Rate Of Brain Atrophy Research Articles

Sex influences the effects of APOE genotype and Alzheimer’s diagnosis on neuropathology and memory

Alzheimer’s disease (AD) is characterized by severe cognitive decline and pathological changes in the brain (brain atrophy, hyperphosphorylation of tau, and deposition of amyloid-beta protein). Females have greater neuropathology (AD biomarkers and brain atrophy rates) and cognitive decline than males, however these effects can depend on diagnosis (amnestic mild cognitive impairment (aMCI) or AD) and APOE genotype (presence of ε4 alleles). Using the ADNI database (N = 630 females, N = 830 males), we analyzed the effect of sex, APOE genotype (non-carriers or carriers of APOEε4 alleles), and diagnosis (cognitively normal (CN), early aMCI (EMCI), late aMCI (LMCI), probable AD) on cognition (memory and executive function), hippocampal volume, and AD biomarkers (CSF levels of amyloid beta, tau, and ptau). Regardless of APOE genotype, memory scores were higher in CN, EMCI, and LMCI females compared to males but this sex difference was absent in probable AD, which may suggest a delay in the onset of cognitive decline or diagnosis and/or a faster trajectory of cognitive decline in females. We found that, regardless of diagnosis, CSF tau-pathology was disproportionately elevated in female carriers of APOEε4 alleles compared to males. In contrast, male carriers of APOEε4 alleles had reduced levels of CSF amyloid beta compared to females, irrespective of diagnosis. We also detected sex differences in hippocampal volume but the direction was dependent on the method of correction. Altogether results suggest that across diagnosis females show greater memory decline compared to males and APOE genotype affects AD neuropathology differently in males and females which may influence sex differences in incidence and progression of aMCI and AD.

The Oral-Gut-Brain AXIS: The Influence of Microbes in Alzheimer's Disease.

Alzheimer’s disease (AD) is one of the most frequently diagnosed neurodegenerative disorders worldwide and poses a major challenge for both affected individuals and their caregivers. AD is a progressive neurological disorder associated with high rates of brain atrophy. Despite its durable influence on human health, understanding AD has been complicated by its enigmatic and multifactorial nature. Neurofibrillary tangles and the deposition of amyloid-beta (Aβ) protein are typical pathological features and fundamental causes of cognitive impairment in AD patients. Dysbiosis of oral and gut microbiota has been reported to induce and accelerate the formation of Aβ plaques and neurofibrillary tangles. For instance, some oral microbes can spread to the brain through cranial nerves or cellular infections, which has been suggested to increase the risk of developing AD. Importantly, the interaction between intestinal microbiota and brain cells has been recognized as influencing the development of AD as well as other neurodegenerative diseases. In particular, the metabolites produced by certain intestinal microorganisms can affect the activity of microglia and further mediate neuroinflammation, which is a leading cause of neuronal necrosis and AD pathogenesis. Which pathogens and associated pathways are involved in the development and progression of AD remains to be elucidated; however, it is well-known that gut microbiota and their metabolites can affect the brain by both direct and indirect means. Understanding the specific mechanisms involved in the interaction between these pathogens and the nervous system is vital for the early intervention in AD. In this review, we aim to comprehensively discuss the possible mechanistic pathways underlying the oral-brain, the gut-brain and the oral-gut-brain associations.

Linear brain atrophy measures in multiple sclerosis and clinically isolated syndromes: a 30-year follow-up

ObjectiveTo determine 30-year brain atrophy rates following clinically isolated syndromes and the relationship of atrophy in the first 5 years and clinical outcomes 25 years later.MethodsA cohort of 132 people...

Predicting brain atrophy from tau pathology: a summary of clinical findings and their translation into personalized models

