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. 2020 Mar 3;14(3):e0008101. doi: 10.1371/journal.pntd.0008101

Helminth infection modulates systemic pro-inflammatory cytokines and chemokines implicated in type 2 diabetes mellitus pathogenesis

Anuradha Rajamanickam 1, Saravanan Munisankar 1, Chandrakumar Dolla 2, Pradeep A Menon 2, Kannan Thiruvengadam 2, Thomas B Nutman 3, Subash Babu 1,3,4,*
Editor: Mathieu Nacher5
PMCID: PMC7069638  PMID: 32126084

Abstract

Background

The prevalence of helminth infections exhibits an inverse association with the prevalence of Type 2 diabetes mellitus (T2DM), and helminths are postulated to mediate a protective effect against T2DM. However, the biological mechanism behind this effect is not known.

Aims/Methods

We postulated that helminth infections act by modulating the pro-inflammatory cytokine and chemokine milieu that is characteristic of T2DM. To examine the association of cytokines and chemokines in helminth-diabetes co-morbidity, we measured the plasma levels of a panel of pro-inflammatory cytokines and chemokines in individuals with Strongyloides stercoralis infection (Ss+) and T2DM at the time of Ss diagnosis and then 6 months after definitive anthelmintic treatment along with uninfected control individuals with T2DM alone (Ss-).

Principal findings

Ss+ individuals exhibited significantly diminished levels of the pro-inflammatory cytokines–IL-1α, IL-1β, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF and chemokines–CCL1, CCL2, CCL3, CCL11, CXCL1, CXCL2, CXCL8, CXCL9, CXCL10 and CXCL11. In contrast, Ss+ individuals exhibited significantly elevated levels of IL-1Ra. Anthelmintic treatment resulted in increased levels of all of the cytokines and chemokines.

Conclusions

Thus, helminth infections alleviate and anthelmintic therapy partially restores the plasma cytokine and chemokine levels in helminth-diabetes co-morbidity. Our data therefore offer a plausible biological mechanism for the protective effect of helminth infections against T2DM.

Author summary

Helminth infections are postulated to provide a degree of protection against the development of metabolic disorders such as T2DM and alleviate pathology following development of such disorders. However, the biological mechanism underlying this interaction is largely unknown. Since pro-inflammatory cytokines and chemokines are major drivers of pathology in T2DM, we examined the influence of coexistent helminth infection (in this case, Strongyloides stercoralis) on the cytokine and chemokine milieu in T2DM. We demonstrate that helminth infection significantly alleviates the pro-inflammatory milieu in T2DM by lowering the systemic levels of cytokines and chemokines. We also demonstrate that anthelmintic therapy exacerbates this pro-inflammatory milieu by partially restoring the high levels of cytokines and chemokines. So, our data uncovers a role for cytokines and chemokines in the mainstream interaction between helminth infections and metabolic disorders.

Introduction

Helminth infections affect about one-quarter of the globe and are highly prevalent in lower to middle-income countries [1]. In contrast, the prevalence of inflammatory metabolic diseases, such as Type 2 diabetes mellitus (T2DM) is high in high-income countries. The absence of exposure to helminth infections has been postulated as one mechanism to explain this markedly increased prevalence of T2DM [26]. Recent observational studies in India, Indonesia, China and Australia have reported that the prevalence of helminth infections was significantly lower in T2DM individuals compared to non-diabetic controls [4, 5, 7, 8], thus confirming a protective effect of helminths against T2DM pathogenesis.

Among various pathophysiological mechanisms underlying the development of T2DM, a major one is the development of chronic, low-level inflammation, also named meta-inflammation, which is characterized by a distinctly exaggerated pro-inflammatory cytokine and chemokine milieu [9]. This ultimately leads to increased insulin resistance and perturbed glucose/lipid metabolism [10]. In contrast, helminth infections are typically characterized by the induction of Type 2 immune responses, with elevations in Type 2 and regulatory cytokines [11]. Moreover, the regulatory networks induced by helminth parasites can modulate bystander immune responses, including those of allergy and auto-immunity [12].

Therefore, we postulated that one possible mechanism by which helminth infections mediate protection against T2DM is by modulating the pro-inflammatory milieu in T2DM. To test this hypothesis, we examined a panel of pro-inflammatory cytokines and chemokines before and after anthelmintic therapy in a cohort of Strongyloides stercoralis–diabetes individuals and compared them to diabetic individuals alone. Our data reveal that helminth infections do indeed diminish the plasma levels of cytokines and chemokines in T2DM and this is partially reversed following chemotherapy.

