WISCONSIN ALZHEIMER’S DISEASE RESEARCH CENTER Pre-Clinical Dementia and Early Detection: Epidemiology and Recent Advances May 2, 2013 Cynthia M. Carlsson, MD, MS Associate Professor of Medicine, Division of Geriatrics Vilas Distinguished Achievement Professor University of Wisconsin School of Medicine and Public Health Madison VA Geriatric Research, Education and Clinical Center (GRECC) Wisconsin Alzheimer’s Disease Research Center (ADRC) Madison, Wisconsin

Disclosures No financial disclosures Studies funded by: National Institute on Aging American Federation for Aging Research State of Wisconsin University of Wisconsin Dept. of Medicine Merck and Co., Inc. supplied study drugs for our investigator-initiated NIH-funded trial

Outline Epidemiology of dementia Early detection of Alzheimer’s disease and non-Alzheimer’s dementias Preclinical dementia biomarkers Conclusions and future directions

Alzheimer’s Disease Prevalence in the United States No. of Persons with AD, Millions Year Hebert et al., Arch Neurol 2003;60(8): 1119-22.

Alzheimer’s Disease Prevalence: Changes with Aging Years Alzheimer’s Association 2013 Alzheimer’s Disease Facts and Figures, Alzheimer’s & Dementia 2013:9(2).

Types of Dementia FTD VaD AD LBD AD + other Schneider JA et al. Brain. 2012 Oct;135(Pt 10):3005-14. Schneider JA et al. Ann Neurol. 2009 Aug;66(2):200-8.

NIH Initiatives to Improve Recognition & Treatment of Dementias Through Identifying Research Priorities National Institute of Neurological Diseases and Stroke National Institute on Aging

Identifying Dementia in Primary Care Alzheimer’s disease Lewy body dementia Fluctuating attention, visual hallucinations, parkinsonism Vascular dementia Acute onset, neuroimaging findings of stroke Frontotemporal dementia Socially inappropriate, lack of inertia and empathy, perseverative, hyperoral Language/spelling problems Parkinson’s disease dementia Has had PD for 5+ years DLB: fluctuating attention, recurrent visual hallucinations, and parkinsonism. Suggestive features include REM sleep behavior disorder, severe neuroleptic sensitivity, and low dopamine transporter uptake in the basal ganglia on functional neuroimaging. Additional supportive features that commonly occur in DLB, but with lower specificity, include repeated falls and syncope, transient, unexplained loss of consciousness, severe autonomic dysfunction, hallucinations in other modalities, systematized delusions, depression, relative preservation of medial temporal lobe structures on structural neuroimaging, reduced occipital activity on functional neuroimaging, prominent slow wave activity on electroencephalogram, and low uptake myocardial scintigraphy.

Can we improve our detection of AD in clinic? Preclinical Stages of Alzheimer’s Disease Can we improve our detection of AD in clinic? Normal aging Mild Cognitive Impairment Alzheimer’s Disease Cognitive Function Accumulating AD Pathology Age Death

Mild Cognitive Impairment Preclinical Stages of Alzheimer’s Disease Preventive Therapy??? No symptoms, BUT early pathology Normal aging Mild Cognitive Impairment Alzheimer’s Disease Cognitive Function Accumulating AD Pathology Age Death 40s-60s

Identifying Asymptomatic At-Risk Adults Neuroimaging Magnetic resonance imaging (MRI) Structure – atrophy, white matter hyperintensities Function – cerebral blood flow Positron emission tomography (PET) FDG-PET – glucose uptake patterns Amyloid imaging – amyloid burden Cerebrospinal fluid biomarkers β-amyloid, tau Cognitive tests Genetic tests (APOE4 allele)

Alzheimer’s Disease Neuroimaging Initiative (ADNI) Currently in its third phase (ADNI, ADNI-GO, ADNI-2) Older controls (n=150), MCI (n=450), AD (n=150), subjective memory complaint (n=100) Developed standardized MRI, PET, CSF methods Identified earliest biomarker changes in AD pathology Elucidated patterns & rates of change of imaging & CSF biomarkers in controls, MCI, & AD pts Identified at-risk participants for clinical trials Now in its third phase (ADNI, ADNI GO and ADNI 2), ADNI 2 is studying the rate of change of cognition, function, brain structure, and biomarkers in 150 elderly controls, 450 subjects with mild cognitive impairment, 150 with mild to moderate AD and a new group of 100 people with significant, yet subtle, memory complaints, referred to as the significant memory concern cohort. Weiner MW et al.. Alz Dementia 8 (2012):S1-S68.

Hippocampal Atrophy in AD Scheltens et al. Lancet Neurol 2002;1:13-20.

Neuroimaging for Alzheimer’s Disease Control AD PIB-PET: Greater amyloid deposition MRI: Greater atrophy FDG-PET: Reduced glucose uptake Blennow K et al. Lancet 2006; 368: 387–403

Regional Cerebral Blood Flow Is Reduced in AD Patients Statistical parametric maps of regional reduced blood flow in R inf parietal cortex, bil posterior cingulate (P <.001), bil superior and middle frontal gyri (P <.001), and L inf parietal lobe (P=.007) in AD patients compared to controls Blood flow is reduced in areas of the brain related to memory & learning in persons with AD compared to people without AD Johnson NA et al. Radiology 2005;234:851-859.

