Neurocognitive Assessment and Retinal Thickness Alterations in Alzheimer Disease: Is There a Correlation

Background: The relation of retinal thickness to neuropsychological indexes of cognitive impairment in patients with Alzheimer disease (AD) remains an area of investigation. The scope of this investigation was to compare volume and thickness changes of neuronal retinal layers in subjects with AD with those of age-matched healthy controls and to estimate the relation between cognitive functioning evaluated by neuropsychological assessment and thickness changes of the retina. Methods: This was a prospective single-site study where we evaluated 25 subjects with probable AD matched for age, sex, and education to 17 healthy control subjects (HC). All participants underwent a full medical evaluation, neuropsychological assessment, and optical coherence tomography (OCT) to evaluate the peripapillary retinal nerve fiber layer (pRNFL) thickness, ganglion cell complex (GCC) thickness, and macular volume. Results: The pRNFL thickness of AD patients showed a significant overall reduction compared with healthy controls (P = <0.0001). Furthermore, pRNFL was reduced in each retinal quadrant, particularly the inferior, nasal, and superior quadrants. GCC thickness and macular volume were reduced in AD patients in comparison with HC (P = 0.004; P = 0.001). Of particular interest was the correlation between OCT findings and neuropsychological assessment; we did not find a significant association of retinal thinning with worse MMSE score, but reduction of macular volume was associated with worse constructional praxis performance. Impairment of semantic-lexical and processing speed was associated with attenuation of macular GCC thickness. Conclusions: OCT can show early thickness changes in AD patients with subtle memory disturbances. These results suggest that correlations between retinal thinning and cognitive performance warrant further investigation.

Original Contribution Neurocognitive Assessment and Retinal Thickness Alterations in Alzheimer Disease: Is There a Correlation? Virginia Cipollini, MD, Solmaz Abdolrahimzadeh, MD, PhD, Fernanda Troili, MD, Antonella De Carolis, MD, PhD, Silvia Calafiore, MD, Luca Scuderi, MD, Franco Giubilei, MD, PhD, Gianluca Scuderi, MD Background: The relation of retinal thickness to neuropsychological indexes of cognitive impairment in patients with Alzheimer disease (AD) remains an area of investigation. The scope of this investigation was to compare volume and thickness changes of neuronal retinal layers in subjects with AD with those of age-matched healthy controls and to estimate the relation between cognitive functioning evaluated by neuropsychological assessment and thickness changes of the retina. Methods: This was a prospective single-site study where we evaluated 25 subjects with probable AD matched for age, sex, and education to 17 healthy control subjects (HC). All participants underwent a full medical evaluation, neuropsychological assessment, and optical coherence tomography (OCT) to evaluate the peripapillary retinal nerve fiber layer (pRNFL) thickness, ganglion cell complex (GCC) thickness, and macular volume. Results: The pRNFL thickness of AD patients showed a significant overall reduction compared with healthy controls (P = ,0.0001). Furthermore, pRNFL was reduced in each retinal quadrant, particularly the inferior, nasal, and superior quadrants. GCC thickness and macular volume were reduced in AD patients in comparison with HC (P = 0.004; P = 0.001). Of particular interest was the correlation between OCT findings and neuropsychological assessment; we did not find a significant association of retinal thinning with worse MMSE score, but reduction of macular volume was associated with worse constructional praxis performance. Impairment of semantic-lexical and processing speed was associated with attenuation of macular GCC thickness. NESMOS Department, S. Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, Rome, Italy. The authors report no conflicts of interest. Supplemental digital content is available for this article. Direct URL citations appear in the printed text and are provided in the HTML and PDF versions of this article on the journal's Web site (www. jneuro-ophthalmology.com). Address correspondence to Virginia Cipollini, MD, NESMOS Department, S. Andrea Hospital, Faculty of Medicine and Psychology, Sapienza University of Rome, Via di Grottarossa 1035-1039, 00189 Rome, Italy; E-mail: [e-mail] 370 Conclusions: OCT can show early thickness changes in AD patients with subtle memory disturbances. These results suggest that correlations between retinal thinning and cognitive performance warrant further investigation. Journal of Neuro-Ophthalmology 2020;40:370-377 doi: 10.1097/WNO.0000000000000831 © 2019 by North American Neuro-Ophthalmology Society D isability and dependency due to dementia is a prominent