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Brain aging in bipolar disorder using a neuroimaging and machine learning-derived metric: Findings from the ENIGMA BD Working Group

Title: Brain aging in bipolar disorder using a neuroimaging and machine learning-derived metric: Findings from the ENIGMA BD Working Group
Authors: Ng, Hui Xin; Abé, Christoph; Alda, Martin; Alonso-Lana, Silvia; Anmella, Gerard; Bauer, Jochen; Borgers, Tiana; Brosch, Katharina; Busatto, Geraldo F; Bøen, Erlend; Canales-Rodríguez, Erick J; Cannon, Dara M; Chaim-Avancini, Tiffany M; Cole, James H; Dannlowski, Udo; De La Cruz, Alan; Einenkel, Karolin; Elvsåshagen, Torbjørn; Favre, Pauline; Fisch, Lukas; Flinkenflügel, Kira; Foley, Sonya; Fullerton, Janice M; Goltermann, Janik; Grotegerd, Dominik; Gruber, Oliver; Haarman, Bartholomeus CM; Hahn, Tim; Hajek, Tomas; Han, Laura KM; Henry, Chantal; Hidalgo-Mazzei, Diego; Houenou, Josselin; Howells, Fleur M; Ingvar, Martin; Jahanshad, Neda; Jiménez, Esther; Karuk, Andriana; Kircher, Tilo; Klahn, Luisa; Kraus, Anna; Krug, Axel; Krämer, Bernd; Kuplicki, Rayus T; Lafer, Beny; Landén, Mikael; Machado-Vieira, Rodrigo; Malt, Ulrik F; Martyn, Fiona M; McDonald, Colm; McPhilemy, Genevieve; Meinert, Susanne; Meller, Tina; Mitchell, Philip B; Mwangi, Benson; Nabulsi, Leila; Nenadić, Igor; Opel, Nils; Otaduy, Maria CG; Overs, Bronwyn J; Polosan, Mircea; Pomarol-Clotet, Edith; Pouchon, Arnaud; Radua, Joaquim; Rauer, Lisa; Repple, Jonathan; Roberts, Gloria; Rodríguez-Cano, Elena; Rosa, Pedro GP; Salvador, Raymond; Sarró, Salvador; Satterthwaite, Theodore D; Savitz, Jonathan; Schmaal, Lianne; Schofield, Peter R; Serpa, Mauricio; Sim, Kang; Soares, Jair C; Topolski, Natasha; Soeiro-de-Souza, Marcio G; Stein, Dan J; Stein, Frederike; Sutherland, Ashley N; Temmingh, Henk S; Thomopoulos, Sophia I; Uhlmann, Anne; Vieta, Eduard; Vilajosana, Enric; Wolf, Daniel H; Wu, Mon-Ju; Zunta-Soares, Giovana B; Zanetti, Marcus V; van den Brink, Wim; Thompson, Paul M; Andreassen, Ole A; Ching, Christopher RK; Eyler, Lisa T; ENIGMA, Bipolar Disorder Working Group; ENIGMA, Brain Age Working Group
Source: Journal of Affective Disorders , Article 121234. (2026) (In press).
Publisher Information: Elsevier BV
Publication Year: 2026
Collection: University College London: UCL Discovery
Subject Terms: Bipolar disorder; Brain age; Brain-PAD; ENIGMA; Medication; Neuroimaging
Description: BACKGROUND: Bipolar disorder (BD) is associated with clinical and biological markers of premature aging. In this largest study of brain age in BD to date, with 2919 participants, we compared brain-predicted age difference (brain-PAD) in individuals with BD and healthy comparison (HC) participants. Brain-PAD is a machine learning-estimated metric that quantifies the difference between an individual's predicted brain age and their chronological age, a potential clinical bio-signature of premature brain aging. Within individuals with BD, we also examined how medication and clinical characteristics were related to brain-PAD. METHODS: Age was predicted from 77 MRI measures of regional subcortical and lateral ventricle volumes, cortical thickness, and surface area for 1342 BD and 1577 HC adult participants, aged 18-75 yrs. old (μ = 37.2; SD = 12.3), from the curated ENIGMA Bipolar Disorder working group (ENIGMA-BD) and leveraging an ENIGMA machine learning model previously trained and validated using independent samples. Chronological age was subtracted from predicted age to produce an individual-level estimate known as brain-PAD. Linear mixed models (adjusting for sex and age as fixed effects and site as a random effect) were used to examine group differences and clinical associations. RESULTS: BD was associated with higher brain-PAD, compared to HC, primarily among older patients, as demonstrated by a significant age by diagnosis interaction (+0.05 [SE: 0.02] years). Individuals with BD on antiepileptic (AED) medications only (+3.20 [SE: 0.78] years) or on both AED and second-generation antipsychotics (SGA) (+3.74 [SE: 0.89] years) demonstrated greater brain-PAD compared to individuals who were not on any of the examined medications. Those taking lithium, whether alone or with AED and SGA independently, showed no difference in brain-PAD compared to individuals not taking any of the examined medications. However, individuals who were taking lithium showed lower brain-PAD compared to those on AED (-4.48 [SE: 0.84] ...
Document Type: article in journal/newspaper
File Description: text
Language: English
Relation: https://discovery.ucl.ac.uk/id/eprint/10221083/
Availability: https://discovery.ucl.ac.uk/id/eprint/10221083/1/1-s2.0-S0165032726000856-main.pdf; https://discovery.ucl.ac.uk/id/eprint/10221083/
Rights: open
Accession Number: edsbas.80B9F917
Database: BASE