Alzheimer’s disease (AD) is a neurodegenerative disease that affects the central nervous system and is the most common cause of dementia in the world (Cunha et al., 2016). This neurodegenerative disease is histologically characterized by the accumulation of beta-amyloid (Aβ) and intracellular neurofibrillary tangles of hyperphosphorylated tau protein (pTau) (Walker, 2020). The main risk factor for developing AD is the age (Capizzano et al., 2004; Chen et al., 2009), following this, two of the genetic risk factors are: having a first-degree family history of AD and carrying at least one ε4 allele for the ApoE gene (Sano et al., 1991; Donix et al., 2010). These subjects with a parent with AD have a 4 to 10 times higher risk of developing the disease (Huang et al., 2004). Some of these high-risk individuals may develop the pathology over time. Therefore, it could be considered that these subjects may be in a preclinical phase, since the first biochemical changes occur even 20 years before cognitive decline appears.

AD is a continuum because it is a progressive neurological disorder that develops gradually over time. This continuum begins when the subject is cognitively healthy, although there are molecular changes that already foreshadow the progression toward cognitive decline, to a phase in which the patient has cognitive impairment that cannot be independent in their daily life (Alzheimer’s association, 2020; Alzheimer’s Association, 2022). MCI can be considered as the stage of cognitive status prior to AD (Sperling et al., 2011). MCI is characterized by impairment of cognitive functions in the performance of everyday activities, that is greater than what would be expected for a person’s age and education level, but not severe enough to interfere significantly with daily activities or independent functioning (Sanford, 2017; Alzheimer’s Association, 2022). When dementia is established current criteria describe three stages: mild AD, moderate AD and severe AD (McKhann et al., 2011; Alzheimer’s Association, 2022).

The retina is a projection of the brain, and it is known that in some brain neurodegenerative diseases there are retinal changes (Ramirez et al., 2017; Colligris et al., 2018; Salobrar-García et al., 2019; Rojas et al., 2020a,b; Alves et al., 2023). In recent decades, numerous studies have investigated retinal alterations in AD, observing that there is neuronal death that first affects the macular region in early stages of the disease, and later, as AD progresses, it affects the peripapillary region of the retina (Blanks et al., 1989; Garcia-Martin et al., 2014; Salobrar-García et al., 2015, 2019; Koronyo et al., 2017). These structural changes are often accompanied by functional visual changes, which have been described in patients with MCI and AD compared to healthy subjects, reporting decreased visual acuity (VA) and contrast sensitivity (CS), as well as poorer colour perception and impaired visuospatial integration (Sadun et al., 1987; Risacher et al., 2013, 2020; Salobrar-García et al., 2015, 2019; Chang et al., 2022). These visual functional tests are easy to perform, quick and non-invasive and can provide information on the onset, stage and evolution of the neurodegeneration.

These changes in visual function can have a significant impact on the daily lives of individuals with AD and their caregivers. It is important to monitor and manage visual changes in individuals with AD to help maintain their quality of life.

Currently, the continuum of AD is well understood in terms of biochemical changes, brain atrophy, and cognitive decline. However, what is not clearly established is how visual function changes in these patients throughout the evolution of the pathology, from preclinical stages to advanced disease. It is therefore crucial to understand the visual changes that occur in these patients, given their importance for maintaining independence in daily life. By gaining a better understanding of visual changes in the context of the disease continuum, we can improve patient care and outcomes. Despite the existence of numerous reports detailing the examination of retinal biomarkers in AD, as evidenced by numerous articles and reviews, the literature concerning the evaluation of visual perception in AD remains limited. This may be attributed to the challenge of obtaining subjective measurements in individuals with cognitive decline. Nonetheless, investigating these visual perceptual variables in early-stage cases may be worthwhile in order to determine whether they can be utilized as supplementary biomarkers for AD. Thus, the aim of this study is to analyze the differences in visual function in the different stages of the disease continuum, from healthy subjects with high genetic risk for the development of the disease to patients with moderate AD.

To our knowledge, this is the first study to analyze the visual function of 5 groups of subjects, corresponding to the different stages of the AD continuum (“Control,” “FH+,” “MCI,” “mild AD” and, “moderate AD”). The study sample was carefully selected, and all participants met the inclusion criteria in terms of diagnosis of neurological disease or any ocular disease that could interfere with the results.

