Cognitive impairment among patients with chronic immune thrombocytopenia.

Immune thrombocytopenia (ITP) is an autoimmune disease typically associated with severely depleted platelet counts. However, additional symptoms (e.g. increased fatigue and memory/concentration difficulties) can profoundly impact patients' quality of life. The nature and severity of cognitive impairment in ITP, and potential association with patient/disease characteristics were evaluated in 49 adults with relapsed/refractory ITP. The Cogstate Brief Battery quantitatively assessed psychomotor function (DET), attention (IDN), visual learning (OCL) and working memory (ONB) individually, as well as DET/IDN and OCL/ONB composites. Clinically important cognitive impairment (defined as z-score ≤ -1) for ≥2 individual tests was observed in 29 patients (59%). Impairment was highest for IDN (67% of patients), followed by DET (53%), ONB (39%) and OCL (16%). A higher magnitude of impairment was observed for the DET/IDN composite (mean z-score -1.54; 95% CI, -1.94 to -1.13) than OCL/ONB (mean z-score -0.21; 95% CI, -0.49 to 0.07). The severity of cognitive impairment was comparable to mild traumatic brain injury and associated with increasing age and fatigue but unrelated to platelet count or corticosteroid use. Overall, these results warrant a clinical need to further consider the potential of cognitive dysfunction in assessing ITP patients.

Physical activity and brain amyloid beta: A longitudinal analysis of cognitively unimpaired older adults.

INTRODUCTION: The current study evaluated the relationship between habitual physical activity (PA) levels and brain amyloid beta (Aß) over 15 years in a cohort of cognitively unimpaired older adults. METHODS: PA and Aß measures were collected over multiple timepoints from 731 cognitively unimpaired older adults participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Aging. Regression modeling examined cross-sectional and longitudinal relationships between PA and brain Aß. Moderation analyses examined apolipoprotein E (APOE) ε4 carriage impact on the PA-Aß relationship. RESULTS: PA was not associated with brain Aß at baseline (ß = -0.001, p = 0.72) or over time (ß = -0.26, p = 0.24). APOE ε4 status did not moderate the PA-Aß relationship over time (ß = 0.12, p = 0.73). Brain Aß levels did not predict PA trajectory (ß = -54.26, p = 0.59). DISCUSSION: Our study did not identify a relationship between habitual PA and brain Aß levels. HIGHLIGHTS: Physical activity levels did not predict brain amyloid beta (Aß) levels over time in cognitively unimpaired older adults (≥60 years of age). Apolipoprotein E (APOE) ε4 carrier status did not moderate the physical activity-brain Aß relationship over time. Physical activity trajectories were not impacted by brain Aß levels.

The brain-derived neurotrophic factor Val66met polymorphism is associated with better attention and working memory performance and resilience to mild chronic stress.

The val66met polymorphism of the brain-derived neurotrophic factor (BDNF) gene has been identified as a potential moderator for the relationship between chronic stress and executive functioning. However, whether the presence of the met allele increases cognitive vulnerability or resilience to stress has yet to be determined. Given the established effects of autonomic activity and psychological arousal on executive functioning, in the present study, 56 healthy university students completed self-report measures of chronic stress, positive arousal (vigour) and negative arousal (anxiety) and measured heart-rate variability to quantify autonomic activity. Participants then completed a cognitive test battery that measured attention, decision-making, visual learning and working memory. Regression analyses demonstrated that Val/met participants performed better on attention and working memory tasks than Val/val participants, but no differences were seen in decision-making and visual learning. Further, Val/met participants were protected from stress-related differences in attention seen in Val/val participants. Val66met was not associated with physiological or psychological arousal. This study demonstrates that val66met plays an important but selective role in cognitive performance.

Development of complex executive function over childhood: Longitudinal growth curve modeling of performance on the Groton Maze Learning Task.

