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Protein biomarkers predict dementia 15 years before diagnosis in new study

warwick.ac.uk

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Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#41

Post by buyohmarkers »

mbreese wrote: post #25
buyohmarkers wrote: post #14

GFAP as dementia biomarker isn't a new discovery. Here's a 2023 meta-analysis that used papers as old as 2020. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10177296/

> Proteins (for example Glial Fibrillary acidic protein, GFAP) had previously been identified as potential biomarkers for dementia in smaller studies, but this new research was much larger and conducted over several years. The article (University press release) does mention this... but seeing a known suspect in the biomarker list would lend some confidence to any novel biomarkers found. So, it's good to see multiple…

Totally a good thing. There's a very long list of biomarker failures, and there's lots of analysis into why so many biomarkers fail in clinical applications.

One starting point for reading: https://academic.oup.com/clinchem/article/59/1/202/5622131

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#43

Post by [deleted] »

dang wrote: post #28
ekianjo wrote: post #13

Earlier quoted context omitted.

people thought for years that amyloid plaques were driving the disease only to be proven utterly wrong you might want to have a bit of humility when dealing with complex systems

Can you please not post in the flamewar style? You've broken the site guidelines here and we've already had to ask you not to do that. https://news.ycombinator.com/newsguidelines.html Edit: actually, since your recent comments look like this, I've banned the account: https://news.ycombinator.com/item?id=39341879 https://news.ycombinator.com/item?id=39341602 https://news.ycombinator.com/item?id=39341585 https://news.y…

[deleted]

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#44

Post by jcims »

dang wrote: post #28
ekianjo wrote: post #13

Earlier quoted context omitted.

people thought for years that amyloid plaques were driving the disease only to be proven utterly wrong you might want to have a bit of humility when dealing with complex systems

Can you please not post in the flamewar style? You've broken the site guidelines here and we've already had to ask you not to do that. https://news.ycombinator.com/newsguidelines.html Edit: actually, since your recent comments look like this, I've banned the account: https://news.ycombinator.com/item?id=39341879 https://news.ycombinator.com/item?id=39341602 https://news.ycombinator.com/item?id=39341585 https://news.y…

Thank you for all of the work you do to keep this as civil a place one could possibly expect to find that’s open to the general public on the internet.

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#45

Post by pama »

rwmj wrote: post #38
bglazer wrote: post #10

One caveat is that this is necessarily a retrospective study. The authors looked at historical data from the UK Biobank, ran a regression, and found these genes. So, it’s not really clear if these genes are actually causing dementia, or if they’re just related to a common cause, or (most likely) tied together through some very complicated web of biological mechanisms. That said, they’re interesting genes. GFAP is exp…

If it's predictive, does it matter?

Yes it does. Think of typical notions of statistical significance when testing one new idea prospectively, say the concept of a p-value, or the AUC used in the paper. Now think instead of a rich dataset and you are free to fish for any of the possibly tens of thousands of signals for one signal or a combination of signals that match your result. Loosely speaking you are overfitting and the threshold for being surprised or having statistical significance is now much more strict.

https://en.wikipedia.org/wiki/Bonferroni_correction

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#46

Post by Fluorescence »

rwmj wrote: post #38
bglazer wrote: post #10

One caveat is that this is necessarily a retrospective study. The authors looked at historical data from the UK Biobank, ran a regression, and found these genes. So, it’s not really clear if these genes are actually causing dementia, or if they’re just related to a common cause, or (most likely) tied together through some very complicated web of biological mechanisms. That said, they’re interesting genes. GFAP is exp…

If it's predictive, does it matter?

I guess one issue is that our environment changes so that what was predictive for the past isn't for the present day.

Can gene expression be affected by pollutants more common decades ago like abestos, coal-dust or leaded petrol? It would be frustrating to only discover this in 15 years time.

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#47

Post by Maxion »

bglazer wrote: post #10

One caveat is that this is necessarily a retrospective study. The authors looked at historical data from the UK Biobank, ran a regression, and found these genes. So, it’s not really clear if these genes are actually causing dementia, or if they’re just related to a common cause, or (most likely) tied together through some very complicated web of biological mechanisms. That said, they’re interesting genes. GFAP is exp…

But it is not a retrospective study? They took blood samples at baseline from all participants, and later on some developed dementia?

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#48

Post by rwmj »

pama wrote: post #45
rwmj wrote: post #38

Earlier quoted context omitted.

If it's predictive, does it matter?

Yes it does. Think of typical notions of statistical significance when testing one new idea prospectively, say the concept of a p-value, or the AUC used in the paper. Now think instead of a rich dataset and you are free to fish for any of the possibly tens of thousands of signals for one signal or a combination of signals that match your result. Loosely speaking you are overfitting and the threshold for being surpris…

Sure, but let's say that we test this and it is predictive on new data (not overfitting), but we have no idea at all how it works. It's still a useful test.

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#49

Post by bglazer »

Maxion wrote: post #47
bglazer wrote: post #10

One caveat is that this is necessarily a retrospective study. The authors looked at historical data from the UK Biobank, ran a regression, and found these genes. So, it’s not really clear if these genes are actually causing dementia, or if they’re just related to a common cause, or (most likely) tied together through some very complicated web of biological mechanisms. That said, they’re interesting genes. GFAP is exp…

But it is not a retrospective study? They took blood samples at baseline from all participants, and later on some developed dementia?

For this to be prospective rather than retrospective, they would have developed the risk model beforehand.

Re: Protein biomarkers predict dementia 15 years before diagnosis in new study

#50

Post by pama »

rwmj wrote: post #48
pama wrote: post #45

Earlier quoted context omitted.

Yes it does. Think of typical notions of statistical significance when testing one new idea prospectively, say the concept of a p-value, or the AUC used in the paper. Now think instead of a rich dataset and you are free to fish for any of the possibly tens of thousands of signals for one signal or a combination of signals that match your result. Loosely speaking you are overfitting and the threshold for being surpris…

Sure, but let's say that we test this and it is predictive on new data (not overfitting), but we have no idea at all how it works. It's still a useful test.

The retrospective regression on a specific dataset might discover a true correlated quantity, if any true correlated quantities were there and their signal was more prominent than the combinations you get from the noise. However, this analysis will always discover a quantity that correlates, by design. These retrospective studies can prompt prospective studies for a correlated quantity (a biomarker in this case) and the careful analysis of the retrospective study methodologies and results can suggest the design of such prospective studies; if a prospective study works, then that is fantastic. The retrospective studies are mostly there for statisticians to figure things out for future tests, except when the signal is simple and phenomenal.
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