public health issue among the elderly population worldwide. There are almost 46 million people in the world who live with dementia; by 2050, the number is predicted to rise to 131.5 million. Alzheimer disease (AD) is the most common form of dementia and accounts for 50%-70% of cases (1). The pathological hallmark of AD is the accumulation of amyloid-beta plaques and tau neurofibrillary tangles in the brain. Advancing age and genetic predisposition are well known risk factors for the disease; however, diabetes, hypertension, obesity, depression, smoking, cognitive inactivity, physical inactivity, and microbiome alterations (more recently brought to scientific community attention) have been implicated as additional risk factors (2-4). AD in its typical form is characterized by prominent episodic memory impairment, with secondary deficits in word-finding skills, spatial cognition, and executive function. Severe neuropsychiatric disturbances are associated with disease progression. However, visual symptoms are often the earliest complaints of patients with AD, and many of the retinal findings associated with AD have been detected early in the disease course. It is well known that abnormalities in visual acuity, color perception, contrast sensitivity, visual field, and motion perception are associated with early AD (5-8). At first, these symptoms were explained by progressive loss of function of primary and associative visual cortices. Recently, some authors have demonstrated pathologic changes in the retina and optic Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution nerve that may be present in the early stages of AD and may represent the earliest sign of the disease, even before the hippocampal damage that impacts memory (9). Several studies have investigated evidence of retinal involvement in AD using imaging techniques such as optical coherence tomography (OCT). This method enables in vivo imaging of the individual layers of the retina, including the ganglion cell complex (GCC), retinal nerve fiber layer (RNFL), and measures macular thickness and volume. OCT has shown significant reductions in retinal thickness in patients with AD (10-12) and in those with mild cognitive impairment (MCI) (13). However, only few studies have examined the relation between RNFL thinning and scores for neuropsychological indexes of cognitive impairment. These results have not been conclusive (14,15). Some authors have reported that the pathological cerebral alterations of AD affect the visual pathways and optic nerve through retrograde degeneration (16,17); however, one study reported that RNFL thickness reduction in AD can be unrelated to changes in cortical visual evoked response, leading to the hypothesis that neuronal loss in these patients is not only due to retrograde degeneration (18). Thus, some have suggested that the pathologic characteristics of AD occur in a simultaneous fashion in the brain and retina. Furthermore, signs of neuroinflammation and Ab plaques and fibrillar t have been observed in ocular tissue both in humans with AD and in animal models (10,11,19-23). The primary aims of this study were to evaluate changes in the retinal layer thickness and volumes by OCT in patients with AD in the early stages of disease. These were compared with OCT measurements from age-matched healthy control subjects to assess whether retinal alterations may represent an early marker of AD pathogenesis. We also sought to clarify the relation between cognitive functioning, evaluated by a complete neuropsychological assessment, and retinal thickness measurements by OCT in patients with AD. METHODS This was a prospective single-site study. The research was approved by the ethical board of the "Sapienza," University of Rome, on December 2017, and was conducted according to the tenets of the Declaration of Helsinki. All subjects were informed regarding the study and gave their consent. Subjects We selected, from a series of 50 consecutive outpatients referred to the Dementia Centre of Sant'Andrea Hospital (Rome, Italy) during a 12-month period, 25 subjects with probable AD (mean age: 74 ± 4 years; 14 [56%] women; mean education duration: 8.4 ± 4.4 years). The diagnosis was made in accordance with the National Institute for Neurological and Communicative Disorders and Stroke- Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 Alzheimer Disease and Related Disorders Association (NINCDS-ADRDA) criteria (24). Patients with AD were matched for age, sex, and education to 17 healthy control subjects (HC) (mean age 70 ± 7 years; 10 [58.8%] women; mean education duration: 8.9 ± 3.5 years). Controls included the patient's spouses (See Supplemental Digital Content, Table E1, http://links.lww.com/WNO/A379). A multidisciplinary staff member determined the diagnosis of cognitive impairment; inclusion criteria were mild cognitive deficit defined as a score of Mini Mental State