This longitudinal study modeled children's complex executive function (EF) development using the Groton Maze Learning Task (GMLT). Using a cohort-sequential design, 147 children (61 males, 5.5-11 years) were recruited from six multicultural primary schools in Melbourne and Perth, Australia. Race/ethnicity data were not available. Children were assessed on the GMLT at 6-month intervals over 2-years between 2010 and 2012. Growth curve models describe age-related change from 5.5 to 12.5 years old. Results showed a quadratic growth trajectory on each measure of error-that is, those that reflect visuospatial memory, executive control (or the ability to apply rules for action), and complex EF. The ability to apply rules for action, while a rate-limiting factor in complex EF, develops rapidly over early-to-mid childhood.

Why a clinical trial is as good as its outcome measure: A framework for the selection and use of cognitive outcome measures for clinical trials of Alzheimer's disease.

A crucial aspect of any clinical trial is using the right outcome measure to assess treatment efficacy. Compared to the rapidly evolved understanding and measurement of pathophysiology in preclinical and early symptomatic stages of Alzheimer's disease (AD), relatively less progress has been made in the evolution of clinical outcome assessments (COAs) for those stages. The current paper aims to provide a benchmark for the design and evaluation of COAs for use in early AD trials. We discuss lessons learned on capturing cognitive changes in predementia stages of AD, including challenges when validating novel COAs for those early stages and necessary evidence for their implementation in clinical trials. Moving forward, we propose a multi-step framework to advance the use of more effective COAs to assess clinically meaningful changes in early AD, which will hopefully contribute to the much-needed consensus around more appropriate outcome measures to assess clinical efficacy of putative treatments. HIGHLIGHTS: We discuss lessons learned on capturing cognitive changes in predementia stages of AD. We propose a framework for the design and evaluation of performance based cognitive tests for use in early AD trials. We provide recommendations to facilitate the implementation of more effective cognitive outcome measures in AD trials.

The relationship between objective physical activity and change in cognitive function.

INTRODUCTION: The current study investigated the association between objectively measured physical activity and cognition in older adults over approximately 8 years. METHODS: We utilized data from 199 cognitively unimpaired individuals from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study, aged ≥60. Actigraphy was used to measure physical activity (intensity, total activity, and energy expenditure) at baseline. Cognition was assessed using a comprehensive cognitive battery every 18-months. RESULTS: Higher baseline energy expenditure predicted better episodic recall memory and global cognition over the follow-up period (p = 0.031; p = 0.047, respectively). Those with higher physical activity intensity and greater total activity also had better global cognition over time (both p = 0.005). Finally, higher total physical activity predicted improved episodic recall memory over time (p = 0.022). DISCUSSION: These results suggest that physical activity can preserve cognition and that activity intensity may play an important role in this association. HIGHLIGHTS: Greater total physical activity predicts preserved episodic memory and global cognition. Moderate intensity physical activity (>3.7 metabolic equivalents of task [MET]) predicts preserved global cognition. Expending > 373 kilocalories per day may benefit episodic memory and global cognition.

Plasma Aß42/40 ratio, p-tau181, GFAP, and NfL across the Alzheimer's disease continuum: A cross-sectional and longitudinal study in the AIBL cohort.

