Andrea Ganna

Current landscape of plasma proteomics from technical innovations to biological insights and biomarker discovery - Communications Chemistry Plasma proteome profiling has surged as a promising avenue for biomarker discovery, yet comprehensive platform comparisons remain scarce. Here, the authors evaluate eight proteomics platforms, revealing key differences and complementary strengths, providing crucial insights for researchers into coverage trade-offs and implicating biomarker discovery and clinical applications.

A pretty comprehensive comparison of most actual #proteomics platforms:

Current landscape of plasma proteomics from technical innovations to biological insights and biomarker discovery

www.nature.com/articles/s42...

Thanks to the many biobanks involved!
And particularly Zhiyu Yang for leading this!

Limited overlap between genetic effects on disease susceptibility and disease survival - Nature Genetics Systematic comparison of genome-wide association results for disease risk and disease-specific mortality for nine common diseases across seven biobanks finds limited overlap between genetic effects on disease susceptibility and survival.

Why it matters? progression genetics is more relevant drug targets + clinical care.

👉 Solutions:
• Build larger, harmonized cohorts & refined progression phenotypes
• Use proxy phenotypes from general population

Read: www.nature.com/articles/s41...

🧬💥 Do the genetics that make you develop a disease also help you survive it? Not much.

Our new study in Nature Genetics including 9 disease and 7 biobanks shows:

• Susceptibility variants ≠ survival
• PRSs for onset weak at predicting progression
• Lifespan PRS predicts survival better

Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model Health registers provide valuable insights into individuals’ health trajectories. This study explores the use of deep learning to model and analyze th…

“Towards modeling evolving longitudinal health trajectories with a transformer-based deep learning model”

in collaboration with Pekka Marttinen at @AaltoUniversity

www.sciencedirect.com/science/arti...

User journeys in cross-European secondary use of health data: insights ahead of the European Health Data Space - PubMed The European Health Data Space (EHDS) regulation aims to facilitate cross-border sharing of health data across Europe. However, practical challenges related to data access, interoperability, quality, ...

If you are interested in our pilot use of cross-EU health data ahead of the European Health Data Space implementation, check this out

pubmed.ncbi.nlm.nih.gov/40926479/

Pan-UK Biobank genome-wide association analyses enhance discovery and resolution of ancestry-enriched effects - Nature Genetics Genome-wide analyses for 7,266 traits leveraging data from several genetic ancestry groups in UK Biobank identify new associations and enhance resources for interpreting risk variants across diverse p...

A project many years in the process, we’re pleased to present our work on multi-ancestry meta-analysis across a boatload of traits in the UK Biobank: www.nature.com/articles/s41...

comparing to one clinical prediction model is one way to think about this. the other is about the re-use of generated trajectories for multiple purposes in just one go: readmission rate, mortality, healthcare costs, disease risk and so on…

Thanks Michel! let’s chat. we want to have this pan-european.

Learning the natural history of human disease with generative transformers - Nature Delphi-2M forecasts a person’s future health, covering more than 1,000 diseases, provides insights into co-morbidity dynamics and generates synthetic data for the training of AI models that have never...

Cool work from @ewanbirney.bsky.social Moritz Gerstung, Tom Fitzgerald about modeling health trajectories with generative AI!

www.nature.com/articles/s41...

A Love Letter to Social Science Genetics Some people call social science genetics a minefield. Others call it dangerous, even irresponsible. I call it the most promising field in life sciences.

Some people call it a minefield. Others call it dangerous, even irresponsible. I call it the most promising field in life sciences.

My love letter to social science genetics: communities.springernature.com/posts/a-love...

One argument is that EHR are easily accessible why PRS are used only in research settings. so why bother if we can use already EHRs? showing that PRS provide complementary info makes them potentially useful. True especially for cancer where EHRs are very weak for disease prediction.

@detroiki.bsky.social and @tuomohartonen.bsky.social co-lead this project. We did it as part of INTERVENE. Thanks especially to Estonia Biobank colleagues! Always a pleasure to work together.

