Role of exosomes in false-positive COVID-19 PCR tests: Non-specificity of SARS-CoV-2-RNA in vivo detection explains artificial post-pandemic peaks

Background: The COVID-19 pandemic priorities have focused on prevention by detection and response. National governments’ prevention response decisions are based upon detection statistics from PCR (polymerase chain reaction) tests that are used to define numbers of (i) COVID-19 infected persons, (ii) COVID-19 hospitalisations, and (iii) COVID-19 deaths. These statistics assume a priori that PCR tests are nigh 100% true detectors of COVID-19 infections. Here we will provide an alternative interpretation, along with the compelling evidence, that false positives have distorted to some degree the statistics of the primary outbreaks, and account for almost the whole of the 2nd and subsequent apparent COVID-19 outbreak peaks in various countries.

Methods: We extract from the published literature on PCR-test outcomes graphical data that reveals the evidence for a very large percentage of false positive results. We review the role of exosomes in the immune response to all respiratory viral infections and its effect on PCR tests. We hypothesise that exosomes, triggered by all viral respiratory infections, are largely responsible for positive outcomes from PCR tests for COVID-19. We test our alternative interpretation for consistency with the empirical epidemiological trends as published by the World Health Organization (WHO). The Scientific Method is used to direct our research efforts.

Findings: We find that PCR testing data for the second and following waves of the COVID-19 pandemic indicate that these waves are mainly artefacts of false-positive results. We find that this interpretation provides a more consistent explanation of the known epidemiology of COVID-19 than the hitherto consensus notion of extremely contagious and rapidly mutating viruses.

Interpretation: The RNA (ribonucleic acid) code detected in PCR tests, previously attributed to SARS-CoV-2, belongs instead to a respiratory-virus-induced immune system response by human cells that liberate exosomes, and that vitiate PCR test results. PCR tests have zero specificity in vivo due to the exosome RNA. PCR tests exhibit excellent specificity in vitro on pure samples of other respiratory viruses. The low success rate of vaccines in preventing COVID-19 is explained by the inexact identification of the SARS-CoV-2 RNA.

Introduction

Recently the World Health Organisation (WHO) published a document [1] that called attention to the relevance of false positive results of Reverse Transcription (RT-) Polymerase Chain Reaction (PCR) tests for a SARS-CoV-2 virus, the causing agent of respiratory disease commonly known as COVID-19. PCR tests are used to directly screen for the presence of viral RNA, which will be detectable in the body before antibodies form or symptoms of the disease are present. During PCR testing for COVID-19, substances known as reverse transcriptase or DNA polymerase are added to a nasopharyngeal sample in a lab. These substances work to make numerous copies of any viral RNA that may be present. This procedure ensures enough copies of the RNA are present to signal a positive result, as specifically designed primers and probes attach themselves to sequences of the genetic code of the virus to signal that a pathogen has been found.

This WHO publication [1] is a reminder that the disease prevalence alters the predictive value of test results. As disease prevalence decreases, the risk of false positives increases. This means (quote) “that the probability that a person who has a positive result (SARS-CoV-2 detected) is truly infected with SARS-CoV-2 decreases as prevalence decreases, irrespective of the claimed specificity” (underlined by us). The WHO alarm notification has been vindicated by a field-study investigation in the UK [2].

In layman’s terms, technical specifications provided by test producers become irrelevant at low SARS-CoV-2 prevalence. The producers may claim their test is 100% specific to the SARS-CoV-2 virus, but in practice, if COVID-19 prevalence in the population is low or zero – as may well happen seasonally – each and every positive result will be a false positive, reducing the amount of information contained in it to zero [3]. Note, however, that since the start of the pandemic, the WHO has been proclaiming that more extensive testing is necessary [4], which could conceivably generate ever-repeating unreal ‘COVID-19 outbreaks’.

