Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 https://doi.org/10.1186/s13195-020-00602-9 RESEARCH Open Access Association between retinal thickness and β-amyloid brain accumulation in individuals with subjective cognitive decline: Fundació ACE Healthy Brain Initiative Marta Marquié1,2*, Sergi Valero1,2, Miguel Castilla-Marti3,4, Joan Martínez1, Octavio Rodríguez-Gómez1, Ángela Sanabria1,2, Juan Pablo Tartari1, Gemma C. Monté-Rubio1,2, Oscar Sotolongo-Grau1, Montserrat Alegret1,2, Alba Pérez-Cordón1, Natalia Roberto1, Itziar de Rojas1, Sonia Moreno-Grau1,2, Laura Montrreal1, Isabel Hernández1,2, Maitee Rosende-Roca1, Ana Mauleón1, Liliana Vargas1, Carla Abdelnour1, Silvia Gil1,2, Ester Esteban-De Antonio1, Ana Espinosa1,2, Gemma Ortega1,2, Francisco Lomeña5, Javier Pavia5, Assumpta Vivas6, Miguel Ángel Tejero6, Marta Gómez-Chiari6, Rafael Simó7,8, Andreea Ciudin7,8, Cristina Hernández7,8, Adelina Orellana1,2, Alba Benaque1, Agustín Ruiz1,2, Lluís Tárraga1,2, Mercè Boada1,2 and on behalf of the FACEHBI study group Abstract Background: Optical coherence tomography (OCT) of the retina is a fast and easily accessible tool for the quantification of retinal structural measurements. Multiple studies show that patients with Alzheimer’s disease (AD) exhibit thinning in several retinal layers compared to age-matched controls. Subjective cognitive decline (SCD) has been proposed as a risk factor for progression to AD. There is little data about retinal changes in preclinical AD and their correlation with amyloid-β (Aβ) uptake. Aims: We investigated the association of retinal thickness quantified by OCT with Aβ accumulation and conversion to mild cognitive impairment (MCI) over 24 months in individuals with SCD. Methods: One hundred twenty-nine individuals with SCD enrolled in Fundació ACE Healthy Brain Initiative underwent comprehensive neuropsychological testing, OCT scan of the retina and florbetaben (FBB) positron emission tomography (PET) at baseline (v0) and after 24 months (v2). We assessed the association of sixteen retinal thickness measurements at baseline with FBB-PET status (+/−) and global standardize uptake value ratio (SUVR) as a continuous measure at v0 and v2 and their predictive value on clinical status change (conversion to mild cognitive impairment (MCI)) at v2. (Continued on next page) * Correspondence: mmarquie@fundacioace.org 1 Research Center and Memory Clinic, Fundació ACE Institut Català de Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran Via Carles III, 85 bis, 08028 Barcelona, Spain 2 Centro de Investigación Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), Instituto de Salud Carlos III, Madrid, Spain Full list of author information is available at the end of the article © The Author(s). 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data. Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 2 of 14 (Continued from previous page) Results: Mean age of the sample was 64.72 ± 7.27 years; 62.8% were females. Fifteen participants were classified as FBB-PET+ at baseline and 22 at v2. Every 1 μm of increased thickness in the inner nasal macular region conferred 8% and 6% higher probability of presenting a FBB-PET+ status at v0 (OR = 1.08, 95% CI = 1.02–1.14, p = 0.007) and v2 (OR = 1.06, 95% CI = 1.02–1.11, p = 0.004), respectively. Inner nasal macular thickness also positively correlated with global SUVR (at v0: β = 0.23, p = 0.004; at v2: β = 0.26, p = 0.001). No retinal measurements were associated to conversion to MCI over 24 months. Conclusions: Subtle retinal thickness changes in the macular region are already present in SCD and correlate with Aβ uptake. Keywords: Optical coherence tomography, Retinal thickness, Subjective cognitive decline, β-Amyloid, Florbetaben, Positron emission tomography Introduction and synaptic loss, inflammation and vascular pathology In the past few decades, there has been an increase of [8]. Currently, it is possible to quantify in vivo the Aβ the global prevalence of dementia that is threatening the burden decades before cognitive symptoms arise using sustainability of healthcare systems worldwide. Alzhei- positron emission tomography (PET) imaging of the mer’s disease (AD), responsible for 60–70% of all de- brain with tracers against the amyloid protein [9] or by mentia cases, is a neurodegenerative condition that measuring Aβ1-42 and Aβ1-40 levels in the cerebrospinal progressively and irreversibly impairs cognition and re- fluid [10]. These tests have a good accuracy but are ei- sults in a complete loss of autonomy [1]. AD is the only ther quite expensive, invasive or not easily available in disorder among the 10 principal causes of mortality still most healthcare centres, thus not useful for population with no treatment or prevention [2]. Most AD cases are screening [11]. diagnosed once cognitive decline is already significant, The development of novel sensitive and specific bio- but it is known that identifying the disease at earlier markers is currently one of the main goals in the AD re- stages would result in cost savings and health benefits search field. In this sense, optical coherence tomography for patients, allowing them to modify their lifestyle, enrol (OCT) of the retina is a fast, inexpensive, non-invasive in clinical trials, access programs of cognitive stimula- and easily accessible tool used to diagnose and monitor tion and social resources and make decisions about their ocular pathologies such as diabetic retinopathy, open- future care. The disappointing results of clinical trials angle glaucoma and age-related macular degeneration testing drugs against AD indicate that these interven- [12]. Embryologically, the retina and optic nerve expand tions were implemented too late in the disease course from the diencephalon and are considered to be part of and acting on an earlier stage would increase the the central nervous system [13]. The retina shares many chances of success [3]. Consequently, there is an urgent structural and functional features with the brain, such as need to develop novel sensitive and specific biomarkers the presence of neurons and glial cells, endothelial cells for the early identification of asymptomatic individuals that form both the blood-brain and blood-retinal bar- at high risk for developing AD dementia before irrevers- riers [14], and axons of the optic nerve that connect the ible damage to the brain has been established and cogni- retina to the brain directly [15]. Thus, the retina is tive decline arises. In this regard, individuals with viewed as “a window to the brain” and is an attractive subjective cognitive decline (SCD) are a convenient tar- proxy to study brain biomarkers. In the past few years, get population for research studies on preclinical AD OCT retinal structural changes have been demonstrated [4]. SCD refers to the self-perception of cognitive prob- in several neurological diseases such as optic neuritis, lems, including memory loss, without impairment on multiple sclerosis, Parkinson’s disease and also AD [16]. standardized cognitive tests [4]. Longitudinal studies Degeneration of the retinal nerve fiber layer (RNFL) and have shown that elderly individuals with SCD have an the ganglion cell layer (GCL) [17] along with the pres- increased risk of progression to cognitive impairment ence of Aβ plaques [18] has been observed in AD post- and dementia [5], more functional deficits [6] and higher mortem tissue. Several studies have shown that patients prevalence of post-mortem AD pathology [7]. All these with AD dementia and mild