SpatialData: an open and universal data framework for spatial omics.

Spatially resolved omics technologies are transforming our understanding of biological tissues. However, the handling of uni- and multimodal spatial omics datasets remains a challenge owing to large data volumes, heterogeneity of data types and the lack of flexible, spatially aware data structures. Here we introduce SpatialData, a framework that establishes a unified and extensible multiplatform file-format, lazy representation of larger-than-memory data, transformations and alignment to common coordinate systems. SpatialData facilitates spatial annotations and cross-modal aggregation and analysis, the utility of which is illustrated in the context of multiple vignettes, including integrative analysis on a multimodal Xenium and Visium breast cancer study.

High-throughput anaerobic screening for identifying compounds acting against gut bacteria in monocultures or communities.

The human gut microbiome is a key contributor to health, and its perturbations are linked to many diseases. Small-molecule xenobiotics such as drugs, chemical pollutants and food additives can alter the microbiota composition and are now recognized as one of the main factors underlying microbiome diversity. Mapping the effects of such compounds on the gut microbiome is challenging because of the complexity of the community, anaerobic growth requirements of individual species and the large number of interactions that need to be quantitatively assessed. High-throughput screening setups offer a promising solution for probing the direct inhibitory effects of hundreds of xenobiotics on tens of anaerobic gut bacteria. When automated, such assays enable the cost-effective investigation of a wide range of compound-microbe combinations. We have developed an experimental setup and protocol that enables testing of up to 5,000 compounds on a target gut species under strict anaerobic conditions within 5 d. In addition, with minor modifications to the protocol, drug effects can be tested on microbial communities either assembled from isolates or obtained from stool samples. Experience in working in an anaerobic chamber, especially in performing delicate work with thick chamber gloves, is required for implementing this protocol. We anticipate that this protocol will accelerate the study of interactions between small molecules and the gut microbiome and provide a deeper understanding of this microbial ecosystem, which is intimately intertwined with human health.

Progression, reliability, predicting parameters and sample size calculations for quantitative fundus autofluorescence measures in ABCA4-related retinopathy.

BACKGROUND/AIMS: To investigate the progression of quantitative autofluorescence (qAF) measures and the potential as clinical trial endpoint in ABCA4-related retinopathy. METHODS: In this longitudinal monocentre study, 64 patients with ABCA4-related retinopathy (age (mean±SD), 34.84±16.36 years) underwent serial retinal imaging, including optical coherence tomography (OCT) and qAF (488 nm excitation) imaging using a modified confocal scanning laser ophthalmoscope with a mean (±SD) review period of 20.32±10.90 months. A group of 110 healthy subjects served as controls. Retest variability, changes of qAF measures over time and its association with genotype and phenotype were analysed. Furthermore, individual prognostic feature importance was assessed, and sample size calculations for future interventional trials were performed. RESULTS: Compared with controls, qAF levels of patients were significantly elevated. The test-retest reliability revealed a 95% coefficient of repeatability of 20.37. During the observation time, young patients, patients with a mild phenotype (morphological and functional) and patients with mild mutations showed an absolute and relative increase in qAF values, while patients with advanced disease manifestation (morphological and functional), and homozygous mutations at adulthood revealed a decrease in qAF. Considering these parameters, required sample size and study duration could significantly be reduced. CONCLUSION: Under standardised settings with elaborated conditions towards operators and analysis to counterbalance variability, qAF imaging might be reliable, suitable for quantifying disease progression and constitutes a potential clinical surrogate marker in ABCA4-related retinopathy. Trial design based on patients' baseline characteristics and genotype has the potential to provide benefits regarding required cohort size and absolute number of visits.

Foveal structure and visual function in nanophthalmos and posterior microphthalmos.

