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Some natural hypomethylating agents in food, water and environment are against distribution and risks of COVID-19 pandemic: Results of a big-data research

Objective: This study analyzes the effects of lifestyle, nutrition, and diets on the status and risks of apparent (symptomatic) COVID-19 infection in Iranian families. Materials and Methods: A relatively extensive questionnaire survey was conducted on more than 20,000 Iranian families (residing in more than 1000 different urban and rural areas in the Islamic Republic of Iran) to collect the big data of COVID-19 and develop a lifestyle dataset. The collected big data included the records of lifestyle effects (e.g. nutrition, water consumption resources, physical exercise, smoking, age, gender, health and disease factors, etc.) on the status of COVID-19 infection in families (i.e. residents of homes). Therefore, an online self-reported questionnaire was used in this retrospective observational study to analyze the effects of lifestyle factors on the COVID-19 risks. The data collection process spanned from May 10, 2020 to March 19, 2021 by selecting 132 samples from more than 40 different social network communities. Results: The research results revealed that food and water sources, which contain some natural hypomethylating agents, mitigated the risks of apparent (symptomatic) COVID-19 infection. Furthermore, the computations on billions of permutations of nutrition conditions and dietary regime items, based on the data collected from people’s diets and infection status, showed that there were many dietary conditions alleviating the risks of apparent (symptomatic) COVID-19 infection by 90%. However, some other diets tripled the infection risk. Conclusion: Some natural hypomethylating agents in food, water, and environmental resources are against the spread and risks of COVID-19.


Introduction
Since World War II, the COVID-19 pandemic has been the most catastrophic event worldwide. Many researchers are trying to solve the multifaceted complex aspects of this pandemic. Lifestyle (and its effects on the risks of a pandemic) is among these aspects (Mutch, 2020).
Researchers argue that there are some lifestyle and dietary factors that can affect the risks of SARS-CoV-2 infection such as physical activities, a current habit of smoking, a former habit of smoking, intake of vitamins (e.g. D, A, K, B and E), intake of micronutrients (e.g. zinc, magnesium, copper, and ferritin), natural bioactive antiviral chemicals (e.g. emodin and curcumin), and natural antimicrobial and anti-inflammation foods (e.g. natural honey, pepper, garlic, and ginger) (Calder, 2020;Siahpoosh, 2020).
An online self-reported questionnaire was used in this retrospective observational study to analyze the effects of lifestyle factors on COVID-19 risks. The big data and numerical method help address the problem accurately (according to the precision medicine and other modern approaches). The relative risk of each factor was determined separately and comparatively. After that, the combination risks of dietary factors (i.e. different dietary conditions and regimes) were determined.
The research results show that lifestyle and nutrition factors had relatively significant impacts on the risks of the apparent (symptomatic) COVID-19 infection. In particular, some natural hypomethylating agents (El-Hussein et al., 2018) in food, water, and environmental resources are against the spread and risks of the COVID-19 pandemic.

Materials and Methods
A relatively extensive questionnaire survey was conducted on more than 20,000 Iranian families (residing in more than 1000 different urban and rural areas in the IRI) to collect big data on COVID-19 and create a lifestyle dataset (with more than 1M data records and more than 1G items obtained from the semantic entailment rules). The collected big data included records regarding the lifestyle effects (e.g. nutrition, water consumption resources, physical activities, smoking habits, age, gender, health and disease factors, and many other items) on the status of the COVID-19 infection in families (i.e. residents of homes).

Sampling and participants
An online self-reported questionnaire was designed in this retrospective observational study to inquire about the status of family members considering COVID-19. The infection status was diagnosed as "non-infection", "suspected infection", "definitive/apparent infection", and "SARS-CoV-2 death". To view the questionnaire and all of its items, you can refer to it (Besharati, 2020).
In three different phases during the first, second, and third COVID-19 peaks in Iran in spring, summer, autumn and winter of (2020-2021), self-reported data regarding lifestyle and COVID-19 were collected from more than 20,000 Iranian families living in more than 1000 urban and rural areas. The data collection process spanned from May 10, 2020 to March 19, 2021 by selecting 132 samples from more than 40 different social network communities (i.e. channels with aggregately more than one million subscribers).
The results include a large body of data pertaining to the lifestyle and COVID-19 with more than one million data records and more than two billion information records.

