OmicSynth proof of concept paper out in AJHG!
It has been a great couple weeks for the team over the holidays, first the large-scale multi-ancestry meta-analysis of Parkinson’s genetics comes out in Nature Genetics … then a few days off for New Year … now the proof of concept paper for the OmicSynth platform is out in the American Journal of Human Genetics.
We all know that drugs developed based on genetics evidence are more than 2x likely to meet approval at regulatory check points, so why not build a modular and scalable platform to assess this for various disease constellations? This is why we built OmicSynth.
Leveraging a combination of multi-omics, single cell sequencing, genome-wide association studies, functional inferences, network memberships and drug annotations, we worked with collaborators at the NIH’s Center for Alzheimer’s and Related Dementias to synthesize all this data and nominate open source drug targets for their diseases of interest!
Some highlights include:
We identify 116 Alzheimer disease, 3 amyotrophic lateral sclerosis (MIM: 105400), 5 Lewy body dementia (MIM: 127750), 46 Parkinson disease (MIM: 605909), and 9 progressive supranuclear palsy (MIM: 601104) target genes passing multiple test corrections.
We created a therapeutic scheme to classify our identified target genes into strata based on druggability and approved therapeutics, classifying 41 novel targets, 3 known targets, and 115 difficult targets (of these, 69.8% are expressed in the disease-relevant cell type from single-nucleus experiments).
Our novel class of genes provides a springboard for new opportunities in drug discovery, development, and repurposing in the pre-competitive space.
In addition, looking at drug-gene interaction networks, we identify previous trials that may require further follow-up such as riluzole in Alzheimer disease.
Open source version of the web platform is here for data exploration.
Amazing effort from the entire team who contributed to the opensource build with CARD.
We are looking forward to future scalable builds for other disease constellations, new collaborators across industry and academia as well as a number of improvements that are already under way such as ingesting your private data and CRISPR screens!