1. The warning signals already have important consequences for public health institutions, which could have far-reaching damaging effects not just on public health services but on the general economy of political decisions based upon PCR test statistics. We note the following 4-point established facts at the outset [1-4].Irrespective of the test specificity claimed by the test manufacturer, PCR tests produce false positive results in appreciable numbers.
2. The fraction of false positive results in all positive results increases as the prevalence of the SARS-CoV-2 virus in the population decreases, e.g. due to the seasonality of all other respiratory infections;
3. In the limiting case of zero prevalence of SARS-CoV-2 virus, all positive PCR test results will inevitably be false positives; hence,
4. PCR tests can never indicate that the SARS-CoV-2 virus went out of circulation, as false positives will appear indefinitely, indicating the alleged presence of the virus.

Accordingly, we have investigated a more plausible explanation for the development of COVID-19 pandemic data since 2019, based upon the alternative interpretation that exosomes play a role in false positive tests of patients who do not carry the COVID-19 virus. We find that the prevailing interpretation of PCR test results does not withstand scientific scrutiny in the light of the experimental or factual observations.

Research in context

Evidence before this study: The COVID-19 pandemic appears to be caused by a highly contagious and quickly mutating virus, with new variants, rapidly emerging all over the world, causing new outbreaks of the pandemic, including the disease in vaccinated persons, and repetitive infection in previous COVID-19 patients. The implication is that the pandemic is a never-ending cycle of new waves, mass PCR testing, and vaccination programs.

Added value of this study: The first wave of COVID-19 that developed in Europe and the US in March-May 2020 was largely real, while two or more subsequent waves are an artefact of false-positive results of PCR tests that are not indicative of rampant, or indeed significant levels of infection by the SARS-CoV-2 virus in the population. The implication is that we can safely stop PCR-testing and mass vaccination of healthy people and end restrictions.

Methodology

Apart from available statistical information, we used the Scientific Method as outlined by K. Popper and R. Feynman, and summarized in our previous publication [5], to compare two different hypotheses explaining the recent COVID-19 pandemics, one following from official WHO (World Health Organization) publications, and another proposed by us (OPS, Ossonoba Philosophical Society). Several important corollaries result from the Scientific Method definition, and are used presently:

• If a piece of experimental evidence is not properly explained by a certain hypothesis, then this hypothesis must be incorrect;
• The simplest of several hypotheses apparently explaining the experimental data is the best one;
• If there are several hypotheses apparently capable of explaining the existing data, then experiments should be made to reject some of these hypotheses; the remaining hypothesis that still stands after this procedure should be accepted as the currently valid scientific theory;

A scientific theory must be falsifiable, and thus must make testable predictions; theories adjusting its explanations in a Bayesian way each time something new unpredictably happens are non-scientific.

Note that the Scientific Method universally applies to all of the subject areas of scientific research that study objective reality, and not to any specific area or areas. This excludes such areas as e.g. mathematics, which studies imaginary objects postulated by researchers.

Exosomes

The important role of exosomes in the functioning of the immune system challenged by a viral respiratory disease is established science [6], although the precise function and molecular mechanisms remain a topical research question [7]. Cells challenged by viruses produce exosomes, apparently signaling the immune system into action. Exosomes are structurally like a flu virus and contain some information in the form of RNA and some attached proteins that provide structural integrity and acceptance by the target cells of the immune system. The immune response to respiratory viruses is evidently triggered by the appearance of exosomes [6,7].

The trigger may also involve individual airway epithelial cells, at least partly, as exosomes were found to contain viral proteins, although not yet at the beginning of the illness, indicating that interaction with the immune system is necessary before that happens. Generally, foreign viral RNA may be identified by comparing it to the cell’s own genetic material. Such function requires specialized cellular machinery, hardly compatible with the normal physiological function of epithelial cells.

Exosomes, however, contain the answer to the ‘where’ question and information contained in the exosome RNA should uniquely identify the virus-challenged airway epithelial cells, allowing the immune system to prepare its targeted response. The exosome RNA structure is probably independent of the pathogenic virus and varies only in conformity with the patient’s individual genome.