Findings about natural hypomethylating agents
According to the research results, some of them are provided in Tables 1, 2, and 3,  food and water resources which contain  some natural hypomethylating agents can  mitigate the risk of the apparent COVID-19 infection. They can be introduced as  below: 1-Some phytochemicals such as curcumin (found richly in turmeric) and trigonelline (found richly in coffee, fenugreek seed, and in lower concentrations, in fruits, vegetables, and natural honey). In addition to their hypomethylating effects, these natural bioactive phytochemicals act as antioxidative and anti-inflammatory agents; therefore, they can resist against the oxidative stress and cytokine storm which play major roles in severe phases of COVID-19 infection (e.g. lung injuries, Internal bleeding, etc.).
4-Islamic fasting for some consecutive days, which had hypomethylating and antiinflammatory effects (Mindikoglu et al., 2020) and in our data, it was observed to mitigate the risk of the apparent COVID-19 infection. 5-Natural honey and its bioactive material.
7-Different types of coffee, especially the intense Arabic coffee, and any sources of trigonelline (Note: some countries with very high and intense consumption rates of coffee (e.g. Laos, Luxembourg, Qatar, and Oman) have had very low rates of fatality in the COVID-19 pandemic). There is a correlation between coffee consumption and reduced rate of fatality in the countries with coffee consumption rates of more than 5 kg per capita; Figure 1). 8-The grape syrup and fruit roll-ups, fruit leather, and any sources of trigonelline and diverse alkaloids. 9-Some types of tea and any sources of diverse alkaloids.
In addition to the bioactive materials, the research results indicate that the following foods, vitamins, and minerals mitigated the risk of the apparent COVID-19 infection: Probiotic dairy products; Vitamin D; Natural sources of vitamin C; Some natural sources of vitamin B3 (excluding fish); and Real sea salt (neither purified, nor filtered).
Finally, the research findings revealed that the following foods would greatly intensify the risk of the apparent COVID-19 infection: Sugar substitutes and artificial sweeteners; fish and some other sources of phosphorous and phosphate (e.g. residues of phosphate fertilizers in some fruits, foods, and surface runoff waters); sugar; soft drinks and soda (rich in phosphorous, anti-calcium, and sugar); fast food; pumpkin; deep-fried food; Western diet and other unhealthy diets.
People who protected their bodies from mild influenza and common cold infections in the previous fall were highly prone to the risk of infection in the resultant data.
According to the computation results of billions of permutations of nutritional conditions and dietary regimes based on the data collected from the dietary and infection status of participants, there were many dietary conditions mitigating the risks of the apparent SARS-CoV-2 infection by 90%, whereas there were some dietary conditions increasing the risks by a factor of 3 or more.
In Table 1, the detailed results (for phase-1 of survey) are provided. Some items are added after initiation of the survey and during it, so the number of gathered questionnaires are different. According to our observations, the green rows are lowering the risk of COVID-19 apparent infection, and according to our observations, the red rows are increasing the risk of COVID-19 apparent infection.  Table 2. Results of phase 1 and 2 of data collection, for more than 15000 families. Between may 2020 and august 2020, about 15,000 questionnaire forms of family lifestyle and COVID-19 state were collected. Please note that for some technical reasons, in this Table, RR is defined as: the ratio of the probability of an outcome in an exposed group to the probability of an outcome in the entire community.

Dietary regimes
The collected dataset was employed to analyze the relative risks of different diets. In fact, a diet is a set of conditions for lifestyle and nutrition. In this study, each diet consisted of a set of four conditions, i.e. having an alpha item, having a beta item, lacking a gamma item, and lacking a zeta item. Instead of alpha, beta, gamma, and zeta items, nearly 100 other items can be placed in the lifestyle and COVID-19 questionnaire. Therefore, regarding the compositional permutation, this betting mode can be defined as one hundred million diets. If other items of the questionnaire (e.g. as ancestral ethnicity) are included in this permutation, the order of two billion diets can be defined, and the relative risk can be determined.
An important real example of the calculations and the results are presented in this section. The collected and processed big data included billions of operations showing that some diets reduced the infection risk by one-tenth. However, some other diets tripled the infection risk. Regarding these two numbers, only the diets given to at least more than 400 families in Tehran were included in their lifestyles; therefore, the diets were not abandoned. The calculation is based on the data collected from May 2020 to August 2020 in relation to more than 3000 families living in Tehran. For instance, according to the calculation based on the collected big data, "daily consumption of yogurt + daily consumption of coffee + no weekly consumption of fish + no excessive consumption of fast food" reduced the infection risk by one-tenth.
Our results suggest that turmeric and natural honey in dietary life style could reduce SARS-CoV-2 mortality ratios in families. Some details are accessible in a separate report (Besharati et al., 2021f).

