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Blood-based diagnostics and prognostics in sporadic Alzheimer's disease (AD) are important for identifying at-risk individuals for therapeutic interventions.In three stages, a total of 34 leukocyte antigens were examined by flow cytometry immunophenotyping. Data were analyzed by logistic regression and receiver operating characteristic (ROC) analyses.We identified leukocyte markers differentially expressed in the patients with AD. Pathway analysis revealed a complex network involving upregulation of complement inhibition and downregulation of cargo receptor activity and Aβ clearance. A proposed panel including four leukocyte markers - CD11c, CD59, CD91, and CD163 - predicts patients' PET Aβ status with an area under the curve (AUC) of 0.93 (0.88 to 0.97). CD163 was the top performer in preclinical models. These findings have been validated in two independent cohorts.Our finding of changes on peripheral leukocyte surface antigens in AD implicates the deficit in innate immunity. Leukocyte-based biomarkers prove to be both sensitive and practical for AD screening and diagnosis.

Glial fibrillary acidic protein (GFAP) is a promising candidate blood-based biomarker for Alzheimer’s disease (AD) diagnosis and prognostication. The timing of its disease-associated changes, its clinical correlates, and biofluid-type dependency will influence its clinical utility. We evaluated plasma, serum, and CSF GFAP in families with autosomal dominant AD (ADAD), leveraging the predictable age at symptom onset to determine changes by stage of disease. Plasma GFAP elevations appear a decade before expected symptom onset, after β-amyloid accumulation and prior to neurodegeneration and cognitive decline. Plasma GFAP distinguished β-amyloid-positive from β-amyloid-negative ADAD participants and showed a stronger relationship with β-amyloid load in asymptomatic than symptomatic ADAD. Higher plasma GFAP was associated with the degree and rate of neurodegeneration and cognitive impairment. Serum GFAP showed similar relationships, but these were less pronounced for CSF GFAP. Our findings support a role for plasma GFAP as a clinical biomarker for β-amyloid-associated cognitive deterioration in AD.

Background Major prevention trials for Alzheimer’s disease (AD) are now focusing on multidomain lifestyle interventions. However, the exact combination of behavioral factors related to AD pathology remains unclear. In 2 cohorts of cognitively unimpaired individuals at risk of AD, we examined which combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle (years of education or lifetime cognitive activity) related to the pathological hallmarks of AD, amyloid-β, and tau deposits. Methods A total of 115 older adults with a parental or multiple-sibling family history of sporadic AD (PREVENT-AD [PRe-symptomatic EValuation of Experimental or Novel Treatments for AD] cohort) underwent amyloid and tau positron emission tomography and answered several questionnaires related to behavioral attributes. Separately, we studied 117 mutation carriers from the DIAN (Dominant Inherited Alzheimer Network) study group cohort with amyloid positron emission tomography and behavioral data. Using partial least squares analysis, we identified latent variables relating amyloid or tau pathology with combinations of personality traits, neuropsychiatric symptoms, and cognitive lifestyle. Results In PREVENT-AD, lower neuroticism, neuropsychiatric burden, and higher education were associated with less amyloid deposition (p = .014). Lower neuroticism and neuropsychiatric features, along with higher measures of openness and extraversion, were related to less tau deposition (p = .006). In DIAN, lower neuropsychiatric burden and higher education were also associated with less amyloid (p = .005). The combination of these factors accounted for up to 14% of AD pathology. Conclusions In the preclinical phase of both sporadic and autosomal dominant AD, multiple behavioral features were associated with AD pathology. These results may suggest potential pathways by which multidomain interventions might help delay AD onset or progression.

Background: Type 2 diabetes related human islet amyloid polypeptide (hIAPP) plays a dual role in Alzheimer’s disease (AD). hIAPP has neuroprotective effects in AD mouse models whereas, high hIAPP concentrations can promote co-aggregation with amyloid-β (Aβ) to promote neurodegeneration. In fact, both low and high plasma hIAPP concentration has been associated with AD. Therefore, non-aggregating hIAPP analogues have garnered interest as a treatment for AD. The aromatic amino acids F23 and I26 in hIAPP have been identified as the key residues involved in self-aggregation and Aβ cross-seeding. Objective: Three novel IAPP analogues with single and double alanine mutations (A1 = F23, A2 = I26, and A3 = F23 + I26) were assessed for their ability to aggregate, modulate Aβ oligomer formation, and alter neurotoxicity. Methods: A range of biophysical methods including Thioflavin-T, gel electrophoresis, photo-crosslinking, circular dichroism combined with cell viability assays were utilized to assess protein aggregation and toxicity. Results: All IAPP analogues showed significantly less self-aggregation than hIAPP. Co-aggregated Aβ42-A2 and A3 also showed reduced aggregation compared to Aβ42-hIAPP mixtures. Self- and co-oligomerized A1, A2, and A3 exhibited random coil conformations with reduced beta sheet content compared to hIAPP and Aβ42-hIAPP aggregates. A1 was toxic at high concentrations compared to A2 and A3. However, co-aggregated Aβ42-A1, A2, or A3 showed reduced neurotoxicity compared to Aβ42, hIAPP, and Aβ42-hIAPP aggregates. Conclusion: These findings confirm that hIAPP analogues with non-aromatic residues at positions 23 and 26 have reduced self-aggregation and the ability to neutralize Aβ42 toxicity. This warrants further characterization of their protective effects in pre-clinical AD models.