INTRODUCTION: Plasma amyloid beta (Aß)1-42/Aß1-40 ratio, phosphorylated-tau181 (p-tau181), glial fibrillary acidic protein (GFAP), and neurofilament light (NfL) are putative blood biomarkers for Alzheimer's disease (AD). However, head-to-head cross-sectional and longitudinal comparisons of the aforementioned biomarkers across the AD continuum are lacking. METHODS: Plasma Aß1-42, Aß1-40, p-tau181, GFAP, and NfL were measured utilizing the Single Molecule Array (Simoa) platform and compared cross-sectionally across the AD continuum, wherein Aß-PET (positron emission tomography)-negative cognitively unimpaired (CU Aß-, n = 81) and mild cognitive impairment (MCI Aß-, n = 26) participants were compared with Aß-PET-positive participants across the AD continuum (CU Aß+, n = 39; MCI Aß+, n = 33; AD Aß+, n = 46) from the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) cohort. Longitudinal plasma biomarker changes were also assessed in MCI (n = 27) and AD (n = 29) participants compared with CU (n = 120) participants. In addition, associations between baseline plasma biomarker levels and prospective cognitive decline and Aß-PET load were assessed over a 7 to 10-year duration. RESULTS: Lower plasma Aß1-42/Aß1-40 ratio and elevated p-tau181 and GFAP were observed in CU Aß+, MCI Aß+, and AD Aß+, whereas elevated plasma NfL was observed in MCI Aß+ and AD Aß+, compared with CU Aß- and MCI Aß-. Among the aforementioned plasma biomarkers, for models with and without AD risk factors (age, sex, and apolipoprotein E (APOE) ε4 carrier status), p-tau181 performed equivalent to or better than other biomarkers in predicting a brain Aß-/+ status across the AD continuum. However, for models with and without the AD risk factors, a biomarker panel of Aß1-42/Aß1-40, p-tau181, and GFAP performed equivalent to or better than any of the biomarkers alone in predicting brain Aß-/+ status across the AD continuum. Longitudinally, plasma Aß1-42/Aß1-40, p-tau181, and GFAP were altered in MCI compared with CU, and plasma GFAP and NfL were altered in AD compared with CU. In addition, lower plasma Aß1-42/Aß1-40 and higher p-tau181, GFAP, and NfL were associated with prospective cognitive decline and lower plasma Aß1-42/Aß1-40, and higher p-tau181 and GFAP were associated with increased Aß-PET load prospectively. DISCUSSION: These findings suggest that plasma biomarkers are altered cross-sectionally and longitudinally, along the AD continuum, and are prospectively associated with cognitive decline and brain Aß-PET load. In addition, although p-tau181 performed equivalent to or better than other biomarkers in predicting an Aß-/+ status across the AD continuum, a panel of biomarkers may have superior Aß-/+ status predictive capability across the AD continuum. HIGHLIGHTS: Area under the curve (AUC) of p-tau181 ≥ AUC of Aß42/40, GFAP, NfL in predicting PET Aß-/+ status (Aß-/+).  AUC of Aß42/40+p-tau181+GFAP panel ≥ AUC of Aß42/40/p-tau181/GFAP/NfL for Aß-/+.  Longitudinally, Aß42/40, p-tau181, and GFAP were altered in MCI versus CU.  Longitudinally, GFAP and NfL were altered in AD versus CU.  Aß42/40, p-tau181, GFAP, and NfL are associated with prospective cognitive decline.  Aß42/40, p-tau181, and GFAP are associated with increased PET Aß load prospectively.

Leukocyte surface biomarkers implicate deficits of innate immunity in sporadic Alzheimer's disease.

INTRODUCTION: Blood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions. METHODS: In three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses. RESULTS: We identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aß clearance. A proposed panel including four leukocyte markers - CD11c, CD59, CD91, and CD163 - predicts patients' PET Aß status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts. CONCLUSION: Our finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis.

Systemic perturbations of the kynurenine pathway precede progression to dementia independently of amyloid-ß.

Increasing evidence suggests that kynurenine pathway (KP) dyshomeostasis may promote disease progression in dementia. Studies in Alzheimer's disease (AD) patients confirm KP dyshomeostasis in plasma and cerebrospinal fluid (CSF) which correlates with amyloid-ß and tau pathology. Herein, we performed the first comprehensive study assessing baseline levels of KP metabolites in participants enrolling in the Australian Imaging Biomarkers Flagship Study of Aging. Our purpose was to test the hypothesis that changes in KP metabolites may be biomarkers of dementia processes that are largely silent. We used a cross-sectional analytical approach to assess non-progressors (N = 73); cognitively normal (CN) or mild cognitive impairment (MCI) participants at baseline and throughout the study, and progressors (N = 166); CN or MCI at baseline but progressing to either MCI or AD during the study. Significant KP changes in progressors included increased 3-hydroxyanthranilic acid (3-HAA) and 3-hydroxyanthranilic acid/anthranilic acid (3-HAA/AA) ratio, the latter having the largest effect on the odds of an individual being a progressor (OR 35.3; 95% CI between 14 and 104). 3-HAA levels were hence surprisingly bi-phasic, high in progressors but low in non-progressors or participants who had already transitioned to MCI or dementia. This is a new, unexpected and interesting result, as most studies of the KP in neurodegenerative disease show reduced 3-HAA/AA ratio after diagnosis. The neuroprotective metabolite picolinic acid was also significantly decreased while the neurotoxic metabolite 3-hydroxykynurenine increased in progressors. These results were significant even after adjustment for confounders. Considering the magnitude of the OR to predict change in cognition, it is important that these findings are replicated in other populations. Independent validation of our findings may confirm the utility of 3-HAA/AA ratio to predict change in cognition leading to dementia in clinical settings.

