900 MHz Electromagnetic Fields Induce Microbiota Dysbiosis and Adaptive Immune System Disorders in Juvenile Rats

doi:10.21203/rs.3.rs-1276651/v1

Download PDF

Research Article

900 MHz Electromagnetic Fields Induce Microbiota Dysbiosis and Adaptive Immune System Disorders in Juvenile Rats

https://doi.org/10.21203/rs.3.rs-1276651/v1

This work is licensed under a CC BY 4.0 License

Version 1

posted

You are reading this latest preprint version

Although cell phones and electronic devices are now integral parts of modern life (especially for young people), the radiofrequency electromagnetic field (RF-EMF) emitted by these devices is a potential health hazard. The effects of RF-EMFs have been assessed in various fields, including epidemiology and neurology. However, there are few published data on the possible effects of RF-EMFs on immune cells; this is surprising, given the importance of the immune system’s role in defending the body against infections and cancer. To assess whether chronic RF-EMF exposure has harmful effects on the immune system in juvenile rats, rats were exposed or not to 900MHz RF-EMF 23h/day during 5 weeks. Hematological, cytometric and bacteriological assays were used to probe differences between exposed and non-exposed tissues. Exposure of rats to 900 MHz RF-EMF was associated with differences in the innate immune system and even more marked in the adaptive immune system. An analysis of the intestinal microbiota revealed dysbiosis, with an over-representation of Enterococcus, Clostridium and Bacteroides spp. Enterococcus was found to have translocated into the spleen in 67% exposed rats. Exposure to a 900 MHz RF-EMF appeared to alter the immune system (and particularly the adaptive immune system) directly or via intestinal dysbiosis.

RF-EMF

chronic exposure

juvenile rat

immune system

The now widespread use of wireless technologies has increased the number of electromagnetic field (EMF) sources in our everyday environment. The most common technology-related EMFs include extremely low frequency (ELF) fields (<60 Hz) and radiofrequency (RF) fields (100 kHz–300 GHz). ELF fields are generated from electrical and electronic appliances, power lines and especially the household alternating current electrical power supply. Devices that emit RFs and microwaves are extensively used in industry (welding machines and induction heaters), telecommunications (TV and radio broadcast stations), medicine (NMR and diathermy), and everyday life (microwave oven and cell phones, now including “fifth generation” (5G) cellular networks). Cell phones emit and receive RFs at ultrahigh frequencies (from 300 MHz to 3 GHz) ^1,2. The International Commission on Non-Ionizing Radiation Protection caps the peak power emitted by cell phones at between 0.1 and 2 watts ³. Some people have accused RF-EMFs (particularly those emitted by cell phones and base stations) of causing sleep disorders, tiredness, headaches, dizziness and/or balance disorders ^4–6. These accusations are subject to debate.

A number of preliminary epidemiologic studies assessed the relationship between EMF exposure (especially cell phone use) and the risk of developing various cancers (especially intracranial tumors)⁷. On the basis of these results, the International Agency of Research of Cancer classified RF-EMFs as possibly carcinogenic in humans (group 2B) ⁸. Since then, further epidemiological studies have confirmed that long-term cell phone use (for more than 10 years) is associated with an increased risk of intracranial tumors ^9,10.

In vivo models are important tools for understanding the effects of RF-EMFs; by limiting external confounding factors, researchers can study the effects of continuous or intermittent exposure in a specific population (e.g. juvenile rats). Some studies of exposure of rodents to 900 MHz fields (the frequency used by most cellphones) evidenced harmful effects on the brain, lymphoid organs, and kidney^11–14, whereas other studies of exposure to the same frequency did not ^15–18.

In vitro cell culture experiments also gave conflicting results; some studies found that neurons, lymphocytes and monocytes were sensitive to EMF exposure, ^19,20 while others found no effects of RF-EMFs on monocytes and epithelial cells²¹.

The impact of RF-EMFs on the rodent immune system is also subject to debate²², and appears to depend strongly on the exposure protocol and the animal’s age. The underlying mechanisms are unclear but might involve histamine release²³ and/or calcineurin inhibition ²⁴. Some studies showed that chronic exposure of growing rats to a 900 MHz RF-EMF was associated with biochemical and oxidative damage to spleen and thymus cells ^11,25. However, other studies of acute or chronic exposure of rodents at 900 MHz did not evidence any changes in lymphocyte populations ^26–28.

