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- Tønnesen, Siren, et al.
(författare)
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Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder : A Multisample Diffusion Tensor Imaging Study
- 2020
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Ingår i: Biological Psychiatry. - : Elsevier BV. - 2451-9022 .- 2451-9030. ; 5:12, s. 1095-1103
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Tidskriftsartikel (refereegranskat)abstract
- BACKGROUND: Schizophrenia (SZ) and bipolar disorder (BD) share substantial neurodevelopmental components affecting brain maturation and architecture. This necessitates a dynamic lifespan perspective in which brain aberrations are inferred from deviations from expected lifespan trajectories. We applied machine learning to diffusion tensor imaging (DTI) indices of white matter structure and organization to estimate and compare brain age between patients with SZ, patients with BD, and healthy control (HC) subjects across 10 cohorts.METHODS: We trained 6 cross-validated models using different combinations of DTI data from 927 HC subjects (18-94 years of age) and applied the models to the test sets including 648 patients with SZ (18-66 years of age), 185 patients with BD (18-64 years of age), and 990 HC subjects (17-68 years of age), estimating the brain age for each participant. Group differences were assessed using linear models, accounting for age, sex, and scanner. A meta-analytic framework was applied to assess the heterogeneity and generalizability of the results.RESULTS: Tenfold cross-validation revealed high accuracy for all models. Compared with HC subjects, the model including all feature sets significantly overestimated the age of patients with SZ (Cohen's d = -0.29) and patients with BD (Cohen's d = 0.18), with similar effects for the other models. The meta-analysis converged on the same findings. Fractional anisotropy-based models showed larger group differences than the models based on other DTI-derived metrics.CONCLUSIONS: Brain age prediction based on DTI provides informative and robust proxies for brain white matter integrity. Our results further suggest that white matter aberrations in SZ and BD primarily consist of anatomically distributed deviations from expected lifespan trajectories that generalize across cohorts and scanners.
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| 2. |
- Beck, Dani, et al.
(författare)
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Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults
- 2022
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Ingår i: NeuroImage. - : Elsevier Science Ltd. - 2213-1582. ; 33
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Tidskriftsartikel (refereegranskat)abstract
- There is an intimate body-brain connection in ageing, and obesity is a key risk factor for poor cardiometabolic health and neurodegenerative conditions. Although research has demonstrated deleterious effects of obesity on brain structure and function, the majority of studies have used conventional measures such as waist-to-hip ratio, waist circumference, and body mass index. While sensitive to gross features of body composition, such global anthropometric features fail to describe regional differences in body fat distribution and composition. The sample consisted of baseline brain magnetic resonance imaging (MRI) acquired from 790 healthy participants aged 18-94 years (mean +/- standard deviation (SD) at baseline: 46.8 +/- 16.3), and follow-up brain MRI collected from 272 of those individuals (two time-points with 19.7 months interval, on average (min = 9.8, max = 35.6). Of the 790 included participants, cross-sectional body MRI data was available from a subgroup of 286 participants, with age range 19-86 (mean = 57.6, SD = 15.6). Adopting a mixed cross-sectional and longitudinal design, we investigated cross-sectional body magnetic resonance imaging measures of adipose tissue distribution in relation to longitudinal brain structure using MRI-based morphometry (T1) and diffusion tensor imaging (DTI). We estimated tissue-specific brain age at two time points and performed Bayesian multilevel modelling to investigate the associations between adipose measures at follow-up and brain age gap (BAG) - the difference between actual age and the prediction of the brains biological age - at baseline and follow-up. We also tested for interactions between BAG and both time and age on each adipose measure. The results showed credible associations between T1-based BAG and liver fat, muscle fat infiltration (MFI), and weight-to-muscle ratio (WMR), indicating older-appearing brains in people with higher measures of adipose tissue. Longitudinal evidence supported interaction effects between time and MFI and WMR on T1-based BAG, indicating accelerated ageing over the course of the study period in people with higher measures of adipose tissue. The results show that specific measures of fat distribution are associated with brain ageing and that different compartments of adipose tissue may be differentially linked with increased brain ageing, with potential to identify key processes involved in age-related transdiagnostic disease processes.