For more than 25 years, the amyloid hypothesis–the paradigm that amyloid is the primary cause of Alzheimer’s disease–has dominated the Alzheimer’s community. Now, increasing evidence suggests that tissue atrophy and cognitive decline in Alzheimer’s disease are more closely linked to the amount and location of misfolded tau protein than to amyloid plaques. However, the precise correlation between tau pathology and tissue atrophy remains unknown. Here we integrate multiphysics modeling and Bayesian inference to create personalized tau-atrophy models using longitudinal clinical images from the Alzheimer’s Disease Neuroimaging Initiative. For each subject, we infer three personalized parameters, the tau misfolding rate, the tau transport coefficient, and the tau-induced atrophy rate from four consecutive annual tau positron emission tomography scans and structural magnetic resonance images. Strikingly, the tau-induced atrophy coefficient of 0.13/year (95% CI: 0.097-0.189) was fairly consistent across all subjects suggesting a strong correlation between tau pathology and tissue atrophy. Our personalized whole brain atrophy rates of 0.68-1.68%/year (95% CI: 0.5-2.0) are elevated compared to healthy subjects and agree well with the atrophy rates of 1-3%/year reported for Alzheimer’s patients in the literature. Once comprehensively calibrated with a larger set of longitudinal images, our model has the potential to serve as a diagnostic and predictive tool to estimate future atrophy progression from clinical tau images on a personalized basis. Statement of SignificanceDeveloping predictive, patient-specific models of Alzheimer’s disease pathology and progression is of paramount importance for effective patient care and potential treatment. Tissue atrophy, the reduction of brain volume, is an important biomarker for Alzheimer’s disease. Similarly, the pathology associated with tau proteins is thought to play a central role in Alzheimer’s disease progression, local atrophy, and a patient’s cognitive decline. The main question is: how do combine the mechanisms of tau propagation and atrophy in a single model that can make the best use of existing data? Here, we first review the dynamics of atrophy in for Alzheimer’s disease and describe a mathematical model that couples tau propagation and atrophy. We then investigate how to fit the model parameters using the longitudinal structural neuroimaging data of four subjects, from the ADNI database, and a Bayesian Markov Chain Monte Carlo inference method. Our approach shows that network neurodegeneration models may hold promise for the predictive, patient-specific modeling of AD using AV-1451 tau PET and T1 structural MRI data.

White matter hyperintensity increases are a feature of familial AD and are associated with increased brain atrophy

AbstractBackgroundRelatively little is known about how white matter hyperintensity (WMH) changes relate to well‐characterised markers of disease progression such as brain atrophy rates in autosomal dominant familial AD (ADAD). Such analyses may improve models of disease progression and indicate whether WMH accrual and brain atrophy are associated features over the disease course.MethodsWe investigated WMH accrual in the Dominantly Inherited Alzheimer Network (DIAN) cohort. Participants included 72 controls, 95 PSEN1, 7 PSEN2 and 27 APP mutation carriers, with longitudinal multi‐modal imaging. WMH were segmented using a semi‐automated protocol. Brain atrophy rate was calculated using the boundary shift integral (BSI). Three statistical models were used: Model 1 used mixed‐effect linear regression to assess WMH accrual by mutation presence or type, adjusting for evidence of cognitive impairment (symptomatic status as defined using CDR). Model 2 assessed the effect of estimated years to onset (EYO) on WMH accrual. Model 3 estimated correlations between residual rates of change after allowing mean rates of change in WMH and brain volume to depend on proximity to expected onset. All models (1‐3) were allowed to depend upon total intracranial volume.ResultsThe table shows summary statistics and rates of change including annualised rates of WMH accrual and brain atrophy. Results from Model 1 showed differences in WMH accrual between mutation groups after adjustment for symptom status (p<0.001), with APP having higher rates of accrual than all other groups. Model 2 demonstrated WMH increases were associated with EYO in PSEN1 and APP groups (p≤0.001, both tests), with an accelerating rate of accrual observed approaching and passing estimated onset in the PSEN1 and PSEN2 groups (p≤0.005, both tests). Model 3 demonstrated associations between residual rates of change in WMH and brain volume in the PSEN1 (r 0.76, p<0.001) and APP (r 0.55, p=0.03) groups (the figure shows crude rates).ConclusionMutation type has an impact on WMH accrual, with APP mutation carriers in this cohort gaining more WMH over time. WMH changes are an important biomarker in ADAD with burden increasing with EYO. WMH and brain atrophy changes track together across the AD disease course.

Vascular risk factors and amyloid pathology: Additive or interactive associations?