The body is vulnerable during early childhood, due to the ongoing development of physiological and neurologic functions²⁹ and the fact that RF-EMFs penetrate further into "juvenile" tissues (including the brain) than into adult tissues ³⁰. Studies of the impact of RF-EMF on juvenile populations are important because young people are intensive users of connected devices ^{31 32,33}. In 2014, Pelletier et al exposed juvenile rats to 900 MHz RF-EMF and described alterations in sleep patterns ³⁴, thermal regulation³⁵, body weight, and food intake ³⁶. The objectives of the present study of juvenile rats were to evaluate (i) the effects of chronic 900 MHz RF-EMF exposure on the innate and adaptive immune systems and the intestinal microbiota ^37–39 (since EMFs reportedly perturb bacterial growth, ^40,41 which might induce gut dysbiosis), and (ii) the impact of any microbiota alterations on the immune system. We evaluated exposed vs. control differences in blood cell counts and (using flow cytometry) adaptive immune cell counts in the blood and lymphoid organs. Bacteria in feces and the spleen were characterized and compared with changes in immune parameters.

RF-EMF exposure induces changes in hematological variables

To assess the impact of RF-EMF exposure on the rat’s immune system, we first measured a number of hematological variables in exposed and control animals (Table 1). The white blood cell (WBC) count was significantly lower in exposed rats than control rats (p=0.0434). The distribution of lymphocyte and neutrophil subsets was also modified. The proportion of neutrophils was significantly greater in the exposed group than in the control group (p=0.0253). In contrast, the proportion of lymphocytes was lower in the exposed group than in the control group (p=0.007). The lymphocyte count was lower in the exposed group than in the control group (p=0.005).

Table 1

**Blood counts** (expressed as the mean ± SEM) in the control group (n=8) and the exposed group (n=9). NS: non-significant, *: p<0.05, **: p<0.01 in a Mann-Whitney test.
Variable	Control	RF-EMF	Intergroup comparison
WBC count (x10⁹/L)	13.17 ± 0.380	9.99 ± 2.299	*
Lymphocytes (%)	70.86 ± 1.371	63.52 ± 2.313	**
Monocytes (%)	6.99 ± 0.299	8.87 ± 1.014	ns
Neutrophils (%)	22.15 ± 1.466	27.57 ± 2.087	*
Lymphocyte count (x10⁹/L)	9.92 ± 0.147	6.93 ± 1.161	**
Monocyte count (*10⁹/L)	0.81 ± 0.108	1.03 ± 0.206	ns
Neutrophil count (x10⁹/L)	2.57 ± 0.374	3.594 ± 0.892	ns

RF-EMF exposure induces changes of B lymphocyte populations and IgG levels.

We used flow cytometry to analyze B lymphocyte subsets in the peripheral blood and the spleen of exposed and control rats (Fig. 1). In the blood, no significant intergroup differences were observed in the B-cell subsets, except for a higher absolute IgG1+ B lymphocyte count (p=0.009) in exposed rats than in control rats (Fig. 1A-B). In the spleen, the proportion of mature B lymphocytes was similar in the two groups (Fig. 1C). However, the proportion of IgG1+ B lymphocytes in exposed rats was higher than in controls (p=0.002). The proportion of memory B lymphocytes in spleen was significantly lower in exposed rats than controls (p=0.001) (Fig. 1C).

We measured the levels of Ig produced by B lymphocytes in the serum of exposed and control rats (Fig. 2). We observed significantly lower proportions of IgG1 (p=0.019) and IgG2c (p=0.003) in exposed rats compared to control. Taken as a whole, these data demonstrate that RF-EMF exposure induces an alteration of immune cells in the peripheral blood and impacts humoral immune response.

RF-EMF exposure induces major changes in T lymphocyte subsets

Both the proportion of T lymphocytes (CD45+ CD3+) and the absolute count in the blood were significantly lower in RF-EMF-exposed animals than in control animals (Fig. 3A, p=0.0012 and p=0.037 respectively). Although the percentages of helper (CD4+) T lymphocytes and cytotoxic (CD8+) T lymphocytes were similar, the absolute counts for these subsets were significantly lower in exposed rats than in control rats (Fig. 3B; p=0.008 (CD4+) and p=0.012 (CD8+), respectively).

As with our observations in the peripheral blood, the proportions of splenic total T lymphocytes (p=0.019) and CD4+ T lymphocytes (p=0.049) were also significantly lower in exposed rats than in control rats (Fig. 3C).

In the thymus, the proportion of total T lymphocytes was similar in the exposed and control groups (Fig. 3D). However, the CD4+ single-positive thymocyte count (but not the CD8+ single-positive thymocyte count) was significantly higher in the exposed group (p=0.031). The double-positive (CD4+/CD8+) thymocyte count was significantly lower in exposed rats (p=0.010; Fig. 3D). The thymic T lymphocyte precursor (CD4-/CD8-) count was also significantly higher in exposed rats than in control rats (p=0.033, Fig. 3D).

RF-EMF exposure induces changes in the composition of intestinal microbiota, together with dysbiosis.

