Retinal Imaging Findings in Carriers With PSEN1-Associated Early-Onset Familial Alzheimer Disease Before Onset of Cognitive Symptoms

Key Points

Question  Do carriers of PSEN1-associated early-onset familial Alzheimer disease who are cognitively unimpaired have retinal alterations detectable by optical coherence tomography compared with noncarrier family members?

Findings  This cross-sectional study found that whole retina and inner retinal layer thinning was demonstrated on optical coherence tomography imaging in carriers of the PSEN1 mutation compared with age-matched noncarriers. A significant interaction between age and PSEN1 mutation on amyloid β levels was found.

Meaning  Optical coherence tomography is a noninvasive technique that may allow analysis of the morphologic and functional changes of the retina in individuals with PSEN1-associated early-onset familial Alzheimer disease, prior to onset of cognitive symptoms.

Importance  Individuals with autosomal dominant mutations for Alzheimer disease are valuable in determining biomarkers present prior to the onset of cognitive decline, improving the ability to diagnose Alzheimer disease as early as possible. Optical coherence tomography (OCT) has surfaced as a potential noninvasive technique capable of analyzing central nervous system tissues for biomarkers of Alzheimer disease.

Objective  To evaluate whether OCT can detect early retinal alterations in carriers of the presenilin 1 (PSEN1 [OMIM 104311]) E280A mutation who are cognitively unimpaired.

Design, Setting, and Participants  A cross-sectional imaging study conducted from July 13, 2015, to September 16, 2020, included 10 carriers of the PSEN1 E280A mutation who were cognitively unimpaired and 10 healthy noncarrier family members, all leveraged from a homogenous Colombian kindred. Statistical analysis was conducted from September 9, 2017, to September 16, 2020.

Main Outcomes and Measures  Mixed-effects multiple linear regression was performed to compare the thickness values of the whole retina and individual retinal layers on OCT scans between mutation carriers and noncarriers. Simple linear-effects and mixed-effects multiple linear regression models were used to assess whether age was an effect modifier for PSEN1 mutation of amyloid β levels and retinal thickness, respectively. Fundus photographs were used to compare the number of arterial and venous branch points, arterial and venous tortuosity, and fractal dimension.

Results  This study included 10 carriers of the PSEN1 E280A mutation who were cognitively unimpaired (7 women [70%]; mean [SD] age, 36.3 [8.1] years) and 10 healthy noncarrier family members (7 women [70%]; mean [SD] age, 36.4 [8.2] years). Compared with noncarrier controls, PSEN1 mutation carriers who were cognitively unimpaired had a generalized decrease in thickness of the whole retina as well as individual layers detected on OCT scans, with the inner nuclear layer (outer superior quadrant, β = –3.06; P = .007; outer inferior quadrant, β = –2.60; P = .02), outer plexiform layer (outer superior quadrant, β = –3.44; P = .03), and outer nuclear layer (central quadrant, β = –8.61; P = .03; inner nasal quadrant, β = –8.39; P = .04; inner temporal quadrant, β = –9.39; P = .02) showing the greatest amount of statistically significant thinning. Age was a significant effect modifier for the association between PSEN1 mutation and amyloid β levels in cortical regions (β = 0.03; P = .001) but not for the association between PSEN1 mutation and retinal thickness. No statistical difference was detected in any of the vascular parameters studied.

Conclusions and Relevance  These findings suggest that OCT can detect functional and morphologic changes in the retina of carriers of familial Alzheimer disease who are cognitively unimpaired several years before clinical onset, suggesting that OCT findings and retinal vascular parameters may be biomarkers prior to the onset of cognitive decline.

