4 ms·

Was expecting a number comparing the amount of mutation with a regular non-astronaut's genetic mutation. It's not there.

jxramos 4y ago
I don't get it, how is it that the simple question of "compared to what?" is just completely omitted and seemingly never even considered by so many authors? Do people just operate with plain dead end facts without context or curiosity about how normal is even characterized or distributed? Is the idea of a nominal case/measure/etc so foreign? I wonder what series of basic questions could be memorized that could be a tool for authors to ask themselves to elicit getting this information or at least stating that the answers are unknown.
- hedora 4y ago
  If I were on a tenure review board, I would argue against treating Nature papers as peer reviewed publications. I keep seeing obvious “strong reject” clickbait from them, specifically. This paper is a prime example.
  - lostlogin 4y ago
    Are you referring to the paper, or the summary of the paper which was linked to here?
    - hedora 4y ago
      The actual paper. It’s the top link in the body of the article.
- michaericalribo 4y ago
  I’m confused…did you read the Science paper itself? In their _first paragraph_ they reference baseline genetic variation, and age-related mutation versus the mutations seen in cancer survivors and—as it turns out—astronauts, in the second paragraph. Lots more details and caveats on the limitations of the data elsewhere in the paper. You seem to be reacting to this article, which is a popular summary of the findings. I don’t even think it’s a misleading article—it conveys the qualitative conclusion (elevated rates of nonstandard mutations), and answers to the questions you posed are available in the full scientific study…
  - hedora 4y ago
    The article links to a Nature paper. Are you reading a different paper? https://www.nature.com/articles/s42003-022-03777-z.pdf https://www.nature.com/articles/s42003-022-03777-z.pdf This is the closest thing I can find to a reference to a control in the first two paragraphs. The figures also suggest they did not have a control, so the use of the phrase “elevated rates” is baseless: > Considering baseline genetic and extrinsic variability, the development of tools that permit the assessment of individual genetic susceptibility would improve risk stratification and long-term clinical management. If funded, that still wouldn’t be a reasonable control. Maybe I’m missing a key sentence or something, but I’ve read the paper, and it seems to boil down to: “Mutations are bad, and this expensive piece of equipment measures mutations, so we stuck expensive astronaut blood in it, and the gauge pointed to a non-zero number”.
    - michaericalribo 4y ago
      Later: > Variants (SNP/ InDel) generated with this method were compared with a normal dataset using Archer’s analysis pipeline to distinguish noise from a true call. The normal dataset was created with sequencing data from seven young, healthy individuals.
      - gus_massa 4y ago
        From the article: > in this astronaut cohort (median age 44 years, range 37–67), I'd like to see also a comparison with 7 normal persons with ~45 years old. How many mutations is the expected value for a ~45 years old person?
        deleted 4y ago
        [deleted]
      - hedora 4y ago
        Archer's analysis pipeline isn't a well defined statistical test. It's a UI that browses results from the type of machine they used: https://www.enzymatics.com/news/archer-analysis-pipeline-update-version-3/ https://www.enzymatics.com/news/archer-analysis-pipeline-upd... They filtered the results with various p-values < 0.01. Their supplementary data: https://www.nature.com/articles/s42003-022-03777-z#Sec9 https://www.nature.com/articles/s42003-022-03777-z#Sec9 doesn't say how many samples the machine produced in the first place, but it does say the filter resulted in 35 hits. That tells us absolutely nothing about the rate of mutations in the astronauts vs the general population, or even if astronauts produce more novel mutations on average vs. the general population. On top of that, they seem to have the data to answer these questions, but don't report it anywhere: Do zero-mission astronauts also show a "true call" in Archer's analysis pipeline? They ran multiple samples from the same astronauts (before and after missions). On average, does the same astronaut have more/more-novel mutations after each mission? These would require additional experiments or data, but seem obvious to check: Do they have unusually high or low numbers of mutations vs. the general population at the same age? If so, grouping the general population sample, what other professions also show a "true call" according to the pipeline?
deleted 4y ago
[deleted]
chromatin 4y ago
That information is relatively well known to those familiar with the field of clonal hematopoiesis, and was likely omitted for brevity. It is not reasonable to expect lay public level of background information to be included in every discipline's scientific publications. I'll point you to the two seminal papers in the field of CH though if you are interested. These were published back-to-back in the same issue of NEJM in 2014 (interestingly from separate competing groups at Harvard). https://www.nejm.org/doi/full/10.1056/nejmoa1408617 https://www.nejm.org/doi/full/10.1056/nejmoa1408617 https://www.nejm.org/doi/full/10.1056/nejmoa1409405 https://www.nejm.org/doi/full/10.1056/nejmoa1409405

jxramos 4y ago

I don't get it, how is it that the simple question of "compared to what?" is just completely omitted and seemingly never even considered by so many authors? Do people just operate with plain dead end facts without context or curiosity about how normal is even characterized or distributed? Is the idea of a nominal case/measure/etc so foreign? I wonder what series of basic questions could be memorized that could be a tool for authors to ask themselves to elicit getting this information or at least stating that the answers are unknown.