These patient genome variations consistently explain several observations, which the consensus hypothesis attributes to the special properties of SARS-COV-2. Indeed, any test would produce a negative outcome for exosomes whose RNA is different from that of the exosomes used for developing the test. This explains the 40% false negatives reported in China at the outset of the pandemic, in patients with classical clinical symptoms of COVID-19.

On the other hand, sequencing of the perceived viral RNA in remote locations necessarily reveals new exosome strains, caused by human genetic variability, but misidentified as new SARS-COV-2 variants. Once tests detecting such exosomes are developed and deployed, these perceived virus variants get instantly discovered everywhere, creating a false and terrifying impression of their fast propagation. The apparent propagation rate of such new variants will only be limited by the throughput of the testing system. Many differing human genomes coexist in various geographic locations due to modern population mobility.

These variant-specific tests would also produce false negatives on patients with differing genomes, albeit on genomes different from the undetectable genomes of the original tests. The exosome origin of the RNA attributed to SARS-COV-2 and its variants explain the fact that PCR tests used on patient biological samples are completely non-specific as regards the virus. Indeed, these tests are specific to exosome RNA, which probably carries no virus information, as postulated above. This, in turn, explains a misdiagnosis phenomenon, that manifests itself in countless observations the more salient of which we itemise and outline in the following section.

Observations explained

We describe some infection cases as ‘false positive multiplication by compulsory contact testing’ (FPMCCT), which requires no further explanation. The second class of false positives is one of the key points of the present paper and is described as illnesses caused by seasonal respiratory viruses, including variants of influenza A and B, common cold rhinoviruses, human coronaviruses, etc [8] all being ‘misdiagnosed by PCR tests as SARS-CoV-2 virus’ (MDSCV), with very high probabilities. This phenomenon will be discussed below in more detail.

The published records of information listed in Table 1 were obtained from mainstream media and verified with Our World in Data [9], wherever quantitative data was called for. The order in which the following salient questions are listed is arbitrary.

Scientific method criteria

Based upon observation, question, and hypothesis criteria of the scientific method, we can objectively analyse the pandemic data, with WHO observations/questions, and alternative OPS explanations, itemised in Table 1. From the point of view of the scientific method defined above we note that it has not been adhered to by scientific advisors to many national governments that have already answered “yes” to the many questions raised by the WHO in ad hoc knee-jerk responses to the pandemic.

The interpretations provided by OPS explanations are compliant with the scientific-method criteria. Unlike WHO, we are not using any alleged or unsubstantiated properties, e.g., hypothetical high rate-of-transmission of SARS-CoV-2 variants. We refer only to information demonstrably correct; however, we question the reliability of analytical tools existing at the present time, like dubious PCR tests [1]. However, the proposed role of exosomes in the false-positive PCR test results will remain a hypothesis that needs to be investigated with some circumspection for more direct laboratory experimental evidence that it is the agent responsible for vitiating PCR test results.

The WHO interpretations require the following hypothetical assumptions for which there is presently no compelling evidence, thus going against the principle of Occam’s razor:

1. Transmission by asymptomatic COVID-19 carriers;
2. Tests really working and being 100% specific in clinical in vivo practice;
3. Vaccines are effective, while vaccinated people are getting ‘infected’.                
4. Effectiveness of vaccines is determined by PCR tests;
5. The same virus generates completely different outbreak dynamics in the first and subsequent waves, due to fast evolution.
   
   The OPS explanations only assume established scientific knowledge that has been conclusively demonstrated:
6. PCR Tests produce false positives both on different respiratory viruses, and on patients having no respiratory viruses at all;
7. Contact PCR testing amplifies the number of tests and false positives;
8. Classic, or nearly Gaussian, dynamics of the first (SARS-CoV-2) wave in 2020 (March-May in Western Europe), and the slower-skewed testing–generated dynamics in the subsequent waves.

