Dataset Information

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

ABSTRACT: Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate functional connectome-based markers of attention. In dataset 1, we use connectome-based predictive modeling and observe successful prediction of performance on an in-scan sustained attention task in a sample of youth, including participants with a neurodiverse condition. The predictions are not driven by confounds, such as head motion. In dataset 2, we find that the attention network model defined in dataset 1 generalizes to predict in-scan attention in a separate sample of neurotypical participants performing the same attention task. In datasets 3-5, we use connectome-based identification and longitudinal scans to probe the stability of the attention network across months to years in individual participants. Our results help elucidate the brain correlates of attentional state in youth and support the further development of predictive dimensional models of other clinically relevant phenotypes.

SUBMITTER: Horien C

PROVIDER: S-EPMC10183743 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature

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A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

Horien Corey C Greene Abigail S AS Shen Xilin X Fortes Diogo D Brennan-Wydra Emma E Banarjee Chitra C Foster Rachel R Donthireddy Veda V Butler Maureen M Powell Kelly K Vernetti Angelina A Mandino Francesca F O'Connor David D Lake Evelyn M R EMR McPartland James C JC Volkmar Fred R FR Chun Marvin M Chawarska Katarzyna K Rosenberg Monica D MD Scheinost Dustin D Constable R Todd RT

Cerebral cortex (New York, N.Y. : 1991) 20230501 10

Difficulty with attention is an important symptom in many conditions in psychiatry, including neurodiverse conditions such as autism. There is a need to better understand the neurobiological correlates of attention and leverage these findings in healthcare settings. Nevertheless, it remains unclear if it is possible to build dimensional predictive models of attentional state in a sample that includes participants with neurodiverse conditions. Here, we use 5 datasets to identify and validate func ...[more]

PMID: 36573438

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Project description:Substantial clinical heterogeneity and comorbidity inherent amongst mental disorders limit the identification of neuroimaging biomarkers that can reliably track clinical symptoms. Strategies that enable generation of meaningful and replicable neurobiological markers at the individual level will push the field of neuropsychiatry forward in developing efficacious personalized treatment. The current study included 142 adult patients with a primary diagnosis of schizophrenia (SCZ), bipolar (BP), or attention deficit/hyperactivity disorder (ADHD), and 67 patient ratings across four behavioral measures. Using functional connectivity derived from a personalized fMRI approach, we identified several candidate imaging markers related to dimensional phenotypes across disorders, assessed the internal and external generalizability of these markers, and compared the probability of replicating findings across datasets using individual and group-averaged defined functional regions. We identified subject-specific connections related to three different clinical domains (attention deficit, appetite-energy, psychosis-positive) in a discovery dataset. Importantly, these connectivity biomarkers were robust and were reproduced in an independent validation dataset. For markers related to neurovegetative symptoms (attention deficit, appetite-energy symptoms), the brain connections involved showed similar connectivity patterns across the different diagnoses. However, psychosis-positive symptoms were associated with connections of varying strength across disorders. Finally, we found that markers for symptom domains were replicable for individually-specified connections, but not for group template-derived connections. Our personalized strategies allowed us to identify meaningful and generalizable imaging markers for symptom domains in patients who exhibit high levels of heterogeneity. These biomarkers may shed new light on the connectivity underpinnings of psychiatric symptoms and lead to personalized interventions.

Project description:BackgroundAttention-deficit/hyperactivity disorder (ADHD) is highly prevalent among youth with or at familial risk for bipolar-I disorder (BD-I), and ADHD symptoms commonly precede and may increase the risk for BD-I; however, associated neuropathophysiological mechanisms are not known. In this cross-sectional study, we sought to investigate brain structural network topology among youth with ADHD, with and without familial risk of BD-I.MethodsWe recruited 3 groups of psychostimulant-free youth (aged 10-18 yr), namely youth with ADHD and at least 1 biological parent or sibling with BD-I (high-risk group), youth with ADHD who did not have a first- or second-degree relative with a mood or psychotic disorder (low-risk group) and healthy controls. We used graph-based network analysis of structural magnetic resonance imaging data to investigate topological properties of brain networks. We also evaluated relationships between topological metrics and mood and ADHD symptom ratings.ResultsA total of 149 youth were included in the analysis (49 healthy controls, 50 low-risk youth, 50 high-risk youth). Low-risk and high-risk ADHD groups exhibited similar differences from healthy controls, mainly in the default mode network and central executive network. We found topological alterations in the salience network of the high-risk group, relative to both low-risk and control groups. We found significant abnormalities in global network properties in the high-risk group only, compared with healthy controls. Among both low-risk and high-risk ADHD groups, nodal metrics in the right triangular inferior frontal gyrus correlated positively with ADHD total and hyperactivity/impulsivity subscale scores.LimitationsThe cross-sectional design of this study could not determine the relevance of these findings to BD-I risk progression.ConclusionYouth with ADHD, with and without familial risk for BD-I, exhibit common regional abnormalities in the brain connectome compared with healthy youth, whereas alterations in the salience network distinguish these groups and may represent a prodromal feature relevant to BD-I risk.

Dataset Information

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

Publications

A generalizable connectome-based marker of in-scan sustained attention in neurodiverse youth.

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