so well deserved! congratulations!!! @pclavell.bsky.social @melelab.bsky.social 🚀⭐️💫

so cool to be part of this work! check it out ⬇️✨

Now online in Blood, the largest genetic study to date of Heavy Menstrual Bleeding, reveals 36 Risk Loci. Most loci are not related to coagulation/hemostasis and instead other biological processes like hormone regulation and Wnt/beta-catenin signaling: pubmed.ncbi.nlm.nih.gov/40324064/

Delighted to share that the revised version of this work on the genetic basis of infertility is now out in @naturegenet.bsky.social ! Give it a read and let us know what you think - rdcu.be/ehEgG 🧬💻

Excited to share our recently published overview of the @estbiobank.bsky.social 🧬
We highlight the unique features of the biobank and the conducted scientific research it has enabled, including the many recall studies that have been carried out over the years!
www.nature.com/articles/s41...

7/ Huge thanks to my amazing mentor Triin Laisk and the brilliant PhD core teammates @jelisavetadzi.bsky.social, @rukinsv.bsky.social – what a journey! 🚀 Grateful to @estbiobank.bsky.social, @finngen.bsky.social, our collaborators & participants. Let’s keep pushing women’s health research forward! 💜

6/ We also explored genetic risk prediction! 🧬
Fanny-Dhelia Pajuste developed a PRS for intrahepatic cholestasis of pregnancy (ICP)—a serious pregnancy complication, which was replicated in the HUNT study by @bnwolford.bsky.social. The PRS showed comparable predictive power to breast cancer PRS.

5/ Population-specific genetic variants in Estonians & Finns helped identify novel genes for uterine fibroids. E.g. a missense variant in MYH11 which encodes for a smooth muscle myosin. A population-specific focus is particularly valuable, since it points at mechanisms relevant across populations.

4/ By analyzing cross-trait genetic & phenotypic correlations, we found shared genetic factors across reproductive health conditions. This is important because identifying shared genetic mechanisms provides insights into shared and disease-specific processes.

3/ We identified 195 genome-wide significant genetic signals, ~40% being novel. Notably, conditions with a metabolic component (e.g., some pregnancy complications) showed higher heritability (10-30%).

2/ We analyzed genetic data from ~300,000 women in the Estonian Biobank & FinnGen to conduct GWAS meta-analyses for 42 female health diagnoses. This helped uncover risk factors & biological mechanisms behind these conditions. Follow below! ⬇️

1/ The women’s health gap contributes to 75 million years of life lost due to health issues. Yet, many female-specific conditions remain under-researched, limiting prevention, diagnosis & treatment. Our study explores this using GWAS, which give hypothesis-free insights into biological processes.

📢 Excited to share our study in @natmedicine.bsky.social
👉 www.nature.com/articles/s41...
We mapped & characterized genetic risk factors for 42 female reproductive health diagnoses. What we found & why it matters? 👇🧵