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6. Development of an individualized risk calculator of treatment resistance in patients with first-episode psychosis (TRipCal) using automated machine learning: a 12-year follow-up study with clozapine prescription as a proxy indicator

Author

Wong, Ting Yat, Luo, Hao, Tang, Jennifer, Moore, Tyler M., Gur, Ruben C., Suen, Yi Nam, Hui, Christy Lai Ming, Lee, Edwin Ho Ming, Chang, Wing Chung, Yan, Wai Ching, Chui, Eileena, Poon, Lap Tak, Lo, Alison, Cheung, Koi-Man, Kan, Chui Kwan, Chen, Eric Yu Hai, and Chan, Sherry Kit Wa

Published
2024
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7. Impact of insurance status on MRI phenotypes in MS

Author

Martin, Melissa Lynne, Robert-Fitzgerald, Timothy, Schindler, Matthew K., Perrone, Christopher, Schultz, Guy, Lynch, Selah, Mirkovic, Nebojsa, Thomas, Sunil, Elahi, Ameena, Reid, Donovan, Moore, Tyler M., Baller, Erica B., Satterthwaite, Theodore D., Cieslak, Matthew, Covitz, Sydney, Adebimpe, Azeez, Manning, Abigail, Markowitz, Clyde E., Detre, John A., Bar-Or, Amit, Kakara, Mihir, and Shinohara, Russell T.

Published
2024
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8. Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS)

Author

Zoupou, Eirini, Moore, Tyler M., Kennedy, Kelly P., Calkins, Monica E., Gorgone, Alesandra, Sandro, Akira Di, Rush, Sage, Lopez, Katherine C., Ruparel, Kosha, Daryoush, Tarlan, Okoyeh, Paul, Savino, Andrew, Troyan, Scott, Wolf, Daniel H., Scott, J. Cobb, Gur, Raquel E., and Gur, Ruben C.

Published
2024
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9. A general exposome factor explains individual differences in functional brain network topography and cognition in youth

Author

Keller, Arielle S., Moore, Tyler M., Luo, Audrey, Visoki, Elina, Gataviņš, Mārtiņš M., Shetty, Alisha, Cui, Zaixu, Fan, Yong, Feczko, Eric, Houghton, Audrey, Li, Hongming, Mackey, Allyson P., Miranda-Dominguez, Oscar, Pines, Adam, Shinohara, Russell T., Sun, Kevin Y., Fair, Damien A., Satterthwaite, Theodore D., and Barzilay, Ran

Published
2024
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11. Comparison of factor analysis models applied to the NCANDA neuropsychological test battery

Author

Cummins, Kevin M, Pitpitan, Eileen V, Brumback, Ty, Moore, Tyler M, Trim, Ryan S, Clark, Duncan B, Brown, Sandra A, and Tapert, Susan F

Subjects
Clinical and Health Psychology, Psychology, Clinical Research, Substance Misuse, Neurosciences, Alcoholism, Alcohol Use and Health, Pediatric, Behavioral and Social Science, Good Health and Well Being, Neuropsychological Tests, General Science & Technology
Abstract

The factor structure of neuropsychological functioning among a large sample (N = 831) of American youth (ages 12-21 at baseline) was investigated in order to identify an optimal model. Candidate models were selected based on their potential to provide service to the study of adolescent development and the effects of heavy episodic alcohol consumption. Data on neuropsychological functioning were obtained from the NCANDA study. This is a longitudinal community study of the effects of alcohol exposure on neurodevelopment. Three conceptually motivated and one empirically motivated factor analysis model of neuropsychological domains were compared based on penalized-likelihood selection criteria and model fit statistics. Two conceptually-motivated models were found to have adequate fit and pattern invariance to function as a measurement model for the Penn Computerized Neurocognitive Battery (Penn CNB) anchored neuropsychological battery in NCANDA. Corroboration of previous factor analysis models was obtained, in addition to the identification of an alternative factor model that has higher discriminant capacity for neuropsychological domains hypothesized to be most sensitive to alcohol exposure in human adolescents. The findings support the use of a factor model developed originally for the Penn CNB and a model developed specifically for the NCANDA project. The NCANDA 8-Factor Model has conceptual and empirical advantages that were identified in the current and prior studies. These advantages are particularly valuable when applied in alcohol research settings.