The observations, and consensus interpretations that we question above, are somewhat contradictory. Compare, for example, items 5, 7, and 10, in which the assumptions that public health measures were both sufficient and insufficient, to reduce propagation of SARS-CoV-2 are questioned. Also, WHO observations of item 7 are contradictory in themselves because strict self-confinement and isolation were imposed already at the onset of the first wave, but inexplicably turned out entirely inefficient, resulting in a classical dynamic of epidemic flu, i.e., 4 weeks up and 7 weeks down, instead of the publicly promised “flattening the curve” with “reduced load on health service system”.

Considering items 2, 9, and 11, SARS-CoV-2 is physically akin to other flu viruses, and its RNA mutates at a similar rate due to RNA reproduction errors in human cells. Therefore, it is unable to produce significantly different variants capable of overcoming the existing immunity much faster than the common cold and other seasonal respiratory viruses, where such major variants come up once in a few years at least. Indeed, dozens of variants of influenza A exist, with immunologically different updates to those major variants still taking many years to appear, which explains large intervals between severe outbreaks of influenza A. Therefore, the explanation provided by the WHO- consensus hypothesis must be erroneous.

Moreover, considering items 6 and 10, any public health measures cannot affect SARS-CoV-2 any differently from the common cold and other seasonal respiratory viruses, for the simple reason that all these viruses are physically indistinguishable and can only propagate within aqueous droplets, losing virility once the droplets dry out. Therefore, if a surgical mask can stop one of the viruses because it stops all droplets, it will similarly stop all others. In fact, we have known for more than 100 years that masks do not affect influenza propagation [10]. Therefore, the explanation provided by the WHO is quite demonstrably untrue.

From experimental evidence item 11, infection statistics for the UK and Israel are inconsistent at the time of writing. Figure 1 shows the plot of new COVID-19 cases in Israel and the UK, which were the most vaccinated countries, with almost all adult population, at the time of writing.

Figure 1: Daily new COVID-19 cases in Israel and the UK, per million population; data taken from Johns Hopkins University, and the plot adapted from Our World in Data5. Note the logarithmic scale. Dashed lines indicate the rate of outbreak development, similar in the two countries. Both countries almost completed their vaccination programs.

Note that Israel has a slightly higher percentage of complete vaccination than the UK, yet lower PCR-positive case numbers at present. However, in Israel, the apparent case infection rate is growing faster than in the UK and is set to overcome UK numbers in a matter of weeks. Therefore, vaccination has no apparent effect on the development of the current case numbers, exactly as predicted by the false-positive explanation.

Finally, we also note that the WHO consensus and OPS explanation produce very different predictions of the future development of the COVID-19 pandemic and very different public health recommendations. We further discuss these differences in the Discussion.

Excess mortalities

Note that there are no valid RNA tests capable of discriminating COVID-19 from other flu-like diseases, as demonstrated above. Therefore, no valid information on the epidemiology of COVID-19 may be obtained from published case statistics, which are all based on RNA tests. For these reasons, excess mortality statistics were considered instead. Excess mortality usually exhibits peaks associated with viral respiratory diseases in the autumn and winter seasons. However, additional peaks appeared in spring in the years 2020 and 2021, attributable to SARS-COV-2 as will be discussed below.

Eastern Europe: Figure 2 shows excess mortality in selected Eastern European countries in 2020-2021. Apparently, these countries did not have adequate meteorological conditions for COVID-19 transmission in the spring of 2020 and therefore had no significant associated mortality in that period. This demonstrates that even in its first outbreak, SARS-COV-2 was transmitted as a seasonal flu virus, requiring adequate meteorological conditions, and was not transmitted outside its preferred season, contrary to what may be inferred from statistics of the new cases derived from RNA tests. It is therefore concluded that SARS-COV-2 is only prevalent in spring, in the same way as all of the previously known human coronaviruses.

Figure 2: Weekly excess mortality in representative Eastern European countries in 2020-2021. Plot adapted from Our World in Data https://ourworldindata.org/explorers/coronavirus-data-explorer Rectangle: February 28 to May 16, showing expected coronavirus prevalence.

