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Gillis G, Bhalerao G, Blane J, Mitchell R, Pretorius PM, McCracken C, Nichols TE, Smith SM, Miller KL, Alfaro‐Almagro F, Raymont V, Martos L, Mackay CE, Griffanti L. From Big Data to the Clinic: Methodological and Statistical Enhancements to Implement the UK Biobank Imaging Framework in a Memory Clinic. Hum Brain Mapp 2025; 46:e70151. [PMID: 39969115 PMCID: PMC11837031 DOI: 10.1002/hbm.70151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/14/2024] [Revised: 11/27/2024] [Accepted: 01/18/2025] [Indexed: 02/20/2025] Open
Abstract
The analysis tools and statistical methods used in large neuroimaging research studies differ from those applied in clinical contexts, making it unclear whether these techniques can be translated to a memory clinic setting. The Oxford Brain Health Clinic (OBHC) was established in 2020 to bridge this gap between research studies and memory clinics. We optimised the UK Biobank imaging framework for the memory clinic setting by integrating enhanced quality control (QC) processes (MRIQC, QUAD, and DSE decomposition) and supplementary dementia-informed analyses (lobar volumes, NBM volumes, WMH classification, PSMD, cortical diffusion MRI metrics, and tract volumes) into the analysis pipeline. We explored associations between resultant imaging-derived phenotypes (IDPs) and clinical phenotypes in the OBHC patient population (N = 213), applying hierarchical FDR correction to account for multiple testing. 14%-24% of scans were flagged by automated QC tools, but upon visual inspection, only 0%-2.4% of outputs were excluded. The pipeline successfully generated 5683 IDPs aligned with UK Biobank and 110 IDPs targeted towards dementia-related changes. We replicated established associations and found novel associations between brain metrics and age, cognition, and dementia-related diagnoses. The imaging protocol is feasible, acceptable, and yields high-quality data that is usable for both clinical and research purposes. We validated the use of this methodology in a real-world memory clinic population, which demonstrates the potential of this enhanced pipeline to bridge the gap between big data studies and clinical settings.
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Affiliation(s)
- Grace Gillis
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Oxford Health NHS Foundation TrustOxfordUK
| | - Gaurav Bhalerao
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Jasmine Blane
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Oxford Health NHS Foundation TrustOxfordUK
| | | | - Pieter M. Pretorius
- Department of NeuroradiologyOxford University Hospitals NHS Foundation TrustOxfordUK
| | - Celeste McCracken
- Division of Cardiovascular Medicine, Radcliffe Department of MedicineUniversity of OxfordOxfordUK
| | - Thomas E. Nichols
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Stephen M. Smith
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Karla L. Miller
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Fidel Alfaro‐Almagro
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Vanessa Raymont
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Oxford Health NHS Foundation TrustOxfordUK
| | - Lola Martos
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Oxford Health NHS Foundation TrustOxfordUK
| | - Clare E. Mackay
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
| | - Ludovica Griffanti
- Department of Psychiatry, Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative NeuroimagingUniversity of OxfordOxfordUK
- Oxford Health NHS Foundation TrustOxfordUK
- Nuffield Department of Clinical Neurosciences, Wellcome Centre for Integrative Neuroimaging, FMRIBUniversity of OxfordOxfordUK
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Zhang W, Dutt R, Lew D, Barch DM, Bijsterbosch JD. Higher amplitudes of visual networks are associated with trait- but not state-depression. Psychol Med 2025; 54:1-12. [PMID: 39757726 PMCID: PMC11769906 DOI: 10.1017/s0033291724003167] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/27/2024] [Revised: 09/09/2024] [Accepted: 11/07/2024] [Indexed: 01/07/2025]
Abstract
Despite depression being a leading cause of global disability, neuroimaging studies have struggled to identify replicable neural correlates of depression or explain limited variance. This challenge may, in part, stem from the intertwined state (current symptoms; variable) and trait (general propensity; stable) experiences of depression.Here, we sought to disentangle state from trait experiences of depression by leveraging a longitudinal cohort and stratifying individuals into four groups: those in remission ('trait depression group'), those with large longitudinal severity changes in depression symptomatology ('state depression group'), and their respective matched control groups (total analytic n = 1030). We hypothesized that spatial network organization would be linked to trait depression due to its temporal stability, whereas functional connectivity between networks would be more sensitive to state-dependent depression symptoms due to its capacity to fluctuate.We identified 15 large-scale probabilistic functional networks from resting-state fMRI data and performed group comparisons on the amplitude, connectivity, and spatial overlap between these networks, using matched control participants as reference. Our findings revealed higher amplitude in visual networks for the trait depression group at the time of remission, in contrast to controls. This observation may suggest altered visual processing in individuals predisposed to developing depression over time. No significant group differences were observed in any other network measures for the trait-control comparison, nor in any measures for the state-control comparison. These results underscore the overlooked contribution of visual networks to the psychopathology of depression and provide evidence for distinct neural correlates between state and trait experiences of depression.