Material and methods

Ethics statement

All the study participants were assessed as part of a natural history study protocol (12-I-073) approved by Institutional Review Boards of the National Institute of Allergy and Infectious Diseases (USA) and the National Institute for Research in Tuberculosis (India), and informed written consent was obtained from all participants. This was the same study population that was previously used for assessment of metabolic parameters [13].

Study population

We enrolled 118 individuals comprising of 60 clinically asymptomatic Ss-infected individuals with T2DM (hereafter Ss+), and 58 individuals with T2DM and no Ss infection (hereafter Ss-) in Kanchipuram District, Tamil Nadu, South India (Table 1). These study participants were all recruited from a rural population by screening of individuals for helminth infection by stool microscopy and serology as described earlier [1417]. All the recruited study participants were aged from 18 to 75 years. Individuals with any previous history of helminth infection or previous anthelmintic treatment or HIV infections, individuals who had iron deficiency anemia, alcoholism, chronic renal failure, hyperbilirubinaemia and those taking large doses of aspirin were excluded from the study. Pregnant or lactating women were excluded from the study.

Table 1. Demographic and Biochemical parameters.

Ss+ Ss-
n = 60 n = 58
M/F 30/30 30/28
Age 46 (24–63) 45 (22–63)
RBG (mg/dl) 179 (140–438) 180.5 (140–198)
HbA1c (%) 8.57 (6.5–12.5) 8.9 (6.5–11.8)
Urea (mg/dl) 19.5 (12.34) 21.9 (11–42)
Creatinine (mg/dl) 0.78 (0.3–1) 0.85 (0.6–1.0)
ALT (U/L) 17.7 (7–60) 22.4 (7–92)
AST (U/L) 27.8 (16–110) 24.7 (11–68)

Parasitological examination and anthelmintic treatment

Ss infection was diagnosed by the presence of IgG antibodies to the recombinant NIE antigen as described earlier [15, 17]. A single stool sample was obtained and examined for intestinal helminth infection by Kato-Katz technique. Stool samples were found to be negative for other intestinal helminths by stool microscopy. Subsequently, Ss infection was further confirmed by specialized stool examination with nutrient agar plate cultures [18]. Filarial infection was excluded in all study participants by virtue of being negative in tests for circulating filarial antigen. All Ss+ study participants were treated with a single dose of ivermectin (12mg) and albendazole (400 mg) and follow–up blood draws were collected six months later. Following anthelmintic treatment, parasitological examinations were repeated after 6 months to confirm successful chemotherapy.

Determination of T2DM status

Diabetes was defined as an HbA1c reading of 6.5% or greater and a random blood glucose of >200 mg/dl, according to the American Diabetes Association criteria. All the biochemical parameters were measured after overnight fasting except random blood glucose. All of the diabetic individuals in this study were newly diagnosed and were not on any anti-diabetic medication previously. All diabetic individuals were referred to the primary health care centre for diabetic treatment.

Measurement of biochemical and anthropometric parameters

Anthropometric measurements, including height, weight and waist circumference, and biochemical parameters, including plasma glucose, lipid profiles and HbA1c were obtained using standardized techniques as described previously [19]. Serum samples were used for biochemical parameters and plasma samples were used for the other measurements.

Measurement of plasma adipocytokines and cytokine levels

Plasma levels of cytokines: IL1α, IL-1β, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF were measured using a Bioplex multiplex assay system (Bio-Rad, Hercules, CA). The levels of chemokines: CCL1, CCL2, CCL3, CCL4, CCL11, CXCL1, CXCL2, CXCL9, CXCL10 and CXCL11 were measured using Human magnetic Luminex Assay Kit from R&D Systems according to the manufacturer’s protocol. Plasma level of IL-1Ra was measured using the Quantikine ELISA kit (R&D Systems) according to the manufacturer's instructions. We measured the Ss+ and Ss- samples side by side for each cytokine.

Statistical analysis

Data analyses were performed using Graph-Pad PRISM Version 8.0 (GraphPad, San Diego, CA) and JMP14 software was used to plot Principle Component Analysis (PCA) and heatmap. Central tendency was measured using Geometric means (GM). Statistically significant differences were analyzed using Mann-Whitney U tests were used to compare Ss+ vs. Ss- and the Wilcoxon signed rank test was used to compare parameters before and after treatment followed by Holm’s correction for multiple comparisons. The logistic regression was not suitable for this data to predict the group differences (i.e. Ss+ and Ss-) because of the multicollinearity between most of the key variables. Those variables significantly different by Mann-Whitney test were also significantly different by the univariate logistics regression model. Sample size calculation was done to detect a significant difference (p<0.05) among the cytokines and chemokines based on preliminary analysis between the two groups. We determined that we needed 58 individuals in each group to detect this difference with a power of 90% and a Type I error of 5%.

