Can AI reveal the risk and co-pathology of multiple neurodegenerative diseases from just a single blood sample? We explored the AI-based diagnostic power on a massive sample (N=17,170) and high-rank plasma proteomics data. #MedSky #neuroskyence #neurosky.

RT @jpreventionalz1: CTAD taskforce: genetic therapies in Alzheimer’s disease. D. Jakabek et al. #AlzheimersDisease….

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RT @KopalJakub: Out now in @natBME: We explore how rare high-effect gene-coding variants (#CNVs) shape brain architecture and influence cog….

Check out lab's latest preprint for MRI super resolution!!!.

RT @NatRevNeurosci: Rethinking excitation/inhibition balance in the human brain — a Comment article by Roi Cohen Kadosh. .

RT @bttyeo: 1/11 Excited to share our @Naturestudy led by @Leon_Oo1 @csabaorban @ZShaoshi. It is well-known that A….

RT @Ali_bioinformtx: We’re excited to share our latest publication in.@NatureMedicine, where we conducted the largest plasma proteomics stu….

RT @_JakeVogel_: ‼️New preprint‼️ . Super excited to share this work by the incredible @anlijuncn. We explore the potential of plasma prote….

RT @anlijuncn: Can AI reveal the risk and co-pathology of multiple neurodegenerative diseases from just a single blood sample? We explored….

[10/10] Finally, thanks to all our best collaborators: Bart Smets, @RowanSaloner, Shinya Tasaki, Ying Xu, Varsha Krish, Farhad Imam, Danielle van Westen, Christopher D. Whelan!.

[9/10] This could not be done with fantastic GNPC. And massive thanks to the coolest @biofinder_study team—Shorena Janelidze, @EStomrud, @SebastianPalmqv , @RikOssenkoppele, @NiklasMattsson4, and @OskarHansson9 —for sharing the awesome data and supporting this project every step.

[8/10] Endless thanks to @_JakeVogel_ for guiding and supporting this work from day one. To our amazing team, especially Alexa Pichet Binette, @ines_hristovska, Gabriele Vilkaite, and @xiaoyucaly, for their enormous support.

[7/10] ProtAIDe-Dx is a step toward the development of scalable, minimally invasive, and multi-disease diagnostic tools for neurodegenerative diseases. We hope our work can establish a benchmark for AI-driven proteomics tools, paving the way for precision medicine in these.

[6/10] We built a proof-of-concept diagnostic report with ProtAIDe-Dx, visualizing diagnostic probabilities across conditions and highlighting proteins that contributed to the individual’s prediction and traits linked to those proteins, enabling a biologically interpretable

[5/10] Could ProtAIDe-Dx aid real-world clinical application? In a memory clinic cohort, ProtAIDe-Dx significantly improved differential diagnosis (especially PD and CVD) when combined with accessible clinical biomarkers (MMSE, MRI, plasma p-tau217 & NfL). (Figure 4D).

[4/10] ProtAIDe-Dx identified a novel and compact set of top predictive proteins. Notably, OMG and Histone H1-2 (H1-2) distinguished controls from all neurodegenerative conditions, and ubiquitin (UBB) was a discriminative protein for FTD. [Figure 3A].

[3/10] The models’ diagnostic probabilities highlighted subgroups of patients with proteomic patterns more similar to a different condition, e.g., AD patients resembling stroke patients, indicating possible misdiagnosis, potential co-pathology, or may even indicate distinct

[2/10] We developed a multi-task model, ProtAIDe-Dx, to provide simultaneous probabilistic diagnosis across six conditions associated with dementia in aging (Control, AD, PD, FTD, ALS, and Stroke/TIA). CVed balanced ranged from 69%-96% and AUCs > 79% across all conditions.

[1/10] For the first time, we can answer this question with the world's largest neurodegeneration proteomics consortium, GNPC @_neuroproteome. #GNPC #Neurodegeneration #Proteomics #OpenScience #ADRD #Biomarkers #Parkinsons #ALS #FTD #NatureMedicine #NatureAging #SomaScan #Plasma.