| 1. |
- Tønnesen, Siren, et al.
(författare)
-
Brain Age Prediction Reveals Aberrant Brain White Matter in Schizophrenia and Bipolar Disorder : A Multisample Diffusion Tensor Imaging Study
- 2020
-
Ingår i: Biological Psychiatry. - : Elsevier BV. - 2451-9022 .- 2451-9030. ; 5:12, s. 1095-1103
-
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.
|
|
| 2. |
- Beck, Dani, et al.
(författare)
-
Adipose tissue distribution from body MRI is associated with cross-sectional and longitudinal brain age in adults
- 2022
-
Ingår i: NeuroImage. - : Elsevier Science Ltd. - 2213-1582. ; 33
-
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.
|
|
| 3. |
- Beck, Dani, et al.
(författare)
-
Dissecting unique and common variance across body and brain health indicators using age prediction
- 2024
-
Ingår i: Human Brain Mapping. - : WILEY. - 1065-9471 .- 1097-0193. ; 45:6
-
Tidskriftsartikel (refereegranskat)abstract
- Ageing is a heterogeneous multisystem process involving different rates of decline in physiological integrity across biological systems. The current study dissects the unique and common variance across body and brain health indicators and parses inter-individual heterogeneity in the multisystem ageing process. Using machine-learning regression models on the UK Biobank data set (N = 32,593, age range 44.6-82.3, mean age 64.1 years), we first estimated tissue-specific brain age for white and gray matter based on diffusion and T1-weighted magnetic resonance imaging (MRI) data, respectively. Next, bodily health traits, including cardiometabolic, anthropometric, and body composition measures of adipose and muscle tissue from bioimpedance and body MRI, were combined to predict 'body age'. The results showed that the body age model demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. The correlation between body age and brain age predictions was 0.62 for the T1 and 0.64 for the diffusion-based model, indicating a degree of unique variance in brain and bodily ageing processes. Bayesian multilevel modelling carried out to quantify the associations between health traits and predicted age discrepancies showed that higher systolic blood pressure and higher muscle-fat infiltration were related to older-appearing body age compared to brain age. Conversely, higher hand-grip strength and muscle volume were related to a younger-appearing body age. Our findings corroborate the common notion of a close connection between somatic and brain health. However, they also suggest that health traits may differentially influence age predictions beyond what is captured by the brain imaging data, potentially contributing to heterogeneous ageing rates across biological systems and individuals. A 'body age' model trained on health traits demonstrated comparable age prediction accuracy to models trained solely on brain MRI data. Health traits may differentially influence age predictions beyond what is captured by the brain imaging data, revealing a degree of unique variance in brain and bodily ageing processes. image
|
|
| 4. |
- Benatar, Michael, et al.
(författare)
-
Safety and efficacy of arimoclomol in patients with early amyotrophic lateral sclerosis (ORARIALS-01) : a randomised, double-blind, placebo-controlled, multicentre, phase 3 trial
- 2024
-
Ingår i: Lancet Neurology. - : Elsevier. - 1474-4422 .- 1474-4465. ; 23:7, s. 687-699
-
Tidskriftsartikel (refereegranskat)abstract
- Background: Amyotrophic lateral sclerosis is a progressive neurodegenerative disorder leading to muscle weakness and respiratory failure. Arimoclomol, a heat-shock protein-70 (HSP70) co-inducer, is neuroprotective in animal models of amyotrophic lateral sclerosis, with multiple mechanisms of action, including clearance of protein aggregates, a pathological hallmark of sporadic and familial amyotrophic lateral sclerosis. We aimed to evaluate the safety and efficacy of arimoclomol in patients with amyotrophic lateral sclerosis.Methods: ORARIALS-01 was a multinational, randomised, double-blind, placebo-controlled, parallel-group trial done at 29 centres in 12 countries in Europe and North America. Patients were eligible if they were aged 18 years or older and met El Escorial criteria for clinically possible, probable, probable laboratory-supported, definite, or familial amyotrophic lateral sclerosis; had an ALS Functional Rating Scale-Revised score of 35 or more; and had slow vital capacity at 70% or more of the value predicted on the basis of the participant's age, height, and sex. Patients were randomly assigned (2:1) in blocks of 6, stratified by use of a stable dose of riluzole or no riluzole use, to receive oral arimoclomol citrate 1200 mg/day (400 mg three times per day) or placebo. The Randomisation sequence was computer generated centrally. Investigators, study personnel, and study participants were masked to treatment allocation. The primary outcome was