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| 3. |
- Moltu, Sissel J., et al.
(författare)
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Arachidonic and docosahexaenoic acid supplementation and brain maturation in preterm infants : a double blind RCT
- 2024
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Ingår i: Clinical Nutrition. - : Elsevier. - 0261-5614 .- 1532-1983. ; 43:1, s. 176-186
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Tidskriftsartikel (refereegranskat)abstract
- Background: Arachidonic acid (ARA) and docosahexaenoic acid (DHA) are important structural components of neural cellular membranes and possess anti-inflammatory properties. Very preterm infants are deprived of the enhanced placental supply of these fatty acids, but the benefit of postnatal supplementation on brain development is uncertain. The aim of this study was to test the hypothesis that early enteral supplementation with ARA and DHA in preterm infants improves white matter (WM) microstructure assessed by diffusion-weighted MRI at term equivalent age.Methods: In this double-blind, randomized controlled trial, infants born before 29 weeks gestational age were allocated to either 100 mg/kg ARA and 50 mg/kg DHA (ARA:DHA group) or medium chain triglycerides (control). Supplements were started on the second day of life and provided until 36 weeks postmenstrual age. The primary outcome was brain maturation assessed by diffusion tensor imaging (DTI) using Tract-Based Spatial Statistics (TBSS) analysis.Results: We included 120 infants (60 per group) in the trial; mean (range) gestational age was 26+3 (22+6 - 28+6) weeks and postmenstrual age at scan was 41+3 (39+1 - 47+0) weeks. Ninety-two infants underwent MRI imaging, and of these, 90 had successful T1/T2 weighted MR images and 74 had DTI data of acceptable quality. TBSS did not show significant differences in mean or axial diffusivity between the groups, but demonstrated significantly higher fractional anisotropy in several large WM tracts in the ARA:DHA group, including corpus callosum, the anterior and posterior limb of the internal capsula, inferior occipitofrontal fasciculus, uncinate fasciculus, and the inferior longitudinal fasciculus. Radial diffusivity was also significantly lower in several of the same WM tracts in the ARA:DHA group.Conclusion: This study suggests that supplementation with ARA and DHA at doses matching estimated fetal accretion rates improves WM maturation compared to control treatment, but further studies are needed to ascertain any functional benefit.Clinical trial registration: www.clinicaltrials.gov; ID:NCT03555019.
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| 5. |
- Schindler, Louise S., et al.
(författare)
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Associations between abdominal adipose tissue, reproductive span, and brain characteristics in post-menopausal women
- 2022
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Ingår i: NeuroImage. - : ELSEVIER SCI LTD. - 2213-1582. ; 36
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Tidskriftsartikel (refereegranskat)abstract
- The menopause transition involves changes in oestrogens and adipose tissue distribution, which may influence female brain health post-menopause. Although increased central fat accumulation is linked to risk of cardiometabolic diseases, adipose tissue also serves as the primary biosynthesis site of oestrogens post-menopause. It is unclear whether different types of adipose tissue play diverging roles in female brain health post-menopause, and whether this depends on lifetime oestrogen exposure, which can have lasting effects on the brain and body even after menopause. Using the UK Biobank sample, we investigated associations between brain characteristics and visceral adipose tissue (VAT) and abdominal subcutaneous adipose tissue (ASAT) in 10,251 post-menopausal females, and assessed whether the relationships varied depending on length of reproductive span (age at menarche to age at menopause). To parse the effects of common genetic variation, we computed polygenic scores for reproductive span. The results showed that higher VAT and ASAT were both associated with higher grey and white matter brain age, and greater white matter hyperintensity load. The associations varied positively with reproductive span, indicating more prominent associations between adipose tissue and brain measures in females with a longer reproductive span. The effects were in general small, but could not be fully explained by genetic variation or relevant confounders. Our findings indicate that associations between abdominal adipose tissue and brain health post-menopause may partly depend on individual differences in cumulative oestrogen exposure during reproductive years, emphasising the complexity of neural and endocrine ageing processes in females.
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