m
Recent Posts
Connect with:
Sunday / September 19.
HomemistoryThe Retina as a Window to the Brain: Imaging Biomarkers for Alzheimer’s Disease

The Retina as a Window to the Brain: Imaging Biomarkers for Alzheimer’s Disease

Dementia is now a national health crisis and, to date, medicine has had nothing to offer as a cure. While clinical detection and diagnosis of dementia was once only possible at postmortem, through innovative research we are now discovering that the biomarkers of this disease can be detected by looking into the eye. In the future, it’s possible to imagine that eye care professionals will play a vital role in managing this terrible disease.

Dementia affects about one in five people in Australia by the age of 85.1 It is projected to cost the government AU$80 billion per year in health spending by 2060, becoming the most expensive disease in the country. Designated as the ninth National Health Priority in 2012,2 Alzheimer’s disease (AD) has recently overtaken cardiovascular disease to become the leading cause of death for women in Australia.3 Interestingly, of the 858 COVID-related deaths recorded in Australia in the first 10 months of 2020, it was noted that 30% had dementia, though they tended to be older and lived in aged care facilities where the outbreaks occurred.

As the lines between neurology and eye care blur, we can begin to imagine a future where eye care practitioners play an increasingly important role in the management of this terrible disease

Figure 1. Biomarkers of AD. Current biomarkers of AD are believed to detect the disease up to 20 years before symptoms manifest. Figure adapted from Frisoni et al., 2012 Nature Review9 CSF = cerebrospinal fluid,
PET = positron emission tomography, MRI = magnetic resonance imaging.

AD is the most common cause of dementia in the world, accounting for 60–70% of all cases.5 The hallmarks of the disease, namely cortical senile ‘plaques’ and neurofibrillary ‘tangles’, were first described by Professor Alois Alzheimer in 1906. However, it was not until 1985 when Melbourne-based neuropathologist Colin Masters and colleague Konrad Beyreuther discovered that the amyloid-beta (Aβ) protein6 played a central role in the formation of senile plaques. Around the same time, the isolation of paired helical filaments7 from neurofibrillary tangles in AD brains were attributed to tau protein misfolding.8 These discoveries laid the foundation for the ‘Amyloid hypothesis’ which posits Aβ as the start of the ‘cascade’ leading to AD.

Figure 2. Shared neural origins between the eye and the brain. The appearance of the optic grooves in the three weekold embryo marks the beginning of eye development. Purple boxes highlight the location of eye development. Figure adapted from OpenStax, commons.wikimedia.org/w/index.php?curid=30147939, creative commons license CC BY 4.0.

BIOMARKERS IN AD

Currently the gold standard way to definitively diagnose AD in a patient with dementia symptoms is through histopathological brain examination postmortem. However, advances in in vivo brain imaging have led to the discovery of promising AD biomarkers. ‘Biomarkers’ may be defined as an objective indicator of a normal biological or pathological process. The most well described AD biomarker, the Pittsburgh Compound C, is believed to be able to detect the disease up to 20 years before physical manifestation (Figure 1).

Figure 3. Post-image acquisition analysis using
Interactive Vessel Analysis (IVAN) software,
developed by Hubbard and colleagues14 at the
University of Wisconsin. Image above shows vessel segmentation within a ring between 0.5 and one disc diameters from the disc centre.

Detection biomarkers, also known as pathological biomarkers, are specific to the disease process but are often poor at monitoring disease severity. These biomarkers are often expensive or inaccessible, making them unsuitable for general screening.

Staging biomarkers are often referred to as ‘topographical’ and while not specific to the disease, are often good at monitoring disease progression. An example is the use of magnetic resonance imaging (MRI) for monitoring hippocampal size.

While these biomarkers are well validated, there is an urgent need for less invasive and more accessible ways to screen for AD.

At present there are no United States Food and Drug Administration (US FDA) approved drugs that can ‘modify’ (i.e. slow down or reverse) the course of the disease.10 The most promising candidate – aducanumab (Biogen) – is an anti-amyloid therapeutic agent with modest longitudinal improvements in patients with early disease. Aducanumab and its closest competitor, Donanemab (Lilly Pharmaceuticals) have completed their Phase 3 trials and are seeking FDA approval at the time of writing.

