Optic disc classification by the Heidelberg Retina Tomograph and by physicians with varying experience of glaucoma

PurposeTo compare the diagnostic accuracy of the Heidelberg Retina Tomograph's (HRT) Moorfields regression analysis (MRA) and glaucoma probability score (GPS) with that of subjective grading of optic disc photographs performed by ophthalmologists with varying experience of glaucoma and by ophthalmology residents.MethodsDigitized disc photographs and HRT images from 97 glaucoma patients with visual field defects and 138 healthy individuals were classified as either within normal limits (WNL), borderline (BL), or outside normal limits (ONL). Sensitivity and specificity were compared for MRA, GPS, and the physicians. Analyses were also made according to disc size and for advanced visual field loss.ResultsForty-five physicians participated. When BL results were regarded as normal, sensitivity was significantly higher (P<5%) for both MRA and GPS compared with the average physician, 87%, 79%, and 62%, respectively. Specificity ranged from 86% for MRA to 97% for general ophthalmologists, but the differences were not significant. In eyes with small discs, sensitivity was 75% for MRA, 60% for the average doctor, and 25% for GPS; in eyes with large discs, sensitivity was 100% for both GPS and MRA, but only 68% for physicians.ConclusionOur results suggest that sensitivity of MRA is superior to that of the average physician, but not that of glaucoma experts. MRA correctly classified all eyes with advanced glaucoma and showed the best sensitivity in eyes with small optic discs

The UK Biobank imaging enhancement of 100,000 participants: rationale, data collection, management and future directions

UK Biobank is a population-based cohort of half a million participants aged 40–69 years recruited between 2006 and 2010. In 2014, UK Biobank started the world’s largest multi-modal imaging study, with the aim of re-inviting 100,000 participants to undergo brain, cardiac and abdominal magnetic resonance imaging, dual-energy X-ray absorptiometry and carotid ultrasound. The combination of large-scale multi-modal imaging with extensive phenotypic and genetic data offers an unprecedented resource for scientists to conduct health-related research. This article provides an in-depth overview of the imaging enhancement, including the data collected, how it is managed and processed, and future direction

Genome-wide analyses reveal a potential role for the <em>MAPT</em>, <em>MOBP</em>, and <em>APOE </em>loci in sporadic frontotemporal dementia

\ua9 2024 The Author(s)Frontotemporal dementia (FTD) is the second most common cause of early-onset dementia after Alzheimer disease (AD). Efforts in the field mainly focus on familial forms of disease (fFTDs), while studies of the genetic etiology of sporadic FTD (sFTD) have been less common. In the current work, we analyzed 4,685 sFTD cases and 15,308 controls looking for common genetic determinants for sFTD. We found a cluster of variants at the MAPT (rs199443; p = 2.5 7 10−12, OR = 1.27) and APOE (rs6857; p = 1.31 7 10−12, OR = 1.27) loci and a candidate locus on chromosome 3 (rs1009966; p = 2.41 7 10−8, OR = 1.16) in the intergenic region between RPSA and MOBP, contributing to increased risk for sFTD through effects on expression and/or splicing in brain cortex of functionally relevant in-cis genes at the MAPT and RPSA-MOBP loci. The association with the MAPT (H1c clade) and RPSA-MOBP loci may suggest common genetic pleiotropy across FTD and progressive supranuclear palsy (PSP) (MAPT and RPSA-MOBP loci) and across FTD, AD, Parkinson disease (PD), and cortico-basal degeneration (CBD) (MAPT locus). Our data also suggest population specificity of the risk signals, with MAPT and APOE loci associations mainly driven by Central/Nordic and Mediterranean Europeans, respectively. This study lays the foundations for future work aimed at further characterizing population-specific features of potential FTD-discriminant APOE haplotype(s) and the functional involvement and contribution of the MAPT H1c haplotype and RPSA-MOBP loci to pathogenesis of sporadic forms of FTD in brain cortex

GMNC risk alleles in individuals with Alzheimer’s disease are associated with cerebrospinal fluid concentrations of proteins involved in neuronal plasticity and blood brain barrier function