Published
2022

12. Inter-rater reliability of subthreshold psychotic symptoms in individuals with 22q11.2 deletion syndrome

Author

Moore, Tyler M, Salzer, Deby, Bearden, Carrie E, Calkins, Monica E, Kates, Wendy R, Kushan, Leila, Gallagher, Robert Sean, Frumer, Dafna Sofrin, Weinberger, Ronnie, McDonald-McGinn, Donna M, Gur, Raquel E, and Gothelf, Doron

Subjects
Biomedical and Clinical Sciences, Clinical Sciences, Pediatric, Clinical Research, Mental health, Adolescent, Adult, Autism Spectrum Disorder, Child, DiGeorge Syndrome, Female, Humans, Male, Marfan Syndrome, Psychotic Disorders, Reproducibility of Results, Young Adult, Velocardiofacial syndrome, DiGeorge, Subthreshold psychotic symptoms, Structured Interview for Prodromal Syndromes, Scale of Prodromal Symptoms, Inter-rater reliability, Psychosis risk syndrome, Neurosciences, Psychology
Abstract

BackgroundPathways leading to psychosis in 22q11.2 deletion syndrome (22q11.2DS) have been the focus of intensive research during the last two decades. One of the common clinical risk factors for the evolution of psychosis in 22q11.2DS is the presence of positive and negative subthreshold psychotic symptoms. The gold standard for measuring subthreshold symptoms is the Structured Interview for Prodromal Syndromes (SIPS) and its accompanying Scale of Prodromal Symptoms (SOPS) ratings. Although the scale has been used by many centers studying 22q11.2DS, the inter-site reliability of the scale in this population has never been established.MethodsIn the present study, experienced clinical assessors from three large international centers studying 22q11.2DS independently rated video recordings of 18 adolescents and young adults with 22q11.2DS.ResultsThe intraclass correlations coefficients (ICCs) among three raters for the SOPS total scores, as well as for the positive, negative, and disorganization subscale scores, were good-to-excellent (ICCs range 0.73-0.93). The raters were also able to reliably determine the subjects' subthreshold syndrome status (ICC = 0.71). The reliability of individual items was good-to-excellent for all items, ranging from 0.61 for motor disturbances [G3] to 0.95 for bizarre thinking.ConclusionsOur results show that trained clinicians can reliably screen for subthreshold psychotic symptoms in individuals with 22q11.2DS. To increase assessment reliability, we suggest specific clarifications and simplifications to the standard SIPS interview for future studies.

Published
2021

13. Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)

Author

Di Sandro, Akira, Moore, Tyler M., Zoupou, Eirini, Kennedy, Kelly P., Lopez, Katherine C., Ruparel, Kosha, Njokweni, Lucky J., Rush, Sage, Daryoush, Tarlan, Franco, Olivia, Gorgone, Alesandra, Savino, Andrew, Didier, Paige, Wolf, Daniel H., Calkins, Monica E., Cobb Scott, J., Gur, Raquel E., and Gur, Ruben C.

Published
2024
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14. Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium

Author

Dwyer, Dominic B., Chand, Ganesh B., Pigoni, Alessandro, Khuntia, Adyasha, Wen, Junhao, Antoniades, Mathilde, Hwang, Gyujoon, Erus, Guray, Doshi, Jimit, Srinivasan, Dhivya, Varol, Erdem, Kahn, Rene S., Schnack, Hugo G., Meisenzahl, Eva, Wood, Stephen J., Zhuo, Chuanjun, Sotiras, Aristeidis, Shinohara, Russell T., Shou, Haochang, Fan, Yong, Schaulfelberger, Maristela, Rosa, Pedro, Lalousis, Paris A., Upthegrove, Rachel, Kaczkurkin, Antonia N., Moore, Tyler M., Nelson, Barnaby, Gur, Raquel E., Gur, Ruben C., Ritchie, Marylyn D., Satterthwaite, Theodore D., Murray, Robin M., Di Forti, Marta, Ciufolini, Simone, Zanetti, Marcus V., Wolf, Daniel H., Pantelis, Christos, Crespo-Facorro, Benedicto, Busatto, Geraldo F., Davatzikos, Christos, Koutsouleris, Nikolaos, and Dazzan, Paola

Published
2023
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17. Network controllability in transmodal cortex predicts psychosis spectrum symptoms

Author

Parkes, Linden, Moore, Tyler M., Calkins, Monica E., Cieslak, Matthew, Roalf, David R., Wolf, Daniel H., Gur, Ruben C., Gur, Raquel E., Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

