Dynamic biomarkers and the pathophysiology of Alzheimer's diseaseRelations between brain tissue loss, CSF biomarkers, and the ApoE genetic profile: a longitudinal MRI study
Introduction
There is an increasing body of evidence from in vivo imaging and postmortem studies indicating that Alzheimer's disease (AD) is associated with a sequence of pathophysiological events that can occur over a long period of time (approximately 20 years) before clinical symptoms become apparent (Price and Morris, 1999). A slow disease progression potentially provides a window for early interventions to reduce or even stop progression of AD. Histopathological studies showed that the hallmarks of the disease, beta amyloid (Aβ)-rich amyloid plaques and neurofibrillary tangles formed by abnormal tau, precede neuron loss in presymptomatic AD patients (Price and Morris, 1999). Substantial accumulations of plaques and tangles in the brain can also be found in nondemented subjects with mild cognitive impairment (MCI), a transitional stage between normal aging and dementia (Aizenstein et al., 2008, Jack et al., 2009, Mintun et al., 2006). Consistent with histopathological findings, cerebrospinal fluid (CSF) chemistry studies have pointed to alterations in CSF Aβ (in particular Aβ1–42), total tau (t-tau), and phosphorylated tau (p-tau181p) concentrations preceding clinical symptoms of AD (Fjell et al., 2008). In general, studies found that increased CSF t-tau and p-tau181p were associated with neuronal and axonal damage, whereas reduced CSF Aβ1–42, the form of Aβ that most readily fibrillizes and deposits earliest in plaques, has been implicated to reflect higher amyloid plaque burden in the brain (Clark et al., 2003, Shaw et al., 2009). However, the CSF measures are not easily interpretable because their origins are not exclusively brain derived and they provide no information about the regional spread of brain damage. Despite this, there is considerable agreement that measuring CSF Aβ1–42, t-tau, and p-tau181p improves the diagnostic accuracy for AD (Andreasen et al., 1999).
Independent of biomarker studies, numerous structural magnetic resonance imaging (MRI) studies have shown a characteristic pattern of brain atrophy in AD and a similar pattern in MCI, primarily affecting regions in the parietotemporal lobe, including the hippocampus, which plays a central role in memory formation (Chetelat and Baron, 2003, deToledo-Morrell et al., 2004, Du et al., 2001, Du et al., 2002, Duarte et al., 2006, Hua et al., 2008, Kramer et al., 2004, Morra et al., 2008, Morra et al., 2009a, Morra et al., 2009b; Schroeter et al., 2009, Thompson et al., 2004, Whitwell et al., 2007, Whitwell et al., 2008). In addition, an increasing number of longitudinal MRI studies show that both AD and MCI are also associated with a regional pattern of increased rates of brain tissue loss compared with normal aging (Desikan et al., 2008, Du et al., 2003, Du et al., 2004, Jack et al., 2004, Jack et al., 2005, Jack et al., 2008b; Stoub et al., 2005). With the emerging findings of CSF biomarker and structural imaging alterations in AD, there is considerable interest in utilizing the CSF and MRI measures together to improve detection of early signs of AD, as well as, in unraveling relationships between CSF Aβ1–42, t-tau, and p-tau181p and MRI measures of regional brain alterations. Recently it has been shown that the combination of CSF biomarkers and atrophy rates can provide better prediction of AD than either source of data alone (Brys et al., 2009; Vemuri et al., 2009a, 2009b). However, whether relationships between brain atrophy rates and CSF biomarkers help further to improve predictions has not fully been explored.
