I thought many here, following the anti-vaxxer rhetoric and, being fair-minded, would appreciate the following journalistic deconstruction of a paper claiming biological pathways for harm from mRNA vaccines.
This is the "mRNA is bad for you" or - more specifically, "COVID spike mRNA is bad for you" anti-vaxxer meme. It is, to me, the most convincing strand of antivaxxer rhetoric. It seems so plausible. After all, mRNA in COVID vaccines is experimental, the vaccines had not been properly tested before its use.
Let us ignore the thing that now changes that. We have had an enormous real-world test now, and the side-effects are very well understood both qualitatively and quantitatively. The balance, for young people where it is unclear, is between small numbers getting the very nasty MIS-C or nasty but not life-threatening long COVID, and smaller numbers getting pericarditis. That risk/benefit has been so well studied there is no room for fair-minded debate. Even if like many year you are inclined to believe in global conspiracies you have to be a full-blown tin-hat wearer to believe regulatory capture independently for every developed nation in the world for the benefit of Pfizer shareholders at the expense of the country's children.
Let us look at a journalistic deconstruction. hat any person familiar with google and scientific phraseology, but without any medical specific, could do.
In this case it is Mr. Data Science doing the deconstruction. He is undoubtedly a very competent scientist - whose job is to look at numbers and work out the diference between coincidence and some real effect over many different domains. That gives him an edge here but if you read his analysis you can ask: "how muhc of this is juts common sense".
I'd be interested in how the antivaxxers posting here deal with this. All I need is a yes of no: "Yes - you agree this specific paper is rubbish in the sense that it is trying to make links that no-one would normally make and that are not supported", or "No - this is antivaxxer rhetoric with no scientific value".
What interests me is how clearly some of the classic publication games (we all do them) play out. For example "self-citation" - who would not do this when it can be justified and ibcreaes ones own citation count? More tricky - in a review paper you self-cite another review paper (as here) and use that as claimed evidence for primary research claiming something. Ummm - not - that is not right. But review papers are a bit like opinion pieces, and you can find a jornal somehere that will publish pretty well anything.
This very long review article presents many details about various biological pathways, most related to cancer, but their links to mRNA vaccines are almost wholly speculative. In some cases, they link to other vaccines, old mRNA technology, or COVID-19 infection, but are not directly linked to mRNA vaccines.
In fact, so much of their evidence is from papers on severe COVID-19 infections, not vaccination, much of the evidence in this article might be better suited to a paper pointing out potential downstream dangers of severe COVID-19 infections than on trying to raise alarm about mRNA vaccination.
A number of places in the article seem to make stronger statements linking mRNA vaccines to some of these processes, but they self-cite a previous review article by senior author McCullough and do not reference any primary biological research making these connections.
They suggest connections of these mechanisms to various anecdotal case reports for herpes zoster reactivation, liver damage, optic neuropathy, T cell lymphoma progression, Hepatitis C reactivation, events not yet confirmed to be related to mRNA vaccination.
The paper amounts to laying out a series of hypotheses about mechanisms of harm that may come from mRNA vaccines. Hypothesis generation is a valuable exercise, including in this context of understanding downstream biological effects of vaccination that might induce harm.
However, not all hypotheses are equally supported. Some are well-girded in direct evidence from relevant studies, while others are more speculative and extrapolate principles from other settings, e.g. SARS-CoV-2 infections or other injected vaccines, as done here.
Mr. COVID data science does have ONE advantage over the rest of us. He is very good at data science which means that he can more easily than most of us understand the many VAERS data claims made by the antivaxxers and which extraordinarily make up a lot of this paper. In fact the VAERS data is the only part of it that (if it were correct) would represent real evidence.
Read the article and ask yourself, “Are any of these points actually demonstrated in the article?"
Scientists have detected, validated, and characterized various minority harm risks of vaccines, including anaphylaxis/myocarditis for mRNA vaccines, and VITT/GBS for viral vectors. Detection, validation, and characterization of any other risk is critically important. And deep characterization of the subgroups at highest risk of these serious complications, and of the severity and long-term effects of them needs to be highly prioritized research and considered in refining vaccination recommendations.
Studies integrating information from existing literature to posit hypotheses explaining these harms and others are potentially useful, which this paper purports to do.
However, the purported “mechanistic frameworks” laid out in this paper lack any documented connections to mRNA vaccines, instead linking them to other vaccines, old mRNA technologies, or COVID-19 infections and speculating connections to mRNA vaccines. This makes their hypotheses speculative at best.
