Alzheimers disease (AD) will become a public health crisis in the very near future if left untreated. There are currently no proven treatments that delay the onset or prevent the progression of AD, although several promising candidates are being tested. During therapy development, it will be critical to have biomarkers that identify individuals at high risk for AD in order to target them for clinical trials and to monitor therapy. Autosomal-dominant AD (ADAD) accounts for a very small proportion of all AD cases (<1%) but the neuropathologic hallmarks and clinical features are similar to the more common sporadic, late-onset form (LOAD). Individuals possessing AD mutations are destined to develop the disease and at a relatively predictable age, thus providing a unique cohort in which to investigate the trajectories/timing of underlying AD pathologies, especially in the preclinical/pre-symptomatic stage. During the initial funding period of DIAN, the Biomarker Core analyzed CSF and plasma samples obtained from participants at baseline, including mutation carriers and non-carriers that fell along a wide spectrum of estimated years to symptomatic onset (EYO). Cross-sectional analyses revealed elevated CSF tau and ptau181, markers of neurodegeneration and/or neurofibrillary tangles, ~15 years prior to the estimated age of symptomatic onset (EAO) (EYO -15). Low levels of CSF A1-42, a marker of amyloid plaques, were observed in carriers ~10 years prior to EAO, but levels appeared to decline much earlier (EYO -25) from levels initially higher than non-carriers. More recent data in DIAN demonstrate the same pattern of elevations in CSF VILIP-1, a tauindependent marker of neurodegeneration, as participants approach their EAO. While these patterns are consistent with what has been reported in cross-sectional studies of LOAD, the trajectory of biomarker changes within individuals as they progress through the disease process is uncertain. With DIAN now evolved to the point of collecting longitudinal samples, we are poised to be able to address this important question. Such information will be critical for the design and evaluation of clinical trials intended to prevent the onset of cognitive decline in at-risk individuals. In the present renewal application, we will build upon our success by:
Aim 1) Maintaining and growing the biorepository of DIAN plasma and CSF samples and coordinating the distribution of samples to qualified investigators for approved studies;
Aim 2) Obtaining fluid analyte measures for evaluation in DIAN crosssectional analyses (including plasma A1-40, Ax-40, A1-42 and Ax-42, CSF A1-42, total tau, and ptau181, and 2 novel biomarker candidates that show robust diagnostic/prognostic utility in LOAD (VILIP-1 and tau seeding activity);and given the critical importance of within-participant analyses in the setting of a biomarker field challenged by limitations in assay stability and reproducibility, Aim 3) Developing and implementing procedures for analysis of longitudinal fluid samples, including analytical protocols and quality control testing.
There are currently no effective treatments that will prevent Alzheimers disease, halt its progression, or delay symptom onset, although several therapeutic approaches are being developed. Elucidating the timing and trajectories of pathology-related biomarkers will aid in disease diagnosis and prognosis and assessing disease risk, especially during the preclinical/asymptomatic period believed to offer the most promise for therapeutic efficacy.
|Lim, Yen Ying; Hassenstab, Jason; Goate, Alison et al. (2018) Effect of BDNFVal66Met on disease markers in dominantly inherited Alzheimer's disease. Ann Neurol 84:424-435|
|Suárez-Calvet, Marc; Capell, Anja; Araque Caballero, Miguel Ángel et al. (2018) CSF progranulin increases in the course of Alzheimer's disease and is associated with sTREM2, neurodegeneration and cognitive decline. EMBO Mol Med 10:|
|Besser, Lilah; Kukull, Walter; Knopman, David S et al. (2018) Version 3 of the National Alzheimer's Coordinating Center's Uniform Data Set. Alzheimer Dis Assoc Disord 32:351-358|
|Kinnunen, Kirsi M; Cash, David M; Poole, Teresa et al. (2018) Presymptomatic atrophy in autosomal dominant Alzheimer's disease: A serial magnetic resonance imaging study. Alzheimers Dement 14:43-53|
|Lee, Seonjoo; Zimmerman, Molly E; Narkhede, Atul et al. (2018) White matter hyperintensities and the mediating role of cerebral amyloid angiopathy in dominantly-inherited Alzheimer's disease. PLoS One 13:e0195838|
|Xiong, Chengjie; Luo, Jingqin; Chen, Ling et al. (2018) Estimating diagnostic accuracy for clustered ordinal diagnostic groups in the three-class case-Application to the early diagnosis of Alzheimer disease. Stat Methods Med Res 27:701-714|
|Karch, Celeste M; Hernández, Damián; Wang, Jen-Chyong et al. (2018) Human fibroblast and stem cell resource from the Dominantly Inherited Alzheimer Network. Alzheimers Res Ther 10:69|
|Day, Gregory S; Gordon, Brian A; Perrin, Richard J et al. (2018) In vivo [18F]-AV-1451 tau-PET imaging in sporadic Creutzfeldt-Jakob disease. Neurology 90:e896-e906|
|Oxtoby, Neil P; Young, Alexandra L; Cash, David M et al. (2018) Data-driven models of dominantly-inherited Alzheimer's disease progression. Brain 141:1529-1544|
|Chhatwal, Jasmeer P; Schultz, Aaron P; Johnson, Keith A et al. (2018) Preferential degradation of cognitive networks differentiates Alzheimer's disease from ageing. Brain 141:1486-1500|
Showing the most recent 10 out of 59 publications