вход по аккаунту


Beyond diagnosis What biomarkers are teaching us about the УbioФlogy of Alzheimer disease.

код для вставкиСкачать
Beyond Diagnosis: What Biomarkers
Are Teaching Us about the
“Bio”logy of Alzheimer Disease
he development of biological markers for in vivo assessment of amyloid-beta (A␤) and tau, the proteins
that define Alzheimer disease (AD) histopathology, promises to revolutionize the diagnosis of this devastating disease. Senile plaques, once visible only at autopsy, can now
be imaged during life with positron emission tomography
(PET) using A␤-specific ligands such as [11C]Pittsburgh
compound B (PiB).1 AD also leaves a molecular signature
in the cerebrospinal fluid (CSF) in the form of decreased
A␤1– 42 and increased total and phosphorylated tau levels.2,3 Major interinstitutional initiatives, such as the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and its
“down under” counterpart, the Australian Imaging Biomarkers and Lifestyle Study of Ageing (AIBL), are optimizing the integration of biomarkers into clinical trials
and demonstrating their potential utility for early, even
presymptomatic, diagnosis of AD.
At the same time, these large collaborative studies
are also yielding another dividend, as they begin to proffer
interesting insights into the biology of AD. Two reports
in this issue of Annals of Neurology demonstrate how in
vivo measures of A␤ and tau not only can serve as diagnostic markers, but—in conjunction with genetics, clinical characterization, and structural neuroimaging—can
help address important, unanswered questions regarding
the mechanisms underlying AD.
One such question has been the significance of ADlike plaque burden found at autopsy in as many as onethird of elderly individuals without discernable cognitive
impairment.4 Do plaques in these individuals represent a
benign accompaniment to normal aging, or are they indicative of preclinical disease? Resolving this fundamental
question about the relationship between A␤ and AD has
become even more pressing in light of disappointing results from clinical trials of A␤-directed therapies,5,6 which
so far have failed to produce a clinical benefit even when
amyloid burden is dramatically reduced.7
Data from Chételat and colleagues8 in this issue
strongly suggest that A␤ accumulation in nondemented
elderly is a harbinger of clinical decline. Using PiB-PET
to study the association between amyloid burden and gray
matter atrophy (measured by magnetic resonance imaging
[MRI]) in 163 AIBL participants spanning the clinical
spectrum from normal cognition to AD, the authors
found that global PiB binding was negatively correlated
with gray matter volume in participants with subjective
cognitive impairment (SCI; those who complained of
memory problems but had no objective deficits on cognitive testing).8 No correlations were found between PiB
binding and gray matter volumes in subjects with mild
cognitive impairment (MCI) or AD, consistent with longitudinal observations that PiB uptake reaches a relative
plateau by MCI or early AD, whereas clinical decline and
neurodegeneration (as measured by MRI or [18F]fluorodeoxyglucose PET) accelerate independent of further
amyloid accumulation.9,10 Gray matter regions inversely
correlated with global PiB in SCI included hippocampus,
precuneus, lateral temporoparietal cortex, and cingulate
cortex, replicating the atrophy pattern seen in AD. This
study thus contributes to a converging literature suggesting that amyloid accumulation in cognitively normal
(CN) individuals is associated with AD-like functional
and structural brain changes.11–16 Although longitudinal
data on PiB-positive normal controls are still sparse, a recent study found that high PiB binding at baseline was
associated with a 5-fold increased risk of cognitive decline,17 supporting the notion that many of these individuals have preclinical AD.
Two other aspects of the Chételat data are noteworthy. In addition to the global effects of PiB on gray matter in SCI, the authors identified local correlations between PiB binding and cortical atrophy in precuneus and
medial prefrontal cortex. These regional relationships are
interesting because they suggest a local effect of A␤ on
brain structure early in the course of AD, possibly independent of neurofibrillary pathology, as tangles would be
unlikely in these regions so early in the disease.18 Also
intriguing is a strong trend toward inverse correlation be© 2010 American Neurological Association
of Neurology
tween PiB binding (but not gray matter volume) and performance on episodic memory tests. Although the authors
appropriately minimize this finding, which after correcting for multiple comparisons missed criteria for statistical
significance, these results hint that in very early disease
stages, amyloid deposition may impact memory performance through nondegenerative mechanisms, such as alterations in local network activity.14 Both of these observations suggest testable hypotheses about the role of A␤
in early AD pathogenesis that are important topics for
further work.
