Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU): Trial Satisfaction and Attitudes towards Future Clinical Trials.

BACKGROUND: Clinical trial satisfaction is increasingly important for future trial designs and is associated with treatment adherence and willingness to enroll in future research studies or to recommend trial participation. In this post-trial survey, we examined participant satisfaction and attitudes toward future clinical trials in the Dominantly Inherited Alzheimer Network Trials Unit (DIAN-TU). METHODS: We developed an anonymous, participant satisfaction survey tailored to participants enrolled in the DIAN-TU-001 double-blind clinical trial of solanezumab or gantenerumab and requested that all study sites share the survey with their trial participants. A total of 194 participants enrolled in the trial at 24 study sites. We utilized regression analysis to explore the link between participants' clinical trial experiences, their satisfaction, and their willingness to participate in upcoming trials. RESULTS: Survey responses were received over a sixteen-month window during 2020-2021 from 58 participants representing 15 study sites. Notably, 96.5% of the survey respondents expressed high levels of satisfaction with the trial, 91.4% would recommend trial participation, and 96.5% were willing to enroll again. Age, gender, and education did not influence satisfaction levels. Participants reported enhanced medical care (70.7%) and pride in contributing to the DIAN-TU trial (84.5%). Satisfaction with personnel and procedures was high (98.3%). Respondents had a mean age of 48.7 years, with most being from North America and Western Europe, matching the trial's demographic distribution. Participants' decisions to learn their genetic status increased during the trial, and most participants endorsed considering future trial participation regardless of the DIAN-TU-001 trial outcome. CONCLUSION: Results suggest that DIAN-TU-001 participants who responded to the survey exhibited high motivation to participate in research, overall satisfaction with the clinical trial, and willingness to participate in research in the future, despite a long trial duration of 4-7 years with detailed annual clinical, cognitive, PET, MRI, and lumbar puncture assessments. Implementation of features that alleviate barriers and challenges to trial participation is like to have a high impact on trial satisfaction and reduce participant burden.

Multiomics Blood-Based Biomarkers Predict Alzheimer's Predementia with High Specificity in a Multicentric Cohort Study.

BACKGROUND: The primary criteria for diagnosing mild cognitive impairment (MCI) due to Alzheimer's Disease (AD) or probable mild AD dementia rely partly on cognitive assessments and the presence of amyloid plaques. Although these criteria exhibit high sensitivity in predicting AD among cognitively impaired patients, their specificity remains limited. Notably, up to 25% of non-demented patients with amyloid plaques may be misdiagnosed with MCI due to AD, when in fact they suffer from a different brain disorder. The introduction of anti-amyloid antibodies complicates this scenario. Physicians must prioritize which amyloid-positive MCI patients receive these treatments, as not all are suitable candidates. Specifically, those with non-AD amyloid pathologies are not primary targets for amyloid-modifying therapies. Consequently, there is an escalating medical necessity for highly specific blood biomarkers that can accurately detect pre-dementia AD, thus optimizing amyloid antibody prescription. OBJECTIVES: The objective of this study was to evaluate a predictive model based on peripheral biomarkers to identify MCI and mild dementia patients who will develop AD dementia symptoms in cognitively impaired population with high specificity. DESIGN: Peripheral biomarkers were identified in a gene transfer-based animal model of AD and then validated during a retrospective multi-center clinical study. SETTING: Participants from 7 retrospective cohorts (US, EU and Australia). PARTICIPANTS: This study followed 345 cognitively impaired individuals over up to 13 years, including 193 with MCI and 152 with mild dementia, starting from their initial visits. The final diagnoses, established during their last assessments, classified 249 participants as AD patients and 96 as having non-AD brain disorders, based on the specific diagnostic criteria for each disorder subtype. Amyloid status, assessed at baseline, was available for 82.9% of the participants, with 61.9% testing positive for amyloid. Both amyloid-positive and negative individuals were represented in each clinical group. Some of the AD patients had co-morbidities such as metabolic disorders, chronic diseases, or cardiovascular pathologies. MEASUREMENTS: We developed targeted mass spectrometry assays for 81 blood-based biomarkers, encompassing 45 proteins and 36 metabolites previously identified in AAV-AD rats. METHODS: We analyzed blood samples from study participants for the 81 biomarkers. The B-HEALED test, a machine learning-based diagnostic tool, was developed to differentiate AD patients, including 123 with Prodromal AD and 126 with mild AD dementia, from 96 individuals with non-AD brain disorders. The model was trained using 70% of the data, selecting relevant biomarkers, calibrating the algorithm, and establishing cutoff values. The remaining 30% served as an external test dataset for blind validation of the predictive accuracy. RESULTS: Integrating a combination of 19 blood biomarkers and participant age, the B-HEALED model successfully distinguished participants that will develop AD dementia symptoms (82 with Prodromal AD and 83 with AD dementia) from non-AD subjects (71 individuals) with a specificity of 93.0% and sensitivity of 65.4% (AUROC=81.9%, p<0.001) during internal validation. When the amyloid status (derived from CSF or PET scans) and the B-HEALED model were applied in association, with individuals being categorized as AD if they tested positive in both tests, we achieved 100% specificity and 52.8% sensitivity. This performance was consistent in blind external validation, underscoring the model's reliability on independent datasets. CONCLUSIONS: The B-HEALED test, utilizing multiomics blood-based biomarkers, demonstrates high predictive specificity in identifying AD patients within the cognitively impaired population, minimizing false positives. When used alongside amyloid screening, it effectively identifies a nearly pure prodromal AD cohort. These results bear significant implications for refining clinical trial inclusion criteria, facilitating drug development and validation, and accurately identifying patients who will benefit the most from disease-modifying AD treatments.

