How do Neurotransmitter Pathways contribute to Neuroimaging Phenotypes?

How do Neurotransmitter Pathways contribute to Neuroimaging Phenotypes? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article How do Neurotransmitter Pathways contribute to Neuroimaging Phenotypes? Amir Ebneabbasi, Amir Ebneabbasi, Mortaza Afshani, Arman Seyed-Ahmadi, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4206011/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Neuroimaging could accurately reflect human behaviour in health and disease, but the mechanism by which image-derived phenotypes correspond to neurotransmitter systems remains uncertain. Prior studies have explored spatial correlations between neuroimaging phenotypes and positron emission tomography radiotracers. However, the influence of neurotransmitters goes beyond the receptors/transporters, influencing a wider array of intracellular components as pivotal parts of neurotransmitter pathways. Here, we used unsupervised learning to understand how the brain maps of healthy functon(i.e., magnetoencephalography frequency-specific power) and abnormal structure (i.e., disorder-specific cortical thickness) are closely anchored to underlying neurotransmitter pathways assessed by gene expression data. To do this, we used large-scale datasets of the Human Connectome Project (HCP), Enhancing NeuroImaging Genetics through Meta-Analysis (ENIGMA) and Allen Human Brain Atlas (AHBA). We considered spatial and random gene null models to mitigate false positives. We replicate our analyses using different gene stability thresholds. This analytic approach paves the way for personalised medicine and advanced biomarkers. Biological sciences/Neuroscience Health sciences/Diseases/Psychiatric disorders Full Text Additional Declarations The authors have declared there is NO conflict of interest to disclose Supplementary Files Supplementrary.xlsx Supplementary Data Supplementary.pdf Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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