Figure 4. Functional imaging of retinal vessels show reduced vascular autoregulation in AD. Green traces represent normative range, red traces show patient’s dynamic vessel response. 4A shows the response of a healthy 70+ year
old. 4B shows a patient with probable AD with confirmed abnormal amyloid levels in their cerebrospinal fluid. Figure adapted from Querques et al., 2019 Scientific Reports.

THE EYE: AN ACCESSIBLE EXTENSION OF THE BRAIN

The retina shares the same neural progenitors as the diencephalon (Figure 2). Post-developmental similarities include their cell classes (neurons and glial), neurotransmitters, blood vessel characteristics, and barrier mechanisms.11 The optic nerve forms a part of the central nervous system and the retrobulbar visual pathway extends across the length of the brain to project into the primary visual cortex. Coupled with a clear optical media, these factors make the eyes a very convenient and accessible part of the brain. Given the role that optometrists and ophthalmologists play in primary eye care, the following section discusses the current state of imaging biomarkers for the detection of AD.

IMAGING BIOMARKERS OF AD

Fundus Photography

+ Amyloid is known to deposit along blood vessel walls in up to 15% of normal ageing, a condition known as cerebral amyloid angiopathy. In AD, it is estimated that at least 80% of patients have coexisting amyloid angiopathy.12 Since the late 1990s, it has been shown that amyloid angiopathy precedes neuronal loss in AD and this is manifested in the brain in the form of cerebral vascular dysregulation and malperfusion. While amyloid is known to constrict vessels through direct mediation and pericyte signalling, a more recent study showed that amyloid beta oligomers – the toxic form of amyloid – are already present in the peripheral blood vessels and in the retina prior to appearing in the brain.13 

Figure 5. OCT changes in early AD patients with otherwise healthy eyes. A. RNFL losses can appear in any sector in AD but show a preference for superior RNFL thinning when compared across entire populations (Figure adapted from Kirbas et al., 201319). B. Macular ganglion cell complex changes in AD have been shown to manifest before optic disc RNFL changes (Figure adapted from Cheung et al., 201720).

Using fundus photography and post-hoc blood vessel analysis software (Figure 3), the cardiovascular health study (n = 2211), Rotterdam Eye Study (n = 6978) and the Reykjavik AGES (n = 3906) showed that reduced vessel branching complexity increased the tortuosity and venous diameter changes in AD. Most population-based studies report up to 10% decrease in venous diameter, with the exception of the Rotterdam Eye Study (increased diameter). However, these changes have been shown to be less relevant clinically when applied on an individual basis.15 

Analyses of static retinal photos are limited by individual variation in physiological factors such as cardiovascular factors e.g. systolic-diastolic range and basal vascular perfusion. One way to overcome these limiting factors is the use of ‘functional’ vessel analysis. The Dynamic Vessel Analyser is one such fundus camera with an in-built flickering light source. By stimulating the retina with flicker, this triggers a metabolic cascade leading to blood vessel dilation. In healthy eyes, vasodilation of up to 10% is expected in the presence of functioning autoregulation. In eyes with probable AD, the capacity for autoregulation is diminished, making this a potentially useful screening tool16 (Figure 4).

Retinal Nerve Fibre Layer Assessment 

Figure 6. Choroidal thinning in AD. Choroidal thickness, as measured using EDI-OCT, is reduced in mild cognitive impairment as well as in AD (Figure adapted from Lopez-de-Eguileta, 202023).

It was first discovered in 1986 that the optic nerve and retinal axons of post-mortem AD eyes were degenerated compared with age matched controls.17 Axonal thinning was most pronounced in the superior quadrants and parafoveal regions of AD eyes. While this provided the anatomical basis for AD changes in the eye, there was no way to non-invasively measure retinal structure for decades to come. Interest in this field resurfaced at the turn of the millennia, with the advent of scanning laser ophthalmoscopes (SLO) and optical coherence tomography (OCT).

In the late 1990s, when time-domain based OCTs were (mostly) limited to qualitative retinal assessment, the use of confocal SLO (e.g. Heidelberg HRT) to measure retinal nerve fibre layer (RNFL) thickness was commonplace. While SLO provided a clear and reliable image of the inner retina, it had limited penetration into the outer retina. As OCT technology shifted from time domain to fourier domain (aka ‘spectral’ domain or ‘HD’), this allowed for better visualisation and more reliable segmentation of the RNFL. The last decade saw the rapid uptake of OCTs in clinic as well as research. Consequently, SLO technology has been adapted for en face imaging (e.g. Optos). Today, modern OCT imaging devices often incorporate both technologies e.g. Heidelberg Spectralis, Zeiss Cirrus 5000 etc.

