suppression of aging for extreme longevity

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COVID-19 predictions: “infectable subgroup” hypothesis

As an amateur in virology, I present preliminary “infectable subgroup” hypothesis to explain:

  1. Why COVID-19 epidemic flattened in all countries even with poor mitigation measures
  2. Why new cases spike only in some (but not all) counties and US states since reopening  
  3. Why epidemiologic prognoses failed

In existing epidemiological models (unless I am mistaken), chances to be infected with SARS-CoV-2 coronavirus depend only on mitigation measures, such as social distancing. Biologically all people are equal. 

Consider in contrast that there are subgroups of highly-infectable (< 20%) and low-infectable people. During epidemic, most highly-infectable people become infected and the curve flattens earlier than models predict (when just a few % of population get infected). When such places re-opened there will be no spike. Spikes will be observed only in places/states that did not flatten the curve yet. In former hot spots, cases will continue decreasing upon reopening.

Noteworthy, on the ships, most people (low-infectable group) do not become sick regardless of how long they stay together. 

Low-infectable person does not get infected (and will not develop antibody either), when exposed to the virus.

The hypothesis also explains why it is more difficult to contain the spread, when just a few cases occur, than to flatten the curve at the peak of cases: All higly-infectable people have been already infected.

What determines infectable phenotype? Unlike COVID-19 vulnerability (mortality rate), infectability does not depend much on age, age-related diseases and gender. So we do not know.

There must be a biological component, including polymorphism. 

Before the mutation had occurred in the bat virus, all people were non-infectable. Mutation rendered people infectable, but not necessarily all people. There is polymorphism of receptors, enzymes and so on. Also non-genetic factors such as diet, etc. may contribute to the infectable phenotype. Behavioral factors (low vs high social behavior) are extrinsic factors of infectability. Family clusters of COVID-19 suggest genetic factors.

Predictions:

  1. There will not be drastic spikes in former hot spots such as some parts of New York upon re-opening. 
  2. There will be no second wave in the Fall, unless the virus mutates once again to make non-infecatble people infectable. There may be new hot spots in previously unaffected places, but this is all first wave.

Further directions: What are the markers and mechanisms of non-infectability?


Rapamycin for COVID-19 by Mikhail V. Blagosklonny

Section 11 from forthcoming review entitled “From causes of aging to death from COVID-19” (read full review soon) As soon as COVID-19 epidemic started, it become clear that COVID-19 vulnerability is aging-dependent condition and the use of rapamycin (Sirolimus) was immediately suggested by independent researches {Sargiacomo, 2020 #9}, {Zhavoronkov, 2020 #105}, {Zhou, 2020 #94}{Omarjee, 2020… Continue Reading

How rapamycin prevents muscle loss and sarcopenia (first draft)

The effect of rapamycin, an anti-aging drug, on the muscle, was puzzling for a decade. It seemed paradoxical that rapamycin, an inhibitor of mTOR component 1 (mTORC1), prevents muscle loss and sarcopenia. Yet, this is well established [1-5]. How is that possibly possible?  The nutrient-sensing mTOR pathway increases protein synthesis and cellular mass growth. Furthermore,… Continue Reading

Rapamycin: time is now … unless it’s too late

In 2006, I published an article that aging is not caused by free radicals nor by any kind of molecule damage but instead is a quasi-program driven in part by mTOR (Target of Rapamycin). By sheer luck, mTOR inhibitors – Sirolimus (rapamycin) and Everolimus – were clinically available. As I summarized in 2006: “…all diseases… Continue Reading