I spent my PhD developing novel genomic technologies, and today I am extra excited to share the last bit of this work, which is a multiplex prime editing (PE) screening framework! (1/n) biorxiv.org/content/10.110…

A new preprint by Gupta et al. reports a missense variant that cancels out the pathogenic effects of APOL1 risk variants for kidney disease in African Americans. This is one of the most impressive disease modifier variants I’ve seen so far. Let’s dive deep

Variation in telomere length (TL) is associated with human disease and aging. In our new preprint, we identify novel genetic determinants of TL using whole-genome sequence data from ~500K UK Biobank participants medrxiv.org/content/10.110…

It's human plasma-protein day @nature! Correlations with health, disease, rare variants nature.com/articles/s4158… nature.com/articles/s4158… nature.com/articles/s4158… UK Biobank deCODE genetics AstraZeneca

Breakthrough research published today in nature shows never-before identified connections between rare genetic variants and proteins. By applying insights from these findings to our ongoing drug discovery efforts, we are turning science into medicine: learn.az/6015uM6ZD

Thrilled to see our paper on rare variant associations with plasma protein levels in the UK Biobank published in @nature today nature.com/articles/s4158… Summary statistics are publicly available at azphewas.com and an interactive portal astrazeneca-cgr-publications.github.io/pqtl-browser/i…

Excited to announce an update to the AstraZeneca PheWAS Portal azphewas.com! Now includes ~470K UK Biobank participant exomes and new rare variant associations for ~3k plasma protein levels from our paper published in nature today tinyurl.com/4h58857f

Super excited to share our preprint on inferring biomarker signatures across 3,308 binary traits from UK Biobank leveraging 67 quantitative traits with #MILTON & boosting PheWAS signals. medrxiv.org/content/10.110…

Nature research paper: Genotyping, sequencing and analysis of 140,000 adults from Mexico City go.nature.com/45lE0UY

We're recruiting! If you have expertise in in large-scale data analysis and are interested in using human genomics data to improve safety assessment of drug targets, this postdoc role in AstraZeneca's Centre for Genomics Research could be your next step. tinyurl.com/bdexc2z3

More than 500,000 genomes are linked to over 15 years of health data. This new global health resource has the potential to advance drug discovery and development of new medicines. It shows what collaboration can achieve. #500KGenomes #WhatScienceCanDo

1. Really excited to share our work using saturation genome editing to generate a variant effect map of the gene DDX3X. nature.com/articles/s4146…. It’s been a privilege to lead this work together with HongKee TAN, with brilliant mentorship from Matt Hurles and @GeretySebastian. A 🧵:

An updated, more diverse iteration of gnomAD – the human genetic database that has transformed out ability to diagnose rare diseases – will help us study the non-coding genome, say @ryandhindsa & Slavé Petrovski go.nature.com/3t6Wrjc

📣 Exciting news! We are taking another stride towards democratising worldwide access! Registered researchers in developing countries may save on data application costs through our newly launched Global Researcher Access Fund 🌍. More details here: ow.ly/JNjU50RbowA

When chronic and rare disease worlds converge bit.ly/45M8IIw Sharon Barr, head of BioPharmaceuticals R&D at AstraZeneca, discusses her chronic disease research priorities, including new diagnostic tools, fixed-dose drugs and a better understanding of disease biology.

Our paper on telomere length (TL) genomics using UK Biobank whole-genome sequencing (WGS) data for over 460K individuals is now out in Nature Genetics. nature.com/articles/s4158… 1/3

Thrilled to see our latest research on early disease prediction, biomarker discovery and novel target detection published in Nature Genetics! 🚀 🎉 nature.com/articles/s4158… AstraZeneca #CGR #MachineLearning #Biomarkers #AI #UKBiobank #HealthcareInnovation #DataScience

MILTON🤖: a model trained on 67 lab/clinical traits (N=500k) + 3K Olink proteins (N=50k) to predict ICD10 diagnoses 👉equal performance for prevalent/incident disease 👉AUCs >0.9 for 121 codes 👉augments case selection for genetic studies🧬 nature.com/articles/s4158…

Delighted to contribute to this new work published last week in Nature Genetics on disease prediction. If our aim is to empower prevention of disease by producing the most powerful and accurate prediction tools then it makes sense to explore any and all data that might be

Interesting work based on MCPS cohort showing ancestry-specific risk of clonal hematopoiesis (CH). Comparing MCPS vs UK Biobank, CH is 1.6 fold less frequent in MCPS participants. Even within MCPS, higher proportion of Indigenous American ancestry is associated with lower risk of