Retinal Microvascular Alterations as the Biomarkers for Alzheimer Disease: Are We There Yet?

State-of-the-Art Review Section Editors: Fiona Costello, MD, FRCP(C) Sashank Prasad, MD Retinal Microvascular Alterations as the Biomarkers for Alzheimer Disease: Are We There Yet? Hong Jiang, MD, PhD, Jianhua Wang, MD, PhD, Bonnie E. Levin, PhD, Bernard S. Baumel, MD, Christian J. Camargo, MD, Joseph F. Signorile, PhD, Tania Rundek, MD, PhD Background: Alzheimer disease (AD) is a heterogeneous and multifactorial disorder with an insidious onset and slowly progressive disease course. To date, there are no effective treatments, but biomarkers for early diagnosis and monitoring of disease progression offer a promising first step in developing and testing potential interventions. Cerebral vascular imaging biomarkers to assess the contributions of vascular dysfunction to AD are strongly recommended to be integrated into the current amyloid-b (Ab) [A], tau [T], and neurodegeneration [(N)]—the “AT(N)” biomarker system for clinical research. However, the methodology is expensive and often requires invasive procedures to document cerebral vascular dysfunction. The retina has been used as a surrogate to study cerebral vascular changes. There is growing interest in the identification of retinal microvascular changes as a safe, easily accessible, low cost, and time-efficient approach to enhancing our understanding of the vascular pathogenesis associated with AD. Evidence acquisition: A systemic review of the literature was performed regarding retinal vascular changes in AD and its prodromal stages, focusing on functional and structural changes of large retinal vessels (vessels visible on fundus photographs) and microvasculature (precapillary arterioles, capillary, and postcapillary venules) that are invisible on fundus photographs. Results: Static and dynamic retinal microvascular alterations such as retinal arterial wall motion, blood flow rate, and microvascular network density were reported in AD, mild cognitive impairment, and even in the preclinical Department of Ophthalmology (HJ, JW), Bascom Palmer Eye Institute, University of Miami Miller School of Medicine, Miami, Florida; Department of Neurology (HJ, BEL, BSB, CJC, TR), University of Miami Miller School of Medicine, Miami, Florida; and Department of Kinesiology and Sports Sciences (JFS), University of Miami, Miami, Florida. Supported by the NIH Center Grant P30 EY014801, NIH NINDS 1R01NS111115-01 (J. Wang), the Ed and Ethel Moor Alzheimer’s Disease Research Program (Florida Health, 20A05, to H. Jiang), and a grant from Research to Prevent Blindness (RPB). The authors report no conflicts of interest. Address correspondence to Hong Jiang, MD, PhD, Bascom Palmer Eye Institute, University of Miami, Miller School of Medicine, 1638 NW 10th Avenue, McKnight Building—Room 202A, Miami, FL 33136; E-mail: [e-mail] Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 stages of the disease. The data are somewhat controversial and inconsistent among the articles reviewed and were obtained based on cross-sectional studies that used different patient cohorts, equipment, techniques, and analysis methods. Conclusions: Retinal microvascular alterations exist across the AD spectrum. Further large scale, within-subject longitudinal studies using standardized imaging and analytical methods may advance our knowledge concerning vascular contributions to the pathogenesis of AD. Journal of Neuro-Ophthalmology 2021;41:251–260 doi: 10.1097/WNO.0000000000001140 © 2020 by North American Neuro-Ophthalmology Society L ate-onset sporadic Alzheimer disease (AD), an insidious onset and slowly progressing neurodegenerative disorder, is the leading cause of disability in older people worldwide. Because of the aging population, dramatically increasing global prevalence of AD poses huge epidemiological burden on society and health care system in all countries in the world. There are currently about 35 million AD patients worldwide and 7 million new cases yearly (1). As a major public health concern, it is critical to effectively prevent and treat AD to slow down the growth of the disease. The cerebral neuronal dysfunction usually manifests decades before the appearance of the cognitive function decline, stressing the importance of sensitive and easy accessible biomarkers for early diagnosis and monitoring of disease progression (2). However, existing biomarkers are inefficient for diagnosis, prognosis, and tracking because they are often costly, require special equipment and facilities (MRI), invasive (bloodborne markers), and often inconclusive (3,4). AD is considered to be a heterogeneous disease with multifactorial causes (4–6). The pathogenesis of AD is unclear. Although amyloid-b (Ab) [A], tau [T], and neurodegeneration [(N)]—the “AT(N)” biomarker system (7,8) has been recommended for AD diagnosis in clinical research, no causal relationship has been established between the A and T biomarkers 251 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review and clinical symptoms (4). Accumulating evidence indicates vascular abnormalities are inextricably linked to the pathogenesis of AD (9,10). Patients with AD commonly have multiple vascular risk factors, and the control of these vascular risk factors helps to improve their cognitive function (11). Evidently, cerebral microvascular alterations, especially at the capillary level (12–15), are among the major pathogenic contributors to cognitive impairment and dementia (16). The decreased cerebral perfusion is reported before the development of cognitive function decline (17) and in patients with AD (18–20). Hence, the incorporation of cerebral vascular dysfunction biomarkers into the “AT(N)” biomarker system is needed (4). However, it is difficult to monitor the cerebral microvascular changes in vivo (21). As an extension of the central nervous system, retinal structural and vascular alterations reflect the cerebral ADrelated pathologic changes (22). Indeed, a significant thinning of the retinal nerve fiber layer (RNFL) and/or the combined ganglion and plexiform layer (GCIPL) that correlate with MRI brain volume decline are reported in patients with AD (23,24) and those patients with mild cognitive impairment (MCI) who converted to AD (25). Hence, retinal structural changes have been suggested to be the markers in staging disease progression (25). Furthermore, clinic-based and population-based studies using fundus photography have demonstrated less complex retinal vasculature, retinal arteriolar narrowing, retinal venular widening, and smaller, more tortuous retinal vessels in patients with AD, compared with cognitively normal controls (CN) (26–30). The present review summarizes the multiple retinal vascular imaging methods used to evaluate the human retinal vascular function with a special focus on the microvasculature that is invisible on fundus photographs in patients with the AD spectrum. The correlations between retina, brain, and AT [N] system were examined. METHODS PubMed and Google Scholar were searched using the keywords “retinal blood flow,” “retinal vasculature,” “Alzheimer disease,” “mild cognitive impairment,” and “preclinical AD.” All published articles regarding functional changes of large retinal vessels (vessel visible on fundus photographs) and microvasculature (precapillary arterioles, capillary, and postcapillary venules) that are invisible on fundus photographs are reviewed and included. The studies solely based on fundus photography images and retinal structural changes were excluded. RESULTS Static Retinal Microvascular Structural Alterations in the AD Spectrum As cerebral capillary dysfunction is related to AD-mediated neurodegeneration (31), it is crucial to study the retinal 252 capillary network alterations. However, the resolution of fundus photography is not high enough to visualize the microvascular network (32). The introduction of optical coherence tomography angiography (OCTA), a noninvasive imaging modality, greatly facilitates visualization of retinal microvasculature (precapillary arterioles, capillary, and postcapillary venules) that would otherwise be invisible with fundus photography (33). Therefore, OCTA greatly simplifies the study of the retinal microvasculature in AD. Two layers of the retinal microvascular network are often defined and studied by OCTA. These microvascular layers include the superficial vascular plexus (SVP) and deep vascular plexus (DVP). SVP sits in the RNFL and GCIPL, and DVP positions in the inner nuclear (INL) and outer plexiform layers (Figs. 1, 2) (34). A summary of OCTA findings of retinal microvascular changes across the AD spectrum is provided in Table 1. Allowing for the differences in patient cohorts, equipment, and techniques, several groups reported significantly reduced densities of SVP in patients with late-onset and sporadic AD, compared with CN (10,35–40). The loss of retinal microvasculature is not only restricted to the macular area but also at radial peripapillary capillaries, indicating the widespread existence of this loss (10). The reduced density of DVP in AD (35,41) and MCI was also reported (35) and associated with GCIPL thinning (35). Furthermore, a more profound loss of DVP in AD compared with MCI indicated that retinal vascular abnormalities might contribute to the potential conversion from MCI to AD (35). More interestingly, the SVP density was found to be highly correlated with the Fazekas scale (42) of brain white matter (10) and negatively associated with the expansion of inferolateral ventricle volume inferolateral ventricle volume (ILV) (37). The Fazekas scale is used to quantify the amount of white matter T2 hyperintense lesions. ILV is known to strongly correlate with cognitive function decline in patients with MCI and AD (38,43). The reduction in retinal vessel density echoes the cerebral hypoperfusion measured by brain MRI in patients with both AD and MCI (18–20). The diminished retinal vascular density could be attributed to aging and vascular risk factors, such as diabetes and hypertension. In addition, Ab is also known to accumulate in small vessel walls and contributes to the degeneration of the vascular smooth muscle cells and loss of vessel wall integrity (44– 46), resulting in cerebral amyloidal angiopathy (47,48). By contrast, Querques et al did not find a significant difference in retinal microvascular density using OCTA in patients with AD, compared with CN. Of note, type 2 diabetes mellitus (T2DM) was an exclusion criterion in this study (49), whereas T2DM is a major risk factor for AD (50,51). Similar results were reported by den Haan et al (52), when studying a group of patients with AD who were relatively young: from 57.3 to 73.5 years (mean ± SD: 65.4 ± 8.1). It is known that vascular dysfunction may not contribute significantly in early-onset AD (53), Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Authors Disease No. of pts AT(N) Biomarker Pre-AD vs CN 13 vs 111 Ab PET O’Bryhim et al (54) Bulut et al (36) Pre-AD vs CN 14 vs 18 CSF or Ab PET AD vs CN 26 vs 26 None Jiang et al (35) AD vs MCI vs CN 12 vs 19 vs 21 None Grewal et al (40) AD vs CN 1 vs 1 (MZ) None Yoon et al (37) AD vs MCI vs CN 39 vs 37 vs 133 None Yoon et al (38) AD vs MCI 9 vs 7 None Zabel et al (41) AD vs CN 27 vs 27 Ab PET Lahme et al (10) AD vs CN 36 vs 38 CSF Zhang et al (39) Querques et al (49) den Haan et al (52) aMCI/eAD vs CN AD vs MCI vs CN 32 vs 16 12 vs 12 vs 32 None CSF AD vs CN 48 vs 38 CSF