Karl Pfleger Profile picture
Jun 8, 2020 5 tweets 3 min read Read on X
#COVID19 cases mostly have low #VitaminD. Fixing low D might reduce deaths 5-10x. There’s no reason not to fix low D & much evidence it might help a lot. Until the data suggests otherwise, fixing low D while getting more data must be prioritized. 1pager: agingbiotech.info/vitamindcovid1…

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More from @KarlPfleger

Sep 16
Short report: The state of the mitochondria portion of the aging biotech field:

50 companies!
$1.4+B raised
700+ people
150+ clinical trials

many MoAs/targets:
mitophagy, transplant, fission, NAD+, UrolithinA, CD38, PINK1, PPARδ, DRP1, USP30, Complex 1, OMA1, & more

Read on: Image
Why is this important?
Mitochondria are central to aging:
It's one of both the original 9 Hallmarks & 7 SENS areas.
It's one of the subareas most directly tied to other subareas.
It's one of the subareas with the most direct relevance to a wide variety of age-related diseases. Image
This is also a sneak preview of part of the in-progress big update/overhaul of , now 40-50% done overall. Everything described in this thread comes directly from this database. The full new version will replace the current list when closer to 100% done.AgingBiotech.info/companies
Read 22 tweets
Aug 26
New PEARL rapamycin study vs CALERIE mild (12%) CR study 🧵:

CR & rapa both ↓mTOR. But frustrating the designs aren't more apples-apples. Many things improved by 1 not reported in other. (Also unfortunate for both we don't have more direct biomarkers of mTOR pathway activity.) Image
We want to estimate long-term benefit. What do these 2 short (relative to lifespan) 1-2yr studies tell us?
What metrics can we directly compare?
See below...
(Links to all papers included below too.)
Frustrating study diffs:

Eg very diff ages: ~38 (CALERIE), ~62 (PEARL)

Frustrating metric diffs:
CR improved BMI, bodyfat%, BP, insulin, & pace of aging, all unreported for PEARL. (End BMI not in any table. Visceral fat reported but not total fat.)
Image
Image
Read 25 tweets
Jul 1
Direct-to-consumer aging clocks give very inconsistent answers. I tried TruDiagnostic, Elysium, GlycanAge, & reg blood draw for PhenoAge on same day in Feb & from same venous blood draw at LabCorp, except Elysium's uses saliva which I did right before going to LabCorp. Notes: 🧵
I chose these 4 clocks for the same-day comparison since they are most respected & used clocks avail to consumers currently. Specific reasons for each:

@TruDiagnostic: team (eg @RyanSmithEpiAge, @VarunDw, @EverythingEpi) comes & presents at aging confs regularly, its the basis for the leaderboard Bryan Johnson's team maintains, they licensed DunedinPACE, & they provided an intrinsic vs extrinsic split per the mix change of immune cell types issue @alantomusiak from Eric Verdin's lab identified recently as a problem with most clocks.

Elysium briefly had @DrMorganLevine as advisor & she supposedly helped develop the 100k+ cpg site Index test, which should be robust to the test-retest variability issue that her recent PC clock paper identified as a problem with most clocks. (TruDiagnostic's clock is also supposed to be robust wrt this issue.)

@GlycanAge: team (@GordanLauc, @entreprylexia) also comes & presents at aging confs & its based on a completely different signal.

PhenoAge (also from @DrMorganLevine) is a gen2 clock that's widely used even clinically by notable longevity expert doctors, & it was easy to add with just a basic blood draw.
Not gonna give all details on which # from which clock but top lines results were all over the place. The 4 age point estimates: 20, 40, 50, 55.
This was a bigger spread than I expected.

2 tests give rate of aging & these also had a big range: 0.77 & 0.95.
Read 13 tweets
Dec 6, 2023
Data from the new TargetD trial suggests that prior vitamin D trials were flawed:

Many people, even professionals, still think vitamin D was a false profit that was disproven by big RCTs. This view is very flawed, for several reasons. A brief history:news-medical.net/news/20231113/…
For decades, thousands of studies have shown reliable correlation of low vitamin D levels & bad health outcomes. Scientifically, the proper way to test the hypothesis that this correlation is causal is RCTs that meaningfully alter the low vitamin D status & then measure outcomes.
Heaney in 2014 published trial design guidelines for nutrients saying essentially the above.

Rule 4 was "The hypothesis to be tested must be that a change in nutrient status (not just a change in diet) produces the sought-for effect."academic.oup.com/nutritionrevie…
Read 15 tweets
Aug 30, 2022
Highly recommend the most recent good review of mechanisms of action of vitamin D affecting Covid risk pubmed.ncbi.nlm.nih.gov/35308241/
by notable Irish researchers who've published in the area throughout the pandemic.

Notable: Directly addresses satisfying Hill's Criteria for causation.
Image is Fig 2: "Molecular pathways in the pathology of Covid-19 thought to be affected by vitamin D"

That's a lot of diff Covid related biology affected by vitamin D!

Great job @RoseAnnekenny1 & co

Some direct quotes f/ the main text of the paper are worth repeating here:

🧵
"Applying the Bradford-Hill criteria [..] the collective literature supports a causal association between low vitamin D status, SARS-CoV-2 infection, and severe COVID-19 [..] A biologically plausible rationale exists for these findings"
Read 19 tweets
Aug 12, 2022
The most basic implication of the uncontroversial strong association between vitamin D levels & health outcomes:

Vitamin D level should be tested in clinical trials for many conditions, including Covid.

Why isn't this routine? Why isn't this discussed more?

Short 🧵 1/5
Vitamin D's causal influence on many health conditions is controversial, mostly for not enough big positive RCTs. But vitD's correlation w/ outcomes in many important conditions (CVD, cancer, diabetes, Covid, etc) is uncontroversial.

See mdpi.com/2072-6643/14/3… for a review.
2/5
Baseline risk is important in clinical trials eg to check risk imbalance, power calcs, & assessing effect size. Google it for a lit sample.

Trials should assess all easy-to-measure significant risk factors. Risks factors are determined mostly by observational data not RCTs.
3/5
Read 5 tweets

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