The Effect of Helminth Infections and Their Treatment on Metabolic Outcomes: Results of a Cluster-Randomized Trial Open Access

Abstract

Noncommunicable diseases accounted for 72.3% of deaths globally in 2016 [1]. Ischemic heart disease and cerebrovascular disease are the highest contributors to this mortality and morbidity [1]. Metabolic disorders such as type 2 diabetes mellitus (T2D) and dyslipidemia are important cardiovascular disease risk factors. In 2017 an estimated 425 million people had diabetes worldwide and the number is projected to increase—disproportionately in low- and middle-income countries (LMICs)—to 629 million by 2045 [2]. Dyslipidemia, which results in atherosclerosis, is the leading risk factor for myocardial infarction and stroke [3, 4].

Chronic, low-grade, obesity-driven inflammation has been implicated in the etiology and progression of insulin resistance and T2D [5]. Atherosclerosis results from a chronic inflammatory state mediated by macrophages in the vascular subendothelium combined with high levels of lipids in the systemic circulation [6]. Lipids are utilized by and involved in mediation of immune processes; therefore, inflammation may influence lipid levels in the circulation [7]. Modulation of these inflammatory processes may delay the development of T2D and atherosclerosis.

More than a billion people are helminth-infected worldwide, predominantly in LMICs [8]. Helminths have coevolved with humans over millions of years so that they survive in the human host but mostly cause only subtle harm. To ensure survival, helminths modify type 2 and regulatory immune responses in the human host [9]. With these immunomodulatory properties, helminths may be able to annul the inflammation that results in metabolic disorders and therefore confer protection [10]. Studies in experimental animals support this hypothesis. Mice infected with Schistosoma mansoni [11], Nippostrongylus brasiliensis [12], and Litomosoides sigmodontis [13] had decreased insulin resistance and improved glucose tolerance compared with uninfected mice. Infection of mice with S. mansoni cercariae [14] and intraperitoneal inoculation of S. mansoni eggs [15] resulted in lower blood lipid levels than in uninfected/uninoculated controls. In mice, S. mansoni infection also reduced development of atherosclerotic lesions [14], and ES-62, a product from the filarial nematode Acanthocheilonema vitae, caused a 60% reduction in aortic atherosclerotic lesions [16].

In humans, published studies investigating the effect of helminths on metabolic outcomes are few and observational, except for a single trial. In China, history of Schistosoma japonicum infection was associated with lower levels of fasting blood glucose, glycated hemoglobin (HbA1c), and insulin resistance, and lower prevalence of diabetes and metabolic syndrome [17], whereas chronic infection with this helminth was associated with lower serum triglycerides and total cholesterol [18]. Among Australian Aboriginals, Strongyloides stercoralis infection was associated with a lower likelihood of diabetes [19], and treatment of Strongyloides worsened glycemic status [20]. Among the Tsimane of the Bolivian Amazon, helminth infection was inversely associated with serum lipid levels [21]. Chronic infection with the trematode Opisthorchis felineus was associated with lower serum cholesterol levels and diminished atherosclerosis in a postmortem study in Russia [22]. In Indonesia, infection with soil-transmitted helminths (STHs) was associated with lower insulin resistance and body mass index (BMI) [23]. The only trial to date, conducted in Indonesia, showed no effect of albendazole treatment for STHs on insulin resistance, BMI, or waist circumference overall, but showed increased insulin resistance in individuals infected with STHs at baseline [24].

Observational studies cannot demonstrate causality and are prone to bias from unmeasured confounders. The only previous trial was done in a setting with high prevalence of STH. However, other parasitic infections such as S. mansoni may have a different impact on metabolic outcomes because of the different location of adult worms and inflammatory and regulatory elements of their life cycles. We therefore aimed to investigate, in a setting of high S. mansoni prevalence, the effect of helminths and their treatment on metabolic outcomes in individuals aged ≥10 years. We also conducted observational analyses to assess cross-sectional associations between helminths and metabolic outcomes.

METHODS

Study Setting and Design

This was a 2-arm, cluster-randomized trial of community-wide intensive vs standard anthelminthic treatment conducted in 26 Lake Victoria fishing villages of Koome subcounty, Mukono district, Uganda (ISRCTN47196031). This population is ethnically diverse with the majority from central Uganda (of Bantu ethnic origin). There is some acculturation as different ethnic groups live together and use Luganda as the lingua franca. The main economic activity is fishing with a minority involved in agriculture. Villages are well defined, geographically separate, and close to the lake. The residents live in temporary housing made from wood (locally obtained) and roofed with iron sheets or plastic. Houses are built close together. The island communities trade with mainland communities (both nearby and far) in fish and general merchandise.

