Dataset Information

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

ABSTRACT: We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

SUBMITTER: Ge R

PROVIDER: S-EPMC10705253 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature

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Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

Ge Ruiyang R Yu Yuetong Y Qi Yi Xuan YX Fan Yunan Vera YV Chen Shiyu S Gao Chuntong C Haas Shalaila S SS Modabbernia Amirhossein A New Faye F Agartz Ingrid I Asherson Philip P Ayesa-Arriola Rosa R Banaj Nerisa N Banaschewski Tobias T Baumeister Sarah S Bertolino Alessandro A Boomsma Dorret I DI Borgwardt Stefan S Bourque Josiane J Brandeis Daniel D Breier Alan A Brodaty Henry H Brouwer Rachel M RM Buckner Randy R Buitelaar Jan K JK Cannon Dara M DM Caseras Xavier X Cervenka Simon S Conrod Patricia J PJ Crespo-Facorro Benedicto B Crivello Fabrice F Crone Eveline A EA de Haan Liewe L de Zubicaray Greig I GI Di Giorgio Annabella A Erk Susanne S Fisher Simon E SE Franke Barbara B Frodl Thomas T Glahn David C DC Grotegerd Dominik D Gruber Oliver O Gruner Patricia P Gur Raquel E RE Gur Ruben C RC Harrison Ben J BJ Hatton Sean N SN Hickie Ian I Howells Fleur M FM Hulshoff Pol Hilleke E HE Huyser Chaim C Jernigan Terry L TL Jiang Jiyang J Joska John A JA Kahn René S RS Kalnin Andrew J AJ Kochan Nicole A NA Koops Sanne S Kuntsi Jonna J Lagopoulos Jim J Lazaro Luisa L Lebedeva Irina S IS Lochner Christine C Martin Nicholas G NG Mazoyer Bernard B McDonald Brenna C BC McDonald Colm C McMahon Katie L KL Nakao Tomohiro T Nyberg Lars L Piras Fabrizio F Portella Maria J MJ Qiu Jiang J Roffman Joshua L JL Sachdev Perminder S PS Sanford Nicole N Satterthwaite Theodore D TD Saykin Andrew J AJ Schumann Gunter G Sellgren Carl M CM Sim Kang K Smoller Jordan W JW Soares Jair J Sommer Iris E IE Spalletta Gianfranco G Stein Dan J DJ Tamnes Christian K CK Thomopolous Sophia I SI Tomyshev Alexander S AS Tordesillas-Gutiérrez Diana D Trollor Julian N JN van 't Ent Dennis D van den Heuvel Odile A OA van Erp Theo Gm TG van Haren Neeltje Em NE Vecchio Daniela D Veltman Dick J DJ Walter Henrik H Wang Yang Y Weber Bernd B Wei Dongtao D Wen Wei W Westlye Lars T LT Wierenga Lara M LM Williams Steven Cr SC Wright Margaret J MJ Medland Sarah S Wu Mon-Ju MJ Yu Kevin K Jahanshad Neda N Thompson Paul M PM Frangou Sophia S

bioRxiv : the preprint server for biology 20231202

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to imag ...[more]

PMID: 38076938

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Project description:ImportanceThe lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in the majority of individuals at psychosis risk may be nested within the range observed in healthy individuals.ObjectiveTo quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high-risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.Design setting and participantsClinical, IQ and FreeSurfer-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1,340 CHR-P individuals [47.09% female; mean age: 20.75 (4.74) years] and 1,237 healthy individuals [44.70% female; mean age: 22.32 (4.95) years] from 29 international sites participating in the ENIGMA Clinical High Risk for Psychosis Working Group.Main outcomes and measuresFor each regional morphometric measure, z-scores were computed that index the degree of deviation from the normative means of that measure in a healthy reference population (N=37,407). Average deviation scores (ADS) for CT, SA, SV, and globally across all measures (G) were generated by averaging the respective regional z-scores. Regression analyses were used to quantify the association of deviation scores with clinical severity and cognition and two-proportion z-tests to identify case-control differences in the proportion of individuals with infranormal (z<-1.96) or supranormal (z>1.96) scores.ResultsCHR-P and healthy individuals overlapped in the distributions of the observed values, regional z-scores, and all ADS vales. The proportion of CHR-P individuals with infranormal or supranormal values in any metric was low (<12%) and similar to that of healthy individuals. CHR-P individuals who converted to psychosis compared to those who did not convert had a higher percentage of infranormal values in temporal regions (5-7% vs 0.9-1.4%). In the CHR-P group, only the ADSSA showed significant but weak associations (|β|<0.09; PFDR<0.05) with positive symptoms and IQ.Conclusions and relevanceThe study findings challenge the usefulness of macroscale neuromorphometric measures as diagnostic biomarkers of psychosis risk and suggest that such measures do not provide an adequate explanation for psychosis risk.

Project description:ImportanceThe lack of robust neuroanatomical markers of psychosis risk has been traditionally attributed to heterogeneity. A complementary hypothesis is that variation in neuroanatomical measures in individuals at psychosis risk may be nested within the range observed in healthy individuals.ObjectiveTo quantify deviations from the normative range of neuroanatomical variation in individuals at clinical high risk for psychosis (CHR-P) and evaluate their overlap with healthy variation and their association with positive symptoms, cognition, and conversion to a psychotic disorder.Design, setting, and participantsThis case-control study used clinical-, IQ-, and neuroimaging software (FreeSurfer)-derived regional measures of cortical thickness (CT), cortical surface area (SA), and subcortical volume (SV) from 1340 individuals with CHR-P and 1237 healthy individuals pooled from 29 international sites participating in the Enhancing Neuroimaging Genetics Through Meta-analysis (ENIGMA) Clinical High Risk for Psychosis Working Group. Healthy individuals and individuals with CHR-P were matched on age and sex within each recruitment site. Data were analyzed between September 1, 2021, and November 30, 2022.Main outcomes and measuresFor each regional morphometric measure, deviation scores were computed as z scores indexing the degree of deviation from their normative means from a healthy reference population. Average deviation scores (ADS) were also calculated for regional CT, SA, and SV measures and globally across all measures. Regression analyses quantified the association of deviation scores with clinical severity and cognition, and 2-proportion z tests identified case-control differences in the proportion of individuals with infranormal (z < -1.96) or supranormal (z > 1.96) scores.ResultsAmong 1340 individuals with CHR-P, 709 (52.91%) were male, and the mean (SD) age was 20.75 (4.74) years. Among 1237 healthy individuals, 684 (55.30%) were male, and the mean (SD) age was 22.32 (4.95) years. Individuals with CHR-P and healthy individuals overlapped in the distributions of the observed values, regional z scores, and all ADS values. For any given region, the proportion of individuals with CHR-P who had infranormal or supranormal values was low (up to 153 individuals [<11.42%]) and similar to that of healthy individuals (<115 individuals [<9.30%]). Individuals with CHR-P who converted to a psychotic disorder had a higher percentage of infranormal values in temporal regions compared with those who did not convert (7.01% vs 1.38%) and healthy individuals (5.10% vs 0.89%). In the CHR-P group, only the ADS SA was associated with positive symptoms (β = -0.08; 95% CI, -0.13 to -0.02; P = .02 for false discovery rate) and IQ (β = 0.09; 95% CI, 0.02-0.15; P = .02 for false discovery rate).Conclusions and relevanceIn this case-control study, findings suggest that macroscale neuromorphometric measures may not provide an adequate explanation of psychosis risk.

Dataset Information

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

Publications

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization.

Similar Datasets

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