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1.
Neuroimage ; 261: 119503, 2022 11 01.
Artículo en Inglés | MEDLINE | ID: mdl-35878723

RESUMEN

Brain iron homeostasis is necessary for healthy brain function. MRI and histological studies have shown altered brain iron levels in the brains of patients with multiple sclerosis (MS), particularly in the deep gray matter (DGM). Previous studies were able to only partially separate iron-modifying effects because of incomplete knowledge of iron-modifying processes and influencing factors. It is therefore unclear to what extent and at which stages of the disease different processes contribute to brain iron changes. We postulate that spatially covarying magnetic susceptibility networks determined with Independent Component Analysis (ICA) reflect, and allow for the study of, independent processes regulating iron levels. We applied ICA to quantitative susceptibility maps for 170 individuals aged 9-81 years without neurological disease ("Healthy Aging" (HA) cohort), and for a cohort of 120 patients with MS and 120 age- and sex-matched healthy controls (HC; together the "MS/HC" cohort). Two DGM-associated "susceptibility networks" identified in the HA cohort (the Dorsal Striatum and Globus Pallidus Interna Networks) were highly internally reproducible (i.e. "robust") across multiple ICA repetitions on cohort subsets. DGM areas overlapping both robust networks had higher susceptibility levels than DGM areas overlapping only a single robust network, suggesting that these networks were caused by independent processes of increasing iron concentration. Because MS is thought to accelerate brain aging, we hypothesized that associations between age and the two robust DGM-associated networks would be enhanced in patients with MS. However, only one of these networks was altered in patients with MS, and it had a null age association in patients with MS rather than a stronger association. Further analysis of the MS/HC cohort revealed three additional disease-related networks (the Pulvinar, Mesencephalon, and Caudate Networks) that were differentially altered between patients with MS and HCs and between MS subtypes. Exploratory regression analyses of the disease-related networks revealed differential associations with disease duration and T2 lesion volume. Finally, analysis of ROI-based disease effects in the MS/HC cohort revealed an effect of disease status only in the putamen ROI and exploratory regression analysis did not show associations between the caudate and pulvinar ROIs and disease duration or T2 lesion volume, showing the ICA-based approach was more sensitive to disease effects. These results suggest that the ICA network framework increases sensitivity for studying patterns of brain iron change, opening a new avenue for understanding brain iron physiology under normal and disease conditions.


Asunto(s)
Encefalopatías , Esclerosis Múltiple , Encéfalo/diagnóstico por imagen , Encéfalo/patología , Encefalopatías/patología , Sustancia Gris/patología , Humanos , Hierro/análisis , Imagen por Resonancia Magnética/métodos , Esclerosis Múltiple/diagnóstico por imagen , Esclerosis Múltiple/patología
2.
Curr Genomics ; 19(6): 420-430, 2018 Sep.
Artículo en Inglés | MEDLINE | ID: mdl-30258274

RESUMEN

Adult-onset neuropsychiatric diseases are one of the most challenging areas of medicine. While symptomatic treatments are available, for most of these diseases the exact pathomechanism is not known, thus, disease-modifying therapies are difficult to conceptualize and find. The two most common and best studied neuropsychiatric diseases affecting higher cortical functions in humans are schizophrenia and Alzheimer's disease; both diseases have high heritability, however, the genetic architecture is not fully elucidated. Robust Single Nucleotide Variant (SNV) studies have identified several loci with modest effect sizes. While Copy Number Variants (CNV) make an important contribution to genetic variation, CNV GWAS suffer from dependence on mainly SNP arrays with underperforming genotyping accuracy. We evaluated dynamic range of the assays for three types of CNV loci, including biallelic deletion, high copy gain, and fusion gene, to assess the depth of exploration of the contribution of CNVs to disease susceptibility. Despite the suboptimal genotyping, novel mechanisms are emerging and further large-scale studies with genotyping assays optimized for CNV detection are needed. Furthermore, the CHRFAM7A human-specific fusion gene association warrants large scale locus specific association studies in AD, schizophrenia, bipolar disorder and ADHD.

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