To date, there are more than 30 high quality studies (pooled n = 1200 AD patients) showing agreement that the OCT is a useful biomarker for AD.18 While there is evidence of generalised RNFL loss, there appears to be a preferential loss in the superior RNFL in AD eyes (Figure 5).

There has also been increasing interest in the analysis of the macular ganglion cell complex, which incorporates the axons (RNFL layer) as well as the dendrites (inner plexiform layer, IPL) of retinal ganglion cells. By analysing the GC+IPL complex, studies have shown that it is possible to detect participants with prodromal AD (mild cognitive impairment symptoms) despite normal RNFL thickness around the optic disc (for review read Cheung et al, 201720 Progress in Retinal and Eye Research).

Although promising, retinal structural changes have to be viewed in the context of co-existing ocular pathology, as well as neurological losses e.g. stroke which often results in retrograde retinal nerve thinning. Perhaps most pertinent is glaucoma, which leads to neurodegenerative changes in the retina. At present, there is no reliable way to separate OCT changes between glaucoma and AD. However, clinical signs such as optic disc cupping, inferior neuroretinal thinning (aka ISNT rule) as well as risk factors such as family history and intraocular pressure, should help distinguish between both conditions.

Figure 7. Curcumin tagging of amyloid deposits in the retina. A. shows the presence of curcumin in the retina but not the brain of a young AD mouse. B. shows curcumin staining of the retina using in vivo fundus autofluorescence imaging of the retina of AD patients. (A. adapted from Koronyo et al., 201139, B. adapted from Koronyo et al., 201740)

Interestingly, an emerging biomarker for glaucoma, the Bruch’s membrane opening – minimum rim width (BMO-MRW), which is progressively enlarged in glaucoma, has been shown to remain unchanged in AD.21 This was despite RNFL and ganglion cell complex thinning in these AD eyes. Further studies are needed to see if BMO-MRW could prove to be a useful differentiator between both glaucoma and AD.

OCT VASCULAR PARAMETERS

The choroid is the most vascularised part of the body, with the greatest density of blood vessels in any tissue. In 2008, using spectral domain OCT, Spaide and colleagues22 first described a way to image the choroid by positioning the OCT closer to the patient’s eye until the cross-sectional retinal image (b-scan image) is inverted. By moving the choroid closer to the sensor, and acquiring these upside-down b-scan images, they were able to improve choroidal resolution. This allowed them to measure the choroidal thickness of 17 young healthy volunteers. Modern OCTs are able to achieve a good image of the choroid, either by incorporating software which inverts the image for the user i.e. EDI mode, or by adding an additional infrared laser to penetrate the RPE e.g. swept source OCTs.

Choroidal thickness measurements are most often obtained directly under the fovea, between the Bruch’s-choroid boundary and the choroid-scleral boundary. This can be done using virtual calipers, available in most OCT software, which provide a surrogate measure of outer retinal blood supply.

Figure 8. Detection of Apoptosing Retinal Cells (DARC) offer real time imaging of dying inner retinal cells in glaucoma. This requires an intravenous delivery of ANX776 two hours prior to imaging. Phase 1 trials show that DARC imaging can detect retinal ganglion cell death up to 18 months before OCT changes. This technology is being adapted for the detection of amyloid burden in the retina in patients with Down’s syndrome. Figure from Yang et al., 201849, creative commons attribution licence (CC BY 4.0).

Most studies report choroidal thinning of up to 35% in prodromal AD,24 mild AD23,25 as well as established AD.26 Interestingly, these changes are not seen on histology,27 suggesting that in vivo choroid thickness is highly dynamic. Indeed, some have reported choroidal thinning in the absence of RNFL changes,26 suggesting that dynamic in vivo vascular changes are occurring prior to axonal degeneration.

OCT angiography (OCTA) technology has been described as early as 2008 by An and Wang.28 Originally described as ‘optical microangiography’ or OMAG, this technology has been made commercially available through Zeiss and Nidek OCTs. Other OCTA algorithms, developed in 2012 and 2016 respectively, are the Split-spectrum amplitude-decorrelation angiography (SSADA)29 found in Optovue OCTs, and Swept Source OCTA (OCTARA)30 in the Topcon OCTs. The commercialisation of these technologies has made OCTA more widely available in the clinical domain.

