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Bandeira CE, Grevet EH, Vitola ES, da Silva BS, Cupertino RB, Picon FA, Ito LT, Tavares MEDA, Rovaris DL, Grimm O, Bau CHD. Exploring Neuroimaging Association Scores in adulthood ADHD and middle-age trajectories. J Psychiatr Res 2024; 176:348-353. [PMID: 38936238 DOI: 10.1016/j.jpsychires.2024.06.025] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/17/2023] [Revised: 05/29/2024] [Accepted: 06/17/2024] [Indexed: 06/29/2024]
Abstract
Attention-Deficit/Hyperactivity Disorder (ADHD) is a neurodevelopmental disorder associated with brain differences in children, but not in adults. A combined evaluation of the regional brain differences could improve statistical power and, consequently, allow the detection of possible effects in adults. Thus, our aim is to verify whether Neuroimaging Association Scores (NAS) are associated with adulthood ADHD and clinical trajectories of the disorder in midlife. Clinical and neuroimaging data were collected for 121 subjects with ADHD (mean age: 47.1 ± 10.5; 43% male) and 82 controls (mean age: 38.2 ± 9.0; 54.9% male). Cases were assessed seven and thirteen years after baseline diagnosis, and their clinical trajectories were classified as stable if they fulfilled ADHD diagnosis in all assessments or unstable if they presented remission and recurrence of symptoms. Neuroimaging data were acquired in the last clinical assessment (thirteen years after baseline) and NAS were calculated as a weighted sum of the associations previously reported by meta-analyses for three types of structural brain modalities: cortical thickness, cortical surface area, and subcortical volume. The NAS for cortical surface area was higher in cases compared to controls. No association was found for NAS and number of symptoms of ADHD or clinical trajectories. The fact that differences were restricted to ADHD diagnostic status suggests a susceptibility effect that is not extended to subtle aspects of the disorder. Our results also suggest that evaluating overall effects may have advantages especially when applied to adult ADHD samples.
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Affiliation(s)
- Cibele Edom Bandeira
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Eugenio Horacio Grevet
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Department of Psychiatry, Faculty of Medicine, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Eduardo Schneider Vitola
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Bruna Santos da Silva
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Basic Health Sciences, Federal University of Health Sciences of Porto Alegre (UFCSPA), Porto Alegre, Brazil
| | | | - Felipe Almeida Picon
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Lucas Toshio Ito
- Department of Biochemistry, Universidade Federal de São Paulo, São Paulo, Brazil; Laboratory of Integrative Neuroscience, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Maria Eduarda de Araujo Tavares
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil
| | - Diego Luiz Rovaris
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Physiological Genomics of Mental Health (PhysioGen Lab), Instituto de Ciencias Biomedicas da Universidade de São Paulo, São Paulo, Brazil
| | - Oliver Grimm
- Department of Psychiatry, Psychosomatic Medicine and Psychotherapy, University Hospital, Goethe University, Frankfurt, Germany
| | - Claiton Henrique Dotto Bau
- ADHD Outpatient Program, Clinical Research Center, Department of Psychiatry, Hospital de Clínicas de Porto Alegre, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Laboratory of Developmental Psychiatry, Center of Experimental Research, Hospital de Clínicas de Porto Alegre, Porto Alegre, Brazil; Graduate Program in Psychiatry and Behavioral Sciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Graduate Program in Genetics and Molecular Biology, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil; Department of Genetics, Institute of Biosciences, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
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Kuang N, Liu Z, Yu G, Wu X, Becker B, Fan H, Peng S, Zhang K, Zhao J, Kang J, Dong G, Zhao X, Sahakian BJ, Robbins TW, Cheng W, Feng J, Schumann G, Palaniyappan L, Zhang J. Neurodevelopmental risk and adaptation as a model for comorbidity among internalizing and externalizing disorders: genomics and cell-specific expression enriched morphometric study. BMC Med 2023; 21:291. [PMID: 37542243 PMCID: PMC10403847 DOI: 10.1186/s12916-023-02920-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2023] [Accepted: 06/01/2023] [Indexed: 08/06/2023] Open
Abstract