AbstractBackgroundThe two commonest contributors to late‐life cognitive impairment are Alzheimer’s (AD) and cerebrovascular disease; these two conditions almost invariably overlap. Understanding the determinants of the pathologies that underpin these conditions and how they interact to influence late‐life brain health is vital for rational risk prevention and for clinical trials.MethodData from the Insight 46 cohort will be presented, comprising individuals from the MRC 1946 British Birth Cohort all born in mainland Britain in one week in 1946. These individuals have been followed prospectively including serial measures of cognition from age 8, cardiovascular risk since the mid‐30s, and a range of cardiac and vascular outcomes in their 60s. At age 69‐71 they had detailed cognitive testing, 3T‐MRI including determination of white matter hyperintensity volume (WMHV) and 18F‐Florbetapir (β‐amyloid) PET. All individuals are being seen for a second visit, two‐years after the first.ResultsA total of 502 participants were assessed cross‐sectionally; data from up to 465 participants (51.0% male, mean age=70.7±0.7, 18.2% β‐amyloid positive) are available. Results of cross‐sectional analyses investigating the relationships between life course cardiovascular risk factors genetics, β‐amyloid and WMHV will be presented, alongside analyses of the associations of these pathologies with cross‐sectional cognitive function and MRI metrics. Investigations exploring mechanistic relationships e.g. between cardiac and vascular outcomes including pulse wave velocity and echocardiography, β‐amyloid and WMHV and cognition will be presented. Interim results of analyses exploring relationships between baseline β‐amyloid and WMHV and rates of cognitive decline and brain atrophy will be described in n=250 (47.6% female, age=72.5±0.33, 18.1% β‐amyloid positive) of the cohort. These results will be compared and contrasted with those from other cohort studies including the Atherosclerosis Risk in Communities (ARIC) study, and Mayo Clinic Study of Ageing.ConclusionCombining life course data, contemporaneous measurement of PET‐amyloid status, WMHV and cognition, vascular metrics and longitudinal measures of brain atrophy and cognitive change provides a powerful opportunity to explore how and when vascular and β‐amyloid pathology influence brain health in later‐life. Emerging evidence from several studies suggest that vascular risk influences the development of cognitive impairment and dementia principally via non‐amyloidogenic pathways.

Cognitive and imaging impacts of left ventricular hypertrophy in people with type 2 diabetes

AbstractBackgroundOlder adults with type 2 diabetes mellitus (T2DM) are at an increased risk of cognitive decline and dementia. Left ventricular hypertrophy (LVH) is prevalent in T2DM and is independently associated with cognitive decline. We conducted a study to establish whether T2DM patients with LVH have increased rates of brain atrophy and cognitive impairment.MethodsThirty‐seven cognitively healthy adults (50 years and older) with T2DM were divided into those with (n=13) and without (n=24) LVH. All participants completed neuropsychological assessments, health‐and‐lifestyle questionnaires, 24‐hour ambulatory blood pressure monitoring, an echocardiogram and a 3T‐MRI scan. FreeSurfer (version 6.0) was used to estimate total brain volume (TBV), mean cortical thickness and subcortical volumes, including the thalami and caudate nuclei. TBV was expressed as a percentage of intracranial volume. Averages between left and right volumes were calculated for subcortical structures. Left ventricular mass was indexed to height2.7 using the American Society of Echocardiography criteria. LVH was defined as >49g/m2.7 for males and >45g/m2.7 for females. Three cognitive domains (visuospatial skills, verbal memory and executive functions) were derived through factor analysis. These variables were used to compare cognitive performance between individuals with and without LVH.ResultsThere was a higher percentage of women (x2=11.01, df=1, p<0.01) in the LVH group. No differences in cortical thickness and TBV were found between groups. The LVH group showed significantly lower volume in the cerebellar cortex (F(1, 32)=5.25 p=0.029) and in the amygdala (F(1, 32)=6.24 p=0.018) after correcting for sex, age, blood pressure and BMI when compared to the no LVH group. Significant differences were found in the visuospatial skills factor (F(1, 43)=4.09; p = 0.049), with the LVH group performing worse than the no LVH group.ConclusionsThe presence of LVH in individuals with T2DM was associated with atrophy in the cerebellar cortex and in the amygdala, as well as with poorer visuospatial function.

Imaging genomics in the ENIGMA Consortium

AbstractBackgroundWe offer an update on recent work by the ENIGMA Consortium, CHARGE Consortium, and UK Biobank ‐ and a worldwide alliance of over 1,400 scientists ‐ to understand how human genetic and epigenetic variation affect biomarkers of brain aging and Alzheimer's disease (AD).MethodFor 10 years, ENIGMA, CHARGE, and (more recently) the UK Biobank have screened the genomes and neuroimaging data from over 50,000 persons worldwide, as well as epigenome‐wide methylation data, to ask: (1) which common and rare genetic variants affect the brain throughout life? (2) which variants affect brain aging and biomarkers of AD ‐ such as hippocampal volume, longitudinal brain atrophy rates over time, and white matter hyperintensities? (3) how do AD risk variants, in APOE and elsewhere, affect brain biomarkers from youth to old age? For 10 years, we harmonized analyses of worldwide anaotmical MRI, diffusion MRI, rsFMRI, and EEG markers across over 200 cohorts, to examine how genome‐wide genomic variation and epigenetic variants affect structural and functional biomarkers of aging and AD.ResultGWAS in over 51,662 persons revealed over 200 common genetic variants affecting cortical architecture; of 255 nominally significant loci (P ≤ 5 × 10−8); 199 survived multiple testing correction (P ≤ 8.3 × 10−10; 187 surface area; 12 thickness). Variation in cortical and hippocampal structure is genetically correlated with cognitive function, AD, Parkinson’s disease, insomnia, major depression and ADHD. ENIGMA's Plasticity Working Group analyzed longitudinal MRI data of 10,163 persons aged 4 to 99 years, and discovered 5 genome‐wide significant loci and 15 genes influencing brain change rates at different times throughout life, and an age‐dependent effect of the APOE haplotype on brain structure. These age‐dependent influences of common genetic variants implicate immunological and metabolic processes. Epigenome‐wide screens revealed additional loci where methylation levels robustly associate with hippocampal volume in cohorts worldwide.ConclusionCommon genetic variants affect rates of brain change, hippocampal and regional cortical measures, throughout life; coordinated analyses of harmonized data are revealing the timing of genetic and epigenetic drivers of brain aging, and the first catalogs of common variants that associate with longitudinal markers of brain aging.

