scholarly journals Accelerated brain ageing and disability in multiple sclerosis

2019 ◽  
Author(s):  
JH Cole ◽  
J Raffel ◽  
T Friede ◽  
A Eshaghi ◽  
W Brownlee ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Research University ◽  
Study Entry ◽  
Research Centre ◽  
Chronological Age ◽  
Age Difference ◽  
Intracranial Volume ◽  
Disability Progression ◽  
Brain Ageing ◽  
The Brain

SummaryBackgroundBrain atrophy occurs in both normal ageing and in multiple sclerosis (MS), but it occurs at a faster rate in MS, where it is the major driver of disability progression. Here, we employed a neuroimaging biomarker of structural brain ageing to explore how MS influences the brain ageing process.MethodsIn a longitudinal, multi-centre sample of 3,565 MRI scans in 1,204 MS/clinically isolated syndrome (CIS) patients and 150 healthy controls (HCs) (mean follow-up time: patients 3⋅41 years, HCs 1⋅97 years) we measured ‘brain-predicted age’ using T1-weighted MRI. Brain-predicted age difference (brain-PAD) was calculated as the difference between the brain-predicted age and chronological age. Positive brain-PAD indicates a brain appears older than its chronological age. We compared brain-PAD between MS/CIS patients and HCs, and between disease subtypes. In patients, the relationship between brain-PAD and Expanded Disability Status Scale (EDSS) at study entry and over time was explored.FindingsAdjusted for age, sex, intracranial volume, cohort and scanner effects MS/CIS patients had markedly older-appearing brains than HCs (mean brain-PAD 11⋅8 years [95% CI 9⋅1—14⋅5] versus −0⋅01 [−3⋅0—3⋅0], p<0⋅0001). All MS subtypes had greater brain-PAD scores than HCs, with the oldest-appearing brains in secondary-progressive MS (mean brain-PAD 18⋅0 years [15⋅4—20⋅5], p<0⋅05). At baseline, higher brain-PAD was associated with a higher EDSS, longer time since diagnosis and a younger age at diagnosis. Brain-PAD at study entry significantly predicted time-to-EDSS progression (hazard ratio 1⋅02 [1⋅01—1⋅03], p<0⋅0001): for every 5 years of additional brain-PAD, the risk of progression increased by 14⋅2%.InterpretationMS increases brain ageing across all MS subtypes. An older-appearing brain at baseline was associated with more rapid disability progression, suggesting ‘brain-age’ could be an individualised prognostic biomarker from a single, cross-sectional assessment.FundingUK MS Society; National Institute for Health Research University College London Hospitals Biomedical Research Centre.

Neuroimaging-based brain-age prediction of first-episode schizophrenia and the alteration of brain age after early medication

2021 ◽  
pp. 1-8
Author(s):  
Yi-Bin Xi ◽  
Xu-Sha Wu ◽  
Long-Biao Cui ◽  
Li-Jun Bai ◽  
Shuo-Qiu Gan ◽  
...  
Keyword(s):  
Diffusion Tensor ◽  
First Episode ◽  
Age Difference ◽  
Healthy Controls ◽  
Data Set ◽  
Brain Ageing ◽  
First Episode Schizophrenia ◽  
Brain Age ◽  
The Brain ◽  
Age Prediction

