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- Bethlehem, RAI, et al.
(författare)
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Brain charts for the human lifespan
- 2022
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Ingår i: Nature. - : Springer Science and Business Media LLC. - 1476-4687 .- 0028-0836. ; 604:79057906, s. 525-
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Tidskriftsartikel (refereegranskat)abstract
- Over the past few decades, neuroimaging has become a ubiquitous tool in basic research and clinical studies of the human brain. However, no reference standards currently exist to quantify individual differences in neuroimaging metrics over time, in contrast to growth charts for anthropometric traits such as height and weight1. Here we assemble an interactive open resource to benchmark brain morphology derived from any current or future sample of MRI data (http://www.brainchart.io/). With the goal of basing these reference charts on the largest and most inclusive dataset available, acknowledging limitations due to known biases of MRI studies relative to the diversity of the global population, we aggregated 123,984 MRI scans, across more than 100 primary studies, from 101,457 human participants between 115 days post-conception to 100 years of age. MRI metrics were quantified by centile scores, relative to non-linear trajectories2 of brain structural changes, and rates of change, over the lifespan. Brain charts identified previously unreported neurodevelopmental milestones3, showed high stability of individuals across longitudinal assessments, and demonstrated robustness to technical and methodological differences between primary studies. Centile scores showed increased heritability compared with non-centiled MRI phenotypes, and provided a standardized measure of atypical brain structure that revealed patterns of neuroanatomical variation across neurological and psychiatric disorders. In summary, brain charts are an essential step towards robust quantification of individual variation benchmarked to normative trajectories in multiple, commonly used neuroimaging phenotypes.
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| 4. |
- Elvsashagen, T, et al.
(författare)
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The genetic architecture of human brainstem structures and their involvement in common brain disorders
- 2020
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Ingår i: Nature communications. - : Springer Science and Business Media LLC. - 2041-1723. ; 11:1, s. 4016-
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Tidskriftsartikel (refereegranskat)abstract
- Brainstem regions support vital bodily functions, yet their genetic architectures and involvement in common brain disorders remain understudied. Here, using imaging-genetics data from a discovery sample of 27,034 individuals, we identify 45 brainstem-associated genetic loci, including the first linked to midbrain, pons, and medulla oblongata volumes, and map them to 305 genes. In a replication sample of 7432 participants most of the loci show the same effect direction and are significant at a nominal threshold. We detect genetic overlap between brainstem volumes and eight psychiatric and neurological disorders. In additional clinical data from 5062 individuals with common brain disorders and 11,257 healthy controls, we observe differential volume alterations in schizophrenia, bipolar disorder, multiple sclerosis, mild cognitive impairment, dementia, and Parkinson’s disease, supporting the relevance of brainstem regions and their genetic architectures in common brain disorders.
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| 5. |
- Salvado, G., et al.
(författare)
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The protective gene dose effect of the APOE epsilon 2 allele on gray matter volume in cognitively unimpaired individuals
- 2022
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Ingår i: Alzheimers & Dementia. - : Wiley. - 1552-5260 .- 1552-5279. ; 18:7, s. 1383-1395
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Tidskriftsartikel (refereegranskat)abstract
- Introduction: Harboring two copies of the apolipoprotein E (APOE) epsilon 2 allele strongly protects against Alzheimer's disease (AD). However, the effect of this genotype on gray matter (GM) volume in cognitively unimpaired individuals has not yet been described. Methods: Multicenter brain magnetic resonance images (MRIs) from cognitively unimpaired epsilon 2 homozygotes were matched (1:1) against all other APOE genotypes for relevant confounders (n = 223). GM volumes of epsilon 2 genotypic groups were compared to each other and to the reference group (APOE epsilon 3/epsilon 3). Results: Carrying at least one epsilon 2 allele was associated with larger GM volumes in brain areas typically affected by AD and also in areas associated with cognitive resilience. APOE epsilon 2 homozygotes, but not APOE epsilon 2 heterozygotes, showed larger GM volumes in areas related to successful aging. Discussion: In addition to the known resistance against amyloid-beta deposition, the larger GM volumes in key brain regions may confer APOE epsilon 2 homozygotes additional protection against AD-related cognitive decline.
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| 7. |
- Albrecht, F., et al.
(författare)
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Unraveling Parkinson's disease heterogeneity using subtypes based on multimodal data
- 2022
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Ingår i: Parkinsonism and Related Disorders. - : Elsevier BV. - 1353-8020 .- 1873-5126. ; 102, s. 19-29
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Tidskriftsartikel (refereegranskat)abstract
- Background: Parkinson's disease (PD) is a clinically and neuroanatomically heterogeneous neurodegenerative disease characterized by different subtypes. To this date, no studies have used multimodal data that combines clinical, motor, cognitive and neuroimaging assessments to identify these subtypes, which may provide complementary, clinically relevant information. To address this limitation, we subtyped participants with mild-moderate PD based on a rich, multimodal dataset of clinical, cognitive, motor, and neuroimaging variables. Methods: Cross-sectional data from 95 PD participants from our randomized EXPANd (EXercise in PArkinson's disease and Neuroplasticity) controlled trial were included. Participants were subtyped using clinical, motor, and cognitive assessments as well as structural and resting-state MRI data. Subtyping was done by random forest clustering. We extracted information about the subtypes by inspecting their neuroimaging profiles and descriptive statistics. Results: Our multimodal subtyping analysis yielded three PD subtypes: a motor-cognitive subtype characterized by widespread alterations in brain structure and function as well as impairment in motor and cognitive abilities; a cognitive dominant subtype mainly impaired in cognitive function that showed frontoparietal structural and functional changes; and a motor dominant subtype impaired in motor variables without any brain alterations. Motor variables were most important for the subtyping, followed by gray matter volume in the right medial postcentral gyrus. Conclusions: Three distinct PD subtypes were identified in our multimodal dataset. The most important features to subtype PD participants were motor variables in addition to structural MRI in the sensorimotor region. These findings have the potential to improve our understanding of PD heterogeneity, which in turn can lead to personalized interventions and rehabilitation.
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