When analysing the MMSE of the study groups, we found statistically significant differences between the control group, the FH+ group and the MCI group, which had a higher MMSE score than the mild and moderate AD groups. The control, FH+ and MCI groups did not differ from each other. In the sample analysed in the present study, the mild AD group had an MMSE of 25.00 (21.00–26.50), a higher score than values reported in other studies (Cronin-Golomb et al., 1995, 2007; Lakshminarayanan et al., 1996), these values indicate that they are patients with a very early stage of the disease. The MMSE score of our patients is very high because our patients were newly diagnosed, and therefore, it is an early phase in each of the stages. All patients had a diagnosis given by a team of geriatricians and neuropsychologists after an extensive battery of tests, including magnetic resonance imaging. We specifically chose this population to reliably answer visual tests, as psychophysical visual tests require patient collaboration, and although the examiners had extensive experience with patients with cognitive impairment, minimal patient involvement was required.

Although there were differences among the different age groups, all patients were over 65 years old, including those in the FH+ group. This inclusion criterion was chosen because it is known that visual function declines around this age range, and the population over 65 years old can be considered as a homogeneous group (Ross et al., 1985; Elliott, 1987; Liutkevičienė et al., 2013; Pelletier et al., 2016). It is noteworthy that subjects in the FH+ group had a younger age range because they were those whose parents had suffered from dementia, and although they had predisposing genetic traits, cognitive decline had not yet developed. That is precisely why the age of this group was lower, and it is interesting to understand what happens at this stage in order to detect possible early differences in visual function.

Patients with AD suffer from various symptoms at different stages, one of which is language problems, including nominative deficits. For this reason, the selection of visual tests was carefully considered in this study, choosing those with limited naming demands and easily performable by these patients. For the measurement of VA, the letters are presented in isolation for identification, as it has been observed that patients perform better on the test and obtain better results in this way (Sadun et al., 1987). Similarly, the analysis of CS with the CSV-1000E test, which has a low influence of VA compared to other existing CS tests (Neargarder et al., 2003) and the colour perception with the Roth 28-hue test that did not require verbalisation of the results by the patients (Berry, 2017; Salobrar-García et al., 2019).

A previous study performed in youngest AD relatives (average age of 56 years old), it was showed a hypersynchronization in functional connectivity measured by magnetoencephalography of high alpha band in comparison with the control group (Ramírez-Toraño et al., 2021). This alteration is caused by a possible imbalance of excitation/inhibition of GABAergic neurons located in the vicinity of Aβ plaques that are deposited very early in AD (Garcia-Marin et al., 2009; Busche and Konnerth, 2016). In the present study, we analysed the visual function of subjects with a family history of AD and over 65 years of age, to test whether there are similar changes in the visual pathway as have been observed in the electric response of the brain.

The results obtained in VA showed a significant decrease in the MCI, mild and moderate AD patients with respect to the control group. This alteration that appears in both preclinical and early stages of the disease could be due to an alteration in the function of neurotransmitters, specifically acetylcholine. It is known that acetylcholine has a crucial role in the peripheral and central nervous systems, and in AD cholinergic neurons, are severely lost in AD (Ferreira-Vieira et al., 2016). In the retina, these neurotransmitter changes are mainly evident in the photoreceptor layer and in the inner nuclear layer and are associated with the loss of cholinergic cells in the retina (Nobili and Sannita, 1997; Schliebs and Arendt, 2006; Oliveira-Souza et al., 2017; Cerquera-Jaramillo et al., 2018). In the literature, according with our results, we found studies in which this loss of VA appears also in patients with cognitive decline and worsens as the disease progresses (Sadun et al., 1987; Salobrar-García et al., 2019; Rehan et al., 2021; Chang et al., 2022; Wu et al., 2022). Also, in the present work, we found a positive correlation between the MMSE score and the VA.

VA and CS impairment may be risk factor for cognitive decline (Ward et al., 2018; Swenor et al., 2019; Smith et al., 2021) and they may precede the onset of clinical cognitive impairment several years earlier. These findings suggest that reduced VA may be an early manifestation of central nervous system degeneration and/or that impaired visual function may contribute to cognitive impairment (Brenowitz et al., 2019; Naël et al., 2019; Swenor et al., 2019; Tran et al., 2020). Also the reduction in VA can be explained by cortical and subcortical dysfunction of the visual system further affecting writing, reading and face recognition (Cerquera-Jaramillo et al., 2018).

