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  1. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    I thought it'd be interesting to compare the DecodeME result for the tissue analysis to other papers. I searched for "MAGMA tissue" in Google Images, DuckDuckGo Images, and searched in Google Scholar to find other papers that included plots like the one here. Panic disorder: Brain regions are...
  2. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    I don't think that's what's happening though. I'm pretty sure the following is right, but it's hard to find good explanations. MAGMA is fully separate from the part where they selected candidate genes based on things like eQTLs and nearness. Instead they take every gene and assign it a score...
  3. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    wigglethemouse posted them a few posts back. These are in order of significance, with most significant at the top.
  4. forestglip

    Comparing DNA Methylation Landscapes in Peripheral Blood from [ME/CFS] and Long COVID Patients, 2025, Peppercorn et al

    Thanks for pushing back on their paper Hutan. The grouping looks even tighter in chillier's random data.
  5. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    I think the rsids that have a "P" (for proxy) refer to another variant in LD with the DecodeME SNP that they tested in the other cohorts if the other cohorts didn't have the variant in question. The ones you named: 1. GRCh38 variant 13:53194927-GT-G rs35306732 2. GRCh37 variant 13:53750354:A:G...
  6. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    I'm just learning about this, but I think technically these 13 genes weren't necessarily enriched in brain tissue. I'm having ChatGPT explain MAGMA to me, and it says it's basically two different analyses. The 13 highest scoring genes from the first part are likely to play a role in the brain...
  7. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    On the topic of the brain expression, I don't remember much discussion about this yet. While all 13 brain tissues had enrichment of ME/CFS genes, there is an ordering of most to least significant that might give some clues. Written out and grouped: I added pituitary gland even though it...
  8. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    On the topic of "what does DecodeME" show, my feeling is that it's really early for anyone to be saying with much confidence that the genes they found point to any specific pathway. From the DecodeME blog and paper respectively: Here are the candidate genes suggested by DecodeME: Is it...
  9. forestglip

    A first study of cytokine genomic polymorphisms in CFS: Positive association of TNF-857 and IFNgamma 874 rare alleles, 2006, Carlo-Stella et al

    Just adding the context from Wikipedia for why they say candidate gene studies don't replicate:
  10. forestglip

    A first study of cytokine genomic polymorphisms in CFS: Positive association of TNF-857 and IFNgamma 874 rare alleles, 2006, Carlo-Stella et al

    TLDR: They didn't do the replication with a second cohort properly, and the significant SNPs don't replicate in DecodeME. Fukuda criteria. They found significantly more participants had the T allele in the TNF-857 SNP. Also fewer had the A allele in the IFN-γ-874 SNP, but this was much less...
  11. forestglip

    A first study of cytokine genomic polymorphisms in CFS: Positive association of TNF-857 and IFNgamma 874 rare alleles, 2006, Carlo-Stella et al

    A first study of cytokine genomic polymorphisms in CFS: Positive association of TNF-857 and IFNgamma 874 rare alleles N Carlo-Stella, C Badulli, A De Silvestri, L Bazzichi, M Martinetti, L Lorusso, S Bombardieri, L Salvaneschi, M Cuccia Published: 2006 [Line breaks added] Objective In the...
  12. forestglip

    [...] Improvements in Long COVID Symptoms Following [Keto Diet + Lifestyle] —A Clinical Case Report and Review [...], 2025, Colgan, Davenport et al

    Clinically Meaningful Improvements in Long COVID Symptoms Following Ketogenic Metabolic Therapy Combined with Lifestyle Interventions—A Clinical Case Report and Review of the Literature Dana Dharmakaya Colgan, Diane D. Stadler, Aluko A. Hope, Heather Zwickey, Todd E. Davenport, Thomas Weimbs...
  13. forestglip

    Association of TLR9-rs352140 Polymorphism and Serum Levels of CRP, IL-6, and Anti-RBD IgG with the Chance of [Long COVID] , 2025, Alavitabar et al

    Association of TLR9-rs352140 Polymorphism and Serum Levels of CRP, IL-6, and Anti-RBD IgG with the Chance of Developing Long COVID-19 Syndrome Zeynab Alavitabar, Hamed Fouladseresht, Amaneh Javid, Ensiye Torki, Majid Hosseinzadeh Background Long COVID-19 syndrome (LCS) is characterized by a...
  14. forestglip

    Possible long COVID biomarker: identification of SARC-CoV-2 related protein(s) in Serum Extracellular Vesicles, 2025, Abbasi et al

    Thread for the above study: A Pilot Study on the Effects of Exercise Training on Cardiorespiratory Performance, Quality of Life, and Immunologic Variables in [LC], 2024, Abbasi+ Another study from this group: Two-Day Cardiopulmonary Exercise Testing in Long COVID Post-Exertional Malaise...
  15. forestglip

    Prospective associations between major depressive disorder, generalized anxiety disorder, fibromyalgia, and [ME/CFS], 2025, Thomas et al

    Prospective associations between major depressive disorder, generalized anxiety disorder, fibromyalgia, and myalgic encephalomyelitis/chronic fatigue syndrome Nathaniel Stembridge Thomas, Michael C. Neale, Kenneth S. Kendler, Hanna M. van Loo, Nathan A. Gillespie Background Functional...
  16. forestglip

    Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, Gardella+

    Circulating cell-free RNA signatures for the characterization and diagnosis of myalgic encephalomyelitis/chronic fatigue syndrome Anne E. Gardella, Daniel Eweis-LaBolle, Conor J. Loy, Emma D. Belcher, Joan S. Lenz, Carl J. Franconi, Sally Y. Scofield, Andrew Grimson, Maureen R. Hanson, Iwijn De...
  17. forestglip

    News from the USA, United States of America

    I don't see one. I'll make a thread. Edit: https://www.s4me.info/threads/circulating-cell-free-rna-signatures-for-the-characterization-and-diagnosis-of-myalgic-encephalomyelitis-chronic-fatigue-syndrome-2025-gardella.45605/
  18. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    Yeah, I realized after posting that with a small heritability it might still not be very useful.
  19. forestglip

    Preprint Initial findings from the DecodeME genome-wide association study of myalgic encephalomyelitis/chronic fatigue syndrome, 2025, DecodeMe Collaboration

    Unrelated to above discussion: The individual variants aren't going to be diagnostically useful from this study. But I wonder if there might be an attempt to make a polygenic risk score from the DecodeME data and then see how well it classifies patients in other databases.
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