cognitive impairment (MCI) data point to SCD being the earliest clinical detectable present with significant RNFL and GCL thinning mea- point of the AD clinical continuum. sured by OCT of the retina compared to healthy individ- Brain accumulation of amyloid-β (Aβ) plaques and uals [19], although these changes are non-AD specific tau-containing neurofibrillary tangles are the main and have also been observed in other degenerative disor- pathophysiological hallmarks of AD, along with neuronal ders such as chronic glaucoma. There is little data about Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 3 of 14 retinal structural changes in preclinical AD and their re- criteria were impairment in activities of daily living, lation with AD biomarkers. presence of psychiatric diagnosis, history of alcoholism In the present study, we aimed to determine whether or epilepsy, renal or liver failure, and severe auditory or baseline retinal structural measurements quantified by visual abnormalities. OCT were associated with Aβ deposition quantified by After 24 months (v2), FACEHBI participants were reas- florbetaben (FBB) PET and clinical changes over 24 sessed using the same neuropsychological battery. A diag- months in a cohort of individuals with SCD. nosis of MCI was established when any of the N-BACE test scores was impaired according to the published cut- Methods offs [23]. Study participants Participants were selected among 200 individuals with Neuro-ophthalmological examination SCD enrolled in Fundació ACE Healthy Brain Initiative At baseline, all participants underwent a neuro- (FACEHBI), a longitudinal observational study with the ophthalmological evaluation that lasted about 20 min goal of investigating the pathophysiology of preclinical and was performed by an optometrist. It comprised (1) AD and the role of SCD as a risk marker for the future anamnesis about past ophthalmological diseases and development of cognitive impairment [20]. FACEHBI treatments, (2) monocular visual acuity (VA) assessment participants were recruited from two different settings: using a pinhole occluder and the Early Treatment of Fundació ACE’s Memory Clinic [21] and the Open Diabetic Retinopathy Study (ETDRS) chart [32], (3) in- House Initiative (OHI) [22]. The OHI is a community- traocular pressure (IOP) measurement by Icare tonome- based engagement program that assesses cognitive status try [33] and (4) OCT of the retina scan. Reduced visual in individuals over 55 years for free and without the acuity was defined as a decimal scale score ≤ 0.4 (equiva- need of a physician’s referral. At baseline (v0) all partici- lent to standard logMAR 6/15) using the ETDRS chart pants underwent neurological and cognitive examina- [32]. High IOP was defined as ≥ 24 mmHg using Icare tions, including the neuropsychological battery of Tonometry [33]. Fundació ACE (N-BACE) [23, 24] and the Spanish ver- sion of the Face-Name Associative Memory Exam (S- Optical coherence tomography FNAME) [25, 26], a set of self-administered question- At baseline, participants were imaged with a 3D-OCT naires and a battery of multimodal biomarkers that in- Maestro®, Fast Map software version 8.40 (Topcon Co., cluded FBB-PET, brain magnetic resonance (MR), Tokyo, Japan). No pupil dilation was performed. OCT of apolipoprotein E (APOE) genotyping and OCT scan of the retina capture was combined with a real colour fun- the retina. dus picture obtained through an internal camera. FACEHBI inclusion criteria were as follows: age > 49 Retinal layer segmentation was performed using the years, education level of at least elementary school (6 Topcon Advanced Boundary Segmentation TM (TABS) years of formal education), score ≥ 8 on the Spanish algorithm as part of the Fast Map software [34]. Modified Questionnaire of Memory Failures in Everyday Three different OCT of the retina protocols were se- (MFE-30) [27], score ≥ 27 on the Spanish version of the lected for the analyses: peripapillary RNFL, macular Mini-Mental State Examination (MMSE) [28, 29], a ETDRS and macular multilayer (Fig. 1). The peripapil- strictly normal performance on the N-BACE [23, 24], lary RNFL protocol was performed using a circle scan Clinical Dementia Rating Score (CDR) [30] of 0 and around the optic disk and included five parameters: score < 11 on the Spanish version of the Hospital “total” refers to the average quantification of the whole Anxiety and Depression (HAD) Scale [31]. Exclusion region (360° measurement), “temporal” to the temporal Fig. 1 OCT of the retina imaging protocols. The three OCT retinal imaging protocols used for the analyses are depicted: a peripapillary RNFL, b macular ETDRS and c macular multilayer. Abbreviations: C centre, ETDRS Early Treatment Diabetic Retinopathy Study, GCL+ ganglion cell layer complex, I inferior, II inner inferior, IN inner nasal, IS inner superior, IT inner temporal, N nasal, RNFL retinal nerve fiber layer, OCT optical coherence tomography, OI outer inferior, ON outer nasal, OS outer superior, OT outer temporal, S superior, T temporal Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 4 of 14 quadrant thickness (316–45°), “superior” to the superior Ethical considerations quadrant thickness (46–135°), “nasal” to the nasal quad- A written consent was obtained from all participants rant thickness (136–225°) and “inferior” to the inferior prior to the enrolment in the study. The FACEHBI quadrant thickness (226–315°). The macular ETDRS protocol received approval from the ethics committee of protocol was obtained scanning a 6 × 6 mm area that was Hospital Clínic i Provincial in Barcelona, Spain divided in three regions: the “centre” region included the (EudraCT number 2014-00079-38). The referral centre innermost 1-mm ring, the “inner” region included the ethics committee approved the patient recruitment, and ring ranging from 1 to 3 mm and the “outer” region in- collection protocols were in accordance with ethical cluded the ring ranging from 3 to 6 mm. Whole retinal standards according to World Medical Association thickness measurements from nine macular sub-regions Declaration of Helsinki—Ethical Principles for Medical (centre, inner temporal, inner superior, inner nasal, Research Involving Human Subjects. inner inferior, outer temporal, outer superior, outer nasal and outer inferior) were obtained in the macular Statistical analysis ETDRS protocol. Lastly, the macular multilayer protocol Data processing and analysis were conducted using SPSS included thickness quantifications of the GCL complex v.24. Alpha level was set at 0.05. and RNFL in the whole macular region. Demographical differences between PET+/− and clin- OCT-derived data from the right eye were analysed. ical groups were assessed using a two-tailed T test for OCT retinal images were reviewed by a consultant oph- quantitative variables and a chi-square test for qualita- thalmologist expert in retinal pathology. OCT-related tive ones, respectively. exclusion criteria were the following: lack of collabor- Thicknesses of sixteen retinal regions at baseline were ation in the neuro-ophthalmological exam or OCT scan, considered as predictors of PET status (+/−) at v0 and OCT data obtained only from the left eye, presence of v2 and of clinical status (SCD vs MCI) at v2, separately. OCT artefacts and diseases that could affect retinal In order to detect the most significant regions and con- thickness (e.g. open-angle glaucoma and other neuropa- trol for false positives, all analyses were executed in two thies, maculopathies, prior retinal surgery, intraocular