Evaluation (MMSE) $19, education of $5 years, and age between 55 and 80 years. We excluded subjects with behavioral disturbances, which could affect their compliance in the study, severe medical comorbidities or neurosensorial deficits, other eye pathology such as glaucoma and diabetic retinopathy, history of retinal surgery, low vision, or history of drug abuse. Subjects were also excluded from the AD group if they had evidence of neurodegenerative disorders or cognitive impairment resulting from other diseases or a coexisting medical condition that could interfere with cognitive assessment. In particular, we excluded 8 patients because of behavioral disturbances, 9 patients because of severe medical comorbidities or neurosensorial deficits, 3 patients because of glaucoma, and 5 patients because of diabetic retinopathy. All the subjects underwent a full medical evaluation, including medical history and complete physical examination. A neuroimaging assessment with brain computer tomography (CT) or MRI was performed to support the diagnosis, as well as a neuropsychological evaluation and OCT examination. Neuropsychological Assessment All subjects underwent a standard neuropsychological evaluation that is used as a screening tool in our dementia center. The subjects' general level of cognitive impairment was evaluated by using the MMSE (25). Several cognitive domains were examined by means of neuropsychological tests that are widely used in the clinical setting and for which normative data are available for the Italian population. The tests used and the parameters considered for each domain are described below: - General intelligence/logical reasoning: Raven's Colored Progressive Matrices (RCPM) (26)-number of correct answers; - Speed of processing: Trail Making Test subtest (27) (TM A) (time in seconds) and Semantic Fluency (28) (word generation by semantic cues): sum of words produced in 60 seconds; - Selective attention (orienting): Visual Search Test (28)- sum of numbers correctly barred in 45 second on 3 trials; - Short-term memory: Verbal: Digit Span Forward (29)-longest correctly repeated series of numbers after oral presentation; 371 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution Visual: Corsi Block Test (29)-longest correctly remembered series of blocks previously pointed by an administrator; - Long-term memory (episodic memory): Verbal Rey Auditory Verbal Learning Test (RAVLT) (26) -delayed recall 15 minutes after 5 learning trials; Visual: Rey-Osterrieth Complex Figure Test (ROCF) (26) -delayed recall after 15 minutes; - Constructional praxis (visuospatial ability): ROCF (26)- correctly copied elements of figure; - Semantic-lexical system: Naming Test (26) (number of correct answers) and Semantic Fluency (28) (word generation by semantic cues; number of words produced in 60 seconds); - Executive functions: Trail Making Test A and B (27)- differential score between subtest B and subtest A (time in seconds) and Phonemic Fluency (28) (word generation by phonological cues; number of words produced in 60 seconds) Because some cognitive domains (speed of processing, semantic-lexical system, and executive function) have been explored using more than one neuropsychological test, we calculated standardized z-scores to obtain a single score for each cognitive domain. The z-scores were computed using mean values and SDs based on all participants but segregated by task. Optical Coherence Tomography Examination Retinal thickness assessment was performed with the spectral-domain optical coherence tomography device SDOCT RTVue according to the standard procedure. In each eye, the peripapillary retinal nerve fiber layer (pRNFL), macular GCC, and macular volume (MV) were evaluated. PRNFL thickness measurement was conducted using the 360° circular scan with a diameter of 3.46 mm centered on the optic disc (fast RNFL thickness mode). Thickness maps were elaborated by automated software, and values were provided for each quadrant (superior, inferior, nasal, and temporal). The fast macular thickness mode, centered on the fovea, was used to determine macular cube volume. The fast GCC thickness mode, centered on the fovea, was used to determine average thickness of the GCC complex, which includes the macular retinal nerve fiber layer, the ganglion cell layer, and the inner plexiform layer thicknesses. Data elaboration was performed with automated software. All OCT images were viewed to exclude for potential pathologic ocular conditions or scan alignment errors. Statistical Analysis Continuous variables were reported as mean ± SD; categorical data were presented using counts and proportions. Sta372 tistical differences between cases and controls were analyzed using the Student t-test and Levene test of equality of variances for continuous variables and the Pearson chi-square test for categorical variables. We calculated the linear correlation using the Pearson