One of the earliest visual manifestations in patients with AD, are alterations in CS (Risacher et al., 2013; Jindal, 2015), which have been associated with impairment in more cognitive domains than other measures of visual functioning (Varadaraj et al., 2021). CS worsens throughout the course of the disease, and is related to damage to the magnocellular pathway of the lateral geniculate nucleus of the central nervous system (Sartucci et al., 2010; Risacher et al., 2013). Epidemiological studies have shown that older adults with impaired CS are at increased risk of cognitive impairment at 10 years of follow-up (Fischer et al., 2016). It was also reported a strong association between brain areas involved in the disease with CS records which may be predictive of abnormal Aβ and p-Tau protein accumulation. In addition, a reduction in CS, measured by frequency doubling technology, has been associated with Aβ and P-Tau brain deposition as well as neurodegeneration, both throughout disease progression and alone in subjects at high risk for AD development (Risacher et al., 2020). In our study there are significant decreases in CS at both, low and high frequencies, between: (i) the control group and the AD groups and, (ii) the FH+ group and the AD groups; as reported in other studies in the literature associated with the MMSE score (Risacher et al., 2013; Salobrar-García et al., 2019). This correlation also has been found in the present study where in addition, we observed that high frequencies are decreased in all groups except for the comparison between the control vs. FH+ group. This decrease therefore already appears in the MCI group. The greatest reduction at higher spatial frequencies has been described by several authors (Hutton et al., 1993; Gilmore and Whitehouse, 1996; Salobrar-García et al., 2015, 2019), but others report that the higher reduction occurs at low spatial frequencies (Levine et al., 1993; Baker et al., 1997; Cronin-Golomb et al., 2007; Polo et al., 2017) and others find no differences with respect to the control group (Schlotterer et al., 1984; Rizzo and Nawrot, 1998; Massoud et al., 2002). The discrepancies observed in the literature in the analysis of CS at different stages of the disease may be due to the heterogeneity of the samples and the tests used to analyze it (Neargarder et al., 2003).

Another of the manifestations in AD patients are alterations in colour perception. These differences could be mainly due to participation both the parvocellular pathway, which is characterized by small axons of the optic nerve (Salamone et al., 2009) and the koniocellular pathway which is involved with the blue-yellow spectrum (Martin et al., 1997). One of the alterations linked to AD is a notable decrease in the cortical region V4, which plays a crucial role in the processing of chromatic information (Chan et al., 2001; Brewer and Barton, 2016). On the other hand, changes in colour vision in AD have been associated with variations in different retinal layers according to Köllner’s rule. While changes in the retinal ganglion cells, optic nerve, visual pathway and visual cortex lead to a deficiency in the red-green axis, changes in the outer retina contribute to alterations in the blue-yellow axis (Huna-Baron et al., 2013; Kim et al., 2022). On the other hand, in the AD, it has been described that there is an degeneration on the photoreceptor cells that does not occur in only one type of cone, which is due to the reduction of melatonin levels and its antioxidant effects that occurs in AD (Savaskan et al., 2002).

When we analyzed colour perception in our patients, we observed that MCI, mild AD and moderate AD had a significant increase in the number of total errors in comparison to FH+ group. Also, the moderate AD group showed a significant increase in the total number errors related to control group. This diffuse involvement has been observed by different authors (Pache et al., 2003; Salamone et al., 2009; Polo et al., 2017; Salobrar-García et al., 2019) and recently Vidal et al. had found that individuals with AD and those with MCI display an acquired color vision deficiency, both in protan and tritan axism that is likely associated with compromised brain metabolism (Vidal et al., 2022).

In our patients, we found in the tritan axis errors, significant differences between the control group and mild and moderate AD groups, as well as between the FH+ and mild and moderate AD. However, we found no significant differences in this axis between the MCI group and the control group. In contrast, a loss in the tritan axis has been reported between the MCI subjects and the control group (Vidal et al., 2022). The MCI group is an intermediate stage between normal subjects and AD patients (Lewis et al., 1987; Black, 1996) that have worse MMSE scores (Vidal et al., 2022). In the present work, in all participants, we observed a negative correlation between the MMSE score and the total error number, tritan and deutan axis.

With respect to the deutan axis, we found statistically significant differences when we compared between the control group and both mild and moderate AD and when we compared between the FH+ and moderate AD groups. Similar than Vidal et al. (2022), we also found no significant differences in the number of errors between the control and MCI groups.

