Relationships between retinal layer thickness and brain volumes in the UK Biobank cohort

Abstract

Background and purpose Current methods to diagnose neurodegenerative diseases are costly and invasive. Retinal neuroanatomy may be a biomarker for more neurodegenerative processes and can be quantified in vivo using optical coherence tomography (OCT), which is inexpensive and noninvasive. We examined the association of neuroretinal morphology with brain MRI image‐derived phenotypes (IDPs) in a large cohort of healthy older people. Methods UK Biobank participants aged 40 to 69 years old underwent comprehensive examinations including ophthalmic and brain imaging assessments. Macular retinal nerve fibre layer (mRNFL), macular ganglion cell‐inner plexiform layer (mGCIPL), macular ganglion cell complex (mGCC) and total macular thicknesses were obtained from OCT. Magnetic resonance imaging (MRI) IDPs assessed included total brain, grey matter, white matter and hippocampal volume. Multivariable linear regression models were used to evaluate associations between retinal layers thickness and brain MRI IDPs, adjusting for demographic factors and vascular risk factors. Results A total of 2131 participants (mean age 55 years; 51% women) with both gradable OCT images and brain imaging assessments were included. In multivariable regression analysis, thinner mGCIPL, mGCC and total macular thickness were all significantly associated with smaller total brain (p < 0.001), grey matter and white matter volume (p < 0.01), and grey matter volume in the occipital pole (p < 0.05). Thinner mGCC and total macular thicknesses were associated with smaller hippocampal volume (p < 0.02). No association was found between mRNFL and the MRI IDPs. Conclusions Markers of retinal neurodegeneration are associated with smaller brain volumes. Our findings suggest that retinal structure may be a biomarker providing information about important brain structure in healthy older adults.

Alterations of optic tract and retinal structure in patients after thalamic stroke

“…These reports suggest retinal neurodegeneration reflects cerebral neurodegeneration, and this mechanism may occur simultaneously. Importantly, prior reports (Ong et al, 2015;Mutlu et al, 2017;Chua et al, 2021) suggested that the retinal sublayer thicknesses reflect the cerebral microstructure (white matter and gray matter microstructure). The brain and retina share many characteristics, including similar microvasculature, embryology, and precise neuronal cell layers; axons from the optic nerve form a direct link, through the optic head, between the retina and the brain, thus, it is suggested that damage in the brain is associated with retinal thinning (especially for peripapillary RNFL and macular GCL) (Cabrera DeBuc et al, 2017;Kwapong et al, 2018;Mutlu et al, 2018).…”

Associations of Alcohol Consumption and Smoking With Disease Risk and Neurodegeneration in Individuals With Multiple Sclerosis in the United Kingdom

“…Optical coherence tomography (OCT) provides fast, noninvasive retinal imaging. 15 Thickness of the macular ganglion cell and inner plexiform layer (mGCIPL) correlates with brain volume measures in the general population 16 and in patients with MS. 14 Retinal atrophy, independent of damage inflicted by optic neuritis, occurs from the early stages of disease 15,17 and correlates with MS disability scores. 18,19 Because smoking and alcohol consumption are correlated behaviors, 20,21 it is difficult to disentangle their respective effects.…”

Retinal Neurovascular Impairment in Non-diabetic and Non-dialytic Chronic Kidney Disease Patients

“…As an extension of the brain and sharing the same embryological origin with the CNS. Chua et al (2020) , Kashani et al (2021) , the retina is widely regarded as an accessible source for studying neurodegenerative and vascular injury processes occurring in the CNS ( Hart et al, 2016 ; Mutlu et al, 2018 ). Consistently, there has also been intense interest in using retinal imaging technology to understand, diagnose, and monitor neurological diseases ( Kashani et al, 2021 ).…”