Search

INTRODUCTION: To support clinical trial designs focused on early interventions, our study determined reliable early amyloid‐β (Aβ) accumulation based on Centiloids (CL) in pre‐dementia populations. METHODS: A total of 1032 participants from the Amyloid Imaging to Prevent Alzheimer's Disease–Prognostic and Natural History Study (AMYPAD‐PNHS) and Insight46 who underwent [18F]flutemetamol, [18F]florbetaben or [18F]florbetapir amyloid‐PET were included. A normative strategy was used to define reliable accumulation by estimating the 95th percentile of longitudinal measurements in sub‐populations (NPNHS = 101/750, NInsight46 = 35/382) expected to remain stable over time. The baseline CL threshold that optimally predicts future accumulation was investigated using precision‐recall analyses. Accumulation rates were examined using linear mixed‐effect models. RESULTS: Reliable accumulation in the PNHS was estimated to occur at >3.0 CL/year. Baseline CL of 16 [12,19] best predicted future Aβ‐accumulators. Rates of amyloid accumulation were tracer‐independent, lower for APOE ε4 non‐carriers, and for subjects with higher levels of education. DISCUSSION: Our results support a 12–20 CL window for inclusion into early secondary prevention studies. Reliable accumulation definition warrants further investigations. [ABSTRACT FROM AUTHOR]

Background: The Catalan Early Onset Neurodegenerative Dementia Network is a multicenter project launched in 2020 with the aim of understanding the epidemiology and clinical care of people with early‐onset neurodegenerative dementia and their caregivers. Methods: Neurologists and geriatricians visiting patients with cognitive impairment in Catalonia were invited to prospectively collect demographical and clinical data from patients with age at onset (AAO) less than 65 years visited during the year 2021. Result: We registered information of 1221 subjects from 14 centers. Mean age was 56,2 years (SD 8.7), 64% were woman. Mean age at symptom onset was 53,9 years (SD 9.1). The most frequent cognitive symptoms at onset were memory impairment (72,9%) and dysexecutive difficulties (21,8%). Mean Mini Mental State Examination (MMSE) score was 26,7 (range 7‐30). Initial clinical diagnose was a non‐neurodegenerative disorder in 81,4% of cases and a neurodegenerative disorder in 17,81%. Genetic counseling accounted for 0,8% of visits. The suspected non‐neurodegenerative and neurodegenerative patients were studied with a neuropsychological test (85,5% vs 86,7%, respectively), magnetic resonance imaging (MRI) (39,9% vs 55,6%), computerized tomography (CT) scan (33,2% vs 34,4%), fluorodeoxyglucose positron emission tomography (FDG‐PET) (6,8% vs 39,0%), amyloid‐PET (3,9% vs 34,4%) and lumbar puncture (7,1%, vs 44,8%). 16,6% of participants had a final diagnose of a neurodegenerative cognitive disorder (10,9% Alzheimer's disease, 2,3% frontotemporal lobular degeneration, 2,1% MCI of suspected neurodegenerative etiology, 0,58% other neurodegenerative dementias); 83,4% were diagnosed with a non‐degenerative disorder (28,4% subjective cognitive decline (SCD), 25,0% mild cognitive impairment of non‐neurodegenerative etiology, 19,8% cognitive impairment after Covid‐19, 10,2% other dementias). Diagnostic delay was higher for neurodegenerative disorders (17 months: median 12 months (interquartile range (IQR) 19) between AAO and first visit +5 months (IQR 8) between first visit and diagnose) than non‐degenerative disorders (12 months: 9 months (IQR 19,6) + 3 months (IQR 7) respectively). Conclusion: Of 1221 patients under 65 years old visited in cognitive disorders units, only 16,6% had a final diagnose of neurodegenerative cognitive disorder. More than a quarter of subjects were diagnosed as SCD and a fifth as cognitive impairment after Covid‐19. In 2021, diagnosis delay was higher in neurodegenerative disorders (median 17 months). [ABSTRACT FROM AUTHOR]

Background: The prevention of symptomatic Alzheimer's disease (AD) is a major endeavor currently in the field, with the prevalence of subjects on the AD continuum (i.e. presence of amyloid‐β [Aβ] pathology) being much higher than previously estimated. However, the extent to which Aβ pathology and its interaction with common risk factors in the aging population relates to disease progression is still limited. The AMYPAD Prognostic and Natural History Study (PNHS) aims to evaluate the value of amyloid‐PET for predicting AD‐related disease progression. Method: A total of 1423 non‐demented subjects were included from the AMYPAD‐PNHS pan‐European cohort (17 sites across 10 Parent Cohorts), for who a baseline [18F]flutemetamol or [18F]florbetaben amyloid‐PET scans that passed quality control was available (Table‐1). Amyloid burden was assessed using the Centiloid (CL) method (whole cerebellum reference region). Independent linear mixed‐effect models were used to assess the predictive value of continuous CL, and its interaction with time, across cognitive domains: mini‐mental state examination (MMSE), memory, attention, language fluency, visuospatial, and executive functions. Years from baseline, age, sex, years of education, cognitive dementia rating (CDR), and APOE‐ε4 were used as independent variables. Clinical follow‐up was 3.4 ± 1.8 years (up to ±10 years) on average. Result: At baseline, 90% of the subjects were classified as cognitively unimpaired (CDR = 0). Based on CL, most subjects were categorized as amyloid‐negative (59%, 0±9CL), followed by grey‐zone (24%, 25±11CL), and amyloid‐positive (17%, 82±21CL). Baseline CL and its interaction with time were predictive of MMSE scores, memory, attention, and language fluency. Baseline CL, but not its interaction with time, was predictive of executive function. Finally, the interaction of baseline CL with time, but not its main effect, was predictive of visuospatial functioning (Figure‐1). Age and sex were significant contributors to nearly all models. Conclusion: Higher baseline CL was associated with lower cognitive performance in all explored domains, suggesting that emerging cerebral amyloid accumulation in non‐demented individuals is predictive of overall cognitive function. Also, higher CL values were predictive of decline across cognitive domains, except for executive function. Further analysis is ongoing, including different confounding factors, longitudinal PET outcomes, and other biomarkers of the disease. [ABSTRACT FROM AUTHOR]

Background: Previous results on amyloid‐PET imaging for predicting functional decline are conflicting. Given that the Centiloid approach (CL) may serve for inclusion in anti‐amyloid trials, we investigated the extent to which CL may predict functional decline in the AMYPAD‐Prognostic and Natural History Study (PNHS), including 1094 participants. Method: We analyzed, cross‐sectionally and longitudinally, the associations between CL and global and sum‐of‐boxes (SOB) Clinical Dementia Rating (CDR), and Instrumental Activity of Daily Living (IADL) scores. Mean follow‐up duration ranged from 2.7‐3.0 years (±1.1‐1.6) depending on the functional score. Longitudinal CDR‐SOB and IADL changes were modeled using linear mixed‐effects models with random intercepts and slopes, covarying age and sex, stratified by CDR global score. Analyses included comparisons between three CL groups (Aβ‐: CL<12; grey‐zone: CL = 12‐50; Aβ+: CL>50) and correlation between the baseline CL and the time for progression on the CDR global score. Result: The baseline CL was significantly higher in CDR = 0 (Mdn = 6.6) than in CDR = 0.5 participants (Mdn = 17.2; p<.001). Baseline CDR‐SOB was significantly higher in Aβ+ (M = 0.48) than in Aβ‐ (M = 0.12) and grey‐zone participants (M = 0.13, p‐values <.001). Baseline IADL was (marginally) significantly lower in Aβ+ (Mdn = 81.3) than in Aβ‐ (Mdn = 82.8, p =.02) and grey‐zone participants (Mdn = 83.5, p =.08, Table 1). Baseline CL significantly predicted subsequent changes in CDR‐SOB and IADL, both in CDR = 0 and CDR = 0.5 participants, but only in the CL>50 groups (βCL12‐50 = 0.03, p =.32,βCL>50 = 0.14, p<.001 for CDR‐SOB in CDR = 0 participants;βCL12‐50 = 0.19, p =.31,βCL>50 = 1.04, p =.01 for CDR‐SOB in CDR = 0.5 participants;βCL12‐50 = ‐0.002, p =.99, βCL>50 = ‐1.00, p =.08 for IADL in CDR = 0 participants; Fig.1). The participants who progressed from global CDR = 0 to CDR = 0.5 (N = 90) had a higher baseline CL (Mdn = 15.16) than stable participants (Mdn = 5.95, p =.002). However, the baseline CL was not associated with a shorter time of clinical progression (rs= ‐.02, p =.8; Fig.2). Conclusion: Cross‐sectionally, amyloid burden expressed in CL units was associated with functional outcomes. A baseline CL>50 predicted subsequent functional decline in CDR‐SOB and IADL scores in clinically normal and mildly clinically impaired participants. At lower CL values, no functional decline was observed during a three‐year follow‐up. Clinically normal individuals with increasing global CDR scores had higher baseline CL values, but these values were not associated with faster clinical progression. [ABSTRACT FROM AUTHOR]