or Ab PET VD higher in RVN in preAD; Same FAZ size Enlarged FAZ in pre-AD VD lower in RVN; Enlarged FAZ AD vs CN: VD lower in RVN, SVP, and DVP; MCI vs CN: VD lower at superonasal quant DVP; Trend of VD loss from CN to MCI to AD VD lower in SVP; Enlarged FAZ AD vs MCI and AD vs NC: VD lower in SVP; MCI vs NC: no difference AD vs MCI: VD lower in SVP AD vs NC: DV lower in DVP; Enlarged FAZ VD lower in SVP and RPCs Correlation OCT Device VD and BPND Zeiss (Cirrus 5000 Angioplex) Inner foveal thinning MMSE Avanti RTVue XR (Optovue) Zeiss (Cirrus 5000 Angioplex) GCIPL and DVP VD Zeiss (Cirrus 5000 Angioplex) n/a Zeiss (Cirrus 5000 Angioplex) n/a Zeiss (Cirrus 5000 Angioplex) Inverse correlation between ILV with VD n/a Zeiss (Cirrus 5000 Angioplex) Avanti RTVue XR (Optovue) VD lower in SVP None Fazekas scale WMT But no CSF Ab or tau level MoCA n/a Avanti RTVue XR (Optovue) Zeiss (Cirrus 5000 Angioplex) None n/a Zeiss (Cirrus 5000 Angioplex) Avanti RTVue XR (Optovue) State-of-the-Art Review van de Kreeke et al (56) OCTA Findings AD, Alzheimer disease; aMCI/eAD, amnestic MCI/early AD; BPND, parametric global cortical nondisplaceable binding protein (Ab); CN, cognitively normal control; CSF, cerebrospinal fluid; CSF, CSF Ab PET and/or Tau; DVP, deep vascular plexus; FAZ, fovea avascular zone; ILV, inferolateral ventricle volume; MZ, monozygotic twins; MCI, mild cognitive impairment; MMSE, minimental state examination; MoCA, montreal cognitive assessment OCTA, optical coherence tomography angiography; pre-AD, preclinical AD; pts, patients; RPCs, radial peripapillary capillaries of optic nerve head; RVN, retinal vascular network; SVP, superior vascular plexus; VD, vessel density; WMT, white matter tissue. 253 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. TABLE 1. OCTA Findings of Retinal Microvascular Changes in the AD spectrum State-of-the-Art Review FIG. 1. OCTA for quantitative analysis of microvascular network in the intraretinal layer. A. Intraretinal layers were imaged using UHR-OCT and segmented using the Orion software. B. The SVP (superior vascular plexus) of a scan of 3 · 3 mm imaged using OCTA with the analyzed area of a 2.5-mm disc (red circle). C. The thickness map of the RNFL + GCIPL in a circular area (f 2.5 mm). The volumetric vascular density (VVD) of the SVP (VVDs) was the vessel density of the SVP (analyzed as fractal dimension Dbox) divided by the tissue volume of the RNFL and GCIPL in the disc (f 2.5 mm). D. The RVN: retinal vascular network. E. The thickness map of the inner retina, including RNFL, GCIPL, INL, and OPL. The VVDr was the vessel density of the RVN (analyzed as fractal dimension Dbox) divided by the tissue volume of the inner retina. F. The DVP: deep vascular plexus (G) The thickness map of the INL and OPL in a disc (f 2.5 mm). The VVDd was the vessel density of the DVP (analyzed as fractal dimension Dbox) divided by the tissue volume of the INL and OPL. GCIPL, combined ganglion cell and inner plexiform layer; INL, inner nuclear layer; OCTA, optical coherence tomography angiography; OPL, outer plexiform layer; RNFL, retinal nerve fiber layer; SVP, superficial vascular plexus; UHR, ultra-high resolution. (cited from Lin et al (34) under open-access license). which might be one of the underlying reasons that no significant difference in retinal microvascular density was found in their study. The size of the fovea avascular zone (FAZ) is correlated with the area with no capillary perfusion, and the enlarged FAZ indicates the loss of the retinal microvessels (Fig. 3) (54,55). The enlarged FAZ was found in preclinical AD (cognitively normal individuals with positive AD biomarkers) (54), similarly as in AD (36,40,41). The enlarged FAZ is correlated with inner foveal thinning (49,54), sustained that retinal microvascular and neuronal alterations could happen very early before the patients have any cognitive function decline. Interestingly, no difference of FAZ size but significantly higher retinal microvessel density in both macular and optic nerve head in preclinical AD was reported by van de Kreeke et al (56). The findings were believed to be due to the inflammation and increased blood flow that related to amyloid accumulation in the early stage, mirroring the changes in the central nervous system (57). Given the thinning of RNFL and GCIPL evidently coexists with the vascular dysfunction through the disease course of AD (35,38,39), simultaneous analysis of both the microvasculature and the neural structure by measuring the 254 volumetric vascular density (Fig. 1) (34,58) may reveal the more precise information of retinal vascular changes in the AD spectrum and could be potentially used in the future retinal vascular study. Functional Retinal Vascular Alterations in the Alzheimer Disease Spectrum In addition to the static microvascular structural alterations, impaired cerebral vasomotion (the spontaneous rhythmic modulation of arterial diameter) and related blood flow alterations are known to contribute to the pathogenesis of AD (59,60). Dysregulation of cerebral blood flow such as reduced blood flow when resting and responding to neuronal stimulation in AD is evident (61,62). To explore the retinal vascular dysfunction in AD, various types of equipment have been used to study the retinal blood flow and vessel reactions. A dynamic vessel analyzer (DVA; Imedos Systems UG, Jena, Germany) measures the retinal vessel responses to diffuse luminance flicker (63–66). The changes of retinal arterial and venous diameter visible on the fundus photographs were measured at baseline, during and after a flickeringlight stimulation (63–66). Significantly reduced retinal arterial dilation response to flicker light impulse was Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review