To further characterize the immune changes observed in exposed rats, we analyzed the intestinal microbiota. The exposed and control groups differed significantly with regard to the microbial counts in the colon tissue (expressed in log CFU/g colon tissue) (Fig. 4). In the colon tissue, the beneficial microbiota was similar in exposed and control rats. In contrast, the pathogenic microbiota was significantly elevated in exposed rats, relative to control rats (Fig. 4A; p=0.024). The difference between the number of beneficial bacteria and the number of pathogenic bacteria was statistically significant in the exposed group (Fig. 4A; p=0.005) but not in the control group (p=0.79). Using conventional bacterial cultures, we identified five genera (Enterococcus, Enterobacteria, Staphylococcus, Clostridium and Bacteroides) in exposed or control rats. In exposed rats, we observed significantly higher counts of Enterococcus (p=0.011), Clostridium (p=0.002) and Bacteroides (p=0.041) (Fig. 4B), and significant translocation of Enterococcus to the spleen (Fig. 4C; p=0.001). These data demonstrate that RF-EMF exposure was associated with intestinal dysbiosis.

The Enterococcus count in the gut is correlated with immune changes

We next probed correlations between changes in the microbiota and changes in immune variables in the exposed and control groups. Significant correlations were only observed in the exposed group (Fig. 5). The Enterococcus count was negatively correlated with the total T lymphocyte count (Fig. 5A., p=0.046) and the helper T lymphocyte count (Fig. 5B; p=0.004) in blood. There were no other correlations with blood T lymphocyte subset counts (data not shown). In the spleen, the proportion of memory B lymphocytes was positively correlated with the Enterococcus count (Fig. 5C, p=0.028).

Over the last few years, the use of RF-EMF-emitting devices (including cell phones, wi-fi devices, and satellite communication systems) has increased markedly – especially among young people. These devices are ubiquitous in everyday life (at home, at school, in public transportation, in the street, etc.) and thus continuously expose us to RF-EMFs. To model the chronic exposure of young organisms, we exposed juvenile rats to a 900 MHz RF-EMF for 23 h/day over a 5-week period (as did Pelletier et al. ³⁴) and analyzed the exposure’s impact on the immune system and the intestinal microbiota.

Although the first research data on the effects of RF-EMF were published over 20 years ago, there is still no consensus on the best model of exposure. Firstly, wireless technologies and thus exposure variables are changing constantly. Secondly, the intensity of RF-EMF exposure is not always clearly established. Some studies have attempted to quantify the intensity of EMFs present in the environment ^42–44. This variable might fluctuate markedly as a function of the geographical area and the number of connected devices close to the individual. In everyday life, the EMF intensity varies; however, the intensity had to be fixed in the present study.

Our results showed that the exposure of rats to an RF-EMF was associated with a lower WBC count, a lower total lymphocyte count, and a higher proportion of neutrophils in the peripheral blood. Similar changes in hematological variables had been observed in a study of juvenile rats exposed to 915 MHz frequencies for 8 h/day over a 2-week period ⁴⁵. In contrast to the results for short exposures⁴⁸, our data suggest that longer exposure to RF-EMF induces an alteration in the immune system in general and in the adaptive immune system in particular. Indeed, we observed differences in some B lymphocyte subsets (IgG1⁺ B lymphocytes and memory B lymphocytes) and in T lymphocyte populations in blood, spleen, and thymus. Modifications in the secretion of Igs into the blood of exposed vs. controls rats reflect a profound change in the adaptive immune system. The present study is the first to have observed this phenomenon.

A study of rats exposed to 900 MHz RF-EMF for 2h/day over a 45-day period highlighted the presence of oxidative stress in secondary lymphoid organs ²⁵. The low lymphocyte counts in the exposed rats in our study might be explained by more frequent apoptosis; it has been shown that 900 MHz RF-EMF induces apoptosis through the mitochondrial pathway via a reactive-oxygen-species- and caspase-3-dependent mechanism ^13,46.

Our analysis of the gut microbiota revealed dysbiosis in rats exposed to RF-EMF. This was characterized by elevated Enterococcus, Clostridium and Bacteroides counts in the gut tissue. Furthermore, Enterococcus had translocated into the spleen in 67% of the exposed rats and only 25% of the control rats.

These bacteria have already been identified in the literature as having an effect on the immune system. Clostridium was associated with food allergies ^47,48, inducing an accumulation of intestinal T regulatory lymphocytes (Tregs) able to inhibit allergic inflammation ⁴⁹ and metabolize short-chain fatty acids; this can have systemic anti-inflammatory effects and influence dendritic cell and T-cell responses ⁵⁰. The bacterium Bacteroides fragilis drives the differentiation of IL-10–secreting Tregs by producing an unusual capsular polysaccharide A. Daillère et al. have demonstrated immunomodulatory effects of Enterococcus hirae during cyclophosphamide therapy. This bacterium was associated with changes in the tumor microenvironment, a low Treg count, and the stimulation of cognate antitumor cytotoxic T lymphocyte responses ⁵¹.