Background: The relationship between cerebrospinal fluid (CSF) biomarkers for Alzheimer's disease (AD), APOE‐ε4 and longitudinal cortical amyloid deposition in preclinical AD is relevant for AD trial design but remains unclear. Thus, we aimed to investigate longitudinal cortical amyloid accumulation on PET as predicted by baseline CSF AD biomarker profiles and APOE‐ε4 carriership in cognitively unimpaired individuals. Method: We selected 330 cognitively unimpaired individuals from 6 cohorts of the AMYPAD study. All had available baseline data on CSF aß1‐42 (A), p‐tau181 (T), APOE‐ε4 carriership (yes/no), and baseline and follow‐up amyloid PET data. To evaluate different AD stages, individuals were classified as A‐T‐, A‐T+, A+T‐, or A+T+ based on CSF biomarker abnormality using center‐specific cut‐offs. We used a continuous outcome measure of global cortical amyloid deposition on PET expressed in centiloids. Analyses were performed in the total sample and stratified for APOE‐ε4, using generalized linear mixed models with random intercepts and slopes, adjusted for age and sex. Result: 58% were female, 49% APOE‐ε4 carriers, and mean age was 64+‐6.1 years, with an average follow‐up of 3 years. 170 individuals were A‐T‐, 70 A‐T+, 59 A+T‐, and 31 A+T+. Baseline cortical amyloid deposition was different between all groups, with A+T+ having the highest deposition, followed by A+T‐, A‐T+ and A‐T‐ (Figure 1, Table 1). Longitudinally, all groups showed increased amyloid deposition, except A‐T‐. Moreover, A+ groups showed greater increases in longitudinal amyloid deposition than A‐ groups. In APOE‐ε4 carriers, all AT groups showed increased longitudinal amyloid deposition, while in non‐carriers, A‐T+ and A‐T‐ did not (Figure 2, Table 1). Only in APOE‐ε4 carriers, A+T+ showed greater increases in longitudinal amyloid deposition than A+T‐, with A+T‐ showing a similar longitudinal deposition as A‐T+. Conclusion: APOE‐ε4 impacts the association between CSF AD biomarkers and longitudinal amyloid PET deposition in cognitively unimpaired persons. Amyloid‐negative APOE‐ε4 carriers could be at an early AD stage, as they showed increased cortical amyloid longitudinally, independent of baseline p‐tau status. In amyloid‐positive persons, p‐tau abnormality related to higher baseline cortical amyloid, but only in APOE‐ε4 carriers to steeper increases in cortical amyloid longitudinally. This has important implications for AD trial design. [ABSTRACT FROM AUTHOR]

Background: Leucine‐rich repeat kinase 2 (LRRK2) common gene variants (tagged by rs76904798) are associated with Parkinson's disease (PD) risk. In a previous study, we found that rs76904798 was associated with CSF GRN levels, but a comprehensive unbiased analysis of associated proteins remains incomplete due to prior focus on cis‐protein quantitative trait loci (pQTL). Using the largest aptamer‐based CSF proteomics study to date (7,006 aptamers (6,138 unique proteins) in 3,107 individuals), we performed a trans‐pQTL study to identify proteins associated with the LRRK2 variants and used additional mediation and pathway analyses to better understand downstream effects (Figure 1). Method: SNP selection using Conditional and Joint Association Analysis (GTCA‐COJO) and PLINK LD r2 scores identified 11 other independently associated SNPs. Fine mapping was performed between each significant aptamer and PD GWAS via proteome‐wide association studies (PWAS) and Mendelian randomization (MR). These aptamers were further analyzed based on PD risk association, brain cell‐type specificity, and gene pathway annotations. Result: Overall, 26 proteins passed FDR correction and eleven were implicated in PD prior like GRN and GPNMB. PWAS analyses using TWAS/FUSION also indicate 12 proteins were significant and positively associated with PD risk, such as novel proteins C1QTNF1 and SDCBP2, and half were validated by the PPMI data. MR analyses indicate that GRN, GPNMB, HLA‐DQA2, CD68, and LCT are also causal for PD risk (Table 1). Cell‐type enrichment analyses indicate microglia‐specific protein enrichment (Fold change: 7.35, P = 4.91×10−5). Enrichment analyses indicate enrichment for leukocyte activation (GO:0045321, P = 0.002) and microglial cell activation (GO:0001774, P = 0.003) pathways. Conclusion: Trans‐pQTL can identify novel protein interactions in an unbiased manner. This study linked LRRK2 variants with both PD implicated (GRN, GPNMB) and novel (ITGB2, C1QTNF1) proteins that have support in our PWAS, MR, and PPMI differential protein level analyses. Microglia and lysosome enrichment support the previous observations regarding the importance of microglia and immune system function in the underlying pathobiology of PD (Figure 2). Our results suggest that the CSF concentrations of these proteins (such as GRN, GPNMB, C1QTNF1, and ITGB2) have potential as biomarkers for target engagement and disease progression modification in clinical trials that target LRRK2. [ABSTRACT FROM AUTHOR]

Background: While the association between tau deposition on PET and brain atrophy on MRI is well documented in the literature, the relation between amyloid deposition and neurodegeneration in the earliest stages of Alzheimer's disease (AD) is less studied. We investigated this relationship in a large cohort of non‐demented individuals. Method: We included 1355 participants from the AMYPAD Prognostic & Natural History study (PNHS) with available MRI and amyloid‐PET. Among those, 753 had longitudinal MRI, with a mean follow‐up time of 3.47 years (SD = 1.55). The FreeSurfer 7.0.1 longitudinal pipeline was used to measure gray matter (GM) thickness and volumes in 40 regions (Reuter et al., 2012; Desikan et al., 2006). From PET scans, cortical amyloid burden was assessed globally using the Centiloid (CL) method. MRI‐derived regional volumes and thickness were harmonized across sites with neuroCombat (Fortin et al., 2018); all variables were Z‐scored. Linear mixed‐effect models were used to investigate the effect of amyloid burden at baseline and its interaction with time on regional volume and thickness measurements. Models were corrected for age, sex, and CDR. P‐values were FDR‐adjusted. Result: Cohort characteristics are shown in Table 1. Decreasing cortical thickness and volumes were observed over time in most regions. At baseline, higher amyloid burden was related to smaller volumes of the hippocampus, amygdala, putamen, and lateral ventricles; and thinner entorhinal cortex, precuneus and posterior cingulate cortex. At follow‐up, subjects with higher baseline amyloid burden showed greater loss of volume and thickness in mainly temporal and parietal regions, as well as amygdala and hippocampal volume (Figure 1). Conclusion: In the largely asymptomatic AMYPAD PNHS cohort, we show that amyloid burden at baseline is predictive of future neurodegeneration, especially affecting temporal volume and parietal thickness. Cortical thickness was slightly more sensitive towards amyloid burden at baseline, while loss of cortical volume was greater than loss of thickness. [ABSTRACT FROM AUTHOR]

Background: The present study aimed to explore the association between Apolipoprotein E (APOE) genotype, the main genetic risk factor for sporadic Alzheimer's Disease (AD), age, and cerebral β‐amyloid (Aβ) aggregation, the earliest pathological event in AD in a large, multicenter, European cohort, the AMYPAD study. Method: We included 876 participants from the AMYPAD cohort who had known APOE genotype and went through at least one Aβ PET imaging. We first looked at the association between Aβ deposition and age according to sex, APOE genotype, and cognitive status. We then used linear regression models to look at the association between Aβ aggregation and APOE genotype in different cerebral regions with age, sex, history of dementia, MMSE score, CDR score, depression, hypercholesterolemia, diabetes and center as covariates. Result: Our participants had a mean age of 67 years old with a mean MMSE score of 28.9/30 and counted 60% of women. We found a positive association between Aβ deposition and age with a gradually stronger association in heterozygous ԑ4 carriers (β (SD) = 1.94 (0.27)) and homozygous ԑ4 carriers (3.18 (0.52)) compared to non‐carriers (0.99 (0.12), p<0.001; Figure). We found similar results when restricting the analyses to cognitively unimpaired participants (heterozygous ԑ4: 1.65 (0.27), p<0.001; homozygous ԑ4: 3.01 (0.52), p<0.001), however Aβ aggregation was less associated to age in participants with mild cognitive impairment (heterozygous ԑ4: 1.33 (1.4), p = 0.33; homozygous ԑ4: 2.34 (1.9), p = 0.29). Moreover, we found an effect of sex on the association between Aβ aggregation and age in ԑ4 non‐carriers characterized by a stronger association in men (1.61 (0.22)) compared to women (0.63 (0.13)). Finally, we observed that the effect of APOE genotype on Aβ aggregation remained similar in the different cerebral regions, with less discernable differences between genotypes in the medial temporal and occipital regions. Conclusion: The number of APOE4 alleles has an impact on the association between age and Aβ aggregation, such that high amyloid was observed at younger ages in homozygous APOE4 carriers than in heterozygous APOE4 carriers and in non‐carriers. The effect of APOE4 on Aβ deposition was global rather than regional in our analysis. [ABSTRACT FROM AUTHOR]