FIG. 2. Representative images of the retinal microvascular networks imaged using optical coherence tomography angiography (OCTA). Patients with Alzheimer disease (AD) (A–C) and mild cognitive impairment (MCI) (D–F) as well as a control subject (G–I) were imaged. Compared with the normal control (G and I), the large vessels in AD and MCI patients had similar densities in the superficial vascular plexus (A and D) and retinal vascular network (C and F) but showed some degrees of tortuosity. The microvessels in the deep vascular plexus in AD (B) and MCI (E) patients seemed to be less dense compared with the normal control (H). Note: the deep vascular plexus images are raw images, showing the graphic projection artifact of the large vessels. Bar = 0.5 mm. (Reproduced and used with permission obtained through RightsLink. Adaptations are themselves works protected by copyright. So in order to publish this adaptation, authorization must be obtained both from the owner of the copyright in the original work and from the owner of copyright in the translation or adaptation). found in patients with AD and MCI, compared with cognitively normal control (NC), and these were correlated with the cerebrospinal fluid Ab level (49). By contrast, Golzan et al (67) reported increased arterial pulsation that was positively associated with neocortical Ab scores in older adults with subjective memory loss and AD. Their analysis was performed after adjusting for comorbidities, such as hypertension, diabetes, and smoking. Similarly, increased but delayed arterial vasodilatation in patients with AD compared with NC and MCI were found by Kotliar et al (68), whereas decreased arterial dilation was found in MCI compared with NC (68). The reasons behind these conflicting reports may be due to different patient cohorts, dissimilar techniques, or other ophthalmologic and systemic conditions, such as diabetes that are known to impact retinal vascular functions (65,66). However, the observed abnormal arteJiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 rial wall movement indicated possible neurovascular coupling impairment secondary to arterial endothelial dysfunction (69) or vessel rigidity (70). Chronic hypoperfusion in the brain and thickened basal membrane of cerebral vessels is reported in patients with AD (71). Furthermore, the alteration of vascular response in subjects with MCI and subjective memory loss implies the vascular dysfunction presented early in the disease course (49,68). Laser Doppler retinal blood flowmetry (CLBF 100, Canon, Tokyo, Japan) was used to measure the retinal blood flow rate (BFR) based on the blood column diameter and the centerline blood velocity in the central retinal artery and vein (72). The measurement is not synchronized with the cardiac cycle. The significantly reduced venous BFR in patients with AD, compared with CN and MCI, and in patients with MCI compared with CN were reported (73,74). Compared with CLBF, 255 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review FIG. 3. Foveal avascular zone (FAZ) and perfusion map. The enface angiography vessel image was obtained using optical coherence tomography (OCT) angiography (Avanti OptoVue; OptoVue). The FAZ is located in the center (the dark area) of the macula in the enface angiography of the retina (A). To visualize capillary perfusion, a Gaussian density filter (4 · 4 pixels) was used to process the skeletonized vascular images, and the capillary density was color coded to create a capillary perfusion map (B), which shows the nonperfusion in the center of the fovea. The bar denotes to percent the regional perfusion rate. which measure central retinal arterial and venular function, the retinal function imager system (Optical Imaging Ltd., Rehovot, Israel) assesses the BFR in precapillary arterioles and postcapillary venules (75,76). The fundus camera-based device uses the motion of red blood cell clusters as the intrinsic motion contrast to noninvasively measure the blood flow velocity and BFR in the precapillary arterioles and postcapillary venules while synchronizing with the cardiac cycle to ensure the mea- surement at the same time point of the cardiac rhythm (Fig. 4) (75,76). Significantly lower BFRs in both arterioles and venules of patients with AD and MCI compared with NC were reported (77). There was no significant difference in age, sex, heart rate, blood pressure, or vascular risk factors among these 3 groups (77). More interestingly, the retinal tissue perfusion (RTP) measured based on the blood flow velocity and tissue volume in which the blood supply perfuse was TABLE 2. Retinal vascular findings as possible image biomarkers in the AD spectrum Retinal Finding Imaging Modality Advantage Disadvantage VD in SVP and DVP (10,35–41,52,54) OCTA Wide availability and no pupil dilation FAZ zone size (36,40,41,54,56) OCTA Wide availability and no pupil dilation Vessel response to flicker (67,68) BFR (73,74) Dynamic vessel analyzer Laser Doppler retinal blood flowmetry Dynamic analysis of vasodilatation Direct measurement of blood flow BFR (77) RFI RTP (78) RFI Direct measurement of blood velocity and flow measurements in venules and arterioles synchronization of heat beat. Direct measurement of tissue perfusion direct measurement of blood velocity and flow measurements in venules and arterioles synchronization of heat beat. No standardized analysis and requirement of clear ocular media No standardized analysis and requirement of clear ocular media No wide accessibility and large vessels only Relative measurement of all flow information, no synchronization of heartbeat, larger vessels only, and no wide accessibility Bright visible light, pupil dilation, requirement of clear ocular media, and no wide accessibility Bright visible light, pupil dilation, requirement of clear ocular media, no wide accessibility, and requirement of retinal tissue volume information AD, Alzheimer disease; BFR, blood flow rate; DVP; deep vascular plexus; FAZ, foveal avascular zone; OCTA, optical coherence tomography angiography; RFI, retinal function imager; RTP, retinal tissue perfusion; SVP, superficial vascular plexus; VD, vessel density. 