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Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth.
Cui, Zaixu; Pines, Adam R; Larsen, Bart; Sydnor, Valerie J; Li, Hongming; Adebimpe, Azeez; Alexander-Bloch, Aaron F; Bassett, Dani S; Bertolero, Max; Calkins, Monica E; Davatzikos, Christos; Fair, Damien A; Gur, Ruben C; Gur, Raquel E; Moore, Tyler M; Shanmugan, Sheila; Shinohara, Russell T; Vogel, Jacob W; Xia, Cedric H; Fan, Yong; Satterthwaite, Theodore D.
Afiliação
  • Cui Z; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Chinese Institute for Brain Research, Beijing, China. Electronic address: cuizaixu@cibr.ac.cn.
  • Pines AR; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Larsen B; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Sydnor VJ; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Li H; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Adebimpe A; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Alexander-Bloch AF; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Child and Adolescent Psychiatry and Behavioral Science, The Children's Hospital of Philadelphia, Philadelphia, Pennsylvania.
  • Bassett DS; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neurology, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Electrical and Systems Engineering, U
  • Bertolero M; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Calkins ME; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Davatzikos C; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Bioengineering, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Electric
  • Fair DA; Masonic Institute for the Developing Brain, Institute of Child Development, College of Education and Human Development, Department of Pediatrics, Medical School, University of Minnesota, Minneapolis, Minnesota.
  • Gur RC; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neurology, U
  • Gur RE; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Neurology, U
  • Moore TM; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Shanmugan S; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Shinohara RT; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania; Penn Statistics in Imaging and Visualization Center, Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Vogel JW; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Xia CH; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Fan Y; Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania.
  • Satterthwaite TD; Penn Lifespan Informatics and Neuroimaging Center, University of Pennsylvania, Philadelphia, Pennsylvania; Department of Psychiatry, University of Pennsylvania, Philadelphia, Pennsylvania; Center for Biomedical Image Computation and Analytics, University of Pennsylvania, Philadelphia, Pennsylvania;
Biol Psychiatry ; 92(12): 973-983, 2022 12 15.
Article em En | MEDLINE | ID: mdl-35927072
ABSTRACT

BACKGROUND:

The spatial layout of large-scale functional brain networks differs between individuals and is particularly variable in the association cortex, implicated in a broad range of psychiatric disorders. However, it remains unknown whether this variation in functional topography is related to major dimensions of psychopathology in youth.

METHODS:

The authors studied 790 youths ages 8 to 23 years who had 27 minutes of high-quality functional magnetic resonance imaging data as part of the Philadelphia Neurodevelopmental Cohort. Four correlated dimensions were estimated using a confirmatory correlated traits factor analysis on 112 item-level clinical symptoms, and one overall psychopathology factor with 4 orthogonal dimensions were extracted using a confirmatory factor analysis. Spatially regularized nonnegative matrix factorization was used to identify 17 individual-specific functional networks for each participant. Partial least square regression with split-half cross-validation was conducted to evaluate to what extent the topography of personalized functional networks encodes major dimensions of psychopathology.

RESULTS:

Personalized functional network topography significantly predicted unseen individuals' major dimensions of psychopathology, including fear, psychosis, externalizing, and anxious-misery. Reduced representation of association networks was among the most important features for the prediction of all 4 dimensions. Further analysis revealed that personalized functional network topography predicted overall psychopathology (r = 0.16, permutation testing p < .001), which drove prediction of the 4 correlated dimensions.

CONCLUSIONS:

These results suggest that individual differences in functional network topography in association networks is related to overall psychopathology in youth. Such results underscore the importance of considering functional neuroanatomy for personalized diagnostics and therapeutics in psychiatry.
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Texto completo: 1 Base de dados: MEDLINE Assunto principal: Individualidade / Transtornos Mentais Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Assunto principal: Individualidade / Transtornos Mentais Idioma: En Ano de publicação: 2022 Tipo de documento: Article