Background Neuroimaging- and machine-learning-based brain-age prediction of schizophrenia is well established. However, the diagnostic significance and the effect of early medication on first-episode schizophrenia remains unclear. Aims To explore whether predicted brain age can be used as a biomarker for schizophrenia diagnosis, and the relationship between clinical characteristics and brain-predicted age difference (PAD), and the effects of early medication on predicted brain age. Method The predicted model was built on 523 diffusion tensor imaging magnetic resonance imaging scans from healthy controls. First, the brain-PAD of 60 patients with first-episode schizophrenia, 60 healthy controls and 21 follow-up patients from the principal data-set and 40 pairs of individuals in the replication data-set were calculated. Next, the brain-PAD between groups were compared and the correlations between brain-PAD and clinical measurements were analysed. Results The patients showed a significant increase in brain-PAD compared with healthy controls. After early medication, the brain-PAD of patients decreased significantly compared with baseline (P < 0.001). The fractional anisotropy value of 31/33 white matter tract features, which related to the brain-PAD scores, had significantly statistical differences before and after measurements (P < 0.05, false discovery rate corrected). Correlation analysis showed that the age gap was negatively associated with the positive score on the Positive and Negative Syndrome Scale in the principal data-set (r = −0.326, P = 0.014). Conclusions The brain age of patients with first-episode schizophrenia may be older than their chronological age. Early medication holds promise for improving the patient's brain ageing. Neuroimaging-based brain-age prediction can provide novel insights into the understanding of schizophrenia.

scholarly journals Brain ageing in schizophrenia: evidence from 26 international cohorts via the ENIGMA Schizophrenia consortium

2022 ◽  
Author(s):  
Constantinos Constantinides ◽  
Laura KM Han ◽  
Clara Alloza ◽  
Linda Antonucci ◽  
Celso Arango ◽  
...  
Keyword(s):  
Clinical Characteristics ◽  
Large Scale ◽  
Age Of Onset ◽  
Collaborative Study ◽  
Brain Magnetic Resonance Imaging ◽  
Age Difference ◽  
Intracranial Volume ◽  
Age Related ◽  
Brain Ageing ◽  
Increased Risk

Schizophrenia (SZ) is associated with an increased risk of life-long cognitive impairments, age-related chronic disease, and premature mortality. We investigated evidence for advanced brain ageing in adult SZ patients, and whether this was associated with clinical characteristics in a prospective meta-analytic study conducted by the ENIGMA Schizophrenia Working Group. The study included data from 26 cohorts worldwide, with a total of 2803 SZ patients (mean age 34.2 years; range 18-72 years; 67% male) and 2598 healthy controls (mean age 33.8 years, range 18-73 years, 55% male). Brain-predicted age was individually estimated using a model trained on independent data based on 68 measures of cortical thickness and surface area, 7 subcortical volumes, lateral ventricular volumes and total intracranial volume, all derived from T1-weighted brain magnetic resonance imaging (MRI) scans. Deviations from a healthy brain ageing trajectory were assessed by the difference between brain-predicted age and chronological age (brain-predicted age difference [brain-PAD]). On average, SZ patients showed a higher brain-PAD of +3.64 years (95% CI: 3.01, 4.26; I2 = 55.28%) compared to controls, after adjusting for age and sex (Cohen's d = 0.50). Among SZ patients, brain-PAD was not associated with specific clinical characteristics (age of onset, duration of illness, symptom severity, or antipsychotic use and dose). This large-scale collaborative study suggests advanced structural brain ageing in SZ. Longitudinal studies of SZ and a range of mental and somatic health outcomes will help to further evaluate the clinical implications of increased brain-PAD and its ability to be influenced by interventions.

scholarly journals 1195Brain-predicted age difference is associated with cognitive processing and delayed recall in later life

2021 ◽  
Vol 50 (Supplement_1) ◽  
Author(s):  
Jo Wrigglesworth ◽  
Nurathifah Yaacob ◽  
Phillip Ward ◽  
Robyn Woods ◽  
John McNeil ◽  
...  
Keyword(s):  
Community Dwelling ◽  
Chronological Age ◽  
Accelerated Ageing ◽  
Age Difference ◽  
Psychomotor Speed ◽  
Delayed Recall ◽  
Memory Decline ◽  
Brain Ageing ◽  
Community Dwelling Older Adults ◽  
Brain Age