steps. pressure [IOP] ≥ 24 mmHg, high myopia [< − 6Dp] or Retinal thickness was analysed as predictor of PET sta- hyperopia [> + 6Dp] and optic nerve congenital tus at v0. First, several logistic regression models were abnormalities). executed (one for each region), with FBB-PET status as the outcome. Age, gender, years of education, APOE ε4 status and OCT of the retina image quality were in- FBB-PET image acquisition and processing cluded as adjusting variables. A second step was carried Previous to each FBB-PET scan, a MR was obtained out, including simultaneously those retinal measures that on a Siemens© Magneton Aera (Erlangen, Germany) obtained a significant effect in the former step, including at Clínica Corachan, Barcelona. FBB-PET scans were the same adjusting variables. acquired in a Siemens© Biograph molecular CT ma- The same sixteen retinal measures, regression model, chine at the Radiology Department from the Hospital adjusting variables and two-step strategy were employed Clínic i Provincial in Barcelona. Four scans of 5 min to analyse retinal thickness as predictor of PET status each were obtained 90 min after the injection of and clinical status at v2, separately. 300 MBq of [F18]-FBB (Neuraceq©), administered as All logistic models were reported as odds ratio (OR) a single slow intravenous bolus (6 s/ml, total volume with 95% confidence intervals, expressed as the probabil- 10 ml). FBB was kindly provided by Life Molecular ity of presenting a PET+ at v0 or v2 or converting to Imaging (previously Piramal). FBB data were co- MCI at v2 per each 1-μm retinal thickness change, registered to the MR-labelled data with the FSL 5.0 respectively. software package (https://fsl.fMRb.ox.ac.uk/fsl/fslwiki) Finally, we explored the association of PET expressed and FreeSurfer (https://surfer.nmr.mgh.harvard.edu). A as a quantitative variable with retinal thickness. For that, global cortical SUVR = 1.35 cut-off was selected to several linear regression models were run using log- classify subjects into PET +/− status [35]. As brain transformed FBB global SUVR as the outcome (one for amyloid uptake distribution among the study partici- each of the sixteen retinal measures as predictors), at v0 pants was not normally distributed, global SUVR and v2 separately. The same adjusting variables were in- quantifications were log transformed prior to their cluded. In a second step, those measures that were sig- use in the analyses. MR and PET images were ob- nificant in the former step were analysed simultaneously, tained in a 90-day window after clinical evaluations. including again the adjusting variables. More detailed information about MR and PET acqui- In all these statistical analysis, the goal of the first uni- sition can be found elsewhere [20]. variate step was to identify potential discriminant factors Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 5 of 14 (thickness of different retinal regions as predictors of and had lower MMSE scores (28.99 ± 99 vs 29.35, p = PET and clinical status, separately) that would then 0.008) than those comprising the final study sample. compete among them in a second multivariate step, in There were no statistical differences in years of educa- order to avoid a large number of predictors in the latter. tion, FBB global SUVR, gender, APOE ε4 status and No specific Bonferroni cut-off was imposed in the first clinical status at v2 (p > 0.05) between excluded and in- exploratory step, as this could have supposed the exclu- cluded participants. No significant differences in retinal sion of significant relevant factors in the final analysis, thickness were detected except in the inferior peripapil- which would have been “penalized” by high p signifi- lary RNFL region, where excluded participants showed cance values. significant thinning (122.17 ± 29.66 vs 132.74 ± 18.01, p = 0.008) (Additional file 1). Results The final sample consisted of 129 SCD individuals Demographic characteristics with available OCT of the retina at baseline and FBB- Two hundred individuals with SCD enrolled in PET at v0 and v2. Demographic characteristics of the FACEHBI underwent the baseline visit (v0) between cohort are detailed in Table 1. Mean age at v0 was December 2014 and March 2016. All participants but 64.72 ± 7.27 years, 62.8% were female, education was one completed the OCT retinal scan. Forty-three indi- 12.49 ± 3.94 years, MMSE score was 29.35 ± 0.88 and viduals were excluded from the analysis due to eye- 24.8% of the participants were APOE ε4 carriers. related pathologies that could potentially affect retinal At v0, SCD participants were classified according to a thickness measurements. Specific causes for exclusion FBB global SUVR cut-off = 1.35 as Aβ− (n = 114, 88.37%, were as follows: previous diagnosis of maculopathy (n = mean global SUVR = 1.17 ± 0.05) and Aβ+ (n = 15, 11) or open-angle glaucoma (n = 10), IOP ≥ 24 (n = 8), 11.63%, mean global SUVR = 1.57 ± 0.20) (Fig. 3a, d). amblyopia (n = 5), AMD (n = 2), other neuropathies (n = Aβ+ participants were significantly older (68.49 ± 4.76 vs 2), strabismus (n = 1), past eye surgery (n = 1) and others 64.22 ± 7.41, p = 0.03) and more frequently APOE ε4 (n = 3). Two individuals were excluded due to FBB-PET carriers (73.7% vs 18.4%, p < 0.001) than those Aβ−, technical reasons. Finally, 25 participants dropped out while there were no differences in gender, education and before v2. The study flow chart is depicted in Fig. 2. MMSE scores (Table 1). Those 71 participants excluded from the study were sig- At v2, 7 participants (6.14%) converted to an Aβ+ sta- nificantly older (67.36 ± 7.20 vs 64.72 ± 7.27, p = 0.01) tus. The sample was divided into Aβ− (n = 107, 82.95%, Fig. 2 Study flow chart. Eligible FACEHBI participants and selection for the final study sample through inclusion and exclusion criteria. Abbreviations: AMD age-related macular degeneration, FACEHBI Fundació ACE Healthy Brain Initiative, FBB florbetaben, IOP intraocular pressure, OCT optical coherence tomography, PET positron emission tomography, v0 baseline visit, v2 2-year follow-up visit Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 6 of 14 Table 1 Demographic characteristics of the study cohort PET status at v0 PET status at v2 Clinical status at v2 Aβ− Aβ+ p Aβ− Aβ+ p SCD MCI p n 114 15 N/A 107 22 N/A 114 15 N/A Age 64.22 ± 7.41 68.49 ± 4.76 0.03* 65.70 ± 7.29 70.82 ± 5.48 0.002* 65.76 ± 6.77 72.73. ± 8.12 < 0.001* Females (%) 71 (62.3%) 10 (66.7%) 0.74 68 (63.55%) 13 (59.1%) 0.69 72 (63.16%) 9 (60%) 0.85 Years of education 12.58 ± 3.94 11.80 ± 3.99 0.48 12.56 ± 3.91 12.14 ± 4.16 0.65 12.80 ± 3.86 10.07 ± 3.83 0.01* MMSE 29.32 ± 0.90 29.53 ± 0.74 0.39 29.22 ± 1.03 29.11 ± 1.32 0.72 29.33 ± 0.88 28.25 ± 1.82 0.06 APOE ε4+ (%) 21 (18.4%) 11 (73.7%) < 0.001* 21 (19.6%) 11 (50%) 0.003* 24 (21.05%) 8 (53.3%) 0.007* A T test was used to analyse differences on age, years of education and MMSE between groups. A Chi-square test was employed to analyse differences on the distribution of females and APOE genotype between groups *Statistical significance was set-up at p < 0.05 Abbreviations: Aβ amyloid-β, APOE apolipoprotein E, MMSE Mini-Mental State Examination, PET positron emission tomography, MCI mild cognitive impairment, SCD subjective cognitive decline, v0 baseline visit, v2 2-year follow-up visit mean global SUVR = 1.19 ± 0.06) and Aβ+ (n = 22, (53.5% vs 21.05%, p = 0.007) than those who remained as 17.05%, mean global SUVR = 1.61 ± 0.28) groups (Fig. 3b, SCD (Table 1). Not unexpectedly, there was not a per- e). Aβ+ participants were significantly older (70.82 ± 5.48 fect overlap between conversion to MCI and Aβ+ status: vs 65.70 ± 7.29, p = 0.002) and more frequently APOE ε4 out of the 15 MCI converters, only 5 were Aβ+ at v0 carriers (50% vs 19.4%, p = 0.003) than those who were and 6 at v2. Aβ−, while there were no differences in gender, educa- Regarding the study settings, 90 participants (69.77%) tion and MMSE scores (Table 1). were recruited through the OHI and 39 (30.23%) At v2, 15 participants converted from SCD to MCI ac- through the Memory Clinic. Individuals from the latter cording to their neuropsychological profile (Fig. 3c). group were significantly older (66.89 ± 7.99 vs 63.77 ± Eight of them had an amnestic subtype and 7 a non- 6.76, p = 0.025) and had a higher risk of MCI conversion amnestic subtype MCI. Those who converted were sig- over 24 months (23.01% vs 6.67%, p = 0.008). FBB global nificantly older (72.73 ± 8.12 vs 65.76 ± 6.77, p < 0.001), SUVR differences were borderline significant, with par- had less years of education (10.07 ± 3.83 vs 12.80 ± 3.86, ticipants from the Memory Clinic having higher SUVR p = 0.01) and were more frequently APOE ε4 carriers (1.27 ± 0.23 vs 1.20 ± 0.10, p = 0.06). There were no Fig. 3 FBB-PET and clinical status of the study participants. The red dashed vertical line in d and e represents the global SUVR cut-off value of 1.35 [35]. Abbreviations: FBB florbetaben, PET positron emission tomography, SUVR standardized uptake value ratio, v0 baseline visit, v2 2-year follow-up visit Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 7 of 14 differences in terms of gender, education, MMSE scores increased in Aβ+ individuals. No apparent group differ- and APOE ε4 status (Additional file 2). ences were observed in other retinal regions. The logistic regression model showed, in the initial step, that five macular sub-areas of the ETDRS chart Association of retinal thickness measurements with FBB- had an independent significant effect on FBB-PET status PET status at v0 (centre: OR = 1.04, p = 0.03; inner temporal: OR = Correlations of retinal thickness among the sixteen re- 1.06, p = 0.03; inner superior: OR = 1.05, p = 0.047; inner gions selected are shown in Additional file 3. As ex- nasal: OR = 1.08, p = 0.007; and inner inferior: OR = 1.05, pected, the within-region correlations were high, while p = 0.04) and v2 (centre: OR = 1.03, p = 0.03; inner tem- correlations between different regions were low to poral: OR = 1.05, p = 0.03; inner superior OR = 1.05, p = moderate. 0.02; inner nasal: OR = 1.06, p = 0.004; and inner inferior: Thickness measurements from the sixteen retinal re- OR = 1.05, p = 0.02) (Table 3). gions from the Aβ− and Aβ+ groups at v0 and v2 and In a subsequent multivariate analysis, those five macu- from the SCD and MCI groups at v2, respectively, are lar regions selected in the former step were analysed to- depicted in Table 2. Raw data showed that Aβ+ partici- gether competing with education, gender, age, APOE ε4 pants had lower peripapillary RNFL thickness measures status and OCT retinal image quality as adjusting covari- at v0, and this difference was amplified at v2. On the ates, at v0 and v2 separately. Only macular inner nasal contrary, inner macular thickness appeared to be thickness remained as significant predictor of FBB-PET Table 2 Retinal thickness measurements by PET and clinical status PET status (+/−) at v0 PET status (+/−) at v2 Clinical status at v2 Aβ− Aβ+ Aβ− Aβ+ SCD MCI n 114 15 107 22 114 15 FBB global SUVR 1.17 ± 0.05 1.57 ± 0.20 1.19 ± 0.06 1.61 ± 0.28 1.24 ± 0.16 1.41 ± 0.39 Peripapillary RNFL Total 100.74 ± 11.84 96.90 ± 19.38 101.27 ± 11.33 95.55 ± 18.40 100.123 ± 13.24 101.56 ± 10.24 Temporal 74.02 ± 10.67 74.23 ± 15.23 74.33 ± 10.60 72.64 ± 14.05 73.84 ± 11.20 75.58 ± 11.62 Superior 118.05 ± 19.75 118.27 ± 18.64 118.85 ± 18.46 114.14 ± 24.59 118.05 ± 19.91 118.26 ± 17.31 Nasal 77.57 ± 16.28 74.24 ± 17.82 77.96 ± 15.75 73.45 ± 19.37 77.16 ± 16.77 77.41 ± 14.02 Inferior 133.28 ± 17.62 128.62 ± 21.0 133.89 ± 17.82 127.14 ± 18.31 132.44 ± 18.50 134.97 ± 14.04 Image quality 47.41 ± 7.42 46.87 ± 7.42 47.52 ± 7.48 46.50 ± 7.02 47.99 ± 7.12 42.44 ± 7.78 ETDRS macula Centre 249.67 ± 21.63 259.91 ± 23.14 249.07 ± 21.56 259.59 ± 22.32 250.03 ± 22.09 257.18 ± 20.63 Inner temporal 300.01 ± 15.72 305.52 ± 15.55 299.56 ± 15.15 305.91 ± 17.76 300.10 ± 15.63 304.80 ± 16.48 Inner superior 312.32 ± 14.54 316.96 ± 18.05 311.74 ± 14.11 318.30 ± 18.07 312.43 ± 14.83 316.14 ± 16.24 Inner nasal 313.41 ± 14.26 321.38 ± 17.62 312.81 ± 13.64 321.71 ± 18.29 313.80 ± 14.89 318.35 ± 14.25 Inner inferior 309.64 ± 14.37 316.04 ± 18.48 309.14 ± 13.87 316.46 ± 18.60 309.64 ± 14.49 316.05 ± 17.70 Outer temporal 254.28 ± 14.26 250.72 ± 15.70 254.22 ± 14.10 252.15 ± 16.11 253.75 ± 14.00 254.75 ± 17.81 Outer superior 269.66 ± 12.92 266.47 ± 16.49 269.48 ± 12.90 268.36 ± 15.65 269.28 ± 12.84 269.34 ± 17.27 Outer nasal 285.87 ± 14.42 288.58 ± 18.38 285.80 ± 14.03 288.05 ± 18.71 285.65 ± 14.16 290.20 ± 19.58 Outer inferior 258.75 ± 13.50 260.79 ± 20.32 258.85 ± 13.69 259.62 ± 17.67 258.43 ± 13.45 263.23 ± 20.12 Image quality 47.60 ± 6.94 48.68 ± 6.40 47.76 ± 7.01 47.55 ± 6.26 48.53 ± 6.36 41.63 ± 7.70 Macular multilayer GCL+ 64.32 ± 4.85 64.47 ± 4.54 64.36 ± 4.79 64.22 ± 4.94 64.42 ± 4.60 63.68 ± 6.25 RNFL 38.02 ± 4.39 39.62 ± 4.96 38.06 ± 4.42 39.93 ± 4.74 38.17 ± 4.37 38.41 ± 5.31 Image quality 47.06 ± 6.94 50.04 ± 5.95 47.19 ± 7.02 48.48 ± 6.17 47.62 ± 6.82 45.80 ± 7.33 Data were expressed as mean ± standard deviation. OCT retinal measurements were expressed as thickness (μm) except for image quality Abbreviations: Aβ amyloid-β, FBB florbetaben, ETDRS Early Treatment Diabetic Retinopathy Study, GCL ganglion cell layer, MCI mild cognitive impairment, PET positron emission tomography, RNFL retinal nerve fiber layer, SCD subjective cognitive decline, SUVR standardized uptake value ratio, v0 baseline visit, v2 follow- up visit at 2 years Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 8 of 14 Table 3 Logistic regression model output of the association of retinal thickness measurements at baseline with PET status at v0 and v2 and clinical status change over 24 months Retinal regions PET status at v0 PET status at v2 Clinical status at v2 Wald OR 95% CI p Wald OR 95% CI p Wald OR 95% CI p Peripapillary RNFL Total 0.69 0.98 0.94–1.03 0.39 2.76 0.97 0.94–1.01 0.10 2.38 1.06 0.98–1.14 0.12 Temporal 0.60 1.03 0.96–1.10 0.44 0.14 0.99 0.94–1.04 0.71 2.81 1.06 0.99–1.14 0.09 Superior 0.37 1.01 0.98–1.05 0.54 0.26 0.99 0.97–1.02 0.61 1.04 1.02 0.98–0.16 0.31 Nasal 1.19 0.98 0.95–1.02 0.28 1.93 0.98 0.95–1.00 0.17 0.03 1.00 0.96–1.05 0.87 Inferior 0.13 0.99 0.96–1.03 0.72 1.18 0.98 0.96–1.01 0.28 3.08 1.04 1.00–1.09 0.08 ETDRS macula Centre 4.93 1.04 1.01–1.08 0.03* 4.98 1.03 1.00–1.06 0.03* 2.11 1.03 0.99–1.06 0.15 Inner temporal 4.88 1.06 1.01–1.12 0.03* 4.82 1.05 1.01–1.09 0.03* 1.48 1.03 0.98–1.08 0.23 Inner superior 3.93 1.05 1.01–1.10 0.047* 5.54 1.05 1.00–1.09 0.02* 1.48 1.03 0.98–1.08 0.22 Inner nasal 7.20 1.08 1.02–1.14 0.007* 8.39 1.06 1.02–1.10 0.004* 1.33 1.03 0.98–1.07 0.25 Inner inferior 4.14 1.05 1.00–1.10 0.04* 5.60 1.05 1.01–1.09 0.02* 2.34 1.04 0.99–1.09 0.13 Outer temporal 0.52 1.02 0.97–1.07 0.47 0.22 1.01 0.97–1.05 0.64 1.26 1.03 0.98–1.09 0.26 Outer superior 0.11 1.00 0.96–1.06 0.74 0.21 1.01 0.97–1.05 0.65 0.73 1.02 0.97–1.08 0.39 Outer nasal 2.47 1.04 0.99–1.08 0.12 1.70 1.02 0.99–1.06 0.19 2.60 1.04 0.99–1.08 0.11 Outer inferior 2.87 1.04 0.99–1.09 0.09 1.52 1.02 0.99–106 0.22 3.63 1.05 1.00–1.11 