Moreover, the role of the apolipoprotein E allele ε4 (ApoE ε4) gene, a major risk factor for AD, ought to be considered for a comprehensive evaluation. Presence of ApoE ε4 is related to abnormal CSF biomarker concentrations (Glodzik-Sobanska et al., 2009, Sunderland et al., 2004), as well as to higher rates of brain atrophy (Basso et al., 2006, Fleisher et al., 2005, Potkin et al., 2009, Schuff et al., 2009, Sluimer et al., 2008). The relationships among all 3 factors, CSF biomarkers, ApoE ε4, and rates of regional brain atrophy, might therefore provide important information about the vulnerability of the brain to AD. Our overall goal in this study was therefore to unravel the relationships among all 3 factors: brain atrophy rates, CSF biomarker concentrations, and presence of ApoE ε4. Toward the goal of identifying an AD biomarker, it will be important to fully understand the relationship between CSF biomarker concentrations and brain degeneration, such as neuron loss, which is thought to underlie the clinical symptoms in AD (Fjell et al., 2008, Jack et al., 2009). While CSF biomarkers relate to cumulative AD pathology in the brain as peripheral measures, MRI as an external tool to elucidate the distribution of the AD related neurodegeneration (i.e., brain atrophy in terms of tissue loss and ventricular enlargement). However, relatively few MRI studies so far have reported correlations between CSF biomarkers and the pattern of brain atrophy or the rate of atrophy progression (Fagan et al., 2009; Fjell et al., 2010a, 2010b; Hampel et al., 2005, Henneman et al., 2009; Herukka et al., 2008; Leow et al., 2009, Schuff et al., 2009). Specifically, in healthy elderly individuals, it has been shown that low CSF levels of Aβ1–42 correlate with ventricular expansion and volumetric reductions in widespread brain areas (Fjell et al., 2010a). In individuals with progressive MCI, low CSF Aβ1–42 concentration and high concentrations of CSF p-tau181p and t-tau are associated with higher subsequent rates of hippocampal atrophy (Hampel et al., 2005, Henneman et al., 2009; Herukka et al., 2008; Schuff et al., 2009). In AD patients, elevated CSF p-tau181p concentrations were associated with higher subsequent rates of hippocampal atrophy and medial temporal atrophy (Hampel et al., 2005, Henneman et al., 2009; Herukka et al., 2008; Leow et al., 2009), while low CSF Aβ1–42 concentrations exhibited larger rates of medial temporal atrophy (Leow et al., 2009). However, the majority of previous MRI studies in this context focused on hippocampal and temporal lobe atrophy and ventricular expansion in MCI and AD patients, while relatively little is known about relations between the CSF biomarker concentrations and atrophy rates of other regions throughout the brain. In addition, variations in these relationships across the spectrum of cognitive impairments have not been comprehensively studied for regions across the brain.
Our main goal in this study was to test the hypothesis that relations between CSF biomarkers (i.e., Aβ1–42, t-tau, and p-tau181p concentrations) and rates of regional brain atrophy not only vary across brain regions but also across the cognitive spectrum, including healthy elderly individuals (CN), individuals with MCI, and AD patients. In particular we tested that: (1) low Aβ1–42 and high t-tau and p-tau181p concentrations were associated with smaller mean regional brain tissue volume and cortical thickness in CN, MCI, and AD; (2) low Aβ1–42 and high t-tau and p-tau181p concentrations were associated with increased rates of regional brain atrophy in CN, MCI, and AD; and (3) the patterns of association were group-specific. In addition, we tested whether abnormal CSF biomarker concentrations and ApoE ε4 status separately or together were associated with higher rates of brain atrophy.
Section snippets
Methods
We examined the baseline regional tissue volume and cortical thickness, and the rate of change in regional tissue volume and cortical thickness across the brain in CN, individuals with MCI, and AD patients. Structural magnetic resonance imaging (MRI) brain scans at multiple time points (4 time point scans — baseline, 6, 12, and 24 months — for CN and AD patients and 5 time point scans — baseline, 6, 12, 18, and 24 months — for individuals with MCI) were acquired at multiple Alzheimer's Disease
Effects of baseline CSF biomarker concentrations on regional mean tissue volumes
The results of associations between biomarkers and mean regional brain tissue volumes (i.e., βCSFbio coefficient) are summarized in Table 2 for those cortical and subcortical ROIs where the baseline CSF biomarker concentrations had significant effect on mean regional tissue volumes (FDR corrected p < 0.05). Listed are both the coefficients from the GLME models (representing change in tissue volume per unit biomarker concentration, i.e., mm3/(pg/mL)) and the likelihood ratio (LR) of the
Discussion
We have 4 major findings: (1) in controls, an association between CSF Aβ1–42 and baseline cortical thickness was observed prominently in regions that generally appear affected in AD. Furthermore, lower CSF Aβ1–42 and higher p-tau181p concentrations were associated with an increase in the rate of ventricular expansion in controls; (2) in MCI subjects, an association was observed between increased CSF tau and decreased baseline caudate volume as well as between lower CSF Aβ1–42 and increased
Disclosure statement
Dr. Tosun, Ms. Truran-Sacrey, Dr. Shaw, and Dr. Trojanowski report no disclosures.
Dr. Schuff received honoraria from the Michael J. Fox foundation, the British Research Council, and Elsevier Publishing company; receives research support from The Michael J. Fox foundation, and Department of Defense (WX), P41 RR023953 (Coinvestigator); P50AG23501 (Coninvestigator).
Dr. Aisen has served as a consultant to Pfizer, Merck, and Novartis.
Dr. Petersen serves as a consultant to Elan Pharmaceuticals, Wyeth
Acknowledgements
Data used in the preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (www.loni.ucla.edu/ADNI). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. Complete listing of ADNI investigators is available at http://www.loni.ucla.edu/ADNI/Collaboration/ADNI_Manuscript_Citations.pdf.
This work is funded by the National
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