Background: Alzheimer's disease (AD) is a complex disease conditioned by environmental and genetic factors. Over the last few years, Genome‐Wide Association Studies (GWAS) have gained increasing interest representing the basis of a personalized medicine that aims to facilitate interventions at the preclinical stages. In most studies, the integration of the high‐dimensional GWAS data is accomplished via polygenic risk scores (PRSs) representing a measure of the genetic risk associated with a given phenotype. For the first time, this study aimed to explore the predictive value of a PRS developed to predict conversion to AD in patients with mild cognitive impairment (MCI) (AD‐PRS) (Bellenguez et al., 2022) on cognitive decline once the AD dementia stage has been established Method: The modulatory effect of genetics on cognitive decline was studied using a sample of 3921 subjects with AD dementia (clinical dementia rating (CDR) ≥1) evaluated at Ace Alzheimer Center Barcelona. Cognitive decline, operationalized as changes in Mini Mental State Examination (MMSE) scores over time, was modeled using multivariate regression models considering clinical and sociodemographic data, and the AD‐PRS. Interaction effects between the AD‐PRS and the other covariates were explored, and subsequently, mediation analyses were applied. Afterward, Machine Learning techniques were used to select the single nucleotide polymorphisms (SNPs) forming the AD‐PRS with the highest predictive value on cognitive decline. Result: Multivariate regression models showed a significant interaction of the AD‐PRS with years of education (coef =.0006; p‐value =.005). Increased scores of AD‐PRS combined with higher formal education were found to be associated with greater cognitive decline. Furthermore, Machine Learning models identified 18 SNPs related to cognitive decline in AD, demonstrating that genetic information improves the predictive performance of the models. Conclusion: This is the first study that demonstrates the predictive capacity of the AD‐PRS on cognitive decline in AD dementia. Years of education were shown to modulate, but not mediate, the effect of the AD‐PRS on cognitive progression. Additionally, a subset of SNPs comprising the AD‐PRS with the highest predictive value of cognitive decline in AD was identified. Altogether, these results provide new insights into the genetics of the disease. [ABSTRACT FROM AUTHOR]

Background: The AMYPAD Prognostic and Natural History Study aims to evaluate the value of (semi‐) quantitative amyloid PET imaging for predicting progression within an Alzheimer's disease risk probability spectrum. The project is actively recruiting non‐demented participants from 17 sites across Europe, with a particular interest in those with emerging amyloid pathology. Methods: As of 17th January 2022, a total of 1,460 participants had been included. Of those, clinical data of 1,015 were processed, with 688 (68%) having at least a quantified amyloid PET at baseline, with [18F]flutemetamol or [18F]florbetaben. The primary metric used to assess amyloid burden was the Centiloid (CL), measured from the ratio of the GAAIN cortical target and whole cerebellum. Scans were categorized as negative (CL≤12), gray‐zone (1250). The distribution of these groups was assessed using a Gaussian mixture model. Independent linear mixed‐effect models were used to explore the predictive value of CL, and its interaction with time, for several cognitive outcomes: mini‐mental state examination (MMSE), memory (immediate recall, IR), attention (digit‐span forward, DSF), language, visuospatial, and executive functions. In addition, years from baseline, parent cohort, age, sex, education, APOE‐ε4, and the Clinical Dementia Rating (CDR) score were used as independent variables. Results: Demographics are shown in Table 1. At baseline, 88% of the subjects were classified as cognitively unimpaired (CDR=0). A majority of 384 (56%) was categorized as negative (1±7CL), 210 (30%) as grey‐zone (14±11CL), and 94 (14%) as positive (58±31CL) [Figure 1]. Baseline CL (‐0.007 [‐0.010; ‐0.004]) and its interaction with time (‐0.002 [‐0.003; ‐0.001]) were predictive of IR. Baseline CL, but not its interaction with time, predicted MMSE (‐0.007, 95%CI [‐0.010; ‐0.003]) and DSF (‐0.003 [‐0.005; ‐0.001]) [Figure 2]. No significant relationships were observed for executive, language, or visuospatial function. Conclusions: Higher baseline CL were associated with lower global cognitive function and attention scores. Whereas, higher CL were associated with a steeper memory decline over time. Current results suggest that cerebral amyloid accumulation is predictive of future overall cognitive function, attention, and memory decline. Further analysis is assured, including more participants, longitudinal PET outcomes, and other biomarkers of the disease. [ABSTRACT FROM AUTHOR]

Background: Research on medical risk profiles and early detection progresses rapidly. With the early knowledge of individual health risks comes, so the hope, the possibility of tailored prevention. Potential users and healthcare providers are facing new challenges in terms of decision‐making for risk prediction, education and counselling, as well as dealing with the risk information obtained. If, as in the case of Alzheimer's disease, there are hardly any therapy and no healing options so far, risk prediction has an existential relevance and social impact, the extent of which has been little investigated yet. Therefore, supporting a self‐determined decision for or against dementia risk prediction, taking into account individual attitudes, needs and expectations, is of major importance. As part of the PreTAD‐project (The Predictive Turn in Alzheimer's Disease: Ethical, Clinical, Linguistic and Legal Aspects), we aim to explore the attitudes, needs and expectations regarding early dementia prediction and risk disclosure in the general population, first‐degree relatives of persons with Alzheimer's dementia or APOE4 allele carriers, and individuals with subjective cognitive decline (SCD). Method: In the work package ethics, we (1) conduct an online‐survey within the general population and (2) carry out 40 narrative interviews with a) individuals from the general population, b) individuals with AD family history, and individuals diagnosed with SCD (either c) ≤ 4 weeks or d) > 4 weeks ago) to get an in‐depth view of individual attitudes and needs regarding early dementia prediction, the reasons for its approval or rejection, and to examine whether personal characteristics play a role in the decision‐making process. We analyze the interviews using type‐building qualitative content analysis (Kuckartz & Rädiker 2022). Result: Preliminary results of the first interviews (n = 5), accompanying the quantitative study, showed that participants tended to confuse the terms prediction and diagnosis in the context of Alzheimer's. The driving reasons for or against prediction were 1) the anticipated impact on self‐determination and 2) self‐awareness, and 3) the anticipated psychological burden of risk knowledge. Conclusion: Healthcare providers should carefully consider individual attitudes and expectations regarding dementia risk prediction as risk disclosure may have serious implications on individuals' self‐determination, self‐awareness and mental health. [ABSTRACT FROM AUTHOR]

Background: In the field of Alzheimer's disease (AD), possibilities of prediction are advancing due to the ever‐widening spectrum of technical and biomedical development. Such procedures become available to healthy persons, revealing risk probabilities to develop Alzheimer's dementia in the course of one's lifespan. The disclosure of and confrontation with such information can influence the individual's self‐understanding, identity and life planning which raises various (bio‐)ethical issues on an individual and societal level. In this qualitative part of the PreTAD project, we aim to reveal information on the participants' identity, through the analysis of their narrations (= narrative identity), by focusing on language patterns participants use to express their positioning concerning risk prediction. Method: In this qualitative‐explorative approach, we conduct N = 40 interviews with the following groups of participants: (a) general population, (b) first‐degree relatives of persons with Alzheimer's dementia, (c) patients diagnosed with subjective cognitive decline (SCD). The interview design is guided by three themes relating to risk prediction of Alzheimer's dementia: (1) individual experiences, (2) points of access and needs, (3) contextualization and associations. With this approach we seek to enable a 'conversational' interview in which linguistic patterns, (self‐)positioning and stance towards risk, health and disease reveal attitudes, individual values and therefore narrative identity. The basis of the multifaceted qualitative and linguistic analysis are Interpretative Phenomenological Analysis (IPA) and Conversation Analysis (CA). Result: Preliminary results show that the deliberate approach of thematically segmented but rather unstructured interaction and the focus on patients' narrations proved fruitful in identifying findings concerning the participants' identity and sense of self in the context of risk‐prediction of dementia. By focusing analytically on linguistic stance (attitude) and direct/indirect (self‐)positioning of the participants, we can gain in‐depth insights into individual values and attitudes towards risk, risk prediction of Alzheimer's dementia and health. Conclusion: According to initial findings, the focus on narrative identity leads to important insights into self‐understanding of persons confronted with a potential risk and can help to refine ethical questions concerning risk prediction. To ensure good clinical practice regarding predictive interventions those should be acknowledged in counselling and risk disclosure communication. [ABSTRACT FROM AUTHOR]

Background: Due to new, more reliable and accessible technologies, a paradigm shift from curative to predictive and preventive medicine is emerging. Despite progress in the field of Alzheimer's dementia risk estimation, little is known about the individual perspectives in this regard. The tri‐national PreTAD (The Predictive Turn in Alzheimer's Disease: Ethical, Clinical, Linguistic and Legal Aspects) project aims to study the perspectives of individuals from the general population, first‐degree relatives of persons with Alzheimer's dementia, APOE4 allele carriers, and of individuals with subjective cognitive decline (SCD) on individual risk factor assessment and dementia risk estimation. In a quantitative and qualitative longitudinal study, needs, preferences and decision‐making parameters will be conducted. Method: For the quantitative study, hypothetical scenarios on predictive AD diagnosis for an individual person were developed. Based on these scenarios, instruments to measure psychological distress, subjective well‐being, quality of life, willingness to make lifestyle changes, and to take preventive measures were applied. The qualitative approach uses individual interviews to obtain complementary in‐depth information on personal preferences. Results of the pilot study with 10 cognitively unimpaired healthy participants and 10 participants with SCD are reported. Result: The participants of the pilot study wanted to know their estimated personal risk of developing Alzheimer's dementia. Higher test accuracy was more important than low invasiveness. In the pilot data, age and the possibility of influencing the risk by lifestyle changes, but also the attitude of relatives, influenced the decision for risk estimation. Willingness to assess dementia risk seems to be independent of the absence of causal treatment options. Conclusion: The PreTAD project will provide a deeper comprehension of needs and preferences regarding the individual dementia risk estimation. From an individual point of view, there seems to be an interest in risk assessment and prediction, which is influenced by a variety of factors. The findings of the PreTAD project will help to incorporate the perspectives of potential users risk estimation in the development of guidance for counseling and clinical management in predictive and preventive approaches in the field of dementia. [ABSTRACT FROM AUTHOR]