0.06 Macular multilayer GCL+ 2.22 1.12 0.96–1.31 0.14 1.65 1.08 0.96–1.21 0.20 0.76 1.07 0.92–1.24 0.38 RNFL 2.35 1.12 0.97–1.30 0.13 1.05 1.06 0.95–1.19 0.31 0.32 1.04 0.91–1.20 0.58 A 2-step logistic regression model was executed for each of the sixteen retinal thickness measures as predictors of PET status (+/−) at v0 and v2 and clinical status (SCD vs MCI) at v2, separately, and including age, gender, education, APOE ε4 status and OCT image quality as adjusting variables *Statistical significance was set-up at p < 0.05 Abbreviations: APOE apolipoprotein E, CI confidence interval, ETDRS Early Treatment Diabetic Retinopathy Study, GCL ganglion cell layer, OR odds ratio, PET positron emission tomography, RNFL retinal nerve fiber layer, v0 baseline visit, v2 follow-up visit at 2 years status at both v0 and v2 (Table 4). The obtained model The macular regions selected in the former step were showed that every 1 μm of increased thickness in the then analysed together competing with the same covari- inner nasal macular region conferred a 8% and 6% ates (Table 6). Only inner nasal macular thickness higher probability of presenting a PET+ at v0 and v2, re- remained significantly associated with FBB global SUVR. spectively (at v0: OR = 1.08, p = 0.007; at v2: OR = 1.06, The model showed that increased thickness in the inner p = 0.004) (Fig. 4a, b). nasal macular region was associated with higher FBB global SUVR both at baseline and after 24 months (at v0: Association of retinal thickness measures with FBB global β = 0.23, p = 0.004; at v2: β = 0.26, p = 0.001) (Fig. 4c, d). SUVR A linear regression analysis was used to assess the asso- Association of retinal thickness measurements with ciation of sixteen selected retinal thickness measures clinical status change at v2 with log-transformed FBB global SUVR at v0 and v2 re- Thickness measurements from the sixteen selected ret- spectively, including education, gender, age, APOE ε4 inal regions divided by clinical status (SCD vs MCI) at status and OCT retinal image quality as covariates v2 are shown in Table 2. (Table 5). The model identified that the thickness of four A logistic regression model was run to analyse the in- macular sub-regions was significantly and positively re- dependent predictive value of the sixteen retinal thick- lated to global SUVR at v0 (centre: β = 0.19, p = 0.02; ness measures on the clinical status at v2 (Table 3). inner nasal: β = 0.23, p = 0.004; inner inferior: β = 0.18, None of the retinal thickness measures analysed had a p = 0.03; and outer inferior: β = 0.18, p = 0.03) and five significant effect on conversion to MCI over 24 months. macular regions at v2 (centre: β = 0.18, p = 0.03; inner superior: β = 0.18, p = 0.03; inner nasal: β = 0.26, p = Discussion 0.001; inner inferior: β = 0.20, p = 0.01; and outer infer- In this study, we analysed the association of retinal ior: β = 0.19, p = 0.03). structural measurements with Aβ brain accumulation in Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 9 of 14 Table 4 Logistic regression model output of the association of macular retinal thickness with PET status at v0 and v2 PET status at v0 PET status at v2 Wald p OR 95% CI Wald p OR 95% CI Years of education 0.003 0.96 1.01 0.84–1.02 0.32 0.57 1.04 0.90–1.21 Gender 0.79 0.37 0.50 0.11–2.29 1.15 0.28 0.52 0.16–1.72 Age 7.00 0.008* 1.20 1.05–1.37 9.59 0.002* 1.17 1.06–1.29 APOE ε4 status 16.03 < 0.001* 32.06 5.87–175.25 10.26 0.001* 6.65 2.09–21.22 OCT retinal image quality 4.03 0.05 1.16 1.00–1.33 1.51 0.22 1.06 0.97–1.16 Inner nasal macular thickness 7.20 0.007* 1.08 1.02–1.14 8.39 0.004* 1.06 1.02–1.11 The five retinal regions that obtained a significant effect in the previous step of the logistic regression model (ETDRS macular centre, inner temporal, inner superior, inner nasal and inner inferior areas) were subsequently analysed together, including education, gender, age, APOE ε4 status and OCT retinal image quality as adjusting variables, separately for v0 and v2. Only inner nasal macular thickness remained as a significant predictor of PET status at v0 and v2, and the obtained model showed that increased thickness in this region at baseline conferred higher probability of a PET status both at v0 and v2 *Statistical significance was set-up at p < 0.05 Abbreviations: APOE apolipoprotein E, CI confidence interval, ETDRS Early Treatment Diabetic Retinopathy Study, OCT optical coherence tomography, OR odds ratio, PET positron emission tomography, v0 baseline visit, v2 follow-up visit at 2 years 129 individuals with SCD. Our data identified a signifi- months. The diagnosis of SCD involves the self- cant thickening of the inner nasal macular region in very perception of cognitive problems with a strictly normal early AD stages (SCD Aβ+ individuals) and a positive as- performance on a comprehensive neuropsychological sociation between thickness in this same region and FBB battery and preservation of autonomy in daily life activ- global SUVR. However, retinal thickness did not predict ities [4]. At baseline, 15 participants were classified as conversion to MCI over 24 months. Aβ+ using a FBB global SUVR cut-off = 1.35 [35]. As our Our study cohort included 129 participants from the cohort was comprised of SCD, which has been proposed FACEHBI study with SCD who underwent FBB-PET as the earliest symptom of the AD continuum, and we and OCT of the retina scan at baseline and after 24 aimed to identify the very initial stages of amyloid Fig. 4 Relationship between inner nasal macular thickness and FBB-PET. Inner nasal macular thickness differences according to the participants’ FBB-PET status (+/−) at v0 (a) and at v2 (b). Correlation between inner macular thickness and FBB global SUVR at v0 (c) and at v2 (d). Both inner nasal macular thickness and FBB global SUVR are expressed as standardized scores after adjustment by age, gender, education, APOE ε4 status and OCT image quality. Abbreviations: APOE apolipoprotein E, FBB Flobetaben, PET positron emission tomography, SUVR standardized uptake value ratio, v0 baseline visit, v2 2-year follow-up visit Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 10 of 14 Table 5 Linear regression analysis output of the association of retinal thickness at baseline with FBB global SUVR at v0 and v2 Retinal regions FBB global SUVR at v0 FBB global SUVR at v2 B 95% CI t β p B 95% CI t β p Peripapillary RNFL Total − 0.001 − 0.001–0.000 − 1.87 − 0.16 0.06 − 0.001 − 0.001–0.000 − 1.66 − 0.14 0.10 Temporal 0.000 − 0.001–0.001 − 1.28 − 0.11 0.20 0.000 − 0.001–0.000 − 1.03 − 0.09 0.31 Superior 0.000 0.000–0.000 − 0.27 − 0.02 0.79 0.000 0.000–0.000 − 0.12 − 0.12 0.91 Nasal 0.000 − 0.001–0.000 − 1.38 − 0.11 0.17 0.000 − 0.001–0.000 − 1.42 − 0.12 0.16 Inferior 0.000 0.000–0.000 − 0.31 − 0.03 0.76 0.000 − 0.001–0.000 − 0.40 − 0.03 0.69 ETDRS macula Centre 0.000 0.000–0.001 2.37 0.19 0.02* 0.000 0.000–0.001 2.17 0.18 0.03* Inner temporal 0.000 0.000–0.001 1.86 0.15 0.07 0.001 0.000–0.001 1.95 0.16 0.05 Inner superior 0.001 0.000–0.001 1.76 0.14 0.08 0.001 0.000–0.001 2.18 0.18 0.03* Inner nasal 0.001 0.000–0.001 2.95 0.23 0.004* 0.001 0.000–0.002 3.27 0.26 0.001* Inner inferior 0.001 0.000–0.001 2.23 0.18 0.03* 0.001 0.000–0.001 2.55 0.20 0.01* Outer temporal 0.000 0.000–0.001 0.62 0.05 0.54 0.000 − 0.001–0.001 0.37 0.03 0.71 Outer superior 0.000 0.000–0.001 0.54 0.05 0.59 0.000 0.000–0.001 0.82 0.07 0.41 Outer nasal 0.000 0.000–0.001 1.25 0.10 0.21 0.001 0.000–0.001 1.65 0.13 0.10 Outer inferior 0.001 0.000–0.001 2.22 0.18 0.03* 0.001 0.000–0.001 2.25 0.19 0.03* Macular