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This was a lovely talk last week, nice to see it out. Could follow even as a simple clinician, and having had >1 beer the night before which is the sign of an excellent methodological talk!

We have an exciting 3-yr postdoc position at Imperial College London using molecular #epidemiology to understand adiposity-driven pancreatic #cancer. Possibility of hybrid working. Deadline 24/07 Mattias Johansson Richard Martin @Karl_SmithByrne Emma Vincent Pls retweet🙏 twtr.to/4oSz9

Happy to share the latest work led by Krista Freimann in my lab. We performed the largest trans-eQTL meta-analysis in a single cell type: 3,734 LCL samples from 9 individual studies. medrxiv.org/content/10.110…

Can proteomics complement disease risk prediciton❓ 👉New data from the UKB-PPP project (N=41,931) suggest it could. 📊Adding 5 to 20 proteins to clinical data/assays led to improved 10-year prediction models for 67 pathologically diverse diseases 🔗nature.com/articles/s4159…

Nice comparison of MR methods by Xianghong Hu published at AJHG AJHG (sciencedirect.com/science/articl…) - which concludes that the best MR method out of 16 considered is... the method that their group developed!

We need your help! 😃 We are interested in how people interpret language used in healthcare reporting and how it could be improved. Please take a few minutes to complete our questionnaire 👇 tinyurl.com/CausalQuest Stephen Burgess Amy Mason

Thrilled to see this out in Genome Research! We here enable risk predictions using GWAS summary stats, unlocking biomarker discovery without follow-up data. Led by Daniel Sens in collab with Bjoern Eskofier. Helmholtz Munich | @HelmholtzMunich PioneerCampus @HelmholtzMunich TU München doi.org/10.1101/gr.279…

Largest to-date GWAS for heart failure🧬❗️ 👉207,346 cases/2,151,210 controls 👉176 risk loci + 4 genes in pLoF variant burden test 👉expl. heritability of rare & common variants: 2.2% & 4.3% 📰Preprint: medrxiv.org/content/10.110… 📊Summ stats: to be released upon publication

Our paper on misleading biases in AD GWAS-by-proxy is published Nature Genetics. We identify the source of biases and explore strategies to reduce them Yuchang Wu Zhongxuan(John) Sun Paper📰: doi.org/10.1038/s41588… Software🧑‍💻: github.com/qlu-lab/GSUB Sumstats⬇️: qlu-lab.org/data.html

Excited to share our work at #ASHG24! My lab at Penn is hiring - reach out if interested in studying complex trait genetics using large biobanks.

Amazing new GWAS resource for CSF and brain metabolite levels (Metabolon, Inc.)🧠🧬 👉2,602 CSF samples of 440 metabolites 👉1,016 brain samples of 962 metabolites 📜Paper: nature.com/articles/s4158… 📊Summ stats: ebi.ac.uk/gwas/ [accession numbers GCST90317902–GCST90319303]

My first PhD student Lianyun_Huang has now successfully defended her PhD and is now Dr Huang! 🎉🎉🎉 Thank you for 4 years of hard work, it’s an honor to be part of your academic journey!

Very excited to share our latest publication in Nature Genetics! Our manuscript shows how Mendelian Randomization (MR) isolates putatively causal links between cell-type specific gene expression & brain phenotypes. nature.com/articles/s4158… Tweetorial below 👇

4/ Combining disease and control tissue is common practice to maximize discovery power; however, we show that up to 41% of eQTLs interact with disease even after correcting for disease status. These relationships are important to clarify for downstream causal inference.

6/ Many interaction-QTLs also influence colocalization; Notably, 23.6% of colocalizations showed disease dependency—e.g., TP53INP1 in the full cohort vs. controls-only.

14/ What’s next? Landmark! The Landmark project is a public-private partnership involving GSK, Novartis, Roche and UCB with the hope to find novel targets for Parkinson’s Disease, currently the fastest growing neurological condition in the world.imperial.ac.uk/news/256397/la…

Diffusion imaging (MRI) captures early changes associated with cerebral small vessel disease🧠 👉Peak width of skeletonized mean diffusivity (PSMD) is among the most promising biomarkers 👉A new GWAS and ExWAS study explores the genetic architecture of PSMD in N=58,403🧬