256 Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review reduced central retinal arterial dilation obtained by the DVA test (49). A summary of retinal vascular findings as possible image biomarkers within the AD spectrum is provided in Table 2. CONCLUSIONS FIG. 4. Retinal blood flow and tissue volume of the inner retina. A. A representative image of the retina from an AD patient was imaged using the RFI with a FOV of 4.3 · 4.3 mm (20-degrees setting) centered on the fovea, corresponding to the dark area in the center. The blood flow velocities (mm/s) were overlaid with the vessels. The arterioles marked in red have negative velocity values, indicating that blood is flowing away from the heart (flow moving toward the fovea). The venules marked in purple have positive velocity values, indicating that blood is flowing toward the heart. To analyze the blood flow in the macula, a 2.5-mm circle (blue) centered on the fovea was outlined. Vessel diameters of the vessels crossing the circle were measured at the locations marked as yellow and green dots. The arteriolar blood flow of these arterioles was calculated using the velocity and diameter (yellow dot). The venular blood flow of these venules was also calculated using velocity and diameter (green dot). All the flow measurements in the arterioles (all yellow dots) were summed to obtain the total arteriolar flow of the macula. Similarly, all the flow measurements in the venules (all green dots) were summed to obtain the total venular flow of the macula. B. To measure the tissue volume, the same eye was imaged using a custom UHR-OCT with a raster scan of 6 · 6 mm. To calculate the tissue-dependent blood perfusion, the volumetric tissue volume of the inner retina, including RFNL, GCIPL, INL, and OPL, was measured using segmentation software (Orion, Voxeleron) in the round area with a diameter of 2.5 mm centered on the fovea. GCIPL, ganglion cell-inner plexiform layer; INL, inner nuclear layer; OPL, outer plexiform layer; ONL, outer nuclear layer; PR, retinal photoreceptor; RNFL, retinal nerve fiber layer; RFI, retinal function imager (cited from Gameiro et al (78) under open-access license. Adaptations are themselves works protected by copyright. So in order to publish this adaptation, authorization must be obtained both from the owner of the copyright in the original work and from the owner of copyright in the translation or adaptation). FOV, field of view. significantly lower in patients with AD compared with NC (78). The RTP was also found to be correlated with GCIPL thickness in these patients with AD (Fig. 4) (78). These findings seemed to echo cerebral hypoperfusion (18–20), and the Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 In summary, there is a growing body of evidence showing important vascular contributions associated with AD. Both static and dynamic retinal vascular changes have been reported in patients with AD, MCI, and even in preclinical stages, supporting the strong vascular contribution to the pathogenesis of AD. The current literature on retinal vascular changes in AD, however, is inconsistent and likely due to different equipment and analysis methods as well as different patients’ characteristics with respect to age range, disease stage, comorbidities, diagnostic criteria, and differing types of neurocognitive assessments. Furthermore, almost all the studies are cross-sectional comparisons of patients with AD vs CN, although some of them involved MCI and preclinical AD patients. To understand the possible causal link between vascular dysfunction and AD, it will be important to study biomarkers associated with disease onset and progression using a large-scale prospective within-subject design, after retinal vasculature among individuals in the early preclinical stages to (subjective memory complaints) symptomatic AD. Adults older than 50 years usually have reduced vision due to presbyopia and require routine eye care with follow-up. Retinal imaging is usually necessary and convenient to perform during their regular eye examination. Noninvasive, costeffective, and easily accessible retinal imaging, such as OCTA, can become a universally available screening tool to identify persons at high risk of AD based on retinal vascular changes. Once developed, these retinal vascular biomarkers, especially at the capillary level, may also be used to monitor disease progression and therapeutic efficacy. To better understand the link between the eye and brain vasculature and other neural structures, future studies with simultaneous imaging of the eye and the brain in patients with AD, MCI, and its preclinical stages are also warranted to further validate the applications of the retinal imaging in AD. STATEMENT OF AUTHORSHIP Category 1: a. Conception and design: H. Jiang; b. Acquisition of data: H. Jiang and J. Wang; c. Analysis and interpretation of data: H. Jiang, J. Wang, B. Levin, J. F. Signorile, and T. Rundek. Category 2: a. Drafting the manuscript: H. Jiang, J. Wang, B. Levin, B. S. Baumel, C. J. Carmago, J. F. Signorile, and T. Rundek; b. Revising it for intellectual content: H. Jiang, J. Wang, B. Levin, B. S. Baumel, C. J. Carmago, J. F. Signorile, and T. Rundek. Category 3: a. Final approval of the completed manuscript: H. Jiang, J. Wang, B. Levin, B. S. Baumel, C. J. Carmago, J. F. Signorile, and T. Rundek. 