Deep Generative Medical Image Harmonization for Improving Cross-Site Generalization in Deep Learning Predictors.

BACKGROUND: In the medical imaging domain, deep learning-based methods have yet to see widespread clinical adoption, in part due to limited generalization performance across different imaging devices and acquisition protocols. The deviation between estimated brain age and biological age is an established biomarker of brain health and such models may benefit from increased cross-site generalizability. PURPOSE: To develop and evaluate a deep learning-based image harmonization method to improve cross-site generalizability of deep learning age prediction. STUDY TYPE: Retrospective. POPULATION: Eight thousand eight hundred and seventy-six subjects from six sites. Harmonization models were trained using all subjects. Age prediction models were trained using 2739 subjects from a single site and tested using the remaining 6137 subjects from various other sites. FIELD STRENGTH/SEQUENCE: Brain imaging with magnetization prepared rapid acquisition with gradient echo or spoiled gradient echo sequences at 1.5 T and 3 T. ASSESSMENT: StarGAN v2, was used to perform a canonical mapping from diverse datasets to a reference domain to reduce site-based variation while preserving semantic information. Generalization performance of deep learning age prediction was evaluated using harmonized, histogram matched, and unharmonized data. STATISTICAL TESTS: Mean absolute error (MAE) and Pearson correlation between estimated age and biological age quantified the performance of the age prediction model. RESULTS: Our results indicated a substantial improvement in age prediction in out-of-sample data, with the overall MAE improving from 15.81 (±0.21) years to 11.86 (±0.11) with histogram matching to 7.21 (±0.22) years with generative adversarial network (GAN)-based harmonization. In the multisite case, across the 5 out-of-sample sites, MAE improved from 9.78 (±6.69) years to 7.74 (±3.03) years with histogram normalization to 5.32 (±4.07) years with GAN-based harmonization. DATA CONCLUSION: While further research is needed, GAN-based medical image harmonization appears to be a promising tool for improving cross-site deep learning generalization. LEVEL OF EVIDENCE: 4 TECHNICAL EFFICACY: Stage 1.

Increasing the Cognitive Screening Efficiency of Global Phase III Trials in Early Alzheimer Disease: The Cognitive Task Force.

PURPOSE: A Cognitive Task Force (CTF) was established for the MissionAD program with the aim of reducing the screen failure (SF) rate to ∼30% and thereby reduce unnecessary subject burden, site burden, and excess trial costs. METHODS/SUBJECTS: The MissionAD program consisted of 2 global phase 3 studies evaluating the BACE inhibitor elenbecestat in subjects with early Alzheimer disease. The CTF monitored and engaged with MissionAD clinical sites to provide support through collegial discussions to maximize the efficiency of the preconsent recruitment phase. RESULTS: The CTF significantly improved cognitive screening efficiency in the MissionAD program, with a 24% decline in cognitive SF rate for the sites that the CTF contacted. The study-wide 11.5% reduction in cognitive SF rates were likely further driven by wider country-level initiatives in which CTF members held CTF-specific Investigator meetings with the recruitment staff, speaking to all sites on a country level regardless of their recruitment performance. CONCLUSIONS: The establishment of a CTF to support efficient cognitive screening is highly recommended for future Alzheimer disease studies. Additional benefits included improved site relationships, increased engagement in MissionAD and access to a group of cognitive experts for consulting, with a focus on achieving more efficient trial recruitment.

Identification of Leukocyte Surface P2X7 as a Biomarker Associated with Alzheimer's Disease.