Abstract Background Brain age is a novel neuroimaging-based marker of ageing that uses machine learning to predict a person’s biological brain age. A higher brain age relative to chronological age (i.e., brain-predicted age difference [brain-PAD]) is considered a sign of accelerated ageing. We examined whether brain-PAD is associated with cognition and the change in cognitive function over time. Methods This study involved 531 cognitively healthy community-dwelling older adults (70+ years). Using a previously trained algorithm, brain age was estimated using T1-weighted structural magnetic resonance images acquired at baseline. Psychomotor speed, delayed recall, verbal fluency and global cognition were assessed at baseline, years 1 and 3. Results At baseline, a significant negative association was observed between brain-PAD and psychomotor speed (r=-0.14, p = 0.001), delayed recall (r=-0.09, p = 0.04), and the three-year change in delayed recall (r=-0.15, p = 0.02), which persisted after adjusting for covariates. Conclusions These findings indicate that accelerated brain ageing in cognitively unimpaired older people is associated with worse psychomotor speed, and delayed recall. This study also provides new evidence that accelerated brain ageing is a risk factor for progressive memory decline. Future research would benefit from further prospective analyses of associations between brain-PAD and cognitive function in community dwelling older adults. Key messages Brain age is a neuroimaging-based marker of biological ageing. A higher estimate of brain age relative to chronological age (i.e., accelerated ageing) is associated with worse psychomotor speed and memory, and memory decline.

scholarly journals Corrigendum

2017 ◽  
Vol 23 (13) ◽  
pp. NP30-NP30
Keyword(s):  
Multiple Sclerosis ◽  
Research University ◽  
Conflicts Of Interest ◽  
Associate Editor ◽  
Steering Committee ◽  
Progressive Multiple Sclerosis ◽  
Research Centre ◽  
Phase Ii Trials ◽  
Spinal Cord Atrophy ◽  
Conflicting Interests

Cawley N, Tur C, Prados F, et al. Spinal cord atrophy as a primary outcome measure in phase II trials of progressive multiple sclerosis. Mult Scler. Epub ahead of print 18 May 2017. DOI: 10.1177/1352458517709954. On page 9 of this article, the Declaration of Conflicting Interests and Funding statements were incorrect. The correct declarations are shown below. Declaration of Conflicting Interests The author(s) declared the following potential conflicts of interest with respect to the research, authorship and/or publication of this article: A.T. has received honoraria and support for travel from Eisai and EXCEMED. He has received support for travel from the International Progressive MS Alliance, as chair of their Scientific Steering Committee and the National MS Society (USA) as a member of their Research Programs Advisory Committee. He receives an honorarium from SAGE Publishing as Editor-in-Chief of Multiple Sclerosis. O.C. acts as a consultant for Novartis, Biogen, Roche, Teva, Genzyme and GE Healthcare. She receives an honorarium from AAN as Associate Editor of Neurology. Funding The author(s) declared receipt of the following financial support for the research, authorship and/or publication of this article: This study was funded by the UK MS Society and supported by the National Institute for Health Research University College London Hospital’s Biomedical Research Centre. The online version of this article has been updated to reflect the correct declarations. Subsequent versions of the article will also be corrected. The authors apologise for this error and any confusion it may have caused.

scholarly journals Brain Aging in Major Depressive Disorder: Results from the ENIGMA Major Depressive Disorder working group

2019 ◽  
Author(s):  
Laura K M Han ◽  
Richard Dinga ◽  
Tim Hahn ◽  
Christopher R K Ching ◽  
Lisa T Eyler ◽  
...  
Keyword(s):  
Major Depressive Disorder ◽  
Depressive Disorder ◽  
Working Group ◽  
Brain Aging ◽  
Chronological Age ◽  
Model Parameters ◽  
Age Difference ◽  
Intracranial Volume ◽  
Major Depressive ◽  
Increased Risk

AbstractBackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset.MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain predicted age difference (brain-PAD).FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohen’s d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004).InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates.FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.

scholarly journals Assessment of Disability Progression Independent of Relapse and Brain MRI Activity in Patients with Multiple Sclerosis in Poland

