Plasma neurofilament light in behavioural variant frontotemporal dementia compared to mood and psychotic disorders.

OBJECTIVE: Blood biomarkers of neuronal injury such as neurofilament light (NfL) show promise to improve diagnosis of neurodegenerative disorders and distinguish neurodegenerative from primary psychiatric disorders (PPD). This study investigated the diagnostic utility of plasma NfL to differentiate behavioural variant frontotemporal dementia (bvFTD, a neurodegenerative disorder commonly misdiagnosed initially as PPD), from PPD, and performance of large normative/reference data sets and models. METHODS: Plasma NfL was analysed in major depressive disorder (MDD, n = 42), bipolar affective disorder (BPAD, n = 121), treatment-resistant schizophrenia (TRS, n = 82), bvFTD (n = 22), and compared to the reference cohort (Control Group 2, n = 1926, using GAMLSS modelling), and age-matched controls (Control Group 1, n = 96, using general linear models). RESULTS: Large differences were seen between bvFTD (mean NfL 34.9 pg/mL) and all PPDs and controls (all < 11 pg/mL). NfL distinguished bvFTD from PPD with high accuracy, sensitivity (86%), and specificity (88%). GAMLSS models using reference Control Group 2 facilitated precision interpretation of individual levels, while performing equally to or outperforming models using local controls. Slightly higher NfL levels were found in BPAD, compared to controls and TRS. CONCLUSIONS: This study adds further evidence on the diagnostic utility of NfL to distinguish bvFTD from PPD of high clinical relevance to a bvFTD differential diagnosis, and includes the largest cohort of BPAD to date. Using large reference cohorts, GAMLSS modelling and the interactive Internet-based application we developed, may have important implications for future research and clinical translation. Studies are underway investigating utility of plasma NfL in diverse neurodegenerative and primary psychiatric conditions in real-world clinical settings.

Towards interpretable speech biomarkers: exploring MFCCs.

While speech biomarkers of disease have attracted increased interest in recent years, a challenge is that features derived from signal processing or machine learning approaches may lack clinical interpretability. As an example, Mel frequency cepstral coefficients (MFCCs) have been identified in several studies as a useful marker of disease, but are regarded as uninterpretable. Here we explore correlations between MFCC coefficients and more interpretable speech biomarkers. In particular we quantify the MFCC2 endpoint, which can be interpreted as a weighted ratio of low- to high-frequency energy, a concept which has been previously linked to disease-induced voice changes. By exploring MFCC2 in several datasets, we show how its sensitivity to disease can be increased by adjusting computation parameters.

Molecular biomarkers for vascular cognitive impairment and dementia.

As disease-specific interventions for dementia are being developed, the ability to identify the underlying pathology and dementia subtypes is increasingly important. Vascular cognitive impairment and dementia (VCID) is the second most common cause of dementia after Alzheimer disease, but progress in identifying molecular biomarkers for accurate diagnosis of VCID has been relatively limited. In this Review, we examine the roles of large and small vessel disease in VCID, considering the underlying pathophysiological processes that lead to vascular brain injury, including atherosclerosis, arteriolosclerosis, ischaemic injury, haemorrhage, hypoperfusion, endothelial dysfunction, blood-brain barrier breakdown, inflammation, oxidative stress, hypoxia, and neuronal and glial degeneration. We consider the key molecules in these processes, including proteins and peptides, metabolites, lipids and circulating RNA, and consider their potential as molecular biomarkers alone and in combination. We also discuss the challenges in translating the promise of these biomarkers into clinical application.

White matter hyperintensities modify relationships between corticospinal tract damage and motor outcomes after stroke.

Motor outcomes after stroke relate to corticospinal tract (CST) damage. Concurrent damage from white matter hyperintensities (WMHs) might impact neurological capacity for recovery after CST injury. Here, we evaluated if WMHs modulate the relationship between CST damage and post-stroke motor impairment outcome. We included 223 individuals from the ENIGMA Stroke Recovery Working Group. CST damage was indexed with weighted CST lesion load (CST-LL). Mixed effects beta-regression models were fit to test the impact of CST-LL, WMH volume, and their interaction on motor impairment. WMH volume related to motor impairment above and beyond CST-LL (ß = 0.178, p = 0.022). We tested if relationships varied by WMH severity (mild vs. moderate-severe). In individuals with mild WMHs, motor impairment related to CST-LL (ß = 0.888, p < 0.001) with a CST-LL x WMH interaction (ß = -0.211, 0.026). In individuals with moderate-severe WMHs, motor impairment related to WMH volume (ß = 0.299, p = 0.044), but did not significantly relate to CST-LL or a CST-LL x WMH interaction. WMH-related damage may be under-recognised in stroke research as a factor contributing to variability in motor outcomes. Our findings emphasize the importance of brain structural reserve in motor outcomes after brain injury.

