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They give the example of HMGCR, an enzyme involved in cholesterol synthesis. Variants in the HMGCR gene identified by GWAS have only a small effect (I've read SNPs had an OR ≥ 0.9). However, drugs such as statins, which inhibit HMGCR, produce large reductions in cholesterol land cardiovascular...

RS stands for the relative probability of success (expressed relative to drug targets without genetic support). The authors extracted data on drug development from Citeline Pharmaprojects for monotherapy programmes added since 2000. The interesting figure is 1D. showing that RS is not...

Chris Ponting pointed to this study following the publication of DecodeME to argue that small effect size in SNPs do not indicate what the potential effect of a drug would be...

I'd also be interested in the full text if someone has acces.

I've been trying to understand this through a made-up analogy. Thought I might share it to see if it holds and if others find it useful or not. Suppose an illness is caused by a structure somewhere in the body that lets cells through that it should hold back, like a dam that is breaking. There...

It's not really important so no problem if they don't find the time to look at this. It's probably because I don't have any experience with GWAS that I don't fully understand.

This might warrant its own thread because it has a lot of info and advice that is not available in other formats. I made this thread about it on social media: 1) There's a new document with care advice for patients with (very) severe ME/CFS. It was published by the Austrian Society for...

The DecodeME participants were 85% females themselves. I think it's the default of GWAS because sex chromosomes have additional difficulties to analyze see: eXclusionarY: 10 years later, where are the sex chromosomes in GWASs? - PMC EDIT: added quote from the paper above

I kind of picked examples with high heritability though. There are other diseases with similarly low heritability estimates such as rheumatoid arthritis so the estimate for ME/CFS is nothing weird. But perhaps a bit lower than some expected.

I think it was this study: Repurposing large health insurance claims data to estimate genetic and environmental contributions in 560 phenotypes (2019) Lakhani et al. | Science for ME Here's the overview from Dibble et al.

To clarify: the link to the Neal lab data includes a search function where you can find the heritability estimate for other diseases using UKB methods similar to what DecodeME used. It seems that ME/CFS isn't like schizophrenia, Crohn's disease or diabetes type 1 for example, which have a...

I got the impression that the ME/CFS estimate still seems quite low compared to other diseases using the same method https://nealelab.github.io/UKBB_ldsc/h2_browser.html https://pmc.ncbi.nlm.nih.gov/articles/PMC3469463/

Something that hasn't been discussed much is the low heritability estimate This was estimated using linkage disequilibrium score regression ( LDSC). If I understand correctly the method is relatively simple: it does a regression analysis of linkage disequilibrium (how much SNPs correlate with...

In an interview with David Tuller, Ponting also said something interesting (starting at minute 21:23):

Yes it seems that figuring out where the signal comes from is quite difficult. The MAGMA gene-tissue analysis for example, used a different approach than FUMA + coloc and suggested different genes (given in supplementary table S4). Interestingly it suggests LRRC7 for the location on chromosome...

In the data analysis plan there was the suggestion of combining the DecodeME and UKB ME/CFS cases to get more power. Was this done or was the idea that the UKB ME/CFS cases are too unreliable?

Thanks, and big thanks to the DecodeME team for uploading all this info! This is all quite new to me so apologies for any errors or dumb questions. I think the INFO score give an indication if the imputation went well by comparing the variance of the dosage (expected number of alternative...

That's probably because 90% of texts and papers on ME/CFS talk about weak data and all these possible connections that have no sound basis. I wonder if you would get better results if you call it illnessX and describe it yourself with what are considered the most robust findings. You could also...

Most (around 90%) of the SNP results are imputed if I understand correctly, not just the HLA region. I'm trying to find info that says which ones were actually measured and which ones imputed.

Anyone who can point me to this study? Seem to have missed it.