Beatriz Urda
@beatrizurda.bsky.social
120 followers 320 following 31 posts
PhDing at Barcelona Supercomputing Center | Exploring disease co-occurrences through omics, bioinformatics & HPC — with an eye on AI bias, and occasionally covered in clay.
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beatrizurda.bsky.social
1/ Everything that could go wrong in paper publishing… did.
A story of patience, absurdity, and persistence 🌀 <1min

From Alfonso Valencia’s lab and a very stubborn PhD student (me).
Reposted by Beatriz Urda
jackamatica.bsky.social
Some diseases show up together. Others rarely appear in the same person

This study looked into whether gene activity (from RNA data) can help explain why

The answer: yes - more than we thought

Relevant as we are testing RNA in LC & ME/CFS patients @amaticahealth

Breakdown:
Reposted by Beatriz Urda
bsc-cns.bsky.social
💻🧬'Los vínculos secretos que existen entre enfermedades.
El estudio del BSC representa el mayor esfuerzo hasta la fecha para explicar científicamente las asociaciones clínicas entre enfermedades'

🗞En @innovaspain.bsky.social
www.bsc.es/4kD

@alfonsovalencia.bsky.social @beatrizurda.bsky.social
Reposted by Beatriz Urda
newsmedical.bsky.social
🧬 New research in PNAS shows how gene expression patterns reveal why some diseases occur together while others don’t.

Scientists uncovered hidden links — with immune pathways playing a major role.

#GeneExpression #Comorbidity #PrecisionHealth

🔗 www.news-medical.net/news/2025090...
Gene expression maps explain why diseases often occur together
This study reveals how gene expression patterns uncover molecular pathways linking comorbidities, enhancing treatment strategies for overlapping diseases.
www.news-medical.net
Reposted by Beatriz Urda
lmrocha.bsky.social
Great #networkmedicine work by @alfonsovalencia.bsky.social's team on deriving comorbidity networks from RNA-seq data to study complex disease relationships. Thy show that molecular mechanisms are behind many of the known comorbidities (often via immune response).
doi.org/10.1073/pnas...
Patient stratification reveals the molecular basis of disease co-occurrences | PNAS
Epidemiological evidence shows that some diseases tend to co-occur; more exactly, certain groups of patients with a given disease are at a higher r...
doi.org
Reposted by Beatriz Urda
0817686.bsky.social
No le habéis hecho mucho caso a esto, pero es muy, muy bonito. Y parece revolucionario. Seguro que volveremos a oír hablar de esto.
beatrizurda.bsky.social
In the end, comorbidities aren’t random,
they can be predicted from the expression of our genes 🧬

And this is just the beginning.
Stay tuned for what comes next 👀🚀
beatrizurda.bsky.social
This was devastating.
Reposted by Beatriz Urda
beatrizurda.bsky.social
Totally! In our case it wasn’t even about sample size, but a basic textbook statistical concept 🤖. We even increased the sample size to show the results still held under the reviewer’s definition—and still, they wouldn’t budge.
beatrizurda.bsky.social
Totally! In our case it wasn’t even about sample size, but a basic textbook statistical concept 🤖. We even increased the sample size to show the results still held under the reviewer’s definition—and still, they wouldn’t budge.
beatrizurda.bsky.social
Muchas gracias por compartir!
Reposted by Beatriz Urda
genteque.bsky.social
Brutal. Investigadores usando el Centro Nacional de Supercomputación (BSC-CNS) han encontrado conexiones clínicas desconocidas (p.e. entre la enfermedad de Crohn y el desarrollo de úlceras), cosa que permitirá mejorar el tratamiento/medicación. Además, todos podemos ya ver toda esa (sigue 🧵)
Reposted by Beatriz Urda
alfonsovalencia.bsky.social
She explains part of the fight over 2 years with an absurd referee (can happen) and an incompetent profesional editor unable to understand even basic statistics - or worse unable to take a decision by him/her self.

But never mind: Beatriz won and the paper is now published in a better journal.
beatrizurda.bsky.social
1/ Everything that could go wrong in paper publishing… did.
A story of patience, absurdity, and persistence 🌀 <1min

From Alfonso Valencia’s lab and a very stubborn PhD student (me).
Reposted by Beatriz Urda
alfonsovalencia.bsky.social
Very happy to get it out.

For scientific & personal reasons this one is special.
Beatriz has done more work and endured the most difficult - and absurd - publications battles I can remember.
Thanks to PNAS for being "normal" and congratulations to Beatriz.

(Beatriz: next one will be easier!)
beatrizurda.bsky.social
🚨 New in PNAS!
🧬 64% of disease co-occurrences can be explained by transcriptomic similarities.

Comorbidities aren’t random—they have a molecular basis.

Here’s how we found it 👇 (1/n)

🔗 doi.org/10.1073/pnas.2421060122

@alfonsovalencia.bsky.social
beatrizurda.bsky.social
12/ This was the road.
👉 Here is the science: bsky.app/profile/beat...
📄 Paper: doi.org/10.1073/pnas.2421060122
beatrizurda.bsky.social
11/ Endless thanks to those who supported, listened, laughed, and advised: my colleagues, Davide Cirillo, and especially @alfonsovalencia.bsky.social, for his unwavering support throughout this wild journey. @bsc-cns.bsky.social
beatrizurda.bsky.social
10/ And yes– I am officially fluent in rebuttals 🥋 It even helped me win Best Talk at ISMB/ECCB 2025 NetBio– for the science, the presentation, and (yes) the Q&A. #ISMBECCB2025
beatrizurda.bsky.social
9/ I wouldn’t wish this road on anyone.
But I’m proud we used the struggle to dig deeper– and that’s where we found some of the most interesting science.

🧬 Novel, underdiagnosed links & mechanisms with therapeutic potential
🧍Works even for rare diseases
🌐 A truly useful resource for the community
beatrizurda.bsky.social
8/ Science already takes time, I hope to help make it worth it.

Finally, terrified, we sent it to PNAS @pnas.org.
After one round of review, reports came back: supportive. Positive.
Accepted 🎉 🎉
beatrizurda.bsky.social
7/ What I learned:
Publishing can be arbitrary.
Some reviewers make up their minds before seeing the evidence.
One reviewer can wield disproportionate power.
Rebuttals must be painfully clear.
Editors often fail to step in, even when the situation is obvious.
Don’t assume fairness in peer review
👇