Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights, 2026, Hoel, Fluge, Mella+
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Tree
Senior Member (Voting Rights)
Hi Butter,
Interesting that you were tested for that. Was that as part of a study or something available to the public?
Tree
Senior Member (Voting Rights)
If you do not mind me asking, you seem to have a vast knowledge of all these studies. How do you keep track and organize these studies?
I struggle to keep track so was interested in how you do it.
ME/CFS Science Blog
Senior Member (Voting Rights)
I try to follow ME/CFS research as closely as I can and sometimes write blogs about them. For example, at the end of the year I write an overview of the most interesting studies of the year, which helps to keep track of the most important ones.
https://mecfsskeptic.com/2024-looking-back-on-a-year-of-me-cfs-research/
I also notice that I tend to ignore the less quality studies more and more. Many papers just aren't worth the time and effort.
I find PXDN very interesting too.
Here's a link to a post I made about earlier findings:
Myopathy as a cause of fatigue in long-term post-COVID-19 symptoms: Evidence of skeletal muscle histopathology, 2022, Hejbøl et al
Was told once by a senior researcher in materials science that when he gets a paper to read he goes straight to the methodology section, and doesn't read the full paper until he knows it is worth reading. Said it saved him a lot of time.
HLA-C has the 39th highest fold change out of the 7326 aptamers they tested (logFC = 0.35). Not significant though (p=.19, q=.45).
Here are all the ones they tested that mentioned HLA:
Edit: Mistyped the q-value.
Here are all the ones they tested that mentioned HLA:
Edit: Mistyped the q-value.
Last edited:
wastwater
Senior Member (Voting Rights)
Homozygous Mutations in PXDN
Cause Congenital Cataract, Corneal Opacity,
and Developmental Glaucoma
Cause Congenital Cataract, Corneal Opacity,
and Developmental Glaucoma
ME/CFS Science Blog
Senior Member (Voting Rights)
Noticed this thread on Twitter which may be useful to merge data with different names for the same gene ID.
Thread by @tangming2005 on Thread Reader App
@tangming2005: 1/ You’re merging gene data across tools. Suddenly nothing matches. ENSEMBL, ENTREZ, TP53, P53… Why so many gene IDs? 2/ Gene ID chaos is real. One gene, three names: ENSEMBL ID, ENTREZ ID, gene symbo...…
threadreaderapp.com
Chandelier
Senior Member (Voting Rights)
https://doi.org/10.1016/j.xcrm.2026.102647
Now published as:
Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights
• Tissue-linked shifts show reduced intracellular and increased secreted proteins
• Immune signatures show reprogramming with reduced neutrophil-derived proteins
• Regulatory networks link immune, vascular, and metabolic dysfunction
We apply aptamer-based serum proteomics to 50 ME/CFS patients and 29 healthy controls, analyzing 7,326 protein targets.
We identify 1,823 aptamers with significant differences between the groups (845 after false discovery rate [FDR] correction).
Distinct patterns of tissue- and process-specific changes are seen.
There is a broad increase in secreted proteins, while intracellular proteins, e.g., from skeletal muscle, particularly show reduction. Immune cell-associated signatures indicate immune reprogramming, including a distinct reduction in proteins secreted by activated neutrophils.
Focused secretome analysis supports intensified regulatory interactions related to immune activity, inflammation, vasculature, and metabolism.
Validation of measurements using antibody-based methods confirms findings for a selection of proteins.
The uncovered serum proteome patterns in ME/CFS patients may contribute to understanding the pathophysiology and inform future biomarker research and therapeutic development.
Now published as:
Charting the circulating proteome in ME/CFS using cross-system profiling to uncover mechanistic insights
August Hoel<a>1</a>,<a>2</a>,<a>7</a> ∙ Fredrik Hoel<a>1</a>,<a>7</a> ∙ Sissel Elisabeth Dyrstad<a>1</a> ∙ Henrique Chapola<a>1</a> ∙ Ingrid Gurvin Rekeland<a>3</a> ∙ Kristin Risa<a>3</a> ∙ Kine Alme<a>3</a> ∙ Kari Sørland<a>3</a> ∙ Karl Albert Brokstad<a>4</a> ∙ Hans-Peter Marti<a>2</a>,<a>5</a> ∙ Olav Mella<a>3</a>,<a>6</a> ∙ Øystein Fluge<a>3</a>,<a>6</a> ∙ Karl Johan Tronstad
Highlights
• Serum proteomics reveals widespread protein changes in ME/CFS patients• Tissue-linked shifts show reduced intracellular and increased secreted proteins
• Immune signatures show reprogramming with reduced neutrophil-derived proteins
• Regulatory networks link immune, vascular, and metabolic dysfunction
Summary
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a debilitating condition often triggered by infections, with unclear mechanisms and no established biomarkers or treatments.We apply aptamer-based serum proteomics to 50 ME/CFS patients and 29 healthy controls, analyzing 7,326 protein targets.
We identify 1,823 aptamers with significant differences between the groups (845 after false discovery rate [FDR] correction).
Distinct patterns of tissue- and process-specific changes are seen.
There is a broad increase in secreted proteins, while intracellular proteins, e.g., from skeletal muscle, particularly show reduction. Immune cell-associated signatures indicate immune reprogramming, including a distinct reduction in proteins secreted by activated neutrophils.
Focused secretome analysis supports intensified regulatory interactions related to immune activity, inflammation, vasculature, and metabolism.
Validation of measurements using antibody-based methods confirms findings for a selection of proteins.
The uncovered serum proteome patterns in ME/CFS patients may contribute to understanding the pathophysiology and inform future biomarker research and therapeutic development.