White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life
Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the un...
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Elsevier
2025-04-01
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| Series: | NeuroImage |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S105381192500134X |
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| author | Max Korbmacher Mario Tranfa Giuseppe Pontillo Dennis van der Meer Meng-Yun Wang Ole A. Andreassen Lars T. Westlye Ivan I. Maximov |
| author_facet | Max Korbmacher Mario Tranfa Giuseppe Pontillo Dennis van der Meer Meng-Yun Wang Ole A. Andreassen Lars T. Westlye Ivan I. Maximov |
| author_sort | Max Korbmacher |
| collection | DOAJ |
| description | Advanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life. |
| format | Article |
| id | doaj-art-b0a8fd4541884738ae5978c185564f30 |
| institution | OA Journals |
| issn | 1095-9572 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | NeuroImage |
| spelling | doaj-art-b0a8fd4541884738ae5978c185564f302025-08-20T02:07:57ZengElsevierNeuroImage1095-95722025-04-0131012113210.1016/j.neuroimage.2025.121132White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late lifeMax Korbmacher0Mario Tranfa1Giuseppe Pontillo2Dennis van der Meer3Meng-Yun Wang4Ole A. Andreassen5Lars T. Westlye6Ivan I. Maximov7Neuro-SysMed Center of Excellence for Clinical Research in Neurological Diseases, Department of Neurology, Haukeland University Hospital, Bergen, Norway; Mohn Medical Imaging and Visualization Centre (MMIV),Department of Radiology, Haukeland University Hospital, Bergen, Norway; Department of Health and Functioning, Western Norway University of Applied Sciences, Bergen, Norway; Correspondence to: Neuro-SysMed group, Department of Neurology, Haukeland University Hospital, Haukelandsveien 22, 5009 Bergen, Norway.Department of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy; Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam,Amsterdam UMC location VUMC, Amsterdam, The NetherlandsDepartment of Advanced Biomedical Sciences, University “Federico II”, Naples, Italy; Department of Radiology and Nuclear Medicine, Vrije Universiteit Amsterdam,Amsterdam UMC location VUMC, Amsterdam, The Netherlands; Department of Brain Repair & Rehabilitation, UCL Queen Square Institute of Neurology,University College London, London, United KingdomCenter for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, NorwayMax Planck Institute for Psycholinguistics, Nijmegen, NetherlandsCenter for Precision Psychiatry, University of Oslo and Oslo University Hospital, Oslo, NorwayDepartment of Psychology, University of Oslo, Oslo, Norway; KG Jebsen Centre for Neurodevelopmental Disorders, University of Oslo, Oslo, NorwayDepartment of Health and Functioning, Western Norway University of Applied Sciences, Bergen, NorwayAdvanced diffusion magnetic resonance imaging (dMRI) allows one to probe and assess brain white matter (WM) organisation and microstructure in vivo. Various dMRI models with different theoretical and practical assumptions have been developed, representing partly overlapping characteristics of the underlying brain biology with potentially complementary value in the cognitive and clinical neurosciences. To which degree the different dMRI metrics relate to clinically relevant geno- and phenotypes is still debated. Hence, we investigate how tract-based and whole WM skeleton parameters from different dMRI approaches associate with clinically relevant and white matter-related phenotypes (sex, age, pulse pressure (PP), body-mass-index (BMI), brain asymmetry) and genetic markers in the UK Biobank (UKB, n=52,140) and the Adolescent Brain Cognitive Development (ABCD) Study (n=5,844). In general, none of the imaging approaches could explain all examined phenotypes, though the approaches were overall similar in explaining variability of the examined phenotypes. Nevertheless, particular diffusion parameters of the used dMRI approaches stood out in explaining some important phenotypes known to correlate with general human health outcomes. A multi-compartment Bayesian dMRI approach provided the strongest WM associations with age, and together with diffusion tensor imaging, the largest accuracy for sex-classifications. We find a similar pattern of metric and tract-dependent asymmetries across datasets, with stronger asymmetries in ABCD data. The magnitude of WM associations with polygenic scores as well as PP depended more on the sample, and likely age, than dMRI metrics. However, kurtosis was most indicative of BMI and potentially of bipolar disorder polygenic scores. We conclude that WM microstructure is differentially associated with clinically relevant pheno- and genotypes at different points in life.http://www.sciencedirect.com/science/article/pii/S105381192500134XWhite matter microstructureDiffusion MRIMagnetic resonance imagingBrain ageing |
| spellingShingle | Max Korbmacher Mario Tranfa Giuseppe Pontillo Dennis van der Meer Meng-Yun Wang Ole A. Andreassen Lars T. Westlye Ivan I. Maximov White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life NeuroImage White matter microstructure Diffusion MRI Magnetic resonance imaging Brain ageing |
| title | White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life |
| title_full | White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life |
| title_fullStr | White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life |
| title_full_unstemmed | White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life |
| title_short | White matter microstructure links with brain, bodily and genetic attributes in adolescence, mid- and late life |
| title_sort | white matter microstructure links with brain bodily and genetic attributes in adolescence mid and late life |
| topic | White matter microstructure Diffusion MRI Magnetic resonance imaging Brain ageing |
| url | http://www.sciencedirect.com/science/article/pii/S105381192500134X |
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