Individual differences in visual evoked potential latency are associated with variance in brain tissue volume in people with multiple sclerosis: An analysis of brain function-structure correlates

Oculomics analysis in multiple sclerosis: Current ophthalmic clinical and imaging biomarkers

Multiple Sclerosis (MS) is a chronic autoimmune demyelinating disease of the central nervous system (CNS) characterized by inflammation, demyelination, and axonal damage. Early recognition and treatment are important for preventing or minimizing the long-term effects of the disease. Current gold standard modalities of diagnosis (e.g., CSF and MRI) are invasive and expensive in nature, warranting alternative methods of detection and screening. Oculomics, the interdisciplinary combination of ophthalmology, genetics, and bioinformatics to study the molecular basis of eye diseases, has seen rapid development through various technologies that detect structural, functional, and visual changes in the eye. Ophthalmic biomarkers (e.g., tear composition, retinal nerve fibre layer thickness, saccadic eye movements) are emerging as promising tools for evaluating MS progression. The eye's structural and embryological similarity to the brain makes it a potentially suitable assessment of neurological and microvascular changes in CNS. In the advent of more powerful machine learning algorithms, oculomics screening modalities such as optical coherence tomography (OCT), eye tracking, and protein analysis become more effective tools aiding in MS diagnosis. Artificial intelligence can analyse larger and more diverse data sets to potentially discover new parameters of pathology for efficiently diagnosing MS before symptom onset. While there is no known cure for MS, the integration of oculomics with current modalities of diagnosis creates a promising future for developing more sensitive, non-invasive, and cost-effective approaches to MS detection and diagnosis.

Peering further into the mind's eye: combining visual evoked potential and optical coherence tomography measures enhances insight into the variance in cognitive functioning in multiple sclerosis

BACKGROUND

Spectral Optical Coherence Tomography (OCT) and Visual Evoked Potentials (VEPs) have both emerged as potentially useful biomarkers of cognitive decline in people with multiple sclerosis (PwMS). Their combined use may provide additional predictive value for identifying disease impact, progression, and remyelination capacity above-and-beyond what is captured using either approach alone.

OBJECTIVE

We examined the relationship between OCT/VEP measures and cognitive functioning in 205 PwMS. OCT measures included Retinal Nerve Fiber Layer Volume (RNFLV), Papillo-Macular Bundle Volume (PBMV), and Macular Volume (MV). VEP measures included latency of the P100, and inter-ocular latency. Cognitive performance was evaluated across seven separate domains of performance, and for overall cognition, using the NeuroTrax computerized testing battery.

RESULTS

Both OCT and VEP measures were significantly correlated with cognitive performance across several domains. Linear regression models that controlled for the influence of visual acuity revealed (1) that reduced MV was significantly predictive of poorer visual-spatial functioning, and (2) that delayed VEP latency was significantly predictive of performance in global cognitive functioning and visual-spatial functioning, after controlling for multiple comparisons. Among PwMS with normal visual acuity, PwMS with a combination of both relatively low MV and delayed VEP latency tended to have poorer performance in the domains of global, executive, and visual-spatial functioning compared to PwMS with both high MV and normal VEP latency.

CONCLUSION

Approaches that combine the use of OCT and VEP measures can enhance insight into underlying factors that contribute to variance in cognitive functioning in PwMS.