Alzheimer disease (AD) is a progressive neurodegenerative disorder hallmarked by decline in memory and cognition. It is considered the most common type of dementia, comprising more than 60% of all cases, and has significant social and economic implications.¹ It has been estimated that more than 5.7 million individuals of all ages in the United States were living with AD in 2018.² There are 2 distinct types of AD: early-onset AD, an autosomal dominant inherited disorder that develops before age 65 years and explains a minority of cases, and late-onset AD, which accounts for more than 95% of AD cases, with symptom onset at age 65 years or later.³ The more common late-onset AD cases are sporadic and are thought to be caused by polygenic risk factors and environmental factors,⁴ which makes early diagnosis of patients with AD difficult, especially in preclinical stages. Optical coherence tomography (OCT) findings have surfaced as a potential biomarker of AD as OCT provides a noninvasive tool capable of detecting abnormalities in central nervous system tissues. To date, studies assessing the retina of patients with sporadic AD have identified decreased thickness of the retinal nerve fiber layer (RNFL)⁵ and the retinal ganglion cell layer (GCL).⁶ Other studies have found that retinal amyloid plaques colocalize to areas of subretinal drusen deposits, which are also seen in individuals with age-related macular degeneration.^7,8 These studies are limited in that patients with AD who are included are already experiencing clinically evident cognitive decline and are of older age, a potential confounder.

The mutated PSEN1 (OMIM 104311) gene, which encodes presenilin 1, is a major causative gene of familial AD with a younger age of onset.⁹ Although the pathogenesis of familial AD may be distinct from sporadic AD and some clinical features may differ, these conditions are markedly similar in terms of their biological profiles, including abnormalities in brain structure, amyloid biomarkers, and brain activity.¹⁰ The inherited nature of familial AD makes it possible to identify carriers through family lineage prior to the onset of clinical symptoms. By studying these individuals early in their clinical course, it is possible to identify unique early biomarkers of disease while reducing many age-related confounding variables (eg, comorbidities and vascular risk factors). Research to date has found that, in carriers of PSEN1 mutations, noninvasive positron emission tomography scans can identify amyloid plaques in the brain approximately 16 years before the clinical onset of mild cognitive impairment and 21 years before onset of dementia.^11-13 In addition, patients with the PSEN1 mutation express higher levels of amyloid β protein in the cerebrospinal fluid and blood serum, and magnetic resonance imaging scans of the brain show characteristic gray matter loss.^14,15 The present study is part of the COLBOS (Colombia-Boston) biomarker study that leverages the world’s largest known autosomal dominant AD kindred.¹⁶ Residing in Antioquia, Colombia, this kindred is estimated to have approximately 5000 living relatives, including about 1800 mutation carriers with an estimated median age of 44 years at the onset of mild cognitive impairment and 49 years at the onset of dementia for the kindred’s carriers.

The retina is anatomically and developmentally considered a part of the central nervous system as it develops from the optic vesicle, a diencephalic bulge.¹⁷ It is well demonstrated that patients with AD may experience various visual disturbances such as deficits in color discrimination, stereoacuity, and contrast sensitivity prior to establishing the diagnosis of AD.^18,19 In the last few years, the retina has received increasing attention as a potential biomarker for AD and other neurodegeneration conditions.

In this study, we analyzed OCT imaging and color fundus photographs of carriers of the PSEN1 E280A mutation who were cognitively unimpaired in an attempt to elucidate early retinal biomarkers of AD.

This cross-sectional study, conducted from July 13, 2015, to September 16, 2020, was part of a prospective observational study on early-onset AD conducted as part of a collaboration between Massachusetts Eye and Ear and Massachusetts General Hospital, both of Harvard Medical School, Boston, Massachusetts, and the Group of Neuroscience of Antioquia, University of Antioquia, Antioquia, Colombia. This research protocol was conducted in accordance with Health Insurance Portability and Accountability Act requirements and the tenets of the Declaration of Helsinki.²⁰ The Massachusetts Eye and Ear and Massachusetts General Hospital IRBs approved this study. Written informed consent was obtained from all participants.

