Background
Currently, Alzheimer’s disease (AD) diagnosis relies on biomarkers that are either expensive, invasive or time‐consuming. The retina is easily accessible and may be used as a ...patient‐friendly and cost‐effective diagnostic tool. Optina Diagnostics’ Mydriatic Hyperspectral Retinal Camera (MHRC) may improve diagnostic abilities of the retina by using rich datasets and artificial intelligence. Here we aim to explore diagnostic possibilities of the MHRC by identifying image features associated with the cerebral amyloid status.
Method
Six cognitively healthy participants with a negative amyloid‐PET scan and twenty‐five participants with a positive amyloid‐PET scan (clinical AD n = 4, preclinical AD n = 21, MMSE ≥17) were recruited from the EMIF‐AD PreclinAD Twin60++ study and Amsterdam Dementia Cohort (Table 1). Retinal imaging was performed using the MHRC that acquires 92 retinal images in an ∼1 second exposure, in steps of 5 nm increments across a spectral range of 450‐905 nm (visible and near‐infrared) on a 31° field‐of‐view (Figure 1). Spatial‐spectral features (n = 2304) were extracted from two or three hyperspectral cubes per participant using different combinations of anatomical masks, spectral regions and texture measures. Morphological features (n = 935) related to the blood vessels (diameter, tortuosity, density and fractal dimension) were also extracted from different retinal zones. Features were assessed with a Tukey’s test for statistical significance to classify the cerebral amyloid status determined by amyloid‐PET scans. Features were considered significant if their p‐value was below 0.05 simultaneously for both our present cohort and an independent cohort of 499 subjects.
Result
Explorative analysis identified thirty significant spatial‐spectral features (p‐value range 0.0033‐0.049) for the classification of the cerebral amyloid‐PET status. Examples of such features covering different spectral ranges and retinal anatomic regions are presented in Figure 2. In contrast, only three morphological features were identified (p‐value range 0.017‐0.049).
Conclusion
Phenotypic features extracted from hyperspectral retinal images hold promise to discriminate between amyloid‐PET positive and negative individuals, beyond morphological features available with conventional retinal imaging. More data are collected from several centers to build a classifier of features with the aim to discriminate amyloid‐PET positive from negative subjects. This would yield a patient‐friendly and non‐invasive retinal biomarker for AD.
Background
Tau tangles are one of the pathological hallmarks of Alzheimer’s disease (AD) and can be quantified using PET. It remains unclear which molecular processes are related to tau aggregation. ...Protein levels in CSF can be used to study such underlying processes. This study aims to identify biological processes related to tau‐PET using unbiased CSF proteomics in participants along the AD continuum.
Method
We included 89 participants with CSF proteomic and 18Fflortaucipir (tau)‐PET data available from the Amsterdam Dementia Cohort and the EMIF‐preclin AD study (N = 68 with abnormal CSF Aβ42 64.7% cognitively impaired, 67.6% tau‐PET visual read positive and N = 21 controls normal cognition and normal CSF AD biomarkers) (table 1). 18Fflortaucipir BPND was quantified in the temporal meta‐ROI (Braak I, Braak III, Braak IV). CSF proteomics was measured using untargeted LC‐MS/MS based on TMT labelling. We included proteins available in the whole sample (n = 1421 proteins). Protein concentrations were normalized to the control group. We determined the relationship between tau‐PET BPND (outcome) with protein levels (determinant) using linear regressions with sex and age as covariates, stratified for group. GO database was used for biological pathway enrichment analyses within the AD group for proteins thresholded at p<0.05 for positive and negative associations separately.
Result
Higher CSF tau levels were associated with higher tau‐PET BPND (β = 0.092, p = 0.002). In total, 458 proteins were associated with tau‐PET BPND in AD. A higher tau‐PET BPND was related to higher levels of 140 proteins and lower levels of 318 proteins. Proteins that showed higher levels with increasing tau‐PET BPND were mainly involved in immune system processes (figure 1), while the proteins with lower levels were predominantly related to synaptic processes and cell signaling (figure 2). No significant associations were found within controls.
Conclusion
Using CSF proteomics, we identified 458 proteins associated with tau‐PET in AD. Higher tau burden was associated with increased levels of proteins involved in immune activation suggesting a role of the immune system in tau accumulation. Furthermore, higher tau burden was associated with lower levels of proteins related to synaptic process hinting at a role for tau in synaptic degeneration.