The psychosis spectrum is associated with structural dysconnectivity concentrated in transmodal association cortex. However, understanding of this pathophysiology has been limited by an exclusive focus on the direct connections to a region. Using Network Control Theory, we measured variation in both direct and indirect structural connections to a region to gain new insights into the pathophysiology of the psychosis spectrum. We used psychosis symptom data and structural connectivity in 1,068 youths aged 8 to 22 years from the Philadelphia Neurodevelopmental Cohort. Applying a Network Control Theory metric called average controllability, we estimated each brain region's capacity to leverage its direct and indirect structural connections to control linear brain dynamics. Next, using non-linear regression, we determined the accuracy with which average controllability could predict negative and positive psychosis spectrum symptoms in out-of-sample testing. We also compared prediction performance for average controllability versus strength, which indexes only direct connections to a region. Finally, we assessed how the prediction performance for psychosis spectrum symptoms varied over the functional hierarchy spanning unimodal to transmodal cortex. Average controllability outperformed strength at predicting positive psychosis spectrum symptoms, demonstrating that indexing indirect structural connections to a region improved prediction performance. Critically, improved prediction was concentrated in association cortex for average controllability, whereas prediction performance for strength was uniform across the cortex, suggesting that indexing indirect connections is crucial in association cortex. Examining inter-individual variation in direct and indirect structural connections to association cortex is crucial for accurate prediction of positive psychosis spectrum symptoms.

Published
2020

18. Efficient Coding in the Economics of Human Brain Connectomics

Author

Zhou, Dale, Lynn, Christopher W., Cui, Zaixu, Ciric, Rastko, Baum, Graham L., Moore, Tyler M., Roalf, David R., Detre, John A., Gur, Ruben C., Gur, Raquel E., Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

In systems neuroscience, most models posit that brain regions communicate information under constraints of efficiency. Yet, evidence for efficient communication in structural brain networks characterized by hierarchical organization and highly connected hubs remains sparse. The principle of efficient coding proposes that the brain transmits maximal information in a metabolically economical or compressed form to improve future behavior. To determine how structural connectivity supports efficient coding, we develop a theory specifying minimum rates of message transmission between brain regions to achieve an expected fidelity, and we test five predictions from the theory based on random walk communication dynamics. In doing so, we introduce the metric of compression efficiency, which quantifies the trade-off between lossy compression and transmission fidelity in structural networks. In a large sample of youth (n = 1,042; age 8-23 years), we analyze structural networks derived from diffusion weighted imaging and metabolic expenditure operationalized using cerebral blood flow. We show that structural networks strike compression efficiency trade-offs consistent with theoretical predictions. We find that compression efficiency prioritizes fidelity with development, heightens when metabolic resources and myelination guide communication, explains advantages of hierarchical organization, links higher input fidelity to disproportionate areal expansion, and shows that hubs integrate information by lossy compression. Lastly, compression efficiency is predictive of behavior--beyond a conventional metric--for cognitive domains including executive function, memory, complex reasoning, and social cognition. Our findings elucidate how macroscale connectivity supports efficient coding, and serve to foreground communication processes that utilize random walk dynamics constrained by network connectivity.

Published
2020

19. Development of white matter fiber covariance networks supports executive function in youth

Author

Bagautdinova, Joëlle, Bourque, Josiane, Sydnor, Valerie J., Cieslak, Matthew, Alexander-Bloch, Aaron F., Bertolero, Maxwell A., Cook, Philip A., Gur, Raquel E., Gur, Ruben C., Hu, Fengling, Larsen, Bart, Moore, Tyler M., Radhakrishnan, Hamsanandini, Roalf, David R., Shinohara, Russel T., Tapera, Tinashe M., Zhao, Chenying, Sotiras, Aristeidis, Davatzikos, Christos, and Satterthwaite, Theodore D.

Published
2023
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23. Unifying Modular and Core-Periphery Structure in Functional Brain Networks over Development

Author

Gu, Shi, Xia, Cedric Huchuan, Ciric, Rastko, Moore, Tyler M., Gur, Ruben C., Gur, Raquel E., Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Quantitative Methods
Abstract

At rest, human brain functional networks display striking modular architecture in which coherent clusters of brain regions are activated. The modular account of brain function is pervasive, reliable, and reproducible. Yet, a complementary perspective posits a core-periphery or rich-club account of brain function, where hubs are densely interconnected with one another, allowing for integrative processing. Unifying these two perspectives has remained difficult due to the fact that the methodological tools to identify modules are entirely distinct from the methodological tools to identify core-periphery structure. Here we leverage a recently-developed model-based approach -- the weighted stochastic block model -- that simultaneously uncovers modular and core-periphery structure, and we apply it to fMRI data acquired at rest in 872 youth of the Philadelphia Neurodevelopmental Cohort. We demonstrate that functional brain networks display rich meso-scale organization beyond that sought by modularity maximization techniques. Moreover, we show that this meso-scale organization changes appreciably over the course of neurodevelopment, and that individual differences in this organization predict individual differences in cognition more accurately than module organization alone. Broadly, our study provides a unified assessment of modular and core-periphery structure in functional brain networks, providing novel insights into their development and implications for behavior.