Our results showed that high Enterococcus counts in the gut tissue were correlated with low total T lymphocyte and CD4+ T lymphocyte counts in the blood of exposed rats. However, our present model did not able us to determine which mechanisms are involved. We hypothesize that the immune deregulations observed in peripheral blood and secondary lymphoid organs are caused (at least in part) by the intestinal dysbiosis. To explore this hypothesis and thus determine whether RF-EMFs have direct and/or indirect effects on the immune system, it would be interesting to exposure germ-free mice. This type of research would make it possible to more specifically target lymphocyte subsets (such as Th17 cells, Treg and innate immune cells) not studied in the present work.

This rat model of chronic exposure to RF-EMF demonstrated the dysregulatory effect of an RF-EMF on the immune system, and particularly an indirect effect through dysbiosis. The adaptive immune system appeared to be affected by the RF-EMF exposure, with major changes in B and T lymphocyte subsets in the blood and in secondary lymphoid organs.

Animals

All animal experiments were approved by the local animal care and use committee and by the French Ministry of Research (registration number: APAFIS 3735-2016012017118094). Experiments were conducted on 17 male Wistar rats (Janvier Labs, Le Genest Saint Isle, France) weighing between 55 and 85 g and aged 3 weeks at the time of their arrival in our animal facility. The RF-EMF-exposed and control (non-exposed) groups comprised 9 and 8 animals, respectively. Each group was housed in a separate anechoic chamber with a 12 hr:12 hr dark/light cycle and controlled thermoneutral air temperature (24 ± 1°C), relative air humidity (mean ± standard deviation (SD): 39±12%) and air velocity (<0.2 m/s). Rats were housed individually in plastic cages (425 mm x 266 mm x 185 mm) within the anechoic chamber. Standard chow (3436EXF12, Serlab, Montataire, France) and drinking water were available ad libitum.

RF-EMF exposure

The RF-EMF exposure protocol was the same as that used by Bosquillon de Jenlis et al. ³⁶. After 4 days of acclimatization, the RF-EMF exposure (23 hours per day, over a 5-week period) was initiated. The climatic chambers were equipped with RF-EMF antennae powered by a generator (model RFS 900–64, RFPA, Artigues-près-Bordeaux, France) emitting a continuous-wave 900 MHz EMF. Antennae (model 800–10465, KATHREIN-Werke KG, Rosenheim, Germany) were placed horizontally in the climatic chamber, 80 cm above the exposed rats’ boxes. The generator’s power was set to obtain a field intensity of 1.8 V/m. The animals’ estimated specific absorption rate was 30 mW/kg. The dose of RF-EMF exposure was checked with a radiofrequency dosimeter (PMM EP600, Narda Safety Test Solutions, Hauppauge, NY) and monitor on computer software (Win EP 600, Narda Safety Test Solutions). To allow animal care, the generator was turned off for one hour a day.

Exposure, sacrifice, and sample collection

After 5 weeks of RF-EMF exposure, the rats were sacrificed by heart puncture under isofluorane 2.5% anesthesia (Iso-Vet 1000 mg/g, Piramal Healthcare UK Ltd, Morpeth, United Kingdom; airflow: 1 L/min). The blood from the heart puncture was collected. Parts of the spleen and thymus were collected postmortem and placed in phosphate buffer saline (PBS, Corning, New York, NY, USA). Splenic or thymic cells were dissociated with the gentleMACS^TM Octo Dissociatior (Miltenyi Biotec, Bergisch Gladbach, Germany), using a spleen program. The samples were passed through a 100 µm sieve and then frozen at -150°C in a solution composed of 9:1 v/v fetal bovine serum (FBS): dimethylsulfoxide (DMSO).

Microbiological analyses

Culture methods

All sample preparation steps (collection, centrifugation, dilution, and inoculation into culture media) were performed on the same day for anaerobe and aerobe assays. Anaerobic conditions were applied first; to protect the anaerobic bacteria, all steps were performed as quickly as possible.

After weighing, thawed sample of intestine and other organs were mashed in an equal weight of cysteine broth and homogenized in a sterile blender in order to maintain adherent bacteria. Next, 1 mL samples of organ homogenate (intestine and organs) were diluted and plated on various selective and non-selective media for qualitative and quantitative cultures of aerobic and anaerobic microbiota (100 µL of diluted medium per plate). Standard microbiological techniques and media were used, as described elsewhere ^{52 53}. All aerobic culture plates were incubated at 37°C for 48 h. All anaerobic culture plates were incubated in an anaerobic chamber (Bactron Anaerobic, Sheldon Manufacturing, Cornelius, OR, USA) and examined after 4 days of incubation at 37°C. The culture plates were evaluated by a researcher who was blinded to the samples’ group assignment. Isolated colonies grown on Petri dishes were counted using an automatic colony counter (Scan® 500, INTERSCIENCE, Saint-Nom-la-Bretèche, France) and expressed as log¹⁰ colony-forming units per gram of tissue (log(CFU)/g).