N Engl J Med 355;13 www.nejm.org September 28, 2006 Cerebrospinal Fluid (CSF) Biomarkers N Engl J Med 355;13 www.nejm.org September 28, 2006

Mild Cognitive Impairment CSF Biomarker Changes in AD CSF -amyloid levels Spinal Fluid Levels Tau CSF tau levels Time Mild Cognitive Impairment Amyloid Healthy Memory Alzheimer’s disease

Hypothetical Model of Dynamic Biomarkers in AD Cerebrovascular dysregulation? Jack et al. Lancet Neurol 2010;9:119-28.

Model of Preclinical Stages of AD Stage 1: Asymptomatic amyloidosis - High PET amyloid tracer retention - Low CSF Aβ42 Stage 2: Amyloidosis + Neurodegeneration - Neuronal dysfunction on FDG-PET/fMRI - High CSF tau/p-tau - Cortical thinning/Hippocampal atrophy Stage 3: Amyloidosis + Neurodegeneration + Subtle Cognitive Decline - Subtle change from baseline level of cognition - Poor performance on challenging cognitive tests - Does not yet meet criteria for MCI Mild cognitive impairment (MCI) →AD Sperling RA, Aisen PS, Beckett LA, et al. Alzheimers Dement 2011;7:280-92.

How Do We Identify Asymptomatic At-Risk Adults? Middle-aged adults w/ parental history of AD Wisconsin Registry for Alzheimer’s Prevention (WRAP) (PI: Mark Sager, MD) N=1,527 mean age 54 yrs 72% with parental history of AD 46% APOE 4 carriers. Parental history effect independent from APOE4 allele carrier status Cognitively normal yet have CSF, MRI, and subtle cognitive changes suggested of preclinical disease

Neuropathologic Changes in AD: CSF Biomarkers in Middle-aged At-risk Adults N=50 middle-aged adults with parental history of AD Carlsson CM et al. J Alzheimer’s Dis 2008 Mar;13:187-197.

Hippocampal Atrophy Precedes Cognitive Decline in Middle-aged, At-risk Adults Parental history positive (n=60) Parental history negative (n=48) Mean age 54 yrs 4-year longitudinal follow-up L R Among all participants: persons with parental history of AD had more atrophy in the L hippocampus (red area above) In APOE4- participants: persons with parental history of AD had more atrophy in the R hippocampus (light blue area above). Okonkwo OC et al. Neurology 2012;78:1769–1776

Do AD Biomarkers Have a Role in Clinical Practice? U.S. Food and Drug Administration approves Amyvid (Florbetapir F 18 Injection) a drug for Positron Emission Tomography (PET)

AD CSF Signature in Asymptomatic Middle-aged At-risk Adults Cognitively normal older adults from ADNI (mean age 76 yrs) Cognitively normal middle-aged adults with parental history of AD from ESPRIT trial (mean age 53 yrs) Normal (n=114) Normal (n=96) CSF P-Tau 181P Level, pg/mL (Log Transformed) CSF A1-42 Level, pg/mL ■ = APOE4 pos, AD sig O = APOE4 neg, AD sig ■ = APOE4 pos, healthy sig O= APOE4 neg, healthy sig Signature 1 (red) = Alzheimer’s disease signature Signature 2 (green) = healthy signature De Meyer G et al. Arch Neurol 2010;67:949-956. Carlsson CM et al. AGS Plenary Session 2012.

In Vivo Amyloid Imaging Predicts Progression from MCI to AD Doraiswamy PM et al. Neurology. 2012 Oct 16;79(16):1636-44

Appropriate Use Criteria for Amyloid PET Patients with persistent or progressive unexplained MCI Patients with possible AD (i.e., atypical clinical course or mixed features) Patients with atypical young-onset dementia K.A. Johnson et al. Alzheimer’s & Dementia 9 (2013) e1–e16.

How Might We Use Biomarkers in the Future? High risk Moderate risk Low risk Very low risk Alzheimer’s Risk Profile Does this patient need newly-approved AD preventive therapy?

Conclusions Early recognition of AD and non-AD dementias in primary care: helps families better understand the disease and how to plan for the future will prepare us to efficiently prevent & treat dementia as therapies are identified will allow us to refer our patients earlier into clinical studies Biomarkers are effective research tools to identify persons at risk for cognitive decline, but have limited clinical utility currently.

Dementia Treatment & Prevention: Opportunities for Primary Care Providers Improve our identification of AD and non-AD dementias Familiarize ourselves with new biomarkers and their clinical indications Aggressively control vascular risk factors Emphasize healthy lifestyles (exercise, weight management) Encourage participation in clinical research

Alzheimer’s Association Trial Match http://www.alz.org/research/clinical_trials/find_clinical_trials_trialmatch.asp http://www.clinicaltrials.gov/ NIA Alzheimer’s Disease Centers http://www.nia.nih.gov/alzheimers/alzheimers-disease-research-centers NIA Alzheimer’s Disease Centers

A special thanks to all of our dedicated research participants. Acknowledgments Wisconsin Alzheimer’s Disease Research Center: Sanjay Asthana, MD Craig Atwood, PhD Ben Austin, PhD Hanna Blazel, MS N. Maritza Dowling, PhD Carey Gleason, PhD Bruce Hermann, PhD Laura Jacobson, BS Sterling Johnson, PhD Ozioma Okonkwo, PhD Luigi Puglielli, MD, PhD Howard Rowley, MD Mark Sager, MD Funding: NIA NCRR UW Department of Medicine Madison VA GRECC WI Comprehensive Memory Program Pilot Award AFAR Merck and Co., Inc. supplied study drugs for NIH-funded study Sahlgrenska Academy, Sweden: Henrik Zetterberg, MD, PhD Kaj Blennow, MD, PhD A special thanks to all of our dedicated research participants.