Published
2019

24. Extensions of Multiple-Group Item Response Theory Alignment: Application to Psychiatric Phenotypes in an International Genomics Consortium

Author

Mansolf, Maxwell, Vreeker, Annabel, Reise, Steven P, Freimer, Nelson B, Glahn, David C, Gur, Raquel E, Moore, Tyler M, Pato, Carlos N, Pato, Michele T, Palotie, Aarno, Holm, Minna, Suvisaari, Jaana, Partonen, Timo, Kieseppä, Tuula, Paunio, Tiina, Boks, Marco, Kahn, René, Ophoff, Roel A, Bearden, Carrie E, Loohuis, Loes Olde, Teshiba, Terri, deGeorge, Daniella, Bilder, Robert M, Investigators, and Consortium, the WGSPD

Subjects
Applied and Developmental Psychology, Education, Specialist Studies In Education, Social and Personality Psychology, Psychology, Human Genome, Genetics, Mental health, Good Health and Well Being, test equating, differential item functioning, mega-analysis, harmonization, data integration, GROUP Investigators, WGSPD Consortium, Specialist Studies in Education, Social Sciences Methods, Specialist studies in education, Applied and developmental psychology, Social and personality psychology
Abstract

Large-scale studies spanning diverse project sites, populations, languages, and measurements are increasingly important to relate psychological to biological variables. National and international consortia already are collecting and executing mega-analyses on aggregated data from individuals, with different measures on each person. In this research, we show that Asparouhov and Muthén's alignment method can be adapted to align data from disparate item sets and response formats. We argue that with these adaptations, the alignment method is well suited for combining data across multiple sites even when they use different measurement instruments. The approach is illustrated using data from the Whole Genome Sequencing in Psychiatric Disorders consortium and a real-data-based simulation is used to verify accurate parameter recovery. Factor alignment appears to increase precision of measurement and validity of scores with respect to external criteria. The resulting parameter estimates may further inform development of more effective and efficient methods to assess the same constructs in prospectively designed studies.

Published
2020

25. Distinct and shared contributions of diagnosis and symptom domains to cognitive performance in severe mental illness in the Paisa population: a case-control study

Author

Service, Susan K, Upegui, Cristian Vargas, Ramírez, Mauricio Castaño, Port, Allison M, Moore, Tyler M, Umanes, Marfred Munoz, Arango, Luis Guillermo Agudelo, Díaz-Zuluaga, Ana M, Espejo, Juanita Melo, López, María Cecilia, Palacio, Juan David, Sánchez, Sergio Ruiz, Valencia, Johanna, Teshiba, Terri M, Espinoza, Alesandra, Loohuis, Loes Olde, De la Hoz Gomez, Juan, Brodey, Benjamin B, Sabatti, Chiara, Escobar, Javier I, Reus, Victor I, Jaramillo, Carlos Lopez, Gur, Ruben C, Bearden, Carrie E, and Freimer, Nelson B

Subjects
Biological Psychology, Psychology, Applied and Developmental Psychology, Depression, Behavioral and Social Science, Bipolar Disorder, Neurosciences, Mental Health, Clinical Research, Brain Disorders, Schizophrenia, Serious Mental Illness, 2.1 Biological and endogenous factors, Aetiology, 2.3 Psychological, social and economic factors, 2.4 Surveillance and distribution, Mental health, Good Health and Well Being, Adult, Case-Control Studies, Cognition, Cognition Disorders, Colombia, Depressive Disorder, Major, Female, Humans, Linear Models, Male, Middle Aged, Schizophrenic Psychology, Young Adult, Clinical Sciences, Public Health and Health Services, Clinical sciences, Applied and developmental psychology, Clinical and health psychology
Abstract