Expansion of chronic lesions is linked to disease progression in relapsing–remitting multiple sclerosis patients

Background: Slow-burning inflammation is putatively associated with lesion expansion and leads to progressive loss of axons and disability worsening. Objective: To investigate the incidence and extent of chronic white matter lesion expansion in relapsing–remitting multiple sclerosis (RRMS) patients and to evaluate its relationship with biomarkers of disease progression. Methods: Pre- and post-gadolinium T1, fluid-attenuated inversion recovery (FLAIR) and diffusion tensor images were acquired from 33 patients. Lesional activity were analysed between baseline and 48 months using custom-designed software. Results: A total of 569 lesions were identified as chronic at baseline, of which 261 were expanding, 236 were stable and 72 were shrinking. In addition, 139 new lesions (both confluent and free-standing) were observed. Chronic lesion expansion was associated with patient’s age and accounted for the bulk (67.3%) of total brain lesion volume increase, while only 32.7% was attributable to new lesion formation. Change in chronic lesion volume correlated with the rate of brain atrophy (r = −0.57, p = 0.001), change of Expanded Disability Status Scale (EDSS; r = 0.38, p = 0.03) and an increase of isotropic diffusivity inside the lesions (r = 0.75, p < 0.001). Conclusion: Expansion of chronic lesions in RRMS patients is the primary determinant of increased T2 total lesion load. It significantly contributes to disease progression and partially driving axonal loss inside the lesions and brain damage outside of lesional tissue.

Protein contributions to brain atrophy acceleration in Alzheimer's disease and primary age-related tauopathy.

Alzheimer's disease is characterized by the presence of amyloid-β and tau deposition in the brain, hippocampal atrophy and increased rates of hippocampal atrophy over time. Another protein, TAR DNA binding protein 43 (TDP-43) has been identified in up to 75% of cases of Alzheimer's disease. TDP-43, tau and amyloid-β have all been linked to hippocampal atrophy. TDP-43 and tau have also been linked to hippocampal atrophy in cases of primary age-related tauopathy, a pathological entity with features that strongly overlap with those of Alzheimer's disease. At present, it is unclear whether and how TDP-43 and tau are associated with early or late hippocampal atrophy in Alzheimer's disease and primary age-related tauopathy, whether either protein is also associated with faster rates of atrophy of other brain regions and whether there is evidence for protein-associated acceleration/deceleration of atrophy rates. We therefore aimed to model how these proteins, particularly TDP-43, influence non-linear trajectories of hippocampal and neocortical atrophy in Alzheimer's disease and primary age-related tauopathy. In this longitudinal retrospective study, 557 autopsied cases with Alzheimer's disease neuropathological changes with 1638 ante-mortem volumetric head MRI scans spanning 1.0-16.8 years of disease duration prior to death were analysed. TDP-43 and Braak neurofibrillary tangle pathological staging schemes were constructed, and hippocampal and neocortical (inferior temporal and middle frontal) brain volumes determined using longitudinal FreeSurfer. Bayesian bivariate-outcome hierarchical models were utilized to estimate associations between proteins and volume, early rate of atrophy and acceleration in atrophy rates across brain regions. High TDP-43 stage was associated with smaller cross-sectional brain volumes, faster rates of brain atrophy and acceleration of atrophy rates, more than a decade prior to death, with deceleration occurring closer to death. Stronger associations were observed with hippocampus compared to temporal and frontal neocortex. Conversely, low TDP-43 stage was associated with slower early rates but later acceleration. This later acceleration was associated with high Braak neurofibrillary tangle stage. Somewhat similar, but less striking, findings were observed between TDP-43 and neocortical rates. Braak stage appeared to have stronger associations with neocortex compared to TDP-43. The association between TDP-43 and brain atrophy occurred slightly later in time (∼3 years) in cases of primary age-related tauopathy compared to Alzheimer's disease. The results suggest that TDP-43 and tau have different contributions to acceleration and deceleration of brain atrophy rates over time in both Alzheimer's disease and primary age-related tauopathy.