Consensus statement for the management of incidentally found brain white matter hyperintensities in general medical practice.

INTRODUCTION: There is a paradigm shift in our understanding of white matter hyperintensities (WMH) found on brain imaging. They were once thought to be a normal phenomenon of ageing and, therefore, warranted no further investigation. However, evidence now suggests these lesions are markers of poor brain and cardiovascular health, portending an increased risk of stroke, cognitive decline, depression and death. Nevertheless, no specific guidelines exist for the management of incidentally found WMH for general medical practitioners and other clinicians ordering brain magnetic resonance imaging scans for diverse clinical indications. Informed by a literature review and expert opinion gleaned from stroke neurologists, medical and imaging specialists, and general practitioners, we present our consensus statement to guide the management of incidentally found WMH in adults. MAIN RECOMMENDATIONS: When incidental WMH are found on brain imaging: Perform a detailed history and examination to screen for neurological events. Investigate for potential undiagnosed or undertreated cardiovascular risk factors, especially hypertension and diabetes mellitus. Commence intensive and individualised cardiovascular risk management when risk factors are uncovered. Treat underlying risk factors via accepted guidelines but note that antiplatelet and anticoagulant medications should not be prescribed for incidental WMH in the absence of an alternative indication. CHANGES TO MANAGEMENT AS A RESULT OF THIS CONSENSUS STATEMENT: A brain health opportunity. We consider the discovery of incidental WMH on brain imaging to represent an opportunity to investigate for common cardiovascular risk factors and to optimise brain health. This can be commenced and monitored by the general practitioner or physician without delay in waiting for an outpatient neurology review.

Optimizing automated white matter hyperintensity segmentation in individuals with stroke.

White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.

The Associations Between Neuropsychiatric Symptoms and Cognition in People with Dementia: A Systematic Review and Meta-Analysis.

Most people with dementia experience neuropsychiatric symptoms (NPS), including anxiety, depression or disinhibition. There is growing interest in the relationship between NPS and cognitive impairment, but data is still limited. This study aimed to investigate the specific associations between NPS and cognition in people with dementia. MEDLINE, EMBASE and PsycINFO were searched for published, peer-reviewed studies of associations between at least one NPS and one cognitive ability in people with dementia. The quality of the studies was assessed with the NIH National Heart, Lung and Blood Institute's quality assessment tools. A meta-analysis was conducted using Robumeta package for R. Ninety studies were included. We found significant associations between NPS, global cognition and cognitive domains, e.g. apathy was associated with global cognitive and memory impairment; dysphoria was associated with worse attention; delusions with executive dysfunction. Increased NPS in people with dementia are associated with worse cognitive performance. There were few studies looking at associations between some neuropsychiatric clusters and cognitive abilities, and there was little research on causal relationships. Our review was limited by the inclusion of studies that reported associations in specific formats, and most included people with a diagnosis of Alzheimer's disease (AD). However, given the large number of studies, this is unlikely to have biased results. More research is needed that includes diverse people with different dementia syndromes. Registration: PROSPERO 2020 CRD42020165565.

Validation of newly derived polygenic risk scores for dementia in a prospective study of older individuals.

INTRODUCTION: Recent genome-wide association studies identified new dementia-associated variants. We assessed the performance of updated polygenic risk scores (PRSs) using these variants in an independent cohort. METHODS: We used Cox models and area under the curve (AUC) to validate new PRSs (PRS-83SNP, PRS-SBayesR, and PRS-CS) compared with an older PRS-23SNP in 12,031 initially-healthy participants ≥70 years of age. Dementia was rigorously adjudicated according to Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria. RESULTS: PRS-83SNP, PRS-SBayesR, and PRS-CS were associated with incident dementia, with fully adjusted (including apolipoprotein E [APOE] ε4) hazard ratios per standard deviation (SD) of 1.35 (1.23-1.47), 1.37 (1.25-1.50), and 1.42 (1.30-1.56), respectively. The AUC of a model containing conventional/non-genetic factors and APOE was 74.7%. This was improved to 75.7% (p = 0.007), 76% (p = 0.004), and 76.1% (p = 0.003) with addition of PRS-83SNP, PRS-SBayesR, and PRS-CS, respectively. The PRS-23SNP did not improve AUC (74.7%, p = 0.95). CONCLUSION: New PRSs for dementia significantly improve risk-prediction performance, but still account for less risk than APOE genotype overall.

