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Paul Morgan, Angharad Morgan, Caroline O’Hagan, Samuel Touchard

Wellcome Trust Consortium for Neuroimmunology of Mood Disorders and Alzheimer’s Disease work package 3: immune system biomarkers in AD progress update. Paul Morgan, Angharad Morgan, Caroline O’Hagan, Samuel Touchard. 14 September 2015. Study design. Initial focus on complement biomarkers

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Paul Morgan, Angharad Morgan, Caroline O’Hagan, Samuel Touchard

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  1. Wellcome Trust Consortium for Neuroimmunology of Mood Disorders and Alzheimer’s Diseasework package 3: immune system biomarkers in ADprogress update Paul Morgan, Angharad Morgan, Caroline O’Hagan, Samuel Touchard 14 September 2015

  2. Study design • Initial focus on complement biomarkers • Include other relevant biomarkers of inflammation • Include relevant biomarkers of the underlying pathology - Abeta. Tau, TREM-2 etc • Link to structural imaging, genetics and other available datasets • Aim to arrive at best set of markers for defined purpose.

  3. Study design • AD versus control • MCI versus control • MCI progression to AD versus non-progressors • MCI/AD correlation/prediction of rate of decline • Add value to structural imaging • Likely different marker sets for different studies.

  4. Methods • ELISA • All assays start out as ELISA to test best reagents and establish ranges for multiplex • Some analytes will stay as ELISA at least in early studies (cost and time) • MSD • Sensitivity: 10-100 fold increase in sensitivity compared to ELISA; detection of analytes at low picogram/ml levels • Dynamic Range: 3-4 log dynamic range vs. 1-2 log range for ELISA (IMPORTANT!) • Accuracy: established assays have low CVs compaers to ELISA • Reduced Sample Volume: 5-25 ul volume vs. 50-100 ul for ELISA • Speed: The entire assay can be performed in 3 hours • Develop as singleplex, combine singleplexes to ensure no cross-talk • Multiplex - measurements for up to 10 analytes/well (6 practical).

  5. Assays ready to run in Cardiff MSD (printing sets at moment) Assay set 1: C3, C4, C5, FH, FB, FI Assay set 2: C5a, TCC, Bb, C3a, iC3b, fD ELISA (developed or in final stages) Properdin, FHR, C1INH, CR1, CR2, C1q, CLU*, C9* Variant-specific (complotype) FHY402H, FBR32Q, C3R102G

  6. Samples Total = 1147 ADC = 367, MCI =268, CTL =512 Dementia case register n=427 Addneuromed n=720 Available data: - Demographics - Cognitive measures - MRI data - Proteomics data

  7. Complement • The complement system is a pivotal part of the immune system and inflammatory processes. • Depending on the trigger, complement can be activated via the classical, alternative, or lectin pathways. • All three pathways culminate in the formation of complement convertases, which results in the proteolytic cleavage of C3 and, later in the cascade, C5. • The resulting active fragments act as proinflammatory and chemotactic anaphylatoxins, opsonins allowing phagocytosis, or anchors for the assembly of the membrane attack complex. • The complement system is kept under tight control by soluble and membrane-bound regulators, including factor H, which inhibits C3 convertases in the alternative pathway, and complement 1 inhibitor, which inhibits several proteases of the classical and lectin pathways. • The final outcome therefore depends on the balance between complement activation and inhibition, and dysregulation of this balance may contribute to neuroinflammation and disease.

  8. Complement activation has been shown to occur in the AD brain, even at very early stages of the disease • Genome-wide association studies have identified AD-associated variants in complement pathway genes • Data from pathway analysis indicates immune system and complement to be important in AD Jones et al. (2010) Genetic evidence implicates the immune system and cholesterol metabolism in the aetiology of Alzheimer's disease. PLoS One 5(11), e13950. Lambert et al. Implication of the immune system in Alzheimer’s disease: evidence from genome-wide pathway analysis. J. Alzheimers Dis. 2010; 20:1107–1118. International Genomics of Alzheimer's Disease Consortium IGAP. (2015) Convergent genetic and expression data implicate immunity in Alzheimer's disease. Alzheimers Dement. 11(6):658-71.