Results

Study population characteristics

The baseline demographic characteristics and biochemical parameters of Ss+ and Ss- individuals are shown in Table 1. As shown and as described previously [13], there were no significant differences in age, sex, BMI or other biochemical parameters between the two groups.

Diminished plasma levels of pro-inflammatory cytokines in Ss+ individuals with T2DM

To determine the effect of Ss infection on the pro-inflammatory cytokine milieu in T2DM, we measured the plasma levels of IL-1α, IL-1β, IL-1Ra, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF in Ss+ and Ss- individuals. As shown in Fig 1, Ss+ individuals had significantly lower levels of IL-1α (GM of 350.1 pg/ml in Ss+ vs. 458.8 pg/ml in Ss-; p = 0.0009), IL-1β (GM of 254.1 pg/ml in Ss+ vs. 342.4 pg/ml in Ss-; p = 0.0008), IL-6 (GM of 65.58 pg/ml in Ss+ vs. 133.3 pg/ml in Ss-; p = 0.0007), IL-12 (GM of 84.46 pg/ml in Ss+ vs. 88.6 pg/ml in Ss-; p = 0.0042), IL-18 (GM of 283.7 pg/ml in Ss+ vs. 412.1 pg/ml in Ss-; p = 0.0260), IL-23 (GM of 244.1 pg/ml in Ss+ vs. 298.2 pg/ml in Ss-; p = 0.0380), IL-27 (GM of 323.8 pg/ml in Ss+ vs. 516.3 pg/ml in Ss-; p = 0.0483), G-CSF (GM of 68.46 pg/ml in Ss+ vs. 114.8 pg/ml in Ss-; p = 0.0426), and GM-CSF (GM of 78.89 pg/ml in Ss+ vs. 95.22 pg/ml in Ss-; p = 0.0448) in comparison with Ss- individuals. In contrast, Ss+ individuals had significantly higher levels of IL-1Ra (GM of 267.6 pg/ml in Ss+ vs. 203.4 pg/ml in Ss-; p = 0.0004). Thus, Ss infection appears to modulate the systemic pro-inflammatory cytokine milieu in T2DM.

Fig 1. Diminished plasma levels of pro-inflammatory cytokines in Ss+ individuals with T2DM.

Fig 1

Plasma levels of IL1-α, IL1-β, IL-1Ra, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF cytokines were measured in Ss+ and Ss- individuals. Each dot is an individual subject with the bar representing the geometric mean (GM). p values were calculated using the Mann-Whitney U tests followed by Holm’s correction for multiple comparisons.

Diminished plasma levels of pro-inflammatory chemokines in Ss+ individuals with T2DM

To determine the effect of Ss infection on the pro-inflammatory chemokine milieu in T2DM, we measured the plasma levels of CCL1, CCL2, CCL3, CCL11, CXCL1, CXCL2, CXCL9, CXCL10 and CXCL11 in Ss+ and Ss- individuals. As shown in Fig 2, Ss+ individuals had significantly lower levels of CCL1 (GM of 878.3 pg/ml in Ss+ vs. 1095 pg/ml in Ss-; p = 0.0010), CCL2 (GM of 227.4 pg/ml in Ss+ vs. 277.9 pg/ml in Ss-; p = 0.0045), CCL3 (GM of 223.6 pg/ml in Ss+ vs. 300.9 pg/ml in Ss-; p = 0.0012), CCL11 (GM of 406.9 pg/ml in Ss+ vs. 521.2 pg/ml in Ss-; p = 0.0091), CXCL1 (GM of 711.4 pg/ml in Ss+ vs. 1040 pg/ml in Ss-; p = 0.0318), CXCL2 (GM of 383.2 pg/ml in Ss+ vs. 578.1 pg/ml in Ss-; p = 0.0410), CXCL8 (GM of 291.1 pg/ml in Ss+ vs. 410.3 pg/ml in Ss-; p = 0.0468), CXCL9 (GM of 432.5 pg/ml in Ss+ vs. 620 pg/ml in Ss-; p = 0.0438), CXCL10 (GM of 347.7 pg/ml in Ss+ vs. 479.5 pg/ml in Ss-; p = 0.0430) and CXCL11 (GM of 313.2 pg/ml in Ss+ vs. 505 pg/ml in Ss-; p = 0.0360) in comparison with Ss- individuals. Thus, Ss infection also appears to modulate the pro-inflammatory chemokine milieu in T2DM.

Fig 2. Diminished plasma levels of pro-inflammatory chemokines in Ss+ individuals with T2DM.

Fig 2

Plasma levels of CCL1, CCL2, CCL3, CCL11, CXCL1, CXL2, CXCL8, CXCL9, CXCL10 and CXCL11 chemokines were measured in Ss+ and Ss- individuals. Each dot is an individual subject with the bar representing the geometric mean (GM). p values were calculated using the Mann-Whitney U tests followed by Holm’s correction for multiple comparisons.