Neuroimaging standards for research into small vessel disease-advances since 2013.

Cerebral small vessel disease (SVD) is common during ageing and can present as stroke, cognitive decline, neurobehavioural symptoms, or functional impairment. SVD frequently coexists with neurodegenerative disease, and can exacerbate cognitive and other symptoms and affect activities of daily living. Standards for Reporting Vascular Changes on Neuroimaging 1 (STRIVE-1) categorised and standardised the diverse features of SVD that are visible on structural MRI. Since then, new information on these established SVD markers and novel MRI sequences and imaging features have emerged. As the effect of combined SVD imaging features becomes clearer, a key role for quantitative imaging biomarkers to determine sub-visible tissue damage, subtle abnormalities visible at high-field strength MRI, and lesion-symptom patterns, is also apparent. Together with rapidly emerging machine learning methods, these metrics can more comprehensively capture the effect of SVD on the brain than the structural MRI features alone and serve as intermediary outcomes in clinical trials and future routine practice. Using a similar approach to that adopted in STRIVE-1, we updated the guidance on neuroimaging of vascular changes in studies of ageing and neurodegeneration to create STRIVE-2.

Train Smart Study: protocol for a randomised trial investigating the role of exercise training dose on markers of brain health in sedentary middle-aged adults.

INTRODUCTION: Regular aerobic exercise is associated with improved cognitive function, implicating it as a strategy to reduce dementia risk. This is reinforced by the association between greater cardiorespiratory fitness and larger brain volume, superior cognitive performance and lower dementia risk. However, the optimal aerobic exercise dose, namely the intensity and mode of delivery, to improve brain health and lower dementia risk has received less attention. We aim to determine the effect of different doses of aerobic exercise training on markers of brain health in sedentary middle-aged adults, hypothesising that high-intensity interval training (HIIT) will be more beneficial than moderate-intensity continuous training (MICT). METHODS AND ANALYSIS: In this two-group parallel, open-label blinded endpoint randomised trial, 70 sedentary middle-aged (45-65 years) adults will be randomly allocated to one of two 12-week aerobic exercise training interventions matched for total exercise training volume: (1) MICT (n=35) or HIIT (n=35). Participants will perform ~50 min exercise training sessions, 3 days per week, for 12 weeks. The primary outcome will be measured as between-group difference in cardiorespiratory fitness (peak oxygen uptake) change from baseline to the end of training. Secondary outcomes include between-group differences in cognitive function and ultra-high field MRI (7T) measured markers of brain health (brain blood flow, cerebrovascular function, brain volume, white matter microstructural integrity and resting state functional brain activity) changes from baseline to the end of training. ETHICS AND DISSEMINATION: The Victoria University Human Research Ethics Committee (VUHREC) has approved this study (HRE20178), and all protocol modifications will be communicated to the relevant parties (eg, VUHREC, trial registry). Findings from this study will be disseminated via peer-review publications, conference presentations, clinical communications and both mainstream and social media. TRIAL REGISTRATION NUMBER: ANZCTR12621000144819.

Neural correlates of verbal fluency revealed by longitudinal T1, T2 and FLAIR imaging in stroke.