BACKGROUND/AIMS: The reason for visual impairment in patients with nanophthalmos and posterior microphthalmos is not completely understood. Therefore, this study aims to investigate foveal structure, and the impact of demographic, clinical and imaging parameters on best-corrected visual acuity (BCVA) in these conditions. METHODS: Sixty-two eyes of 33 patients with nanophthalmos (n=40) or posterior microphthalmos (n=22), and 114 eyes of healthy controls with high-resolution retinal imaging including spectral-domain or swept-source optical coherence tomography images were included in this cross-sectional case-control study. Foveal retinal layer thickness was determined by two independent readers. A mixed-effect model was used to perform structure-function correlations and predict the BCVA based on subject-specific variables. RESULTS: Most patients (28/33) had altered foveal structure associated with loss of foveal avascular zone and impaired BCVA. However, widening of outer nuclear layer, lengthening of photoreceptor outer segments, normal distribution of macular pigment and presence of Henle fibres were consistently found. Apart from the presence of choroidal effusion, which had significant impact on BCVA, the features age, refractive error, axial length and retinal layer thickness at the foveal centre explained 61.7% of the variability of BCVA. CONCLUSION: This study demonstrates that choroidal effusion, age, refractive error, axial length and retinal layer thickness are responsible for the majority of interindividual variability of BCVA as well as the morphological foveal heterogeneity in patients with nanophthalmos or posterior microphthalmos. This might give further insights into the physiology of foveal development and the process of emmetropisation, and support clinicians in the assessment of these disease entities.

Reliability of Retinal Pathology Quantification in Age-Related Macular Degeneration: Implications for Clinical Trials and Machine Learning Applications.

Purpose: To investigate the interreader agreement for grading of retinal alterations in age-related macular degeneration (AMD) using a reading center setting. Methods: In this cross-sectional case series, spectral-domain optical coherence tomography (OCT; Topcon 3D OCT, Tokyo, Japan) scans of 112 eyes of 112 patients with neovascular AMD (56 treatment naive, 56 after three anti-vascular endothelial growth factor injections) were analyzed by four independent readers. Imaging features specific for AMD were annotated using a novel custom-built annotation platform. Dice score, Bland-Altman plots, coefficients of repeatability, coefficients of variation, and intraclass correlation coefficients were assessed. Results: Loss of ellipsoid zone, pigment epithelium detachment, subretinal fluid, and drusen were the most abundant features in our cohort. Subretinal fluid, intraretinal fluid, hypertransmission, descent of the outer plexiform layer, and pigment epithelium detachment showed highest interreader agreement, while detection and measures of loss of ellipsoid zone and retinal pigment epithelium were more variable. The agreement on the size and location of the respective annotation was more consistent throughout all features. Conclusions: The interreader agreement depended on the respective OCT-based feature. A selection of reliable features might provide suitable surrogate markers for disease progression and possible treatment effects focusing on different disease stages. Translational Relevance: This might give opportunities for a more time- and cost-effective patient assessment and improved decision making as well as have implications for clinical trials and training machine learning algorithms.

Inferred retinal sensitivity in recessive Stargardt disease using machine learning.

Spatially-resolved retinal function can be measured by psychophysical testing like fundus-controlled perimetry (FCP or 'microperimetry'). It may serve as a performance outcome measure in emerging interventional clinical trials for macular diseases as requested by regulatory agencies. As FCP constitute laborious examinations, we have evaluated a machine-learning-based approach to predict spatially-resolved retinal function ('inferred sensitivity') based on microstructural imaging (obtained by spectral domain optical coherence tomography) and patient data in recessive Stargardt disease. Using nested cross-validation, prediction accuracies of (mean absolute error, MAE [95% CI]) 4.74 dB [4.48-4.99] were achieved. After additional inclusion of limited FCP data, the latter reached 3.89 dB [3.67-4.10] comparable to the test-retest MAE estimate of 3.51 dB [3.11-3.91]. Analysis of the permutation importance revealed, that the IS&OS and RPE thickness were the most important features for the prediction of retinal sensitivity. 'Inferred sensitivity', herein, enables to accurately estimate differential effects of retinal microstructure on spatially-resolved function in Stargardt disease, and might be used as quasi-functional surrogate marker for a refined and time-efficient investigation of possible functionally relevant treatment effects or disease progression.

PROGRESSION OF ABCA4-RELATED RETINOPATHY: Prognostic value of demographic, functional, genetic, and imaging parameters.