We present a cross-sectional analysis of 20 participants, including 10 carriers of the PSEN1 E280A mutation and 10 healthy noncarrier control adults, all of whom were from Colombia, with a family history of PSEN1 mutations. The selection and recruitment of the study participants has been well described in previous studies.²¹ In brief, volunteers with known carrier and noncarrier status of the PSEN1 E280A mutation from a common ancestral lineage in Colombia were recruited to participate. All patients were screened for the presence of neurologic disorders, psychiatric disorders, drug use disorders, or contraindications to undergoing magnetic resonance imaging studies. Clinical and cognitive measures were acquired in Colombia by Spanish-speaking psychologists. Neuroimaging (magnetic resonance imaging and positron emission tomography) and ophthalmic examinations were completed in Boston. Patients with known ophthalmic pathologic conditions or history of ocular trauma were not included.

Each patient underwent a complete ophthalmic evaluation by a retinal specialist (L.A.K. or J.B.M.) at Massachusetts Eye and Ear including best-corrected visual acuity, intraocular pressure, slitlamp biomicroscopy, and dilated fundus examination. In addition, each patient underwent spectral domain OCT (Spectralis), color fundus photography (Optos Inc), and fundus autofluorescence (Optos Inc). Each patient underwent a positron emission tomography scan of the brain with an amyloid β tracer (Pittsburgh B compound) at Massachusetts General Hospital according to previously published protocols.¹⁶ Pittsburgh B compound retention was estimated as a global cortical mean Pittsburgh B compound distribution volume ratio that included frontal, lateral temporal, and retrosplenial cortices tracer uptake, as previously described.^22,23

Structural measurements of retinal layers were obtained using the Heidelberg Spectralis OCT built-in software (Heidelberg Eye Explorer, version 1.9.10.0). Two masked research investigators (R.F.S. and R.Z.) and 1 masked experienced clinical investigator (G.W.A.) assessed the automatic segmentation lines of each retinal layer to evaluate whether the lines appropriately delineated the limits of the RNFL, GCL, inner plexiform layer, inner nuclear layer (INL), outer plexiform layer (OPL), and outer nuclear layer (ONL) according to the International Nomenclature for Optical Coherence Tomography Panel.⁵

A thickness map was generated according to the conventional Early Treatment Diabetic Retinopathy Study (ETDRS) grid.²⁴ The grid consists of 9 sectors: a central circle with a diameter of 1 mm and 2 concentric rings with a diameter of 3 mm and 6 mm, each divided into 4 quadrants (superior, nasal, inferior, and temporal). The investigators assessed the positioning of the grid through the “Thickness Map” function in Heidelberg Eye Explorer, version 1.9.10.0. If the grid was not appropriately positioned, the investigator would manually position the grid so that it was centered on the fovea. Finally, the total thickness values of the retina as well as each retinal layer were obtained in each of the 9 ETDRS sectors.

Retinal vessels were segmented in color fundus photography images without eyelid artifact using MATLAB, version R2017b (The Mathworks Inc) image processing. The image was converted to grayscale, contrast enhanced (Figure 1A), converted to a binary image using local thresholding via the Niblack method,²⁵ and subsequently noise reduced (Figure 1B). Skeletonization of the binary image was performed and short terminal branch segments were pruned by the spur module of bwmorph in MATLAB for 50-pixel lengths. Fractal dimension (Minkowski-Bouligand dimension) of the whole image was calculated using the box-counting method.^26,27 Vessel branch points were then searched in the image and visually confirmed, and vessel segments were defined by a continuous line of pixels between branch points (Figure 1C). A single trained and masked researcher (J.Y.P.) assigned each vessel segment as either an artery or vein (Figure 1D).

Tortuosity index in each vessel segment was defined as arc length divided by chord length, which gives reproducible tortuosity results in medium-length vessels. Arc length was calculated by MATLAB’s bwdistgeodesic function. Chord length was calculated from the coordinates of 2 end points of each vessel segment. Vessel segments were color coded based on their tortuosity index in the final image for visual confirmation. Total mean tortuosity of the entire image was calculated as a weighted mean of tortuosity index for chord length.