Although each OCTA algorithm has its own strengths and weaknesses, they work on similar principles – to detect movement of blood cells through image stabilised retinal vessels. To achieve this requires at least two to four b-scans at the same location.31 This is possible only in OCTs with the capacity to track eye movements/ register images of the same spatial location (but separated in time), and a scan speed of ≥65,000 axial scans per second (typical OCTA enabled OCTs exceed 100,000 Hz) in order to capture movement.

Given the infancy of this technology, there is no normative database for comparison. At present, most OCTA devices provide a measure of vascular density of the inner retinal vasculature i.e. the superficial and deep layers. Another measurement provided is the size of the foveal avascular zone (in mm2), which is a surrogate measure for central retinal perfusion – in the way that cup to disc ratio is a surrogate measure for neuroretinal rim thinning.

Presently, there are only a handful of studies comparing OCTA parameters in AD. However this is expected to change over the next few years. Current results are conflicting, with some reporting reduced vascular density in the macular region,32 and increased vessel density in the macular and peripapillary region,33 while others found no differences compared with healthy controls.15 As this technology improves, it is expected that the sensitivity for detection will increase over time.

Direct Visualisation Of Amyloid Plaques In The Retina 

The presence of amyloid has only recently been discovered in the retina and it is thought to deposit in the ganglion cells (especially abundant in melanopsin containing ganglion cells34), plexiform layers35 and in blood vessels.36 Prior to this discovery in 2008, it was thought to be found only as sub-retinal deposits – existing as a component of drusen. However, no correlation between age-related macular degeneration (AMD) and increased risk of AD has been found.37 Interestingly, a wide field imaging (Optos) case study series in AD patients showed increased peripheral (but not central) drusen deposition over time,38 suggesting that increased sub retinal amyloid a distinguishing feature between both diseases.

Figure 9. Hyperspectral retinal imaging shows increased reflectance in eyes with prodromal AD. A. shows a
diagrammatical representation of hyperspectral scanning of the same fundus image across sequential wavelengths.
B. shows the hyperspectral grouped trace in AD (red) compared with controls (blue). Reproduced with kind permission from Creative Commons by Community Eye Health.50

Perhaps the ‘holy grail’ of ocular biomarkers is the direct visualisation of AD hallmarks such as amyloid or tau deposits in the eye. This would provide the most direct evidence of the disease, thereby increasing specificity as well as sensitivity. Similar in concept to brain imaging, the use of fluorescent markers or radioligands (in the case of PET) with high binding affinity to AD hallmarks may allow for direct visualisation of amyloid or tau protein.

One such compound is curcumin, a potent antioxidant commonly found in curry dishes (turmeric spice). Studies in animal models of AD show that intravenously delivered curcumin cross the blood retinal and blood brain barrier to tag amyloid deposits in the retina as well as the brain39 (Figure 7). Researchers have shown that in mice, amyloid is detected in the retina even before they appear in the brain (Figure 7A).

Although curcumin has strong binding affinity to amyloid, it suffers from poor bioavailability when delivered orally due to poor gut absorption and other factors. To circumvent this, AD patients were given extraordinarily high doses of curcumin (10 times the recommended dose) mixed into a chocolate pudding. They were dosed daily for either two or ten days, with the ten-day group showing maximum amyloid staining of the retina at day ten, persisting even after 28 days (Figure 7B).

The results of these studies are intriguing as they suggest that the presence of retinal plaques is a potential early biomarker of AD. Once thought to occur secondary to brain deposition, there is increasing evidence to show that not only are retinal cells capable of producing amyloid locally,41 they form small particles that appear to leave biological signatures that are not detected in the brain until the advanced stages.42-44 Additionally, the lamellar arrangement of the retina, coupled with high resolution imaging (relative to brain imaging), is favourable for the detection of these subtle changes.