Background: Optical Coherence Tomography angiography (OCT‐A) is a novel tool that allows the detection of retinal vascular changes. The comparison of OCT‐A measures with brain vascular burden is essential to validate the former as a surrogate of cerebrovascular damage and biomarker of cognitive decline. We aimed to investigate the association of macular vessel density (VD) in the superficial plexus assessed by OCT‐A with measures of cerebrovascular pathology quantified by brain magnetic resonance imaging (MRI) in a cohort of non‐demented individuals. Method: Clinical, demographical, APOE ε4 status, amyloid status, OCT‐A and brain MRI data from non‐demented participants of the FACEHBI and BIOFACE studies were included. We analyzed the association of macular VD in four quadrants (superior, nasal, inferior and temporal) with brain vascular burden using the Fazekas scale scores (dichotomized in two categories, 0‐1 vs 2‐3), assessed in a logistic regression analysis, and the volume of white matter hyperintensities (WMH) quantified by Freesurfer assessed in a multiple regression analysis. We additionally explored the associations of macular VD with hippocampal volume, ventricles volume and Alzheimer Disease cortical signature (ADCS) thickness assessed in a multiple regression analysis. All analyses were adjusted for age and dyslipidemia. Result: The study cohort comprised 188 participants: 89 with subjective cognitive decline (SCD) and 99 with mild cognitive impairment (MCI). Logistic regression analysis showed no significant differences of regional macular VD between the two Fazekas groups (all, p>0.05). Multiple regression analysis showed no significant association of regional macular VD with the volume of WMH (all, p>0.05). Macular VD in the nasal and inferior quadrants were positively associated with hippocampal volume (p = 0.009 and p = 0.021, respectively), but no association was detected with ventricles volume or ADCS thickness (both p>0.05). Conclusion: Our study showed that retinal vascular measures (regional macular VD in the superficial vascular plexus) assessed by OCT‐A were not associated with brain vascular damage quantified by the Fazekas scale and the WMH burden n in a cohort of non‐demented research participants with SCD and MCI. [ABSTRACT FROM AUTHOR]

Background: The Alzheimer Association has recently remarked the diagnostic and prognostic revolution that plasma biomarkers will mean for AD diagnosis, and highlighting the need of further research to translate them as a realistic option in the clinical practice. However, many studies to date have assessed them in research cohorts. Here we evaluated the diagnostic performance and clinical applicability of plasma pTau181 as a predictive marker of dementia risk in a real‐world memory clinic cohort. Method: The ACE cohort encompass 1649 patients with subjective cognitive decline (SCD), mild cognitive impairment (MCI), AD dementia and other dementias, with a complete battery of neurological tests, biochemistry data, and paired CSF and plasma samples of the Ace Alzheimer Center Barcelona memory clinic. CSF AB42, AB40, pTau181 and tTau, and plasma pTau181 were measured using the Lumipulse G1200 automatic platform (Fujirebio Inc.). Complete cohort were divided in the Testing cohort (n = 1000) and Validation cohort (n = 649). Result: Plasma pTau181 significantly correlated (P<0.0001) with CSF pTau181 in MCI, AD dementia and other dementias, but not in SCD. Sex appeared not significant in plasma pTau181 levels, whereas age significantly influenced in the biomarker's performance. ROC curve of A+T+ patients vs rest showed an AUC = 0.8250 and P<0.0001. Specifically for MCI patients, ROC curve of MCI A+T+ vs MCI A‐T‐ showed and AUC = 0.8874 and P<0.0001. A cut off value of 1.300 pg/ml of plasma pTau181 exhibited a 93.6% sensibility, 72.4% specificity, 77.8% precision and only 8.3% of false negatives in MCI patients. Hazard ratio of survival of conversion analysis showed that MCI patients above this cut off value exhibited a 4.570 higher risk to convert to dementia than MCI under the cut off value. Validation cohort confirmed these findings. Conclusion: Plasma pTau181 could be useful as a pre‐screening biomarker of MCI patients with high risk to progress to dementia. However, positive patients will also require a CSF/PET confirmatory test. Plasma pTau181 by itself does not present a suitable performance in SCD patients. Another biomarker or a combination of biomarkers would be needed to this population. Further studies are need to obtain more clinical data and improve the biomarker performance to finally substitute CSF/PET biomarkers. [ABSTRACT FROM AUTHOR]

Background: Quantitative trait loci (QTL) are successful at identifying the functional gene for many loci identified through GWAS. While expression QTL (eQTL) studies robustly examine tissue‐specificity, most protein QTL (pQTL) studies have been limited to plasma. We have previously demonstrated that pQTL associations are highly tissue‐specific. Given the relevance of cerebrospinal fluid (CSF) to Alzheimer's disease (AD) and other forms of neurodegeneration, we developed a CSF‐specific pQTL atlas and integrated it with AD GWAS to identify novel causal proteins for AD. Method: We generated CSF proteomics (Somalogic, 7,584 analytes) data for 3,107 individuals. pQTL mapping was performed using a three‐stage approach: discovery, replication, and meta‐analysis. We analyzed the tissue‐ and molecule‐specificity of our associations by comparing to plasma & brain pQTLs and various eQTLs. We performed a proteome‐wide association study (PWAS) and Mendelian randomization (MR) to prioritize proteins affecting AD. We determined shared protein‐disease genetic regulation using colocalization. Using AD‐associated proteins, we built risk models of disease status. Result: We identified 2,316 significant pQTL (1,247 in cis and 1,069 in trans) for 1,960 proteins, of which 1,720 were novel and not reported in the largest currently available pQTL studies in plasma or brain. Through PWAS, we identified 440 proteins associated with AD risk, which show enrichment in neurons (with APOE region) or microglia/macrophages (without APOE). MR prioritized 37 proteins as causal and colocalization identified 153 proteins that share genetic etiology with AD. Seventeen of these proteins overlap between all three methods and multiple (including PILRA, PRSS8, and SIRPA) represent novel causal proteins for AD. A protein risk score using PWAS‐identified proteins outperformed a polygenic risk score (PRS) at predicting amyloid/tau positivity across ages (AUC: 0.852‐0.906 vs. 0.724‐0.806, P<0.002) and across APOE genotypes (AUC: 0.809‐0.893 vs. 0.70‐0.80, P<0.027). Conclusion: We reported the largest CSF pQTL analysis to date and confirmed that CSF pQTLs are largely tissue‐specific. We identified proteins involved in AD that confirm reported candidate genes and prioritize new ones at GWAS loci. We developed accurate prediction models using prioritized proteins. Our findings offer insights into AD biology undetected with plasma pQTL analyses, supporting proteogenomic databases in neurologically‐relevant tissues. [ABSTRACT FROM AUTHOR]

Background: Triggering receptor expressed on myeloid cells 2 (TREM2) plays a critical role in microglial activation, survival, and apoptosis, as well as in Alzheimer's disease (AD) pathogenesis. We previously reported the MS4A locus as a key modulator for soluble TREM2 (sTREM2) in cerebrospinal fluid (CSF). Here, we pursued the largest CSF study to identify additional novel genetic modifiers of sTREM2. Method: We performed the genome‐wide association study (GWAS) of CSF sTREM2 in 3350 individuals of European ancestry from eight cohorts. To identify functional genes, we performed multi‐ethnic fine mapping with 250 non‐European individuals. Functional validation using peripheral blood mononuclear cell‐derived macrophages was performed. Colocalization and Mendelian randomization (MR) was performed for the causality of sTREM2 in AD. Result: The known MS4A locus and three novel loci were identified at genome‐wide significance. In the MS4A locus, we identified two independent missense variants (p.M178V in MS4A4A and p.A112T in MS4A6A) that drove the association through multi‐ethnic fine mapping. They showed an epistatic effect for sTREM2 and AD risk. The novel TREM2 locus on chromosome 6 contained two rare missense variants (rs142232675 p.D87N, P = 2.71×10‐10; rs75932628 p.R47H, P = 7.16×10‐19) associated with sTREM2 and AD risk. Another novel locus in the intergenic region between TGFBR2 and RBMS3 (rs73823326, P = 3.86×10‐9) included a regulatory variant with a microglia‐specific chromatin loop for promoters of TGFBR2. Using cell‐ based assays we demonstrate that TGFBR2, but not RBMS3, modify sTREM2 levels. The last novel locus NECTIN2 on chromosome 19 (rs11666329, P = 2.52×10‐8) was independent of APOE genotype and colocalized with cis‐eQTL of NECTIN2 in the brain cortex and cis‐pQTL of NECTIN2 in CSF (PP.H4 = 0.83). This variant was also associated with AD risk (P = 1.52×10‐66) and age at onset (P = 3.26×10‐5). Our MR results confirmed the significant protective effect of sTREM2 on reducing AD risk. Conclusion: To our knowledge, this is the largest study to date aiming at identifying genetic modifiers of CSF sTREM2. We provided novel insights for MS4A and TREM2, the two well‐ known gens for AD risk. We also identified TGFBR2 and NECTIN2 as additional modulators involved in TREM2 biology. Our findings provide new insight to unravel sTREM2 modulators and their role in AD. [ABSTRACT FROM AUTHOR]