257 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review REFERENCES 1. Dementia: Fact Sheet. World Health Organization 2019. Geneva, Switzerland WHO; 2019. 2. Holtzman DM, Morris JC, Goate AM. Alzheimer’s disease: the challenge of the second century. Sci Transl Med. 2011;3:77sr1. 3. Sharma N, Singh AN. Exploring biomarkers for Alzheimer’s disease. J Clin Diagn Res. 2016;10:KE01–KE06. 4. Sweeney MD, Montagne A, Sagare AP, Nation DA, Schneider LS, Chui HC, Harrington MG, Pa J, Law M, Wang DJJ, Jacobs RE, Doubal FN, Ramirez J, Black SE, Nedergaard M, Benveniste H, Dichgans M, Iadecola C, Love S, Bath PM, Markus HS, Salman RA, Allan SM, Quinn TJ, Kalaria RN, Werring DJ, Carare RO, Touyz RM, Williams SCR, Moskowitz MA, Katusic ZS, Lutz SE, Lazarov O, Minshall RD, Rehman J, Davis TP, Wellington CL, Gonzalez HM, Yuan C, Lockhart SN, Hughes TM, Chen CLH, Sachdev P, O’Brien JT, Skoog I, Pantoni L, Gustafson DR, Biessels GJ, Wallin A, Smith EE, Mok V, Wong A, Passmore P, Barkof F, Muller M, Breteler MMB, Roman GC, Hamel E, Seshadri S, Gottesman RF, van Buchem MA, Arvanitakis Z, Schneider JA, Drewes LR, Hachinski V, Finch CE, Toga AW, Wardlaw JM, Zlokovic BV. Vascular dysfunction-the disregarded partner of Alzheimer’s disease. Alzheimers Dement. 2019;15:158–167. 5. Nation DA, Sweeney MD, Montagne A, Sagare AP, D’Orazio LM, Pachicano M, Sepehrband F, Nelson AR, Buennagel DP, Harrington MG, Benzinger TLS, Fagan AM, Ringman JM, Schneider LS, Morris JC, Chui HC, Law M, Toga AW, Zlokovic BV. Blood-brain barrier breakdown is an early biomarker of human cognitive dysfunction. Nat Med. 2019;25:270–276. 6. Nelson AR, Sweeney MD, Sagare AP, Zlokovic BV. Neurovascular dysfunction and neurodegeneration in dementia and Alzheimer’s disease. Biochim Biophys Acta. 2016;1862:887–900. 7. Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Feldman HH, Frisoni GB, Hampel H, Jagust WJ, Johnson KA, Knopman DS, Petersen RC, Scheltens P, Sperling RA, Dubois B. A/T/N: an unbiased descriptive classification scheme for Alzheimer disease biomarkers. Neurology. 2016;87:539–547. 8. Jack CR Jr, Bennett DA, Blennow K, Carrillo MC, Dunn B, Haeberlein SB, Holtzman DM, Jagust W, Jessen F, Karlawish J, Liu E, Molinuevo JL, Montine T, Phelps C, Rankin KP, Rowe CC, Scheltens P, Siemers E, Snyder HM, Sperling R; NIA-AA. Research Framework: toward a biological definition of Alzheimer’s disease. Alzheimers Dement. 2018;14:535–562. 9. Santos CY, Snyder PJ, Wu WC, Zhang M, Echeverria A, Alber J. Pathophysiologic relationship between Alzheimer’s disease, cerebrovascular disease, and cardiovascular risk: a review and synthesis. Alzheimers Dement (Amst). 2017;7:69–87. 10. Lahme L, Esser EL, Mihailovic N, Schubert F, Lauermann J, Johnen A, Eter N, Duning T, Alnawaiseh M. Evaluation of ocular perfusion in Alzheimer’s disease using optical coherence tomography angiography. J Alzheimers Dis. 2018;66:1745– 1752. 11. de la Torre JC. Is Alzheimer’s disease a neurodegenerative or a vascular disorder? Data, dogma, and dialectics. Lancet Neurol. 2004;3:184–190. 12. Hunter JM, Kwan J, Malek-Ahmadi M, Maarouf CL, Kokjohn TA, Belden C, Sabbagh MN, Beach TG, Roher AE. Morphological and pathological evolution of the brain microcirculation in aging and Alzheimer’s disease. PLoS One. 2012;7:e36893. 13. Brown WR, Thore CR. Review: cerebral microvascular pathology in ageing and neurodegeneration. Neuropathol Appl Neurobiol. 2011;37:56–74. 14. Bhat NR. Vasculoprotection as a convergent, multi-targeted mechanism of anti-AD therapeutics and interventions. J Alzheimers Dis. 2015;46:581–591. 15. Ostergaard L, Jespersen SN, Engedahl T, Gutierrez JE, Ashkanian M, Hansen MB, Eskildsen S, Mouridsen K. Capillary dysfunction: its detection and causative role in dementias and stroke. Curr Neurol Neurosci Rep. 2015;15:37. 258 16. Snyder HM, Corriveau RA, Craft S, Faber JE, Greenberg SM, Knopman D, Lamb BT, Montine TJ, Nedergaard M, Schaffer CB, Schneider JA, Wellington C, Wilcock DM, Zipfel GJ, Zlokovic B, Bain LJ, Bosetti F, Galis ZS, Koroshetz W, Carrillo MC. Vascular contributions to cognitive impairment and dementia including Alzheimer’s disease. Alzheimers Dement. 2015;11:710–717. 17. Park KW, Yoon HJ, Kang DY, Kim BC, Kim S, Kim JW. Regional cerebral blood flow differences in patients with mild cognitive impairment between those who did and did not develop Alzheimer’s disease. Psychiatry Res. 2012;203:201–206. 18. Hays CC, Zlatar ZZ, Wierenga CE. The utility of cerebral blood flow as a biomarker of preclinical Alzheimer’s disease. Cell Mol Neurobiol. 2016;36:167–179. 19. Ruitenberg A, Den HT, Bakker SL, van Swieten JC, Koudstaal PJ, Hofman A, Breteler MM. Cerebral hypoperfusion and clinical onset of dementia: the Rotterdam Study. Ann Neurol. 2005;57:789–794. 20. Austin BP, Nair VA, Meier TB, Xu G, Rowley HA, Carlsson CM, Johnson SC, Prabhakaran V. Effects of hypoperfusion in Alzheimer’s disease. J Alzheimers Dis. 2011;26(suppl 3):123– 133. 21. Smith EE, Beaudin AE. New insights into cerebral small vessel disease and vascular cognitive impairment from MRI. Curr Opin Neurol. 2018;31:36–43. 22. Ngolab J, Honma P, Rissman RA. Reflections on the utility of the retina as a biomarker for Alzheimer’s disease: a literature review. Neurol Ther. 2019;8:57–72. 23. den HJ, Janssen SF, van de Kreeke JA, Scheltens P, Verbraak FD, Bouwman FH. Retinal thickness correlates with parietal cortical atrophy in early-onset Alzheimer’s disease and controls. Alzheimers Dement (Amst). 2018;10:49–55. 24. Liu S, Ong YT, Hilal S, Loke YM, Wong TY, Chen CL, Cheung CY, Zhou J. The association between retinal neuronal layer and brain structure is disrupted in patients with cognitive impairment and Alzheimer’s disease. J Alzheimers Dis. 2016;54:585–595. 