In a previous work, we found that in subjects with moderate AD the PDT showed a high direct correlation with the MMSE score and the aROC curves showed a good prognostic value (Salobrar-García et al., 2019). In the present study, our MCI patients showed no differences in PDT, however there were statistically significant differences between the mild and moderate AD groups and the control and FH+ groups. In addition, we also found a statistically significant positive correlation between the MMSE score and PDT. These results could be explained due to alterations in the visual processing in the AD pathology, that would take place in the regions involved in the magnocellular pathway (parietal and frontal brain areas) (Bar, 2003; Saumier et al., 2005).

Overall, our results of the aROC curves suggest that some psychophysical tests may be useful in identifying individuals with cognitive decline or disease, with the CS test analysing the 12 cpd and 18 cpd showing particular promise in distinguishing between control groups and those with mild or moderate AD.

As all the research works, this study shows strengths and some limitations. One of the first limitations is the low number of participants in each of the study groups. However, it should be noted that these have been carefully selected and that all participants met strict ophthalmological and memory criteria. We could be sure that all visual defects found are due to neurodegeneration and not to a visual problem. Despite having no biological biomarkers of the disease, the clinical diagnosis of the participants was made by professionals who followed standard criteria. It would be interesting for future studies to have bigger samples and to be able to correlate them with functional findings. On the other hand, it would be very interesting to carry out longitudinal studies of participants at high genetic risk for the development of AD and patients with MCI, so that we could learn about the evolution of the functional changes found in these early stages of the pathology. One of the strengths of this study is that the tests used in the present study to analyse visual function are easy to apply and could be useful together with neuropsychological tests and imaging tests for the diagnosis of AD, however, we are aware that other tests could be used for the analysis of visual function such as pupillometry, analysis of extraocular movements, and other tests for the analysis of visual function.

In conclusion, alterations in visual function appear already in subjects with MCI and evolve when AD disease is established. These differences seem to remain stable between the different early stages of AD (mild and moderate AD). Although in the present study we found no differences in visual function in the FH+ group, it would nevertheless be interesting to carry out longitudinal studies in these population to find out whether they develop the disease in the future. Therefore, visual psychophysical tests are a useful, simple and complementary tool to neuropsychological tests to facilitate diagnosis in the preclinical and early stages of AD and they correlated with the cognitive function.

The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.

The studies involving human participants were reviewed and approved by the research followed the tenets of the Declaration of Helsinki, and the studies were approved by the local ethics committee (HCSC) with the internal code 11/372-E, 18/422-E_BS and 20/698-E_Tesis. The patients/participants provided their written informed consent to participate in this study.

LE-H, IL-C, RH, MS, MD-L, AR, JS, FM, PG, JR, and ES-G: conceptualization and validation. LE-H, IL-C, RH, MS, LS-P, FR-T, JM, JF-A, PR, SA, MD-L, AR, JS, FM, PG, JR, and ES-G: methodology. LE-H, IL-C, RH, MS, FR-T, SA, MD-L, AR, JS, FM, PG, JR, and ES-G: formal analysis. LE-H, IL-C, RH, MS LS-P, FR-T, JM, JF-A, PR, SA, MD-L, AR, JS, FM, PG, JR, and ES-G: investigation. RH, MD-L, AR, JS, FM, PG, and JR: resources. LE-H, IL-C, MS, LS-P, FR-T, JM, JF-A, PR, SA, and ES-G: data curation. LE-H, IL-C, RH, LS-P, MD-L, AR, JR, and ES-G: writing—original draft preparation, LE-H, IL-C, RH, AR, JS, JR, and ES-G: writing—review and editing. RH, JR, and ES-G: supervision. RH, MD-L, AR, JS, FM, PG, JR, and ES-G: project administration. RH, FR-T, AR, JS, FM, PG, and JR: funding acquisition. All authors contributed to the article and approved the submitted version.

This research was funded by the Research Network RETIBRAIN (RED2018-102499-T) of the Spanish Ministry of Science and Innovation; and the Spanish Ministry of Economy and Compet-itiveness (Grant PSI2015-68793-C3-1-R) and by the Spanish Ministry of Economy and Competi-tiveness under the Grant PSI2015-68793-C3-1-R [D601], by the project B2017/BMD-3760 from NEUROCENTRO. IL-C was currently supported by a Postdoctoral Fellowship (CT42/18-CT43/18) from the Complutense University of Madrid. JF-A was currently supported by a Predoctoral Fellowship (FPU17/01023) from the Spanish Ministry of Science, Innovation, and Universities. LS-P was currently supported by a Predoctoral Fellowship (CT82/20-CT83/20) and JM was currently supported by a Predoctoral Fellowship (CT58/21-CT59/21) from the Complutense University of Madrid.

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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