BackgroundSevere mental illness diagnoses have overlapping symptomatology and shared genetic risk, motivating cross-diagnostic investigations of disease-relevant quantitative measures. We analysed relationships between neurocognitive performance, symptom domains, and diagnoses in a large sample of people with severe mental illness not ascertained for a specific diagnosis (cases), and people without mental illness (controls) from a single, homogeneous population.MethodsIn this case-control study, cases with severe mental illness were ascertained through electronic medical records at Clínica San Juan de Dios de Manizales (Manizales, Caldas, Colombia) and the Hospital Universitario San Vicente Fundación (Medellín, Antioquía, Colombia). Participants were assessed for speed and accuracy using the Penn Computerized Neurocognitive Battery (CNB). Cases had structured interview-based diagnoses of schizophrenia, bipolar 1, bipolar 2, or major depressive disorder. Linear mixed models, using CNB tests as repeated measures, modelled neurocognition as a function of diagnosis, sex, and all interactions. Follow-up analyses in cases included symptom factor scores obtained from exploratory factor analysis of symptom data as main effects.FindingsBetween Oct 1, 2017, and Nov 1, 2019, 2406 participants (1689 cases [schizophrenia n=160; bipolar 1 disorder n=519; bipolar 2 disorder n=204; and major depressive disorder n=806] and 717 controls; mean age 39 years (SD 14); and 1533 female) were assessed. Participants with bipolar 1 disorder and schizophrenia had similar impairments in accuracy and speed across cognitive domains. Participants with bipolar 2 disorder and major depressive disorder performed similarly to controls, with subtle deficits in executive and social cognition. A three-factor model (psychosis, mania, and depression) best represented symptom data. Controlling for diagnosis, premorbid IQ, and disease severity, high lifetime psychosis scores were associated with reduced accuracy and speed across cognitive domains, whereas high depression scores were associated with increased social cognition accuracy.InterpretationCross-diagnostic investigations showed that neurocognitive function in severe mental illness is characterised by two distinct profiles (bipolar 1 disorder and schizophrenia, and bipolar 2 disorder and major depressive disorder), and is associated with specific symptom domains. These results suggest the utility of this design for elucidating severe mental illness causes and trajectories.FundingUS National Institute of Mental Health.

Published
2020

27. Genetic correlates of phenotypic heterogeneity in autism

Author

Warrier, Varun, Zhang, Xinhe, Reed, Patrick, Havdahl, Alexandra, Moore, Tyler M., Cliquet, Freddy, Leblond, Claire S., Rolland, Thomas, Rosengren, Anders, Rowitch, David H., Hurles, Matthew E., Geschwind, Daniel H., Børglum, Anders D., Robinson, Elise B., Grove, Jakob, Martin, Hilary C., Bourgeron, Thomas, and Baron-Cohen, Simon

Published
2022
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30. Mobile footprinting: linking individual distinctiveness in mobility patterns to mood, sleep, and brain functional connectivity

Author

Xia, Cedric Huchuan, Barnett, Ian, Tapera, Tinashe M., Adebimpe, Azeez, Baker, Justin T., Bassett, Danielle S., Brotman, Melissa A., Calkins, Monica E., Cui, Zaixu, Leibenluft, Ellen, Linguiti, Sophia, Lydon-Staley, David M., Martin, Melissa Lynne, Moore, Tyler M., Murtha, Kristin, Piiwaa, Kayla, Pines, Adam, Roalf, David R., Rush-Goebel, Sage, Wolf, Daniel H., Ungar, Lyle H., and Satterthwaite, Theodore D.

Published
2022
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32. Temporal sequences of brain activity at rest are constrained by white matter structure and modulated by cognitive demands

Author

Cornblath, Eli J., Ashourvan, Arian, Kim, Jason Z., Betzel, Richard F., Ciric, Rastko, Adebimpe, Azeez, Baum, Graham L., He, Xiaosong, Ruparel, Kosha, Moore, Tyler M., Gur, Ruben C., Gur, Raquel E., Shinohara, Russell T., Roalf, David R., Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

A diverse white matter network and finely tuned neuronal membrane properties allow the brain to transition seamlessly between cognitive states. However, it remains unclear how static structural connections guide the temporal progression of large-scale brain activity patterns in different cognitive states. Here, we analyze the brain's trajectories through a high-dimensional activity space at the level of single time point activity patterns from functional magnetic resonance imaging data acquired during passive visual fixation (rest) and an n-back working memory task. We find that specific state space trajectories, which represent temporal sequences of brain activity, are modulated by cognitive load and related to task performance. Using diffusion-weighted imaging acquired from the same subjects, we use tools from network control theory to show that linear spread of activity along white matter connections constrains the brain's state space trajectories at rest. Additionally, accounting for stimulus-driven visual inputs explains the different trajectories taken during the n-back task. We also used models of network rewiring to show that these findings are the result of non-trivial geometric and topological properties of white matter architecture. Finally, we examine associations between age and time-resolved brain state dynamics, revealing new insights into functional changes in the default mode and executive control networks. Overall, these results elucidate the structural underpinnings of cognitively and developmentally relevant spatiotemporal brain dynamics.

