Kane, K. | Search bioRxiv

bioRxiv2026

Multiomic analysis of non-glaucomatous human trabecular meshwork cells.

Glaucoma is an irreversible blinding disease that affects millions of individuals worldwide. Elevated intraocular pressure (IOP), regulated by the trabecular meshwork (TM) in the anterior eye, is the only modifiable risk factor. Human TM cells can be cultured from donor eyes, providing a precious resource for studying factors that induce or prevent glaucoma. The goal of this study was to produce datasets that define the molecular profile of human non-glaucomatous TM cells. Using 18 human TM cell strains cultured from non-glaucomatous individuals deposited from seven laboratories in the USA and UK, this study used transcriptomic, proteomic, lipidomic, and metabolomic analyses to characterize the molecular content of TM cells. The data herein provides the most comprehensive multiomic analyses of human TM cells to date and will be a useful resource for researchers and clinicians in the TM and glaucoma fields.

cell biology↗

bioRxiv2023

Uncovering and mitigating bias in large, automated MRI analyses of brain development

Large, population-based MRI studies of adolescents promise transformational insights into neurodevelopment and mental illness risk 1, 2. However, MRI studies of youth are especially susceptible to motion and other artifacts 3, 4. These artifacts may go undetected by automated quality control (QC) methods that are preferred in high-throughput imaging studies, 5 and can potentially introduce non-random noise into clinical association analyses. Here we demonstrate bias in structural MRI analyses of children due to inclusion of lower quality images, as identified through rigorous visual quality control of 11,263 T1 MRI scans obtained at age 9-10 through the Adolescent Brain Cognitive Development (ABCD) Study6. Compared to the best-rated images (44.9% of the sample), lower-quality images generally associated with decreased cortical thickness and increased cortical surface area measures (Cohens d 0.14-2.84). Variable image quality led to counterintuitive patterns in analyses that associated structural MRI and clinical measures, as inclusion of lower-quality scans altered apparent effect sizes in ways that increased risk for both false positives and negatives. Quality-related biases were partially mitigated by controlling for surface hole number, an automated index of topological complexity that differentiated lower-quality scans with good specificity at Baseline (0.81-0.93) and in 1,000 Year 2 scans (0.88-1.00). However, even among the highest-rated images, subtle topological errors occurred during image preprocessing, and their correction through manual edits significantly and reproducibly changed thickness measurements across much of the cortex (d 0.15-0.92). These findings demonstrate that inadequate QC of youth structural MRI scans can undermine advantages of large sample size to detect meaningful associations.

neuroscience↗