Despite this, there remains contention in the literature about whether amyloid in the retina aggregates in sufficient quantity to be detected through curcumin tagging (for review see Gupta et al, 2020 Progress in Retinal and Eye Research45). In the same vein, others have shown that tau deposits can be tagged and imaged in the in vivo retina after intravenous delivery of modified PET radioligands such as florbetapir.46,47 

Another imaging approach is to forgo amyloid/tau detection altogether, instead focussing on damage secondary to the pathological process. Given the propensity for ganglion cell damage early in the disease, the imaging of dying (apoptosing) ganglion cells has also been suggested as an early detection biomarker of AD. In their recent ‘Detection of Apoptosing Retinal Cells’ (DARC) Phase I trial, researchers at University College of London delivered a modified histological marker for apoptosis (annexin V) coupled with a fluorescent dye intravenously, two hours prior to imaging. Not only were they able to establish safety, they showed that DARC imaging (Figure 8) analysed using artificial intelligence, was able to detect glaucoma progression up to 18 months earlier than OCT.48 They have extended their Phase II recruitment to include AMD, down syndrome (AD surrogate) and optic neuritis (multiple sclerosis surrogate).

Though promising, one disadvantage of these biomarkers is the need for systemic administration of an extraneous compound. In the short term, safety and tolerability studies are needed to further assess the biological profiles of these compounds. In the longer term, population studies are needed to assess their efficacy.

HYPERSPECTRAL NON-INVASIVE IMAGING OF RETINAL AMYLOID CONTENT

Hyperspectral imaging in essence, is the spectral scanning of an area using sequential wavelengths in the ultraviolet, visible and infrared spectrum range. This technique has long been employed by NASA’s hyperion satellites to determine the mineral, water and biological content found in a given geographical location. This technique was originally borrowed from chemistry, where the spectral absorption of light passing through a solution is related to the concentration of the solute (spectroscopy).

In the eye, the main absorber of light is the crystalline lens and the various chromophores within the retina i.e. macular pigment, blood (oxyhaemoglobin) and melanin from the retinal pigment epithelium. After accounting for individual variation between patients,50 hyperspectral imaging of the retina may be used to determine the concentration of proteins based on their amount of light scatter. In the case of AD, the protein responsible for light scatter is soluble amyloid – a toxic form of amyloid that is smaller than the visible spectrum (<400 μm). By borrowing this concept, studies have shown that AD mouse and human retinae, with confirmed amyloid deposits, possessed unique spectral signatures (Figure 9) that were distinct from control.51,52 

In 2019, an interdisciplinary team out of Melbourne was the first in the world to demonstrate utility of non-invasive hyperspectral imaging in AD patients recruited from the Australian Imaging, Biomarker & Lifestyle (AIBL) study of ageing. Using a now commercially available device (Optina hyperspectral camera) in 15 patients with mild cognitive impairment, the authors showed a difference in the spectral signatures obtained in the prodromal AD group compared with healthy controls (Figure 9). They also found a correlation between retinal protein levels and brain amyloid content using PET. While promising, more studies are needed to further validate these findings.

CONCLUSION

At the start of this article, I mentioned that the two leading disease modifying drug candidates – Aducanumab and Donanemab – only work in early disease. One often cited reason for the abysmally low success rate53 of AD drug trials is that patients did not actually have AD upon postmortem assessment. Another reason is that patients were recruited when the disease was already too advanced.11 

These limitations may be overcome by the use of biomarkers. Yet existing biomarkers are expensive, preventing the adoption of mass screening programs as well as limiting recruitment of participants through neurology clinics where symptoms are already apparent. This has the knock-on effect of lowering success rates, especially in drugs focusing on neuroprotection or targeting the disease process.

Only by developing tools that enable population wide screening can we maximise our chances of developing a cure for AD. For this to occur, an interdisciplinary approach is needed to continue pushing the boundaries of AD diagnosis and management. As the lines between neurology and eye care blur, we can begin to imagine a future where eye care practitioners play an increasingly important role in the management of this terrible disease.

To earn your CPD hours from this article visit mieducation.com/the-retina-as-a-windowto- the-brain. 

Dr Jeremiah Lim B.Optom, Mphil, PhD (Melb) is a member of the Caring Futures Institute and a senior lecturer in the Optometry teaching section, College of Nursing and Health Science, at Flinders University in South Australia. 