Published
2018

33. Influence of Neighborhood SES on Functional Brain Network Development

Author

Tooley, Ursula A., Mackey, Allyson P., Ciric, Rastko, Ruparel, Kosha, Moore, Tyler M., Gur, Ruben C., Gur, Raquel E., Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Neurons and Cognition
Abstract

Higher socioeconomic status (SES) in childhood is associated with increased cognitive abilities, higher academic achievement, and decreased incidence of mental illness later in development. Accumulating evidence suggests that these effects may be due to changes in brain development induced by environmental factors. While prior work has mapped the associations between neighborhood SES and brain structure, little is known about the relationship between SES and intrinsic neural dynamics. Here, we capitalize upon a large community-based sample (Philadelphia Neurodevelopmental Cohort, ages 8-22 years, n=1012) to examine developmental changes in functional brain network topology as estimated from resting state functional magnetic resonance imaging data. We quantitatively characterize this topology using a local measure of network segregation known as the clustering coefficient, and find that it accounts for a greater degree of SES-associated variance than meso-scale segregation captured by modularity. While whole-brain clustering increased with age, high-SES youth displayed faster increases in clustering than low-SES youth, and this effect was most pronounced for regions in the limbic, somatomotor, and ventral attention systems. The effect of SES on developmental increases in clustering was strongest for connections of intermediate physical length, consistent with faster decreases in local connectivity in these regions in low-SES youth, and tracked changes in BOLD signal complexity in the form of regional homogeneity. Our findings suggest that neighborhood SES may fundamentally alter intrinsic patterns of inter-regional interactions in the human brain in a manner that is consistent with greater segregation of information processing in late childhood and adolescence., Comment: 9 pages, 6 figures. Cerebral Cortex (2019)

Published
2018
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34. Sex differences in network controllability as a predictor of executive function in youth

Author

Cornblath, Eli J., Tang, Evelyn, Baum, Graham L., Moore, Tyler M., Roalf, David R., Gur, Ruben C., Gur, Raquel E., Pasqualetti, Fabio, Satterthwaite, Theodore D., and Bassett, Danielle S.

Subjects
Quantitative Biology - Neurons and Cognition, Computer Science - Systems and Control
Abstract

Executive function emerges late in development and displays different developmental trends in males and females. Sex differences in executive function in youth have been linked to vulnerability to psychopathology as well as to behaviors that impinge on health. Yet, the neurobiological basis of these differences is not well understood. Here we test the hypothesis that sex differences in executive function in youth stem from sex differences in the controllability of structural brain networks as they rewire over development. Combining methods from network neuroscience and network control theory, we characterize the network control properties of structural brain networks estimated from diffusion imaging data acquired in males and females in a sample of 882 youth aged 8-22 years. We summarize the control properties of these networks by estimating average and modal controllability, two statistics that probe the ease with which brain areas can drive the network towards easy- versus difficult-to-reach states. We find that females have higher modal controllability in frontal, parietal, and subcortical regions while males have higher average controllability in frontal and subcortical regions. Furthermore, average controllability values in the medial frontal cortex and subcortex, both higher in males, are negatively related to executive function. Finally, we find that average controllability predicts sex-dependent individual differences in activation during an n-back working memory task. Taken together, our findings support the notion that sex differences in the controllability of structural brain networks can partially explain sex differences in executive function. Controllability of structural brain networks also predicts features of task-relevant activation, suggesting the potential for controllability to represent context-specific constraints on network state more generally.

Published
2018

35. Linking Individual Differences in Personalized Functional Network Topography to Psychopathology in Youth

Author

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, and Satterthwaite, Theodore D.

Published
2022
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37. The NASA Twins Study: A multidimensional analysis of a year-long human spaceflight

