Refining Models of Amyloid Accumulation in Alzheimer’s Disease
The knowledge that Alzheimer’s disease begins with a preclinical phase that lasts for 20 years or more has focused researchers’ minds on prevention. However, they need to know more about how fast pathology progresses, how to predict who will develop the disease, and when a person’s symptoms might appear. Speakers at the Alzheimer’s Association International Conference 2016, held July 22-28 in Toronto, presented new pathology, imaging, and cerebrospinal fluid data that offered clues to these mysteries. Talks pinned down the rate of amyloid accumulation, highlighted a region where plaque formation might correlate with imminent cognitive decline, and clarified the temporal relationship between Aβ signals in the CSF and in the brain. Researchers also provided more evidence that inflammatory processes cause the brain to swell early in AD, which could complicate the interpretation of brain volume changes during disease progression and treatment. Ultimately, the new information will sharpen trial selection criteria and inform therapeutic strategies.
How Slowly Does Aβ Build Up?
Many current therapeutic strategies attempt to curb amyloid plaque buildup or clear existing deposits. However, researchers still do not know the rate of Aβ accumulation, or how much they need to remove to preserve brain health. Because everyone’s brain, healthy and otherwise, contains soluble Aβ, what constitutes abnormal levels of the peptide? The advent of amyloid PET may provide an answer to this last question, said Colin Masters of the University of Melbourne in Australia. Using PET, researchers have defined a cutoff between normal and abnormal Aβ levels, and since the majority of the Aβ in the brain occupies detergent-soluble or insoluble pools, both of which show up on PET scans, PET signal intensity should reflect total Aβ, Masters predicted.
To relate PET scans to peptide levels, Masters and colleague Blaine Roberts at Melbourne compared PiB uptake to total Aβ measured in brain lysates from more than a dozen participants in the Australian Imaging, Biomarker & Lifestyle Flagship Study of Ageing (AIBL) who died shortly after undergoing the PET scan. As predicted, the researchers found a tight correlation between the PiB signal in the frontal cortex and the Aβ load in frontal cortex lysates. In people whose brains were at the threshold for amyloid positivity (an SUVR of 1.45 in this case) when they died, the researchers measured about 3.2 μg Aβ per gram of frontal cortex. In people who had a PiB scan typical of AD, with an SUVR of about 2.3, they found 13 μg Aβ per gram of frontal cortex.
To expand this analysis to the whole brain, Masters and Roberts used structural MRI to determine total volume—and by extrapolation, weight—of gray matter in each person’s brain, and multiplied it by the measured amounts of Aβ per gram of tissue. Assuming a similar concentration of Aβ throughout the brain, they calculated that the average PiB-negative brain contained 1.7 mg of Aβ, while AD brains held 6.5 mg. The difference, 4.8 mg, represents Aβ that accumulates in disease. Because it takes two decades or more for Aβ to accumulate in the brain, it likely accrues at a rate of about 28 ng/hour, the researchers calculated. This assumes that the rate of accumulation is a constant, which may not be the case, Masters noted.
Researchers at AAIC found the results intriguing. Clifford Jack of the Mayo Clinic in Rochester, Minnesota, was impressed by the calculation that 1.7 mg of brain amyloid could lie below the detection threshold for PET scans. The fact that this “invisible” Aβ makes up as much as one-fourth of the total in people with “heads full” of amyloid illustrates the limits of a PET scan’s sensitivity, he told Alzforum. Jack emphasized the therapeutic implications of knowing the Aβ accumulation rate. “The rate of reduction in amyloid deposition needed to achieve a meaningful effect could come right out of these calculations,” he suggested.
How does the 28ng/hr rate compare to other estimates? Previously, Randall Bateman and colleagues at Washington University, St. Louis, measured soluble Aβ production and clearance rates in the CSF of healthy volunteers and AD patients using stable isotope-linked kinetics (SILK). Bateman and colleagues found that healthy adults normally produce and clear about 580 ng total Aβ each hour, indicating no accumulation of Aβ. In late-onset AD patients, by contrast, the hourly clearance rate from CSF drops by about one-quarter, or 145 ng/hr, suggesting the peptide could be building up (see Jun 2006 news; Jul 2010 conference news; Potter et al., 2013). This does not necessarily mean that amount of Aβ piles up in the brain every hour, however, since other clearance routes exist besides CSF (see Sep 2015 news). The AIBL data, which measured brain deposition rather than peripheral clearance, suggest that only about 5 percent of the 580 ng/hr production of Aβ becomes trapped in amyloid plaques in people who develop AD.