The protocol has been published elsewhere [25]. In brief, 13 villages were randomized to intensive and 13 to standard intervention. Intensive treatment comprised praziquantel 40 mg/kg single-dose administered using an extended height pole (which extended treatment to include preschool age groups) and albendazole 400 mg triple-dose, both quarterly. Standard treatment comprised single-dose praziquantel (40 mg/kg) annually and single-dose albendazole (400 mg) biannually. Trial interventions started in September 2012. Originally, the trial was designed to investigate the effects of 3 years’ intervention on allergy-related outcomes and helminth-related morbidity, but interventions were extended for an extra year, allowing us to assess their impact on metabolic outcomes.

Randomization and Masking

This was an open trial. Villages were randomized in a 1:1 ratio using restricted randomization to ensure balance for village size, previous community-wide anthelminthic treatment, and distance from the subcounty health center [25].

Exposures and Outcomes

The exposures of interest were anthelminthic intervention (for the trial) and helminth infections (for observational analyses). The primary outcome was insulin resistance measured by the homeostatic model assessment of insulin resistance (HOMA-IR) [26], calculated as (fasting serum insulin [μU/mL] × fasting glucose [mmol/L]) / 22.5. Secondary outcomes were fasting blood glucose, HbA1c, fasting serum lipids (triglycerides, total cholesterol, high-density lipoprotein cholesterol [HDL-c], low-density lipoprotein cholesterol [LDL-c]), blood pressure, BMI, waist circumference, waist-to-hip ratio, and (for the trial) helminth infection status.

Procedures

The effects of helminths and anthelminthic intervention were assessed in a household survey conducted in all study villages after 4 years of intervention. We selected 70 households per village by simple random sampling using Stata version 13.0 software (StataCorp, College Station, Texas) (Supplementary Methods). Permission for household participation was sought from each household head or another adult in the household if the head was absent. Household members aged ≥10 years were invited to participate.

After obtaining written informed consent from each household member (and assent from individuals aged 10–17 years), a questionnaire was administered. Data were collected on sociodemographic characteristics, diet, exercise, lifestyle, and personal and family history of diabetes and hypertension. Participants’ blood pressure (BP), weight, height, and waist and hip circumference were measured using standardized procedures (Supplementary Methods). Peripheral venous blood was collected after an overnight fast for measurement of the primary and secondary outcomes (Supplementary Methods).

Each participant was requested to provide 1 stool sample, from which duplicate slides were made and examined independently by 2 experienced technicians using the Kato-Katz method. Stool real-time polymerase chain reaction (PCR) was also used to detect S. mansoni, hookworm (Necator americanus), and S. stercoralis infection (Supplementary Methods).

Statistical Methods

For this survey, we planned to recruit 1950 participants (Supplementary Methods). Statistical analyses were done using Stata version 13.0 software; all analyses allowed for within-cluster correlations. The trial analysis was by intention-to-treat and measured cluster-level differences. For continuous outcomes, means were calculated for each village (cluster-specific means) and the mean of these within each study arm was used as a summary measure of the outcome in that study arm. The t test was used to compare cluster-specific means between arms, with corresponding 95% confidence intervals (CIs) computed. Continuous outcomes with skewed cluster-specific mean distributions were log-transformed before analysis and results back-transformed to give geometric mean ratios. For binary outcomes, we calculated risk ratios by dividing the mean of the cluster-specific proportions in the intensive arm by that in the standard arm. P values were calculated from t tests comparing cluster-specific proportions, and CIs using a Taylor series approximation to estimate standard errors. For all outcomes, the effects of the intervention were additionally adjusted for age and sex using a 2-stage approach [27].

The individual level observational analysis was performed to assess helminths as risk factors for metabolic disease. Potential confounders were identified based on a causal diagram (Supplementary Figure 1). Crude and adjusted associations were estimated using linear regression models fitted for each worm separately. Stata “svy” commands were used to allow for clustering of participants within villages, and for the non-self-weighting survey design due to variable village sizes. For adjusted analyses, only risk factors/confounders crudely associated with the outcome with P value ≤ .15 were included in final models. No corrections were made for multiple testing.

