reduced risk of impaired fasting glucose, but not with insulin secretion [42]. Outside SSA, onene Chinese study by Yuhong and colleagues found that history of previous S. mansoni infection was associated with reduced risk of diabetes and better metabolic profile among adults aged >60 years [43]. Similarly, Wiria and colleagues found that helminths were associated with modest improvement in insulin sensitivity not accounted by body mass index reduction alone [44]. Most previous studies investigated the role of helminths on insulin resistance and not both insulin resistance and β-cell function. Therefore, our study adds novel data on this subject. We think at least two mechanisms could explain the beneficial effect of schistosomes on β-cell function among HIV-uninfected participants found in our study. First, Schistosoma infection could have reduced the negative effects of pro-inflammatory cytokines, including interleukin-1beta (IL-1β), tumour necrosis factor-α (TNF-α) and gamma-interferon (γ-IFN) on islet β cells [45] by shifting Th1 to Th2 immune response [4, 5]. In animal studies it has been shown that extracts of soluble S. mansoni worm or eggs antigens induced secretion of anti-inflammatory cytokines including IL-10, IL-4 and IL-5 from T cells and subsequently prevented development of type 1 diabetes in non-obese mice [46]. Similarly, in a group of mice with diabetes induced with streptozotocin (pancreatic islets β-cell toxin), those infected with Schistosoma mansoni had more pancreatic β-cells mass and less focal degeneration as well as lower glucose level in comparison to those without Schistosoma infection [47]. Second, by switching Th1 to Th2 immunomodulation profile, Schistosoma infection could have reduced white adipose tissue inflammation, and subsequently leading to reduced insulin resistance [48]. The reduced insulin resistance would have resulted in reduced β-cells glucotoxicity [49] contributing to improved β-cell function. However, we found that Schistosoma infection was not associated with reduced insulin resistance. Although this could have been due to the fact that the predictive ability of HOMA-IR on insulin resistance was only modest in this population [50].

Although geohelminth infections were not associated with improved β-cell function, possibly due to lack of strong immune-modulatory effects [26], they were associated with lower total fat mass as well as reduced waist circumference independent of physical activity. This could have been due to loss of appetite associated with systemic or intestinal infections, but this is unlikely since it was independent of systemic inflammation (measured by CRP) and was observed in HIV-uninfected participants but not among HIV-infected participants, the population group at a higher risk of experiencing loss of appetite. So these changes were mostly likely a reflection of body weight reduction which is characteristic of helminth infections [48]. In mice studies, administration of Schistosoma egg antigens were associated with reduced risk of obesity [48, 51]. Additionally, Wiria and colleagues found parasite intensity was negatively associated with body weight [44] and a Chinese study observed previous schistosome intensity was associated with current weight [43]. Reduction of abdominal fat is known to reduce the risk of diabetes, although this was not evident in the current study. This may have been because the observed loss in waist circumference was only modest.

Association of Schistosoma and geohelminth infections among HIV-infected patients

In this analysis we found that among HIV-infected patients, geohelminth and Schistosoma infections were associated with reduced insulin secretion, although this was not accompanied by corresponding higher glucose or HbA1c level. This is in accordance with studies that had shown that schistosomiasis could worsen HIV progression [52] and that immunological shift from Th1 to Th2, leaves the body unarmed to combat viral and bacterial infections which could lead to severe infections and subsequently to insulin resistance [39, 40]. Insulin resistance resulting in hyperglycaemia could have led to reduced β-cell function secondary to glucotoxicity [17].

However, we found no effect on insulin resistance despite the fact that insulin resistance is commonly associated with systemic inflammation among HIV-infected patients. It is therefore possible that the negative effect on β-cell function could be explained by other mechanisms including direct deleterious effects of pro-inflammatory cytokines on β-cells. Further research to understand mechanisms underlying development of helminth-associated β-cell function and possibly insulin resistance would help in developing strategies to prevent or manage diabetes in these populations.

Implications of results

Although Schistosoma and geohelminth infections should be prevented and treated, such measures could remove protection against diabetes and other metabolic diseases among HIV-uninfected populations. Although this is not a justification to withdraw prevention or treatment modalities, these measures should be implemented alongside other strategies to reduce risk of metabolic diseases including promotion of physical activity, weight reduction, consumption of healthy diet as well as avoiding excessive alcohol intake. Such non-communicable diseases (NCDs) prevention strategies are important to HIV-infected individuals particularly those not yet on ART since although reduced β-cell function was not related to overt hyperglycaemia these patients could quickly develop hyperglycaemia if they harbor other risk factors. Similarly, it is important to encourage early initiation as well as lifelong adherence of ART to reduce risk of β-cell function associated with Schistosoma and geohelminth infections. This is important because despite the roll out of the universal test-and treat policy which encourages HIV testing and immediate uptake of ART, many HIV patients do not start ART in timely fashion and, of those starting, up to 50% are lost to follow-up or become non-adherent within 3 years of starting treatment [53] thus increasing their diabetes risk. Finally, in view of these results, trials testing effects of Schistosoma or geohelminths derived antigens on risk of metabolic diseases should be encouraged to help develop interventions for the prevention of diabetes and other NCDs.

Strengths and weaknesses

The strength of this study is that it included both HIV-infected and un-infected to assess the role of Schistosoma and geohelminth-HIV coinfection on β-cell function and insulin resistance; thus results can be generalized to wider populations in SSA where these helminths and HIV have high prevalence and overlap widely. In addition, the prevalence of Schistosoma and geohelminth infections was based on stool/urine examination and not symptom-based algorithms thus reducing potential for misclassification bias. However, in the assessment of helminths we only collected one day stool samples and diagnostic methods used have lower sensitivity compared to molecular and immunodiagnostic methods [54, 55], thus we may have underestimated the helminth prevalence. Also we did ask participants to refrain from physical activity during fasting because we knew most of our participants would walk or catch a public transport to our research clinic, but we expected this to be short with minimal effect in lowering glucose level. This study was cross-sectional and therefore causality cannot be confirmed. Although we controlled for potential confounders, we cannot rule out that there remained residual confounding. Finally, the sample size for participants on ART was the smallest, despite this being an important group given that most HIV patients should be on ART. Future larger studies should assess the association of helminth infections on β-cell function and insulin resistance among patients on ART.