Anthelmintic treatment significantly increases the plasma cytokine levels in T2DM

To determine the effect of anthelmintic treatment on the pro-inflammatory cytokine milieu in T2DM, we measured the plasma levels of IL1α, IL-1β, IL-1Ra, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF in Ss+ individuals before (pre-T) and 6 months after anthelmintic treatment (post-T). At post-T, the levels of IL1α (GM of 350.1 pg/ml in pre-T vs. 496 pg/ml in post-T; p = 0.0009), IL-1β (GM of 254.1 pg/ml in pre-T vs. 268.7 pg/ml in post-T; p = 0.0008), IL-6 (GM of 65.58 pg/ml in pre-T vs. 78.4 pg/ml in post-T; p = 0.0007), IL-12 (GM of 84.76 pg/ml in pre-T vs. 90.14 pg/ml in post-T; p = 0.0006), IL-18 (GM of 283.7 pg/ml in pre-T vs. 374.9 pg/ml in post-T; p = 0.0005), IL-23 (GM of 244.1 pg/ml in pre-T vs. 312.5 pg/ml in post-T; p = 0.0004), IL-27 (GM of 323.8 pg/ml in pre-T vs. 444.3 pg/ml in post-T; p = 0.0006), G-CSF (GM of 68.47 pg/ml in pre-T vs. 88.41 pg/ml in post-T; p = 0.0044) and GM-CSF (GM of 78.89 pg/ml in pre-Tvs. 92.99 pg/ml in post-T; p = 0.0427) were all significantly increased in comparison to pre-T levels (Fig 3). In contast, the levels of IL1Ra (GM of 267.6 pg/ml in pre-T vs. 250.2 pg/ml in post-T; p = 0.0001) was significantly decreased at post-T. Thus, anthelmintic treatment partially restores the pro-inflammatory cytokine milieu in T2DM.

Fig 3. Anthelmintic treatment significantly increased the plasma cytokine levels in T2DM.

Fig 3

Plasma levels of IL1-α, IL1-β, IL-1Ra, IL-6, IL-12, IL-18, IL-23, IL-27, G-CSF and GM-CSF cytokines were measured in Ss+ individuals pretreatment [Pre-T] and 6 months following treatment [post-T] were measured. The data are represented as line graphs with each line representing a single individual. p values were calculated using the Wilcoxon signed rank test followed by Holm’s correction for multiple comparisons.

Anthelmintic treatment significantly increases the plasma chemokine levels in T2DM

To determine the effect of anthelmintic treatment on the pro-inflammatory chemokine milieu in T2DM, we measured the plasma levels of CCL1, CCL2, CCL3, CCL11, CXCL1, CXCL2, CXCL9, CXCL10 and CXCL11 in Ss+ individuals before (pre-T) and 6 months after anthelmintic treatment (post-T). At post-T, the levels of CCL1 (GM of 878.3 pg/ml in pre-T vs. 939.2 pg/ml in post-T; p = 0.0009), CCL2 (GM of 227.4 pg/ml in pre-T vs. 272.1 pg/ml in post-T; p = 0.0008), CCL3 (GM of 223.6 pg/ml in pre-T vs. 282.7 pg/ml in post-T; p = 0.0007), CXCL1 (GM of 711.4 pg/ml in pre-T vs. 763.8 pg/ml in post-T; p = 0.0006), CXCL2 (GM of 383.2 pg/ml in pre-T vs. 512.9 pg/ml in post-T; p = 0.0005), CXCL8 (GM of 292.1 pg/ml in pre-T vs. 327.9 pg/ml in post-T; p = 0.0004), CXCL9 (GM of 432.5 pg/ml in pre-T vs. 546.6 pg/ml in post-T; p = 0.0009), CXCL10 (GM of 347.7 pg/ml in pre-T vs. 408.7 pg/ml in post-T; p = 0.0220) and CXCL11 (GM of 313.2 pg/ml in pre-T vs. 332.7 pg/ml in post-T; p = 0.0318) were all significantly increased in comparison to pre-T levels (Fig 4). Thus, anthelmintic treatment partially restores the pro-inflammatory chemokine milieu in T2DM.

Fig 4. Anthelmintic treatment significantly increased the plasma chemokine levels in T2DM.

Fig 4

Plasma levels of CCL1, CCL2, CCL3, CCL11, CXCL1, CXL2, CXCL8, CXCL9, CXCL10 and CXCL11 chemokines were measured in Ss+ individuals pretreatment [Pre-T] and 6 months following treatment [post-T] were measured. The data are represented as line graphs with each line representing a single individual. p values were calculated using the Wilcoxon signed rank test followed by Holm’s correction for multiple comparisons.