Two-Year Prognostic Utility of Plasma p217+tau across the Alzheimer's Continuum.

BACKGROUND: Plasma p217+tau has shown high concordance with cerebrospinal fluid (CSF) and positron emission tomography (PET) measures of amyloid-ß (Aß) and tau in Alzheimer's Disease (AD). However, its association with longitudinal cognition and comparative performance to PET Aß and tau in predicting cognitive decline are unknown. OBJECTIVES: To evaluate whether p217+tau can predict the rate of cognitive decline observed over two-year average follow-up and compare this to prediction based on Aß (18F-NAV4694) and tau (18F-MK6240) PET. We also explored the sample size required to detect a 30% slowing in cognitive decline in a 2-year trial and selection test cost using p217+tau (pT+) as compared to PET Aß (A+) and tau (T+) with and without p217+tau pre-screening. DESIGN: A prospective observational cohort study. SETTING: Participants of the Australian Imaging, Biomarker and Lifestyle Flagship Study of Ageing (AIBL) and Australian Dementia Network (ADNeT). PARTICIPANTS: 153 cognitively unimpaired (CU) and 50 cognitively impaired (CI) individuals. MEASUREMENTS: Baseline p217+tau Simoa® assay, 18F-MK6240 tau-PET and 18F-NAV4694 Aß-PET with neuropsychological follow-up (MMSE, CDR-SB, AIBL-PACC) over 2.4 ± 0.8 years. RESULTS: In CI, p217+tau was a significant predictor of change in MMSE (ß = -0.55, p < 0.001) and CDR-SB (ß =0.61, p < 0.001) with an effect size similar to Aß Centiloid (MMSE ß = -0.48, p = 0.002; CDR-SB ß = 0.43, p = 0.004) and meta-temporal (MetaT) tau SUVR (MMSE: ß = -0.62, p < 0.001; CDR-SB: ß = 0.65, p < 0.001). In CU, only MetaT tau SUVR was significantly associated with change in AIBL-PACC (ß = -0.22, p = 0.008). Screening pT+ CI participants into a trial could lead to 24% reduction in sample size compared to screening with PET for A+ and 6-13% compared to screening with PET for T+ (different regions). This would translate to an 81-83% biomarker test cost-saving assuming the p217+tau test cost one-fifth of a PET scan. In a trial requiring PET A+ or T+, p217+tau pre-screening followed by PET in those who were pT+ would cost more in the CI group, compared to 26-38% biomarker test cost-saving in the CU. CONCLUSIONS: Substantial cost reduction can be achieved using p217+tau alone to select participants with MCI or mild dementia for a clinical trial designed to slow cognitive decline over two years, compared to participant selection by PET. In pre-clinical AD trials, p217+tau provides significant cost-saving if used as a pre-screening measure for PET A+ or T+ but in MCI/mild dementia trials this may add to cost both in testing and in the increased number of participants needed for testing.

Can We Use Blood Biomarkers as Entry Criteria and for Monitoring Drug Treatment Effects in Clinical Trials? A Report from the EU/US CTAD Task Force.

In randomized clinical trials (RCTs) for Alzheimer's Disease (AD), cerebrospinal fluid (CSF) and positron emission tomography (PET) biomarkers are currently used for the detection and monitoring of AD pathological features. The use of less resource-intensive plasma biomarkers could decrease the burden to study volunteers and limit costs and time for study enrollment. Blood-based markers (BBMs) could thus play an important role in improving the design and the conduct of RCTs on AD. It remains to be determined if the data available on BBMs are strong enough to replace CSF and PET biomarkers as entry criteria and monitoring tools in RCTs.