In another study in this issue, Vemuri and colleagues used AD biomarkers to investigate the role of apolipoprotein E4 (ApoE4) in AD.19 Studying nearly 400
ADNI subjects, again ranging from CN through MCI to
AD, the authors used CSF A␤1– 42 levels as a surrogate for
plaque pathology, CSF total tau as a measure of neuronal
injury, and MRI atrophy in AD-specific brain regions (reflected by the STructural Abnormality iNDex [STAND]
score) to reflect neurodegeneration. Across the cognitive
spectrum from CN to AD, CSF A␤1– 42 was more abnormal in ApoE4 carriers than noncarriers, whereas CSF tau
and STAND scores did not differ by ApoE status except
in MCI. ApoE4 carriers with MCI and AD were also significantly younger than their noncarrier counterparts.
These findings are consistent with previous reports suggesting that ApoE4 increases the risk of AD at least in
part through acceleration of A␤-dependent processes.20 –22
Vemuri et al further found that ApoE4 may alter
the relationship between biomarkers and cognitive state.
In ApoE4 noncarriers, all 3 biomarkers (A␤1-42, tau, and
MRI STAND score) worsened in conjunction with declining Mini Mental State Examination (MMSE) performance. But in those with ApoE4, only the MRI paralleled
declining cognition; A␤ and tau showed little relationship
with MMSE, likely because they were already highly abnormal in E4-positive CN and MCI subjects. Based on
these data, the authors propose that the AD pathological
cascade in ApoE4 carriers is shifted not only to an earlier
age, but also in relation to clinical status, such that E4
carriers reach a relative plateau of A␤ pathology while
cognitively normal, whereas noncarriers continue to accumulate pathological burden as they transition from CN to
MCI and finally to AD. Although interesting, this longitudinal interpretation of cross-sectional data should be
treated with caution. If the ApoE4-negative cohort had a
higher proportion of non-AD pathophysiology in the CN
and MCI groups at enrollment, as seems likely, then the
apparent increase in A␤ and tau pathology in the noncarriers from CN to MCI to AD could be explained by different degrees of biological heterogeneity in the 3 groups,
rather than by true longitudinal change. However, if replicated in longitudinal studies, Vemuri’s finding would
provide a plausible biological mechanism for the apparent
resistance of ApoE4-positive AD patients to anti-amyloid
There are limitations to the ability of biomarker
studies to define the biological mechanisms of AD, most
notably the fact that they are by nature correlational and
thus unable to prove causal relationships. It is also not yet
clear which biological processes linked to AD biomarkers
are most important for pathogenesis. With A␤, for example, is the most disease-relevant activity the plaque deposition reflected by PiB, changes in soluble A␤ seen in
CSF, or another linked but not directly measured species,
such as A␤ oligomers? Additional approaches will be necessary to distinguish between these (and other) possibilities.
Such caveats notwithstanding, biomarker studies are
advancing the field by providing a clearer picture of the
dynamic relationships between AD pathology, neurodegeneration, and cognition. The reports in this issue suggest that A␤-related changes occur early, beginning (and
perhaps even reaching a plateau) when clinical symptoms
are minimal or absent, and triggering a pathological cascade that includes neurofibrillary tangle formation, synaptic and network dysfunction, neuronal loss, and clinical
decline. Whereas Vemuri and colleagues propose that
these events occur in sequence,23 Chételat et al suggest
that A␤ may directly lead to neurodegeneration in the
preclinical phase, with tangle-mediated neurodegeneration
predominating later in the disease course.16 Whichever
proves to be true, perhaps the most important lesson relates to treating the disease; both studies offer hope of a
therapeutic window during which pathology can be detected in vivo, yet clinical symptoms are minimal, and
little irreversible neurodegeneration has occurred.
Gil D. Rabinovici, MD
Memory and Aging Center
Department of Neurology
University of California, San Francisco
San Francisco, CA
Helen Wills Neuroscience Institute
University of California, Berkeley
Berkeley, CA
Erik D. Roberson, MD, PhD
Center for Neurodegeneration and Experimental Therapeutics
Alzheimer’s Disease Center
Departments of Neurology and Neurobiology
University of Alabama at Birmingham
Birmingham, AL
Klunk WE, Engler H, Nordberg A, et al. Imaging brain amyloid in
Alzheimer’s disease with Pittsburgh compound-B. Ann Neurol
2004;55:306 –319.
Volume 67, No. 3
Rabinovici and Roberson: Biomarkers and AD
Blennow K, Hampel H. CSF markers for incipient Alzheimer’s
disease. Lancet Neurol 2003;2:605– 613.