PCA analysis and heatmaps reveal trends in cytokine and chemokine milieu in helminth-T2DM co-morbidity

To assess the trends in cytokine and chemokine discrimination between Ss+ (both pre- and post-treatment) and Ss- individuals, we plotted PCA with different inputs. As shown in Fig 5A, PCA analysis shows that cytokines and chemokines cluster differently between Ss+ (pre-treatment) and Ss- individuals. In contrast, as shown in Fig 5B, PCA analysis shows very little clustering between Ss+ (post-treatment) and Ss- individuals. Finally, heatmap analysis using the geometric mean values of cytokine and chemokine levels shows the highly upregulated expression profile in Ss- individuals and the moderately upregulated expression profile in post-T individuals compared to pre-T Ss+ individuals (Fig 5C). Thus, these analysis help reveal the power of cytokines and chemokines to demarcate the effect of Ss infection on T2DM.

Fig 5. Principal component Analysis (PCA) and heatmaps depicting circulating levels of cytokines and chemokines in Ss+ (pre- and post-treatment) and Ss- individuals.

Fig 5

(A and B) Principal component analysis (PCA) was performed to show the distribution of data from the combination of two groups Ss+ (blue circles) and Ss- (red circles)(A); and Post-T Ss+ (blue circles) and Ss- (red circles) (B). The PCA represents the two principal components of variation. (C) Heatmaps depicting the circulating levels of cytokines and chemokines in Ss+ (pre- and post-treatment) and Ss- individuals. Data (and scale) are log10 geometric mean fold change for each of the analytes measured for each of the groups. Plasma levels for Ss+, post treated and Ss- individuals were shown respectively, in which each row stands for a sample and each column stands for a cytokine and chemokines. Red color represents the highest values whereas blue color indicates the lowest values measured for each analyte.

Discussion

During the last few years, several studies have highlighted the important role played by the immune system in regulating metabolic homeostasis in both animal models and human disease [20, 21]. The cross-talk between innate and adaptive immune cell subsets on the one hand and the metabolic cells on the other leads to a complex network governing metabolic functions both at a systemic and tissue specific level [20, 21]. Interestingly, regulatory pathways induced by chronic helminth infections have been associated with reduced insulin resistance and a lower prevalence of metabolic syndrome and T2DM [4, 5, 7, 8, 13, 22], suggesting that helminth-mediated immunomodulation affords a protective effect against metabolic diseases [23].

Elevated levels of pro-inflammatory cytokines have been described in both cross-sectional and prospective studies in T2DM [2426]. Moreover, heightened levels of IL-1β and IL-6 are predictive of T2DM [25, 27]. In addition, other pro-inflammatory cytokines such as IL-1α, IL-12 and IL-18 are linked to pancreatic islet inflammation [9, 28]. IL-23 is known to induce beta cell oxidative and ER stress in diabetic animal models [29], while IL-27 might play a pathogenic role [30], and IL-12 contributes to angiogenesis [31]. Similarly, GM-CSF and G-CSF also contribute to the pathogenesis of inflammation in T2DM [9, 28]. The elevated levels of these pro-inflammatory cytokines in T2DM is thought to reflect the activation of innate immune cells driven by increased nutrient concentrations. The sum total of these effects contributes to glucotoxicity, lipotoxicity, oxidative and ER stress of pancreatic islets in T2DM [10]. Similar to cytokines, a variety of chemokines are also involved in islet inflammation, oxidative and ER stress and dysglycemia. These include CC and CXC chemokines including CCL1, CCL2, CCL3, CCL11, CXCL1, CXCL2, CXCL9, CXCL10 and CXCL11 [9, 28]. Our data highlight a novel feature of helminth–T2DM interaction in demonstrating the depression of circulating levels of all of the cytokines and chemokines mentioned above. Thus, coexistent chronic infection with Ss is associated with a dampened inflammatory cytokine and chemokine response in T2DM. Thus, our study provides a plausible biological mechanism for the observational studies showing a protective effect of helminth infection against T2DM.

While an inverse association has been reported between infection with Schistosoma japonicum and Ss and the prevalence of metabolic syndrome and T2DM, anthelmintic therapy was shown to impair metabolic homeostasis as characterized by increased homeostatic model assessment for insulin resistance (HOMA-IR) and haemoglobin A1c [4, 13, 22]. Our study again offers a plausible biological mechanism for this effect by demonstrating that anthelmintic treatment restores (at least partially) the elevated levels of pro-inflammatory cytokines and chemokines in T2DM. As clearly demonstrated by the PCA and heatmap analysis, anthelmintic treatment alone does not cause a complete reversion to the systemic levels of cytokines and chemokines seen in helminth uninfected T2DM individuals. This is possibly due to the fact that helminth induced immunomodulation might require more time to return to homeostasis.

