Psychiatry and Neuroimaging Genetics

The overall goal of our research is to better understand the biological underpinnings of psychiatric disorders using novel analytical approaches in magnetic resonance imaging (MRI) and genetics. In recent years, advances in genetics and neuroimaging have led to unprecedented amounts of biological data in relation to psychiatric disorders. Now, the challenge is to translate these data into useful knowledge for clinical psychiatry. We use several strategies to enhance the clinical potential of neuroimaging and genetics for psychiatry. Our approach generally involves data-driven methods in genomics and neuroimaging, with application to longitudinal and deeply phenotyped clinical samples.

The processes underlying the remission of a psychiatric disorder are not necessarily the same as the reversal of the causes. In our project “Determinants of Long-term Trajectories in ADHD” (DELTA), we aim to identify genetic and brain factors that specifically contribute to remission and persistence of attention-deficit/hyperactivity disorders (ADHD). In DELTA, we are conducting a 4^th follow-up of children who participated in the Dutch NeuroIMAGE study of ADHD. These individuals are now between 18 and 35 years old, and have been studied for up to 16 years, providing genetic data, MRI scans, and detailed clinical, cognitive and demographic information. Capitalising on our 7 Tesla scanner at the Erwin L. Hahn Institute in Essen, we added as a new measurement an ultra-high resolution MP2RAGHE scan, which allows us investigate cortical morphology in the finest anatomical detail.

Very large sample sizes are required to obtain statistics that reliable describe genome-brain-behaviour relationships. In contrast, studies like DELTA, with detailed clinical information, novel neuroimaging data, and/or longitudinal information, tend to be small. Therefore, a second important focus of our group is the innovative use of genome-wide statistics from large samples and consortia, with applied modelling to our own data. For example, we show that contrasting adult case-control genome-wide statistics with children’s case-control genome-wide statistics can be used to compute a new polygenic score that is associated with clinical changes over time within the individual patient.

Current progress in multifactorial genetics and neuroimaging in psychiatry, and especially their combination, would not be possible without international consortia. Our group participates in several ENIGMA working groups (ENIGMA1-3, ADHD, Bipolar Disorder, Schizophrenia, DTI, Plasticity, Lifespan), and we are members of the IMpACT Consortium, and the ADHD working group of the Psychiatric Genomics Consortium (PGC).

Emma.sprooten@donders.ru.nl

Department of Cognitive Neuroscience
Radboud University Nijmegen Medical Centre
P.O. Box 9101 / HP 205
6500 HB Nijmegen
The Netherlands

- Guimaraes JPOFT, Franke B, Beckmann CF, Bralten J, Sprooten E. (2021) Missing genetic links between general factors of brain resting-state functional magnetic resonance imaging, cognition and psychopathology. BioRxiv 2021.11.19.469227; doi: https://doi.org/10.1101/2021.11.19.469227.

- Damatac CG, Soheili-Nezhad S, Freches GB, Zwiers MP, de Bruijn S, Ikde S, Portengen CM, Abelmann AC, Dammers JT, van Rooij D, Akkermans SEA, Naaijen J, Franke B, Buitelaar JK, Beckmann CF, Sprooten E (2021). Longitudinal changes of ADHD symptoms in association with white matter microstructure: a tract-specific fixel-based analysis. bioRxiv 2021.11.19.469248; doi: https://doi.org/10.1101/2021.11.19.469248. 

- Soheili-Nezhad S, Beckmann CF, Sprooten E. (2021) Independent Genomic Sources of Brain Structure and Function. bioRxiv 2021.01.06.425535; doi: https://doi.org/10.1101/2021.01.06.425535

- Brouwer, Rachel M. & ENIGMA plasticity working group, et al. (In Press). Age-dependent genetic variants associated with longitudinal changes in brain structure across the lifespan. Nature Neuroscience.

- Guimaraes JPOFT, Sprooten E, Beckmann CF, Franke B, Bralten J. (In Press). Shared genetic influences on resting-state functional networks of the brain. Human Brain Mapp..