Machine learning on relative risks of ethnicity diets
Machine learning was employed to develop a model for the prediction of the "relative risk of different ethnic groups" from the "relative risk of diet items in different ethnic groups" with an accuracy of more than 85%. The calculation details are accessible in a separate report (Besharati et al., 2021b). Accordingly, the relative risk of diet items can be related to the relative risk of their consuming groups. Hence, the infection risk of a group was a function of its diet (with an accuracy of 85%). Moreover, the other effective factors were excluded from calculations, although it does not mean that they left no effects. Figure 1. The effect of coffee on reducing COVID-19 mortality in groups of 4 countries. We considered only the countries with more than 5 kg per-capita annual consumption of coffee. Table 3. Results of phase 3 of data collection, for more than 5000 families. Please note that for some technical reasons, in this Table, RR is defined as: the ratio of the probability of an outcome in an exposed group to the probability of an outcome in the entire community.

Risk-reducing and -increasing items based on the regression analysis
To conduct these analyses, a previously described method (Besharati et al., 2021d) was employed on the Turin National Super-Computing Platform (IPM, 2021). According to the regression analysis of features and topological data analysis, the items playing central roles in mitigating the risk of SARS-CoV-2 were introduced as bell peppers, turmeric, natural honey, dates, olive oil, garlic, "weekly broth consumption", natural sources of vitamin C, "low and controlled consumption of oils", walnuts and nuts, fruit roll-ups, stewed squash (non-fried), eggplant, fasting, coffee, and "fennel and its edible products".
Moreover, the items increasing the apparent COVID-19 infection risk were introduced as consumption of soft drinks, sugar, fried food, fast food, artificial and diet sweeteners, high consumption of fish, and even high consumption of chicken, according to the results of this observational study.

Consumption ratio of items between infection and no infection groups
We compared the trends of running averages of consumption (the calculated consumption ratio for a window of 50 participants) for transition between infection and no infection groups ( Figure  2). The depicted curve is like a frequency response function (FRF) _a function used to quantify the response of a system to an excitation_. Here, the excitation is an ordered transition from no infection reports to peak 1 infection reports, then peak 2, then peak 3, then peak 4 and then peak 5 infection reports. Again here, the response is the fluctuations of consumption ratio of nutrition items. So, an ascending response curve could be associated with a risk-full nutrition item. A descending response curve could be associated with a protective nutrition item. The gap value between the no infection group average-consumption-ratio (ACR) and infection group ACR could be considered the gain (or power) of response. Natural honey, olives and olive oil, head cabbage, rose water, tahini, garlic, dates sap, grape sap, bell pepper, curcumin, fenugreek and coffee are some examples of protective high-gain items. Soft drinks (soda), fried food and fast foods are examples of risk-full high-gain items.

Thyroid and SARS-CoV-2
Based on the evidence from the collected big data and other data from Iran and other countries, it appears that there is a significant relationship between the level of thyroid hormones and the risk of death due to the SARS-CoV-2 infection. This relationship is used in the prognosis of death. For more details, please refer to its separate report (Besharati et al., 2021c).