The limitations of the study include the absence of oral glucose tolerance testing for diabetes, the moderate sample size and the absence of testing for protozoa. Nevertheless, our study offers novel insights into the immunological interactions between helminth infections and metabolic disorders. In summary, our study demonstrates that Ss infection may provide a degree of protection from the pathology associated with T2DM by modulating the surrounding cytokine and chemokine milieu. Our data also suggest that helminth derived molecules or even helminth infection (per se) could offer novel therapeutic approaches to treating inflammatory metabolic diseases.

Acknowledgments

We thank Dr. M. Satiswaran, B. Suganthi and Prabbu Balakrishnan for valuable assistance in collecting the clinical data for this study. We thank N. Pavan Kumar for technical assistance. We thank the staff of the Department of Epidemiology, NIRT, for valuable assistance in recruiting the patients for this study.

Data Availability

All relevant data are within the manuscript and its Supporting Information files.

Funding Statement

This research was supported [in part] by the National Institutes of Health, funded by NCI Contract No. 75N91019D00024, Task Order No. 75N91019F00131. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

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PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0008101.r001

Decision Letter 0

Mathieu Nacher, Maria Victoria Periago

19 Dec 2019

Dear Dr. Babu:

Thank you very much for submitting your manuscript "Helminth infection modulates systemic pro-inflammatory cytokines and chemokines implicated in Type 2 diabetes mellitus pathogenesis" (#PNTD-D-19-01779) for review by PLOS Neglected Tropical Diseases. Your manuscript was fully evaluated at the editorial level and by independent peer reviewers. The reviewers appreciated the attention to an important problem, but raised some substantial concerns about the manuscript as it currently stands. These issues must be addressed before we would be willing to consider a revised version of your study. We cannot, of course, promise publication at that time.

We therefore ask you to modify the manuscript according to the review recommendations before we can consider your manuscript for acceptance. Your revisions should address the specific points made by each reviewer.

When you are ready to resubmit, please be prepared to upload the following:

(1) A letter containing a detailed list of your responses to the review comments and a description of the changes you have made in the manuscript.

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Please provide a short caption, including credits, uploaded as a separate "Other" file. If your image is from someone other than yourself, please ensure that the artist has read and agreed to the terms and conditions of the Creative Commons Attribution License at http://journals.plos.org/plosntds/s/content-license (NOTE: we cannot publish copyrighted images).

(4) If applicable, we encourage you to add a list of accession numbers/ID numbers for genes and proteins mentioned in the text (these should be listed as a paragraph at the end of the manuscript). You can supply accession numbers for any database, so long as the database is publicly accessible and stable. Examples include LocusLink and SwissProt.

(5) To enhance the reproducibility of your results, we recommend that you deposit your laboratory protocols in protocols.io, where a protocol can be assigned its own identifier (DOI) such that it can be cited independently in the future. For instructions see http://journals.plos.org/plosntds/s/submission-guidelines#loc-methods

Please note while forming your response, if your article is accepted, you may have the opportunity to make the peer review history publicly available. The record will include editor decision letters (with reviews) and your responses to reviewer comments. If eligible, we will contact you to opt in or out.

While revising your submission, please upload your figure files to the Preflight Analysis and Conversion Engine (PACE) digital diagnostic tool, https://pacev2.apexcovantage.com/ PACE helps ensure that figures meet PLOS requirements. To use PACE, you must first register as a user. Then, login and navigate to the UPLOAD tab, where you will find detailed instructions on how to use the tool. If you encounter any issues or have any questions when using PACE, please email us at figures@plos.org.

We hope to receive your revised manuscript by Feb 17 2020 11:59PM. If you anticipate any delay in its return, we ask that you let us know the expected resubmission date by replying to this email.

To submit a revision, go to https://www.editorialmanager.com/pntd/ and log in as an Author. You will see a menu item call Submission Needing Revision. You will find your submission record there.

Sincerely,

Mathieu Nacher

Guest Editor

PLOS Neglected Tropical Diseases

Maria Periago

Deputy Editor

PLOS Neglected Tropical Diseases

***********************

Reviewer's Responses to Questions

Key Review Criteria Required for Acceptance?

As you describe the new analyses required for acceptance, please consider the following:

Methods

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

-Is the study design appropriate to address the stated objectives?

-Is the population clearly described and appropriate for the hypothesis being tested?

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

-Were correct statistical analysis used to support conclusions?

-Are there concerns about ethical or regulatory requirements being met?