Axonal damage and astrocytosis are biological correlates of grey matter network integrity loss: a cohort study in autosomal dominant Alzheimer disease.

Brain development and maturation leads to grey matter networks that can be measured using magnetic resonance imaging. Network integrity is an indicator of information processing capacity which declines in neurodegenerative disorders such as Alzheimer disease (AD). The biological mechanisms causing this loss of network integrity remain unknown. Cerebrospinal fluid (CSF) protein biomarkers are available for studying diverse pathological mechanisms in humans and can provide insight into decline. We investigated the relationships between 10 CSF proteins and network integrity in mutation carriers (N=219) and noncarriers (N=136) of the Dominantly Inherited Alzheimer Network Observational study. Abnormalities in Aß, Tau, synaptic (SNAP-25, neurogranin) and neuronal calcium-sensor protein (VILIP-1) preceded grey matter network disruptions by several years, while inflammation related (YKL-40) and axonal injury (NfL) abnormalities co-occurred and correlated with network integrity. This suggests that axonal loss and inflammation play a role in structural grey matter network changes. Key points: Abnormal levels of fluid markers for neuronal damage and inflammatory processes in CSF are associated with grey matter network disruptions.The strongest association was with NfL, suggesting that axonal loss may contribute to disrupted network organization as observed in AD.Tracking biomarker trajectories over the disease course, changes in CSF biomarkers generally precede changes in brain networks by several years.

A Conformational Variant of p53 (U-p53AZ) as Blood-Based Biomarker for the Prediction of the Onset of Symptomatic Alzheimer's Disease.

BACKGROUND: Ongoing research seeks to identify blood-based biomarkers able to predict onset and progression of Alzheimer's disease (AD). OBJECTIVE: The unfolded conformational variant of p53 (U-p53AZ), previously observed in AD individuals, was evaluated in plasma samples from individuals participating in the Australian Imaging, Biomarkers and Lifestyle (AIBL) cohort for diagnostic and prognostic assessment, validated on a neuropsychological-based diagnosis, over the course of six years. DESIGN: Retrospective Longitudinal Prognostic biomarker study. SETTING: Single-center study based on the AIBL cohort. PARTICIPANTS: 482 participants of the AIBL cohort, aged 60-85 years, without uncontrolled diabetes, vascular disease, severe depression or psychiatric illnesses. MEASUREMENTS: The AlzoSure® Predict test, consisting of immunoprecipitation (IP) followed by liquid chromatography (LC) tandem mass spectrometry (MS/MS), was performed to quantify the AZ 284® peptide as readout of U-p53AZ and compared with an independent neuropsychological diagnosis. The amyloid load via amyloid ß-positron emission tomography (Aß-PET) and supporting clinical information were included where possible. RESULTS: U-p53AZ diagnostic and prognostic performance was assessed in both time-independent and time-dependent (36, 72 and 90 months following initial sampling) analyses. Prognostic performance of Aß-PET and survival analyses with different risk factors (gender, Aß-PET and APOE ε4 allele status) were also performed. U-p53AZ differentiated neuropsychologically graded AD from non-AD samples, and its detection at intermediate/high levels precisely identified present and future symptomatic AD. In both time-independent and time-dependent prognostic analyses U-p53AZ achieved area under the curve (AUC) >98%, significantly higher than Aß-PET AUCs (between 84% and 93%, P respectively <0.0001 and <0.001). As single factor, U-p53AZ could clearly determine the risk of AD neuropsychological diagnosis over time (low versus intermediate/high U-p53AZ hazard ratio=2.99). Proportional hazards regression analysis identified U-p53AZ levels as a major independent predictor of AD onset. CONCLUSIONS: These findings support use of U-p53AZ as blood-based biomarker predicting whether individuals would reach neuropsychologically-defined AD within six years prior to AD diagnosis. Integration of U-p53AZ in screening processes could support refined participant stratification for interventional studies.

Cerebrospinal fluid neurofilament light predicts the rate of executive function decline in younger-onset dementia.