Rates of Brain Atrophy Across Disease Stages in Familial Frontotemporal Dementia Associated With MAPT, GRN, and C9orf72 Pathogenic Variants

Several clinical trials are planned for familial forms of frontotemporal lobar degeneration (f-FTLD). Precise modeling of brain atrophy in f-FTLD could improve the power to detect a treatment effect. To characterize regions and rates of atrophy in the 3 primary f-FTLD genetic groups (MAPT, GRN, and C9orf72) across all disease stages from asymptomatic to dementia. This investigation was a case-control study of participants enrolled in the Advancing Research and Treatment for Frontotemporal Lobar Degeneration or Longitudinal Evaluation of Familial Frontotemporal Dementia studies. The study took place at 18 North American academic medical centers between January 2009 and September 2018. Participants with f-FTLD (n = 100) with a known pathogenic variant (MAPT [n = 28], GRN [n = 33], or C9orf72 [n = 39]) were grouped according to disease stage (ie, Clinical Dementia Rating [CDR] plus National Alzheimer's Coordinating Center [NACC] FTLD module). Included were participants with at least 2 structural magnetic resonance images at presymptomatic (CDR + NACC FTLD = 0 [n = 57]), mild or questionable (CDR + NACC FTLD = 0.5 [n = 15]), or symptomatic (CDR + NACC FTLD = ≥1 [n = 28]) disease stages. The control group included family members of known pathogenic variant carriers who did not carry the pathogenic variant (n = 60). This study fitted bayesian linear mixed-effects models in each voxel of the brain to quantify the rate of atrophy in each of the 3 genes, at each of the 3 disease stages, compared with controls. The study also analyzed rates of clinical decline in each of these groups, as measured by the CDR + NACC FTLD box score. The sample included 100 participants with f-FTLD with a known pathogenic variant (mean [SD] age, 50.48 [13.78] years; 53 [53%] female) and 60 family members of known pathogenic variant carriers who did not carry the pathogenic variant (mean [SD] age, 47.51 [12.43] years; 36 [60%] female). MAPT and GRN pathogenic variants were associated with increased rates of volume loss compared with controls at all stages of disease. In MAPT pathogenic variant carriers, statistically significant regions of accelerated volume loss compared with controls were identified in temporal regions bilaterally in the presymptomatic stage, with global spread in the symptomatic stage. For example, mean [SD] rates of atrophy in the left temporal were -231 [47] mm3 per year during the presymptomatic stage, -381 [208] mm3 per year during the mild stage, and -1485 [1025] mm3 per year during the symptomatic stage (P < .05). GRN pathogenic variant carriers generally had minimal increases in atrophy rates between the presymptomatic and mild stages, with rapid increases in atrophy rates in the symptomatic stages. For example, in the right frontal lobes, annualized volume loss was -267 [81] mm3 per year in the presymptomatic stage and -182 [90] mm3 per year in the mild stage, but -1169 [555] mm3 per year in the symptomatic stage. Compared with the other groups, C9orf72 expansion carriers showed minimal increases in rate of volume loss with disease progression. For example, the mean (SD) annualized rates of atrophy in the right frontal lobe in C9orf72 expansion carriers was -272 (118) mm3 per year in presymptomatic stages, -310 (189) mm3 per year in mildly symptomatic stages, and -251 (145) mm3 per year in symptomatic stages. These findings are relevant to clinical trial planning and suggest that the mechanism by which C9orf72 pathogenic variants lead to symptoms may be fundamentally different from the mechanisms associated with other pathogenic variants.

Diffuse axonal injury predicts neurodegeneration after moderate-severe traumatic brain injury.