multilayer GCL+ 0.001 − 0.001–0.003 1.05 0.09 0.30 0.001 − 0.001–0.003 0.86 0.08 0.39 RNFL 0.001 − 0.001–0.002 0.91 0.07 0.37 0.001 − 0.001–0.003 1.03 0.08 0.30 A linear regression model for each of the sixteen retinal thickness measures was executed using log-transformed FBB global SUVR as the outcome, for v0 and v2 separately. In all analysis age, gender, education, APOE ε4 status and OCT retinal image quality were included as covariates *Statistical significance was set-up at p < 0.05 Abbreviations: APOE apolipoprotein E, CI confidence interval, ETDRS Early Treatment Diabetic Retinopathy Study, FBB florbetaben, GCL ganglion cell layer complex, OCT optical coherence tomography, OR odds ratio, RNFL retinal nerve fiber layer, SUVR standardized uptake value ratio, v0 baseline visit, v2 follow-up visit at 2 years accumulation, we chose a liberal/low cut-off to divide that amyloid positivity increases with age [39]), the def- the sample. In spite of this, the resulting 11.63% rate of inition of cognitive normality (our study used strict Aβ positivity is slightly lower than those reported in neuropsychological criteria, such that only one score other series [36–38]. Several reasons could account for below the established cut-offs in any single N-BACE this, including the mean age of the sample (our study [23] test precluded an individual to be classified as SCD) participants were relatively young, while it is well known and finally the setting of the study (70% of our sample Table 6 Linear regression analysis output of the association of retinal thickness with FBB global SUVR at v0 and v2 Log-transformed FBB global SUVR at v0 Log-transformed FBB global SUVR at v2 B 95% CI t β p B 95% CI t β p Years of education 0.001 − 0.001–0.003 1.04 0.09 0.30 0.001 − 0.001–0.003 0.81 0.07 0.42 Gender 0.000 − 0.016–0.016 − 0.04 − 0.002 0.98 0.001 − 0.019–0.021 0.10 0.008 0.92 Age 0.001 0.000–0.003 2.70 0.23 0.008* 0.002 0.001–0.004 3.30 0.28 0.004* APOE ε4 status 0.044 0.027–0.061 5.16 0.41 < 0.001* 0.049 0.028–0.070 4.60 0.37 < 0.001* OCT image quality 0.001 0.000–0.002 1.73 0.14 0.09 0.001 0.000–0.002 1.41 0.11 0.16 Inner nasal macular thickness 0.001 0.000–0.001 2.95 0.23 0.004* 0.001 0.000–0.002 3.27 0.26 0.001* A second step of the linear regression model was executed with log-transformed FBB global SUVR as the outcome, including simultaneously the regions with a significant effect in the previous step (macular ETDRS centre, inner nasal, inner inferior and outer inferior areas for v0, and macular ETDRS centre, inner nasal, inner superior, inner inferior and outer inferior areas for v2) as predictors, separately. In all analysis, years of education, gender, age, APOE ε4 status and OCT retinal image quality were included as adjusting covariates. The output model showed that only retinal thickness in the inner nasal macular sub-region was positively associated with global SUVR, both at v0 and v2 *Statistical significance was set-up at p < 0.05 Abbreviations: APOE apolipoprotein E, FBB florbetaben, CI confidence interval, ETDRS Early Treatment Diabetic Retinopathy Study, OCT optical coherence tomography, OR odds ratio, RNFL retinal nerve fiber layer, SUVR standardized uptake value ratio, v0 baseline visit, v2 visit at 2 years Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 11 of 14 came from the OHI vs 30% from the Memory Clinic). A In line with our findings showing retinal thickening in recent multicentric study highlighted that the risk of de- the pre-dementia AD phase, Snyder et al. reported that mentia is strongly increased in SCD individuals from a the surface area of inclusion bodies increased as a func- clinical setting but less in a community-based setting [40]. tion of amyloid burden in a group of 63 cognitively In line with that, our participants from the Memory Clinic healthy individuals with a trend toward a selective vol- were significantly older and had higher risk of converting ume increase in the inner plexiform layer in Aβ+ indi- to MCI and a trend to higher FBB global SUVR. viduals (n = 10) compared to those Aβ− (n = 53) [47]. The main finding of the study is that structural retinal Ascaso et al. showed an increase of macular thickness changes are already present in preclinical AD stages and and volume in 21 MCI patients compared to 18 AD and can be detected by OCT. Our data showed that Aβ+ 41 healthy individuals [48]. In the twin study published SCD participants exhibited a significant thickening of by van de Kreet et al. reported above, a positive associ- the inner nasal macular region at baseline even after ation between flutemetamol uptake and inner macular controlling for age, gender, education, APOE ε4 status thickness was observed, although did not remain signifi- and OCT retinal image quality, both at baseline and cant after multiple testing correction [46]. after 24 months. Additionally, RNFL thinning in Aβ+ Most of these studies reported exclusively cross- participants was observed at v2, although its difference sectional OCT of the retina data. Resembling our design, compared to those Aβ− did not reach statistical Santos et al. reported longitudinal OCT of the retina significance. and Aβ-PET data over 27 months [49]. A decrease in Our results do not completely concur with those of macular RNFL volume was demonstrated in the preclin- similar studies. Of note, few groups have investigated ical AD group (n = 15) compared to controls (n = 41) the relationship between retinal thickness and Aβ and this change was related to Aβ deposition, while accumulation in non-demented individuals and most GCL volume change was related to age but not to amyl- articles included a relatively low number of partici- oid burden. pants, reported only cross-sectional data and consid- Our study design did not allow us to explain the erably inconsistent findings regarding the regions and underlying pathological changes of the macular thicken- direction of retinal changes (thinning vs thickening) ing observed in Aβ+ individuals, as we could not directly associated with Aβ deposition. In order to correctly assess in vivo the presence of Aβ in the retina, we did interpret OCT of the retina literature results in the not have other AD-related biomarkers apart from FBB- dementia field, it is important to have in mind that PET, neither we had autopsy data available. However, retinal thickness data obtained from different OCT we can speculate that a plausible explanation for the ini- devices are not readily interchangeable and it is tial macular thickening in Aβ+ individuals could be the relevant to know the average thickness and volumes accumulation of amyloid deposits in the retina, as it has obtained from the particular OCT device used in each been reported in AD transgenic mouse models [18], study, which are known to be influenced by age, post-mortem human AD brain tissue [13] and using gender and ocular pathologies [41]. Additionally, two in vivo fluorescent imaging on human retinas from AD previous studies from our own group highlighted that patients [47]. OCT retinal image quality significantly differs among Another explanation could be the presence of neuroin- SCD, MCI and dementia groups and is an important flammation, which is an uncontrolled microglia and predictor of OCT retinal image variability within astroglia activation in the brain in response to failures in these populations [42, 43]. Still, most studies in the homeostasis and tissue damage related to Aβ and tau de- dementia field do not include OCT retinal image position. Neuroinflammation takes place in