Shaw LM, Vanderstichele H, Knapik-Czajka M, et al. Cerebrospinal fluid biomarker signature in Alzheimer’s disease neuroimaging initiative subjects. Ann Neurol 2009;65:403– 413.
to symptom severity in very mild to mild AD dementia and is
detectable in asymptomatic amyloid-positive individuals. Cereb
Cortex 2009;19:497–510.
Sperling RA, Laviolette PS, O’Keefe K, et al. Amyloid deposition
is associated with impaired default network function in older persons without dementia. Neuron 2009;63:178 –188.
Green RC, Schneider LS, Amato DA, et al. Effect of tarenflurbil
on cognitive decline and activities of daily living in patients with
mild Alzheimer disease: a randomized controlled trial. JAMA
Sheline YI, Raichle ME, Snyder AZ, et al. Amyloid plaques disrupt resting state default mode network connectivity in cognitively normal elderly. Biol Psychiatry 2010;67:584 –587.
Salloway S, Sperling R, Gilman S, et al. A phase 2 multiple
ascending dose trial of bapineuzumab in mild to moderate Alzheimer disease. Neurology 2009;73:2061–2070.
Fagan AM, Head D, Shah AR, et al. Decreased cerebrospinal
fluid A␤42 correlates with brain atrophy in cognitively normal elderly. Ann Neurol 2009;65:176 –183.
Morris JC, Roe CM, Grant EA, et al. Pittsburgh compound B
imaging and prediction of progression from cognitive normality
to symptomatic Alzheimer disease. Arch Neurol 2009;66:
1469 –1475.
Braak H, Braak E. Neuropathological staging of Alzheimer-related
changes. Acta Neuropathol 1991;82:239 –259.
Vemuri P, Wiste HJ, Weigand SD, et al. Effect of APOE on
biomarkers of amyloid load and neuronal pathology in Alzheimer
disease. Ann Neurol 2010;67:122–131.
Reiman EM, Chen K, Liu X, et al. Fibrillar amyloid-␤ burden in
cognitively normal people at 3 levels of genetic risk for Alzheimer’s disease. Proc Natl Acad Sci U S A 2009;106:6820 – 6825.
Morris JC, Roe CM, Xiong C, et al. APOE predicts amyloid-␤ but
not tau Alzheimer pathology in cognitively normal aging. Ann
Neurol (in press).
Bennett DA, Schneider JA, Arvanitakis Z, et al. Neuropathology
of older persons without cognitive impairment from two
community-based studies. Neurology 2006;66:1837–1844.
Holmes C, Boche D, Wilkinson D, et al. Long-term effects of
A␤42 immunisation in Alzheimer’s disease: follow-up of a randomised, placebo-controlled phase I trial. Lancet 2008;372:
216 –223.
Chételat G, Villemagne VL, Bourgeat P, et al. Relationship between atrophy and ␤-amyloid deposition in Alzheimer’s disease.
Ann Neurol 2010;66:000 – 000.
Engler H, Forsberg A, Almkvist O, et al. Two-year follow-up of
amyloid deposition in patients with Alzheimer’s disease. Brain
2006;129:2856 –2866.
Jack CR Jr, Lowe VJ, Weigand SD, et al. Serial PIB and MRI in
normal, mild cognitive impairment and Alzheimer’s disease: implications for sequence of pathological events in Alzheimer’s disease. Brain 2009;132:1355–1365.
Mormino EC, Kluth JT, Madison CM, et al. Episodic memory loss
is related to hippocampal-mediated ␤-amyloid deposition in elderly subjects. Brain 2009;132:1310 –1323.
Kok E, Haikonen S, Luoto T, et al. Apolipoprotein E-dependent
accumulation of Alzheimer disease-related lesions begins in middle age. Ann Neurol 2009;65:650 – 657.
Jack CR Jr, Lowe VJ, Senjem ML, et al. 11C PiB and structural
MRI provide complementary information in imaging of Alzheimer’s disease and amnestic mild cognitive impairment. Brain
2008;131:665– 680.
Jack CR Jr, Knopman DS, Jagust WJ, et al. Hypothetical model
of dynamic biomarkers of the Alzheimer’s pathological cascade.
Lancet Neurol 2010;9:119 –128.
Dickerson BC, Bakkour A, Salat DH, et al. The cortical signature
of Alzheimer’s disease: regionally specific cortical thinning relates
March, 2010
DOI: 10.1002/ana.22020
Без категории
Размер файла
63 Кб
whats, biomarkers, уbioфlogy, beyond, teaching, disease, alzheimers, diagnosis
Пожаловаться на содержимое документа