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Ian Berry
@LaughingGenome
clinical laboratory geneticist, exome sequencer, science enthusiast, husband, father
340 Following 577 Followers 1.5K Posts
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So you’re telling me, after nearly quarter of a century of GWAS, after which they’ve discovered not very much about human heritability, that GWAS outcomes are mostly noise? That is… somewhat predictable, I guess (p < 5 × 10−8).
On reflection, I think this paper actually burys the lede about association studies. A more pointed conclusion might be that many tens or hundreds of millions of dollars in functional follow-up on disease-variant associations [1] have been essentially wasted, and are continuing to be wasted, chasing biological noise. Oops.View quoted post on X
The lines of reasoning is about as follows. If we assume:
1. Most traits are highly polygenic, such that in the limit approximately every gene is associated (via a regulatory association) to every trait
2. Ranking single-variant associations by 'significance' is effectively arbitrary because the ranking is dominated by allele frequencies/drift
Then:
3. Any gene prioritization that comes from a single-variant association study (as currently analyzed) is uninformative about trait biology [2].
4. Functional studies looking to understand the impact of the 'top' GWAS hits for traits are not in fact studying the most 'important' genes for those traits, but rather an effectively random subset of genes
5. The amount of money spent on the functional studies in point 4 measures at least in the tens or hundreds of millions of dollars over the past decade, and probably billions [3]
Am I missing something @spence_jeffrey_ @Hakha_Most @jkpritch ?
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[1] E.g. grants.nih.gov/grants/guide/p… and many others like it
[2] But note the single-variant ranking is of course extremely important for trait prediction and applications where 'realized heritability' is what matters
[3] NHGRI budget alone is ~$700M/year genome.gov/sites/default/…
Nearly a clean sweep of the top five for @NickLutsko … open.spotify.com/wrapped/share/…
And this isn’t at all dangerous or ethically questionable…
Try submitting x-ray, PET, MRI or other medical images to Grok for analysis.View quoted post on X
This is still early stage, but it is already quite accurate and will become extremely good.
Let us know where Grok gets it right or needs work.
And, presumably, identifying all those who have a nonorganic form of kidney disease. Massively under-diagnosed worldwide. In England, the Genomic Medicine Service has ensured more equitable access, including whole genome sequencing for suspected genetic cystic renal disease.
Study of kidney disease hospitalizations finds that genetic kidney disease leads to higher & more costly admissions than non-genetic chronic kidney disease, highlighting the need for tailored secondary prevention & resource allocation bit.ly/3U0kpHa @AndrewMallett8 #GIMOView quoted post on X