Dear Solutions Lab,
My name is Alaa Gouda. I am a PhD researcher at Teesside University my project involves using bioinformatics techniques, particularly spatial transcriptomics, to enable early detection of neurodegenerative diseases, especially Lewy body dementia and Parkinson’s disease.
I am currently struggling with data availability in this area. I am reaching out to ask if you have access to spatial transcriptomics datasets relevant to these diseases, or if you could guide me to resources, databases, or collaborators where I might obtain such data.
Any help or advice would be greatly appreciated.
Dear Alaa,
Happy to help!
There are tons of resources out there for Parkinsons/ Lewy body omic datasets, but as far as I’m aware, not a a great deal of well-powered spatial transcriptomic data (if anyone reading this knows of any, please share in the comments). A good starting point I go for when seeking out the type of data you’re after is either the synapse or broad institute single cell portal. Both allow quite specific searches and have a lot of available datasets.
If you’re interested in early changes to detect Parkinson’s, I would also check out the Parkinson’s Progression Marker’s Initiative database which is a fantastically characterised PD cohort with tons of -omic outcomes measured (albeit principally in biofluids). I’d also check out the partner dataset FoundIn-PD, which is a goldmine of omic characterisation of patient derived dopaminergic iPSC samples. Neither PPMI nor FoundIn-PD have spatial data though (to my knowledge), but may be well suited to meet some of your general research aims.
If you’re after more specific datasets, I’d point you towards the Goralski 2024 paper. I’ll note that the Nanostring GeoMX methods used in this dataset are different from other “single-cell” spatial data. The majority of the data from this dataset is neuron-specific and you can think of more as a sorted-cell experiment with an added broad level of spatial metadata. They do also have CosMX data which does resolve single cells, but I believe in this study, just from mouse samples. I’d also check out the Kamath 2022 data. As with the other dataset, the Slide-Seq spatial data from this study is non-human (it’s generated in primates), but there is a wealth of single cell PD data in this publication that might suit your purposes.
I hope some of these resources are useful and good luck!
Nature Careers Blog
Dr Becky Carlyle
Hi Josh,
Just to thank you very much for taking the time to respond to Alaa’s query. This is invaluable information for our project. We have followed up a lot of your recommendations.
Best wishes,
Ahmad (Alaa’s PhD supervisor)