Important insights into the early pathogenesis of Alzheimer's disease can be provided by studies of autosomal dominant Alzheimer's disease and Down syndrome. However, it is unclear whether the timing and spatial distribution of amyloid accumulation differs between people with autosomal dominant Alzheimer's disease and those with Down syndrome. We aimed to directly compare amyloid changes between these two groups of people.In this cross-sectional study, we included participants (aged ≥25 years) with Down syndrome and sibling controls who had MRI and amyloid PET scans in the first data release (January, 2020) of the Alzheimer's Biomarker Consortium-Down Syndrome (ABC-DS) study. We also included carriers of autosomal dominant Alzheimer's disease genetic mutations and non-carrier familial controls who were within a similar age range to ABC-DS participants (25-73 years) and had MRI and amyloid PET scans at the time of a data freeze (December, 2020) of the Dominantly Inherited Alzheimer Network (DIAN) study. Controls from the two studies were combined into a single group. All DIAN study participants had genetic testing to determine PSEN1, PSEN2, or APP mutation status. APOE genotype was determined from blood samples. CSF samples were collected in a subset of ABC-DS and DIAN participants and the ratio of amyloid β42 (Aβ42) to Aβ40 (Aβ42/40) was measured to evaluate its Spearman's correlation with amyloid PET. Global PET amyloid burden was compared with regards to cognitive status, APOE ɛ4 status, sex, age, and estimated years to symptom onset. We further analysed amyloid PET deposition by autosomal dominant mutation type. We also assessed regional patterns of amyloid accumulation by estimated number of years to symptom onset. Within a subset of participants the relationship between amyloid PET and CSF Aβ42/40 was evaluated.192 individuals with Down syndrome and 33 sibling controls from the ABC-DS study and 265 carriers of autosomal dominant Alzheimer's disease mutations and 169 non-carrier familial controls from the DIAN study were included in our analyses. PET amyloid centiloid and CSF Aβ42/40 were negatively correlated in carriers of autosomal dominant Alzheimer's disease mutations (n=216; r=-0·565; p0·0001) and in people with Down syndrome (n=32; r=-0·801; p0·0001). There was no difference in global PET amyloid burden between asymptomatic people with Down syndrome (mean 18·80 centiloids [SD 28·33]) versus asymptomatic mutation carriers (24·61 centiloids [30·27]; p=0·11) and between symptomatic people with Down syndrome (77·25 centiloids [41·76]) versus symptomatic mutation carriers (69·15 centiloids [51·10]; p=0·34). APOE ɛ4 status and sex had no effect on global amyloid PET deposition. Amyloid deposition was elevated significantly earlier in mutation carriers than in participants with Down syndrome (estimated years to symptom onset -23·0 vs -17·5; p=0·0002). PSEN1 mutations primarily drove this difference. Early amyloid accumulation occurred in striatal and cortical regions for both mutation carriers (n=265) and people with Down syndrome (n=128). Although mutation carriers had widespread amyloid accumulation in all cortical regions, the medial occipital regions were spared in people with Down syndrome.Despite minor differences, amyloid PET changes were similar between people with autosomal dominant Alzheimer's disease versus Down syndrome and strongly supported early amyloid dysregulation in individuals with Down syndrome. Individuals with Down syndrome aged at least 35 years might benefit from early intervention and warrant future inclusion in clinical trials, particularly given the relatively high incidence of Down syndrome.The National Institute on Aging, Riney and Brennan Funds, the Eunice Kennedy Shriver National Institute of Child Health and Human Development, the German Center for Neurodegenerative Diseases, and the Japan Agency for Medical Research and Development.