One of the core behavioral features associated with obsessive compulsive symptomatology is the inability to inhibit thoughts and/or behaviors. Neuroimaging studies have indicated abnormalities in ...frontostriatal and dorsolateral prefrontal - anterior cingulate circuits during inhibitory control in patients with obsessive compulsive disorder compared with controls. In the present study, task performance and brain activation during Stroop color-word and Flanker interference were compared within monozygotic twin pairs discordant for obsessive compulsive symptoms and between groups of pairs scoring very low or very high on obsessive compulsive symptoms, in order to examine the differential impact of non-shared environmental versus genetic risk factors for obsessive compulsive symptomatology on inhibitory control related functional brain activation. Although performance was intact, brain activation during inhibition of distracting information differed between obsessive compulsive symptom high-scoring compared to low-scoring subjects. Regions affected in the discordant group (e.g., temporal and anterior cingulate gyrus) were partly different from those observed to be affected in the concordant groups (e.g., parietal gyrus and thalamus). A robust increase in dorsolateral prefrontal activity during response interference was observed in both the high-scoring twins of the discordant sample and the high-scoring twins of the concordant sample, marking this structure as a possible key region for disturbances in inhibitory control in obsessive compulsive disorder.
The prevalence of brain pathologies increases with age and cognitive and physical functions worsen over the lifetime. It is unclear whether these processes show a similar increase with age. We ...studied the association of markers for brain pathology cognitive and physical functions with age in 288 cognitively normal individuals aged 60-102 years selected from the cross-sectional EMIF-AD PreclinAD and 90+ Study at the Amsterdam UMC. An abnormal score was consistent with a score below the 5th percentile in the 60- to 70-year-old individuals. Prevalence of abnormal scores was estimated using Generalized Estimating Equations (GEE) models. The prevalence of abnormal handgrip strength, the Digit Symbol Substitution Test, and hippocampal volume showed the fastest increase with age and abnormal MMSE score, muscle mass, and amyloid aggregation the lowest. The increase in prevalence of abnormal markers was partly dependent on sex, level of education, and amyloid aggregation. We did not find a consistent pattern in which markers of brain pathology cognitive and physical processes became abnormal with age.
Abstract
Background
The past year, the retina has received increasing attention as a possible biomarker for (preclinical) Alzheimer’s disease (AD). Though cross‐sectional differences where ...inconsistently replicated in literature, longitudinal change over time of retinal layer thickness and/or retinal vascular parameters (RVPs) may differ between preclinical AD and controls.
Method
149 cognitively healthy monozygotic twins aged ≥60 were included from the EMIF‐AD PreclinAD study.
1
Participants were classified as preclinical AD (Aβ+) based on a positive 18Fflutemetamol PET image and as controls (Aβ‐) on a negative flutemetamol PET image. As a continuous measure of Aβ aggregation we used the 18Fflutemetamol PET binding potential (
BP
ND
). At baseline and follow‐up, after a mean of 22 months (range 15 – 32 months), the total and individual inner retinal layer thickness in the macular region (ETDRS ring), the peripapillary retinal nerve fiber layer thickness and 7 RVPs were measured on optical coherence tomography (OCT) and fundus images. OCT measurements could be analyzed in 145 participants and fundus images in 114 participants. Ocular measurements were compared between Aβ+ and Aβ‐ participants and related to the
BP
ND
.
Result
There were no differences in change over time in any of the measured retinal layer thicknesses between pre‐clinical AD patients (n=16) and controls (n=129) (see figure 1). We did, however, find a positive association between
BP
ND
values and an increase in the inner plexiform layer (IPL) thickness in the inner perifoveal ETDRS ring (CI: 0.575 – 2.841, p=0.003). Although arteriolar caliber, venular caliber and tortuosity of arteries all showed a significant decrease over time in the total group, no differences were found between Aβ+ (n=13) en Aβ‐ participants (n=111, table 1), nor did these RVP changes show a relation to
BP
ND
value at baseline.
Conclusion
The use of OCT measurements and RVPs as a longitudinal screening method for preclinical AD seems limited, but IPL changes may serve as a starting point for future research. Reference: (1) Konijnenberg E, Carter SF, Ten Kate M, den Braber A, Tomassen J, Amadi C, et al. The EMIF‐AD PreclinAD study: study design and baseline cohort overview. Alzheimers Res Ther. 2018;10(1):75.
Background
Older individuals with intact cognition and pathological amyloid depositions are at increased risk for memory decline. At this point the precise biological processes leading to cognitive ...decline are unclear. We tested the role of genetic influences on the relationship between amyloid pathology and subsequent memory decline over time using a monozygotic twin approach, and whether these relationships were dependent on the methodology used to determine amyloid aggregation.