@fimm-uh.bsky.social

Check out @tuomohartonen.bsky.social blog post on our study, out today in Nature Genetics, comparing electronic health record-based risk scores with genetic polygenic scores, and how they work better together!

tuomohartonen.substack.com/p/medical-re...

Cross-biobank generalizability and accuracy of electronic health record-based predictors compared to polygenic scores - Nature Genetics Comparison of electronic health record-based phenotype risk scores (PheRS) and polygenic scores (PGS) across 13 common diseases and three biobank-based studies indicates that PheRS and PGS may provide...

Are electronic health records (EHR) more predictive of disease onset than polygenic scores? Can we transfer EHR-based prediction models between countries? Our study on these questions using 3 biobank-based studies with N>845K, is out in @natgenet.nature.com today:

www.nature.com/articles/s41...

Original Sin by Kathryn Paige Harden: 9780593447628 | PenguinRandomHouse.com: Books An intellectually daring and deeply intimate exploration of how genetics complicates our ideas about blame, punishment and moral responsibility—from acclaimed psychologist and author of The Genetic....

I wrote another book & I'm very excited (& nervous) for it to be released into the world: www.penguinrandomhouse.com/books/714593...

Happy to see this online!

Having an extra sex chromosome really challenge the binary definition of sex based on XX and XY. So it is not only a medical, but also an important societal question.

Can you even access cosmos as university researcher?

I’m in general amazed how easy is to combine health data in US. It would impossible for a patient to opt out on the use of their data

Impressive paper by EPIC. They built a autoregressive transformer on 150M individuals and 115 billion
medical events.

Including: diagnoses, medications, lab values, procedure

Cons: model is not shared (and unlikely will be)

arxiv.org/pdf/2508.12104

Of course, if genetics is done routinely, there would be more public acceptance.
But the next frontier is: can an opt-out framework apply to biological specimens collected in clinic? Will this depend on which kind of -omics technique is used ? e.g. It might be ok for LDL but what about WGS?

thanks! to your question: Even now, if a genetic test is done in the clinic, researchers can access without consent under an opt-out framework. EHDS allows that (although countries might put some access restrictions specifically on genetics).

Monthly update - July 2025 Picks of the Month

Papers of the months in Health Data Science

healthdatascience.substack.com/p/monthly-up...

Conclusions: iPSYCH challenged the legal and ethical differences that exist between samples and data. This is a good thing. But, they should have envisioned an opt-out mechanism from the beginning, similar to what the European Health Data Space introduces for health data

I.e. they would not have the "key" to link samples to individuals. Now this fundamental rule has been broken, probably creating more damage than benefits.

Now iPSYCH researchers have been asked to inform participants they are in the study, so they can opt-out.

But this poses a new challenge: researchers have been originally granted access to these samples because there would not be any recontacting of participants.

This is where it gets fascinating: health data can be accessed without consent, but what about biological samples? In many countries, this is not possible, but an IRB allowed iPSYCH researchers to do that.

Is the DNA in a "biological form" different from DNA in a digital form?

This approach has been used in the Nordics for many years and GDPR allows this as "public interest". The counterweight to this "lack of consent" is that individuals should not be recontacted.

iPSYCH, however, did not apply such legal bases simply to "data", but to biological DNA samples.

iPSYCH have been operating without informed consent. An approach that is fairly common when using health data (e.g. EHR/national registers). The idea is that it would be impractical to ask everyone for consent, and it would reduce the study's representativeness.

Blood taken from Danish babies ended up in huge genetic study—without consent The iPsych project, which investigates the genetics of psychiatric disorders, has sent 140,000 opt-out notices amid backlash

The iPSYCH study represents a unique example to understand the ethical and legal challenges of using existing samples/data for health research. A thread 🧵

www.science.org/content/arti...

Dived into past, present & future of human genetics with brilliant students & mentors.Grateful for the chance to present my work on personalized sequence→expression prediction and discussions with @sashagusevposts.bsky.social @bpasaniuc.bsky.social @mashaals.bsky.social @tuuliel.bsky.social & others