Alzheimer's disease (AD) has shown altered immune responses in the periphery. We studied P2X7 (a proinflammatory receptor and a scavenger receptor) and two integrins, CD11b and CD11c, on the surface of circulating leukocytes and analysed their associations with Aß-PET, brain atrophy, neuropsychological assessments, and cerebrospinal fluid (CSF) biomarkers. Total 287 age-matched, sex-balanced participants were recruited in a discovery cohort and two validation cohorts through the AIBL study and studied using tri-colour flow cytometry. Our results demonstrated reduced expressions of P2X7, CD11b, and CD11c on leukocytes, particularly monocytes, in Aß +ve cases compared with Aß -ve controls. P2X7 and integrin downregulation was observed at pre-clinical stage of AD and stayed low throughout disease course. We further constructed a polygenic risk score (PRS) model based on 12 P2RX7 risk alleles to assess the genetic impact on P2X7 function in AIBL and ADNI cohorts. No significant association was identified between the P2RX7 gene and AD, indicating that P2X7 downregulation in AD is likely caused by environmental changes rather than genetic factors. In conclusion, the downregulation of P2X7 and integrins at pre-clinical stage of AD indicates altered pro-inflammatory responses, phagocytic functions, and migrating capabilities of circulating monocytes in early AD pathogenesis. Our study not only improves our understanding of peripheral immune involvement in early stage of AD but also provides more insights into novel biomarker development, diagnosis, and prognosis of AD.

Undetected Neurodegenerative Disease Biases Estimates of Cognitive Change in Older Adults.

Neurodegenerative disease is highly prevalent among older adults and, if undetected, may obscure estimates of cognitive change among aging samples. Our aim in this study was to determine the nature and magnitude of cognitive change in the absence of common neuropathologic markers of neurodegenerative disease. Cognitively normal older adults (ages 65-89 years, N = 199) were classified as normal or abnormal using neuroimaging and cerebrospinal-fluid biomarkers of ß-amyloid, tau, and neurodegeneration. When cognitive change was modeled without accounting for biomarker status, significant decline was evident for semantic memory, processing speed, and working memory. However, after adjusting for biomarker status, we found that the rate of change was attenuated and that the biomarker-normal group demonstrated no decline for any cognitive domain. These results indicate that estimates of cognitive change in otherwise healthy older adults will be biased toward decline when the presence of early neurodegenerative disease is not accounted for.

Acute neuroimmune stimulation impairs verbal memory in adults: A PET brain imaging study.

Psychiatric and neurologic disorders are often characterized by both neuroinflammation and cognitive dysfunction. To date, however, the relationship between neuroinflammation and cognitive dysfunction remains understudied in humans. Preclinical research indicates that experimental induction of neuroinflammation reliably impairs memory processes. In this paradigm development study, we translated those robust preclinical findings to humans using positron emission tomography (PET) imaging with [11C]PBR28, a marker of microglia, and lipopolysaccharide (LPS), a potent neuroimmune stimulus. In a sample of 18 healthy adults, we extended our previous findings that LPS administration increased whole-brain [11C]PBR28 availability by 31-50%, demonstrating a robust neuroimmune response (Cohen's ds > 1.6). We now show that LPS specifically impaired verbal learning and recall, hippocampal memory processes, by 11% and 22%, respectively (Cohen's ds > 0.9), but did not alter attention, motor, or executive processes. The LPS-induced increase in [11C]PBR28 binding was correlated with significantly greater decrements in verbal learning performance in the hippocampus (r = -0.52, p = .028), putamen (r = -0.50, p = .04), and thalamus (r = -0.55, p = .02). This experimental paradigm may be useful in investigating mechanistic relationships between neuroinflammatory signaling and cognitive dysfunction in psychiatric and neurologic disorders. It may also provide a direct approach to evaluate medications designed to rescue cognitive deficits associated with neuroinflammatory dysfunction.

Androgen receptor CAG repeat length as a moderator of the relationship between free testosterone levels and cognition.