BACKGROUND Comorbidity is the rule rather than the exception for childhood and adolescent onset mental disorders, but we cannot predict its occurrence and do not know the neural mechanisms underlying comorbidity. We investigate if the effects of comorbid internalizing and externalizing disorders on anatomical differences represent a simple aggregate of the effects on each disorder and if these comorbidity-associated cortical surface differences relate to a distinct genetic underpinning. METHODS We studied the cortical surface area (SA) and thickness (CT) of 11,878 preadolescents (9-10 years) from the Adolescent Brain and Cognitive Development Study. Linear mixed models were implemented in comparative and association analyses among internalizing (dysthymia, major depressive disorder, disruptive mood dysregulation disorder, agoraphobia, panic disorder, specific phobia, separation anxiety disorder, social anxiety disorder, generalized anxiety disorder, post-traumatic stress disorder), externalizing (attention-deficit/hyperactivity disorder, oppositional defiant disorder, conduct disorder) diagnostic groups, a group with comorbidity of the two and a healthy control group. Genome-wide association analysis (GWAS) and cell type specificity analysis were performed on 4468 unrelated European participants from this cohort. RESULTS Smaller cortical surface area but higher thickness was noted across patient groups when compared to controls. Children with comorbid internalizing and externalizing disorders had more pronounced areal reduction than those without comorbidity, indicating an additive burden. In contrast, cortical thickness had a non-linear effect with comorbidity: the comorbid group had no significant CT differences, while those patient groups without comorbidity had significantly higher thickness compare to healthy controls. Distinct biological pathways were implicated in regional SA and CT differences. Specifically, CT differences were associated with immune-related processes implicating astrocytes and oligodendrocytes, while SA-related differences related mainly to inhibitory neurons. CONCLUSION The emergence of comorbidity across distinct clusters of psychopathology is unlikely to be due to a simple additive neurobiological effect alone. Distinct developmental risk moderated by immune-related adaptation processes, with unique genetic and cell-specific factors, may contribute to underlying SA and CT differences. Children with the highest risk but lowest resilience, both captured in their developmental morphometry, may develop a comorbid illness pattern.
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Affiliation(s)
- Nanyu Kuang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Zhaowen Liu
- School of Computer Science, Northwestern Polytechnical University, Xi'an, Shanxin, People's Republic of China
| | - Gechang Yu
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Xinran Wu
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Benjamin Becker
- Clinical Hospital of Chengdu Brain Science Institute, MOE Key Laboratory for Neuroinformation, University of Electronic Science and Technology of China, Chengdu, People's Republic of China
| | - Huaxin Fan
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Songjun Peng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Kai Zhang
- Institute of Computer Science and Technology, East China Normal University, Shanghai, People's Republic of China
| | - Jiajia Zhao
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
| | - Jujiao Kang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Shanghai Center for Mathematical Sciences, Fudan University, Shanghai, People's Republic of China
| | - Guiying Dong
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China
| | - Xingming Zhao
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- MOE Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence and MOE Frontiers Center for Brain Science, Fudan University, Shanghai, People's Republic of China
- Zhangjiang Fudan International Innovation Center, Shanghai, 200433, People's Republic of China
| | - Barbara J Sahakian
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Department of Psychiatry, School of Clinical Medicine, University of Cambridge, Cambridge, UK
| | - Trevor W Robbins
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Department of Psychology, Behavioural and Clinical Neuroscience Institute, University of Cambridge, Cambridge, UK
| | - Wei Cheng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, 321004, China
- Shanghai Medical College and Zhongshan Hospital Immunotherapy Technology Transfer Center, Shanghai, 200032, China
| | - Jianfeng Feng
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China
- Shanghai Center for Mathematical Sciences, Shanghai, 200433, People's Republic of China
- Department of Computer Science, University of Warwick, Coventry, CV4 7AL, UK
- Collaborative Innovation Center for Brain Science, Fudan University, Shanghai, 200433, People's Republic of China
- Fudan ISTBI-ZJNU Algorithm Centre for Brain-inspired Intelligence, Zhejiang Normal University, Jinhua, People's Republic of China
| | - Gunter Schumann
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.
- PONS Research Group, Department of Psychiatry and 20 Psychotherapy, Humboldt University, Berlin and Leibniz Institute for Neurobiology, Campus Charite Mitte, Magdeburg, Germany.
| | - Lena Palaniyappan
- Douglas Mental Health University Institute, Department of Psychiatry, McGill University, Montreal, QC, Canada.
- Department of Psychiatry, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
- Robarts Research Institute, University of Western Ontario, London, ON, Canada.
- Department of Medical Biophysica, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
| | - Jie Zhang
- Institute of Science and Technology for Brain Inspired Intelligence, Fudan University, Shanghai, People's Republic of China.
- Key Laboratory of Computational Neuroscience and Brain Inspired Intelligence, Ministry of Education, Fudan University, Beijing, People's Republic of China.
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