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Affiliation(s)
- Wei Zhang
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
| | - Rosie Dutt
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Biological Sciences Collegiate Division, University of Chicago, Chicago, IL, USA
| | - Daphne Lew
- Center for Biostatistics and Data Science, Institute for Informatics, Data Science, and Biostatistics, Washington University School of Medicine, St. Louis, MO, USA
| | - Deanna M. Barch
- Department of Radiology, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychiatry, Washington University School of Medicine, St. Louis, MO, USA
- Department of Psychological and Brain Sciences, Washington University in St. Louis, St. Louis, MO, USA
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Zhang X, Liang C, Feng M, Xin H, Fu Y, Gao Y, Sui C, Wang N, Wang Y, Zhang N, Guo L, Wen H. Aberrant brain structural-functional connectivity coupling associated with cognitive dysfunction in different cerebral small vessel disease burdens. CNS Neurosci Ther 2024; 30:e70005. [PMID: 39228091 PMCID: PMC11371661 DOI: 10.1111/cns.70005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2024] [Revised: 07/19/2024] [Accepted: 08/06/2024] [Indexed: 09/05/2024] Open
Abstract
AIMS Emerging evidence suggests that cerebral small vessel disease (CSVD) pathology changes brain structural connectivity (SC) and functional connectivity (FC) networks. Although network-level SC and FC are closely coupled in the healthy population, how SC-FC coupling correlates with neurocognitive outcomes in patients with different CSVD burdens remains largely unknown. METHODS Using multimodal MRI, we reconstructed whole-brain SC and FC networks for 54 patients with severe CSVD burden (CSVD-s), 106 patients with mild CSVD burden (CSVD-m), and 79 healthy controls. We then investigated the aberrant SC-FC coupling and functional network topology in CSVD and their correlations with cognitive dysfunction. RESULTS Compared with controls, the CSVD-m patients showed no significant change in any SC-FC coupling, but the CSVD-s patients exhibited significantly decreased whole-brain (p = 0.014), auditory/motor (p = 0.033), and limbic modular (p = 0.011) SC-FC coupling. For functional network topology, despite no change in global efficiency, CSVD-s patients exhibited significantly reduced nodal efficiency of the bilateral amygdala (p = 0.024 and 0.035) and heschl gyrus (p = 0.001 and 0.005). Notably, for the CSVD-s patients, whole-brain SC-FC coupling showed a significantly positive correlation with MoCA (r = 0.327, p = 0.020) and SDMT (r = 0.373, p = 0.008) scores, limbic/subcortical modular SC-FC coupling showed a negative correlation (r = -0.316, p = 0.025) with SCWT score, and global/local efficiency (r = 0.367, p = 0.009 and r = 0.353, p = 0.012) showed a positive correlation with AVLT score. For the CSVD-m group, whole-brain and auditory/motor modular SC-FC couplings showed significantly positive correlations with SCWT (r = 0.217, p = 0.028 and r = 0.219, p = 0.027) and TMT (r = 0.324, p = 0.001 and r = 0.245, p = 0.013) scores, and global/local efficiency showed positive correlations with AVLT (r = 0.230, p = 0.020 and r = 0.248, p = 0.012) and SDMT (r = 0.263, p = 0.008 and r = 0.263, p = 0.007) scores. CONCLUSION Our findings demonstrated that decreased whole-brain and module-dependent SC-FC coupling associated with reduced functional efficiency might underlie more severe burden and worse cognitive decline in CSVD. SC-FC coupling might serve as a more sensitive neuroimaging biomarker of CSVD burden and provided new insights into the pathophysiologic mechanisms of clinical development of CSVD.