R between the mean values of the RNFL and GCC for both the right and left eyes and the raw MMSE scores. Spearman nonparametric rank correlations were used to assess any correlation between the cognitive dimension investigated by neuropsychological evaluation and the OCT measures, including RNFL and GCC thickness and macular volume in both right and left eyes. All comparisons or correlations with P values ,0.05 were considered statistically significant. Statistical analysis was performed using R Core Team 2014 software. RESULTS The demographic and clinical data for the 25 subjects with probable AD and the 17 healthy control subjects (HC) enrolled in the study are summarized in Table 1. The first aim of the study was to compare the values obtained by SDOCT assessment of the subjects with probable AD and the control group. For both the right and the left eyes, we analyzed the following variables: pRNFL, evaluated both as total peripapillary thickness and for each of the 4 quadrants (superior, nasal, temporal, and inferior), overall values of GCC, and macular volume. Figures 1 and 2 show representative scans of the pRNFL and GCC thickness in a patient with AD. The pRNFL thickness of AD subjects showed a significant overall reduction compared with healthy controls (RNFL values in total examined eyes: 91.6 ± 9.72 mm vs 108.1 ± 9.02 mm, P = ,0.0001; right eyes: 91.7 ± 11.3 mm vs 108.8 ± 11.8 mm, P = 0.0002; and left eyes: 91.5 ± 9.73 mm vs 107.4 ± 7.86 mm, P = ,0.0001) (Table 2). Furthermore, analysis of the values in each of the 4 retinal quadrants confirmed that AD subjects have a lower pRNFL thickness compared with the control group, considering the pooled sample of all eyes examined and, singularly, the right and left eyes (Table 3). The main difference between the AD group and the control group was in the inferior (222.3%), superior (220.9%), and nasal (217%) quadrants; differences were less pronounced in the temporal quadrant (29.86%) (Table 3). Moreover, the overall thickness of the GCC was significantly reduced in AD subjects when compared with the control group (GCC values in total examined eyes: 91.75 ± 11.9 mm vs 101.7 ± 7.19, P = 0.004; right eyes: 91.8 ± 11.73 mm vs 103.5 ± 9.91 mm, P = 0.0006; and left eyes 91.7 ± 15.64 mm vs 99.8 ± 4.9 mm, P = 0.011) (Table 2). Finally, regarding the macular volume, we found that the overall values were higher in the group of healthy controls than in AD subjects (macular volume values in total examined eyes: 6.9 ± 0.64 mm3 vs 7.6 ± 0.23 mm3, Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 1. Demographical and clinical data of AD subjects and healthy control subjects Sex (Male/female) Age (years) Education duration (years) MMSE AD Subjects (n = 25) Healthy Controls (n = 17) P value 11/14 72.5 ± 4.3 8.4 ± 4.4 24.2 ± 3.8 7/10 71.5 ± 6.1 8.9 ± 3.5 29.2 ± 0.7 0.89 0.07 0.63 ,0.001 Data are mean ± SD. AD, Alzheimer disease; MMSE, Mini Mental State Evaluation. P = 0.001; right eyes: 7.7 ± 0.28 mm3 vs 7.0 ± 0.76 mm3, P = 0.002; left eyes: 7.5 ± 0.27 mm3 vs 6.8 ± 0.6 mm3, P = ,0.0001) (Table 2). The MMSE score was 24.2 ± 3.8 for AD patients and 29.2 ± 0.6 for healthy controls (P ,0.001) (See Supplemental Digital Content, Table 1, http://links.lww.com/ WNO/A379). In the AD group, we evaluated the possible associations between OCT measurements and scores for the cognitive domains investigated by the neuropsychological assessment (See Supplemental Digital Content, Table E1, http://links.lww.com/WNO/A379). Worse scores for the MMSE were not associated with thinning or reductions in the OCT measurements (See Supplemental Digital Content, Table E1, http://links.lww.com/WNO/A379). Considering separately each cognitive domain, we found that reduced macular volume was associated with worse constructional praxis (right eyes: P = 0.033, r = 0.518; left eyes: P = 0.04, r = 0.523). A similar association was found between reduced GCC thickness and worse scores for the semantic-lexical system, predominantly using measurements from the left eyes (P = 0.07, r = 0.359) and for processing speed based on measurements from both eyes (right eyes: P = 0.05, r = 0.387; left eyes: P = 0.06, r = 0.376). Overall pRNFL thickness was lower among those with higher verbal long-term memory based on measurements for the right eyes (P = 0.06, r = 20.375) (See Supplemental Digital Content, Table E1, http://links.lww.com/WNO/A379). Finally, the results for pRNFL thickness in each of the 4 quadrants showed reductions in the inferior quadrant thickness for the right eye and increased general intelligence (P = 0.02, r = 20.45), increased verbal long-term memory (P = 0.02, r = 20.45), and increased verbal short-term memory FIG. 1. Spectral-domain optical coherence tomography image of the peripapillary retinal nerve fiber layer (pRNFL) in a patient with Alzheimer disease. Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 373 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution FIG. 2. Spectral-domain optical coherence tomography showing thickness of the macular ganglion cell complex (GCC) in a patient with Alzheimer disease. (P = 0.03, r = 20.428). Superior quadrant measures for pRNFL were thinner among patients with better scores for the semantic-lexical system (P = 0.04 r = 20.413) (data not shown). CONCLUSIONS The first aim of our study was to compare pRNFL thickness, macular GCC thickness, and macular volume in patients with mild AD and age-matched controls. Previous studies (16,30) reported a reduction of RFNL thickness in each of the 4 retinal quadrants, suggesting diffuse axonal degeneration in AD patients, with predominance in the superior and inferior quadrants. Our results showed significant reductions in the individual quadrants. Moreover, we found that macular measurements, including macular volume and macular GCC thickness, were markedly reduced in both eyes of patients with AD. This strongly implies that degeneration of retinal ganglion cells should be added to the neuropathological changes found in patients with AD and that RNFL and GCC thickness can be used to differentiate patients with AD from normal aging (18). Indeed, the retinal changes seem to track the aggregation of beta amyloid brain plaques well before cognitive problems arise. OCT scanning may be a noninvasive, rapid, and inexpensive option to identify people who could be at a high risk for AD. 374 Another purpose of our study was to verify the existence of a correlation between structural retinal degeneration (OCT parameters) and the cognitive impairment in patients with AD. Data in the literature are conflicting, but most studies showed a more consistent correlation between cognitive impairment and full macular thickness or inner retinal layers (31,32). A relation between RNFL thinning and cognitive impairment evaluated by MMSE was reported in AD patients, suggesting that measurement of RNFL may be used as a disease progression marker (33). Moreover, Iseri et al (18) found that total macular volume and MMSE scores were significantly correlated in AD. The EPIC-Norfolk study also reported an association between RNFL thickness (measured by Heidelberg Retina Tomograph) and cognitive test scores assessing global function, recognition, learning, episodic memory, and premorbid intelligence in a population of older British adults (34). By contrast, other studies have found that OCT measurements were not correlated with MMSE, ADAS-Cognitive subscale, and Clinical Dementia Rating (CDR) evaluations (35). Recently, Gao et al have observed RNFL thinning in all quadrants, especially in the nasal region, with no relation to the MMSE and AD severity (36). However, other studies found significant correlations between MMSE scores and RNFL thickness (33), as well as choroidal thickness at all locations (37). We did not find a significant association between MMSE and pRNFL thickness, macular GCC Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution TABLE 2. RNFL, GCC, and macular volume in AD subjects and healthy control subjects AD Subjects (n = 25) Overall RNFL in examined eyes (mm) Overall RNFL OD (mm) Overall RNFL OS (mm) Overall GCC in examined eyes (mm) Overall GCC OD (mm) Overall GCC OS (mm) Overall macular Volume in examined eyes (mm3) Macular Volume OD (mm3) Macular Volume OS (mm3) 91.6 ± 9.72 (numbers of eyes = 50) 91.7 ± 11.3 91.5 ± 9.73 91.75 ± 11.9 (numbers of eyes = 50) 91.8 ± 11.73 91.7 ± 15.64 6.9 ± 0.64 (numbers of eyes = 50) 7.0 ± 0.76 6.8 ± 0.60 Healthy Controls (n = 17) T Test P value 108.1 ± 9.02 (numbers of eyes = 34) 108.8 ± 11.8 107.4 ± 7.86 101.7 ± 7.19 (numbers of eyes = 34) 103.5 ± 9.91 99.8 ± 4.94 7.6 ± 0.23 (numbers of eyes = 34) 25.55 ,0.0001 24.71 25.83 23.07 0.0002 ,0.0001 0.004 23.51 22.41 23.90 0.0006 0.011 0.001 23.13 24.46 0.002 ,0.0001 7.7 ± 0.28 7.5 ± 0.27 Data are mean ± SD. AD, Alzheimer disease; GCC, ganglion cell complex; OD, right eye; OS, left eye; RNFL, retinal nerve fiber layer. thickness, and macular volume. Because of the evidence that pRNFL thickness may decrease with advancing disease (30), a possible explanation of our results is that our patients did not suffer from severe AD; thus, the MMSE may be not sensitive enough to detect subtle changes in the early phase of cognitive deterioration. Even if we did not use other biomarkers of AD, a correlation with more sensitive and specific cognitive tests, such as a formal neuropsychological evaluation, has the potential to improve diagnostic accuracy in the absence of histopathological data. In our study, reduction of macular volume was selectively associated with a worse constructional praxis performance. Moreover, impairment of the semantic-lexical system and processing speed was associated with the attenuation of macular GCC thickness. Verbal fluency tests have detected changes during very early cognitive decline (as many as 