Ethical Considerations

Ethical clearance was granted by the Uganda Virus Research Institute Research ethics committee (reference GC/127/17/01/573), the London School of Hygiene and Tropical Medicine (reference 9917), and the Uganda National Council for Science and Technology (reference HS 2185). Permission to conduct the work was granted by community leaders in all study villages.

RESULTS

Between April and November 2017, 70 households were randomly selected from each village except in 2 villages with fewer households where all were selected. Of eligible households and eligible individuals in those households, 71.3% (1276/1790) and 87.0% (1898/2181), respectively, agreed to participate. We examined 1817 of 1898 (95.7%) participants, and 1686 of 1898 (88.8%) provided blood samples after an overnight fast. Numbers of participants providing data were balanced across trial arms (Figure 1).

Figure 1.

Flowchart of the survey on metabolic outcomes in the Lake Victoria Island Intervention Study on Worms and Allergy-related Diseases cluster-randomized trial. *In 2 villages, the total number of households per village was <70, and therefore all households (41 and 69, respectively) were invited to participate. Abbreviations: BMI, body mass index; HOMA-IR, homeostatic model assessment of insulin resistance.

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Characteristics of participants are shown in Table 1. This is a young population with a mean age of 31.5 years (standard deviation [SD], 11 years) considering that individuals aged <10 years were excluded. There are more males than females and the main occupation is fishing; the majority (1309/1898 [69%]) reported daily contact with the lake. Activity levels were high: 920/1898 (48.4%) reported vigorous physical activity at least weekly, with a mean number of days of 2.8 (SD, 2.7 days). Diet mainly consists of fish (eaten on average 4.8 days a week) and is low in fruit (on average 1 day a week). The majority of participants (1218/1898 [64.2%]) reported having lived in the village in which they were surveyed throughout the 4-year intervention period. Only 283 of 1898 (14.9%) had ever undergone BP measurement and 80 of 1898 (4.2%) had previously had blood sugar levels tested.

Participants living in intensive anthelminthic intervention villages had lower S. mansoni prevalence than those in standard intervention villages (stool Kato-Katz: intensive 21.9%, standard 35.6%, P = .02; stool PCR: intensive 37.3%, standard 56.0%, P = .01). Similar effects were observed for hookworm (stool PCR: intensive 2.3%, standard 4.8%, P = .03) and Strongyloides (stool PCR: intensive 4.8%, standard 9.0%, P = .02). Around half of S. mansoni infections were of light intensity (intensive 12.2%, standard 17.4%). The intervention had no effect on Trichuris trichiura (Table 2).

There was no evidence of a difference in HOMA-IR between the study arms (Table 3). However, there was some evidence of a difference in mean LDL-c, higher in the intensive arm (2.86 vs 2.60 mmol/L; adjusted mean difference, 0.26 [95% CI, −.03 to .56]; P = .08). No differences were seen between trial arms for the other metabolic parameters (Table 3). Further analysis of the metabolic outcomes categorized as binary (diabetes, impaired fasting glucose, hypertension, obesity, and metabolic syndrome) showed no differences between trial arms (Supplementary Table 1).

Key associations from our observational analysis are shown in Table 4; all associations tested are shown in Supplementary Table 2. Schistosoma mansoni–infected participants had lower total cholesterol levels than uninfected participants (4.24 mmol/L vs 4.64 mmol/L; crude mean difference, −0.40 [95% CI, −.62 to −.19]; P = .001). Strong evidence for this association remained after adjusting for age, sex, occupation, residence, diet, exercise, family history of obesity, and paternal and maternal tribe (−0.25 [95% CI, −.44 to .07]; P = .01). Schistosoma mansoni infection was associated with lower LDL-c (2.37 vs 2.80 mmol/L; −0.25 [95% CI, −.49 to −.02]; P = .04) but not with HDL-c. Strongyloides infection was associated with lower LDL-c levels (P = .003). Participants with heavy S. mansoni infection intensity had the lowest triglyceride levels (P = .0004) and lowest diastolic BP (P = .01). Participants with moderate S. mansoni infection intensity had the lowest LDL-c levels (P = .04). Coinfection with multiple (increasing) helminth species was associated with lower total and LDL-c (trend P = .02).