Statistical analysis was conducted from September 9, 2017, to September 16, 2020. All statistical analyses were conducted using R, version 3.6.3 (R Foundation for Statistical Computing). Normally distributed continuous data were reported as mean values with SDs and assessed for statistical significance by parametric tests, such as the t test, whereas skewed continuous data were reported as median values with interquartile ranges (IQRs) and assessed for statistical significance by nonparametric tests, such as the Mann-Whitney test. We used a mixed-effects multiple regression model accounting for correlation between the 2 eyes of the same patient. We present results with regression coefficients, 95% CIs, and 2-sided P values; P < .05 was considered significant. Simple linear regression and mixed-effects multiple linear regression were used to assess whether age was an effect modifier for PSEN1 mutation of amyloid β levels and retinal thickness, respectively.

We included 20 participants (40 eyes), who were divided into 10 carriers with a known genetic history of PSEN1 mutation (7 women [70%]; mean [SD] age, 36.3 [8.1] years) and 10 healthy noncarrier controls (7 women [70%]; mean [SD] age, 36.4 [8.2] years). There were no significant differences between the PSEN1 carrier group and the control group in terms of age (P = .98), sex (P > .99), median education in years (11.0 years [IQR, 1.0-13.0 years] vs 12.0 years [IQR, 6.0-17.0 years]; P = .08), or median Mini-Mental State Examination score (28.00 [IQR, 16.00-30.00] vs 29.00 [IQR, 27.00-30.00]; P = .22) (Table 1).

Mixed-effects multiple linear regression analysis revealed that when compared with the noncarrier control group, the PSEN1 carrier group had generalized whole retinal thinning, reaching statistical significance in the outer superior quadrant (β = −16.28; P = .02), outer nasal quadrant (β = −13.30; P = .04), outer temporal quadrant (β = −13.45; P = .046), inner superior quadrant (β = −16.75; P = .02), inner nasal quadrant (β = −15.75; P = .02), inner inferior quadrant (β = −14.00; P = .02), and inner temporal quadrant (β = −11.60; P = .04). When comparing individual retinal layers, the PSEN1 carrier group showed statistically significant retinal thinning in the outer superior quadrant (β = −3.06; P = .007) and outer inferior quadrant (β = −2.60; P = .02) of the INL, outer superior quadrant (β = −3.44; P = .03) of the OPL, and central quadrant (β = −8.61; P = .03), inner nasal quadrant (β = −8.39; P = .04), and inner temporal quadrant (β = −9.39; P = .02) of the ONL (Figure 2 and Figure 3). Although there was thinning in multiple quadrants in the RNFL and GCL, it did not reach statistical significance (eTable 1 in the Supplement).

There was significant interaction between age and PSEN mutation associated with amyloid β levels (Table 2) as well as many other brain regions, with a statistically significant (β = 0.03; P = .001) elevation in the distribution volume ratio. Mixed-effects multiple linear regression analysis for total retinal thickness for age and PSEN1 mutation as covariates showed the interaction between age and PSEN1 mutation associated with retinal thickness to be not significant in all regions (Table 2). This finding indicates that age was a significant effect modifier for the association between PSEN1 mutation and amyloid β levels but not significant for the association between PSEN1 mutation and retinal thickness.

There was no difference between the number of arterial and venous branch points, arterial and venous tortuosity, or fractal dimension between the control and PSEN1 carrier groups (eTable 2 in the Supplement).

We present a study assessing for clinical markers of AD using both retinal OCT and retinal vasculature parameters in carriers of PSEN1-associated early-onset familial AD who were cognitively unimpaired. We found that PSEN1 carriers who were cognitively unimpaired demonstrated thinning of the whole retina, which was most prominent in the INL, ONL, and OPL. In the PSEN1 carrier sample, age was a significant effect modifier for the association between PSEN1 mutation and amyloid β levels in cortical regions but not significant for the association between PSEN1 mutation and retinal thickness.