INTRODUCTION: Determining disease severity and predicting prognosis in younger onset-dementia (YOD) remains challenging. Whether CSF biomarkers neurofilament light (NfL), tau and amyloidß 42 (Aß42) can help provide such information has been underexplored. METHODS: Patients with YOD and CSF analysis were identified. We compared baseline NfL, tau and Aß42 concentrations with contemporaneous Neuropsychiatry Unit Cognitive Assessment Tool (NUCOG) scores to assess their association with severity of cognitive impairment. Cognitive decline, as measured by longitudinal NUCOG assessment, was correlated against baseline biomarker levels to assess their utility in predicting the rate of cognitive decline. RESULTS: 78 patients with YOD (mean age = 56 years, SD = 8) and CSF analysis were identified. Dementia types included Alzheimer's disease, behavioural variant frontotemporal dementia, dementia not-otherwise-specified and other. Tau was associated with contemporaneous memory dysfunction (r = -0.556, 95% CI:[-0.702,-0.393], p < .001). 21 patients had longitudinal cognitive assessment up to 82 months from CSF sampling. NfL was associated with the rate of executive function decline (r = 0.755, 95% CI:[0.259,0.937], p < .001). Aß42 was associated with the rate of memory decline (r = -0.582, 95% CI:[-0.855,-0.274], p = .007) and rate of total NUCOG decline (r = -0.515, 95% CI: [-0.809, -0.227], p = .017). CONCLUSION: CSF tau is related to contemporaneous memory impairment in YOD. NfL and Aß42 levels are associated with the rate of executive function and memory decline, respectively, and may have a role in prognostication in YOD.

Association between Cognitive Function and Clustered Cardiovascular Risk of Metabolic Syndrome in Older Adults at Risk of Cognitive Decline.

OBJECTIVES: Metabolic syndrome (MetS) represents a cluster of obesity and insulin resistance-related comorbidities. Abdominal obesity, hypertension, elevated triglyceride and glucose levels are components of MetS and may have a negative effect on cognitive function, but few cognitive studies have examined the combined risk severity. We sought to determine which specific cognitive abilities were associated with MetS in older adults at risk of cognitive decline. DESIGN: Cross-sectional study. PARTICIPANTS: 108 AIBL Active participants with memory complaints and at least one cardiovascular risk factor. MEASUREMENTS: Cardiovascular parameters and blood tests were obtained to assess metabolic syndrome criteria. The factors of MetS were standardized to obtain continuous z-scores. A battery of neuropsychological tests was used to evaluate cognitive function. RESULTS: Higher MetS z-scores were associated with poorer global cognition using ADAS-cog (adjusted standardized beta=0.26, SE 0.11, p<0.05) and higher Trail Making B scores (adjusted beta=0.23, SE 0.11, p<0.05). Higher MetS risk was related to lower cognitive performance. CONCLUSION: Combined risk due to multiple risk factors in MetS was related to lower global cognitive performance and executive function. A higher MetS risk burden may point to opportunities for cognitive testing in older adults as individuals may experience cognitive changes.

Application of the NIA-AA Research Framework: Towards a Biological Definition of Alzheimer's Disease Using Cerebrospinal Fluid Biomarkers in the AIBL Study.

BACKGROUND: The National Institute on Aging and Alzheimer's Association (NIA-AA) have proposed a new Research Framework: Towards a biological definition of Alzheimer's disease, which uses a three-biomarker construct: Aß-amyloid, tau and neurodegeneration AT(N), to generate a biomarker based definition of Alzheimer's disease. OBJECTIVES: To stratify AIBL participants using the new NIA-AA Research Framework using cerebrospinal fluid (CSF) biomarkers. To evaluate the clinical and cognitive profiles of the different groups resultant from the AT(N) stratification. To compare the findings to those that result from stratification using two-biomarker construct criteria (AT and/or A(N)). DESIGN: Individuals were classified as being positive or negative for each of the A, T, and (N) categories and then assigned to the appropriate AT(N) combinatorial group: A-T-(N)-; A+T-(N)-; A+T+(N)-; A+T-(N)+; A+T+(N)+; A-T+(N)-; A-T-(N)+; A-T+(N)+. In line with the NIA-AA research framework, these eight AT(N) groups were then collapsed into four main groups of interest (normal AD biomarkers, AD pathologic change, AD and non-AD pathologic change) and the respective clinical and cognitive trajectories over 4.5 years for each group were assessed. In two sensitivity analyses the methods were replicated after assigning individuals to four groups based on being positive or negative for AT biomarkers as well as A(N) biomarkers. SETTING: Two study centers in Melbourne (Victoria) and Perth (Western Australia), Australia recruited MCI individuals and individuals with AD from primary care physicians or tertiary memory disorder clinics. Cognitively healthy, elderly NCs were recruited through advertisement or via spouses of participants in the study. PARTICIPANTS: One-hundred and forty NC, 33 MCI participants, and 27 participants with AD from the AIBL study who had undergone CSF evaluation using Elecsys® assays. INTERVENTION (if any): Not applicable. MEASUREMENTS: Three CSF biomarkers, namely amyloid ß1-42, phosphorylated tau181, and total tau, were measured to provide the AT(N) classifications. Clinical and cognitive trajectories were evaluated using the AIBL Preclinical Alzheimer Cognitive Composite (AIBL-PACC), a verbal episodic memory composite, an executive function composite, California Verbal Learning Test - Second Edition; Long-Delay Free Recall, Mini-Mental State Examination, and Clinical Dementia Rating Sum of Boxes scores. RESULTS: Thirty-eight percent of the elderly NCs had no evidence of abnormal AD biomarkers, whereas 33% had biomarker levels consistent with AD or AD pathologic change, and 29% had evidence of non-AD biomarker change. Among NC participants, those with biomarker evidence of AD pathology tended to perform worse on cognitive outcome assessments than other biomarker groups. Approximately three in four participants with MCI or AD had biomarker levels consistent with the research framework's definition of AD or AD pathologic change. For MCI participants, a decrease in AIBL-PACC scores was observed with increasing abnormal biomarkers; and increased abnormal biomarkers were also associated with increased rates of decline across some cognitive measures. CONCLUSIONS: Increasing biomarker abnormality appears to be associated with worse cognitive trajectories. The implementation of biomarker classifications could help better characterize prognosis in clinical practice and identify those at-risk individuals more likely to clinically progress, for their inclusion in future therapeutic trials.