Reviewer #1: Do the author have data on CRP IL-1Ra? This inflammation markers are very robust and changes would support authors hypothesis

Reviewer #2: The work developed demonstrates that Ss+ individuals exhibited significantly diminished levels of the proinflammatory cytokines and chemokines. Anthelmintic treatment resulted in increased levels of all of the cytokines and chemokines, being a work of great relevance. The same research group published previous work with the same samples studied in: Clin Infect Dis. 2019 Aug 15; 69(4): 697–704. Metabolic Consequences of Concomitant Strongyloides stercoralis Infection in Patients With Type 2 Diabetes Mellitus with equal design and only differentiating in the studied cytokines. I suggest the author submit the article as short communication to show the other data found.

-Are the objectives of the study clearly articulated with a clear testable hypothesis stated? YES

-Is the study design appropriate to address the stated objectives? YES

- Is the population clearly described and appropriate for the hypothesis being tested? NO

- Is the sample size sufficient to ensure adequate power to address the hypothesis being tested? NO

- Were correct statistical analysis used to support conclusions? NO

- -Are there concerns about ethical or regulatory requirements being met? YES

- How was sample calculated? How were participants selected?

- What parasitological method is used? How many samples were analyzed? What other methods were used to exclude other helminths? describe in more detail the methods used.

- The participants with strongyloides had no other helminths? Other studies verify the influence of other helminths and protozoa in dm2, being important to exclude other parasites or to include in the analyzes.

- Was only fasting glucose and HbA1c used to confirm diabetes? Why was the glucose tolerance test not performed? may have samples that are intolerant that they could have failed to include using fasting glucose alone.

- How dm1 and type 2 was differentiated? how can you be sure to be type 2? Clinical signs were considered to differentiate between dm1 and dm2.

- What is the rationale for hematological and other biochemical analyzes of the project? what purpose? This data was not used for anything.

- Justify the statistical analyzes studied at work. why was it used? why no logistic regression was performed to evaluate the effect of strongyloides on dm2

- For the analysis of the comparison of the groups in relation to the dosages, how was the comparison made? using average or median? looking at the figures some analysis seems that the confidence interval overlaps between the groups and would not have significant difference.

- Why was no analysis of clustered cytokines performed? What relationship between them?

Reviewer #3: -Are the objectives of the study clearly articulated with a clear testable hypothesis stated?

YES

-Is the study design appropriate to address the stated objectives?

YES

-Is the population clearly described and appropriate for the hypothesis being tested?

YES

-Is the sample size sufficient to ensure adequate power to address the hypothesis being tested?

YES

-Were correct statistical analysis used to support conclusions?

YES

-Are there concerns about ethical or regulatory requirements being met?

YES

--------------------

Results

-Does the analysis presented match the analysis plan?

-Are the results clearly and completely presented?

-Are the figures (Tables, Images) of sufficient quality for clarity?

Reviewer #1: Figure 3 and 4 are visually not well presented. It would be helpful to see the mean values of pre and post, and may be have different colors for changes going up or down

Reviewer #2: -Does the analysis presented match the analysis plan? NO

- -Are the results clearly and completely presented? NO

- -Are the figures (Tables, Images) of sufficient quality for clarity? YES

Reviewer #3: -Does the analysis presented match the analysis plan?

YES

-Are the results clearly and completely presented?

YES

-Are the figures (Tables, Images) of sufficient quality for clarity?

YES

--------------------

Conclusions

-Are the conclusions supported by the data presented?

-Are the limitations of analysis clearly described?

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

-Is public health relevance addressed?

Reviewer #1: Yes

Reviewer #2: -Are the conclusions supported by the data presented? NO

-Are the limitations of analysis clearly described? NO

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study? YES

-Is public health relevance addressed? NO

Reviewer #3: -Are the conclusions supported by the data presented?

YES, but the author did not measure any anti inflammatory markers

-Are the limitations of analysis clearly described?

NO, the author should add the limitations of thi study

-Do the authors discuss how these data can be helpful to advance our understanding of the topic under study?

YES

-Is public health relevance addressed?

YES, partially.

--------------------

Editorial and Data Presentation Modifications?

Use this section for editorial suggestions as well as relatively minor modifications of existing data that would enhance clarity. If the only modifications needed are minor and/or editorial, you may wish to recommend “Minor Revision” or “Accept”.

Reviewer #1: See above my suggestions which I consider as minor

Reviewer #2: (No Response)

Reviewer #3: Method Section:

For the determination of T2DM status, the author used HbA1c and Random Blood Glucose. If possible, the author should also describe other factors that might affect HbA1c level in the study population eg anemia, etc.

For the measurement of cytokines level, the author should describe whether the measurements were done in paired samples ( SS pos and SS neg side by side for each sample)?