Background: Understanding the role of amyloid imaging in the earliest stages of Alzheimer’s Disease (AD) becomes increasingly relevant for secondary prevention. In this context, the AMYPAD Prognostic and Natural History Study (PNHS) is an open‐label, prospective, multi‐centre cohort study (http://amypad.eu/) to determine the value of quantitative amyloid PET imaging in determining AD dementia risk. The study recruits from several European cohorts and aims at enrolling 2000 non‐demented individuals with a particular focus on those with emerging amyloid pathology. Method: As of January 25th, 2020, AMYPAD PNHS had 17 actively recruiting sites across Europe, and 782 non‐demented participants (>95% cognitively unimpaired) had consented to participate in the study. Of those, 448 are from EPAD LCS, 129 from EMIF‐AD Twin 60++, 111 from FACEHBI, 70 from ALFA+, 17 from FPACK, and 7 from the UCL‐2010‐412 cohort. Of the consented subjects, 334 already had an amyloid PET scan before this study. Within AMYPAD PNHS, 588 subjects have hitherto been scanned with either [18F]flutemetamol or [18F]florbetaben. Of note, 53.6% of the total number of scans have been acquired with a dual‐time window dynamic protocol. The primary outcome measure is the Centiloid value (CL) using the whole cerebellum as reference region, to enable quantitative comparability between the two tracers in the study. Also, images have been visually assessed by local raters. Of the 588 acquired scans, 296 have been quantified with IXICO’s LEAP pipeline and passed Quality Control, thus rendering valid CL values. Subjects were categorized as amyloid‐negative (CL≤12); as in a “gray‐zone” (1250) and a Gaussian Mixture Model was used to assess the population’s Centiloid distribution. Result: Based on visual assessment, 28% of the fully 296 quantified scans were visually rated as positive and 72% as negative. Quantitatively, 50% of them were categorized as negative, 33% in the gray‐zone, and 17% were positive (Figure 1). Centiloid values ranged from ‐30.3 to 154.2 (Mean±SD: 22.5±32.0 CL) (Figure 2). Conclusion: Preliminary quantitative results indicate that PNHS is being successful in recruiting a cohort mostly composed of cognitively unimpaired individuals who are enriched for early amyloid abnormalities, which is the intended target population. [ABSTRACT FROM AUTHOR]

Background: Hippocampal sclerosis of aging (HS) is one of the most predominant causes of dementia in elder populations and it is often misdiagnosed as Alzheimer's disease (AD). HS has recently been found to show a hippocampal atrophy pattern that might be key for the differentiation of this pathology from AD in the early stages of dementia. Method: In this study, we aimed to find SNPs associated with AD diagnosis that might be related to HS. To that end, we calculated a polygenic risk score (PRS) combining SNPs associated with AD by Bellenguez et al. (2022) and assessed their relation with HS‐by‐proxy based on magnetic resonance imaging (MRI) data of hippocampal subfield volumes from 1,130 individuals without dementia syndrome. Result: Our results show a significant association of AD‐PRS with fimbria and hippocampal body and head volumes. Association with these hippocampal subfields was also observed on the individual effects of the AD‐related variants in the SHARPIN (rs34173062) and TNIP1 (rs871269) genes. Besides, these loci remained consistently associated to HS‐aging after increasing the sample size by including an independent cohort of healthy individuals (N = 729). Conclusion: The results presented in this study suggest that some SNPs that have recently been identified as AD variants might be closely related to atrophy in hippocampal subfields instead of AD, and hence, could be instrumental to refine AD and HS pathways, their interrelationships, and to elaborate specific treatment for each condition. [ABSTRACT FROM AUTHOR]

Background: Rising knowledge about fundamental molecular mechanisms of diseases, the possibility to digitally collect a wealth of lifestyle data, and increasing diagnostic capabilities in early risk prediction make it as easy as never before to calculate a personalized risk for future diseases. Knowing and influencing that risk becomes a matter of personal choice and responsibility. Consequences both on the individual and on the societal level result from this predictive turn in medicine. By means of the evolving accessibility and reliability of biomarker‐based diagnostics and risk prediction in Alzheimer's disease (AD), we address the ethical perspective on this highly relevant topic. Method: In the ethical part of the PreTAD project, we pursue a Mixed‐Methods approach and will (1) conduct a survey with 150 individuals within the healthy population (50 per participating country; baseline + 6‐month follow‐up). Participants will be surveyed with quantitative standardized tests, newly developed questions, and by utilizing hypothetical scenarios of AD biomarker risk disclosure. Employing hypothetical scenarios serves to reveal the needs and attitudes of healthy individuals regarding early prediction of AD. We will (2) conduct 40 narrative interviews (baseline + 6‐month follow‐up) with healthy individuals, healthy individuals at risk (AD family history or APOE4 carriers), individuals diagnosed with subjective cognitive decline (SCD) (> 4 weeks), and individuals with recent (≤ 4 weeks) SCD diagnosis. Result: Predictive knowledge can be associated with different perspectives on the self, discrimination and (self‐)stigmatization. We therefore address self‐perception, self‐determination as well as identity and authenticity with regard to the attitudes of people sharing different prior experiences with AD. We want to learn about the relationship between identity, authenticity and attitudes toward a personalized risk profile for future disease. Additionally, we aim at highlighting the individual's needs in the course of an AD risk prediction in different groups of individuals, providing a detailed analysis of this phenomenon in a trinational and interdisciplinary (clinical, ethical, legal and linguistic) perspective. Conclusion: In this presentation, we will outline the methodology of a multilevel ethical analysis on fundamental questions of the paradigm shift towards predictive medicine ‐ exemplified by AD. [ABSTRACT FROM AUTHOR]

Background: Brain metabolism perturbation in dementia is not well understood. Metabolite levels are quantitative traits that have been linked to genetic loci. Existing metabolite quantitative trait loci (MQTL) were found mostly using tissues other than cerebrospinal fluid (CSF) and brain, which being less than ideal for studying neurodegenerative diseases. The first CSF MQTL study was published last year, but with limited power. Therefore, we hope to expand our knowledge on MQTL in the central nervous system to better understand neurological disorders. Method: We performed metabolome‐wide genome‐wide association study (M‐GWAS). More than 400 metabolites passed QC in CSF from 2329 participants recruited from five cohorts (CASTLE project). We performed a three‐stage study design: discovery (1224 CASTLE participants), replication (meta‐analysis of results from 1087 CASTLE participants and 291 CSF participants (Panyard, D.J. et. al 2021)) and meta‐analyses. Linear regression model includes age, sex, genetics principal components, genotyping array, and cohort information as covariates. We defined an association region to be 1 Mb interval centered on the index SNP (lowest study‐wide P value) by performing clumping of signals using plink1.9. We merged association regions if they share overlapping chromosome location to identify genetic locus associated with metabolite level traits. Future plan includes association study including rare variants, functional annotation of each locus, conditional analysis to identify independent signals, replication of identified signals, M‐GWAS for Brain metabolomics datasets (1169 samples in total), comparing features of identified associations amongst multi‐tissue (CSF, brain and blood) using mashr in R. In addition, colocalization and Mendelian randomization analysis will be performed to discover metabolites contributing to neurological disorders. Result: The preliminary CSF M‐GWAS study jointing five cohorts identified 165 associations in 125 metabolites from 90 loci. Meta‐analysis on the discovery and replication results will be utilized for the downstream functional annotation, tissue comparison, and disease mechanistic exploration. Conclusion: We present the largest CSF M‐GWAS study so far and showed a substantial number of genetic association findings for metabolites. We not only expect to replicate a number of our findings using studies with blood and CSF tissues, but also expect to discover novel signals that has potential for being unique to CSF. [ABSTRACT FROM AUTHOR]

Background: The most relevant risk factor in Alzheimer's disease (AD) is age. Aging is a complex process involving several biological changes which lead to chronic cellular stress and to a sterile tissue inflammation. During aging cells become senescent which is seen as morphological changes and secretion of immune signaling mediators associated with systemic low‐grade inflammation. Interestingly, during neurodegenerative processes such AD, microglia, astrocytes, and vascular unit cells become senescent. To explore the potential connection between immune signaling mediators, ageing, and biomarkers of AD, we have quantified in CSF several immune related molecules link to AD and analyzed their connection with known biological clocks. Method: Biological age was obtained by deriving the epigenetic clock in DNA derived from peripheral blood. To this end, DNA methylation data was generated using the EPIC array from Illumina in two cohorts including 348 individuals (cognitively normal, subjective cognitive decline and mild cognitive impairment) from DELCODE study and 267 individuals (mild cognitive impairment). Data was prepared and normalized using standard quality controls. Horvath's and Hannum epiClocks were computed for all individuals in both cohorts. AD biomarkers including Amyloid‐ß, phosphor‐tau and total tau along with a panel of inflammation markers were measured in CSF samples. Result: Both epiClocks showed a significant strong correlation with chronological age in both cohorts. Methylation age and chronological age showed both a significant association with classical AD biomarkers, as well as a subsets of inflammation markers. The meta‐analysis confirmed the association of the Epiclocks and the chronological age with all AD biomarkers as well as with YKL40, sTREM2, C‐1 and MIF. Based on the difference between the calculated epiClock and the chronological age, we derived an index reporting on increase in biological aging rate (age‐acceleration). This index, however, did not show significant association with any of the AD biomarkers and inflammation markers. Conclusion: Our study shows a link between inflammatory markers and methylation age in both healthy aging and pre‐dementia stages of AD. However, biological clocks derived from peripheral tissue seem to be independent of potential AD pathology and inflammation occurring in the aging brain. Thus, these biomarkers are not increasing the odds for methylation age‐acceleration. [ABSTRACT FROM AUTHOR]