Imaging of tau deposits in adults with Niemann-Pick type C disease: a case-control study.

PURPOSE: Niemann-Pick type C (NPC) is a cholesterol storage disease characterized by disruption in the endosomal-lysosomal transport system that leads to the accumulation of cholesterol and glycolipids in lysosomes. Developmental cognitive delay and progressive motor and cognitive impairment are characteristic of the disease. Tau accumulation has been reported in some NPC patients. We investigated the presence of tau and Aß-amyloid deposits in a group of NPC patients and for comparison in age-matched healthy controls (HC). METHODS: Eight NPC patients and seven HC were included in the study. Participants underwent tau imaging with 18F-AV1451 and amyloid imaging with 11C-PiB. Both 18F-AV1451 and 11C-PiB standardized uptake value ratios were generated using the cerebellar cortex as the reference region. Associations between imaging results, and clinical and neurocognitive parameters were assessed through nonparametric analyses. RESULTS: All participants were Aß-negative. Four NPC patients presented with high tau burden in the brain. A 21-year-old female patient and a 40-year-old male patient showed high neocortical tau burden in a pattern different from that observed in patients with Alzheimer's disease, while the same 40-year-old male patient, a 40-year-old female patient and a 50-year-old female patient showed high regional tau burden in the mesial temporal cortex. Spearman's correlation analysis showed an association between tau burden in the mesial temporal lobe and age (p = 0.022), and age at symptom onset (p = 0.009), and between frontotemporal tau and duration of symptoms (p = 0.027). There were no correlations between global and regional tau and cognitive parameters. CONCLUSION: Four of eight NPC patients showed tau deposition in the brain. The results of our exploratory study suggest that while tau deposits do not affect cognitive performance, tau deposits are associated with measures of disease onset and progression. Further studies in a larger cohort of NPC patients are needed to confirm these initial findings.

Reduced TRPC6 mRNA levels in the blood cells of patients with Alzheimer's disease and mild cognitive impairment.

Transient receptor potential canonical 6 (TRPC6) inhibits ß-amyloid (Aß) production. Hyperforin, the TRPC6 agonist, reduces Aß levels and improves cognitive performance in Alzheimer's disease (AD) models. However, it's unknown whether TRPC6 expression is changed in AD patients. In this case-control study, we measured TRPC6 expression levels in the peripheral blood cells of four independent AD sets from five hospitals and one mild cognitive impairment (MCI) set from a local community (229 AD, 70 MCI, 40 Parkinson disease and 359 controls from China, total n=698) using quantitative real-time PCR assay. We found a specific reduction of TRPC6 mRNA levels in four AD sets and one MCI set. The median TRPC6 mRNA levels were lower in the following: (1) combined AD patients than in age-matched controls (0.78 vs 1.73, P<0.001); (2) mild-to-moderate AD patients than in age-matched controls (0.81 vs 1.73, P<0.001); and (3) MCI patients than in age-matched controls (0.76 vs 1.72, P<0.001). In the receiver-operating characteristic curve analysis, the area under curve was 0.85 for combined AD, 0.84 for mild-to-moderate AD and 0.79 for MCI. In a subgroup of AD patients with brain Aß examination, TRPC6 was associated with standardized uptake value ratio of Pittsburgh Compound B (Spearman's r=-0.49, P=0.04) and cerebrospinal fluid Aß42 (Spearman's r=0.43, P=0.04). The TRPC6 reduction in AD patients was further confirmed in blood RNA samples from The Australian Imaging, Biomarkers and Lifestyle Flagship Study of Aging, in post-mortem brain tissues from The Netherlands Brain Bank and in induced pluripotent stem cells-derived neurons from Chinese donors. We conclude that TRPC6 mRNA levels in the blood cells are specifically reduced in AD and MCI patients, and TRPC6 might be a biomarker for the early diagnosis of AD.