Traumatic brain injury is associated with elevated rates of neurodegenerative diseases such as Alzheimer's disease and chronic traumatic encephalopathy. In experimental models, diffuse axonal injury triggers post-traumatic neurodegeneration, with axonal damage leading to Wallerian degeneration and toxic proteinopathies of amyloid and hyperphosphorylated tau. However, in humans the link between diffuse axonal injury and subsequent neurodegeneration has yet to be established. Here we test the hypothesis that the severity and location of diffuse axonal injury predicts the degree of progressive post-traumatic neurodegeneration. We investigated longitudinal changes in 55 patients in the chronic phase after moderate-severe traumatic brain injury and 19 healthy control subjects. Fractional anisotropy was calculated from diffusion tensor imaging as a measure of diffuse axonal injury. Jacobian determinant atrophy rates were calculated from serial volumetric T1 scans as a measure of measure post-traumatic neurodegeneration. We explored a range of potential predictors of longitudinal post-traumatic neurodegeneration and compared the variance in brain atrophy that they explained. Patients showed widespread evidence of diffuse axonal injury, with reductions of fractional anisotropy at baseline and follow-up in large parts of the white matter. No significant changes in fractional anisotropy over time were observed. In contrast, abnormally high rates of brain atrophy were seen in both the grey and white matter. The location and extent of diffuse axonal injury predicted the degree of brain atrophy: fractional anisotropy predicted progressive atrophy in both whole-brain and voxelwise analyses. The strongest relationships were seen in central white matter tracts, including the body of the corpus callosum, which are most commonly affected by diffuse axonal injury. Diffuse axonal injury predicted substantially more variability in white matter atrophy than other putative clinical or imaging measures, including baseline brain volume, age, clinical measures of injury severity and microbleeds (>50% for fractional anisotropy versus <5% for other measures). Grey matter atrophy was not predicted by diffuse axonal injury at baseline. In summary, diffusion MRI measures of diffuse axonal injury are a strong predictor of post-traumatic neurodegeneration. This supports a causal link between axonal injury and the progressive neurodegeneration that is commonly seen after moderate/severe traumatic brain injury but has been of uncertain aetiology. The assessment of diffuse axonal injury with diffusion MRI is likely to improve prognostic accuracy and help identify those at greatest neurodegenerative risk for inclusion in clinical treatment trials.

Advanced MRI features in relapsing multiple sclerosis patients with and without CSF oligoclonal IgG bands

Oligoclonal IgG bands (OCB) in cerebrospinal fluid (CSF) are important in diagnosis of multiple sclerosis (MS). We evaluated the MRI features of clinically definite MS subjects with and without CSF-OCB. Relapsing MS subjects were recruited from a prospective registry in a university center. CSF-OCB were detected using isoelectric focusing and lgG-specific immunofixation. MRI metrics including brain volumes, lesion volumes and microstructural measures, were analyzed by FMRIB Software Library (FSL) and Statistical Parametric Mapping (SPM). Seventy-five subjects with relapsing MS were analyzed. Forty-four (59%) subjects had an interval MRI at around 1 year. CSF-OCB were detected in 46 (61%) subjects. The OCB-positive group had a higher proportion of cerebellar lesions than the OCB-negative group (23.9% vs. 3.4%, p = 0.057). Except for amygdala volumes which were lower in the OCB-positive group (p = 0.034), other regional brain volumes including the subcortical deep gray matter and corpus callosum were similar. The two groups also showed comparable brain atrophy rate. For DTI, the OCB-positive group showed significantly higher mean diffusivity (MD) value in perilesional normal-appearing white matter (p = 0.043). Relapsing MS patients with and without CSF-OCB shared similar MRI features regarding volumetric analyses and DTI microstructural integrity.

Dynamic Regional Brain Atrophy Rates in the First Year After Ischemic Stroke.

Brain atrophy can be regarded as an end-organ effect of cumulative cardiovascular risk factors. Accelerated brain atrophy is described following ischemic stroke, but it is not known whether atrophy rates vary over the poststroke period. Examining rates of brain atrophy allows the identification of potential therapeutic windows for interventions to prevent poststroke brain atrophy. We charted total and regional brain volume and cortical thickness trajectories, comparing atrophy rates over 2 time periods in the first year after ischemic stroke: within 3 months (early period) and between 3 and 12 months (later period). Patients with first-ever or recurrent ischemic stroke were recruited from 3 Melbourne hospitals at 1 of 2 poststroke time points: within 6 weeks (baseline) or 3 months. Whole-brain 3T magnetic resonance imaging was performed at 3 time points: baseline, 3 months, and 12 months. Eighty-six stroke participants completed testing at baseline; 125 at 3 months (76 baseline follow-up plus 49 delayed recruitment); and 113 participants at 12 months. Their data were compared with 40 healthy control participants with identical testing. We examined 5 brain measures: hippocampal volume, thalamic volume, total brain and hemispheric brain volume, and cortical thickness. We tested whether brain atrophy rates differed between time points and groups. A linear mixed-effect model was used to compare brain structural changes, including age, sex, years of education, a composite cerebrovascular risk factor score, and total intracranial volume as covariates. Atrophy rates were greater in stroke than control participants. Ipsilesional hemispheric, hippocampal, and thalamic atrophy rates were 2 to 4 times greater in the early versus later period. Regional atrophy rates vary over the first year after stroke. Rapid brain volume loss in the first 3 months after stroke may represent a potential window for intervention. Registration: URL: https://www.clinicaltrials.gov. Unique identifier: NCT02205424.