Abstract Background GWAS studies showed that cerebrospinal fluid (CSF) levels of total‐tau in Alzheimer’s disease (AD) are associated with genetic variations in GMNC (Cruchaga,2013). GMNC is involved in neural progenitor cell differentiation and regulates the generation of multiciliated ependymal cells (Kyrousi,2015), but the precise role of GMNC in AD pathophysiology remains unclear. We investigated which processes were associated with GMNC risk alleles by studying its associations with CSF levels of 1705 proteins in AD individuals. Method We selected 432 individuals with abnormal CSF amyloid beta 1‐42 levels from the EMIF‐AD multimodality biomarker discovery study and ADNI. We measured 1705 proteins by untargeted mass spectrometry (EMIF‐AD), the Human DiscoveryMAP panel (ADNI) or targeted mass spectroscopy (ADNI). We correlated the number of GMNC rs9877502‐A risk alleles with protein levels in additive models. To characterise proteins associated with GMNC risk alleles, we performed pathway enrichment analyses for Gene Ontology biological processes (GO‐BP) and ChEA transcription factors. Result Average age was 71.2 years. At least one GMNC rs9877502‐A risk allele was present in 60% of the AD individuals. Increasing number of GMNC risk alleles was associated with increased total‐tau, as expected, and with increased levels of 591 other proteins (35% of proteins measured). These proteins were associated with neuronal plasticity related processes (table) and SUZ12 and REST transcription factors, which are neuronal transcription repressors (all p‐FDR corrected>6.34e‐18). GMNC risk alleles were further associated with decreased levels of 105 proteins, including 72 proteins associated with blood brain barrier (BBB) permeability. Conclusion Within AD individuals, GMNC risk alleles are not only associated with increased total‐tau levels but also with increased levels of neuronal plasticity associated proteins. We also found that GMNC risk allele carriers may have less BBB dysfunction than non‐carriers. Further studies are needed to clarify the association of GMNC with neuronal plasticity and BBB function in AD. References Cruchaga, Neuron 2013: 256‐268. Kyrousi, C. , Development 2015: 3661‐3674

Uncovering Social States in Healthy and Clinical Populations Using Digital Phenotyping and Hidden Markov Models: Observational Study

Abstract Background Brain related disorders are characterized by observable behavioral symptoms, for example social withdrawal. Smartphones can passively collect behavioral data reflecting digital activities, such as communication app usage and calls. This data is collected objectively in real time, avoiding recall bias, and may therefore be a useful tool for measuring behaviors related to social functioning. Despite promising clinical utility, analyzing smartphone data is challenging as datasets often include a range of missingness-prone temporal features. Objective Hidden Markov Models (HMMs) provide interpretable, lower-dimensional temporal representations of data, allowing missingness. We aimed to investigate the HMM as a method for modeling smartphone time series data. Methods We applied an HMM to an aggregate dataset of smartphone measures designed to assess phone-related social functioning in healthy controls (HCs), participants with schizophrenia, Alzheimer’s disease (AD) and memory complaints. We trained the HMM on a subset of HCs (n=91) and selected a model with socially “active” and “inactive” states, then generated hidden state sequences per participant and calculated their “total dwell time”, i.e. the percentage of time spent in the socially active state. Linear regression models were used to compare the total dwell time to social and clinical measures in a subset of participants with available measures, and logistic regression was used to compare total dwell times between diagnostic groups and HCs. We primarily report results from a two-state HMM but also verified results in HMMs with more hidden states, and trained on the whole participant dataset. Results We identified lower total dwell times in AD (n=26) versus withheld HCs (n=156) (odds ratio=0.95, FDR corrected P <.001), as well as in participants with memory complaints (n=57) (odds ratio=0.97, FDR corrected P =0.004). The AD result was very robust across HMM variations, whilst the memory complaints result was less robust. We also observed an interaction between AD group and total dwell time when predicting social functioning (FDR corrected P =0.02). No significant relationships regarding total dwell time were identified for participants with schizophrenia (n=18). Conclusions We found the HMM to be a practical, interpretable method for digital phenotyping analysis, providing an objective phenotype that is a possible indicator of social functioning