After macroscopic and microscopic observations (Gram staining procedures), biochemical assays were performed. A number of specific chromogenic media were also used. Again, the results were read by a researcher who was blinded to the samples’ group assignment.

Bacterial translocation to the spleen

The spleen was removed for the culture of translocated organisms. Bacteria were counted and identified according to their characteristic colonies and microscopic features and by using matrix-assisted laser desorption ionization time-of-flight mass spectroscopy (as described by Joly et al. ⁵⁴) under aseptic conditions. Thawed tissue samples were placed in sterile, preweighed glass containers. On the day of inoculation, organs were weighed, placed in sterile lab blender bags, and then homogenized in Ringer’s saline solution (Bio-Rad, Marnes-la-Coquette, France). Lastly, plates were inoculated with the resulting homogenate. The conventional media have been described elsewhere ⁵³. After incubation, bacteria were identified and counted using standard microbiological techniques by a researcher who was blinded to the samples’ group assignment ⁵². The lactobacilli and bifidobacterial were considered to be beneficial microbes, whereas enterococci, enterobacteria, clostridia, Bacteroides and staphylococci were considered to be pathogenic.

Data acquisition and analysis

Blood analyses

On the day after sacrifice, a complete blood count was determined on a KT-6400 analyzer (Genrui Biotech Inc., Shenzhen, China). Next, peripheral blood mononuclear cells (PBMCs) from non-exposed or exposed animals were separated using gradient separation in Ficoll Pacques Plus© (GE-Healthcare, Little Chalfont, United Kingdom). The top Ficoll phase (i.e. the plasma sample) was frozen at -150°C. The PBMC band was collected, washed in PBS, pelleted at 300 x g, and then frozen at – 150°C in a solution composed of 9:1 v/v FBS:DMSO.

Flow cytometry analyses

Single-cell suspensions prepared from the spleen, thymus or PBMCs were thawed in RPMI (Roswell Park Memorial Institute) medium (PAN-Biotech, Aidenbach, Germany) supplemented with 10% FBS (Eurobio, Courtaboeuf, France), 2 mM L-glutamine (Sigma Aldrich, Saint-Louis, Missouri, USA) and 10 U/mL penicillin-streptomycin (Sigma Aldrich) for three hours. The cells were then stained with fluorochrome-conjugated antibodies (Abs). The following Abs were used for flow cytometry experiments: PE-anti-rat-CD3 (clone REA223), APC-anti-rat-CD4 (clone REA482), FITC-anti-CD8a (clone REA437), FITC-anti-rat-immunoglobulin (Ig)M (clone ES26-13D3.4), APC-anti-rat-CD45R (clone REA450), APCVio770-anti-rat-CD45 (clone REA504), FITC-anti-rat-CD161 (clone REA227), APC, anti-rat-IgG1 (clone RG11/39.2) (Miltenyi Biotec). Lymphoid cell populations were analyzed after gating (1 x 10⁵ viable cells), according to their forward scatter and side scatter. B lymphocytes (CD45+/CD3-/CD45R+), active B lymphocytes (CD45+/CD3-/IgG1+), immature B lymphocytes (CD45+/CD3-/IgM+), switched B lymphocytes (CD45+/CD3-/IgG1+), memory B lymphocytes (CD45+/CD3-/CD45R+/CD27+), T lymphocytes (CD45+/CD3+), helper T lymphocytes (CD45+/CD3+/CD4+CD8a-) and cytotoxic T lymphocytes (CD45+/CD3+/CD4-CD8a+) subset were detected according to a previously described gating strategy ^55–57. All sample were acquired using a MACSQuantify (Miltenyi Biotec). The flow cytometry data were analyzed using FlowJo software (version 10.2).

Serum analyses

Immunoglobulin concentrations in plasma samples were determined using an Antibody Isotyping 6-Plex Rat ProcartaPlex© assay (Invitrogen, Carlsbad, CA). Plasma samples were first diluted 4000-fold, as recommended by the manufacturer. Bead immunoassay results were read on a MagPix Milliplex Map system (Merck, Fontenay-sous-Bois, France) and analyzed with ProcartaPlex© Analysis software (Invitrogen).