Thus, within the time interval considered, Eastern European countries had a rhinovirus peak in the autumn of 2020 and their first coronavirus peak in the spring of 2021. Czechia also had a discernible flu A peak, with its maximum on January 10. It is possible that rhinovirus mortality was amplified by clinical diagnostic errors induced by the results of invalid PCR tests that signalled COVID-19 in rhinovirus cases.

Western Europe: Figure 3 shows excess morality in selected Western European countries. Contrary to Eastern European countries, Western European countries apparently had suitable meteorological conditions for COVID-19 outbreak already in the spring of 2020 and strong peaks of excess mortality in this period. These peaks occurred during the first wave of COVID-19 in Europe. The mortality peaks of the second COVID-19 outbreak in the spring of 2021 were significantly smaller, about 25% of the first outbreak, indicating that population-wide immunity was already quite advanced after the first outbreak. Note that other human coronaviruses do not produce strong mortality peaks in spring; therefore, their mutations should be significantly slower than those of flu A. It is therefore reasonable to expect that spring mortality peaks associated with COVID-19 will also disappear in a year or two after sufficient immunity is accumulated in the population. On the other hand, it seems reasonable that stronger coronavirus mortality peaks were associated with the newly appeared coronavirus, as has happened with SARS-COV-2. The second outbreak in the UK did not appear at the same time as that in other countries, occurring probably about 2 months earlier, due to a significantly different climate. The excess mortality peaks in autumn 2020 and winter 2020-2021 are attributable to rhinovirus and flu A. The small and sharp mortality peak appearing in Germany, Netherlands, and France in August 2020 is attributable to the heat wave.

Figure 3: Weekly excess mortality in representative Western European countries in 2020-2021. Plot adapted from Our World in Data https://ourworldindata.org/explorers/coronavirus-data-explorer Rectangles: March 1 to May 24, 2020, and February 28 to May 16, 2021, showing expected coronavirus prevalence.

It is therefore concluded that SARS-COV-2 is quite similar to other coronaviruses, in that it appears only seasonally, in most European countries in spring, and its associated excess mortality is on the way to extinction in a few more years, indicating rapid acquisition of population-wide immunity. There are no indications of rapid mutations of this new virus, which would slow down the observed reduction in the spring excess mortality. Additional excess mortality in seasons with low SARS-COV-2 prevalence is apparently induced by the utilization of the results of RNA tests in the clinical practice, which leads to the exaggerated scale of pandemics and misdiagnosis of other respiratory viruses and bacteria such as SARS-COV-2. This may cause contamination of patients already carrying a different respiratory virus by SARS-COV-2 in hospitals, where the virus may be surviving and propagating even outside its preferred season, due to the air-conditioned environment facilitating virus transfer from authentic virus carriers.

Discussion

Our revised explanation for the various observations of the COVID-19 epidemiology, along with predictions for the development of the COVID-19 pandemic are so far entirely consistent with all known experimental observations as evidenced by published statistical data. We have been unable, as yet, to conduct clinical experiments to confirm the reality of the MDSCV, however, researchers in St. Petersburg have obtained experimental evidence that a large fraction of COVID-19 patients have additional respiratory viruses in their system [11]. To avoid an infinite sequence of pseudo-COVID-19 outbreaks and constant mass revaccinations, mass testing for SARS-CoV-2 and its variants should be immediately discontinued, along with futile attempts to identify asymptomatic carriers, and the respective resources used to provide remedies for chronic patients with other conditions, who were left without medical help by reorienting all medical service towards COVID-19 pandemics.

MDSCV phenomenon may be tested for in the laboratory by infecting human volunteers with known respiratory viruses other than SARS-CoV-2 and using standard PCR tests for SARS-CoV-2 on those who develop symptoms, in a strictly quadruple-blind experimental design. In an approach not requiring volunteers, patients diagnosed with SARS-CoV-2 may be retested for seasonal respiratory viruses, which will be present in most cases producing what is erroneously interpreted as COVID-19 due to false-positive results of PCR tests.