Time course and diagnostic utility of NfL, tau, GFAP, and UCH-L1 in subacute and chronic TBI.

To determine whether neurofilament light (NfL), glial fibrillary acidic protein (GFAP), tau, and ubiquitin C-terminal hydrolase-L1 (UCH-L1) measured in serum relate to traumatic brain injury (TBI) diagnosis, injury severity, brain volume, and diffusion tensor imaging (DTI) measures of traumatic axonal injury (TAI) in patients with TBI. Patients with TBI (n = 162) and controls (n = 68) were prospectively enrolled between 2011 and 2019. Patients with TBI also underwent serum, functional outcome, and imaging assessments at 30 (n = 30), 90 (n = 48), and 180 (n = 59) days, and 1 (n = 84), 2 (n = 57), 3 (n = 46), 4 (n = 38), and 5 (n = 29) years after injury. At enrollment, patients with TBI had increased serum NfL compared to controls (p < 0.0001). Serum NfL decreased over the course of 5 years but remained significantly elevated compared to controls. Serum NfL at 30 days distinguished patients with mild, moderate, and severe TBI from controls with an area under the receiver-operating characteristic curve (AUROC) of 0.84, 0.92, and 0.92, respectively. At enrollment, serum GFAP was elevated in patients with TBI compared to controls (p < 0.001). GFAP showed a biphasic release in serum, with levels decreasing during the first 6 months of injury but increasing over the subsequent study visits. The highest AUROC for GFAP was measured at 30 days, distinguishing patients with moderate and severe TBI from controls (both 0.89). Serum tau and UCH-L1 showed weak associations with TBI severity and neuroimaging measures. Longitudinally, serum NfL was the only biomarker that was associated with the likely rate of MRI brain atrophy and DTI measures of progression of TAI. Serum NfL shows greater diagnostic and prognostic utility than GFAP, tau, and UCH-L1 for subacute and chronic TBI. This study provides Class III evidence that serum NfL distinguishes patients with mild TBI from healthy controls.

Comparison of brain atrophy in patients with multiple sclerosis treated with first- versus second-generation disease modifying therapy without clinical relapse.

The silent progression of patients with multiple sclerosis (MS) has been reported. The aim of this study was to investigate the association between brain atrophy rates and disease-modifying drugs (DMDs) in patients with MS during their relapse-free period. Patients with relapsing-remitting MS were classified into two groups on the basis of clinical records, i.e. a first-generation DMD group treated with interferon-beta-1a, interferon-beta-1b or glatiramer acetate and a second-generation DMD group treated with dimethyl fumarate, fingolimod or natalizumab. Brain volume was calculated with SPM12. A total of 45 patients with relapsing-remitting MS were enrolled in the first-generation (n=22) or second-generation (n=23) DMD group. The annualized relapse rate was lower in the first-generation than in the second-generation DMD group (median 0.26 vs. 0.59; P<0.001). The annualized atrophy rate of the normalized brain volume was not different between the first- and second-generation DMD groups after analysis of covariance (median 0.13% vs. 0.59%; P=0.17). The median annualized atrophy rate of normalized brain volume in the first-generation DMD group was similar to the previously reported annual brain atrophy rate of healthy controls, which may suggest that treatment with a first-generation DMD need not be changed when patients with MS are clinically inactive.

Midlife alcohol consumption and longitudinal brain atrophy: the PREVENT-Dementia study

Background and aimsConsensus is lacking on whether light to moderate consumption of alcohol compared to abstinence is neuroprotective. In this study, we investigated the relationship between self-reported alcohol use and brain volume change over 2 years in middle-aged subjects.MethodsA sample of 162 subjects (aged 40–59 at baseline) from the PREVENT-Dementia programme underwent MRI scans on two separate occasions (mean interval 734 days; SD 42 days). We measured longitudinal rates of brain atrophy using the FSL Siena toolbox, and change in hippocampal volume from segmentation in SPM.ResultsControlling for age and sex, there were no significant associations of either total brain, ventricular, or hippocampal volume change with alcohol consumption. Adjusting for lifestyle, demographic and vascular risk factors did not alter this.ConclusionsWe did not find any evidence of influence of alcohol consumption on changes in brain volume over a 2-year period in 40–60-year-olds.

