HOW CAN NEUROIMAGING HELP UNDERSTAND, DIAGNOSE, AND DEVELOP TREATMENTS FOR ALZHEIMER'S DISEASE?

Part F – AD and biomarkers for the future

NUCLEAR MEDICINE GRAND ROUNDS Stanford University J. Wesson Ashford, M.D., Ph.D.

Clinical Professor (affiliated), Department of Psychiatry and Behavioral Sciences Senior Research Scientist, Stanford / VA Aging Clinical Research Stanford University and VA Palo Alto Health Care System January 5, 2010 Slides at: www.medafile.com

(Dr. Ashford’s lectures)

Shoghi-Jadid et al., 2002

FDDNP-PET scans in the parietal region (top) and the temporal region (bottom) in one control subject and one subject with mild cognitive impairment who was reclassified on follow-up as having Alzheimer's disease. Scans of the subject with mild cognitive impairment, who was reclassified as having Alzheimer's disease, showed increased binding in the frontal (8.6%), parietal (8.9%), and lateral temporal (6.6%) regions. Red and yellow areas correspond to high FDDNP binding values. Small et al., NEJM, 12/2006

Small et al., NEJM, 2006

CSF in Alzheimer’s Disease, both MCI and Dementia patients: Low A β and High Tau

AD Patients 700 600 500 400 300 200 100 0

A β Sunderland T, et al. JAMA. 2003;289:2094-2103.

Control Patients

Tau

CSF of subjects with MCI progressing to AD has elevated tau, decreased β-amyloid The relative risk of progression to AD substantially increased in patients with MCI who had pathological concentrations of T tau and A42 at baseline (hazard ratio 17·7, p0·0001). The association between pathological CSF and progression to Alzheimer’s disease was much stronger than, and independent of, established risk factors including age, sex, education,

APOE

genotype, and plasma homocysteine .

Hansson et al., Lancet Neurology 2006

ADNI data, 2008

ADNI CSF Data – total tau

Number of participants that provided CSF at baseline Ages +std of participants that provided CSF at baseline APOE genotype 33 34 44 Normal MCI 67 (72%) 24 (26%) 2 (2%) 82 (44%) 81 (44%) 22 (12%) Mild AD 29 (31%) 42 (45%) 22 (24%) APOE genotype 33 34 44 Normal MCI Mild AD 75.8 ± 5.0

75.8 ± 6.0

77.0 ± 1.4

75.4 ± 8.4

73.9 ± 6.7

72.2 ± 6.0

76.3 ± 8.6

75.6 ± 6.6

69.8 ± 7.0

CSF ABeta levels ± std APOE genotype 33 34 44 Normal MCI Mild AD 212.4 ± 48.4

189.1 ± 59.8

168.8 ± 52.3

156.0 ± 47.8

148.4 ± 42.4

139.0 ± 27.2

126.0 ± 2.8

119.8 ± 23.5

116.2 ± 22.3

CSF tau levels ± std APOE genotype 33 34 44 Normal MCI Mild AD 67.8 ± 26.9

71.0 ± 2.8

83.6 110.6 ± ± 40.8

123.8 ± 68.6

81.8 ± 42.6

122.4 ± 72.7

113.3 ± 42.0

45.9

128.9 ± 53.1

ADNI Data – CSF ABeta, total tau

Comparison 33 vs 34 33 vs 44 34 vs 44 Normal vs MCI Normal vs Mild AD MCI vs Mild AD p-value <.0001

<.0001

0.08

0.57

0.15

0.20

Comparison 33 vs 34 33 vs 44 34 vs 44 Normal vs MCI Normal vs Mild AD MCI vs Mild AD p-value 0.07

0.67

0.99

0.05

<.01

0.06

CSF Measure Implications

• The variations in CSF tau and A-beta that are associated with Normal, MCI, and AD in the full ADNI sample change when APOE is considered. (There are more APOE-e4 carriers in the AD-related diagnostic categories, allowing for this statistical misrepresentation to occur.) • A-beta levels decrease in association with APOE-related increasing AD risk (more e4), but are not significantly associated with age or diagnosis.

• Tau levels increase in association with more AD pathology diagnostically, but are not associated with APOE genotype or age.

• (Other studies have shown decreased A-beta levels in the familial AD genotype individuals.) • Consequently, low CSF A-beta levels are an indication of vulnerability to AD pathology in critical brain neurons, not a measure of disease pathogenesis (the prodromal decline may last many years).

• Elevated CSF-tau level increases indicate impairment of function in critical brain neurons, reflecting the extent of AD pathology.

• The biggest factor predisposing to AD is age, and the major factor moderating the effect of age is APOE genotype (note that TOMM-40 genotype may be more closely related to this effect).

Potential AD Biomarkers

• Blood, urine Aβ40? Aβ42? Neuritic threads?