the Combined Assessment of Function and Survival (CAFS) rank score over 76 weeks of treatment. The primary outcome and safety were analysed in the modified intention-to-treat population. This trial is registered with ClinicalTrials.gov, NCT03491462, and is completed.Findings: Between July 31, 2018, and July 17, 2019, 287 patients were screened, 245 of whom were enrolled in the trial and randomly assigned. The modified intention-to-treat population comprised 239 patients (160 in the arimoclomol group and 79 in the placebo group): 151 (63%) were male and 88 (37%) were female; mean age was 57·6 years (SD 10·9). CAFS score over 76 weeks did not differ between groups (mean 0·51 [SD 0·29] in the arimoclomol group vs 0·49 [0·28] in the placebo group; p=0·62). Cliff's delta comparing the two groups was 0·039 (95% CI –0·116 to 0·194). Proportions of participants who died were similar between the treatment groups: 29 (18%) of 160 patients in the arimoclomol group and 18 (23%) of 79 patients in the placebo group. Most deaths were due to disease progression. The most common adverse events were gastrointestinal. Adverse events were more often deemed treatment-related in the arimoclomol group (104 [65%]) than in the placebo group (41 [52%]) and more often led to treatment discontinuation in the arimoclomol group (26 [16%]) than in the placebo group (four [5%]).Interpretation: Arimoclomol did not improve efficacy outcomes compared with placebo. Although available biomarker data are insufficient to preclude future strategies that target the HSP response, safety data suggest that a higher dose of arimoclomol would not have been tolerated.Funding: Orphazyme.
|
|
| 5. |
- Pasin, Chloé, et al.
(författare)
-
Sex and gender in infection and immunity : addressing the bottlenecks from basic science to public health and clinical applications
- 2023
-
Ingår i: Royal Society Open Science. - 2054-5703. ; 10:7
-
Tidskriftsartikel (refereegranskat)abstract
- Although sex and gender are recognized as major determinants of health and immunity, their role is rarely considered in clinical practice and public health. We identified six bottlenecks preventing the inclusion of sex and gender considerations from basic science to clinical practice, precision medicine and public health policies. (i) A terminology-related bottleneck, linked to the definitions of sex and gender themselves, and the lack of consensus on how to evaluate gender. (ii) A data-related bottleneck, due to gaps in sex-disaggregated data, data on trans/non-binary people and gender identity. (iii) A translational bottleneck, limited by animal models and the underrepresentation of gender minorities in biomedical studies. (iv) A statistical bottleneck, with inappropriate statistical analyses and results interpretation. (v) An ethical bottleneck posed by the underrepresentation of pregnant people and gender minorities in clinical studies. (vi) A structural bottleneck, as systemic bias and discriminations affect not only academic research but also decision makers. We specify guidelines for researchers, scientific journals, funding agencies and academic institutions to address these bottlenecks. Following such guidelines will support the development of more efficient and equitable care strategies for all.
|
|
| 6. |
- Schindler, Louise S., et al.
(författare)
-
Associations between abdominal adipose tissue, reproductive span, and brain characteristics in post-menopausal women
- 2022
-
Ingår i: NeuroImage. - : ELSEVIER SCI LTD. - 2213-1582. ; 36
-
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.
|
|
| 7. |
- Subramaniapillai, Sivaniya, et al.
(författare)
-
Sex and gender in health research: Intersectionality matters
- 2024
-
Ingår i: Frontiers in Neuroendocrinology. - : ACADEMIC PRESS INC ELSEVIER SCIENCE. - 0091-3022 .- 1095-6808. ; 72
-
Forskningsöversikt (refereegranskat)abstract
- Research policies aiming to integrate sex and gender in scientific studies are receiving increased attention in academia. Incorporating these policies into health research is essential for improving targeted and equitable healthcare outcomes, by considering both disparities and similarities between individuals relating to sex and gender. Although these efforts are both urgent and critical, only an intersectional approach, which considers broad and multidimensional aspects of an individual's identity, can provide a complete understanding of the factors that impact health. In this commentary, we emphasize that in order to approach health equity, it is crucial to examine how sex and gender intersect with factors such as culture, ethnicity, minority status, and socioeconomic conditions to influence health outcomes. To facilitate evidence-based health interventions with tangible impact, we must consider disparities linked to both biological and environmental factors.
|
|
| 8. |
- van der Meer, Dennis, et al.