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Affiliation(s)
- Xinyue Zhang
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Changhu Liang
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Mengmeng Feng
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Haotian Xin
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Yajie Fu
- Shandong Medicine and Health Key Laboratory of Abdominal Medical Imaging, Department of Medical Ultrasound, The First Affiliated Hospital of Shandong First Medical University and Shandong Provincial Qianfoshan Hospital, Jinan, Shandong, China
| | - Yian Gao
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Chaofan Sui
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Na Wang
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Yuanyuan Wang
- School of Medical Imaging, Binzhou Medical University, Yantai, Shandong, China
| | - Nan Zhang
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Lingfei Guo
- Key Laboratory of Endocrine Glucose and Lipids Metabolism and Brain Aging, Department of Radiology, Ministry of Education, Shandong Provincial Hospital Affiliated to Shandong First Medical University, Jinan, Shandong, China
| | - Hongwei Wen
- Key Laboratory of Cognition and Personality (Ministry of Education), Faculty of Psychology, Southwest University, Chongqing, China
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Kok DE, Saunders R, Nelson A, Smith D, Ford D, Mathers JC, McKay JA. Influence of maternal folate depletion on Art3 DNA methylation in the murine adult brain; potential consequences for brain and neurocognitive health. Mutagenesis 2024; 39:196-204. [PMID: 38417824 PMCID: PMC11040152 DOI: 10.1093/mutage/geae007] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 02/27/2024] [Indexed: 03/01/2024] Open
Abstract
The developmental origins of health and disease hypothesis suggest early-life environment impacts health outcomes throughout the life course. In particular, epigenetic marks, including DNA methylation, are thought to be key mechanisms through which environmental exposures programme later-life health. Adequate maternal folate status before and during pregnancy is essential in the protection against neural tube defects, but data are emerging that suggest early-life folate exposures may also influence neurocognitive outcomes in childhood and, potentially, thereafter. Since folate is key to the supply of methyl donors for DNA methylation, we hypothesize that DNA methylation may be a mediating mechanism through which maternal folate influences neurocognitive outcomes. Using bisulphite sequencing, we measured DNA methylation of five genes (Art3, Rsp16, Tspo, Wnt16, and Pcdhb6) in the brain tissue of adult offspring of dams who were depleted of folate (n = 5, 0.4 mg folic acid/kg diet) during pregnancy (~19-21 days) and lactation (mean 22 days) compared with controls (n = 6, 2 mg folic acid/kg diet). Genes were selected as methylation of their promoters had previously been found to be altered by maternal folate intake in mice and humans across the life course, and because they have potential associations with neurocognitive outcomes. Maternal folate depletion was significantly associated with Art3 gene hypomethylation in subcortical brain tissue of adult mice at 28 weeks of age (mean decrease 6.2%, P = .03). For the other genes, no statistically significant differences were found between folate depleted and control groups. Given its association with neurocognitive outcomes, we suggest Art3 warrants further study in the context of lifecourse brain health. We have uncovered a potential biomarker that, once validated in accessible biospecimens and human context, may be useful to track the impact of early-life folate exposure on later-life neurocognitive health, and potentially be used to develop and monitor the effects of interventions.
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Affiliation(s)
- Dieuwertje E Kok
- Division of Human Nutrition and Health, Wageningen University & Research, P.O. Box 17, 6700 AA Wageningen Stippeneng 4, 6708 WE Wageningen Wageningen Campus l Building 124 (Helix), Wageningen, The Netherlands
| | - Rachael Saunders
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Andrew Nelson
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Darren Smith
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - Dianne Ford
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
| | - John C Mathers
- Human Nutrition & Exercise Research Centre, Centre for Healthier Lives, Population Health Sciences Institute, Newcastle University, Room M2.060, 2nd floor William Leech Building, Framlington Place, Newcastle upon Tyne, NE2 4HH, United Kingdom
| | - Jill A McKay
- Department of Applied Sciences, Faculty of Health and Life Sciences, Northumbria University, Northumberland Building, Newcastle Upon Tyne, NE1 8ST, United Kingdom
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