Age-related decrease in testosterone levels is a potential risk factor for cognitive decline in older men. However, observational studies and clinical trials have reported inconsistent results on the effects of testosterone on individual cognitive domains. Null findings may be attributed to factors that studies have yet to consider. In particular, individual variations in polyglutamine (CAG) length in the androgen receptor (AR) gene could alter androgenic activity in brain regions associated with cognitive processes including memory and executive functions. However, the role of AR CAG repeat length as a moderator of the relationship between testosterone levels and cognition has not been investigated. Therefore, we aimed to examine the relationship between baseline calculated free testosterone (cFT) levels, change in cFT levels over 18 months and CAG repeat length on cognitive performance in memory, executive function, language, attention and processing speed domains. These relationships were examined in 304 cognitively normal older male participants of the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Ageing. In the attention and processing speed domain, a short CAG repeat length appears to exacerbate the effects of low baseline cFT levels that are also lower than expected at follow-up. These results highlight that individual variations in AR CAG repeat length should be considered in future studies and clinical trials that examine the complex relationship between testosterone and cognition.

The impact of the wake maintenance zone on attentional capacity, physiological drowsiness, and subjective task demands during sleep deprivation.

We aimed to investigate the impact of the Wake Maintenance Zone (WMZ) on measures of drowsiness, attention, and subjective performance under rested and sleep deprived conditions. We studied 23 healthy young adults (18 males; mean age = 25.41 ± 5.73 years) during 40 hr of total sleep deprivation under constant routine conditions. Participants completed assessments of physiological drowsiness (EEG-scored slow eye movements and microsleeps), sustained attention (PVT), and subjective task demands every two hours, and four-hourly ocular motor assessment of inhibitory control (inhibition of reflexive saccades on an anti-saccade task). Tests were analyzed relative to dim light melatonin onset (DLMO); the WMZ was defined as the 3 hr prior to DLMO, and the preceding 3 hr window was deemed the pre-WMZ. The WMZ did not mitigate the adverse impact of ~37 hr sleep deprivation on drowsiness, sustained attention, response inhibition, and self-rated concentration and difficulty, relative to rested WMZ performance (~13 hr of wakefulness). Compared to the pre-WMZ, though, the WMZ improved measures of sustained attention, and subjective concentration and task difficulty, during sleep deprivation. Cumulatively, these results expand on previous work by characterizing the beneficial effects of the WMZ on operationally-relevant indices of drowsiness, inhibitory attention control, and self-rated concentration and task difficulty relative to the pre-WMZ during sleep deprivation. These results may inform scheduling safety-critical tasks at more optimal circadian times to improve workplace performance and safety.

Aggregation of Abnormal Memory Scores and Risk of Incident Alzheimer's Disease Dementia: A Measure of Objective Memory Impairment in Amnestic Mild Cognitive Impairment.

OBJECTIVES: The criteria for objective memory impairment in mild cognitive impairment (MCI) are vaguely defined. Aggregating the number of abnormal memory scores (NAMS) is one way to operationalise memory impairment, which we hypothesised would predict progression to Alzheimer's disease (AD) dementia. METHODS: As part of the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing, 896 older adults who did not have dementia were administered a psychometric battery including three neuropsychological tests of memory, yielding 10 indices of memory. We calculated the number of memory scores corresponding to z ≤ -1.5 (i.e., NAMS) for each participant. Incident diagnosis of AD dementia was established by consensus of an expert panel after 3 years. RESULTS: Of the 722 (80.6%) participants who were followed up, 54 (7.5%) developed AD dementia. There was a strong correlation between NAMS and probability of developing AD dementia (r = .91, p = .0003). Each abnormal memory score conferred an additional 9.8% risk of progressing to AD dementia. The area under the receiver operating characteristic curve for NAMS was 0.87 [95% confidence interval (CI) .81-.93, p < .01]. The odds ratio for NAMS was 1.67 (95% CI 1.40-2.01, p < .01) after correcting for age, sex, education, estimated intelligence quotient, subjective memory complaint, Mini-Mental State Exam (MMSE) score and apolipoprotein E ϵ4 status. CONCLUSIONS: Aggregation of abnormal memory scores may be a useful way of operationalising objective memory impairment, predicting incident AD dementia and providing prognostic stratification for individuals with MCI.

MRI signatures of brain age and disease over the lifespan based on a deep brain network and 14 468 individuals worldwide.