hedora 4y ago
If I were on a tenure review board, I would argue against treating Nature papers as peer reviewed publications. I keep seeing obvious “strong reject” clickbait from them, specifically. This paper is a prime example.
- lostlogin 4y ago
  Are you referring to the paper, or the summary of the paper which was linked to here?
  - hedora 4y ago
    The actual paper. It’s the top link in the body of the article.
michaericalribo 4y ago
I’m confused…did you read the Science paper itself? In their _first paragraph_ they reference baseline genetic variation, and age-related mutation versus the mutations seen in cancer survivors and—as it turns out—astronauts, in the second paragraph. Lots more details and caveats on the limitations of the data elsewhere in the paper. You seem to be reacting to this article, which is a popular summary of the findings. I don’t even think it’s a misleading article—it conveys the qualitative conclusion (elevated rates of nonstandard mutations), and answers to the questions you posed are available in the full scientific study…
- hedora 4y ago
  The article links to a Nature paper. Are you reading a different paper? https://www.nature.com/articles/s42003-022-03777-z.pdf https://www.nature.com/articles/s42003-022-03777-z.pdf This is the closest thing I can find to a reference to a control in the first two paragraphs. The figures also suggest they did not have a control, so the use of the phrase “elevated rates” is baseless: > Considering baseline genetic and extrinsic variability, the development of tools that permit the assessment of individual genetic susceptibility would improve risk stratification and long-term clinical management. If funded, that still wouldn’t be a reasonable control. Maybe I’m missing a key sentence or something, but I’ve read the paper, and it seems to boil down to: “Mutations are bad, and this expensive piece of equipment measures mutations, so we stuck expensive astronaut blood in it, and the gauge pointed to a non-zero number”.
  - michaericalribo 4y ago
    Later: > Variants (SNP/ InDel) generated with this method were compared with a normal dataset using Archer’s analysis pipeline to distinguish noise from a true call. The normal dataset was created with sequencing data from seven young, healthy individuals.
    - gus_massa 4y ago
      From the article: > in this astronaut cohort (median age 44 years, range 37–67), I'd like to see also a comparison with 7 normal persons with ~45 years old. How many mutations is the expected value for a ~45 years old person?
      - deleted 4y ago
        [deleted]
    - hedora 4y ago
      Archer's analysis pipeline isn't a well defined statistical test. It's a UI that browses results from the type of machine they used: https://www.enzymatics.com/news/archer-analysis-pipeline-update-version-3/ https://www.enzymatics.com/news/archer-analysis-pipeline-upd... They filtered the results with various p-values < 0.01. Their supplementary data: https://www.nature.com/articles/s42003-022-03777-z#Sec9 https://www.nature.com/articles/s42003-022-03777-z#Sec9 doesn't say how many samples the machine produced in the first place, but it does say the filter resulted in 35 hits. That tells us absolutely nothing about the rate of mutations in the astronauts vs the general population, or even if astronauts produce more novel mutations on average vs. the general population. On top of that, they seem to have the data to answer these questions, but don't report it anywhere: Do zero-mission astronauts also show a "true call" in Archer's analysis pipeline? They ran multiple samples from the same astronauts (before and after missions). On average, does the same astronaut have more/more-novel mutations after each mission? These would require additional experiments or data, but seem obvious to check: Do they have unusually high or low numbers of mutations vs. the general population at the same age? If so, grouping the general population sample, what other professions also show a "true call" according to the pipeline?

deleted 4y ago

[deleted]

chromatin 4y ago

That information is relatively well known to those familiar with the field of clonal hematopoiesis, and was likely omitted for brevity. It is not reasonable to expect lay public level of background information to be included in every discipline's scientific publications. I'll point you to the two seminal papers in the field of CH though if you are interested. These were published back-to-back in the same issue of NEJM in 2014 (interestingly from separate competing groups at Harvard). https://www.nejm.org/doi/full/10.1056/nejmoa1408617 https://www.nejm.org/doi/full/10.1056/nejmoa1408617 https://www.nejm.org/doi/full/10.1056/nejmoa1409405 https://www.nejm.org/doi/full/10.1056/nejmoa1409405