the retina as quality as a covariate in the analysis, while our data well as in the brain and results in hypertrophy of neu- show that it would be advisable to do so. Thus, com- rons and glial cells [50]. While the RNFL is made up paring results from the literature should be done with largely of axons, the macula mostly contains the cell caution. somas [51]. Thus, the oedema secondary to glial cell ac- Golzan et al. observed a slight GCL thinning in 28 AD tivation in the macula could account for the selective dementia patients compared to 50 Aβ− controls but no thickening in this retinal region observed in the SCD differences with preclinical AD individuals [44]. O’Bry- Aβ+ group. him et al. detected an increase in the foveal avascular Raw OCT retinal data additionally showed that Aβ+ zone area and a reduction in the inner foveal thickness participants experienced thinning of the peripapillary in an Aβ+ group (n = 14) compared to 16 controls [45]. RNFL at v2, although differences did not reach statistical Recently, van de Kreeke et al. did not detect differences significance after accounting for covariates. This finding in macular or RNFL thickness between 18 Aβ+ and 147 could be due to the onset of atrophy in the optic nerve Aβ− healthy elderly monozygotic twins [46]. after 24 months in our cohort. Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 12 of 14 Over 24 months, 15 participants who were initially Supplementary information diagnosed as SCD converted to MCI. It is important Supplementary information accompanies this paper at https://doi.org/10. 1186/s13195-020-00602-9. to mention that in our study a diagnosis of MCI only required performing under normality in one of the N- Additional file 1. Differences between excluded and included BACE battery subtests [23]. Not all the MCI con- participants. Table with demographical, clinical, FBB-PET and OCT differ- verters experienced memory impairment neither the ences between those 71 participants excluded from the study and those 129 included in the final sample. A T-test was used to analyse differences suspected underlying aetiology for their cognitive defi- on age, years of education, MMSE scores, global SUVR at v0 and all OCT- cits was AD. Besides, a few of them returned to a derived thickness measurements between groups. A Chi-Square test was SCD status in the next follow-up study visit (v3), employed to analyse differences on the distribution of females, APOE genotype, FBB-PET+ at v0 and converters to MCI at v2 between groups. pointing to non-degenerative MCI causes, such as *Statistical significance was set-up at p < 0.05. Abbreviations: APOE = apo- psychological disorders. In line with that, and not un- lipoprotein E; MMSE = mini-mental state examination; PET = positron expectedly, the MCI converter status did not perfectly emission tomography; MCI = mild cognitive impairment; v0 = baseline visit; v2 = 2y follow-up visit. overlap with PET status (only 5 and 6 of MCI con- Additional file 2. Differences between participants coming from the verters were PET+ at v0 and v2, respectively). Prob- Memory Clinic and those from the Open House Initiative. Description: ably due to these reasons, we could not detect retinal Demographical, clinical and FBB-PET differences between participants thickness differences between SCD and MCI partici- coming from the Memory Clinic and those from the Open House Initia- tive. A T-test was used to analyse differences on age, years of education, pants at v2. In this regard, our data point to amyloid MMSE scores, and global SUVR at v0. A Chi-Square test was employed to accumulation being a closer endophenotype to the analyse differences on the distribution of females, APOE genotype, FBB- underlying degeneration occurring in very early stages PET+ at v0 and converters to MCI at v2 between groups. *Statistical sig- nificance was set-up at p < 0.05. Abbreviations: APOE = apolipoprotein E; of AD, when cognitive changes are still very subtle. MMSE = mini-mental state examination; MCI = mild cognitive impairment; Moreover, the neuropsychological battery used in this OHI = Open House Initiative; v0 = baseline visit; v2 = 2y follow-up visit. study [23] is optimized to detect a more profound Additional file 3. Matrix of correlations of retinal thickness in multiple cognitive deterioration later in time, but it might be retinal regions. Description: Values over the diagonal line represent raw Peason’s r correlations between retinal measurements. Values below the insensitive to the cognitive changes that occur during diagonal line represent Pearson’s r correlations between retinal the prodromal stages of AD. measurements adjusted by age, gender, years of education, APOE status We acknowledge that our study has several and OCT image quality. Statistical significance was set-up at p < 0.05* and < 0.01**. Abbreviations: ETDRS = Early Treatment for Diabetes Retin- strengths and limitations. The strengths include the opathy Study; GCL = ganglion cell layer; RNFL = retinal nerve fiber layer. use of biomarkers to identify preclinical AD, the de- tailed characterization of the study participants and Acknowledgements the use of age, gender, education, OCT retinal image We acknowledge all participants from the FACEHBI study. We thank the quality and APOE ε4 as covariates. Limitations in- investigators from Fundació ACE Barcelona Alzheimer Treatment and clude the relatively small sample size (especially for Research Center, Hospital Clinic and Clínica Corachan for their close collaboration and continuous intellectual input. We also thank Topcon for its the subgroup with abnormal Aβ), the short follow-up reliability as a technological partner and Life Molecular Imaging for providing period, the use of PET imaging instead of CSF to de- the florbetaben compound for PET scanning. termine early Aβ positivity, the use of a convenience Collaborators: The FACEHBI study group: N. Aguilera, M. Berthier, M. Buendia, S. Bullich, F. Campos, P. Cañabate, C. Cuevas, A. Gailhajenet, J. Giménez, R. sample derived from a research study instead of a Gismondi, M. Guitart, M. Ibarria, A. Lafuente, E. Martín, M. Moreno, A.B. population-based one and the exclusion of a substan- Nogales, L. Núñez, A. Páez, A. Pancho, E. Pelejà, V. Pérez-Grijalba, P. Pesini, S. tial part of the cohort due to ophthalmological path- Preckler, J. Romero, S. Ruiz, M. Sarasa, M. Torres. ologies known to interfere with retinal thickness Authors’ contributions measurements. MM, SV, MC-M, JM, AR and MB contributed to the overall design and imple- mentation of the study. MM, MC-M, JM, OR-G and AS were responsible for the conduction of the study. JM performed the neuro-opthalmological ex- aminations and OCT scans of the study participants. MC-M reviewed all OCT Conclusions images of the study participants and implemented the OCT-related exclusion In our sample of 129 individuals with SCD, thicken- criteria. GM-R and OS-G performed FBB-PET image analysis and provided ing of the inner nasal macular region was associated SUVR data. OR-G, AS, JPT, MA, AP-C, NR, IH, MR-R, AM, LV; CA, SG, EE-D, AE and GO performed clinical and neuropsychological evaluations of the study with FBB-PET+ status and positively correlated with participants. SM-G, IdR, LM, AO and AR performed APOE analysis. MM, SV and global SUVR. Our data suggest that structural retinal AR were responsible for the data management and statistical analyses. FL changes are already present in very early stages of the and JP were responsible for FBB-PET acquisition. AV, MAT and MG-C were responsible