pathology in neurodegenerative disease Susan M Landau, PhD Helen - PowerPoint PPT Presentation

PET neuroimaging approaches to characterizing underlying molecular pathology in neurodegenerative disease Susan M Landau, PhD Helen Wills Neuroscience Institute University of California, Berkeley Lawrence Berkeley National Lab

Disclosures Cortexyme NeuroVision

Overview Detection of b -amyloid (A b ) and tau pathology in Alzheimer’s disease Time course of changes Regional specificity NIA-AA Research Framework Practical considerations for PET in clinical trials Future imaging biomarkers in neurodegenerative diseases a -synuclein, inflammation, synaptic density, vascular disease, TDP-43

Age Related Neuropathology Neurofibrillary Tangles (tau) b -amyloid plaques (A b ) A b plaques NFTs 0 0 A I/II B III/IV C V/VI

In vivo Measurement of A b and Tau with PET Imaging Fibrillar A b A b and tau A b PET Imaging e.g. [ 11 C] PIB, [ 18 F] florbetapir, [ 18 F] florbetaben, [ 18 F] flutemetamol Paired helical filament tau Tau PET Imaging e.g. [ 18 F] flortaucipir (AV1451), [ 18 F] MK-6240, [ 18 F] GTP1, [ 18 F] PI- 2620

A b PET imaging in aging and dementia Alzheimer’s Disease Normal Aging (Amyloid Negative) Normal Aging (Amyloid Positive) ~30% of cognitively normal people in their 70s and above have substantial A b accumulation by PET

Amyloid Hypothesis: AD Biomarker progression b -amyloid Cognitive Decline Neurodegeneration: and Dementia Tau pathology Synaptic dysfunction Metabolic decline Brain atrophy

Regional specificity Amyloid PET Florbetapir SUVR: cortical sumary region mean/ whole cerebellum mean

Cortical A b accumulation over the disease trajectory 32% florbetapir+ Normal Subjective 35% florbetapir+ Memory Complaint Frequency 48% florbetapir+ Early MCI 65% florbetapir+ Late MCI 86% florbetapir+ AD Total N=1064 Florbetapir Cortical SUVR

A b PET imaging – postmortem associations La Joie et al. Alz & Dementia (in press) Cortical A b PET retention is highly associated with A b plaques at autopsy in 179 diverse cases

Cortical A b accumulation predicts cognitive decline Elevated A b predicts ADAS-cog decline in In cognitively normal, A b- individuals, negative MCI and AD but increasing A b is associated with memory decline Landau et al Neurology 2016 And in cognitively normal individuals Donohue et al JAMA 2017 Landau et al Neurology 2018

Time course of changes Rate of Aβ accumulation is not constant throughout the disease trajectory Florbetapir SUVR annual change 0.050 0.025 0.000 -0.025 0.8 1.0 1.2 Florbetapir Cortical Summary SUVR Jack et al. Neurology (2013) Villemagne et al. Lancet Neurol (2013)

Regional specificity Amyloid PET Tau PET Braak III/IV Braak V/VI Braak I/II Neocortical Inferolateral temporal/ Medial temporal limbic (extra-temporal) Florbetapir SUVR: cortical sumary region mean/ whole cerebellum mean Flortaucipir SUVRs: Braak stage-based region means/ cerebellar grey matter mean

Tau increases with impairment and elevated A b Medial temporal AV1451 Inferolateral temporal/limbic AV1451 Neocortical (extra-temporal) AV1451 A b - A b - A b - A b + A b + A b + Unimpaired Impaired Unimpaired Impaired Unimpaired Impaired

Co-occurrence of A b and tau are linked to cognitive decline Higher tau is linked to poorer cognition for A b + individuals A b - A b + = Higher tau is linked to retrospective cognitive decline in A b + individuals A b - A b +

2018 NIA-AA Research Framework Jack et al. Alz & Dementia 2018

2018 NIA-AA Research Framework Distributions differ across A, T, N biomarkers Determining standardized cut-points for positivity is challenging Normal (-) Abnormal (+) Normal (-) Abnormal (+) A b PET Tau PET Normal (-) Abnormal (+) Abnormal (+) Normal (-) FDG metaROI Hippocampal Volume Jack et al. Alz & Dementia 2018 Jack et al. Alz & Dementia 2018

Tau increases with impairment and elevated A b Medial temporal AV1451 Inferolateral temporal/limbic AV1451 Neocortical (extra-temporal) AV1451 A b - A b - A b - A b + A b + A b + 19% 90% upper A b- threshold of 141 A b -normals High FTP A b+ 29% Low FTP Unimpaired Impaired Unimpaired Impaired Unimpaired Impaired ADNI LOAD Atypical/EOAD Maass et al. NeuroImage 2017 Lowe et al. Brain 2018