15 years before the clinical diagnosis of AD) (38). This may explain the results in our patients with an early cognitive impairment. Surprisingly, we did not find a significant correlation between inner retinal thinning and the memory domain score, even if an episodic memory deficit is traditionally the predominant initial complaint in most cases of AD. RNFL thickness alterations may affect axons and alter synaptic function, leading to cognitive deterioration in specific areas. Indeed, a recent study showed that total macular thickness was associated with posterior cortical atrophy on MRI, suggesting a direct correlation between macular thinning and focal neuronal loss of TABLE 3. RNFL in each of the 4 quadrants of the eye (superior, nasal, temporal, and inferior) in AD subjects and healthy control subjects RNFL Site Superior quadrant in examined eyes Superior quadrant OD Superior quadrant OS Nasal quadrant in examined eyes Nasal quadrant OD Nasal quadrant OS Temporal quadrant in examined eyes Temporal quadrant OD Temporal quadrant OS Inferior quadrant in examined eyes Inferior quadrant OD Inferior quadrant OS AD Subjects (n = 25) (mm) 111.9 ± 13.2 (numbers of eyes = 109.6 ± 18.8 114.5 ± 10.63 63.8 ± 9.17 (numbers of eyes = 63.3 ± 12.6 64.9 ± 10.1 72.2 ± 8.4 (numbers of eyes = 75.0 ± 10.4 69.5 ± 9.8 116.8 ± 18.5 (numbers of eyes = 119.9 ± 19.0 114.8 ± 21.3 Healthy Controls (n = 17) (mm) 50) 50) 50) 50) 132.8 ± 12.3 (numbers of eyes = 133.2 ± 15.6 132.4 ± 12.0 80.8 ± 11.5 (numbers of eyes = 81.2 ± 15.4 80.5 ± 14.6 82 ± 11.3 (numbers of eyes = 85.9 ± 13.5 78.1 ± 10.5 139.1 ± 18.8 (numbers of eyes = 139.8 ± 26.6 138.4 ± 16.4 AD-Controls Variation (%) T Test P value 220.9 25.14 ,0.0001 217.7 213.5 217.0 24.43 23.87 25.27 ,0.0001 0.0002 ,0.0001 222.0 219.4 29.86 23.96 23.79 23.2 0.0002 0.0003 0.003 212.7 211.0 222.3 22.81 22.71 23.78 0.0044 0.0049 0.001 214.2 217.1 22.66 23.83 0.0065 0.0002 34) 34) 34) 34) Data are mean ± SD. AD, Alzheimer disease; OD, right eye; OS, left eye; RNFL, retinal nerve fiber layer. Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 375 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution specific cortical areas, such as the posterior cingulate, parietal-occipital sulcus (including the cuneus), and parietal lobe. These areas are all involved in visual processing (39). Further investigations in large cohorts of patients are needed to determine the association of RNFL thickness with neuroimaging data and other biomarkers of AD. Such investigations will clarify the underlying mechanisms of these clinical findings. Finally, the mechanisms behind the association between worse cognitive function and increased thickness of pRNFL in the inferior and superior quadrants remain to be clarified. A report on patients with MCI suggested that inferior quadrant RNFL thickness was inversely associated with the episodic memory score and could serve as a biomarker of risk of conversion from MCI to AD (15). A possible explanation of the inverse relation between pRNFL and cognitive test scores could relate to pathologic gliosis preceding loss of neurons and ultimate decreased thickness (40); this concept has been reinforced by histopathology work suggesting that gliosis precedes human AD pathology in the brain (41). OCT technology cannot differentiate between gliosis and axonal projections in the RNFL, and longitudinal studies are necessary to ascertain whether the dynamic changes in the retina are associated with the changes in cognitive function along the course of disease (14). Indeed, only a limited number of studies have investigated OCT as a predictor of future cognitive decline, demonstrating greater degrees of RNFL thinning in the superior quadrant in patients who maintained stable cognitive function (14) and greater reductions in RNFL thickness in the inferior quadrant in participants whose cognitive status deteriorated (42). OCT is a rapid, safe, and noninvasive method of imaging that is used to assess retinal degeneration in numerous ophthalmologic and neurological disorders. From our experience, and in accordance with previous studies (43), it could be suggested that OCT can be used to improve the early diagnosis of AD in individuals with subtle memory disturbances. We acknowledge the relatively small number of subjects and the lack of follow-up as a limitation of our study. Moreover, diagnosis of AD was based on clinical criteria and neuroimaging assessment with brain CT or MRI, without the support of biomarkers (e.g., amyloid PET, CSF, and/or FDGPET). Strengths of our study include the relatively rigorous inclusion and exclusion criteria. Moreover, we analyzed the results of a complete neuropsychological battery, which allowed us to explore associations between retinal changes and various aspects of cognitive performance. In conclusion, despite its limitations, our study provides further evidence that retinal thinning may