Diffusion-weighted imaging has been widely used in the research on post-stroke verbal fluency but acquiring diffusion data is not always clinically feasible. Achieving comparable reliability for detecting brain variables associated with verbal fluency impairments, based on more readily available anatomical, non-diffusion images (T1, T2 and FLAIR), enables clinical practitioners to have complementary neurophysiological information at hand to facilitate diagnosis and treatment of language impairment. Meanwhile, although the predominant focus in the stroke recovery literature has been on cortical contributions to verbal fluency, it remains unclear how subcortical regions and white matter disconnection are related to verbal fluency. Our study thus utilized anatomical scans of ischaemic stroke survivors (n = 121) to identify longitudinal relationships between subcortical volume, white matter tract disconnection, and verbal fluency performance at 3- and 12-months post-stroke. Subcortical grey matter volume was derived from FreeSurfer. We used an indirect probabilistic approach to quantify white matter disconnection in terms of disconnection severity, the proportion of lesioned voxel volume to the total volume of a tract, and disconnection probability, the probability of the overlap between the stroke lesion and a tract. These disconnection variables of each subject were identified based on the disconnectome map of the BCBToolkit. Using a linear mixed multiple regression method with 5-fold cross-validations, we correlated the semantic and phonemic fluency scores with longitudinal measurements of subcortical grey matter volume and 22 bilateral white matter tracts, while controlling for demographic variables (age, sex, handedness and education), total brain volume, lesion volume, and cortical thickness. The results showed that the right subcortical grey matter volume was positively correlated with phonemic fluency averaged over 3 months and 12 months. The finding generalized well on the test data. The disconnection probability of left superior longitudinal fasciculus II and left posterior arcuate fasciculus was negatively associated with semantic fluency only on the training data, but the result aligned with our previous study using diffusion scans in the same clinical population. In sum, our results presented evidence that routinely acquired anatomical scans can serve as a reliable source for deriving neural variables of post-stroke verbal fluency performance. The use of this method might provide an ecologically valid and more readily implementable analysis tool.

Association of Brain Age, Lesion Volume, and Functional Outcome in Patients With Stroke.

BACKGROUND AND OBJECTIVES: Functional outcomes after stroke are strongly related to focal injury measures. However, the role of global brain health is less clear. In this study, we examined the impact of brain age, a measure of neurobiological aging derived from whole-brain structural neuroimaging, on poststroke outcomes, with a focus on sensorimotor performance. We hypothesized that more lesion damage would result in older brain age, which would in turn be associated with poorer outcomes. Related, we expected that brain age would mediate the relationship between lesion damage and outcomes. Finally, we hypothesized that structural brain resilience, which we define in the context of stroke as younger brain age given matched lesion damage, would differentiate people with good vs poor outcomes. METHODS: We conducted a cross-sectional observational study using a multisite dataset of 3-dimensional brain structural MRIs and clinical measures from the ENIGMA Stroke Recovery. Brain age was calculated from 77 neuroanatomical features using a ridge regression model trained and validated on 4,314 healthy controls. We performed a 3-step mediation analysis with robust mixed-effects linear regression models to examine relationships between brain age, lesion damage, and stroke outcomes. We used propensity score matching and logistic regression to examine whether brain resilience predicts good vs poor outcomes in patients with matched lesion damage. RESULTS: We examined 963 patients across 38 cohorts. Greater lesion damage was associated with older brain age (ß = 0.21; 95% CI 0.04-0.38, p = 0.015), which in turn was associated with poorer outcomes, both in the sensorimotor domain (ß = -0.28; 95% CI -0.41 to -0.15, p < 0.001) and across multiple domains of function (ß = -0.14; 95% CI -0.22 to -0.06, p < 0.001). Brain age mediated 15% of the impact of lesion damage on sensorimotor performance (95% CI 3%-58%, p = 0.01). Greater brain resilience explained why people have better outcomes, given matched lesion damage (odds ratio 1.04, 95% CI 1.01-1.08, p = 0.004). DISCUSSION: We provide evidence that younger brain age is associated with superior poststroke outcomes and modifies the impact of focal damage. The inclusion of imaging-based assessments of brain age and brain resilience may improve the prediction of poststroke outcomes compared with focal injury measures alone, opening new possibilities for potential therapeutic targets.

Changes in White Matter Microstructure Over 3 Years in People With and Without Stroke.