Method
We selected 78 monozygotic twins with at baseline normal cognition from the EMIF‐AD PreclinAD study (Table 1), who had completed 4 years of follow‐up. We defined baseline amyloid status using either visual read of dynamic 18Fflutemetamol PET images or CSF amyloid‐β 1‐42/1‐40 (Aβ42/40) ratio (ADx Neurosciences/Euroimmun assays) <0.066 (based on Gaussian mixture modelling). Memory was tested at baseline, 2‐year and 4‐year, with six tests combined into one composite score. Associations between baseline amyloid status and subsequent decline on memory was tested using linear mixed models with main effect amyloid status, time and amyloid*time, adjusted for age, sex, education and genetic relatedness. We repeated analyses taking continuous CSF Aβ42/40 ratio and PET binding potential (BPND) values as predictors. To examine the role of genetic influences on observed associations we performed cross‐twin cross‐trait analysis.
Result
Nine individuals had abnormal Aβ at baseline and did not differ in age, sex and education from Aβ‐ subjects. They had a faster decline in memory than Aβ‐ subjects (ß=‐0.127(SE=0.041), pamyloid*time=0.002, Figure 1). Continuous measures of amyloid burden also predicted memory decline at follow‐up (CSF Aβ42/40 ratio ß=0.055(SE=0.016), PET BPND ß=‐0.040(SE=0.014), both p<0.005). Baseline CSF Aβ42/40 ratio in one twin could predict memory decline in its co‐twin (r=0.31,p=0.04), which suggests similar genetic factors underlie these processes, however this relation did not reach significance when using amyloid‐PET BPND (r=‐0.12,p=0.35).
Conclusion
In our study CSF Aβ42/40 ratio was more sensitive for detecting early pathophysiological changes compared to PET BPND. A larger sample is needed to confirm this finding. Our twin approach suggests that in preclinical AD amyloid burden and memory performance may share common genetic pathways. The next step will be to identify what these underlying shared biological mechanisms are.
Abstract
Background
Older individuals with intact cognition and pathological amyloid depositions are at increased risk for memory decline. At this point the precise biological processes leading to ...cognitive decline are unclear. We tested the role of genetic influences on the relationship between amyloid pathology and subsequent memory decline over time using a monozygotic twin approach, and whether these relationships were dependent on the methodology used to determine amyloid aggregation.
Method
We selected 78 monozygotic twins with at baseline normal cognition from the EMIF‐AD PreclinAD study (Table 1), who had completed 4 years of follow‐up. We defined baseline amyloid status using either visual read of dynamic
18
Fflutemetamol PET images or CSF amyloid‐β 1‐42/1‐40 (Aβ
42/40
) ratio (ADx Neurosciences/Euroimmun assays) <0.066 (based on Gaussian mixture modelling). Memory was tested at baseline, 2‐year and 4‐year, with six tests combined into one composite score. Associations between baseline amyloid status and subsequent decline on memory was tested using linear mixed models with main effect amyloid status, time and amyloid*time, adjusted for age, sex, education and genetic relatedness. We repeated analyses taking continuous CSF Aβ
42/40
ratio and PET binding potential (BP
ND
) values as predictors. To examine the role of genetic influences on observed associations we performed cross‐twin cross‐trait analysis.
Result
Nine individuals had abnormal Aβ at baseline and did not differ in age, sex and education from Aβ‐ subjects. They had a faster decline in memory than Aβ‐ subjects (ß=‐0.127(SE=0.041), p
amyloid*time
=0.002, Figure 1). Continuous measures of amyloid burden also predicted memory decline at follow‐up (CSF Aβ
42/40
ratio ß=0.055(SE=0.016), PET BP
ND
ß=‐0.040(SE=0.014), both p<0.005). Baseline CSF Aβ
42/40
ratio in one twin could predict memory decline in its co‐twin (r=0.31,p=0.04), which suggests similar genetic factors underlie these processes, however this relation did not reach significance when using amyloid‐PET BP
ND
(r=‐0.12,p=0.35).
Conclusion
In our study CSF Aβ
42/40
ratio was more sensitive for detecting early pathophysiological changes compared to PET BP
ND
. A larger sample is needed to confirm this finding. Our twin approach suggests that in preclinical AD amyloid burden and memory performance may share common genetic pathways. The next step will be to identify what these underlying shared biological mechanisms are.
Background
The past year, the retina has received increasing attention as a possible biomarker for (preclinical) Alzheimer’s disease (AD). Though cross‐sectional differences where inconsistently ...replicated in literature, longitudinal change over time of retinal layer thickness and/or retinal vascular parameters (RVPs) may differ between preclinical AD and controls.