Author

Garrett-Bakelman, Francine E, Darshi, Manjula, Green, Stefan J, Gur, Ruben C, Lin, Ling, Macias, Brandon R, McKenna, Miles J, Meydan, Cem, Mishra, Tejaswini, Nasrini, Jad, Piening, Brian D, Rizzardi, Lindsay F, Sharma, Kumar, Siamwala, Jamila H, Taylor, Lynn, Vitaterna, Martha Hotz, Afkarian, Maryam, Afshinnekoo, Ebrahim, Ahadi, Sara, Ambati, Aditya, Arya, Maneesh, Bezdan, Daniela, Callahan, Colin M, Chen, Songjie, Choi, Augustine MK, Chlipala, George E, Contrepois, Kévin, Covington, Marisa, Crucian, Brian E, De Vivo, Immaculata, Dinges, David F, Ebert, Douglas J, Feinberg, Jason I, Gandara, Jorge A, George, Kerry A, Goutsias, John, Grills, George S, Hargens, Alan R, Heer, Martina, Hillary, Ryan P, Hoofnagle, Andrew N, Hook, Vivian YH, Jenkinson, Garrett, Jiang, Peng, Keshavarzian, Ali, Laurie, Steven S, Lee-McMullen, Brittany, Lumpkins, Sarah B, MacKay, Matthew, Maienschein-Cline, Mark G, Melnick, Ari M, Moore, Tyler M, Nakahira, Kiichi, Patel, Hemal H, Pietrzyk, Robert, Rao, Varsha, Saito, Rintaro, Salins, Denis N, Schilling, Jan M, Sears, Dorothy D, Sheridan, Caroline K, Stenger, Michael B, Tryggvadottir, Rakel, Urban, Alexander E, Vaisar, Tomas, Van Espen, Benjamin, Zhang, Jing, Ziegler, Michael G, Zwart, Sara R, Charles, John B, Kundrot, Craig E, Scott, Graham BI, Bailey, Susan M, Basner, Mathias, Feinberg, Andrew P, Lee, Stuart MC, Mason, Christopher E, Mignot, Emmanuel, Rana, Brinda K, Smith, Scott M, Snyder, Michael P, and Turek, Fred W

Subjects
Mental Health, Genetics, Adaptation, Physiological, Adaptive Immunity, Astronauts, Body Weight, Carotid Arteries, Carotid Intima-Media Thickness, DNA Damage, DNA Methylation, Gastrointestinal Microbiome, Genomic Instability, Humans, Male, Space Flight, Telomere Homeostasis, Time Factors, United States, United States National Aeronautics and Space Administration, General Science & Technology
Abstract

To understand the health impact of long-duration spaceflight, one identical twin astronaut was monitored before, during, and after a 1-year mission onboard the International Space Station; his twin served as a genetically matched ground control. Longitudinal assessments identified spaceflight-specific changes, including decreased body mass, telomere elongation, genome instability, carotid artery distension and increased intima-media thickness, altered ocular structure, transcriptional and metabolic changes, DNA methylation changes in immune and oxidative stress-related pathways, gastrointestinal microbiota alterations, and some cognitive decline postflight. Although average telomere length, global gene expression, and microbiome changes returned to near preflight levels within 6 months after return to Earth, increased numbers of short telomeres were observed and expression of some genes was still disrupted. These multiomic, molecular, physiological, and behavioral datasets provide a valuable roadmap of the putative health risks for future human spaceflight.

Published
2019

43. Dissociable multi-scale patterns of development in personalized brain networks

Author

Pines, Adam R., Larsen, Bart, Cui, Zaixu, Sydnor, Valerie J., Bertolero, Maxwell A., Adebimpe, Azeez, Alexander-Bloch, Aaron F., Davatzikos, Christos, Fair, Damien A., Gur, Ruben C., Gur, Raquel E., Li, Hongming, Milham, Michael P., Moore, Tyler M., Murtha, Kristin, Parkes, Linden, Thompson-Schill, Sharon L., Shanmugan, Sheila, Shinohara, Russell T., Weinstein, Sarah M., Bassett, Danielle S., Fan, Yong, and Satterthwaite, Theodore D.

Published
2022
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44. Morphological integration of the human brain across adolescence and adulthood

Author

Nadig, Ajay, Seidlitz, Jakob, McDermott, Cassidy L., Liu, Siyuan, Bethlehem, Richard, Moore, Tyler M., Mallard, Travis T., Clasen, Liv S., Blumenthal, Jonathan D., Lalonde, François, Gur, Ruben C., Gur, Raquel E., Bullmore, Edward T., Satterthwaite, Theodore D., and Raznahan, Armin

Published
2021

46. Direct and Indirect Associations of Widespread Individual Differences in Brain White Matter Microstructure With Executive Functioning and General and Specific Dimensions of Psychopathology in Children

Author

Cardenas-Iniguez, Carlos, Moore, Tyler M., Kaczkurkin, Antonia N., Meyer, Francisco A.C., Satterthwaite, Theodore D., Fair, Damien A., White, Tonya, Blok, Elisabet, Applegate, Brooks, Thompson, Lauren M., Rosenberg, Monica D., Hedeker, Donald, Berman, Marc G., and Lahey, Benjamin B.