Docking study
A molecular docking study showed that T3 and T4 hormones had comparable docking scores in comparison with remdesivir, trigonelline, and emodin (the COVID-19 Docking Server was used) (Kong et al., 2020) for binding to some COVID-19 proteins (Table 4 and Figure  3). Furthermore, the compound nicotinate mononucleotide (i.e. a derivative of trigonelline) with the formula of C11H15NO9P+ succeeded in inhibiting the RNA-dependent RNA polymerase (RdRp (RTP site)) protein in the novel coronavirus with a score value of -9.3 (kcal/mol). It acted better than the energy amount for the remdesivir molecule (-9.2 (kcal/mol)) in inhibiting the same protein.
Since inhibition of this protein plays a major role in the inhibitory function of remdesivir against the novel coronavirus (Mindikoglu et. Al., 2020), nicotinate mononucleotide compound can be considered an alternative to remdesivir in inhibiting the virus. Figure 2. For a-b-d, the members of "No Infection Group" consumed the item more than the members of "Infection Group". So the item may be protective. For c, the members of "No Infection Group" consumed the item less than the members of "Infection Group". So the item may be risk-full.
As the molecular weight of nicotinate mononucleotide (336 g/mol) is nearly half that of Remdesivir (603 g/mol), it is better in terms of both protein adhesion and absorption capacity. The main precursor of nicotinate mononucleotide, i.e. trigonelline alkaloid, is a naturally-occurring plant secondary metabolite, and nicotinate mononucleotide itself is present in mammalian biomolecular pathways. Therefore, it is likely to be more available, more cost-effective, and more non-toxic, and can act better than remdesivir.

Proposed model
A model was hypothesized to explain the results. Some natural hypomethylating agents (in their simple forms or complexes such as alkaloid-metal complexes and trigonelline compounds) were able to attach to viroporins (and other viral proteins) as well as the virus RNA to mark them, disrupt their functionalities, destroy their sequences, and hack the cybernetics of the viral information encoded in them. After all, the cargo mechanisms and cargo proteins acting naturally on the hypomethylating agents in a cell and its membrane (such as heavy metal pumps, arsenic pumps, and intercellular RNA transport mechanisms) managed to export and deport the hostile virus RNA from the cell cytoplasm. There are some reports regarding triiodothyronine (T3) reduction in some SARS-CoV-2 patients (Besharati et al., 2021c). According to a rigorous machine learning classification, the T3level proved to be the key control variable for fatal outcomes in reported metabolomics data of the patients. The lower levels of T3 are associated with unbalanced states of the immune system, and the down-regulation of T3 is associated with up-regulation of "CD4/CD8 ratio" (Besharati et al., 2021c). This phenomenon could cause severe autoimmune reactions and be responsible for fatal outcomes of SARS-CoV-2.  Hence, the people with lower levels of T3 in their blood samples are at higher levels of SARS-CoV-2 mortality risk. There is also evidence about the downregulatory effects of T3 on the proinflammatory mechanisms of the SARS-CoV-2. In fact, the pro-inflammatory cytokines IL-1β and IL-6, which are downregulated by induction of the triggering receptor expressed on myeloid cells 2 (TREM2) pathway, were downregulated by T3 and sobetirome in microglia and macrophages stimulated with the pro-inflammatory SARS-CoV-2 spike protein (Ferrara et al., 2021). The molecular docking study shows that T3 and T4 had comparable docking scores as opposed to remdesivir, trigonelline, and emodin (the COVID-19 Docking Server was used) for binding to some COVID-19 proteins. A linear regression model (with correlation coefficient 0.98) correlated Urinary Iodine Concentration (UIC) and SARS-CoV-2 mortality rates of 91 countries until February, 24 2021. This finding is worthwhile for our hypothesis, because the iodine metabolism is related to the thyroid state and functions. Age, diabetes, obesity, ethnicity, gender, genetics, person's mood (Besharati et al., 2021e), epigenetics, and environmental factors (e.g. pollution and ionizingradiation) can affect people's T3 blood levels. This finding can exactly explain the reported effects of those risk factors (Besharati et al., 2021c).
The human Angiotensin-converting enzyme 2 (ACE2) transmembrane protein (Hoffmann et al., 2020) is also another factor that the natural polypeptides of metal-alkaloids can use to ban the entry point of the novel coronavirus into the cell. Zinc, Cu, and arsenic are some heavy metals that can construct polypeptides (Banerjee, 2014) from trigonelline and some other small molecules.
Recent studies support the proposed model. The metabolomics analyses of the hospitalized COVID-19 patients in the USA (Seattle) (Su et al., 2020), China (Wuhan) , and some other countries (Besharati et al., 2021a), reported in separate studies, showed that trigonelline in the patient's blood had an RR<1 for the severity and death caused by the COVID-19. This can be interpreted as a protective effect of trigonelline (Other evidence about this issue is available in a separate report (Besharati et al., 2021a).