Sulfotransferase 1A3/4 copy number variation is associated with neurodegenerative disease.

The cytosolic aryl sulfotransferase genes SULT1A3 and SULT1A4 are located on chromosome 16p11.2 in a region of chromosomal instability. SULT1A3/4 are important enzymes in the metabolism of catecholamines linked to neurodegenerative diseases such as Parkinson's and Alzheimer's. In the present study, copy number variation of the SULT1A3/4 genes in healthy individuals, as well as a cohort of Parkinson's disease and Alzheimer's disease patients was examined. In all subjects, SULT1A3/4 copy number varied from 1 to 10. In Alzheimer's disease patients, there was a significantly lower copy number compared to controls, and a positive correlation between copy number and age of disease onset. By contrast, there were no differences in Parkinson's disease patients. However, when early-onset Parkinson's disease was evaluated separately, there appeared to be an association with gene copy number and risk. The current study shows that these neurodegenerative diseases may be related to SULT1A3/4 copy number.

APOE and BDNF polymorphisms moderate amyloid ß-related cognitive decline in preclinical Alzheimer's disease.

Accumulation of ß-amyloid (Aß) in the brain is associated with memory decline in healthy individuals as a prelude to Alzheimer's disease (AD). Genetic factors may moderate this decline. We examined the role of apolipoprotein E (ɛ4 carrier[ɛ4(+)], ɛ4 non-carrier[ɛ4(-)]) and brain-derived neurotrophic factor (BDNF(Val/Val), BDNF(Met)) in the extent to which they moderate Aß-related memory decline. Healthy adults (n=333, Mage=70 years) enrolled in the Australian Imaging, Biomarkers and Lifestyle study underwent Aß neuroimaging. Neuropsychological assessments were conducted at baseline, 18-, 36- and 54-month follow-ups. Aß positron emission tomography neuroimaging was used to classify participants as Aß(-) or Aß(+). Relative to Aß(-)ɛ4(-), Aß(+)ɛ4(+) individuals showed significantly faster rates of cognitive decline over 54 months across all domains (d=0.40-1.22), while Aß(+)ɛ4(-) individuals showed significantly faster decline only on verbal episodic memory (EM). There were no differences in rates of cognitive change between Aß(-)ɛ4(-) and Aß(-)ɛ4(+) groups. Among Aß(+) individuals, ɛ4(+)/BDNF(Met) participants showed a significantly faster rate of decline on verbal and visual EM, and language over 54 months compared with ɛ4(-)/BDNF(Val/Val) participants (d=0.90-1.02). At least two genetic loci affect the rate of Aß-related cognitive decline. Aß(+)ɛ4(+)/BDNF(Met) individuals can expect to show clinically significant memory impairment after 3 years, whereas Aß(+)ɛ4(+)/BDNF(Val/Val) individuals can expect a similar degree of impairment after 10 years. Little decline over 54 months was observed in the Aß(-) and Aß(+) ɛ4(-) groups, irrespective of BDNF status. These data raise important prognostic issues in managing preclinical AD, and should be considered in designing secondary preventative clinical trials.

Prognostic serum miRNA biomarkers associated with Alzheimer's disease shows concordance with neuropsychological and neuroimaging assessment.

There is no consensus for a blood-based test for the early diagnosis of Alzheimer's disease (AD). Expression profiling of small non-coding RNA's, microRNA (miRNA), has revealed diagnostic potential in human diseases. Circulating miRNA are found in small vesicles known as exosomes within biological fluids such as human serum. The aim of this work was to determine a set of differential exosomal miRNA biomarkers between healthy and AD patients, which may aid in diagnosis. Using next-generation deep sequencing, we profiled exosomal miRNA from serum (N=49) collected from the Australian Imaging, Biomarkers and Lifestyle Flagship Study (AIBL). Sequencing results were validated using quantitative reverse transcription PCR (qRT-PCR; N=60), with predictions performed using the Random Forest method. Additional risk factors collected during the 4.5-year AIBL Study including clinical, medical and cognitive assessments, and amyloid neuroimaging with positron emission tomography were assessed. An AD-specific 16-miRNA signature was selected and adding established risk factors including age, sex and apolipoprotein ɛ4 (APOE ɛ4) allele status to the panel of deregulated miRNA resulted in a sensitivity and specificity of 87% and 77%, respectively, for predicting AD. Furthermore, amyloid neuroimaging information for those healthy control subjects incorrectly classified with AD-suggested progression in these participants towards AD. These data suggest that an exosomal miRNA signature may have potential to be developed as a suitable peripheral screening tool for AD.