Background: Expression quantitative trait locus (eQTL) studies have been influential in identifying gene targets for many complex diseases. However, levels of mRNA often correlate poorly with levels of the protein that they encode, due to rates of degradation, translation, or alternative splicing, among other reasons. By correlating protein levels to genetic variation, pQTLs can elucidate a more accurate genetic architecture that underlies disease. While few large‐scale studies have considered cerebrospinal fluid (CSF) protein levels, CSF biomarker levels are one of the primary diagnostic tools in Alzheimer's disease (AD), highlighting CSF's relevance to brain aging and AD pathology. Here, we present CSF pQTL analysis of over 3,000 individuals. Method: We generated CSF levels of 7,584 analytes for 3,065 samples using the aptamer‐based SOMAscan 7k platform. CSF levels of 4,884 analytes for additional 1,158 samples were also included. After stringent quality control, 3,107 unrelated European samples were selected for analysis. We performed pQTL analysis using a linear model with protein levels as the outcome variable, using a three‐stage study design: discovery, replication, and meta‐analysis. We performed colocalization of our pQTLs with eQTLs and GWAS loci, and compared our results to pQTLs from plasma studies to identify CSF‐specific pQTLs. We used Mendelian Randomization (MR) to identify proteins potentially causative for AD and other traits. Result: This study represents the first use of the SOMAscan 7k platform in CSF, as well as the largest pQTL analysis of CSF to date. Of 3818 analytes currently tested in our discovery set, 1480 have at least one SNP associated with analyte level at p < 5×10−8. Analyses are ongoing. Conclusion: We previously performed pQTL analysis of CSF using the SOMAscan 1.3k platform, where 425 pQTLs were identified and 3 proteins (PTP1B, Siglec‐3, and SLAF5) were found through MR to be involved in AD risk, as well as 48 additional protein associations for other neurodegenerative diseases. This study expands on those findings by including 6,000 more proteins and much larger samples, allowing for greater power. This study will be vital for identifying novel proteins involved in AD and elucidate novel drug targets for AD and other neurodegenerative disorders. [ABSTRACT FROM AUTHOR]

Background: Diagnostics for early detection and risk prediction in Alzheimer's disease (AD) are constantly evolving. Blood‐based biomarkers may replace more invasive and expensive methods (such as CSF and PET) and lead to a higher accessibility in the detection of AD pathology. These developments may result in an extended availability of risk prediction, also for patients with subjective cognitive decline (SCD) or symptom‐free individuals at risk. The PreTAD project aims at providing data and analyses on people's perspectives towards prediction as well as the effect of predictive medicine on individuals and society from a clinical, ethical, legal and linguistic point of view. Method: The empirical survey of PreTAD will focus on three different groups: 150 healthy participants with a family history of AD or APOE4 carriership; 150 participants with previously diagnosed SCD and 90 participants with newly diagnosed SCD ≤ 4 weeks. The participants will be studied with standardized quantitative tests, including newly developed assessments and will be provided with hypothetical scenarios of AD‐biomarker risk outcomes and disclosure. The longitudinal survey will be conducted by specialized Memory Clinics in Cologne, Geneva and Barcelona over a period of 6 months. To achieve a comprehensive approach, the trial design of our interdisciplinary collaboration combines quantitative assessment with qualitative (narrative) interviews, as well as ethical and legal analyses. In this presentation, we report the design of the study. Result: Our study serves to understand the perspectives, needs and preferences of cognitively healthy individuals with increased risk for AD regarding early AD‐biomarker testing and risk prediction of dementia. We will also obtain information on the participants understanding of risk and expectations towards risk prediction. It will also focus on psychological distress during the process of risk prediction, subjective well‐being, quality of life, identity and self‐perception measures as well as the willingness to undertake lifestyle changes and prevention. Conclusion: Our trinational project aims to contribute to the urgent need of creating a framework for good clinical practice regarding the prediction of AD in presymptomatic at‐risk‐stages. [ABSTRACT FROM AUTHOR]

Background: Diagnostics for early detection of Alzheimer's disease (AD), using biomarkers, and dementia risk prediction are constantly evolving which will eventually lead to an extended availability even for symptom‐free individuals. These developments of predictive medicine are changing medical procedures and ways of thinking as well as opportunities for patients. Furthermore, they are slowly exerting influence on public attitudes towards medicine. The PreTAD project aims at providing insights on people's perspectives towards prediction as well as the effect of predictive medicine on individuals and society from a clinical, ethical, legal and linguistic point of view. Method: In the linguistic part of the PreTAD study, we address the fact that patients and their relatives bring common knowledge, discursive arguments and attitudes – and thereby certain expectations – into the doctor‐patient‐interaction, for example into a counseling visit for predictive interventions. Among personal sources, the origin and distribution of that knowledge can be the public media discourse (online and offline). On the basis of an empirical linguistic media analysis (German, English), we seek to determine public knowledge about AD and dementia risk prediction before we aim to elaborate communicative patterns and influential arguments of the public discourse on this topic. Result: The findings of the linguistic approach of the PreTAD study contribute to the understanding of people's perspectives, preconceptions, stereotypes, expectations and hopes regarding dementia risk prediction. To ensure good clinical practice regarding predictive interventions, especially in pre‐symptomatic at‐risk stages, the latter have to be acknowledged and carefully negotiated in doctor‐patient‐interaction. Conclusion: A closer look at public knowledge, influential communicative patterns and attitudes towards AD, early detection diagnostics, and dementia risk prediction can shed light on the broader context of present counseling challenges. [ABSTRACT FROM AUTHOR]

Objective: Recent studies have shown that positron emission tomography (PET) tracer AV-1451 exhibits high binding affinity for paired helical filament (PHF)-tau pathology in Alzheimer's brains. However, the ability of this ligand to bind to tau lesions in other tauopathies remains controversial. Our goal was to examine the correlation of in vivo and postmortem AV-1451 binding patterns in three autopsy-confirmed non-Alzheimer tauopathy cases.Methods: We quantified in vivo retention of [F-18]-AV-1451 and performed autoradiography, [H-3]-AV-1451 binding assays, and quantitative tau measurements in postmortem brain samples from two progressive supranuclear palsy (PSP) cases and a MAPT P301L mutation carrier. They all underwent [F-18]-AV-1451 PET imaging before death.Results: The three subjects exhibited [F-18]-AV-1451 in vivo retention predominantly in basal ganglia and midbrain. Neuropathological examination confirmed the PSP diagnosis in the first two subjects; the MAPT P301L mutation carrier had an atypical tauopathy characterized by grain-like tau-containing neurites in gray and white matter with heaviest burden in basal ganglia. In all three cases, autoradiography failed to show detectable [F-18]-AV-1451 binding in multiple brain regions examined, with the exception of entorhinal cortex (reflecting incidental age-related neurofibrillary tangles) and neuromelanin-containing neurons in the substantia nigra (off-target binding). The lack of a consistent significant correlation between in vivo [F-18]-AV-1541 retention and postmortem in vitro binding and tau measures in these cases suggests that this ligand has low affinity for tau lesions primarily made of straight tau filaments.Interpretation: AV-1451 may have limited utility for in vivo selective and reliable detection of tau aggregates in these non-Alzheimer tauopathies. ANN NEUROL 2017;81:117-128. [ABSTRACT FROM AUTHOR]

Background: Aging is the greatest non‐genetic risk factor for many diseases including Alzheimer's Disease (AD) and its mechanisms are thus increasingly recognized as potential therapeutic targets. Since the molecular relationships between normal aging and AD are still largely unknown, we took advantage of recent methodological developments to measure more than 7k proteins in plasma to identify common but also different molecular mechanisms involved in aging and AD. Method: Recently, we developed new data‐driven bioinformatics approaches that uncovered marked non‐linear alterations in the human plasma proteome with age (Lehallier et al. Nature Medicine 2019). We applied these machine learning approaches to 271 patients at different stages of AD (61 subjects with Subjective Cognitive Decline: SCD, 106 with Mild Cognitive Impairment: MCI and 104 with AD) and compared these changes to those observed in a healthy aging cohort (370 subjects, 18‐69 years). Result: The analysis of proteomics trajectories confirmed marked non‐linear alterations in the human plasma proteome with aging and uncovered the complex molecular choreography of AD. By analyzing trajectories of groups of proteins, we identified multiple clusters of proteins that are differentially affected during aging and AD. These clusters were enriched for various biological processes relevant for AD progression such as the complement and coagulation cascades, axon guidance and angiogenesis (q<0.05) Conclusion: Altogether, our results reveal the intricate connections between aging and AD at the molecular level. The integrated proteomics trajectories analysis performed in this study allows the identification of new targets possibly playing a key role in AD but also pinpoints when these proteins are deviating from their normal trajectories and thus when they should be targeted by new therapies. [ABSTRACT FROM AUTHOR]

