## 2 Methods
### Ophthalmic Examination and Optical Coherence Tomography (OCT)  
A detailed ophthalmic examination was conducted in all participants, including corrected distance visual acuity (logarithm of the minimum angle of resolution; (logMAR)) and intraocular pressure (mmHg). Detailed anterior segment and fundus examinations were performed, and wide-field colour fundus images were taken using a laser scanning ophthalmoscope (Optomap; Optos Plc., Dunfermline, UK). Examination of the microvasculature and retinal thickness of each layer of the macula was performed using a Spectralis OCT (Spectralis HRA + OCT; Heidelberg Engineering, Heidelberg, Germany). All participants underwent three OCT scans on the same day as their cognitive evaluation. A peripapillary ring (SD-OCT RNFL diameter, 3.50 mm) and posterior-pole scan were conducted. All images fulfilled the spell-out OSCAR-IB criteria [17], with an enhanced automatic real-time functioning (ART) level of 25. Spectralis OCT software (Spectralis HRA + OCT; Heidelberg Engineering, Heidelberg, Germany, Version 4.0) allowed for automatic segmentation with options for manual adjustment and identification of the upper and lower RNFL limits to minimize artefacts such as defocus, shadows, eye movement and blinking, and calculate the average RNFL thickness. A Heidelberg Spectralis Axonal exam report was generatedand viewed following each participant's scan. Peripapillary RNFL thickness global retinal nerve fibre layer (gRNFL), as well as sectoral RNFL thicknesses, including nasal, temporal, temporal inferior, temporal superior, nasal inferior, and nasal superior quadrants, were measured for analysis in this study. Non-invasive vascular imaging was conducted using the Spectralis HRA + OCT OCT-A module to examine the retinal microvasculature covering a macular area of 6 \(\times\) 6 mm centered on the fovea for the superficial capillary plexus (SCP) and deep capillary plexus (DCP) of the retina. As Spectralis does not automate density values, vessel density analysis was performed using ImageJ software 1.53o (National Institutes of Health, Bethesda, MD, USA) with a method adapted from [PERSON] et al. [10; 18]. The macula OCTA image was imported into ImageJ software, 1.53o where it was binarised and skeletonised. FAZ features were measured with increased magnification. The border of the FAZ was manually traced using the polygon selection tool. Measurable features including area (mm\({}^{2}\)), perimeter (mm), and circularity were defined using the set measurements of shape descriptor features within the software 1.53o. Circularity is defined as an index such that closer to 1 indicates more circular in shape and closer to 0 indicates greater irregularity. The projection artefacts of the superficial layer were removed in the deep-layer images using built-in software 1.53o native to the Spectralis HRA + OCT. All images were exported into the ImageJ 1.50 software to measure the FAZ area and VD. We manually outlined the FAZ using the polygon selection tool and calculated the VD of the 6 \(\times\) 6 mm macula, except the FAZ (central foveal 0.5 mm radius area). The OCT-A data were collected and evaluated independently by two researchers, and the average values used for the statistical evaluation. The analysis of the FAZ and VD in ImageJ were conducted blindly to avoid potential bias by researchers who were masked to the APOE genotype and all clinical measures and had no knowledge of the results of MRI imaging. The manual scans were also reviewed by two researchers before exporting from the instrument. Eyes with retinal diseases (e.g., age-related macular degeneration, diabetic retinopathy, epiretinal membrane, and macular hole), optic nerve diseases (e.g., glaucoma, and ischemic optic neuropathy), and significant media opacity with poor quality (signal strength \(<\) 70 on OCTA and \(<\)25 on OCT) were excluded from the analyses (Figures 1 and 2). Retinal capillary density maps derived from OCTA images for an apolipoprotein E (APOE) \(\epsilon\)4 carrier and non-carrier.