References 

  1. Access Economics. Keeping dementia front of mind: incidence and prevalence 2009-2050. 1-96 (Alzheimer’s Australia, Australia, 2009).
  2. DoHA. Dementia made a national health priority area. (2012). www.health.gov.au.
  3. AIHW. Australia’s health 2018: in brief. (2018). www.aihw.gov.au/getmedia/7c42913d-295f-4bc9-9c24-4e44eff4a04a/aihw-aus-221.pdf.aspx?inline=true.
  4. AIHW. Dementia deaths during the COVID-19 pandemic in Australia. (2021). www.aihw.gov.au/reports/dementia/dementia-deaths-during-the-covid-19-pandemic-in-au.
  5. WHO. Dementia: a public health priority. 112 (World Health Organization Geneva, Switzerland, 2012).
  6. Glenner, G. G. & Wong, C. W. Alzheimer’s disease and Down’s syndrome: sharing of a unique cerebrovascular amyloid fibril protein. Biochemical and biophysical research communications 122, 1131-1135 (1984).
  7. Selkoe, D. J., Ihara, Y. & Salazar, F. J. Alzheimer’s disease: insolubility of partially purified paired helical filaments in sodium dodecyl sulfate and urea. Science 215, 1243-1245, doi:10.1126/science.6120571 (1982).
  8. Kosik, K. S., Joachim, C. L. & Selkoe, D. J. Microtubule-associated protein tau (tau) is a major antigenic component of paired helical filaments in Alzheimer disease. Proceedings of the National Academy of Sciences of the United States of America 83, 4044-4048 (1986).
  9. Frisoni, G. B. Biomarker trajectories across stages of Alzheimer disease. Nature Reviews Neurology 8, 299-300, doi:10.1038/nrneurol.2012.81 (2012).
  10. Cummings, J., Lee, G., Ritter, A., Sabbagh, M. & Zhong, K. Alzheimer’s disease drug development pipeline: 2020. Alzheimer’s & Dementia: Translational Research & Clinical Interventions 6, e12050, doi.org/10.1002/trc2.12050 (2020).

 11. Nguyen, C. T. O. et al. Retinal biomarkers provide “insight” into cortical pharmacology and disease. Pharmacol Ther 175, 151-177, doi:10.1016/j.pharmthera.2017.02.009 (2017).

  1. Ellis, R. J. et al. Cerebral amyloid angiopathy in the brains of patients with Alzheimer’s disease: the CERAD experience, Part XV. Neurology 46, 1592-1596, doi:10.1212/wnl.46.6.1592 (1996).
  2. Habiba, U. et al. Detection of retinal and blood Aβ oligomers with nanobodies. 13, e12193, doi.org/10.1002/dad2.12193 (2021).
  3. Hubbard, L. D. et al. Methods for evaluation of retinal microvascular abnormalities associated with hypertension/sclerosis in the Atherosclerosis Risk in Communities Study. Ophthalmology 106, 2269-2280, doi:10.1016/s0161-6420(99)90525-0 (1999).
  4. den Haan, J. et al. Is retinal vasculature a biomarker in amyloid proven Alzheimer’s disease? Alzheimer’s & dementia (Amsterdam, Netherlands) 11, 383-391, doi:10.1016/j.dadm.2019.03.006 (2019).