Serum neurofilament light chain in FTLD: association with C9orf72, clinical phenotype, and prognosis.

ObjectiveThe aim of the present study was to compare the levels of serum neurofilament light chain (sNfL) in frontotemporal lobar degeneration (FTLD) patients of different clinical subtypes (bvFTD, PPA, and FTLD‐MND) and with or without the C9orf72 repeat expansion, and to correlate sNfL levels to disease progression, assessed by the brain atrophy rate and survival time.MethodsThe sNfL levels were determined from 78 FTLD patients (C9orf72 repeat expansion carriers [n = 26] and non‐carriers [n = 52]) with Single Molecule Array (SIMOA). The progression of brain atrophy was evaluated using repeated T1‐weighted MRI scans and the survival time from medical records.ResultsIn the total FTLD cohort, sNfL levels were significantly higher in C9orf72 repeat expansion carriers compared to non‐carriers. Considering clinical phenotypes, sNfL levels were higher in the C9orf72 repeat expansion carriers than in the non‐carriers in bvFTD and PPA groups. Furthermore, sNfL levels were the highest in the FTLD‐MND group (median 105 pg/mL) and the lowest in the bvFTD group (median 27 pg/mL). Higher sNfL levels significantly correlated with frontal cortical atrophy rate and subcortical grey matter atrophy rate. The higher sNfL levels also associated with shorter survival time.InterpretationOur results indicate that the C9orf72 repeat expansion carriers show elevated sNFL levels compared to non‐carriers and that the levels differ among different clinical phenotypes of FTLD. Higher sNfL levels correlated with a shorter survival time and cortical and subcortical atrophy rates. Thus, sNfL could prove as a potential prognostic biomarker in FTLD.

Association of hippocampal volume polygenic predictor score with baseline and change in brain volumes and cognition among cognitively healthy older adults

A high hippocampal volume polygenic predictor score (HV-PPS), computed based on GWAS summary statistics (n = 33,536), could be protective against declines in brain volume and cognition in older adults. Linear mixed-effects models with random intercepts and slopes were used to estimate associations of HV-PPS with baseline and annual rate of change in both brain volumes (n = 508) and cognitive performance (n = 1041) in Caucasian Baltimore Longitudinal Study of Aging participants. Higher HV-PPS was associated with greater baseline volumes of the hippocampus and parahippocampal gyrus, and slower rates of ventricular enlargement and volume loss in frontal and parietal white matter, all adjusted for intracranial volume. In addition, higher HV-PPS was associated with better executive function performance and slower rates of decline in verbal fluency scores over time. Individuals with a genetic predisposition toward larger hippocampal volumes show better baseline executive function, slower decline in verbal fluency performance, and slower rates of longitudinal brain atrophy.

Interaction between Apolipoprotein E and Butyrylcholinesterase Genes on Risk of Alzheimer's Disease in a Prospective Cohort Study.

An epistatic interaction between the ɛ4 allele of apolipoprotein E (APOEɛ4) gene and the K-variant of butyrylcholinesterase (BCHE-K) genes has been previously reported to increase risk of Alzheimer's disease (AD). However, these observations were largely from case-control studies with small sample sizes. To examine the interaction between APOEɛ4 and BCHE-K on: 1) the risk of incident AD and 2) rates of change in brain volumes and cognitive performance during the preclinical stages of AD in a prospective cohort study. The study sample for survival analysis included 691 Caucasian participants (age at baseline, 58.4±9.9 years; follow-up time,16.9±9.7 years) from the Baltimore Longitudinal Study of Aging. The neuroimaging sample included 302 participants with 1,388 magnetic resonance imaging (MRI) scans. Cognitive performance was assessed in 703 participants over 4,908 visits. A total of 122 diagnoses (79 AD, 43 mild cognitive impairment [MCI]) were identified. Participants with both APOEɛ4 and BCHE-K variants had a 3.7-fold greater risk of AD (Hazard ratio [HR] 95% CI=1.99-6.89, p < 0.001) compared to non-carriers of both genes (APOE ɛ4 x BCHE-K interaction p = 0.025). There was no APOE ɛ4-BCHE-K interaction effect on rate of cognitive decline and brain atrophy. The APOE and BCHE genes interact to influence risk of incident AD/MCI but not rates of brain atrophy and decline in cognitive performance before onset of cognitive impairment. This may suggest the epistatic interaction between APOE ɛ4 and BCHE-K on AD risk is disease stage-dependent.