It is a pleasure to work with Maarja. Congratulations on this well-deserved MSCA Postdoctoral Fellowship!

The impact of low-frequency genetic variants on serum protein levels www.biorxiv.org/content/10.64898/2026.03...

Gene-environment equivalence: The fundamental principle of Mendelian randomization In this Perspective, George Davey Smith and colleagues outline how and why gene-environment equivalence, the fundamental principle of Mendelian Randomization (MR), must be properly applied and critica...

Failure to understand that the fundamental principle of Mendelian randomization (MR) is of gene-environment equivalence contributes to the flood of nonsense MR papers that are appearing; Shah Ebrahim, Gib Hemani and I explain why in this short commentary. journals.plos.org/plosmedicine...

In our new preprint, we develop a genetic proxy for hepatic AGT synthesis inhibition, enabling human genetic validation of a promising emerging antihypertensive target.

AGT is an emerging target of liver-delivered RNA-based antihypertensive therapeutics👇

Nice to see this out! Great work by Kiran Kumar and Sebastian Zöllner!

New online! From DNA microarrays to somatic mosaicism in population cohorts

Portrait of Simone Rubinacci, PhD, smiling and seated, wearing a black top. Blue background. To the right is a quote: "What makes FIMM special is how seamlessly everything is integrated. Biologists, clinicians, and data scientists work closely together, not just in theory but in practice. On top of that, access to large-scale national data enables us to ask questions that simply couldn’t be explored elsewhere." Below the quote: Simone Rubinacci, PhD FIMM-EMBL Group Leader since 2024 Logos of the University of Helsinki and FIMM are at the top right.

We are recruiting 1-2 early-stage Group Leaders in Data Science and AI for Molecular & Health Data!
If you dream of analysing population-scale datasets with cutting-edge tech, Finland is calling!
Apply here by 15 March:
jobs.helsinki.fi/job/Helsinki...
@helsinki.fi @hilife-helsinki.bsky.social

Cool, but looking at the results, it does not actually seem better than others: going from KGP phase 1 to 3, the compres. ratio improves by 2.4x, while others, e.g. XSI improves by 6.4x.
Need a benchmark on large-scale WGS data (I tried, out of curiosity, but I gave up as it requires too much RAM)

🚨 Our parent-of-origin study is out in Nature! 🧬
Maternal and paternal alleles can have distinct — even opposite — effects on human traits, revealing a hidden layer of genetic architecture that standard GWAS miss.
🔗 www.nature.com/articles/s41...

Highlights below!

MetaGLIMPSE: Meta Imputation of Low Coverage Sequencing Data for Modern and Ancient Genomes www.biorxiv.org/content/10.1101/2025.06....