Published
2022
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47. Classification of Suicide Attempt Risk Using Environmental and Lifestyle Factors in 3 Large Youth Cohorts.

Author

Visoki, Elina, Moore, Tyler M., Zhang, Xinhe, Tran, Kate T., Ly, Christina, Gataviņš, Mārtiņš M., DiDomenico, Grace E., Brogan, Leah, Fein, Joel A., Warrier, Varun, Guloksuz, Sinan, and Barzilay, Ran

Subjects
ATTEMPTED suicide, SUICIDE risk factors, SUICIDAL behavior in youth, CHILDREN'S hospitals, SUICIDAL behavior
Abstract

This cohort study investigates the cumulative contribution of environmental and lifestyle (exposome) factors to risk of suicide attempt among youth. Key Points: Question: What is the cumulative contribution of environmental and lifestyle (exposome) factors to risk of suicide attempt among youth? Findings: In this cohort study including 40 364 youth, aggregate exposomic scores of risk and protective factors consistently explained substantial variance in suicide attempt over and above clinical risk benchmarks in diverse clinical and population youth cohorts from the US and the UK. Meaning: Results of this cohort study suggest that exposomic scores of suicide attempt provide a generalizable method for risk classification that can be applied in clinical or population settings and can advance reproducibility in suicide research. Importance: Suicide is the third-leading cause of death among US adolescents. Environmental and lifestyle factors influence suicidal behavior and can inform risk classification, yet quantifying and incorporating them in risk assessment presents a significant challenge for reproducibility and clinical translation. Objective: To quantify the aggregate contribution of environmental and lifestyle factors to youth suicide attempt risk classification. Design, Setting, and Participants: This was a cohort study in 3 youth samples: 2 national longitudinal cohorts from the US and the UK and 1 clinical cohort from a tertiary pediatric US hospital. An exposome-wide association study (ExWAS) approach was used to identify risk and protective factors and compute aggregate exposomic scores. Logistic regression models were applied to test associations and model fit of exposomic scores with suicide attempts in independent data. Youth from the Adolescent Brain Cognitive Development (ABCD) study, the UK Millennium Cohort Study (MCS), and the Children's Hospital of Philadelphia emergency department (CHOP-ED) were included in the study. Exposures: A single-weighted exposomic score that sums significant risk and protective environmental/lifestyle factors. Main Outcome and Measure: Self-reported suicide attempt. Results: A total of 40 364 youth were included in this analysis: 11 564 from the ABCD study (3 waves of assessment; mean [SD] age, 12.0 [0.7] years; 6034 male [52.2%]; 344 attempted suicide [3.0%]; 1154 environmental/lifestyle factors were included in the ABCD study), 9000 from the MCS cohort (mean [SD] age, 17.2 [0.3] years; 4593 female [51.0%]; 661 attempted suicide [7.3%]; 2864 environmental/lifestyle factors were included in the MCS cohort), and 19 800 from the CHOP-ED cohort (mean [SD] age, 15.3 [1.5] years; 12 937 female [65.3%]; 2051 attempted suicide [10.4%]; 36 environmental/lifestyle factors were included in the CHOP-ED cohort). In the ABCD discovery subsample, ExWAS identified 99 risk and protective exposures significantly associated with suicide attempt. A single weighted exposomic score that sums significant risk and protective exposures was associated with suicide attempt in an independent ABCD testing subsample (odds ratio [OR], 2.2; 95% CI, 2.0-2.6; P <.001) and explained 17.6% of the variance (based on regression pseudo-R2) in suicide attempt over and above that explained by age, sex, race, and ethnicity (2.8%) and by family history of suicide (6.3%). Findings were consistent in the MCS and CHOP-ED cohorts (explaining 22.6% and 19.3% of the variance in suicide attempt, respectively) despite clinical, demographic, and exposure differences. In all cohorts, compared with youth at the median quintile of the exposomic score, youth at the top fifth quintile were substantially more likely to have made a suicide attempt (OR, 4.3; 95% CI, 2.6-7.2 in the ABCD study; OR, 3.8; 95% CI, 2.7-5.3 in the MCS cohort; OR, 5.8; 95% CI, 4.7-7.1 in the CHOP-ED cohort). Conclusions and Relevance: Results suggest that exposomic scores of suicide attempt provided a generalizable method for risk classification that can be applied in diverse samples from clinical or population settings. [ABSTRACT FROM AUTHOR]

Published
2024
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