2021 ◽  
Vol 10 (4) ◽  
pp. 868
Author(s):  
Katarzyna Kapica-Topczewska ◽  
François Collin ◽  
Joanna Tarasiuk ◽  
Agata Czarnowska ◽  
Monika Chorąży ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Brain Activity ◽  
Brain Mri ◽  
Disability Progression ◽  
Program Monitoring ◽  
Therapeutic Program ◽  
Relapsing Remitting ◽  
Second Year ◽  
Multiple Sclerosis Patients ◽  
Relapsing Remitting Multiple Sclerosis

The aim of the study was to verify the association of clinical relapses and brain activity with disability progression in relapsing/remitting multiple sclerosis patients receiving disease-modifying treatments in Poland. Disability progression was defined as relapse-associated worsening (RAW), progression independent of relapse activity (PIRA), and progression independent of relapses and brain MRI Activity (PIRMA). Data from the Therapeutic Program Monitoring System were analyzed. Three panels of patients were identified: R0, no relapse during treatment, and R1 and R2 with the occurrence of relapse during the first and the second year of treatment, respectively. In the R0 panel, we detected 4.6% PIRA patients at 24 months (p < 0.001, 5.0% at 36 months, 5.6% at 48 months, 6.1% at 60 months). When restricting this panel to patients without brain MRI activity, we detected 3.0% PIRMA patients at 12 months, 4.5% at 24 months, and varying from 5.3% to 6.2% between 36 and 60 months of treatment, respectively. In the R1 panel, RAW was detected in 15.6% patients at 12 months and, in the absence of further relapses, 9.7% at 24 months and 6.8% at 36 months of treatment. The R2 group was associated with RAW significantly more frequently at 24 months compared to the R1 at 12 months (20.7%; p < 0.05), but without a statistical difference later on. In our work, we confirmed that disability progression was independent of relapses and brain MRI activity.

scholarly journals Determinants of therapeutic lag in multiple sclerosis

2021 ◽  
pp. 135245852098130
Author(s):  
Izanne Roos ◽  
Emmanuelle Leray ◽  
Federico Frascoli ◽  
Romain Casey ◽  
J William L Brown ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Expanded Disability Status Scale ◽  
Disability Progression ◽  
Delayed Onset ◽  
Disease Characteristics ◽  
Disability Status ◽  
Male Sex ◽  
Pre Treatment ◽  
Patient Subgroups

Background: A delayed onset of treatment effect, termed therapeutic lag, may influence the assessment of treatment response in some patient subgroups. Objectives: The objective of this study is to explore the associations of patient and disease characteristics with therapeutic lag on relapses and disability accumulation. Methods: Data from MSBase, a multinational multiple sclerosis (MS) registry, and OFSEP, the French MS registry, were used. Patients diagnosed with MS, minimum 1 year of exposure to MS treatment and 3 years of pre-treatment follow-up, were included in the analysis. Studied outcomes were incidence of relapses and disability accumulation. Therapeutic lag was calculated using an objective, validated method in subgroups stratified by patient and disease characteristics. Therapeutic lag under specific circumstances was then estimated in subgroups defined by combinations of clinical and demographic determinants. Results: High baseline disability scores, annualised relapse rate (ARR) ⩾ 1 and male sex were associated with longer therapeutic lag on disability progression in sufficiently populated groups: females with expanded disability status scale (EDSS) < 6 and ARR < 1 had mean lag of 26.6 weeks (95% CI = 18.2–34.9), males with EDSS < 6 and ARR < 1 31.0 weeks (95% CI = 25.3–36.8), females with EDSS < 6 and ARR ⩾ 1 44.8 weeks (95% CI = 24.5–65.1), and females with EDSS ⩾ 6 and ARR < 1 54.3 weeks (95% CI = 47.2–61.5). Conclusions: Pre-treatment EDSS and ARR are the most important determinants of therapeutic lag.

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