  9. Literature review_1genes

  10. IGAP GWAS (Lambert et al., 2013) • Data suggested major pathway involved in AD: Immune response and inflammation (HLA-DRB5–DRB1, INPP5D and MEF2C) • Complement genes • CLU • CR1 • CR2 • C1s • C1r • CR1L CR1 levels have been associated with a number of inflammatory conditions. Only 1 study in AD: elevated CSF levels of CR1 in AD (Daborg et al., 2012) CR2 has been measured in inflammatory conditions such as arthritis, systemic sclerosis, systemic lupus erythematosus, Sjogren's syndrome and has been found to be reduced in these conditions compared to controls. No studies in AD. CLU protein levels have previously been shown to be associated with AD

  11. TREM2 • Rare variants in TREM2 gene increase susceptibility to AD, with an odds ratio similar to that of ApoE4 • The encoded protein functions in immune response and may be involved in chronic inflammation by triggering the production of constitutive inflammatory cytokines • TREM2 expression is upregulated in the brain of patients with AD • Measurement of TREM2 protein levels in CSF reported at Alzheimer's Association International Conference 2015 - 2 studies, both reported increased TREM2 in AD CSF

  12. Literature review_2proteins

  13. Complement proteins_1 • Thambisetty et al., 2011 performed a proteomic analysis of plasma to derive biomarkers associated with brain atrophy in AD • Plasma concentrations of five proteins, together with age and sex, explained more than 35% of variance in whole brain volume in AD patients • complement component C3 • complement activation fragment C3a • Complement regulator FI • c-fibrinogen • alpha-1-microglobulin

  14. Complement proteins_2 • Systematic review of candidate biomarkers for AD in serum (Zabel et al., 2012) • 25 cross-sectional, proteomic serum and plasma-based biomarker studies • Identification of 18 candidate protein biomarkers • Several proteins involved in the complement cascade were found in the serum of AD patients (C3, C4 C1INH, FH, clusterin)

  15. Complement proteins_3 • Muenchhoff et al., 2015 compared the plasma protein profiles of MCI, AD, and cognitively normal control subjects from two independent cohorts • Plasma proteins in complement that showed significantly different levels: • C4BPA C4b-binding protein alpha chain • CFH complement factor H • CFB complement factor B • SERPING1 plasma protease C1 inhibitor

  16. cytokines • Meta-analysis of cytokines in AD (Swardfager et al., 2010) • Forty studies measuring peripheral blood cytokine concentrations • Higher peripheral concentrations of IL-6, TNF-α, IL-1β, TGF-β, IL-12 and IL-18 in AD subjects compared with control subjects.

  17. biomarker signature • Ray et al., 2007 established an 18-marker blood plasma-based test to differentiate those with AD from those with normal cognition, with an overall accuracy of 89% • This work was built on by O’Bryant and colleagues who examined the implications of using plasma-based biomarkers to create an algorithm to detect AD presence and generated a blood test based profile consisting of 21 plasma proteins, which yielded an accuracy of 96% in distinguishing those with AD from those with normal cognition (O’Bryant et al., 2014) • The top five plasma proteins included in this blood-test were; interleukin 5 (IL-5), IL-6, IL-7, tumor necrosis factor-alpha (TNF-a), and C-reactive protein (CRP) • Combining two of the top five biomarkers (TNF-a and IL-7) with one neuropsychological measure (Clock 4-point), yielded excellent accuracy in detecting early AD (Edwards et al., 2014)

  18. Preliminary study in Cardiff • C1S C9 CLU FI FH C4d TCC iC3B • First visit sample • Association for diagnosis AD V control: CLU only sig • MCI conversion: CLU TCC FI

  19. Timescale • Ready to go with large panel of ELISA and singleplex MSD assays; • Currently measuring unrelated samples to develop skills (and generate data); • Multiplex sets 1 and 2 currently printing, available next month, sufficient for ~1600 patient samples; • Now need best sample sets to get optimal data to permit focus on fewer analytes in a (single) multiplex for future studies. • MSD progression/non-progression is key question.

  20. Future work_1 Additional biomarkers to consider: Complement: • C1s • C1r • CR1L Pathology markers: • TREM 2 Cytokines: • IL5 • IL6 • IL7 • TNFalpha • CRP • IL-1 beta • TGF-beta • IL-12 • IL-18 Chemokines: CXCL8, CCL2, CCL3, CCL5 MMPs: MMP-2, MMP-9, MMP-3, MMP-14 TACE TIMP-1, TIMP-2

  21. Future work_2 New samples from EMIF catalogue • Longtitudinal samples - measure biomarker levels at several time points • Stable AD versus rapidly declining AD • MCI progressors/non-progressors • Others? • NSAIDs and other interventions? • Development of algorithms to select marker sets.

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