reflect neurodegenerative changes of AD brain. OCT may thus be useful for future AD research. Further studies are needed to better 376 understand the relation between retinal thinning and cognitive performance in patients with AD. STATEMENT OF AUTHORSHIP Category 1: a. Conception and design: F. Giubilei, G. Scuderi, and V. Cipollini; b. Acquisition of data: V. Cipollini, F. Troili, A. De Carolis, S. Calafiore, and L. Scuderi; c. Analysis and interpretation of data: V. Cipollini, A. De Carolis, and S. Abdolrahimzadeh. Category 2: a. Drafting the manuscript: V. Cipollini, A. De Carolis, and S. Abdolrahimzadeh; b. Revising it for intellectual content: F. Giubilei and G. Scuderi. Category 3: a. Final approval of the completed manuscript: V. Cipollini, A. De Carolis, S. Abdolrahimzadeh, F. Giubilei, and G. Scuderi. REFERENCES 1. Prince PM, Ali G, Ali G. World Alzheimer report 2015. In: The Global Impact of Dementia. London, United Kingdom: Alzheimers Disease International, 2015. 2. Banes DE, Yaffe K. The projected effect of risk factor reduction on Alzheimer's disease progression. Lancet Neurol. 2011;10:819-828. 3. Dinan TG, Cryan JF. Gut instincts: microbiota as a key regulator of brain development, ageing, and neurodegeneration. J Physiol. 2017;595:489-503. 4. Abraham D, Feher J, Scuderi GL, Szabo D, Dobolyi A, Cservenak M, Juhasz J, Ligeti B, Pongor S, Gomez-Cabrera MC, Vina J, Higuchi M, Suzuki K, Boldogh I, Radak Z. Exercise and probiotics attenuate the development of Alzheimer's disease in transgenic mice: role of microbiome. Exp Gerontol. 2019;115:122-131. 5. Whittaker KW, Burdon MA, Shah P. Visual field loss and Alzheimer's disease. Eye (Lond). 2002;16:206-208. 6. Mendez MF, Tomsak RL, Remler B. Disorders of the visual system in Alzheimer's disease. Neurology. 1990;40:439-443. 7. Cronin-Golomb A, Vorkin S, Rizzo JF, Cohen J, Growden JH. Visual dysfunction in Alzheimer's disease: relation to normal aging. Ann Neurol. 1991;29:41-52. 8. Pache M, Smeets CH, Gasio PF, Savaskan E, Flammer J, WirzJustice A, Kaiser HJ. Colour vision deficiencies in Alzheimer's disease. Age Ageing. 2003;32:422-426. 9. Chiu K, Chan TF, Wu A, Leung IY, So KF, Chang RC. Neurodegeneration of the retina in mouse models of Alzheimer's disease: what can we learn from the retina? Age. 2012;34:633-649. 10. Parisi V, Restuccia R, Fattapposta F, Mina C, Bucci M, Pierelli F. Morphological and functional retinal impairment in Alzheimer's disease patients. Clin Neurophysiol. 2001;112:1860-1867. 11. Parisi V. Correlation between morphological and functional retinal impairment in patients affected by ocular hypertension, glaucoma, demyelinating optic neuritis and Alzheimer's disease. Semin Ophthalmol. 2003;18:50-57. 12. Berisha F, Feke GT, Trempe CL, McMeel JW, Schepens CL. Retinal abnormalities in early Alzheimer's disease. Invest Ophthalmol Vis Sci. 2007;48:2285-2289. 13. Kesler A, Vakhapova V, Korczyn AD, Naftaliev E, Neudorfer M. Retinal thickness in patients with mild cognitive impairment and Alzheimer's disease. Clin Neurol Neurosurg. 2011;113:523-526. 14. Shen Y, Shi Z, Jia R, Zhu Y, Cheng Y, Feng W, Li C. The attenuation of retinal nerve fiber layer thickness and cognitive deterioration. Front Cell Neurosci. 2013;7:142. 15. Shen Y, Liu L, Cheng Y, Feng W, Shi Z, Zhu Y, Wu W, Li C. Retinal nerve fiber layer thickness is associated with episodic memory deficit in mild cognitive impairment patients. Curr Alzheimer Res. 2014;11:259-266. Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Original Contribution 16. Ascaso FJ, Cruz N, Modrego PJ, Lopez-Anton R, Santabarbara J, Pascual LF. Retinal alterations in mild cognitive impairment and Alzheimer's disease: an optical coherence tomography study. J Neurol. 2014;261:1522-1530. 17. Leuba G, Saini K. Pathology of subcortical visual centres in relation to cortical degeneration in Alzheimer's disease. Neuropathol Appl Neurobiol. 1995;21:410-422. 18. Iseri PK, Altinaş O, Tokay T, Yüksel N. Relationship between cognitive impairment and retinal morphological and visual functional abnormalities in Alzheimer disease. J Neuroophthalmol. 2006;26:18-24. 19. Koromyo-Hamaoui M, Koronyo Y, Ljubimov AV, Miller CA, Ko MK, Black KL, Schwartz M, Farkas DL. Identification of amyloid plaques in retinas from Alzheimer's patients and noninvasive in vivo optical imaging of retinal plaques in a mouse model. Neuroimage. 2011;54(suppl 1):S204-S217. 20. Koromyo Y, Biggs D, Barron E, Boyer DS, Pearlman JA, Au WJ, Kile SJ, Blanco A, Fuchs DT, Ashfaq A, Frautschy S, Cole GM, Miller CA, Hinton DR, Verdooner SR, Black KL, Koronyo-Hamaoui M. Retinal amyloid pathology and proof-of-concept imaging trial in Alzheimer's disease. JCI Insight. 2017;2:e93621. 21. Kayabasi U, Sergott RC, Rispoli M. Retinal examination in the diagnosis of Alzheimer's disease. Int J Ophthalmic Pathol. 2014;3:4. 