Statistical analyses

The normality of the data distribution was checked with the Agostino-Pearson test. In order to compare control and exposed groups and probe correlations between the two, we applied Mann Whitney, Wilcoxon, chi-squared and Pearson’s r tests, as appropriate (see the figure legends). Statistical analyses were performed with GraphPad Prism software (version 8.4.0, GraphPad Software, San Diego, CA, USA). Quantitative variables were expressed as the median (range) in the figures and as the mean ± SEM in the table. The threshold for statistical significance was set to p<0.05.

Acknowledgments

We thank Ludovic Didier (Head of the PlatAnN facility, Université de Picardie Jules Verne, Amiens, France) for assistance with animal experiments, and Luciane Zabijak (at the ICAP facility, Université de Picardie Jules Verne, Amiens, France) for assistance with cell analyses.

Author Contributions

J-P.M., L.C., A.P. contributed to the design of the study. A.B.D.J. helped with A.C. and S.D. in conducting of the in vivo study. L.C., H.O-H. performed hematological and cytometric experiments. N.D. and H.K-C. performed microbiological experiments. H.G., L.C., M.N. and J-P.M. analyzed the data. M.N. and L.C. wrote the manuscript. L.G., H.K-C., V.B., A.P. and J-P.M. critically evaluated the results and enhanced the manuscript.

Breckenkamp, J., Berg, G. & Blettner, M. Biological effects on human health due to radiofrequency/microwave exposure: a synopsis of cohort studies. Radiat. Environ. Biophys. 42, 141–154 (2003).
Moradi, M., Naghdi, N., Hemmati, H., Asadi-Samani, M. & Bahmani, M. Effect of Ultra High Frequency Mobile Phone Radiation on Human Health. Electron. Physician 8, 2452–2457 (2016).
International Commission on Non-Ionizing Radiation Protection. ICNIRP statement on the ‘Guidelines for limiting exposure to time-varying electric, magnetic, and electromagnetic fields (up to 300 GHz)’. Health Phys. 97, 257–258 (2009).
Johansson, O. Electrohypersensitivity: a functional impairment due to an inaccessible environment. Rev. Environ. Health 30, 311–321 (2015).
Leitgeb, N. & Schröttner, J. Electrosensibility and electromagnetic hypersensitivity. Bioelectromagnetics 24, 387–394 (2003).
Seitz, H., Stinner, D., Eikmann, T., Herr, C. & Röösli, M. Electromagnetic hypersensitivity (EHS) and subjective health complaints associated with electromagnetic fields of mobile phone communication--a literature review published between 2000 and 2004. Sci. Total Environ. 349, 45–55 (2005).
Hardell, L. World Health Organization, radiofrequency radiation and health - a hard nut to crack (Review). Int. J. Oncol. 51, 405–413 (2017).
International Agency for Research on Cancer (Lyon, France). International Agency for Research on Cancer (Lyon, France). Press Realease 1–6 (2011).
Bortkiewicz, A., Gadzicka, E. & Szymczak, W. Mobile phone use and risk for intracranial tumors and salivary gland tumors – A meta-analysis. Int. J. Occup. Med. Environ. Health 30, 27–43 (2017).
Momoli, F. et al. Probabilistic Multiple-Bias Modeling Applied to the Canadian Data From the Interphone Study of Mobile Phone Use and Risk of Glioma, Meningioma, Acoustic Neuroma, and Parotid Gland Tumors. Am. J. Epidemiol. 186, 885–893 (2017).
Aydin, B. & Akar, A. Effects of a 900-MHz Electromagnetic Field on Oxidative Stress Parameters in Rat Lymphoid Organs, Polymorphonuclear Leukocytes and Plasma. Arch. Med. Res. 42, 261–267 (2011).
Fragopoulou, A. F. et al. Whole body exposure with GSM 900MHz affects spatial memory in mice. Pathophysiol. Off. J. Int. Soc. Pathophysiol. 17, 179–187 (2010).
Mercantepe, T., Tümkaya, L., Gökçe, M. F., Topal, Z. S. & Esmer, E. Effect of 900-MHz Electromagnetic Field on the Cerebellum: A Histopathological Investigation. Sisli Etfal Hastan. Tip Bul. 52, 129–134 (2018).
Okatan, D. Ö. et al. Continuous 900-megahertz electromagnetic field applied in middle and late-adolescence causes qualitative and quantitative changes in the ovarian morphology, tissue and blood biochemistry of the rat. Int. J. Radiat. Biol. 94, 186–198 (2018).
Galloni, P. et al. Effects of 900 MHz electromagnetic fields exposure on cochlear cells’ functionality in rats: Evaluation of distortion product otoacoustic emissions. Bioelectromagnetics 26, 536–547 (2005).
Jin, Y. B. et al. Effects of simultaneous combined exposure to CDMA and WCDMA electromagnetic field on immune functions in rats. Int. J. Radiat. Biol. 88, 814–821 (2012).
Nasta, F. et al. Effects of GSM-modulated radiofrequency electromagnetic fields on B-cell peripheral differentiation and antibody production. Radiat. Res. 165, 664–670 (2006).
Petitdant, N. et al. Alteration of adaptive behaviors of progeny after maternal mobile phone exposure. Environ. Sci. Pollut. Res. 25, 10894–10903 (2018).
Del Vecchio, G. et al. Continuous exposure to 900MHz GSM-modulated EMF alters morphological maturation of neural cells. Neurosci. Lett. 455, 173–177 (2009).
Szymański, Ł. et al. Immunotropic effects in cultured human blood mononuclear cells exposed to a 900 MHz pulse-modulated microwave field. J. Radiat. Res. (Tokyo) 61, 27–33 (2020).
Bouwens, M. et al. Low-frequency electromagnetic fields do not alter responses of inflammatory genes and proteins in human monocytes and immune cell lines. Bioelectromagnetics 33, 226–237 (2012).
Ohtani, S. et al. The effects of radio-frequency electromagnetic fields on T cell function during development. J. Radiat. Res. (Tokyo) 56, 467–474 (2015).
Gangi, S. & Johansson, O. A theoretical model based upon mast cells and histamine to explain the recently proclaimed sensitivity to electric and/or magnetic fields in humans. Med. Hypotheses 54, 663–671 (2000).
Doyon, P. R. & Johansson, O. Electromagnetic fields may act via calcineurin inhibition to suppress immunity, thereby increasing risk for opportunistic infection: Conceivable mechanisms of action. Med. Hypotheses 106, 71–87 (2017).
Hancı, H. et al. Can prenatal exposure to a 900 MHz electromagnetic field affect the morphology of the spleen and thymus, and alter biomarkers of oxidative damage in 21-day-old male rats? Biotech. Histochem. Off. Publ. Biol. Stain Comm. 90, 535–543 (2015).
Gatta, L. et al. Effects of in vivo exposure to GSM-modulated 900 MHz radiation on mouse peripheral lymphocytes. Radiat. Res. 160, 600–605 (2003).
Laudisi, F. et al. Prenatal exposure to radiofrequencies: effects of WiFi signals on thymocyte development and peripheral T cell compartment in an animal model. Bioelectromagnetics 33, 652–661 (2012).
Prisco, M. G. et al. Effects of GSM-Modulated Radiofrequency Electromagnetic Fields on Mouse Bone Marrow Cells. Radiat. Res. 170, 803–810 (2008).
Rice, D. & Barone, S. Critical periods of vulnerability for the developing nervous system: evidence from humans and animal models. Environ. Health Perspect. 108<bvertical-align:super;> </bvertical-align:super;><background-color:#C8BE84;bvertical-align:super;>Suppl 3</background-color:#C8BE84;bvertical-align:super;>, 511–533 (2000).