Summary
Due to the results of present study, the natural resources of hypomethylating agents in water, food, and the environment can reduce the risk of the COVID-19 pandemic. The results of previous studies support our findings with numerous internal and external evidence (Özçelik et al., 2011;Calder, 2020;Siahpoosh, 2020;Su et al., 2020;Wu et al., 2020;Chowdhury et al., 2018;Omidi-Ardali et al.,2019;Costa et al., 2020;Karimi et al., 2021;Bousquet et al., 2021).
For an overall summarization of our other findings in a regulatory network model, see Figure  4. Considering the effects of trigonelline and compounds synthesized from it, the results of the risk analysis, ODDs ratios, and relative risks proposed that it can be used both as supplemental food and a candidate drug to conduct an intervention in the process of the COVID-19 prevention and treatment.
The limitations in the process of designing and executing the present research included: 1: Limitation of the statistical population. Due to the limited financial resources available for the study, it was impossible to carry out a population census regarding all members of a statistical population. Therefore, voluntary random sampling was done on mobile social network platforms (based on selfmotivated participation of the subjects). 2: Even though several time frames within almost a year (the different COVID-19 peaks) were used for data collection, the method could be improved by performing a comprehensive cohort study. 3: The researchers sought to use many data resources to conduct a surjective survey on different samples of the statistical population (i.e. Iran's total population). However, one hundred percent surjection of the statistical survey cannot be guaranteed in terms of data diversity. Nonetheless, the internal and external evaluation of the data indicated their stratification and surjection of diversity. 4: Considering that the participants were volunteers and self-motivated, a very long questionnaire (with regard to the number of items) could not be used. The questionnaire included 100 items; however, a more comprehensive research can cover more items (i.e. several hundred items) on lifestyle and nutrition. 5: This research employed a method similar to that of other related studies and relied on the results obtained from the self-reports of participants. A small percentage of error is inevitable in this method. Our estimate based on internal and external evaluation of data accuracy suggested that the percent error and percent deviation caused by underreporting or misreporting were less than 5% of the total results.
The results of this research propose that nutrition and lifestyle are two important pivots or dimensions in fighting the COVID-19 pandemic. The natural hypomethylating agents in water and food together with lifestyle (exercising, fasting, and getting enough and proper sleep) can play a deciding role in the risk distribution of the spread of COVID-19. Specifically, trigonelline and the compounds synthesized from it can serve as a candidate in areas of research on prevention and treatment of COVID-19. The results of molecular docking (in-silico study) suggested that, the compounds synthesized from trigonelline could compete with the current first-line drugs of COVID-19 (especially, remdesivir in modern medicine and emodin in Chinese traditional medicine). It is worth noting that trigonelline with honey-water (i.e. a mixture of honey and water boiled over a gentle fire and then mixed with fenugreek herbal tea) was one of the prescriptions for treatment of pneumonia in Iranian-Islamic traditional medicine in past centuries acute respiratory syndromes epidemics.
Naturally, the results of this research alone cannot be used as a basis for general medical prescriptions by the regulating organizations during the COVID-19 pandemic, but, it can be considered a turning point in the course of SARS-Cov-2 and Phytomedicine studies. Taking into account the consistent results of previous studies and the present research, it can be expected that the regulating organizations dealing with the COVID-19 pandemic can conclude that use of natural hypomethylating agents in nutrition can be considered a centerpiece in the fight against the COVID-19 pandemic. Especially, the recommendation to consume materials containing trigonelline such as coffee, fenugreek seed herbal tea, bell pepper, anti-inflammatory spices, natural honey, fresh fruits-and-vegetables, rose water and some other available natural materials that, according to the results of studies, are effective in the distribution of the risks posed by COVID-19 in order to reduce the risks of apparent (symptomatic) infection.
There is some evidence that suggest the role of intake of iodine and thyroid hormones in the epidemiological status of SARS-CoV-2 (Besharati et al., 2021c). There is a hypothesis that the cause of fatal outcomes of SARS-CoV-2 is related to thyroid hormones (Besharati et al., 2021c).
The method employed in this research, which was based on big data and crowdsourced contribution of people through social networks, can be used in other health studies (especially on communicable diseases and noncommunicable diseases such as cancer, diabetes, metabolic syndrome, and even genetic diseases) to collect observational data. The main characteristics of this research method were its low cost, costeffectiveness and stratified big-data.