(författare)
-
The link between liver fat and cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
- 2022
-
Ingår i: Communications Biology. - : NATURE PORTFOLIO. - 2399-3642. ; 5:1
-
Tidskriftsartikel (refereegranskat)abstract
- A GWAS study of European individuals uncovers genetic associations between whole-body MRI derived measures and cardiometabolic diseases and highlights the key role of liver fat in cardiometabolic health. Obesity and associated morbidities, metabolic associated fatty liver disease (MAFLD) included, constitute some of the largest public health threats worldwide. Body composition and related risk factors are known to be heritable and identification of their genetic determinants may aid in the development of better prevention and treatment strategies. Recently, large-scale whole-body MRI data has become available, providing more specific measures of body composition than anthropometrics such as body mass index. Here, we aimed to elucidate the genetic architecture of body composition, by conducting genome-wide association studies (GWAS) of these MRI-derived measures. We ran both univariate and multivariate GWAS on fourteen MRI-derived measurements of adipose and muscle tissue distribution, derived from scans from 33,588 White European UK Biobank participants (mean age of 64.5 years, 51.4% female). Through multivariate analysis, we discovered 100 loci with distributed effects across the body composition measures and 241 significant genes primarily involved in immune system functioning. Liver fat stood out, with a highly discoverable and oligogenic architecture and the strongest genetic associations. Comparison with 21 common cardiometabolic traits revealed both shared and specific genetic influences, with higher mean heritability for the MRI measures (h(2 )= .25 vs. .13, p = 1.8x10(-7)). We found substantial genetic correlations between the body composition measures and a range of cardiometabolic diseases, with the strongest correlation between liver fat and type 2 diabetes (r(g )= .49, p = 2.7x10(-22)). These findings show that MRI-derived body composition measures complement conventional body anthropometrics and other biomarkers of cardiometabolic health, highlighting the central role of liver fat, and improving our knowledge of the genetic architecture of body composition and related diseases.
|
|
| 9. |
- van der Meer, Dennis, et al.
(författare)
-
The role of liver fat in cardiometabolic diseases is highlighted by genome-wide association study of MRI-derived measures of body composition
- 2022
-
Annan publikation (övrigt vetenskapligt/konstnärligt)abstract
- Background & AimsObesity and associated morbidities, metabolic associated liver disease (MAFLD) included, constitute some of the largest public health threats worldwide. Body composition and related risk factors are known to be heritable and identification of their genetic determinants may aid in the development of better prevention and treatment strategies. Recently, large-scale whole-body MRI data has become available, providing more specific measures of body composition than anthropometrics such as body mass index. Here, we aimed to elucidate the genetic architecture of body composition, by conducting the first genome-wide association study (GWAS) of these MRI-derived measures.MethodsWe ran both univariate and multivariate GWAS on fourteen MRI-derived measurements of adipose and muscle tissue distribution, derived from scans from 34,036 White European UK Biobank participants (mean age of 64.5 years, 51.5% female).ResultsThrough multivariate analysis, we discovered 108 loci with distributed effects across the body composition measures and 256 significant genes primarily involved in immune system functioning. Liver fat stood out, with a highly discoverable and oligogenic architecture and the strongest genetic associations. Comparison with 21 common cardiometabolic traits revealed both shared and specific genetic influences, with higher mean heritability for the MRI measures (h2=.25 vs. .16, p=1.4×10−6). We found substantial genetic correlations between the body composition measures and a range of cardiometabolic diseases, with the strongest correlation between liver fat and type 2 diabetes (rg=.48, p=1.6×10−22).ConclusionsThese findings show that MRI-derived body composition measures complement conventional body anthropometrics and other biomarkers of cardiometabolic health, highlighting the central role of liver fat, and improving our knowledge of the genetic architecture of body composition and related diseases.
|
|
