Brain-age prediction: Systematic evaluation of site effects, and sample age range and size.

Structural neuroimaging data have been used to compute an estimate of the biological age of the brain (brain-age) which has been associated with other biologically and behaviorally meaningful measures of brain development and aging. The ongoing research interest in brain-age has highlighted the need for robust and publicly available brain-age models pre-trained on data from large samples of healthy individuals. To address this need we have previously released a developmental brain-age model. Here we expand this work to develop, empirically validate, and disseminate a pre-trained brain-age model to cover most of the human lifespan. To achieve this, we selected the best-performing model after systematically examining the impact of seven site harmonization strategies, age range, and sample size on brain-age prediction in a discovery sample of brain morphometric measures from 35,683 healthy individuals (age range: 5-90 years; 53.59% female). The pre-trained models were tested for cross-dataset generalizability in an independent sample comprising 2101 healthy individuals (age range: 8-80 years; 55.35% female) and for longitudinal consistency in a further sample comprising 377 healthy individuals (age range: 9-25 years; 49.87% female). This empirical examination yielded the following findings: (1) the accuracy of age prediction from morphometry data was higher when no site harmonization was applied; (2) dividing the discovery sample into two age-bins (5-40 and 40-90 years) provided a better balance between model accuracy and explained age variance than other alternatives; (3) model accuracy for brain-age prediction plateaued at a sample size exceeding 1600 participants. These findings have been incorporated into CentileBrain (https://centilebrain.org/#/brainAGE2), an open-science, web-based platform for individualized neuroimaging metrics.

The protocol for an observational Australian cohort study of CADASIL: The AusCADASIL study.

Introduction: Cerebral Autosomal Dominant Arteriopathy with Subcortical Infarcts and Leukoencephalopathy (CADASIL) is a rare genetic condition with a broad phenotypic presentation. This study aims to establish the first Australian cohort of individuals affected by CADASIL (AusCADASIL) and examine its clinical features and longitudinal course, and to investigate neuroimaging and blood biomarkers to assist in early diagnosis and identify disease progression. Methods: Participants will be recruited from six study centres across Australia for an observational study of CADASIL. We aim to recruit 150 participants with diagnosed CADASIL, family history of CADASIL or suspected CADASIL symptoms, and 150 cognitively normal NOTCH3 negative individuals as controls. Participants will complete: 1) online questionnaires on medical and family history, mental health, and wellbeing; 2) neuropsychological evaluation; 3) neurological examination and brain MRI; 4) ocular examination and 5) blood sample donation. Participants will have annual follow-up for 4 years to assess their progression and will be asked to invite a study partner to corroborate their self-reported cognitive and functional abilities.Primary outcomes include cognitive function and neuroimaging abnormalities. Secondary outcomes include investigation of genetics and blood and ocular biomarkers. Data from the cohort will contribute to an international consortium, and cohort participants will be invited to access future treatment/health intervention trials. Discussion: AusCADASIL will be the first study of an Australian cohort of individuals with CADASIL. The study will identify common pathogenic variants in this cohort, and characterise the pattern of clinical presentation and longitudinal progression, including imaging features, blood and ocular biomarkers and cognitive profile.

Multi-omics and pathway analyses of genome-wide associations implicate regulation and immunity in verbal declarative memory performance.

BACKGROUND: Uncovering the functional relevance underlying verbal declarative memory (VDM) genome-wide association study (GWAS) results may facilitate the development of interventions to reduce age-related memory decline and dementia. METHODS: We performed multi-omics and pathway enrichment analyses of paragraph (PAR-dr) and word list (WL-dr) delayed recall GWAS from 29,076 older non-demented individuals of European descent. We assessed the relationship between single-variant associations and expression quantitative trait loci (eQTLs) in 44 tissues and methylation quantitative trait loci (meQTLs) in the hippocampus. We determined the relationship between gene associations and transcript levels in 53 tissues, annotation as immune genes, and regulation by transcription factors (TFs) and microRNAs. To identify significant pathways, gene set enrichment was tested in each cohort and meta-analyzed across cohorts. Analyses of differential expression in brain tissues were conducted for pathway component genes. RESULTS: The single-variant associations of VDM showed significant linkage disequilibrium (LD) with eQTLs across all tissues and meQTLs within the hippocampus. Stronger WL-dr gene associations correlated with reduced expression in four brain tissues, including the hippocampus. More robust PAR-dr and/or WL-dr gene associations were intricately linked with immunity and were influenced by 31 TFs and 2 microRNAs. Six pathways, including type I diabetes, exhibited significant associations with both PAR-dr and WL-dr. These pathways included fifteen MHC genes intricately linked to VDM performance, showing diverse expression patterns based on cognitive status in brain tissues. CONCLUSIONS: VDM genetic associations influence expression regulation via eQTLs and meQTLs. The involvement of TFs, microRNAs, MHC genes, and immune-related pathways contributes to VDM performance in older individuals.

Examining the validity of the Mini-Mental State Examination (MMSE) and its domains using network analysis.

BACKGROUND: The Mini-Mental State Examination (MMSE) is the most widely used standardised screener for impairments across a range of cognitive domains. However, the degree to which its domains (orientation, registration, attention, recall, language, and visuospatial) capture cognitive functioning measured using standardised neuropsychological tests is unclear. METHOD: A longitudinal research design with four biannual assessments over a 6-year period was used with an initial sample of 1037 older adults (aged above 70 years). Participants completed MMSE and neuropsychological tests at each assessment. Network analysis was utilised to investigate unique associations among the MMSE and its domains and neuropsychological test performance at each time point. RESULTS: The total MMSE and two of its domains, language and recall, were associated with neuropsychological memory performance. The MMSE orientation, registration and visuospatial domains did not have any unique associations with neuropsychological performance. No stable internal interconnections between MMSE domains were found over time. The association of total MMSE as well as its recall domain with neuropsychological memory performance remained very similar over the 6-year period. CONCLUSIONS: The present study adds evidence to the validity of the MMSE and supports the clinical usage of the MMSE, whereby the total score is used for screening patients with or without cognitive impairments, with repeated administration to monitor cognitive changes over time, to inform intervention. However, the tool is not able to diagnose the cases for changes in specific cognitive domains and as such, should not replace a complete neuropsychological assessment.