  5. Querques, G. et al. Functional and morphological changes of the retinal vessels in Alzheimer’s disease and mild cognitive impairment. Scientific reports 9, 63-63, doi:10.1038/s41598-018-37271-6 (2019).
  6. Hinton, D. R., Sadun, A. A., Blanks, J. C. & Miller, C. A. Optic-nerve degeneration in Alzheimer’s disease. The New England journal of medicine 315, 485-487, doi:10.1056/NEJM198608213150804 (1986).
  7. Chan, V. T. T. et al. Spectral-Domain OCT Measurements in Alzheimer’s Disease: A Systematic Review and Meta-analysis. Ophthalmology 126, 497-510, doi:10.1016/j.ophtha.2018.08.009 (2019).
  8. Kirbas, S., Turkyilmaz, K., Anlar, O., Tufekci, A. & Durmus, M. Retinal nerve fiber layer thickness in patients with Alzheimer disease. Journal of neuro-ophthalmology : the official journal of the North American Neuro-Ophthalmology Society 33, 58-61, doi:10.1097/WNO.0b013e318267fd5f (2013).
  9. Cheung, C. Y., Ikram, M. K., Chen, C. & Wong, T. Y. Imaging retina to study dementia and stroke. Progress in retinal and eye research 57, 89-107, doi:10.1016/j.preteyeres.2017.01.001 (2017).
  10. Lopez-de-Eguileta, A. et al. Ganglion cell layer thinning in prodromal Alzheimer’s disease defined by amyloid PET. Alzheimers Dement (N Y) 5, 570-578, doi:10.1016/j.trci.2019.08.008 (2019).
  11. Spaide, R. F., Koizumi, H. & Pozzoni, M. C. Enhanced depth imaging spectral-domain optical coherence tomography. American journal of ophthalmology 146, 496-500, doi:10.1016/j.ajo.2008.05.032 (2008).
  12. López-de-Eguileta, A. et al. Evaluation of choroidal thickness in prodromal Alzheimer’s disease defined by amyloid PET. PloS one 15, e0239484, doi:10.1371/journal.pone.0239484 (2020).
  13. Bulut, M. et al. Choroidal Thickness in Patients with Mild Cognitive Impairment and Alzheimer’s Type Dementia. Journal of ophthalmology 2016, 7, doi:10.1155/2016/7291257 (2016).
  14. Cunha, J. P. et al. Choroidal thinning: Alzheimer’s disease and aging. Alzheimer’s & dementia (Amsterdam, Netherlands) 8, 11-17, doi:10.1016/j.dadm.2017.03.004 (2017).
  15. Gharbiya, M. et al. Choroidal thinning as a new finding in Alzheimer’s disease: evidence from enhanced depth imaging spectral domain optical coherence tomography. Journal of Alzheimer’s disease : JAD 40, 907-917, doi:10.3233/jad-132039 (2014).
  16. Asanad, S. et al. The retinal choroid as an oculovascular biomarker for Alzheimer’s dementia: A histopathological study in severe disease. Alzheimer’s & dementia (Amsterdam, Netherlands) 11, 775-783, doi:10.1016/j.dadm.2019.08.005 (2019).
  17. An, L. & Wang, R. K. In vivo volumetric imaging of vascular perfusion within human retina and choroids with optical micro-angiography. Optics express 16, 11438-11452, doi:10.1364/oe.16.011438 (2008).
  18. Jia, Y. et al. Split-spectrum amplitude-decorrelation angiography with optical coherence tomography. Optics express 20, 4710-4725, doi:10.1364/OE.20.004710 (2012).