These findings suggest that OCT can detect functional and morphologic changes in the retina of carriers of familial AD who are cognitively unimpaired, several years before clinical onset of cognitive decline. Given the biological profile similarities of familial AD with sporadic AD, including abnormalities in brain structure, amyloid biomarkers, and brain activity, our results may be generalizable to sporadic AD as well. This finding suggests that OCT imaging may serve as a noninvasive way of screening patients at risk of familial or sporadic AD prior to the onset of cognitive changes, aiding in early identification and counseling of patients with AD, as well as the design of future AD clinical trials.

As prior research has shown that pathologic changes can be seen in the retina of patients with noninherited forms of AD^28,29 as well as findings on retinal imaging such as OCT³⁰ and fundus photography,³¹ we examined whether similar retinal findings could be detected in a cohort of individuals with PSEN1 mutations prior to the onset of clinical symptoms of dementia. Furthermore, we investigated if such findings were correlated with disease progression.

Unlike earlier studies reporting a significant reduction in peripapillary RNFL thickness in individuals with nonfamilial AD,³² our familial AD cohort showed a statistically significant reduction in the INL and ONL. Thinning of the RNFL and GCL was present but was not statistically significant. Given our finding of pathologic thinning of the intraretinal layers rather than localized thinning of the GCL, it is possible that an intrinsic intraretinal disease process accounts for these findings, rather than retrograde damage from the optic tract and associated brain structures. Inner nuclear layer, ONL, and OPL thinning may be due to a lack of PSEN1 proteolysis function, resulting in cell death of the INL, ONL, and OPL, which is distinct from currently proposed mechanisms for sporadic AD retinal thinning, which include breakdown of the retinal pigment epithelium and blood-retina tight junctions due to presence of amyloid β deposits in the retina, and subsequent increase in reactive oxygen species and complement activation via factor B upregulation.³³

In a previously published patient cohort, there was an age-related association with disease progression and amyloidopathy.^11,14 Previous work on noninherited AD showed that the RNFL undergoes progressive thinning from minor cognitive impairment to AD,⁵ and that GCL thinning is correlated with severity of cognitive impairment as well.⁶ In our cohort, age was a significant effect modifier of the association between PSEN1 mutation and amyloid β levels (eTable 2 in the Supplement). However, the effect modification between PSEN1 mutation and retinal thickness was tenuous (Table 2). It is unknown whether this is owing to a small sample size or an indication that changes in retinal thickness in familial AD appear at an even earlier age than the patient cohort in our study. If the latter is the case, younger patients with PSEN1 mutation might show evidence of age-related retinal thinning.

Previous studies have shown associations between retinal vascular markers and AD, specifically with vascular tortuosity and fractal dimension (as a surrogate for overall vascular complexity).^34,35 Degenerative changes in cerebral vasculature due to amyloid β deposition and subsequent smooth muscle cell loss may also account for changes in vascular tortuosity in patients with AD.^36,37 In the PSEN1 carriers, we did not find any significant differences in arterial or venous tortuosity. This lack of difference could be owing to the significant phenotypical variability of PSEN1 AD, but may also be associated with the distinctive pathogenesis of PSEN1 AD, as there is an increased production of amyloid β in the neurosensory retina rather than poor clearance of certain apolipoprotein isoforms. Our method of quantification of vascular tortuosity was laborious and time intensive, but future studies using OCT angiography may be easier to implement and may reveal whether there are differences in retinal vascular flow associated with retinal vessel changes, which may be a more direct marker of possible amyloid deposition rather than vascular tortuosity or fractal dimension. Current research supports this idea, as O’Bryhim and colleagues³⁸ in a recent case-control study of 32 participants reported biomarker-positive findings for those with non–early-onset preclinical AD who underwent OCT angiography testing to evaluate retinal vasculature. The study suggests that there is foveal avascular zone enlargement in these individuals perhaps due to retinal degeneration from amyloid β accumulation within the retina.

Although several studies have demonstrated morphologic and structural changes in the retina of patients with AD by using OCT, only a few assessed the prognostic or diagnostic value of OCT in patients without preexisting cognitive decline (ie, preclinical AD).^39-43 To our knowledge, this is the first study that aimed to evaluate the clinical utility of OCT or retinal vascular parameters as novel biomarkers in PSEN1 mutation carriers.