25. Choi SH, Park SJ, Kim NR. Macular ganglion cell -inner plexiform layer thickness is associated with clinical progression in mild cognitive impairment and Alzheimers disease. PLoS One. 2016;11:e0162202. 26. Cheung CY, Ong YT, Ikram MK, Ong SY, Li X, Hilal S, Catindig JA, Venketasubramanian N, Yap P, Seow D, Chen CP, Wong TY. Microvascular network alterations in the retina of patients with Alzheimer’s disease. Alzheimers Dement. 2014;10:135–142. 27. Frost S, Kanagasingam Y, Sohrabi H, Vignarajan J, Bourgeat P, Salvado O, Villemagne V, Rowe CC, Macaulay SL, Szoeke C, Ellis KA, Ames D, Masters CL, Rainey-Smith S, Martins RN; AIBL Research Group. Retinal vascular biomarkers for early detection and monitoring of Alzheimer’s disease. Transl Psychiatry. 2013;3:e233. 28. Williams MA, McGowan AJ, Cardwell CR, Cheung CY, Craig D, Passmore P, Silvestri G, Maxwell AP, McKay GJ. Retinal microvascular network attenuation in Alzheimer’s disease. Alzheimers Dement (Amst). 2015;1:229–235. 29. Cheung CY, Ong YT, Ikram MK, Chen C, Wong TY. Retinal microvasculature in Alzheimer’s disease. J Alzheimers Dis. 2014;42(suppl 4):S339–S352. 30. Cheung CY, Chan VTT, Mok VC, Chen C, Wong TY. Potential retinal biomarkers for dementia: what is new? Curr Opin Neurol. 2019;32:82–91. 31. Nielsen RB, Egefjord L, Angleys H, Mouridsen K, Gejl M, Moller A, Brock B, Braendgaard H, Gottrup H, Rungby J, Eskildsen SF, Ostergaard L. Capillary dysfunction is associated with symptom severity and neurodegeneration in Alzheimer’s disease. Alzheimers Dement 2017;13:1143–1153. 32. Spaide RF, Klancnik JM Jr, Cooney MJ. Retinal vascular layers imaged by fluorescein angiography and optical coherence tomography angiography. JAMA Ophthalmol. 2015;133:45– 50. 33. Fingler J, Readhead C, Schwartz DM, Fraser SE. Phasecontrast OCT imaging of transverse flows in the mouse retina and choroid. Invest Ophthalmol Vis Sci. 2008;49:5055–5059. Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review 34. Lin Y, Jiang H, Liu Y, Rosa GG, Gregori G, Dong C, Rundek T, Wang J. Age-related alterations in retinal tissue perfusion and volumetric vessel density. Invest Ophthalmol Vis Sci. 2019;60:685–693. 35. Jiang H, Wei Y, Shi Y, Wright CB, Sun X, Gregori G, Zheng F, Vanner EA, Lam BL, Rundek T, Wang J. Altered macular microvasculature in mild cognitive impairment and alzheimer disease. J Neuroophthalmol. 2018;38:292–298. 36. Bulut M, Kurtulus F, Gozkaya O, Erol MK, Cengiz A, Akidan M, Yaman A. Evaluation of optical coherence tomography angiographic findings in Alzheimer’s type dementia. Br J Ophthalmol. 2018;102:233–237. 37. Yoon SP, Thompson AC, Polascik BW, Calixte C, Burke JR, Petrella JR, Grewal DS, Fekrat S. Correlation of OCTA and volumetric MRI in mild cognitive impairment and Alzheimer’s disease. Ophthalmic Surg Lasers Imaging Retina. 2019;50:709–718. 38. Yoon SP, Grewal DS, Thompson AC, Polascik BW, Dunn C, Burke JR, Fekrat S. Retinal microvascular and neurodegenerative changes in Alzheimer’s disease and mild cognitive impairment compared with control participants. Ophthalmol Retina. 2019;3:489–499. 39. Zhang YS, Zhou N, Knoll BM, Samra S, Ward MR, Weintraub S, Fawzi AA. Parafoveal vessel loss and correlation between peripapillary vessel density and cognitive performance in amnestic mild cognitive impairment and early Alzheimer’s Disease on optical coherence tomography angiography. PLoS One. 2019;14:e0214685. 40. Grewal DS, Polascik BW, Hoffmeyer GC, Fekrat S. Assessment of differences in retinal microvasculature using OCT angiography in Alzheimer’s disease: a twin discordance report. Ophthalmic Surg Lasers Imaging Retina 2018;49:440–444. 41. Zabel P, Kaluzny JJ, Wilkosc-Debczynska M, Gebska-Toloczko M, Suwala K, Zabel K, Zaron A, Kucharski R, Araszkiewicz A. Comparison of retinal microvasculature in patients with Alzheimer’s disease and primary open-angle glaucoma by optical coherence tomography angiography. Invest Ophthalmol Vis Sci. 2019;60:3447–3455. 42. Fazekas F, Chawluk JB, Alavi A, Hurtig HI, Zimmerman RA. MR signal abnormalities at 1.5 T in Alzheimer’s dementia and normal aging. AJR Am J Roentgenol. 1987;149:351–356. 43. Jack CR Jr, Shiung MM, Gunter JL, O’Brien PC, Weigand SD, Knopman DS, Boeve BF, Ivnik RJ, Smith GE, Cha RH, Tangalos EG, Petersen RC. Comparison of different MRI brain atrophy rate measures with clinical disease progression in AD. Neurology. 2004;62:591–600. 44. Blaise R, Mateo V, Rouxel C, Zaccarini F, Glorian M, Bereziat G, Golubkov VS, Limon I. Wild-type amyloid beta 1-40 peptide induces vascular smooth muscle cell death independently from matrix metalloprotease activity. Aging Cell. 2012;11:384–393. 45. Vinters HV, Wang ZZ, Secor DL. Brain parenchymal and microvascular amyloid in Alzheimer’s disease. Brain Pathol. 1996;6:179–195. 46. Kalaria RN, Premkumar DR, Pax AB, Cohen DL, Lieberburg I. Production and increased detection of amyloid beta protein and amyloidogenic fragments in brain microvessels, meningeal vessels and choroid plexus in Alzheimer’s disease. Brain Res Mol Brain Res. 1996;35:58–68. 47. Knight MJ, McCann B, Kauppinen RA, Coulthard EJ. Magnetic resonance imaging to detect early molecular and cellular changes in Alzheimer’s disease. Front Aging Neurosci. 2016;8:139. 48. Weller RO, Boche D, Nicoll JA. Microvasculature changes and cerebral amyloid angiopathy in Alzheimer’s disease and their potential impact on therapy. Acta Neuropathol. 2009;118:87–102. 49. Querques G, Borrelli E, Sacconi R, De VL, Leocani L, Santangelo R, Magnani G, Comi G, Bandello F. Functional and morphological changes of the retinal vessels in Alzheimer’s disease and mild cognitive impairment. Sci Rep. 2019;9:63. 50. Carvalho C, Cardoso S. Diabetes-Alzheimer’s disease link: targeting mitochondrial dysfunction and redox imbalance. Antioxid Redox Signal. 2020. (epub ahead of print). Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 51. Jayaraj RL, Azimullah S, Beiram R. Diabetes as a risk factor for Alzheimer’s disease in the Middle East and its shared pathological mediators. Saudi J Biol Sci. 2020;27:736–750. 52. den Haan J, van de Kreeke JA, van Berckel BN, Frederik B, Teunissen CE, Scheltens P, Verbraak FD, Bouwman FH. Is retinal vasculature a biomarker in amyloid proven Alzheimer’s disease? Alzheimers Dement (Amst). 2019:383–391. 53. Armstrong A. Risk factors for Alzheimer’s disease. Folia Neuropathol. 2019;57:87–105. 54. O’Bryhim BE, Apte RS, Kung N, Coble D, Van Stavern GP. Association of preclinical Alzheimer disease with optical coherence tomographic angiography findings. JAMA Ophthalmol. 2018;136:1242–1248. 55. Bresnick GH, Condit R, Syrjala S, Palta M, Groo A, Korth K. Abnormalities of the foveal avascular zone in diabetic retinopathy. Arch Ophthalmol. 1984;102:1286–1293. 56. van de Kreeke JA, Nguyen HT, Konijnenberg E, Tomassen J, den BA, Ten KM, Yaqub M, van BB, Lammertsma AA, Boomsma DI, Tan SH, Verbraak F, Visser PJ. Optical coherence tomography angiography in preclinical Alzheimer’s disease. Br J Ophthalmol. 2020;104:157–161. 57. Kinney JW, Bemiller SM, Murtishaw AS, Leisgang AM, Salazar AM, Lamb BT. Inflammation as a central mechanism in Alzheimer’s disease. Alzheimers Dement (NY). 2018;4:575–590. 58. Jiang H, Gameiro GR, Liu Y, Lin Y, Jeffrey H, Deng Y, Gregori G, Delgado S, Wang J. Visual function and disability are associated with increased retinal volumetric vessel density in patients with multiple sclerosis. Am J Ophthalmol. 2020;213:34–45. 59. Di Marco LY, Farkas E, Martin C, Venneri A, Frangi AF. Is vasomotion in cerebral arteries impaired in Alzheimer’s disease? J Alzheimers Dis. 2015;46:35–53. 60. Zlokovic BV. Neurovascular pathways to neurodegeneration in Alzheimer’s disease and other disorders. Nat Rev Neurosci. 2011;12:723–738. 61. Girouard H, Iadecola C. Neurovascular coupling in the normal brain and in hypertension, stroke, and Alzheimer disease. J Appl Physiol. 2006;100:328–335. 62. Iadecola C. Neurovascular regulation in the normal brain and in Alzheimer’s disease. Nat Rev Neurosci. 2004;5:347–360. 63. Corvi F, La SC, Benatti L, Querques L, Lattanzio R, Bandello F, Querques G. Impact of intravitreal ranibizumab on vessel functionality in patients with retinal vein occlusion. Am J Ophthalmol. 2015;160:45–52. 64. Corvi F, Querques G, La SC, Lattanzio R, Bandello F. Dynamic and static retinal vessel analyses IN patients with macular edema secondary to retinal vein occlusion. Retina. 2015;35:2052–2059. 65. La SC, Corvi F, Bandello F, Querques G. Static characteristics and dynamic functionality of retinal vessels in longer eyes with or without pathologic myopia. Graefes Arch Clin Exp Ophthalmol. 2016;254:827–834. 66. Benatti L, Corvi F, Tomasso L, Darvizeh F, La SC, Querques L, Bandello F, Querques G. Dynamic functionality and static changes of retinal vessels in diabetic patients treated with intravitreal ranibizumab. Acta Diabetol. 2017;54:39–43. 67. Golzan SM, Goozee K, Georgevsky D, Avolio A, Chatterjee P, Shen K, Gupta V, Chung R, Savage G, Orr CF, Martins RN, Graham SL. Retinal vascular and structural changes are associated with amyloid burden in the elderly: ophthalmic biomarkers of preclinical Alzheimer’s disease. Alzheimers Res Ther. 2017;9:13. 68. Kotliar K, Hauser C, Ortner M, Muggenthaler C, Diehl-Schmid J, Angermann S, Hapfelmeier A, Schmaderer C, Grimmer T. Altered neurovascular coupling as measured by optical imaging: a biomarker for Alzheimer’s disease. Sci Rep. 2017;7:12906. 69. Newman EA. Functional hyperemia and mechanisms of neurovascular coupling in the retinal vasculature. J Cereb Blood Flow Metab. 2013;33:1685–1695. 70. Nagel E, Vilser W. Autoregulative behavior of retinal arteries and veins during changes of perfusion pressure: a clinical study. Graefes Arch Clin Exp Ophthalmol. 2004;242:13–17. 259 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited. State-of-the-Art Review 71. Kalaria RN. Small vessel disease and Alzheimer’s dementia: pathological considerations. Cerebrovasc Dis. 2002;13(suppl 2):48–52. 72. Yoshida A, Feke GT, Mori F, Nagaoka T, Fujio N, Ogasawara H, Konno S, Mcmeel JW. Reproducibility and clinical application of a newly developed stabilized retinal laser Doppler instrument. Am J Ophthalmol. 2003;135:356–361. 73. Feke GT, Hyman BT, Stern RA, Pasquale LR. Retinal blood flow in mild cognitive impairment and Alzheimer’s disease. Alzheimers Dement (Amst). 2015;1:144–151. 74. Berisha F, Feke GT, Trempe CL, McMeel JW, Schepens CL. Retinal abnormalities in early Alzheimer’s disease. Invest Ophthalmol Vis Sci. 2007;48:2285–2289. 75. Landa G, Jangi AA, Garcia PM, Rosen RB. Initial report of quantification of retinal blood flow velocity in normal human 260 subjects using the Retinal Functional Imager (RFI). Int Ophthalmol. 2012;32:211–215. 76. Lopes de Faria JM, Andreazzi DD, Larico Chavez RF, Arthur AM, Arthur R, Iano Y. Reliability and validity of digital assessment of perifoveal capillary network measurement using high-resolution imaging. Br J Ophthalmol. 2014;98:726–729. 77. Jiang H, Liu Y, Wei Y, Shi Y, Wright CB, Sun X, Rundek T, Baumel BS, Landman J, Wang J. Impaired retinal microcirculation in patients with Alzheimer’s disease. PLoS One. 2018;13:e0192154. 78. Gameiro GR, Jiang H, Liu Y, Deng Y, Sun X, Nascentes B, Baumel B, Rundek T, Wang J. Retinal tissue hypoperfusion in patients with clinical Alzheimer’s disease. Eye Vis. 2018;5:21. Jiang et al: J Neuro-Ophthalmol 2021; 41: 251-260 Copyright © North American Neuro-Ophthalmology Society. Unauthorized reproduction of this article is prohibited.