BackgroundInsights gained from studying individuals with autosomal dominant Alzheimer's disease have broadly influenced mechanistic hypotheses, biomarker development, and clinical trials in both sporadic and dominantly inherited Alzheimer's disease. Although pathogenic variants causing autosomal dominant Alzheimer's disease are highly penetrant, there is substantial heterogeneity in levels of amyloid β (Aβ) between individuals. We aimed to examine whether this heterogeneity is related to disease progression and to investigate the association with mutation location within PSEN1, PSEN2, or APP.MethodsWe did cross-sectional and longitudinal analyses of data from the Dominantly Inherited Alzheimer's Network (DIAN) observational study, which enrols individuals from families affected by autosomal dominant Alzheimer's disease. 340 participants in the DIAN study who were aged 18 years or older, had a history of autosomal dominant Alzheimer's disease in their family, and who were enrolled between September, 2008, and June, 2019, were included in our analysis. 206 participants were carriers of pathogenic mutations in PSEN1, PSEN2, or APP, and 134 were non-carriers. 62 unique pathogenic variants were identified in the cohort and were grouped in two ways. First, we sorted variants in PSEN1, PSEN2, or APP by the affected protein domain. Second, we divided PSEN1 variants according to position before or after codon 200. We examined variant-dependent variability in Aβ biomarkers, specifically Pittsburgh-Compound-B PET (PiB-PET) signal, levels of CSF Aβ1-42 (Aβ42), and levels of Aβ1-40 (Aβ40).FindingsCortical and striatal PiB-PET signal showed striking variant-dependent variability using both grouping approaches (p0·7), and CSF Aβ42 levels (codon-based grouping: p=0·49; domain-based grouping: p=0·095). Longitudinal PiB-PET signal also varied across codon-based groups, mirroring cross-sectional analyses.InterpretationAutosomal dominant Alzheimer's disease pathogenic variants showed highly differential temporal and regional patterns of PiB-PET signal, despite similar functional progression. These findings suggest that although increased PiB-PET signal is generally seen in autosomal dominant Alzheimer's disease, higher levels of PiB-PET signal at an individual level might not reflect more severe or more advanced disease. Our results have high relevance for ongoing clinical trials in autosomal dominant Alzheimer's disease, including those using Aβ PET as a surrogate marker of disease progression. Additionally, and pertinent to both sporadic and autosomal dominant Alzheimer's disease, our results suggest that CSF and PET measures of Aβ levels are not interchangeable and might reflect different Aβ-driven pathobiological processes.FundingNational Institute on Aging, Doris Duke Charitable Foundation, German Center for Neurodegenerative Diseases, Japanese Agency for Medical Research and Development.

Background The Australian Imaging and Biomarker Lifestyle (AIBL) study of aging is designed to aid the discovery of biomarkers. The current study aimed to discover differentially expressed plasma proteins that could yield a blood-based screening tool for Alzheimer’s disease. Methods The concentration of proteins in plasma covers a vast range of 12 orders of magnitude. Therefore, to search for medium to low abundant biomarkers and elucidate mechanisms of AD, we immuno-depleted the most abundant plasma proteins and pre-fractionated the remaining proteins by HPLC, prior to two-dimensional gel electrophoresis. The relative levels of approximately 3400 protein species resolved on the 2D gels were compared using in-gel differential analysis with spectrally resolved fluorescent protein detection dyes (Zdyes™). Here we report on analysis of pooled plasma samples from an initial screen of a sex-matched cohort of 72 probable AD patients and 72 healthy controls from the baseline time point of AIBL. Results We report significant changes in variants of apolipoprotein E, haptoglobin, α1 anti-trypsin, inter-α trypsin inhibitor, histidine-rich glycoprotein, and a protein of unknown identity. α1 anti-trypsin and α1 anti-chymotrypsin demonstrated plasma concentrations that were dependent on APOE ε4 allele dose. Our analysis also identified an association with the level of Vitamin D binding protein fragments and complement factor I with sex. We then conducted a preliminary validation study, on unique individual samples compared to the discovery cohort, using a targeted LC-MS/MS assay on a subset of discovered biomarkers. We found that targets that displayed a high degree of isoform specific changes in the 2D gels were not changed in the targeted MS assay which reports on the total level of the biomarker. Conclusions This demonstrates that further development of mass spectrometry assays is needed to capture the isoform complexity that exists in theses biological samples. However, this study indicates that a peripheral protein signature has potential to aid in the characterization of AD.