Dietary patterns and cognitive decline in an Australian study of ageing.

The aim of this paper was to investigate the association of three well-recognised dietary patterns with cognitive change over a 3-year period. Five hundred and twenty-seven healthy participants from the Australian Imaging, Biomarkers and Lifestyle study of ageing completed the Cancer Council of Victoria food frequency questionnaire at baseline and underwent a comprehensive neuropsychological assessment at baseline, 18 and 36 months follow-up. Individual neuropsychological test scores were used to construct composite scores for six cognitive domains and a global cognitive score. Based on self-reported consumption, scores for three dietary patterns, (1) Australian-style Mediterranean diet (AusMeDi), (2) western diet and (3) prudent diet were generated for each individual. Linear mixed model analyses were conducted to examine the relationship between diet scores and cognitive change in each cognitive domain and for the global score. Higher baseline adherence to the AusMeDi was associated with better performance in the executive function cognitive domain after 36 months in apolipoprotein E (APOE) ɛ4 allele carriers (P<0.01). Higher baseline western diet adherence was associated with greater cognitive decline after 36 months in the visuospatial cognitive domain in APOE ɛ4 allele non-carriers (P<0.01). All other results were not significant. Our findings in this well-characterised Australian cohort indicate that adherence to a healthy diet is important to reduce risk for cognitive decline, with the converse being true for the western diet. Executive function and visuospatial functioning appear to be particularly susceptible to the influence of diet.

Voyage au bout de la nuit: Aß and tau imaging in dementias.

The last decade has witnessed the development and characterization of tracers for the evaluation of neuropathology in vivo. The introduction of these tracers, namely ß-amyloid (Aß) and later tau, are providing the tools to change the landscape and refine our understanding of Aß and tau deposition in the brain, allowing to investigate the causes, refine diagnosis and improve treatment of major neurodegenerative conditions such as Alzheimer's disease (AD), chronic traumatic encephalopathy (CTE) and frontotemporal lobar degeneration (FTLD). Aß and tau imaging allow examination of the regional and global changes of these disease markers over time as well as their relationship with other relevant parameters such as cognitive performance and neurodegenerative changes. Aß and tau imaging will enable to establish the role Aß and tau play -and interplay- in aging and disease. Aß and tau imaging value resides in being not only diagnostic, prognostic or progression markers, but also surrogate markers of disease, crucial for patient recruitment and efficacy evaluation of disease-specific therapies.

An anemia of Alzheimer's disease.

Lower hemoglobin is associated with cognitive impairment and Alzheimer's disease (AD). Since brain iron homeostasis is perturbed in AD, we investigated whether this is peripherally reflected in the hematological and related blood chemistry values from the Australian Imaging Biomarker and Lifestyle (AIBL) study (a community-based, cross-sectional cohort comprising 768 healthy controls (HC), 133 participants with mild cognitive impairment (MCI) and 211 participants with AD). We found that individuals with AD had significantly lower hemoglobin, mean cell hemoglobin concentrations, packed cell volume and higher erythrocyte sedimentation rates (adjusted for age, gender, APOE-ɛ4 and site). In AD, plasma iron, transferrin, transferrin saturation and red cell folate levels exhibited a significant distortion of their customary relationship to hemoglobin levels. There was a strong association between anemia and AD (adjusted odds ratio (OR)=2.43, confidence interval (CI) (1.31, 4.54)). Moreover, AD emerged as a strong risk factor for anemia on step-down regression, even when controlling for all other available explanations for anemia (adjusted OR=3.41, 95% CI (1.68, 6.92)). These data indicated that AD is complicated by anemia, which may itself contribute to cognitive decline.

Associations between gonadotropins, testosterone and ß amyloid in men at risk of Alzheimer's disease.

