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Blood Based Biomarkers of Risk for Alzheimer’s D isease among Adults with Down syndrome

This study explores the identification of preclinical blood-based biomarkers for the early detection and prediction of Alzheimer's disease (AD) in adults with Down syndrome (DS), who are at high risk for developing AD. Proteomic profiles were examined to identify proteins associated with increased risk of mild cognitive impairment (MCI) and AD. The study found that blood-based profiles, particularly inflammatory markers, may have utility in predicting the onset of MCI and AD in adults with DS.

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Blood Based Biomarkers of Risk for Alzheimer’s D isease among Adults with Down syndrome

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  1. Blood Based Biomarkers of Risk for Alzheimer’s Disease among Adults with Down syndrome Nicole Schupf. Ph.D. Columbia University Medical Center

  2. Dementia Risk in Adults with Down Syndrome. • Adults with Down syndrome are at high risk for early onset of Alzheimer’s Disease • Virtually all adults with DS have neuropathological changes consistent with AD, including deposition of Aβ in diffuse and neuritic plaques, by 40 years of age • Most will develop clinical dementiaby their late 60s

  3. Neuropathological changes: Neuritic Plaques

  4. Neuropathological changes: Neurofibrillary Tangles

  5. Increased Risk of Dementia in Adults with DS • Attributed, in part, to triplication and overexpression of amyloid precursor protein (APP) on chromosome 21, leading to elevated levels of Aβ peptides. • However: --There large individual differences in Aβ peptide levels; -- There is wide range of dementia onset age and a substantial proportion main their abilities even at older ages despite extensive neuropathology --- Our study sought to identify preclinical blood based biomarkers of risk to identify those most likely to develop dementia

  6. Cumulative Incidence of Alzheimer's Disease in Adults with DS and the General Population Cumulative Incidence Age

  7. Blood Based Preclinical Biomarkers • Identifying preclinical biomarkers of risk and determining which individuals with DS are at the highest risk: (a) can provide insights into AD pathogenesis in adults with DS, (b) are critical to the early identification of MCI and dementia risk, and (c) can guide the development of effective intervention. (d) While cerebrospinal fluid (CSF) and positron emission tomography (PET) scan biomarkers are accurate in detecting AD pathology, they are invasive and not cost-effective

  8. Proteomic Profiles • Prior work from Dr. O’Bryant’s lab has validated a profile of proteins for detecting MCI and AD in the general population, across cohorts, assay technologies, species and tissue. • Here we examined the utility of our previous profile for predicting the development of MCI and AD among a cohort of adults with DS

  9. Classification of clinical status • Dementia classification was made based upon consensus case conferences relying on evidence of stability or decline in cognitive and functional performance profiles over time • Individuals were classified as: • No Dementia: No cognitive or functional decline • Mild Cognitive impairment: indications of cognitive and/or functional declines are present but severity or breadth is insufficient to indicate presence of dementia • Possible Dementia: some signs and symptoms of decline in cognitive and functional status were present, but evidence of progressive decline over an extended period of time is limited • Definite Dementia: based upon substantial decline in cognitive and functional status over time

  10. Aging and Dementia in Adults with DS cohort : Participant Characteristics: • N=356 • non-demented; n=273 • Incident dementia; n=83 • Incident MCI; n = 101 • Mean age at blood draw 51.4 (sd=7.1, 31-78) • Female n=266 • Male n=133 • Up to 10 years of follow-up

  11. Proteomic risk scores for MCI and AD • Proteomics were conducted on banked plasma samples via electrochemiluminescence from a previously generated algorithm. Support vector machine (SVM) analyses were utilized to create proteomic risk scores • We identified high/low cut-points scores for incident MCI and incident AD. • Cox proportional hazards modeling examined the relation of the proteomic cut-scores to onset of MCI and AD, adjusting for age, sex, level of function, race/ethnicity and the APOEE4 allele.

  12. Baseline characteristics for Incident MCI Baseline characteristics for incident MCI * P < .05

  13. Cumulative Incidence of MCI High Low HR = 7.09* *Adjusted for age at blood draw, sex, level of intellectual disability and APOE E4

  14. Baseline characteristics for incident AD Baseline for incident AD * P < .05

  15. Cumulative Incidence of AD by risk score with time since blood draw as the time to event variable. Cumulative Incidence of AD High Low HR=11.29* *Adjusted for age at blood draw, sex, level of intellectual disability and APOE E4

  16. Comparison of general population profile with profile of MCI and AD in adults with DS Plasma AD Profile in non-Hispanic Whites Plasma Profile of Incident MCI in Down Syndrome – 8 of top 10 markers overlap Plasma Profile of Incident AD in Down Syndrome – 7 of top 10 markers overlap

  17. Predictors • The top 10 proteins associated with increased risk of MCI included IL6,CRP, l309, slCAM1, IL10, SAA, TPO, PPY, TenacinC, TARC • The top 10 markers associated with increased risk of AD included IL6,CRP, l309, slCAM1, IL10, SAA, TPO, PPY, TenacinC, TARC • It is noteworthy that the profiles were heavily weighted towards inflammatory markers for both MCI-DS and AD

  18. Summary and Conclusions • These results support the possibility of blood based profiles having utility in predicting onset of MCI and AD among adults with DS • Inflammatory processes have been linked to the pathogenesis of Alzheimer’s disease and neuropsychiatric symptoms . A number of pro- and anti-inflammatory markers have been related to neuropsychiatric symptoms and functional level in aging and Alzheimer’s disease including TNFα ,IL-1 IL-6 IL-7 IL-10 , IL-15 and IL-18 • it is possible that the proinflammatory biomarker profile will identify a specific subset of adults with DS where anti-inflammatory interventions, as a part of multi-modal therapy, may be of particular use • We are extending these analyses and relating them to imaging (MRI, PET), metabolomic and genetic biomarkers in our new study of Biomarkers of Alzheimer's disease in Adults with Down Syndrome (ADDS), which is part of the Alzheimer’s Biomarkers Consortium- Down Syndrome (ABC-DS) funded by the NIA and NICHD

  19. Acknowledgements • Co-investigators: , Fan Zhang, Joseph H. Lee, Sharon J. Krinsky-McHale, Deborah Pang, Warren B. Zigman, Wayne Silverman, James Hall and Sid O’Bryant • Supported by grant IIRG-08-90655 from the Alzheimer's Association (Schupf, O’Bryant), by grants P01HD035897 (Silverman) from NICHD, R01AG014673 (Schupf) from NIA, and by NYS through its Office for People with Developmental Disabilities. • We thank the study participants and participating agencies from the tri-state area that made these studies possible

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