The author should also describe about other factors that might affect inflammatory markers, eg infections, medications, etc -- and whether this has been addressed by excluding those subjects or adjust for these factors in the analysis

--------------------

Summary and General Comments

Use this section to provide overall comments, discuss strengths/weaknesses of the study, novelty, significance, general execution and scholarship. You may also include additional comments for the author, including concerns about dual publication, research ethics, or publication ethics. If requesting major revision, please articulate the new experiments that are needed.

Reviewer #1: This is a very interesting observational study, which may be a starting point for further studies and drug development. The hypothesis is clear, the data are solid and the manuscript is well written. The major limitation is that the study is purely correlative, but it does not take away from its originality.

Reviewer #2: (No Response)

Reviewer #3: This is a well written article. The author describes the fact that helminth infections could modulate systemic pro-inflammatory cytokines and chemokines in newly diagnosed diabetes.

However, several issues need to be addressed.

Major

Why did the author did not measure any anti-inflammatory cytokines or chemokines?

Minor comments

The author should also describe about other factors that might affect inflammatory markers, eg infections, medications, etc -- and whether this has been addressed by excluding those subjects or adjust for these factors in the analysis

For the measurement of cytokines level, the author should describe whether the measurements were done in paired samples ( SS pos and SS neg side by side for each sample)?

For the determination of T2DM status, the author used HbA1c and Random Blood Glucose. If possible, the author should also describe other factors that might affect HbA1c level in the study population eg anemia, etc.

--------------------

PLOS authors have the option to publish the peer review history of their article (what does this mean?). If published, this will include your full peer review and any attached files.

If you choose “no”, your identity will remain anonymous but your review may still be made public.

Do you want your identity to be public for this peer review? For information about this choice, including consent withdrawal, please see our Privacy Policy.

Reviewer #1: Yes: Marc Donath

Reviewer #2: No

Reviewer #3: No

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0008101.r003

Decision Letter 1

Mathieu Nacher, Maria Victoria Periago

29 Jan 2020

Dear Dr. Babu,

We are pleased to inform you that your manuscript 'Helminth infection modulates systemic pro-inflammatory cytokines and chemokines implicated in Type 2 diabetes mellitus pathogenesis' has been provisionally accepted for publication in PLOS Neglected Tropical Diseases.

Before your manuscript can be formally accepted you will need to complete some formatting changes, which you will receive in a follow up email. A member of our team will be in touch within two working days with a set of requests.

Please note that your manuscript will not be scheduled for publication until you have made the required changes, so a swift response is appreciated.

IMPORTANT: The editorial review process is now complete. PLOS will only permit corrections to spelling, formatting or significant scientific errors from this point onwards. Requests for major changes, or any which affect the scientific understanding of your work, will cause delays to the publication date of your manuscript.

Should you, your institution's press office or the journal office choose to press release your paper, you will automatically be opted out of early publication. We ask that you notify us now if you or your institution is planning to press release the article. All press must be co-ordinated with PLOS.

Thank you again for supporting Open Access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Mathieu Nacher

Guest Editor

PLOS Neglected Tropical Diseases

Maria Periago

Deputy Editor

PLOS Neglected Tropical Diseases

***********************************************************

PLoS Negl Trop Dis. doi: 10.1371/journal.pntd.0008101.r004

Acceptance letter

Mathieu Nacher, Maria Victoria Periago

27 Feb 2020

Dear Dr. Babu,

We are delighted to inform you that your manuscript, "Helminth infection modulates systemic pro-inflammatory cytokines and chemokines implicated in Type 2 diabetes mellitus pathogenesis," has been formally accepted for publication in PLOS Neglected Tropical Diseases.

We have now passed your article onto the PLOS Production Department who will complete the rest of the publication process. All authors will receive a confirmation email upon publication.

The corresponding author will soon be receiving a typeset proof for review, to ensure errors have not been introduced during production. Please review the PDF proof of your manuscript carefully, as this is the last chance to correct any scientific or type-setting errors. Please note that major changes, or those which affect the scientific understanding of the work, will likely cause delays to the publication date of your manuscript. Note: Proofs for Front Matter articles (Editorial, Viewpoint, Symposium, Review, etc...) are generated on a different schedule and may not be made available as quickly.

Soon after your final files are uploaded, the early version of your manuscript will be published online unless you opted out of this process. The date of the early version will be your article's publication date. The final article will be published to the same URL, and all versions of the paper will be accessible to readers.

Thank you again for supporting open-access publishing; we are looking forward to publishing your work in PLOS Neglected Tropical Diseases.

Best regards,

Serap Aksoy

Editor-in-Chief

PLOS Neglected Tropical Diseases

Shaden Kamhawi

Editor-in-Chief

PLOS Neglected Tropical Diseases

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    Data Availability Statement

    All relevant data are within the manuscript and its Supporting Information files.


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