Longitudinal tau PET Still early! Jack et al. Brain 2018

PET in Clinical Trials: Practical considerations Cross-sectional PET Longitudinal PET (Subject selection) (Target Engagement) Scan cost Participant burden and cost Multiple PET scans (+ MRI?) Scanner changes Radiation exposure PET vs blood-based vs CSF markers Scan-rescan variability; Longitudinal changes are usually small Multisite studies Different scanners Ligand-specific methodological challenges Different tracers Determining a followup time period with Identification of intervention “sweet spot” adequate power (biomarker-specific) (biomarker-specific)

Amyloid clearance LY3002813 (N3pG) Gantanerumab Baseline 3 months Klein et al. AAIC 2018 6 months

2018 NIA-AA Research Framework Beyond amyloid and tau Rabinovici et al Alz & Dem 2017 Biomarker targets in development [A] Plasma or retinal amyloid [T] New tau PET ligands [N] Neurofilament light, Synaptic density ([C11] UCB-J) [V] Vascular disease [I] Inflammation [S] a -synuclein TDP-43 Jack et al. Alz & Dementia 2018 Jack et al. Alz & Dementia 2018

Upcoming imaging biomarkers Neuroinflammation with Synaptic density with [11C] UCB-J [11C] – (R) -PK11195 Chen et al. JAMA Neurol 2018 PET markers of a -synuclein and TDP-43 in development Parbo et al. Neurobiol Dis 2018

Genetics Lifestyle and (ApoE) Age environment Other pathology ( a -synuclein, TDP-43) Cerebrovascular Disease b -amyloid Cognitive Decline and Neurodegeneration: Dementia Tau pathology Synaptic dysfunction Metabolic decline Brain atrophy

Recent A b and tau PET work has emphasized detection of earliest pathological AD changes, and associations with cognitive decline Research framework relies on amyloid [A], tau [T], and neurodegenerative [N] biomarkers to identify and stage AD pathological changes PET has been used successfully in clinical trials for participant selection and tracking of target engagement despite methodological challenges In vivo characterization of other comorbid pathology is a key developing area

Thank you UC Berkeley ADNI collaborators ADNI participants & staff Bill Jagust Gil Rabinovici Michael Weiner Clifford Jack Danielle Harvey ADNI sponsors Suzanne Baker Renaud La Joie Robert Koeppe Laurel Beckett Deniz Korman Tessa Harrison Duygu Tosun Andrew Saykin Chester Mathis Paul Aisen Eric Reiman Ronald Petersen Kewei Chen Michael Donohue Leslie Shaw Arthur Toga John Trojanowski Karen Crawford

Example [18F] flortaucipir tau PET cases MCI: 80yo male A A b - (4 scans) A b - ApoE4- CDR-sb=0.5 High FTP ADAS-cog=12 Braak III/IV = 1.72 0.5 1.2 2.0 MCI: 78yo male A b + (4 scans) B A b + ApoE4- Low FTP CDR-sb=1.0 ADAS-cog=6 Braak III/IV = 1.14 MCI: 83yo male C A b + (4 scans) A b + ApoE4+ CDR-sb=1.5 Low FTP ADAS-cog=9 Braak III/IV = 1.35

High vs low FTP groups Inferolateral temporal/limbic AV1451 A b - A b + Unimpaired Impaired A b – A b + (N=80) (N=71) Non-AD dementia Possible AD with Possible AD with comorbid Low Non-AD dementia comorbid pathology pathology 81% FTP 29% Primary Age Typical MCI/AD Primary Age Related Tauopathy High Related Typical MCI/AD (PART) Tauopathy (PART) 19% 71% FTP

Flortaucipir is variable among impaired (MCI / AD) individuals A b – A b + - Fewer AD-specific biomarker Non-AD dementia Possible AD with characteristics Possible AD with Low comorbid Non-AD dementia comorbid - Mostly male pathology Schneider et al Brain 2016 pathology FTP Greater hippocampal 81% 29% - Cerebrovascular or TDP-43 pathology atrophy + hypometabolism Primary Age Typical MCI/AD Primary Age may account for cognitive symptoms Related Tauopathy High Related Typical MCI/AD supports a medial temporal (e.g. Schneider et al Brain 2016) (PART) Tauopathy (PART) FTP 19% 71% predominant role that could be AD-independent Understanding the characteristics of “atypical tau” individuals will be important for effective selection of participants for clinical trials of tau-modifying treatments

Tau PET variability Ossenkoppele et al JAMA 2018 Whitwell et al Ann Neurol 2018

Distribution of suprathreshold (>1.4 SUVR) voxels Unimpaired (N/SMC) Impaired (Early/Late MCI, AD) A b - % subjects with suprathreshold voxels 10% 50% 80% A b +

Fan et al. Brain 2018

Cons Consid iderable overla rlap p with thin in the he low tau au rang ange am among ind ndiv ivid iduals s acr acros oss s the he di dise sease sp spect ctrum (i (in n LOAD) D) Conversely Con ly, hi high gh ne neoc ocortic tical tau au in n unim unimpair ired su subje bjects ts has has al also so 18)  PART be been n repo port rted (e (e.g. g. Lowe et al al. Br Brain in 20 2018

Medial temporal AV1451 A b - A b + Resembles MAPT406W mutation pattern