Wiart, J., Hadjem, A., Varsier, N. & Conil, E. Numerical dosimetry dedicated to children RF exposure. Prog. Biophys. Mol. Biol. 107, 421–427 (2011).
The Common Sense Census: Media Use by Kids Age Zero to Eight, 2017. https://www.commonsensemedia.org/research/the-common-sense-census-media-use-by-kids-age-zero-to-eight-2020.
Kabali, H. K. et al. Exposure and Use of Mobile Media Devices by Young Children. Pediatrics 136, 1044–1050 (2015).
Kılıç, A. O. et al. Exposure to and use of mobile devices in children aged 1–60 months. Eur. J. Pediatr. 178, 221–227 (2019).
Pelletier, A. et al. Effects of chronic exposure to radiofrequency electromagnetic fields on energy balance in developing rats. Environ. Sci. Pollut. Res. 20, 2735–2746 (2013).
Pelletier, A. et al. Does Exposure to a Radiofrequency Electromagnetic Field Modify Thermal Preference in Juvenile Rats? PLOS ONE 9, e99007 (2014).
Bosquillon de Jenlis, A., Del Vecchio, F., Delanaud, S., Bach, V. & Pelletier, A. Effects of co-exposure to 900 MHz radiofrequency electromagnetic fields and high-level noise on sleep, weight, and food intake parameters in juvenile rats. Environ. Pollut. 256, 113461 (2020).
Levy, M., Blacher, E. & Elinav, E. Microbiome, metabolites and host immunity. Curr. Opin. Microbiol. 35, 8–15 (2017).
Sherwani, M. A., Tufail, S., Muzaffar, A. F. & Yusuf, N. The skin microbiome and immune system: Potential target for chemoprevention? Photodermatol. Photoimmunol. Photomed. 34, 25–34 (2018).
Jiao, Y., Wu, L., Huntington, N. D. & Zhang, X. Crosstalk Between Gut Microbiota and Innate Immunity and Its Implication in Autoimmune Diseases. Front. Immunol. 11, 282 (2020).
Al-Harbi, F. F. et al. Nonthermal control of Escherichia coli growth using extremely low frequency electromagnetic (ELF-EM) waves. Biomed. Mater. Eng. 29, 809–820 (2018).
Crabtree, D. P. E., Herrera, B. J. & Kang, S. The response of human bacteria to static magnetic field and radiofrequency electromagnetic field. J. Microbiol. Seoul Korea 55, 809–815 (2017).
Ramirez-Vazquez, R., Gonzalez-Rubio, J., Arribas, E. & Najera, A. Personal RF-EMF exposure from mobile phone base stations during temporary events. Environ. Res. 175, 266–273 (2019).
Waldmann-Selsam, C., Balmori-de la Puente, A., Breunig, H. & Balmori, A. Radiofrequency radiation injures trees around mobile phone base stations. Sci. Total Environ. 572, 554–569 (2016).
Wall, S., Wang, Z.-M., Kendig, T., Dobraca, D. & Lipsett, M. Real-world cell phone radiofrequency electromagnetic field exposures. Environ. Res. 171, 581–592 (2019).
Kim, H. S. et al. Effects of exposure to electromagnetic field from 915 MHz radiofrequency identification system on circulating blood cells in the healthy adult rat. Bioelectromagnetics 39, 68–76 (2018).
Lu, Y.-S., Huang, B.-T. & Huang, Y.-X. Reactive Oxygen Species Formation and Apoptosis in Human Peripheral Blood Mononuclear Cell Induced by 900 MHz Mobile Phone Radiation. Oxidative Medicine and Cellular Longevity vol. 2012 e740280 https://www.hindawi.com/journals/omcl/2012/740280/ (2012).
Chen, C.-C., Chen, K.-J., Kong, M.-S., Chang, H.-J. & Huang, J.-L. Alterations in the gut microbiotas of children with food sensitization in early life. Pediatr. Allergy Immunol. Off. Publ. Eur. Soc. Pediatr. Allergy Immunol. 27, 254–262 (2016).
Ling, Z. et al. Altered fecal microbiota composition associated with food allergy in infants. Appl. Environ. Microbiol. 80, 2546–2554 (2014).
Nagano, Y., Itoh, K. & Honda, K. The induction of Treg cells by gut-indigenous Clostridium. Curr. Opin. Immunol. 24, 392–397 (2012).
Fyhrquist, N. The Human Microbiota and Its Relationship with Allergies. Gastroenterol. Clin. North Am. 48, 377–387 (2019).
Daillère, R. et al. Enterococcus hirae and Barnesiella intestinihominis Facilitate Cyclophosphamide-Induced Therapeutic Immunomodulatory Effects. Immunity 45, 931–943 (2016).
Lennette, E. H. & American Society for Microbiology. Manual of clinical microbiology. (American Society for Microbiology, 1985).
Reygner, J. et al. Inulin Supplementation Lowered the Metabolic Defects of Prolonged Exposure to Chlorpyrifos from Gestation to Young Adult Stage in Offspring Rats. PloS One 11, e0164614 (2016).
Joly Condette, C. et al. Use of molecular typing to investigate bacterial translocation from the intestinal tract of chlorpyrifos-exposed rats. Gut Pathog. 8, 50 (2016).
Barnett-Vanes, A., Sharrock, A., Birrell, M. A. & Rankin, S. A Single 9-Colour Flow Cytometric Method to Characterise Major Leukocyte Populations in the Rat: Validation in a Model of LPS-Induced Pulmonary Inflammation. PloS One 11, e0142520 (2016).
Han, Y., Jin, Y., Miao, Y., Shi, T. & Lin, X. Improved RANKL expression and osteoclastogenesis induction of CD27+CD38- memory B cells: A link between B cells and alveolar bone damage in periodontitis. J. Periodontal Res. 54, 73–80 (2019).
Chen, J. et al. The ginsenoside metabolite compound K exerts its anti-inflammatory activity by downregulating memory B cell in adjuvant-induced arthritis. Pharm. Biol. 54, 1280–1288 (2016).

No competing interests reported.

Download PDF

Version 1

posted

You are reading this latest preprint version

900 MHz Electromagnetic Fields Induce Microbiota Dysbiosis and Adaptive Immune System Disorders in Juvenile Rats

Status:

Version 1

Abstract

Figures

Introduction

Results

RF-EMF exposure induces changes in hematological variables

RF-EMF exposure induces major changes in T lymphocyte subsets

Discussion

Material And Methods

Declarations

References

Additional Declarations

Status:

Version 1