Background: It is demonstrated that the soluble TREM2 in the cerebrospinal fluid (CSF) is associated with Alzheimer disease (AD). Recent studies by our group found that it is the MS4A4A and/or MS4A6A locus that plays a role in modulating sTREM2 and is also associated with AD risk. The goal of this study is to validate and extend findings from previous studies using a larger cohort, identify functional genes, and determine the overlap of the genetic architecture of CSF TREM2 levels with other traits. Method: We used 3,033 individuals from Knight ADRC, ADNI, DIAN, and PPMI, and 8,499,039 variants (MAF >0.01) to identify protein quantitative trait loci (pQTLs) that modify TREM2 levels via a linear regression including age, sex, first 10 genetic principal components and array/cohort as covariates. TREM2 protein measurements were obtained from SomaScan 7k platform. Colocalization analyses were conducted for AD risk as well as functional genes from eQTLGen. LDSC and GNOVA and Mendelian randomization (MR) is being used to determine the overlap of the genetic architecture of sTREM2 levels with those for AD risk, onset and progression, as well as cardiovascular and lipid traits. Result: The pQTL analysis identified the previously discovered MS4A gene region on chr11 (rs72918674, P = 7.009e‐58) as well as a peak on chr3 (rs73823326, P = 2.227e‐09). The lead variant resides in the intron of MS4A6A gene. Conditional analysis on this variant revealed rs10897026 as an additional independent signal located in the intron of MS4A4A. Chr11 peak colocalized with AD risk (PP‐H4 = 0.97) and MS4AE and MS4A6A expression QTL in blood (PP‐H4 = 0.97 and 0.96, respectively). Four regulatory region variants are in high linkage disequilibrium (LD) with chr3 index variant. RBMS3 and TGFBR2 are two genes flanking the chr3 peak, both expressed in microglia. Conclusion: This is the largest study to date aiming at identifying genetic modifiers of CSF sTREM2. The findings validated discoveries from previous studies and identified a novel signal on chr3 at genome‐wide significance. We propose two new genes, RBMS3 and TGFBR2 on chr3, could be involved in TREM2 biology. Our findings provide new insight to unravel sTREM2 modulators and their role in AD. [ABSTRACT FROM AUTHOR]

Objective: To examine region- and substrate-specific autoradiographic and in vitro binding patterns of positron emission tomography tracer [F-18]-AV-1451 (previously known as T807), tailored to allow in vivo detection of paired helical filament-tau-containing lesions, and to determine whether there is off-target binding to other amyloid/non-amyloid proteins.Methods: We applied [F-18]-AV-1451 phosphor screen autoradiography, [F-18]-AV-1451 nuclear emulsion autoradiography, and [H-3]-AV-1451 in vitro binding assays to the study of postmortem samples from patients with a definite pathological diagnosis of Alzheimer disease, frontotemporal lobar degeneration-tau, frontotemporal lobar degeneration-transactive response DNA binding protein 43 (TDP-43), progressive supranuclear palsy, corticobasal degeneration, dementia with Lewy bodies, multiple system atrophy, cerebral amyloid angiopathy and elderly controls free of pathology.Results: Our data suggest that [F-18]-AV-1451 strongly binds to tau lesions primarily made of paired helical filaments in Alzheimer brains (eg, intraneuronal and extraneuronal tangles and dystrophic neurites), but does not seem to bind to a significant extent to neuronal and glial inclusions mainly composed of straight tau filaments in non-Alzheimer tauopathy brains or to lesions containing β-amyloid, α-synuclein, or TDP-43. [F-18]-AV-1451 off-target binding to neuromelanin- and melanin-containing cells and, to a lesser extent, to brain hemorrhagic lesions was identified.Interpretation: Our data suggest that [F-18]-AV-1451 holds promise as a surrogate marker for the detection of brain tau pathology in the form of tangles and paired helical filament-tau-containing neurites in Alzheimer brains but also point to its relatively lower affinity for lesions primarily made of straight tau filaments in non-Alzheimer tauopathy cases and to the existence of some [F-18]-AV-1451 off-target binding. These findings provide important insights for interpreting in vivo patterns of [F-18]-AV-1451 retention. [ABSTRACT FROM AUTHOR]

Background: To explore the impact of Metabolic Syndrome (MetS) and its components on Cognitive Composites (CCs) domain scores and on White Matter Hyperintensities (WMHs) in individuals experiencing Subjective Cognitive Decline (SCD). Method: Two hundred participants from the FACEHBI cohort underwent structural Magnetic Resonance Imaging (MRI), 18F‐Florbetaben Positron Emission Tomography (FBB‐PET), and a comprehensive neuropsychological assessment. MetS was defined using the Joint Interim Statement of the International Diabetes Federation Task Force on Epidemiology and Prevention criteria (elevated fasting glucose, elevated blood pressure, reduced HDL‐C, elevated triglycerides and elevated waist circumference). WMHs were addressed through the Fazekas scale, the Age‐related white matter changes (ARWMC) scale, and the FreeSurfer pipeline. Ten CCs domain scores were created using principal components analysis (PCA): (1) executive function fluency, (2) executive function processing speed, (3) executive function attention, (4) verbal memory, (5) visual memory, (6) face–name associative memory, (7) face–occupation associative memory, (8) language, (9) visuoperception, and (10) praxis. Age, sex, education, and Apolipoprotein E (APOE) were used as adjusting variables. Several analyses were performed to explore a sex effect. Result: Forty‐seven individuals matched the MetS criteria. This syndrome behaves differently based on sex. Only women with MetS showed better performance in language (p =.002; OR = 2.12) than those without MetS. The only differentiating component between both groups (presence/absence MetS) was that women in the MetS subgroup presented greater abdominal obesity (Mann‐Whitney p =.001). From Mets group, antihypertensive drug treatment was significantly associated with better praxis scores (p =.012; OR = 1.84) and HDL‐C drug treatment with better language scores but worse episodic memory performance (p =.028; OR = 1.60; and p =.007; OR =.57, respectively). Drug treatment for elevated glucose was associated with low WMH load in the ARWMC scale (β= ‐.144; p =.045). Conclusion: This study demonstrated a protective effect of MetS in cognitive performance among SCD women with greater abdominal obesity and a lack of association between MetS and WMH load, although further investigation is needed to explore the long term impact of its entity. [ABSTRACT FROM AUTHOR]

Background: Subjective cognitive decline (SCD) has been associated with increased risk of subsequent mild cognitive impairment (MCI) and dementia. Evidence from magnetic resonance imaging studies shows that neurodegenerative changes are already present years before dementia and thus, examining brain changes in SCD may contribute to identify potential biomarkers at an early stage of Alzheimer’s disease. Method: 198 individuals with SCD from the FACEHBI cohort were included (124 females; mean age 65.76 years). All subjects underwent magnetic resonance imaging and 18F‐Florbetaben positron emission tomography scan at baseline and were clinically follow‐up. Whole‐brain cortical surface‐based morphometry analysis were conducted using Freesurfer. Changes in cortical morphology (cortical thickness and surface area) were examined in relation to age, gender, brain amyloid beta deposition, ApoE‐e4 status (52 carrier/ 146 non carrier) and progression to MCI or dementia at the 4‐year follow‐up. Age, sex and years of education were included as covariates in all analyses. Result: At p=0.05 corrected, higher age was associated with widespread cortical thickness reduction and reduced surface area in bilateral parahippocampal, left cuneus and middle frontal and in the right superior frontal cortex. Males had reduced cortical thickness in the right lingual and reduced surface area in the right superior temporal cortex. Higher amyloid beta deposition was related to higher surface area in the left inferior parietal cortex and no significant results were found in relation to ApoE‐e4 status. At the 4‐year follow‐up, 33 subjects had progressed to MCI and 118 remained cognitively unimpaired, but there were no significant differences in baseline cortical thickness or surface area between them. With a liberal threshold of p<0.0001 uncorrected, we found a cluster of reduced cortical thickness in the right isthmus cingulate in those who converted to MCI four years later. Conclusion: Brain morphological changes in SCD are mainly characterized by cortical thickness reduction in relation to age and increased left inferior parietal surface area in relation to higher brain amyloid burden. Baseline reduced cortical thickness in the right isthmus cingulate is the only region associated with subsequent clinical progression to MCI and thus, it might be a useful predictive biomarker of cognitive decline in SCD individuals. [ABSTRACT FROM AUTHOR]

Background: The diagnosis of mild cognitive impairment (MCI) due to Alzheimer's disease (AD) is based on either cerebrospinal fluid (CSF) or neuroimaging biomarkers (Albert et al, 2011). Currently, several non‐invasive and cheaper blood‐based biomarkers are being investigated, including neuronal‐derived plasma exosomes (NPEs) (Winston et al, 2016). The role of neuroinflammation, oxidative stress and early vascular changes, prior to the onset of amyloidosis, has been described in the pathogenesis of AD (Iturria‐Medina et al, 2016) and vascular‐related proteins can be traced in plasma and NPEs using proteomics. However, these changes have not been studied in early onset MCI (EOMCI), that is, when symptoms begin under the age of 65 (Rossor et al, 2010). Objective: To describe the rationale, study design and baseline characteristics of the BIOFACE cohort, a two‐year prospective observational study on EOMCI conducted at Fundació ACE in Barcelona, Spain. The study goal is to characterize different clinical, neuropsychological and biomarker phenotypes and to investigate CSF and plasma proteomics as well as the role of NPEs as early biomarkers of AD. Method: Participants underwent neurological and neuropsychological batteries and multimodal biomarkers including brain MRI, APOE genotyping, plasma and NPEs, saliva, CSF, non‐invasive arterial peripheral testing, anthropometrics and neuro‐ophthalmological examinations. In the final visit, participants will undergo brain MRI, lumbar puncture and blood extraction for NPEs. Result: Ninety‐seven patients with EOMCI were recruited. Most participants were women (59.8%). Mean age at symptom onset was 57 years; mean MMSE score was 28 with a mean of 12.13 years of education. First degree and presenile family history of dementia was present in 60.8% and 15.5%, respectively. Depressive and anxiety disorders, along with vascular risk factors, were the most frequent comorbidities. Syndromic diagnoses were established: possible amnestic MCI (n=32), possible non‐amnestic MCI (n=33), probable amnestic MCI (n=16) and probable non amnestic MCI (n=16). CSF biomarkers (ATN classification): A+ (n=15), A‐T/N+ (n=13), A‐T‐N‐ (n=57). Conclusion: BIOFACE is a two‐year observational study of cognition and biomarkers that will shed light on the physiopathology and the potential utility of plasma proteomics and NPEs as non‐invasive early diagnostic and prognostic biomarkers in individuals with early onset MCI. [ABSTRACT FROM AUTHOR]

