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Your search keyword '"National Institute for Health and Care Research (US)"' showing total 2 results
Start Over Author "National Institute for Health and Care Research (US)" Publisher nature publishing group
2 results on '"National Institute for Health and Care Research (US)"'

1. Robust estimation of cortical similarity networks from brain MRI

Author

Gates Cambridge Scholarships, Schmidt Futures, National Institute of Mental Health (US), St Catharine's College, Autism Research Trust, Junta de Andalucía, Universidad de Sevilla, National Institutes of Health (US), National Institute for Health and Care Research (US), Alan Turing Institute, Sebenius, Isaac, Seidlitz, Jakob, Warrier, Varun, Bethlehem, Richard A. I., Alexander-Bloch, Aaron, Mallard, Travis T., Romero García, Rafael, Bullmore, Edward T., Morgan, Sarah E., Gates Cambridge Scholarships, Schmidt Futures, National Institute of Mental Health (US), St Catharine's College, Autism Research Trust, Junta de Andalucía, Universidad de Sevilla, National Institutes of Health (US), National Institute for Health and Care Research (US), Alan Turing Institute, Sebenius, Isaac, Seidlitz, Jakob, Warrier, Varun, Bethlehem, Richard A. I., Alexander-Bloch, Aaron, Mallard, Travis T., Romero García, Rafael, Bullmore, Edward T., and Morgan, Sarah E.

Abstract

Structural similarity is a growing focus for magnetic resonance imaging (MRI) of connectomes. Here we propose Morphometric INverse Divergence (MIND), a new method to estimate within-subject similarity between cortical areas based on the divergence between their multivariate distributions of multiple MRI features. Compared to the prior approach of morphometric similarity networks (MSNs) on n > 11,000 scans spanning three human datasets and one macaque dataset, MIND networks were more reliable, more consistent with cortical cytoarchitectonics and symmetry and more correlated with tract-tracing measures of axonal connectivity. MIND networks derived from human T1-weighted MRI were more sensitive to age-related changes than MSNs or networks derived by tractography of diffusion-weighted MRI. Gene co-expression between cortical areas was more strongly coupled to MIND networks than to MSNs or tractography. MIND network phenotypes were also more heritable, especially edges between structurally differentiated areas. MIND network analysis provides a biologically validated lens for cortical connectomics using readily available MRI data.

Published
2023

2. Polygenic risk score-based phenome-wide association study identifies novel associations for Tourette syndrome

Author

National Institutes of Health (US), Lundbeck Foundation, German Research Foundation, Royal Netherlands Academy of Arts and Sciences, National Science Centre (Poland), National Institute for Health and Care Research (US), NIHR Biomedical Research Centre (UK), Jain, Pritesh, Miller-Fleming, Tyne, Topaloudi, Apostolia, Yu, Dongmei, Drineas, Petros, Georgitsi, Marianthi, Yang, Zhiyu, Rizzo, Renata, Müller-Vahl, Kirsten R., Tumer, Zeynep, Mol Debes, Nanette, Hartmann, Andreas, Depienne, Christel, Worbe, Yulia, Mir, Pablo, Cath, Danielle, Boomsma, Dorret I., Roessner, Veit, Wolańczyk, Tomasz, Janik, Piotr, Szejko, Natalia, Zekanowski, Cezary, Barta, Csaba, Nemoda, Zsofia, Tarnok, Zsanett, Buxbaum, Joseph D., Grice, Dorothy, Glennon, Jeffrey, Stefansson, Hreinn, Hengerer, Bastian, Benaroya‑Milshtein, Noa, Cardona, Francesco, Hedderly, Tammy, Heyman, Isobel, Huyser, Chaim, Morer, Astrid, Mueller, Norbert, Münchau, Alexander, Plessen, Kerstin J., Porcelli, Cesare, Walitza, Susanne, Schrag, Anette, Martino, Davide, The Psychiatric Genomics Consortium Tourette Syndrome Working Group (PGC-TS), The EMTICS collaborative group, Dietrich, Andrea, The TS-EUROTRAIN Network, Mathews, Carol A., Scharf, Jeremiah M., Hoekstra, Pieter J., Davis, Lea K., Paschou, Peristera, National Institutes of Health (US), Lundbeck Foundation, German Research Foundation, Royal Netherlands Academy of Arts and Sciences, National Science Centre (Poland), National Institute for Health and Care Research (US), NIHR Biomedical Research Centre (UK), Jain, Pritesh, Miller-Fleming, Tyne, Topaloudi, Apostolia, Yu, Dongmei, Drineas, Petros, Georgitsi, Marianthi, Yang, Zhiyu, Rizzo, Renata, Müller-Vahl, Kirsten R., Tumer, Zeynep, Mol Debes, Nanette, Hartmann, Andreas, Depienne, Christel, Worbe, Yulia, Mir, Pablo, Cath, Danielle, Boomsma, Dorret I., Roessner, Veit, Wolańczyk, Tomasz, Janik, Piotr, Szejko, Natalia, Zekanowski, Cezary, Barta, Csaba, Nemoda, Zsofia, Tarnok, Zsanett, Buxbaum, Joseph D., Grice, Dorothy, Glennon, Jeffrey, Stefansson, Hreinn, Hengerer, Bastian, Benaroya‑Milshtein, Noa, Cardona, Francesco, Hedderly, Tammy, Heyman, Isobel, Huyser, Chaim, Morer, Astrid, Mueller, Norbert, Münchau, Alexander, Plessen, Kerstin J., Porcelli, Cesare, Walitza, Susanne, Schrag, Anette, Martino, Davide, The Psychiatric Genomics Consortium Tourette Syndrome Working Group (PGC-TS), The EMTICS collaborative group, Dietrich, Andrea, The TS-EUROTRAIN Network, Mathews, Carol A., Scharf, Jeremiah M., Hoekstra, Pieter J., Davis, Lea K., and Paschou, Peristera

Abstract

Tourette Syndrome (TS) is a complex neurodevelopmental disorder characterized by vocal and motor tics lasting more than a year. It is highly polygenic in nature with both rare and common previously associated variants. Epidemiological studies have shown TS to be correlated with other phenotypes, but large-scale phenome wide analyses in biobank level data have not been performed to date. In this study, we used the summary statistics from the latest meta-analysis of TS to calculate the polygenic risk score (PRS) of individuals in the UK Biobank data and applied a Phenome Wide Association Study (PheWAS) approach to determine the association of disease risk with a wide range of phenotypes. A total of 57 traits were found to be significantly associated with TS polygenic risk, including multiple psychosocial factors and mental health conditions such as anxiety disorder and depression. Additional associations were observed with complex non-psychiatric disorders such as Type 2 diabetes, heart palpitations, and respiratory conditions. Cross-disorder comparisons of phenotypic associations with genetic risk for other childhood-onset disorders (e.g.: attention deficit hyperactivity disorder [ADHD], autism spectrum disorder [ASD], and obsessive-compulsive disorder [OCD]) indicated an overlap in associations between TS and these disorders. ADHD and ASD had a similar direction of effect with TS while OCD had an opposite direction of effect for all traits except mental health factors. Sex-specific PheWAS analysis identified differences in the associations with TS genetic risk between males and females. Type 2 diabetes and heart palpitations were significantly associated with TS risk in males but not in females, whereas diseases of the respiratory system were associated with TS risk in females but not in males. This analysis provides further evidence of shared genetic and phenotypic architecture of different complex disorders.

Published
2023

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