Testosterone and gonadotropins have been associated with cognitive decline in men and the modulation of ß amyloid (Aß) metabolism. The relatively few studies that have investigated whether changes in one or a combination of these hormones influence Aß levels have focused primarily on plasma Aß(1-40) and not on the more pathogenic Aß(1-42). Currently, no study has investigated whether these hormones are associated with an increase in brain amyloid deposition, ante mortem. Through the highly characterised Australian imaging, biomarkers and lifestyle study, we have determined the impact of these hormones on plasma Aß levels and brain amyloid burden (Pittsburgh compound B (PiB) retention). Spearman's rank correlation and linear regression analysis was carried out across the cohort and within subclassifications. Luteinizing hormone (LH) was the only variable shown, in the total cohort, to have a significant impact on plasma Aß(1-40) and Aß(1-42) levels (beta=0.163, P<0.001; beta=0.446, P<0.001). This held in subjective memory complainers (SMC) (Aß(1-40); beta=0.208, P=0.017; Aß(1-42); beta=0.215, P=0.017) but was absent in mild cognitive impairment (MCI) and Alzheimer's disease (AD) groups. In SMC, increased frequency of the APOE-ɛ4 allele (beta=0.536, P<0.001) and increasing serum LH levels (beta=0.421, P=0.004) had a significant impact on PiB retention. Whereas in MCI, PiB retention was associated with increased APOE-ɛ4 allele copy number (beta=0.674, P<0.001) and decreasing calculated free testosterone (beta=-0.303, P=0.043). These findings suggest a potential progressive involvement of LH and testosterone in the early preclinical stages of AD. Furthermore, these hormones should be considered while attempting to predict AD at these earliest stages of the disease.

A blood-based predictor for neocortical Aß burden in Alzheimer's disease: results from the AIBL study.

Dementia is a global epidemic with Alzheimer's disease (AD) being the leading cause. Early identification of patients at risk of developing AD is now becoming an international priority. Neocortical Aß (extracellular ß-amyloid) burden (NAB), as assessed by positron emission tomography (PET), represents one such marker for early identification. These scans are expensive and are not widely available, thus, there is a need for cheaper and more widely accessible alternatives. Addressing this need, a blood biomarker-based signature having efficacy for the prediction of NAB and which can be easily adapted for population screening is described. Blood data (176 analytes measured in plasma) and Pittsburgh Compound B (PiB)-PET measurements from 273 participants from the Australian Imaging, Biomarkers and Lifestyle (AIBL) study were utilised. Univariate analysis was conducted to assess the difference of plasma measures between high and low NAB groups, and cross-validated machine-learning models were generated for predicting NAB. These models were applied to 817 non-imaged AIBL subjects and 82 subjects from the Alzheimer's Disease Neuroimaging Initiative (ADNI) for validation. Five analytes showed significant difference between subjects with high compared to low NAB. A machine-learning model (based on nine markers) achieved sensitivity and specificity of 80 and 82%, respectively, for predicting NAB. Validation using the ADNI cohort yielded similar results (sensitivity 79% and specificity 76%). These results show that a panel of blood-based biomarkers is able to accurately predict NAB, supporting the hypothesis for a relationship between a blood-based signature and Aß accumulation, therefore, providing a platform for developing a population-based screen.

Factors affecting subjective memory complaints in the AIBL aging study: biomarkers, memory, affect, and age.

BACKGROUND: The prognostic value of subjective memory complaints (SMCs) in the diagnosis of dementia of the Alzheimer's type is unclear. While some studies have found an association between SMCs and cognitive decline, many have found a stronger association with depression, which raises questions about their diagnostic utility. METHODS: We examined the cross-sectional association between SMC severity (as measured using the MAC-Q, a brief SMC questionnaire) and affect, memory, and Alzheimer's disease (AD) biomarkers (ß-amyloid deposition and the apolipoprotein E ε4 (APOEε4) allele) in healthy elderly controls (HC; M = 78.74 years, SD = 6.7) and individuals with mild cognitive impairment (MCI; M = 72.74 years, SD = 8.8). We analyzed a subset of individuals drawn from the Australian Imaging Biomarkers and Lifestyle (AIBL) Study of Aging. RESULTS: SMCs were more severe in MCI patients than in HCs. SMC severity was related to affective variables and the interaction between age and group membership (HC/MCI). Within the HC group, SMC severity was related to affective variables only, while severity correlated only with age in the MCI group. SMCs were not related to cognitive variables or AD biomarkers. CONCLUSION: SMCs were related to solely by poorer mood (greater depressive and anxious symptomatology) in the cognitively healthy elderly however mean levels were subclinical. This finding argues for the assessment of affective symptomatology in conjunction with cognitive assessment in elderly memory complainers. Future AIBL research will focus on assessing other AD biomarkers, such as brain atrophy and Aß plasma markers, in relation to complaint severity. Once our 36-month follow-up data are collected, we propose to assess whether SMCs can predict future cognitive decline.