It was researchers, predominantly working in public sector universities & laboratories, who developed many of the ideas & techniques that are now being used on a massive scale by the big tech companies.
Maria Leptin's (@marialep.bsky.social) speech @europarl.europa.eu erc.europa.eu/news-events/...
I see lots of patients with obesity who develop heart attacks. Often they have normal cholesterol, blood pressure and glucose levels are normal.
So why do they get heart attacks?
We identified endotrophin as a mechanism whereby obesity causes heart disease. 🧵
www.nature.com/articles/s41...
Much appreciated, Vadim!
Here's our latest work on proteome profiling of self-sampled dried blood spots to gain insights into the heterogeneity of the immune response against infections and vaccinations. We enrolled random citizens by postal mail to learn more about the molecular effects beyond those seeking medical care.
We finally bring it all together in a knowledge graph, to demonstrate which proteins are good indicators of drug treatment.
Explore here omicscience.org/apps/prot_fo...
We bring this resources directly to your study via enrichment analysis, demonstrating hidden insights and residual confounding among published studies.
github.com/comp-med/r-p...
We demonstrate how this knowledge can guide biomarker identification, reducing candidate lists by almost 40-fold.
This included disease-specific findings like a >2.5-fold increased risk for abdominal aortic aneurysm associated with plasma levels of MMP12.
Not all people are the same, any many factors explaining variance differ across the sexes, but also genetically-inferred ancestry.
Some genetic variants much more important in people of Non-European ancestry.
We demonstrate that some of the variation can be traced back to specific tissues and cell-types, including #Fibroblasts as so far under-appreciated contributing cell-type.
We identify different axes along proteins vary, incorporating >1.7k variables.
We explain >25% of variation for >50% of proteins.
Modifiable factors explained >> non-modifiable factors -> proteins are great as dynamic read out
⭐Preprint alert⭐
Blood #Proteomics can now measure 1000s of proteins, but what can they tell us?
We used #MachineLearning in @ukbiobank.bsky.social to derive the foundations of plasma levels >3k proteins among 40 people.
www.medrxiv.org/content/10.1...