This study has a few important limitations. Because our study was conducted in a well-defined Colombian kindred of early-onset AD, the validity of generalizing our results to late-onset AD and other AD-associated mutations is uncertain. Furthermore, with only 20 participants, the small sample size limited our statistical power, but the sample size is a function of the relative rarity of early-onset familial AD.²¹

At present, OCT can detect pathologic changes in the retina of patients with noninherited forms of AD. In our study, significant thinning in the INL and ONL was demonstrated on OCT scans of the PSEN1 mutation carrier group compared with the age-matched control group. Our results suggest that OCT can also detect functional and morphologic changes in the retina of patients with familial AD even prior to the onset of cognitive decline. Additional cohort studies with larger samples will be required to confirm whether OCT can be used as an early biomarker to identify cognitively normal individuals at higher risk for AD.

Accepted for Publication: September 27, 2020.

Published Online: November 12, 2020. doi:10.1001/jamaophthalmol.2020.4909

Corresponding Authors: John B. Miller, MD, Retina Service, Department of Ophthalmology, Massachusetts Eye and Ear, Harvard Medical School, 243 Charles St, Boston, MA 02114 (john_miller@meei.harvard.edu); Yakeel T. Quiroz, PhD, Department of Psychiatry, Massachusetts General Hospital, Harvard Medical School, 55 Fruit St, Boston, MA 02114 (yquiroz@mgh.harvard.edu).

Author Contributions: Drs Armstrong and Miller had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Armstrong, Kim, Quiroz, and Miller contributed equally to the work.

Concept and design: Kim, Park, Silverman, Lopera, Arboleda-Velasquez, Miller.

Acquisition, analysis, or interpretation of data: Armstrong, Kim, Vingopoulos, Park, Garg, Kasetty, Silverman, Zeng, Douglas, Lopera, Baena, Giraldo, Norton, Cronin-Golomb, Quiroz, Miller.

Drafting of the manuscript: Armstrong, Kim, Vingopoulos, Park, Garg, Zeng, Douglas, Miller.

Critical revision of the manuscript for important intellectual content: Armstrong, Kim, Vingopoulos, Park, Garg, Kasetty, Silverman, Douglas, Lopera, Baena, Giraldo, Norton, Cronin-Golomb, Arboleda-Velasquez, Quiroz, Miller.

Statistical analysis: Park, Garg, Silverman.

Obtained funding: Kim, Arboleda-Velasquez, Miller.

Administrative, technical, or material support: Armstrong, Kim, Vingopoulos, Kasetty, Zeng, Baena, Miller.

Supervision: Armstrong, Kim, Lopera, Quiroz, Miller.

Conflict of Interest Disclosures: None reported.

Funding/Support: This study was funded by grants UH3 NS100121 and RF1 NS110048 from the National Institute of Neurological Disorders and Stroke (Dr Arboleda-Velasquez), the Grimshaw-Gudewicz Charitable Foundation (Drs Arboleda-Velasquez, Miller, and Kim), grant DP5OD019833 from the National Institutes of Health Office of the Director, grant R01 AG054671 from the National Institute on Aging, the Alzheimer’s Association, and grants 1200-228010 and 1200-228767 from Massachusetts General Hospital ECOR (Dr Quiroz). Dr Lopera was supported by an anonymous foundation and by the Administrative Department of Science, Technology and Innovation (Colciencias Colombia; grant 111565741185).

Role of the Funder/Sponsor: The funding sources had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

Additional Contributions: The authors thank the PSEN1 Colombian families for contributing their valuable time and effort, without which this study would not have been possible. We thank the research staff of the Group of Neuroscience of Antioquia, Massachusetts General Hospital, and Massachusetts Eye and Ear for their help coordinating study visits for the COLBOS project. We would also like to thank all the photographers in the Massachusetts Eye and Ear Fluorescein Laboratory who captured all of the beautiful images used in the presented work.