30.. Stanga, P. E. et al. Swept-Source Optical Coherence Tomography Angio™ (Topcon Corp, Japan): Technology Review. Developments in ophthalmology 56, 13-17, doi:10.1159/000442771 (2016).

  1. Spaide, R. F., Fujimoto, J. G., Waheed, N. K., Sadda, S. R. & Staurenghi, G. Optical coherence tomography angiography. Progress in retinal and eye research 64, 1-55, doi:10.1016/j.preteyeres.2017.11.003 (2018).
  2. Yoon, S. P. et al. Correlation of OCTA and Volumetric MRI in Mild Cognitive Impairment and Alzheimer’s Disease. Ophthalmic surgery, lasers & imaging retina 50, 709-718, doi:10.3928/23258160-20191031-06 (2019).
  3. van de Kreeke, J. A. et al. Optical coherence tomography angiography in preclinical Alzheimer’s disease. 104, 157-161, doi:10.1136/bjophthalmol-2019-314127 %J British Journal of Ophthalmology (2020).
  4. La Morgia, C. et al. Melanopsin retinal ganglion cell loss in Alzheimer disease. Annals of neurology 79, 90-109, doi:10.1002/ana.24548 (2016).
  5. Dutescu, R. M. et al. Amyloid precursor protein processing and retinal pathology in mouse models of Alzheimer’s disease. Graefe’s archive for clinical and experimental ophthalmology = Albrecht von Graefes Archiv fur klinische und experimentelle Ophthalmologie 247, 1213-1221, doi:10.1007/s00417-009-1060-3 (2009).
  6. Liu, B. et al. Amyloid-peptide vaccinations reduce {beta}-amyloid plaques but exacerbate vascular deposition and inflammation in the retina of Alzheimer’s transgenic mice. The American journal of pathology 175, 2099-2110, doi:10.2353/ajpath.2009.090159 (2009).
  7. Smilnak, G. J. et al. Comorbidity of age-related macular degeneration with Alzheimer’s disease: A histopathologic case-control study. PloS one 14, e0223199-e0223199, doi:10.1371/journal.pone.0223199 (2019).
  8. Csincsik, L. et al. Peripheral Retinal Imaging Biomarkers for Alzheimer’s Disease: A Pilot Study. Ophthalmic research 59, 182-192, doi:10.1159/000487053 (2018).
  9. Koronyo-Hamaoui, M. et al. Identification of amyloid plaques in retinas from Alzheimer’s patients and noninvasive in vivo optical imaging of retinal plaques in a mouse model. NeuroImage 54 Suppl 1, S204-217, doi:10.1016/j.neuroimage.2010.06.020 (2011).
  10. Koronyo, Y. et al. Retinal amyloid pathology and proof-of-concept imaging trial in Alzheimer’s disease. JCI insight 2, doi:10.1172/jci.insight.93621 (2017).
  11. Ratnayaka, J. A., Serpell, L. C. & Lotery, A. J. Dementia of the eye: the role of amyloid beta in retinal degeneration. Eye 29, 1013-1026, doi:10.1038/eye.2015.100 (2015).
  12. Mirzaei, M. et al. Upregulation of Proteolytic Pathways and Altered Protein Biosynthesis Underlie Retinal Pathology in a Mouse Model of Alzheimer’s Disease. Molecular neurobiology 56, 6017-6034, doi:10.1007/s12035-019-1479-4 (2019).
  13. Deng, L. et al. Amyloid β Induces Early Changes in the Ribosomal Machinery, Cytoskeletal Organization and Oxidative Phosphorylation in Retinal Photoreceptor Cells. Frontiers in Molecular Neuroscience 12, doi:10.3389/fnmol.2019.00024 (2019).
  14. Habiba, U. et al. Age-Specific Retinal and Cerebral Immunodetection of Amyloid-β Plaques and Oligomers in a Rodent Model of Alzheimer’s Disease. Journal of Alzheimer’s disease : JAD 76, 1135-1150, doi:10.3233/jad-191346 (2020).
  15. Gupta, V. B. et al. Retinal changes in Alzheimer’s disease- integrated prospects of imaging, functional and molecular advances. Progress in retinal and eye research, 100899, doi:10.1016/j.preteyeres.2020.100899 (2020).
  16. Kerbage, C. et al. Detection of Amyloid beta Signature in the Lens and Its Correlation in the Brain to Aid in the Diagnosis of Alzheimer’s Disease. American journal of Alzheimer’s disease and other dementias 30, 738-745, doi:10.1177/1533317513520214 (2015).
  17. Kile, S. et al. Reduction of Amyloid in the Brain and Retina After Treatment With IVIG for Mild Cognitive Impairment. American journal of Alzheimer’s disease and other dementias 35, 1533317519899800, doi:10.1177/1533317519899800 (2020).
  18. Cordeiro, M. F. et al. Real-time imaging of single neuronal cell apoptosis in patients with glaucoma. Brain : a journal of neurology 140, 1757-1767, doi:10.1093/brain/awx088 (2017).
  19. Yang, E., Al-Mugheiry, T. S., Normando, E. M. & Cordeiro, M. F. Real-Time Imaging of Retinal Cell Apoptosis by Confocal Scanning Laser Ophthalmoscopy and Its Role in Glaucoma. Frontiers in neurology 9, doi:10.3389/fneur.2018.00338 (2018).
  20. Hadoux, X. et al. Non-invasive in vivo hyperspectral imaging of the retina for potential biomarker use in Alzheimer’s disease. Nature communications 10, 4227, doi:10.1038/s41467-019-12242-1 (2019).
  21. Nguyen, C. T. O. et al. Amyloid-beta in the rodent retina exhibits a characteristic hyperspectral profile. Investigative ophthalmology & visual science 57, 2215-2215 (2016).
  22. More, S. S., Beach, J. M. & Vince, R. Early Detection of Amyloidopathy in Alzheimer’s Mice by Hyperspectral Endoscopy. Investigative ophthalmology & visual science 57, 3231-3238, doi:10.1167/iovs.15-17406 (2016).
  23. Yiannopoulou, K. G., Anastasiou, A. I., Zachariou, V. & Pelidou, S.-H. Reasons for Failed Trials of Disease-Modifying Treatments for Alzheimer Disease and Their Contribution in Recent Research. Biomedicines 7, 97, doi:10.3390/biomedicines7040097 (2019).

DECLARATION

DISCLAIMER : THIS WEBSITE IS INTENDED FOR USE BY HEALTHCARE PROFESSIONALS ONLY.
By agreeing & continuing, you are declaring that you are a registered Healthcare professional with an appropriate registration. In order to view some areas of this website you will need to register and login.
If you are not a Healthcare professional do not continue.