BACKGROUND AND OBJECTIVES: Cerebral white matter health can be estimated by MRI-derived indices of microstructure. White matter dysfunction is increasingly recognized as a contributor to neurodegenerative disorders affecting cognition and to functional outcomes after stroke. Reduced indices of white matter microstructure have been demonstrated cross-sectionally in stroke survivors compared with stroke-free participants, but longitudinal changes in the structure of white matter after stroke remain largely unexplored. We aimed to characterize white matter micro- and macrostructure over 3 years after stroke and study associations with white matter metrics and cognitive functions. METHODS: Patients with first-ever or recurrent ischemic stroke of any etiology in any vascular territory were compared with stroke-free age- and sex-matched controls. Those diagnosed with hemorrhagic stroke, TIA, venous infarction, or significant medical comorbidities, psychiatric and neurodegenerative disorders, substance abuse, or history of dementia were excluded. Diffusion-weighted MRI data at 3, 12, and 36 months were analyzed using a longitudinal fixel-based analysis, sensitive to fiber tract-specific differences within a voxel. It was used to examine whole-brain white matter degeneration in stroke compared with control participants. We studied microstructural differences in fiber density and macrostructural changes in fiber-bundle cross-section, in relation to cognitive performance. Analyses were performed controlling for age, intracranial volume, and education (family-wise error-corrected p < 0.05, nonparametric testing over 5,000 permutations). RESULTS: We included 71 participants with stroke (age 66 ± 12 years, 22 women) and 36 controls (age 69 ± 5 years, 13 women). We observed extensive white matter structural degeneration across the whole brain, particularly affecting the thalamic, cerebellar, striatal, and superior longitudinal tracts and corpus callosum. Importantly, follow-up regression analyses in 72 predefined tracts showed that the decline in fiber density and cross-section from 3 months to 3 years was associated with worse cognitive performance at 3 years after stroke, especially affecting visuospatial processing, processing speed, language, and recognition memory. DISCUSSION: We conclude that white matter neurodegeneration in ipsi- and contralesional thalamic, striatal, and cerebellar tracts continues to be greater in stroke survivors compared with stroke-free controls. White matter degeneration persists even years after stroke and is associated with poststroke cognitive impairment. TRIAL REGISTRATION INFORMATION: ClinicalTrails.gov NCT02205424.

Insomnia Symptoms and Biomarkers of Alzheimer's Disease in the Community.

BACKGROUND: Insomnia is one of the most common sleep disorders yet its relationship to the biology of Alzheimer's disease remains equivocal. OBJECTIVE: We investigated the cross-sectional relationship between insomnia symptom severity and cerebrospinal fluid (CSF) concentrations of Alzheimer's disease biomarkers in a cognitively unimpaired middle-aged community sample. METHODS: A total of 63 participants from the Healthy Brain Project (age = 59±7 years; 67% women) completed a lumbar puncture and two weeks of actigraphy to measure two of insomnia's core features: difficulty initiating sleep (prolonged sleep onset latency) and difficulty maintaining sleep (wake after sleep onset [WASO] and number of awakenings). Additionally, the Insomnia Severity Index (ISI) was completed by 58 participants. Linear and Tobit regression were used to estimate the associations between each insomnia variable and CSF Aß42, phosphorylated tau 181 (p-tau181), total-tau, and neurofilament light chain protein (NfL), adjusting for age, sex, and APOEɛ4 genotype. RESULTS: Higher ISI score was associated with greater average levels of CSF Aß42 (per point: 30.7 pg/mL, 95% CI: 4.17-57.3, p = 0.023), as was higher WASO (per 10 min: 136 pg/mL, 95% CI: 48-223, p = 0.002) and more awakenings (per 5:123 pg/mL, 95% CI = 55-192, p < 0.001). Difficulty initiating sleep was not associated with CSF Aß42, nor were insomnia features associated with p-tau181, total-tau, or NfL levels. CONCLUSION: Insomnia symptoms were associated with higher CSF Aß42 levels in this relatively young, cognitively unimpaired sample. These findings may reflect increased amyloid production due to acute sleep disruption.

Bridging Big Data: Procedures for Combining Non-equivalent Cognitive Measures from the ENIGMA Consortium.

Investigators in neuroscience have turned to Big Data to address replication and reliability issues by increasing sample sizes, statistical power, and representativeness of data. These efforts unveil new questions about integrating data arising from distinct sources and instruments. We focus on the most frequently assessed cognitive domain - memory testing - and demonstrate a process for reliable data harmonization across three common measures. We aggregated global raw data from 53 studies totaling N = 10,505 individuals. A mega-analysis was conducted using empirical bayes harmonization to remove site effects, followed by linear models adjusting for common covariates. A continuous item response theory (IRT) model estimated each individual's latent verbal learning ability while accounting for item difficulties. Harmonization significantly reduced inter-site variance while preserving covariate effects, and our conversion tool is freely available online. This demonstrates that large-scale data sharing and harmonization initiatives can address reproducibility and integration challenges across the behavioral sciences.