Method
149 cognitively healthy monozygotic twins aged ≥60 were included from the EMIF‐AD PreclinAD study.1 Participants were classified as preclinical AD (Aβ+) based on a positive 18Fflutemetamol PET image and as controls (Aβ‐) on a negative flutemetamol PET image. As a continuous measure of Aβ aggregation we used the 18Fflutemetamol PET binding potential (BP
ND). At baseline and follow‐up, after a mean of 22 months (range 15 – 32 months), the total and individual inner retinal layer thickness in the macular region (ETDRS ring), the peripapillary retinal nerve fiber layer thickness and 7 RVPs were measured on optical coherence tomography (OCT) and fundus images. OCT measurements could be analyzed in 145 participants and fundus images in 114 participants. Ocular measurements were compared between Aβ+ and Aβ‐ participants and related to the BP
ND.
Result
There were no differences in change over time in any of the measured retinal layer thicknesses between pre‐clinical AD patients (n=16) and controls (n=129) (see figure 1). We did, however, find a positive association between BP
ND values and an increase in the inner plexiform layer (IPL) thickness in the inner perifoveal ETDRS ring (CI: 0.575 – 2.841, p=0.003). Although arteriolar caliber, venular caliber and tortuosity of arteries all showed a significant decrease over time in the total group, no differences were found between Aβ+ (n=13) en Aβ‐ participants (n=111, table 1), nor did these RVP changes show a relation to BP
ND value at baseline.
Conclusion
The use of OCT measurements and RVPs as a longitudinal screening method for preclinical AD seems limited, but IPL changes may serve as a starting point for future research. Reference: (1) Konijnenberg E, Carter SF, Ten Kate M, den Braber A, Tomassen J, Amadi C, et al. The EMIF‐AD PreclinAD study: study design and baseline cohort overview. Alzheimers Res Ther. 2018;10(1):75.
Background
Plasma levels of phosphorylated‐tau (P‐tau) are able to identify core Alzheimer’s Disease (AD) pathologies, but its value in cognitively unimpaired individuals needs further study. We ...aimed to investigate the value of plasma P‐tau at threonine‐181 (P‐tau181) for predicting amyloid pathology in cognitively unimpaired individuals followed over 10 years.
Method
From the EMIF‐AD PreclinAD study we selected 74 individuals, aged 60 years and older (Table 1) with normal cognition, that had plasma samples available that were collected at time of amyloid status assessment, as well as 10 years earlier (median (IQR) = ‐9.7 (2)). Amyloid status was defined using visual read of dynamic 18Fflutemetamol‐PET images or CSF amyloid‐β1‐42/1‐40<0.065 (Euroimmun). Simoa assays were applied to measure plasma P‐tau181 levels (Eli Lilly). ROC curve analysis was used to determine the value of plasma P‐tau181 in predicting amyloid status. Further, linear mixed models, adjusted for age and sex, were applied to assess longitudinal change in plasma P‐tau181, using time and the interaction between time and amyloid status as a predictor.
Result
Amyloid‐positive individuals had higher plasma P‐tau181 levels compared to amyloid‐negative individuals, both at time of amyloid status assessment and 10 years earlier. Plasma P‐tau181 obtained 10 years prior to amyloid status assessment was able to discriminate amyloid status with similar high Area Under Curve, sensitivity and specificity as plasma P‐tau181 obtained at time of amyloid status assessment (Figure 1). Longitudinally, we observed a general increase in plasma P‐tau181 levels over time (β=0.10, p<.001). Interestingly, amyloid‐positive individuals showed a steeper increase in plasma P‐tau181 levels over 10 years compared to amyloid‐negative individuals (time*amyloid‐β‐interaction: β=0.16, p=.005 (Figure 2)).
Conclusion
Our data suggest that plasma P‐tau181 can be used to predict AD pathology in cognitively unimpaired individuals. The high discriminative value observed, even using plasma P‐tau181 collected 10 years prior to amyloid status assessment, indicates the potential of this marker as an early amyloid pathology pre‐screening tool in the normal aging population. The observed amyloid dependent longitudinal increases in plasma P‐tau181 levels indicates this marker to be eligible for disease monitoring.
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.
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.
Deep white matter hyperintensities volume was positively associated with retinal tortuosity in veins (P = 0.004) and fractal dimension in arteries (P = 0.001) and veins (P = 0.032), periventricular white matter hyperintensities volume was positively associated with retinal venous width (P = 0.028). Intratwin pair correlations were moderate to high for all small vessel disease/retinal vascular parameter variables (r = 0.49-0.87, P < 0.001). Cross-twin cross-trait analyses showed that retinal venous tortuosity of twin 1 could predict deep white matter hyperintensities volume of the co-twin (r = 0.23, P = 0.030). Within twin-pair differences for retinal venous tortuosity were associated with within twin-pair differences in deep white matter hyperintensities volume (r = 0.39, P = 0.001).
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.
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