– Most studies suggest not helpful • Protein levels in blood – Proteomics, Leptin.

– Lower Leptin predicts MCI progression to dementia • CSF: Aβ40? Aβ42? Others Aβ species?

– Possibly highly predictive • CSF: tau, p-tau – Assess active disease progression.

• Neuroimaging – Structural (volumetric assessments) – Functional (FDG-PET, SPECT) – Specific protein imaging (PET)

Clinical State Neuro pathology

Alzheimer’s Disease: Course, Pathology, Biomarkers

Normal None Pre Symptomatic AD Mild Cognitive Impairment AD Amyloid Plaques, No Tangles Amyloid Plaques Few Tangles Amyloid Plaques Many Tangles CSF Biomarkers Normal tau Normal A

b

tau?

A

b?

High tau Low A

b

High tau Low A

b

Disease Progression

NEED TO FOCUS ON ITEMS TO ASSESS THE ALZHEIMER CONTINUUM

• ITEMS MAY BE: – TEST COMPONENTS – QUESTIONNAIRES – DATA FROM FAMILY – BRAN SCAN VOXELS – CSF MEASURES • ITEM ANALYSIS PROVIDES THE ERROR ESTIMATION

Differential Diagnosis: Top Ten

(easy mnemonic device: AVDEMENTIA)

1. A

lzheimer Disease (pure ~40%, + mixed~70%, ? dLbd)

2. V

ascular Disease, MID

3. D

rugs,

D

epression,

D

elirium

4. E

thanol (? more in Vets) (5-20%) (5-15%)

5. M

edical /

M

etabolic Systems

6. E

ndocrine (thyroid, diabetes),

E

ars,

E

yes,

E

nviron.

7. N

eurologic (other primary degenerations, fronto temporal, - consider diffuse Lewy body dementia, Parkinson component)

8. T

umor,

T

oxin,

T

rauma

9. I

nfection,

I

diopathic,

I

mmunologic

10. A

mnesia,

A

utoimmune, Sleep

A

pnea,

A

AMI Adapted from Yesavage, 1979

AD Is Often Misdiagnosed

Patient initially diagnosed with AD

Yes 28% No 72%

Patient’s first diagnosis other than AD

35% 14% 14% 9% 7% 21% Dementia (not AD) Depression Normal aging Stroke No diagnosis Other Source: Consumer Health Sciences, LLC. Alzheimer’s Caregiver Project. 1999.

AD is Under-diagnosed

• Early Alzheimer’s disease is subtle, the diagnosis continues to be missed – it is easy for family members to avoid the problem and compensate for the patient – physicians tend to miss the initial signs and symptoms • Less than half of AD patients are diagnosed – Estimates are that 25% to 50% of cases remain undiagnosed – Diagnoses are missed at all levels of severity: mild, moderate, severe • Undiagnosed AD patients often face avoidable social, financial, and medical problems • Early diagnosis and appropriate intervention may lessen disease burden – Early treatment may improve overall course substantially • No definitive laboratory test for diagnosing AD exists – Efforts to develop biomarkers, early recognition by brain scan Evans DA. Milbank Quarterly. 1990; 68:267-289

Justification for Brain Scan in Dementia Diagnosis

• Differential Diagnosis: Tumor, Stroke, Subdural Hematoma, Normal Pressure Hydrocephalus, Encephalomalacia • Confirmation of atrophy pattern • Estimation of severity of brain atrophy • MRI shows T2 white matter changes – Periventricular, basal ganglia, focal vs confluent – These may indicate vascular pathology • SPECT, PET - estimation of regions of physiologic dysfunction, areas of infarction • PET – AD – fronto-temporal dementia differential • Helps family to visualize problem

Future Directions for Brain Imaging in Alzheimer’s Disease at Stanford / VA

A major institute for focusing on Alzheimer’s disease is needed • High resolution MRI – 3-4 T – Hippocampal, entorhinal measurements, DTI to assess tracks – Accurate atrophy assessment • MR spectroscopy – see neuron loss (NAA) • fMRI – functional – see changes related to memory loss • PET ligands – PIB – DDNP – New agents • Longitudinal observation and measurement • Drug trials with brain imaging outcome measures • Quantification of Alzheimer pathology, other pathology • Linkage of computerized tests with brain changes

Alzheimer Diagnostic and Treatment Development Center

• Need a center that can accurately diagnose Alzheimer’s disease and quantify its level of severity in living patients – CSF tau and beta-amyloid levels – Brain scans – MRI, MRS, PET (fDDNP, PIB or related compound) – Genetic testing – with counseling – Computerized cognitive testing • Accurate assessment of severity would allow rapid, efficient testing of treatments for AD – Measure actual effects on CSF chemicals – Determine if PET indices of pathology are developing more slowly, stopped developing, or are resolving.

– Resolve rate of change effects, relate to level of severity – Lead to prevention, focus on genetic-determined treatments