Background: Cumulative data suggest that subjective cognitive decline (SCD) could be an early clinical manifestation of Alzheimer's disease (AD). The performance of blood based AD‐related biomarkers at this early stage of the disease continuum has not been sufficiently studied yet. Method: We explored the association between total Aβ42 to total Aβ40 ratio in plasma (TP42/40) assessed by ABtest (Araclon Biotech) and cortical β‐amyloid assessed by Florbetaben positron emission tomography (FBB‐PET, Life Molecular Imaging) scan in 162 cases of SCD from the Fundació ACE Healthy Brain Initiative (FACEHBI) with plasma and FBB‐PET data at baseline (V0) and two years follow‐up (V2) visits. All plasma samples were analyzed simultaneously at the time of V2. Cut‐off for PET‐FBB positivity was established at a global standardized uptake volume ratio (SUVR)>1.45. Result: TP42/40 was significantly lower in FBB‐PET‐ve) than in FBB‐PET+ve group at both time points (Mann‐Whitney test P<0.0001). The AUC in the ROC analysis for the relevant demographic variables (age and APOE genotype) to discriminate FBB‐PET status at V0 and V2 was 80% and 83%, respectively. Those values increased significantly (P<0.01) up to 90% and 92%, respectively, when TP42/40 was included as a predictive variable within the model. The performance parameters of TP42/40 to discriminate FBB‐PET status in V0∼V2 were SEN 1.0∼0.94, SPE 0.49∼0.42, PPV 0.16∼0.15 and NPV 1.0∼0.98, respectively. Caution should be exerted when interpreting these values because they could be biased given the very low prevalence of FBB‐PET+ve (8.6%) in this early population, at the current SUVR cut‐off. Nevertheless, in a recruiting scenario targeting FBB‐PET+ve individuals with SCD, a pre‐screening step based on TP42/40 could save 46%∼34% of PET scans. Furthermore, those individuals with a TP42/40 ratio in the lowest quartile at V0 showed significantly (P<0.01) greater increases of FBB‐PET SUVR at V2 than those with a V0 plasma ratio in the two upper quartiles. Conclusion: TP42/40 is consistently associated with cortical β‐amyloid burden assessed by FBB‐PET in individuals with SCD. The TP42/40 could be a useful tool helping in the recruitment of SCD individuals with preclinical Alzheimer's. [ABSTRACT FROM AUTHOR]

Background: Traditional quantitative cut‐offs for amyloid PET positivity have been defined to discriminate Alzheimer's dementia (AD) subjects from elderly Aβ‐negative non‐demented controls. Currently, observational and interventional studies focus on earlier stages of Aβ deposition, where established cut‐offs might not be appropriate. Here, we review recent developments on early pathology identification, and provide supporting evidence from three cohorts for the establishment of a "gray‐zone" of amyloid burden. Method: Data from three cohorts of cognitively unimpaired individuals were included, namely ALFA+ (n=357), FACEHBI (n=228) and the AMYPAD Prognostic Study (n=122). PET scans ([18F]flutemetamol and [18F]florbetaben) were analyzed in Centiloid (CL) units. Gaussian Mixture Modelling was used to fit two/three Gaussians to the global CL values, and the cut‐off for early pathology detection was defined as two standard deviations above the mean of the left Gaussian. Then, the data was merged to derived a joint cut‐off. Finally, these data‐driven cut‐offs were compared to previously established thresholds in the context defining a range of CL values where pathology is emerging. Result: GMM identified a cut‐off of CL=11 for FACEHBI, CL=14 for ALFA+, CL=17 for AMYPAD and CL=11 for the cohorts combined (Figure 1). Similarly, Salvadó et al identified two cut‐offs based on a direct comparison with established CSFAβ42 thresholds: CL=12 to rule out‐amyloid pathology and CL=29 to denote established pathology. With a different approach, the FACEHBI working group finds CL=13 as an early threshold defined based on young healthy controls, and CL=36 as an established cut‐off to separate healthy elderly from Aβ‐positive AD‐dementia subjects. In AMYPAD, where a more comprehensive sampling of the AD continuum is present, fitting 3 Gaussians through the data allows the identification of two data‐driven cut‐offs: CL=13 and CL=29. Conclusion: A number of recent and current reports converge to the utility of two cut‐offs for amyloid PET abnormality, an early cut‐off around CL=11‐17 where pathology may be emerging, and a second around CL=29‐36 where amyloid burden levels greatly correspond to neuropathology findings. Together, these create a gray‐zone of CL values pre‐AD dementia levels of amyloid burden, which can improve the detection of emerging pathology in observational and secondary prevention trials. [ABSTRACT FROM AUTHOR]

Background: Clinical diagnosis of Alzheimer's disease (AD) increasingly incorporate CSF biomarkers. However due to the intrinsic variability of the immunodetection techniques used to measure these biomarkers, it is recommended to establish in‐house cutoffs defining the positivity/negativity of CSF biomarkers. Method: We quantified CSF Aβ1‐42, t‐Tau, p181Tau and Aβ1‐40 with standard INNOTEST® ELISA and Lumipulse G® chemiluminescence enzyme‐immunoassay (CLEIA) performed on automated Lumipulse G600II. Determination of cutoffs included patients clinically diagnosed with Alzheimer Disease (AD, n=37) and amyloid‐negative Subjective Cognitive Decline subjects (SCD, n=45), cognitively stable during 3‐years and with no evidence of brain amyloidosis in 18F‐Florbetaben‐labeled positron emission tomography (FBB‐PET). To compare both methods, a subset of samples for Aβ1‐42 (n=519), t‐Tau (n=399), p181Tau (n=77) and Aβ1‐40 (n=44) were analyzed. Kappa agreement of single biomarkers and Aβ1‐42/Aβ1‐40 was performed in an independent group of mild cognitive impairment (MCI) and dementia patients (n=68). Result: Cutoffs values of Aβ1‐42 and t‐Tau were higher for CLEIA than for ELISA and similar for p181Tau. Spearman coefficients ranged between 0.81 for Aβ1‐40 and 0.96 for p181TAU. Passing‐Bablok analysis showed a systematic and proportional difference for all biomarkers but only systematic for Aβ1‐40. Bland‐Altman analysis showed an average difference between methods in favor of CLEIA. Kappa agreement for single biomarkers were good but lower for Aβ1‐42/Aβ1‐40. Conclusion: We established internal cutoffs to discriminate AD patients from amyloid‐negative SCD individuals. Results obtained by both methods are not interchangeable but showed good agreement. We propose automated CLEIA as a good alternative to manual ELISA together with Aβ1‐42/Aβ1‐40 to classify amyloidosis. [ABSTRACT FROM AUTHOR]

Background: It is well known that Alzheimer's disease (AD) has a strong genetic component. Even though it is a highly heritable disease, a big fraction of AD heritability remains to be elucidated. Genetic analysis of endophenotypes tightly linked to the disease might help to identify or confirm AD genetic risk factors. Methods: GWAS results Amyloid β (Aβ42) in cerebrospinal fluid (CSF) or positron emission tomography (PET) measures were combined in a single meta‐analysis. Six independent GWAS were run using a generalized linear model with four principal components and status as a covariate (PLINK software). The datasets had data for two different amyloid endophenotypes: CSF‐Aβ42 levels from ADNI, Marqués de Valdecilla Hospital (Santander) and Fundació ACE (N= 1051); or PET‐SUVR (amyloid global standardized uptake ratio) from ADNI and Fundació ACE (N= 607). GWAS results were meta‐analysed using the sample size weighted method (METAL software). To reduce false positive findings, only genetic signals with opposite effect direction in PET and CSF endophenotypes were considered. Finally, we tried to replicate previously known genes for AD (de Rojas et al., MedRxiv 2019). Results: After selecting SNPs with opposite effect on CSF and PET associations (N= 325051), we only observed genome wide significance in APOE locus (rs429358, P‐value= 2.202×10‐48) in the meta‐GWAS. We also observed several suggestive signals in chromosomes 3, 5 and 6 (rs72977014, rs13164192 and rs4960198); further studies are needed to add evidence of AD association. Finally, relative to known AD genes we were able to replicate CR1 (rs4844610, P‐value= 0.045) signal. Conclusion: By combining data from both β‐amyloid endophenotypes (CSF and PET) we were able to replicate some well‐known AD genes indicating that this approach could be a useful strategy to identify novel variants increasing the knowledge of AD genetic architecture. [ABSTRACT FROM AUTHOR]