Alzheimer’s Disease (AD) is the most common form of dementia, characterised by extracellular amyloid deposition as plaques and intracellular neurofibrillary tangles of tau protein. As no current clinical test can diagnose individuals at risk of developing AD, the aim of this project is to evaluate a blood-based biomarker panel to identify individuals who carry this risk. We analysed the levels of 22 biomarkers in clinically classified healthy controls (HC), mild cognitive impairment (MCI) and Alzheimer’s participants from the well characterised Australian Imaging, Biomarker and Lifestyle (AIBL) study of aging. High levels of IL-10 and IL-12/23p40 were significantly associated with amyloid deposition in HC, suggesting that these two biomarkers might be used to detect at risk individuals. Additionally, other biomarkers (Eotaxin-3, Leptin, PYY) exhibited altered levels in AD participants possessing the APOE ε4 allele. This suggests that the physiology of some potential biomarkers may be altered in AD due to the APOE ε4 allele, a major risk factor for AD. Taken together, these data highlight several potential biomarkers that can be used in a blood-based panel to allow earlier identification of individuals at risk of developing AD and/or early stage AD for which current therapies may be more beneficial.

Alzheimer's disease (AD) is a degenerative brain disorder and is the most common form of dementia. Minimally invasive approaches are required that combine biomarkers to identify individuals who are at risk of developing mild cognitive impairment (MCI) and AD, to appropriately target clinical trials for therapeutic discovery as well as lifestyle strategies aimed at prevention. Buccal mucosa cells from the Australian Imaging, Biomarkers and Lifestyle Flagship Study of Ageing cohort (n=60) were investigated for cytological markers that could be used to identify both MCI and AD individuals. Visual scoring of the buccal cytome demonstrated a significantly lower frequency of basal and karyorrhectic cells in the MCI group compared with controls. A high content, automated assay was developed using laser scanning cytometry to simultaneously measure cell types, nuclear DNA content and aneuploidy, neutral lipid content, putative Tau and amyloid-β (Aβ) in buccal cells. DNA content, aneuploidy, neutral lipids and Tau were similar in all groups. However, there was significantly lower Tau protein in both basal and karyolytic buccal cell types compared with differentiated buccal cells. Aβ, as measured by frequency of cells containing Aβ signal, as well as area and integral of Aβ signal, was significantly higher in the AD group compared with the control group. Buccal cell Aβ was correlated with mini-mental state examination (MMSE) scores (r = -0.436, P=0.001) and several blood-based biomarkers. Combining newly identified biomarkers from buccal cells with those already established may offer a potential route for more specific biomarker panels which may substantially increase the likelihood of better predictive markers for earlier diagnosis of AD.

The ε4 polymorphism of the APOE gene confers a substantially increased risk of developing Alzheimer's disease. However, the influence of the ε4 allele on age-related cognitive functioning is more contentious. Previously, we demonstrated relatively little evidence for a role of the ε4 allele on baseline cognitive performance in older adults in the Australian Imaging, Biomarkers and Lifestyle (AIBL) Study of Ageing (Foster et al., 2013). We here investigated whether the APOE ε4 allele influenced cognitive status over time when the AIBL cohort was studied longitudinally over a 3-year period. The AIBL neuropsychological test battery was administered at baseline, after 18 months and again after 36 months. Participants comprised 764 Healthy Controls and 131 Mild Cognitively Impaired individuals enrolled in the AIBL Study of Ageing. We compared individuals within each group with and without an ε4 allele. Healthy Controls with an ε4 allele manifested a modest acceleration in cognitive decline over 36 months on measures of verbal episodic memory. By contrast, Mild Cognitively Impaired individuals with an ε4 allele showed increased cognitive decline across a range of cognitive tasks, putatively reflecting early cognitive signs of Alzheimer's disease. Given the long prodromal period that has been noted in late onset Alzheimer's disease, we suggest that these findings are consistent with a prodromal account rather than a phenotypic account of ε4-related cognitive ageing.

O2-13-06 PREDICTING ALZHEIMER’S DISEASE FROM A BLOOD-BASED BIOMARKER PROFILE: RESULTS FROM AIBL AT 54 MONTHS Samantha C. Burnham, David Ames, David Baker, Ashley I. Bush, Lynne Cobiac, James Doecke, Kathryn A. Ellis, Noel Garry Faux, Richard Head, Harri Kiiveri, Simon Matthew Laws, Ralph Martins, Paul Maruff, Greg Savage, Bill Wilson, Lance Macaulay, Christopher Cleon Rowe, Colin Louis Masters, AIBL RESEARCH