PURPOSE: To investigate the prognostic value of demographic, functional, genetic, and imaging parameters on retinal pigment epithelium atrophy progression secondary to ABCA4-related retinopathy. METHODS: Patients with retinal pigment epithelium atrophy secondary to ABCA4-related retinopathy were examined longitudinally with fundus autofluorescence imaging. Lesion area, perimeter, circularity, caliper diameters, and focality of areas with definitely decreased autofluorescence were determined. A model was used to predict the lesion enlargement rate based on baseline variables. Sample size calculations were performed to model the power in a simulated interventional study. RESULTS: Sixty-eight eyes of 37 patients (age range, 14-78 years) with a follow-up time of 10 to 100 months were included. The mean annual progression of retinal pigment epithelium atrophy was 0.89 mm. The number of atrophic areas, the retina-wide functional impairment, and the age-of-onset category constituted significant predictors for future retinal pigment epithelium atrophy growth, explaining 25.7% of the variability. By extension of a simulated study length and/or specific patient preselection based on these baseline characteristics, the required sample size could significantly be reduced. CONCLUSION: Trial design based on specific shape-descriptive factors and patients' baseline characteristics and the adaption of the trial duration may provide potential benefits in required cohort size and absolute number of visits.

Prediction of Function in ABCA4-Related Retinopathy Using Ensemble Machine Learning.

Full-field electroretinogram (ERG) and best corrected visual acuity (BCVA) measures have been shown to have prognostic value for recessive Stargardt disease (also called "ABCA4-related retinopathy"). These functional tests may serve as a performance-outcome-measure (PerfO) in emerging interventional clinical trials, but utility is limited by variability and patient burden. To address these limitations, an ensemble machine-learning-based approach was evaluated to differentiate patients from controls, and predict disease categories depending on ERG ('inferred ERG') and visual impairment ('inferred visual impairment') as well as BCVA values ('inferred BCVA') based on microstructural imaging (utilizing spectral-domain optical coherence tomography) and patient data. The accuracy for 'inferred ERG' and 'inferred visual impairment' was up to 99.53 ± 1.02%. Prediction of BCVA values ('inferred BCVA') achieved a precision of ±0.3LogMAR in up to 85.31% of eyes. Analysis of the permutation importance revealed that foveal status was the most important feature for BCVA prediction, while the thickness of outer nuclear layer and photoreceptor inner and outer segments as well as age of onset highly ranked for all predictions. 'Inferred ERG', 'inferred visual impairment', and 'inferred BCVA', herein, represent accurate estimates of differential functional effects of retinal microstructure, and offer quasi-functional parameters with the potential for a refined patient assessment, and investigation of potential future treatment effects or disease progression.

Progression of Retinopathy Secondary to Maternally Inherited Diabetes and Deafness - Evaluation of Predicting Parameters.

PURPOSE: To investigate the prognostic value of demographic, functional, and imaging parameters on retinal pigment epithelium (RPE) atrophy progression secondary to maternally inherited diabetes and deafness (MIDD) and to evaluate the application of these factors in clinical trial design. DESIGN: Retrospective observational case series. METHODS: Thirty-five eyes of 20 patients (age range, 24.9-75.9 years) with genetically proven MIDD and demarcated RPE atrophy on serial fundus autofluorescence (AF) images were included. Lesion size and shape-descriptive parameters were longitudinally determined by 2 independent readers. A linear mixed-effect model was used to predict the lesion enlargement rate based on baseline variables. Sample size calculations were performed to model the power in a simulated interventional study. RESULTS: The mean follow-up time was 4.27 years. The mean progression rate of RPE atrophy was 2.33 mm2/year, revealing a dependence on baseline lesion size (+0.04 [0.02-0.07] mm2/year/mm2, P < .001), which was absent after square root transformation. The fovea was preserved in the majority of patients during the observation time. In the case of foveal involvement, the loss of visual acuity lagged behind central RPE atrophy in AF images. Sex, age, and number of atrophic foci predicted future progression rates with a cross-validated mean absolute error of 0.13 mm/year and to reduce the required sample size for simulated interventional trials. CONCLUSIONS: Progressive RPE atrophy could be traced in all eyes using AF imaging. Shape-descriptive factors and patients' baseline characteristics had significant prognostic value, guiding appropriate subject selection and sample size in future interventional trial design.