for brain MR acquisition. RS, AC and CH were responsible for the AD continuum and OCT of the retina has potential initial set-up of the neuro-opthalmology clinic and OCT scan. All authors as a biomarker for preclinical AD. Further research contributed to the drafting of the manuscript and approved the final version. on retinal structural and vascular changes in the AD continuum and their association with amyloid, tau Funding This project has received funding from the European Union’s Horizon 2020 and inflammation biomarkers in larger samples is research and innovation programme under the Marie Skłodowska-Curie warranted. grant agreement no. 796706, and the Instituto de Salud Carlos III (ISCIII) Marquié et al. Alzheimer's Research & Therapy (2020) 12:37 Page 13 of 14 grant PI19/00335 Acción Estratégica en Salud, integrated in the Spanish 4. Jessen F, Amariglio RE, van Boxtel M, Breteler M, Ceccaldi M, Chételat G, National R+D+I Plan and financed by ISCIII-Subdirección General de Evalua- et al. A conceptual framework for research on subjective cognitive decline ción and the Fondo Europeo de Desarrollo Regional (FEDER-Una manera de in preclinical Alzheimer’s disease. Alzheimers Dement. 2014;10(6):844–52. hacer Europa") awarded to M.M. 5. Reisberg B, Shulman MB, Torossian C, Leng L, Zhu W. Outcome over seven Funds were also obtained from donations from “La nit de l’Alzheimer”, a years of healthy adults with and without subjective cognitive impairment. charity dinner initiative that takes place yearly as part of the “Festival Castell Alzheimers Dement. 2010;6(1):11–24. de Peralada” (2016-2018). 6. Ogata S, Hayashi C, Sugiura K, Hayakawa K. Association between subjective The neuro-ophthalmology exam devices were acquired with a grant EFSD/ memory complaints and impaired higher-level functional capacity in people Lilly Mental Health and Diabetes 2013 Programme of the European Founda- aged 60 years or older. Arch Gerontol Geriatr. 2015;60(1):201–5. tion for the Study of Diabetes (EFSD) awarded to the project “Retinal neuro- 7. Kryscio RJ, Abner EL, Cooper GE, Fardo DW, Jicha GA, Nelson PT, et al. Self- degeneration in type 2 diabetes as biomarker of Alzheimer’s disease” under reported memory complaints: implications from a longitudinal cohort with the leadership of C.H. autopsies. Neurology. 2014;83(15):1359–65. Funds from Fundació ACE Institut Català de Neurociències Aplicades, Grifols, 8. Hyman BT, Phelps CH, Beach TG, Bigio EH, Cairns NJ, Carrillo MC, et al. Life Molecular Imaging, Araclon Biotech, Alkahest, Laboratorio de análisis National Institute on Aging–Alzheimer’s Association guidelines for the Echevarne and IrsiCaixa are supporting the FACEHBI study. These sponsors neuropathologic assessment of Alzheimer’s disease. Alzheimers Dement. were not involved in the study design, data collection, analysis or 2012;8(1):1–13. interpretation. The sponsors have reviewed the manuscript and have given 9. Martínez G, Vernooij RW, Fuentes Padilla P, Zamora J, Flicker L, Bonfill CX. their approval. 18F PET with florbetaben for the early diagnosis of Alzheimer’s disease dementia and other dementias in people with mild cognitive impairment Availability of data and materials (MCI). Cochrane Database Syst Rev. 2017;11:CD012883. The data, which support this study, are not publicly available but are 10. Mo J-A, Lim J-H, Sul A-R, Lee M, Youn YC, Kim H-J. Cerebrospinal fluid β- available from the corresponding author on reasonable request. amyloid1–42 levels in the differential diagnosis of Alzheimer’s disease—systematic review and meta-analysis. Squitti R, editor. PLoS One. 2015 10(2):e0116802. Ethics approval and consent to participate 11. Counts SE, Ikonomovic MD, Mercado N, Vega IE, Mufson EJ. Biomarkers for A written consent was obtained from all participants prior to the enrolment the early detection and progression of Alzheimer’s disease. in the study. The FACEHBI protocol received approval from the ethics Neurotherapeutics. 2017;14(1):35–53. committees of Hospital Clínic i Provincial in Barcelona, Spain (EudraCT 12. Jaffe GJ, Caprioli J. Optical coherence tomography to detect and manage number 2014-00079-38). The referral centre ethics committee approved the retinal disease and glaucoma. Am J Ophthalmol. 2004;137(1):156–69. patient recruitment, and collection protocols were in accordance with ethical standards according to World Medical Association Declaration of Helsin- 13. den Haan J, Verbraak FD, Visser PJ, Bouwman FH. Retinal thickness in ki—Ethical Principles for Medical Research Involving Human Subjects. Alzheimer’s disease: a systematic review and meta-analysis. Alzheimer’s Dement Diagn Assess Dis Monit. 2017;6:162–70. 14. Díaz-Coránguez M, Ramos C, Antonetti DA. The inner blood-retinal barrier: Consent for publication cellular basis and development. Vis Res. 2017;139:123–37. Not applicable. 15. Byerly MS, Blackshaw S. Vertebrate retina and hypothalamus development. Wiley Interdiscip Rev Syst Biol Med. 2009;1(3):380–9. Competing interests 16. Lamirel C, Newman N, Biousse V. The use of optical coherence tomography MB has consulted for Araclon, Avid, Grifols, Lilly, Nutricia, Roche, Eisai and in neurology. Rev Neurol Dis. 2009;6(4):E105–20. Servier. She received fees from lectures and funds for research from Araclon, 17. Sadun AA, Bassi CJ. Optic nerve damage in Alzheimer’s disease. Biogen, Grifols, Nutricia, Roche and Servier. She has not received personal Ophthalmology. 1990;97(1):9–17. compensations from these organizations. The rest of the authors declare that 18. Koronyo-Hamaoui M, Koronyo Y, Ljubimov AV, Miller CA, Ko MK, Black KL, they have no competing interests. et al. Identification of amyloid plaques in retinas from Alzheimer’s patients and noninvasive in vivo optical imaging of retinal plaques in a mouse Author details model. Neuroimage. 2011;54(Suppl 1):S204–17. 1 Research Center and Memory Clinic, Fundació ACE Institut Català de 19. Tas A, Yolcu U, Ilhan A, Gundogan FC. Detection of retinal nerve fibre layer Neurociències Aplicades - Universitat Internacional de Catalunya (UIC), Gran degeneration in patients with Alzheimer’s disease using optical coherence Via Carles III, 85 bis, 08028 Barcelona, Spain. 2Centro de Investigación tomography: searching new biomarkers. Acta Ophthalmol. 2015;93(6):e507. Biomédica en Red de Enfermedades Neurodegenerativas (CIBERNED), 20. Rodriguez-Gomez O, Sanabria A, Perez-Cordon A, Sanchez-Ruiz D, Instituto de Salud Carlos III, Madrid, Spain. 3Clínica Oftalmológica Dr. Castilla, Abdelnour C, Valero S, et al. FACEHBI: a prospective study of risk factors, Barcelona, Spain. 4Department of Ophthalmology, Hospital del Mar and biomarkers and cognition in a cohort of individuals with subjective Hospital de l’Esperança - Parc de Salut Mar, Barcelona, Spain. 5Department of cognitive decline. Study rationale and research protocols. J Prev Alzheimer’s Radiology, Hospital Clínic i Provincial de Barcelona, Universitat de Barcelona, Dis. 2017;4(2):100–8. Barcelona, Spain. 6Department of Diagnostic Imaging, Clínica Corachan, 21. Boada M, Tárraga L, Hernández I, Valero S, Alegret M, Ruiz A, et al. Barcelona, Spain. 7Centro de Investigación Biomédica en Red de Diabetes y Design of a comprehensive Alzheimer’s disease clinic and research Enfermedades Metabólicas Asociadas (CIBERDEM), Instituto de Salud Carlos center in Spain to meet critical patient and family needs. Alzheimers III, Madrid, Spain. 8Institut de Recerca Vall d’Hebron, Universitat Autònoma de Dement. 2014;10(3):409–15. 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