Previous studies have shown that mild cognitive impairment (MCI) may be reflective of the early stages of more pronounced neurodegenerative disorders such as Alzheimer's disease (AD). There is a need for a minimally invasive and inexpensive diagnostic to identify those who exhibit cellular pathology indicative of MCI and AD risk so that they can be prioritized for primary preventative measures. The hypothesis was that a minimally invasive approach using cytological markers in isolated buccal mucosa cells can be used to identify individuals of both MCI and AD. An automated buccal cell assay was developed using laser scanning cytometry (LSC) to measure buccal cell type ratios, nuclear DNA content and shape, and neutral lipid content of buccal cells from clinically diagnosed AD (n = 13) and MCI (n = 13) patients prior to treatment compared to age- and gender-matched controls (n = 26). DNA content was significantly higher in all cell types in both MCI (P 0.01) and AD (P 0.05) compared with controls mainly due to an increase in2N nuclei. Abnormal nuclear shape (circularity) was significantly increased in transitional cells in MCI (P 0.001) and AD (P 0.01) when compared to controls. In contrast, neutral lipid content (as measured by Oil red O "ORO" staining) of buccal cells was significantly lower in the MCI group (P 0.05) compared with the control group. The ratio of DNA content/ORO in buccal basal cells for both MCI and AD was significantly higher compared to the control group, with ratios for MCI being approximately 2.8-fold greater (P 0.01) and AD approximately 2.3-fold greater (P 0.05) than the control group. Furthermore, there was a strong negative correlation between buccal cell DNA content and ORO content in the AD group (r(2) = 0.75, P 0.0001) but not in MCI or controls. The changes in the buccal cell cytome observed in this study could prove useful as potential biomarkers in identifying individuals with an increased risk of developing MCI and eventually AD.

factors influence the proportion of dementia subtypes. Dementia in India is expected to reach epidemic proportions in the next two decades but studies on dementia are few. We studied patients attending a memory clinic in a private hospital in South India to describe the clinical profile and compare the socio-cultural factors influencing diagnosis and dementia care in this population with studies from developed countries. Methods: Consecutive patients attending the memory clinic at Manipal hospital, Bangalore over three years were included. Socio-demographic information including income, education and linguistic background was collected. All patients underwent detailed neurological evaluation, cognitive testing, blood tests and neuroimaging. The diagnosis of MCI, dementia and the different subtypes was based on standard criteria. Results: The mean age at presentation was 65.8(9.0) years, range 4087 years. There were 127 men and 93 women. Of the total 220 patients, MCI was diagnosed in 57 (25.9%), Alzheimer’s disease (AD) in 62 (28.1%), vascular dementia (VaD) in 38 (17.3%), and mixed dementia in four patients. 37 (16.8%) patients were diagnosed as frontotemporal lobar degeneration (FTD) and its variants. Other degenerative dementias were seen in 13 and miscellaneous causes in 8 patients. One patient did not appear to have any cognitive impairment. Majority of the patients (80.4%) were bilingual or multilingual and 10 (4.9%) patients were illiterate. VaD was more common in men (3:1) and AD in women (1.5:1). Majority of the MCI patients had depression (54.4%) and seven patients developed AD during follow-up. All the patients were cared for at home by relatives except for one patient who had an appointed caretaker. Conclusions: Alzheimer’s disease was more common than vascular dementia in this study from an urban hospital in South India, in spite of the high prevalence of vascular risk factors in this population. Depression was a common cause of mild cognitive impairment. In this study of a relatively young (mean age) dementia cohort, all patients had home based care in contrast to studies from developed countries. P1-146 PREDICTORS OF COGNITIVE DECLINE AT 18 MONTH FOLLOW UPAMONG 1112 PARTICIPANTS IN THE AUSTRALIAN IMAGING, BIOMARKERS AND LIFESTYLE FLAGSHIP STUDY OFAGEING (AIBL) Kathryn A. Ellis, Christopher Rowe, ColinMasters, Cassandra Szoeke, Kevin Taddei, Ralph Martins, Victor Villemagne, Michael Fahey, David Ames, PaulMaruff, Ping Zhang, Greg Savage, AIBLResearch Group, Lance Macaulay, University of Melbourne, Kew; Austin Health, University of Melbourne, Heidelberg, Melbourne; University of Melbourne, Melbourne, VIC; CSIRO, Melbourne; Edith Cowan University, Perth; Edith Cowan University, Perth; Austin Health, Melbourne; Division of Mathematics, Informatics and Statistics, CSIRO, Parkville, VIC; National Ageing Research Institute, Parkville; CogState, Melbourne; CSIRO, Parkville; Macquarie Centre for Cognitive Science, Macquarie University, Sydney, NSW; Mental Health Research Institute, Perth; CSIRO, Parkville.