We are finally left with a striking contradiction between the excellent specificity of SARS-CoV-2 tests demonstrated on de facto samples of other respiratory viruses in vitro as per the information provided by the test producers, and the apparently zero specificity of the same tests revealed in vivo in clinical practice, as demonstrated here. To address this contradiction, note that all tests (and vaccines) were produced using the genetic information published by the SARS-CoV-2 discoverers in the appropriate databases.

Consulting the respective seminal publications [12], we find that the respective genetic material had been identified computationally without preparing an isolate of the respective virus particles, and without separating them physically from other carriers of genetic material that may be present in the biological samples [12]. Noting that tests apparently produce false positive results in people carrying some respiratory virus different from SARS-CoV-2, we must conclude that the alleged genetic code of the SARS-CoV-2 virus had been wrongly identified, belonging instead to something generated by human airway epithelial cells challenged with respiratory viruses and containing RNA, for instance, to exosomes, as explained above.

It is no surprise, therefore, that the tests are totally non-specific in the clinical practice while demonstrating excellent specificity in vitro: samples of other respiratory viruses used for in vitro trials were not contaminated with products of human cells, whereas all biological samples used to identify RNA code of SARS-CoV-2 have been in contact with such cells [12]. Note also that SARS-CoV-2 RNA had been found similar to that of another virus, which casts reasonable doubt on that previous identification.

It appears also that the RNA codes of SARS-CoV-2 variants, very similar to that of the original COVID-19 virus, have also been wrongly identified. Given that the alleged SARS-CoV-2 RNA should be in fact generated by human airway epithelial cells used for virus culturing [12], it is possible to explain high rates of false negative results in COVID-19 patients. RNA induced by the virus in challenged human cells may vary from patient to patient, due to individual genetic differences, making it not recognizable by the test.

Having inferred an erroneous identification of the genetic material belonging to SARS-CoV-2, we can interpret the low success rates of all the existing vaccines, requiring multiple doses to produce a reasonable immune response. Indeed, the vaccines are based on the genetic material, probably of exosomes, generated in human airway epithelial cells challenged by respiratory viruses, and not on the genetic material of the SARS-CoV-2 virus itself. Immunity generated by such vaccines will suppress the own exosomes, and therefore delay the immune system response in COVID patients. These vaccines may also exacerbate problems in patients with other diseases that induce cell responses akin to that generated by respiratory viruses, probably explaining some of the adverse reactions to vaccination amongst younger recipients.

Conclusion

Scientific Method states [5] that science should be searching for evidence contradicting accepted hypotheses, in order to move our knowledge forward. In the present case, as a means for challenging the mainstream hypothesis, we suggest that patients diagnosed with COVID-19 should be additionally tested for other respiratory viruses, to find out whether the same virus is also detected in vivo by tests designed to detect those other viruses. Indirect evidence of this being the case is given by Flunet statistics [13], where a second strong yearly flu peak appeared in spring, after the beginning of the COVID-19 pandemic. Note that spring is the season when human coronaviruses circulate and that no strong peak had been present in spring prior to pandemics. We predict that this additional peak will disappear completely in a few more years, indicating it describes the action of a pathogen different from conventional Flu A/B viruses, circulating predominantly in winter of the North Hemisphere. Yet, the viruses appearing during this spring peak are being detected by the respective tests as Flu A/B viruses.

Contributors

IK and PS guided and performed all the initial observations and data analysis. IK guided the conceptualisation and investigation and wrote the first draft of the article. LVW guided the writing, review, and editing, and contributed to the interpretation sections. All authors contributed to the analysis of the data used and/or referenced, and to the acquisition, drafting of results, and revising it critically for important intellectual content. All authors have full access to all the data in the study and take full responsibility for the decision to submit for publication.

This study received financing from Foundation for Science and Technology (FCT), Portugal, grant number UIDB/00631/2020 for the University of Algarve CEOT research center.

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