22. Cohen RM, Rezai-ZadehK, Weitz TM, Rentsendorj A, Gate D, Spivak I, Bholat Y, Vasilevko V, Glabe CG, Breunig JJ, Rakic P, Davtyan H, Agadjanyan MG, Kepe V, Barrio JR, Bannykh S, Szekely CA, Pechnick RN, Town T. Transgenic Alzheimer rat with plaques, tau pathology, behavioural impairment, oligomeric ab and frank neuronal loss. J Neurosci. 2013;33:6245-6256. 23. Tsuruma K, Tanaka Y, Shimazawa M, Hara H. Induction of amyloid precursor protein by the neurotoxic peptide, amyloidbet 25-30, cause retinal ganglion cell death. J Neurochem. 2010;113:1545-1554. 24. McKhann G, Drachman D, Folstein M, Katzman R, Price D, Stadlan EM. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's disease. Neurology. 1984;34:939-944. 25. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state." A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12:189-198. 26. Carlesimo GA, Caltagirone C, Gainotti G. The Mental Deterioration Battery: normative data, diagnostic reliability and qualitative analyses of cognitive impairment. The Group of Standardization of the Mental Deterioration Battery. Eur Neurol. 1996;36:378-384. 27. Giovagnoli AR, Del Pesce M, Mascheroni S, Simoncelli M, Laiacona M, Capitani E. Trail Making Test: normative values from 287 normal adult controls. Ital J Neurol Sci. 1996;17:305-309. 28. Spinnler H, Tognoni G. Standardizzazione e taratura italiana di test neuropsicologici: gruppo italiano per lo studio neuropsicologico dell'invecchiamento [in Italian]. Ital J Neurol Sci. 1987(suppl 8):1-120. 29. Orsini A, Grossi D, Capitani E, Laiacona M, Papagno C, Vallar G. Verbal and spatial immediate memory span: normative data from 1,355 adults and 1,112 children. Ital J Neurol Sci. 1987;8:539-548. Cipollini et al: J Neuro-Ophthalmol 2020; 40: 370-377 30. Coppola G, Di Renzo A, Ziccardi L, Martelli F, Fadda A, Manni G, Barboni P, Pierelli F, Sadun AA, Parisi V. Optical coherence tomography in Alzheimer's disease: a meta-analysis. PLoS One. 2015;10:e0134750. 31. Thomson KL, Yeo JM, Waddell B, Cameron JR, Pal S. A systematic review and meta-analysis of retinal nerve fiber layer change in dementia, using optical coherence tomography. Alzheimers Dement (Amst). 2015;1:136-143. 32. Choi SH, Park SJ, Kim NR. Macular ganglion cell -inner plexiform layer thickness is associated with clinical progression in mild cognitive impairment and Alzheimers disease. PLoS One. 2016;11:e0162202. 33. Oktem EO, Derle E, Kibaroglu S, Oktem C, Akkoyun I, Can U. The relationship between the degree of cognitive impairment and retinal nerve fiber layer thickness. Neurol Sci. 2015;36:1141-1146. 34. Khawaja AP, Chan MPY, Yip JLY, Broadway DC, Garway-Heath DF, Luben R, Hayat S, Matthews FE, Brayne C, Khaw KT, Foster PJ. Retinal nerve fiber layer measures and cognitive function in the EPIC-Norfolk cohort study. Invest Ophthalmol Vis Sci. 2016;57:1921-1926. 35. Gharbiya M, Trebbastoni A, Parisi F, Manganiello S, Cruciani F, D'Antonio F, De Vico U, Imbriano L, Campanelli A, De Lena C. Choroidal thinning as a new finding in Alzheimer's Disease: evidence from enhanced depth imaging spectral domain optical coherence tomography. J Alzheimers Dis. 2014;40:907-917. 36. Gao L, Liu Y, Li X, Bai Q, Liu P. Abnormal retinal nerve fiber layer thickness and macula lutea in patients with mild cognitive impairment and Alzheimer's disease. Arch Gerontol Geriatr. 2015;60:162-167. 37. Bulut M, Yaman A, Erol MK, Kurtuluş F, Toslak D, Do gan B, Çoban DT, Başar EK. Choroidal thickness in patients with mild cognitive impairment and Alzheimer's type dementia. J Ophthalmol. 2016;2016:7291257. 38. Amieva H, Mokri H, Le Goff M, Meillon C, Jacqmin-Gadda H, Foubert-Samier A, Orgogozo JM, Stern Y, Dartigues JF. Compensatory mechanisms in higher-educated subjects with Alzheimer's disease: a study of 20 years of cognitive decline. Brain. 2014;17:1167-1175. 39. den Haan J, Janssen SF, van de Kreeke JA, Scheltens P, Verbraak FD, Bouwman FH. Retinal thickness correlates with parietal cortical atrophy in early-onset Alzheimer's disease and controls. Alzheimers Dement (Amst). 2017;10:49-55. 40. Knoll B, Simonett J, Volpe NJ, Farsiu S, Ward M, Rademaker A, Weintraub S, Fawzi AA. Retinal nerve fiber layer thickness in amnestic mild cognitive impairment: case-control study and meta-analysis. Alzheimers Dement (Amst). 2016;4:85-93. 41. Lad EM, Mukherjee D, Stinnett SS, Cousins SW, Potter GG, Burke JR, Farsiu S, Whitson HE. Evaluation of inner retinal layers as biomarkers in mild cognitive impairment to moderate Alzheimer's disease. PLoS One. 2018;13:e0192646. 42. Shi Z, Wu Y, Wang M, Cao J, Feng W, Cheng Y, Li C, Shen Y. Greater attenuation of retinal nerve fiber layer thickness in Alzheimer's disease patients. J Alzheimers Dis. 2014;40:277- 283. 43. Liu D, Zhang L, Li Z, Zhang X, Wu W, Yang H, Min B, Zhang X, Ma D, Lu Y. Thinner changes of the retinal nerve fiber layer in patients with mild cognitive impairment and Alzheimer's disease. BMC Neurol. 2015;15:14. 377 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited.