14 research outputs found
Retinal thickness as a potential biomarker in patients with amyloid-proven early- and late-onset Alzheimer's disease
Introduction: Retinal thickness measured with optical coherence tomography has been proposed as
a noninvasive biomarker for Alzheimer’s disease (AD). We therefore measured retinal thickness in
well-characterized AD and control participants, considering ophthalmological confounders.
Methods: We included 57 amyloid-proven AD cases and 85 cognitively normal, amyloid-negative
controls. All subjects underwent retinal thickness measurements with spectral domain optical
coherence tomography and an ophthalmological assessment to exclude ocular disease.
Results: Retinal thickness did not discriminate cases from controls, including stratified analyses for
early- versus late-onset AD. We found significant associations between macular thickness and global
cortical atrophy [b 20.358; P 5 .01] and parietal cortical atrophy on magnetic resonance imaging
[b 20.371; P , .01] in AD cases.
Discussion: In this study, representing the largest optical coherence tomography cohort with
amyloid-proven AD cases, we show that retinal thickness does not discriminate AD from controls,
despite evident changes on clinical, neuroimaging, and CSF measures, querying the use of retinal
thickness measurements as an AD biomarke
Retinal and Cerebral Microvasculopathy: Relationships and Their Genetic Contributions
PURPOSE: Retinal microvasculopathy may reflect small vessel disease in the brain. Here we test
the relationships between retinal vascular parameters and small vessel disease, the influence
of cardiovascular risk factors on these relationships, and their common genetic background in
a monozygotic twin cohort.
METHODS: We selected 134 cognitively healthy individuals (67 monozygotic twin pairs) aged
‡60 years from the Netherlands Twin Register for the EMIF-AD PreclinAD study. We measured
seven retinal vascular parameters averaged over both eyes using fundus images analyzed with
Singapore I Vessel Assessment. Small vessel disease was assessed on MRI by a volumetric
measurement of periventricular and deep white matter hyperintensities. We calculated
associations between RVPs and WMH, estimated intratwin pair correlations, and performed
twin-specific analyses on relationships of interest.
RESULTS: Deep white matter hyperintensities volume was positively associated with retinal
tortuosity in veins (P ¼ 0.004) and fractal dimension in arteries (P ¼ 0.001) and veins (P ¼
0.032), periventricular white matter hyperintensities volume was positively associated with
retinal venous width (P ¼ 0.028). Intratwin pair correlations were moderate to high for all
small vessel disease/retinal vascular parameter variables (r ¼ 0.49–0.87, P < 0.001). Crosstwin
cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep
white matter hyperintensities volume of the co-twin (r ¼ 0.23, P ¼ 0.030). Within twin-pair
differences for retinal venous tortuosity were associated with within twin-pair differences in
deep white matter hyperintensities volume (r ¼ 0.39, P ¼ 0.001).
CONCLUSIONS: Retinal arterial fractal dimension and venous tortuosity have associations with
deep white matter hyperintensities volume. Twin-specific analyses suggest that retinal venous
tortuosity and deep white matter hyperintensities volume have a common etiology driven by
both shared genetic factors and unique environmental factors, supporting the robustness of
this relationship
The EMIF-AD PreclinAD study: study design and baseline cohort overview
BACKGROUND: Amyloid pathology is the pathological hallmark in Alzheimer’s disease (AD) and can precede clinical
dementia by decades. So far it remains unclear how amyloid pathology leads to cognitive impairment and dementia.
To design AD prevention trials it is key to include cognitively normal subjects at high risk for amyloid pathology and to
find predictors of cognitive decline in these subjects. These goals can be accomplished by targeting twins, with
additional benefits to identify genetic and environmental pathways for amyloid pathology, other AD biomarkers,
and cognitive decline.
METHODS: From December 2014 to October 2017 we enrolled cognitively normal participants aged 60 years and
older from the ongoing Manchester and Newcastle Age and Cognitive Performance Research Cohort and the
Netherlands Twins Register. In Manchester we included single individuals, and in Amsterdam monozygotic twin
pairs. At baseline, participants completed neuropsychological tests and questionnaires, and underwent physical
examination, blood sampling, ultrasound of the carotid arteries, structural and resting state functional brain magnetic
resonance imaging, and dynamic amyloid positron emission tomography (PET) scanning with [18F]flutemetamol. In
addition, the twin cohort underwent lumbar puncture for cerebrospinal fluid collection, buccal cell collection,
magnetoencephalography, optical coherence tomography, and retinal imaging.
RESULTS: We included 285 participants, who were on average 74.8 ± 9.7 years old, 64% female. Fifty-eight participants
(22%) had an abnormal amyloid PET scan.
CONCLUSIONS: A rich baseline dataset of cognitively normal elderly individuals has been established to estimate risk
factors and biomarkers for amyloid pathology and future cognitive declin
Ocular biomarkers for cognitive impairment in nonagenarians; a prospective cross-sectional study
BACKGROUND: Ocular imaging receives much attention as a source of potential biomarkers for dementia. In the present study, we analyze these ocular biomarkers in cognitively impaired and healthy participants in a population aged over 90 years (= nonagenarian), and elucidate the effects of age on these biomarkers. METHODS: For this prospective cross-sectional study, we included individuals from the EMIF-AD 90+ study, consisting of a cognitively healthy (N = 67) and cognitively impaired group (N = 33), and the EMIF-AD PreclinAD study, consisting of cognitively healthy controls aged ≥60 (N = 198). Participants underwent Optical Coherence Tomography (OCT) and fundus photography of both eyes. OCT was used to asses total and individual inner retinal layer thickness in the macular region (Early Treatment Diabetic Retinopathy Study circles) as well as peripapillary retinal nerve fiber layer thickness, fundus images were analyzed with Singapore I Vessel Assessment to obtain 7 retinal vascular parameters. Values for both eyes were averaged. Differences in ocular biomarkers between the 2 nonagenarian groups were analyzed using linear regression, differences between the individual nonagenarian groups and controls were analyzed using generalized estimating equations. RESULTS: Ocular biomarkers did not differ between the healthy and cognitively impaired nonagenarian groups. 19 out of 22 ocular biomarkers assessed in this study differed between either nonagenarian group and the younger controls. CONCLUSION: The ocular biomarkers assessed in this study were not associated with cognitive impairment in nonagenarians, making their use as a screening tool for dementing disorders in this group limited. However, ocular biomarkers were significantly associated with chronological age, which were very similar to those ascribed to occur in Alzheimer's Disease