Deep learning has emerged as a powerful approach to constructing imaging signatures of normal brain ageing as well as of various neuropathological processes associated with brain diseases. In particular, MRI-derived brain age has been used as a comprehensive biomarker of brain health that can identify both advanced and resilient ageing individuals via deviations from typical brain ageing. Imaging signatures of various brain diseases, including schizophrenia and Alzheimer's disease, have also been identified using machine learning. Prior efforts to derive these indices have been hampered by the need for sophisticated and not easily reproducible processing steps, by insufficiently powered or diversified samples from which typical brain ageing trajectories were derived, and by limited reproducibility across populations and MRI scanners. Herein, we develop and test a sophisticated deep brain network (DeepBrainNet) using a large (n = 11 729) set of MRI scans from a highly diversified cohort spanning different studies, scanners, ages and geographic locations around the world. Tests using both cross-validation and a separate replication cohort of 2739 individuals indicate that DeepBrainNet obtains robust brain-age estimates from these diverse datasets without the need for specialized image data preparation and processing. Furthermore, we show evidence that moderately fit brain ageing models may provide brain age estimates that are most discriminant of individuals with pathologies. This is not unexpected as tightly-fitting brain age models naturally produce brain-age estimates that offer little information beyond age, and loosely fitting models may contain a lot of noise. Our results offer some experimental evidence against commonly pursued tightly-fitting models. We show that the moderately fitting brain age models obtain significantly higher differentiation compared to tightly-fitting models in two of the four disease groups tested. Critically, we demonstrate that leveraging DeepBrainNet, along with transfer learning, allows us to construct more accurate classifiers of several brain diseases, compared to directly training classifiers on patient versus healthy control datasets or using common imaging databases such as ImageNet. We, therefore, derive a domain-specific deep network likely to reduce the need for application-specific adaptation and tuning of generic deep learning networks. We made the DeepBrainNet model freely available to the community for MRI-based evaluation of brain health in the general population and over the lifespan.

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging database (11 studies; 10,216 subjects). METHODS: Three brain signatures were calculated: Brain-age, AD-like neurodegeneration, and white matter hyperintensities (WMHs). Brain Charts measured and displayed the relationships of these signatures to cognition and molecular biomarkers of AD. RESULTS: WMHs were associated with advanced brain aging, AD-like atrophy, poorer cognition, and AD neuropathology in mild cognitive impairment (MCI)/AD and cognitively normal (CN) subjects. High WMH volume was associated with brain aging and cognitive decline occurring in an ≈10-year period in CN subjects. WMHs were associated with doubling the likelihood of amyloid beta (Aß) positivity after age 65. Brain aging, AD-like atrophy, and WMHs were better predictors of cognition than chronological age in MCI/AD. DISCUSSION: A Brain Chart quantifying brain-aging trajectories was established, enabling the systematic evaluation of individuals' brain-aging patterns relative to this large consortium.

Assessing the utility of a virtual-reality neuropsychological test battery, 'CONVIRT', in detecting alcohol-induced cognitive impairment.

New technologies such as virtual reality (VR) and eye-tracking software have paved the way for more sophisticated and ecologically valid measures of cognitive function. Testing the sensitivity and reliability of such measurements in response to acute alcohol intoxication provides a first step in establishing how these measures may operate in relation to cognitive impairments observed post-concussion. Healthy young adults (N = 54, M = 20.65, SD = 2.06, 30 females) completed the CONVIRT test battery (manual simple and choice reaction-time and saccade reaction-time) at three breath alcohol concentration (BrAC) levels: 0.00%T1, 0.05%T2, 0.08%T3. Participants consumed alcoholic beverages at 30-min intervals, with BrAC monitored at 15-min intervals using a breathalyser. All three CONVIRT measures were sensitive to changes in cognitive performance induced by alcohol at BrAC levels at or exceeding 0.05%. A composite measure was also sensitive to alcohol intoxication (Cohen's d = .85 at BrAC = 0.05%; d = 1.20 at BrAC = 0.08%). Strong test-retest reliability was observed (all r < .80), with no gender differences noted. CONVIRT measures were reliable and detected dose-dependent changes in alcohol-induced cognitive impairment. Potentially, the ecologically valid measures may assist in better quantifying the effects of conditions such as concussion, on cognitive performance.