- Leenders AEM, Damatac CG, Soheili-Nezhad S, Chauvin RJM, Mennes MJJ, Zwiers MP, van Rooij D, Akkermans SEA Naaijen J, Franke B, Buitelaar JK, Beckmann CF, Sprooten E. (2021) Associations between attention-deficit hyperactivity disorder (ADHD) symptom remission and white matter microstructure: A longitudinal analysis. J Child Adolesc Psychiatry Advances. https://doi.org/10.1002/jcv2.12040.​

- Sprooten E, Franke B, Greven CU (2021). The P-factor and its genomic and neural equivalents: an integrated perspective. Mol Psychiatry. 2021 Feb 1. doi: 10.1038/s41380-021-01031-2. PMID: 33526822.

- Soheili-Nezhad S, van der Linden RJ, Olde Rikkert M, Sprooten E*, Poelmans G* (2021). Long genes are more frequently affected by somatic mutations and show reduced expression in Alzheimer's disease: Implications for disease etiology. Alzheimers Dement. Mar;17(3):489-499. doi: 10.1002/alz.12211. Epub 2020 Oct 19. PMID: 33075204. *Shared last authors.

- Damatac CG, Chauvin RJM, Zwiers MP, van Rooij D, Akkermans SEA, Naaijen J, Hoekstra PJ, Hartman CA, Oosterlaan J, Franke B, Buitelaar JK, Beckmann CF, Sprooten E (2020). White Matter Microstructure in Attention-Deficit/Hyperactivity Disorder: A Systematic Tractography Study in 654 Individuals. Biol Psychiatry Cogn Neurosci Neuroimaging. S2451-9022(20)30205-6. doi: 10.1016/j.bpsc.2020.07.015. PMID: 33054990. 

- Cupertino RB, Soheili-Nezhad S, Grevet EH, Bandeira CE, Picon FA, Tavares MEA, Naaijen J, van Rooij D, Akkermans S, Vitola ES, Zwiers MP, Rovaris DL, Hoekstra PJ, Breda V, Oosterlaan J, Hartman CA, Beckmann CF, Buitelaar JK, Franke B, Bau CHD, Sprooten E (2020). Reduced fronto-striatal volume in attention-deficit/hyperactivity disorder in two cohorts across the lifespan. Neuroimage Clin. 28:102403. doi: 10.1016/j.nicl.2020.102403. PMID: 32949876.

- Soheili-Nezhad S, Jahanshad N, Guelfi S, Khosrowabadi R, Saykin AJ, Thompson PM, Beckmann CF, Sprooten E, Zarei M (2020); Alzheimer's Disease Neuroimaging. Imaging genomics discovery of a new risk variant for Alzheimer's disease in the postsynaptic SHARPIN gene. Hum Brain Mapp. Sep;41(13):3737-3748. doi: 10.1002/hbm.25083. PMID: 32558014.

- Rovira P, & ADHD Working Group of the PGC; et al. (2020). Neuropsychopharmacology. 45(10):1617-1626. doi: 10.1038/s41386-020-0664-5. Epub 2020 Apr 12. PMID: 32279069. ​

- Guimaraes JPOFT, Bralten J, Greven CU, Franke B, Sprooten E*, Beckmann CF* (2019). Discovering the shared biology of cognitive traits determined by genetic overlap. Neuroimage. 2020 Mar;208:116409. doi: 10.1016/j.neuroimage.2019.116409. PMID: 31785419. *Shared last authors ​

- Soheili-Nezhad S, Sedghi A, Schweser F, Eslami Shahr Babaki A, Jahanshad N, Thompson PM, Beckmann CF, Sprooten E, Toghae M (2019). Structural and Functional Reorganization of the Brain in Migraine Without Aura. Front Neurol. 10:442. doi: 10.3389/fneur.2019.00442. PMID: 31133962.

- Sprooten E, O'Halloran R, Dinse J, Lee WH, Moser DA, Doucet GE, Goodman M, Krinsky H, Paulino A, Rasgon A, Leibu E, Balchandani P, Inglese M, Frangou S (2019). Depth-dependent intracortical myelin organization in the living human brain determined by in vivo ultra-high field magnetic resonance imaging. Neuroimage. 185:27-34. doi: 10.1016/j.neuroimage.2018.10.023. PMID: 30312809.

- Sprooten E, Rasgon A, Goodman M, Carlin A, Leibu E, Lee WH, Frangou S (2017). Addressing reverse inference in psychiatric neuroimaging: Meta-analyses of task-related brain activation in common mental disorders. Hum Brain Mapp. 38(4):1846-1864. doi: 10.1002/hbm.23486. Epub 2017 Jan 9. PubMed PMID: 28067006; PubMed Central PMCID: PMC5347927.

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