Boosting the Prognostic Value of Amyloid Imaging
Researchers also want better biomarkers to tell them how close a person is to developing symptoms. Although amyloid accumulates for 20 years before symptoms appear, plaques by themselves are an insensitive marker of imminent decline. Striatal amyloid accumulation may better predict symptom onset than cortical amyloid does, argued Bernard Hanseeuw of Massachusetts General Hospital, Charlestown. Striatal plaques form at later Braak stages, and the presence of striatal, but not cortical, amyloid at autopsy correlates with a diagnosis of AD (see Thal et al., 2002; Beach et al., 2012).
To find out if striatal plaques could flag late preclinical stages, Hanseeuw analyzed brain imaging and cognitive data from 346 participants in the Harvard Aging Brain Study (HABS) and 1,087 in the Alzheimer's Disease Neuroimaging Initiative (ADNI). The whole group comprised 646 cognitively normal participants, 574 with mild cognitive impairment, and 213 with AD. In these cohorts, amyloid PET scans detected striatal amyloid only when cortical amyloid was high, in agreement with postmortem studies. High striatal amyloid also correlated with a high tau PET signal. Overall, Hanseeuw and colleagues found striatal plaques in 94 percent of HABS participants diagnosed with AD, but only 14 percent of the cognitively normal HABS group. The percentages were slightly lower in ADNI, at 68 and 8 percent, respectively. Hanseeuw noted that the PiB scans used in HABS might be more sensitive to striatal amyloid than the florbetapir scans used by ADNI, perhaps because the latter compound binds surrounding white matter more. In addition, ADNI contained a fraction of participants diagnosed with AD who never had the disease, or brain amyloid.
Overall, the data support the idea that those few cognitively normal elderly who had striatal amyloid might be further along in the disease process than those without, Hanseeuw believed. To test this, he studied the association between striatal amyloid and cognitive decline in just the cognitively normal participants. Over one to five years of follow-up, those with striatal plaques at baseline declined twice as fast on cognitive tests as those with cortical plaques only (see image above). People with striatal amyloid also lost more hippocampal volume over the course of the study. “Striatal amyloid could be used to identify cognitively normal elderly who are at the greatest risk of decline,” Hanseeuw claimed.
CSF Versus Imaging
While striatal amyloid may mark the late preclinical phase, Sebastian Palmqvist of Lund University, Sweden, made a case for CSF Aβ42 being one of the earliest preclinical markers of AD. Levels of this fluid biomarker drop as amyloid plaques accumulate in the brain, and this becomes apparent before amyloid PET scans turn positive, Palmqvist claimed. Previous cross-sectional studies had hinted at this, with some participants having low CSF Aβ42 in the absence of an amyloid PET signal, but it was unclear if all of these PET–negative individuals were on track for AD (see Fagan et al., 2009; Mattsson et al., 2015). Confusing matters further, at least one study reported finding a few people with positive amyloid scans and normal CSF Aβ42 (see Landau et al., 2013).
To observe the relationship of the two markers over time, Palmqvist and colleagues Niklas Mattsson and Oskar Hansson at Lund stratified 437 ADNI 2 participants according to whether they were positive or negative on each. For brain amyloid, they used florbetapir PET data, choosing a low, conservative cutoff of 0.79 SUVR for positivity. CSF Aβ42 levels in ADNI2 were determined by the AlzBio3 assay, with the standard cutoff of less than 192 ng/L indicating positivity. After excluding borderline individuals who were within 5 percent of the cutoffs, the researchers found no participants who were CSF–/PET+, but 26 people who were CSF+/PET–, i.e., people whose CSF Aβ levels were already abnormal but whose PET scans were not.
Most people in this group were cognitively normal and stable, Palmqvist said. They had no evidence of elevated CSF tau or hippocampal atrophy. They had also higher CSF Aβ42 levels than the PET+ group, suggesting they were at an earlier stage of disease. Reinforcing this, the PET+ group lost more hippocampal volume over the course of two years than the CSF+/PET– group, and their brain metabolism and memory dwindled more. Importantly, the CSF+/PET– group accumulated Aβ at the same rate (1.2 percent increase in PET scan SUVR per year) as the PET+ group, and three times faster than the CSF–/PET– group, suggesting both of the CSF+ groups were on the path to AD. Given this rate, it would take an average of seven to 10 years for a CSF+/PET– person to become amyloid-positive on a PET scan, Palmqvist calculated (see Palmqvist et al., 2016). Altogether, the findings suggest that CSF measurements can discern amyloid accumulation before PET scans do, and that people with low CSF Aβ generally go on to become amyloid-positive on PET as well, Palmqvist said.
The data engendered lively debate at AAIC. Some researchers speculated that the results illustrate the limitations of florbetapir, and that other tracers might pick up lower levels of accumulation. Palmqvist countered that he has found similar results with flutemetamol, albeit in a cross-sectional study. One audience member wondered if some people with low CSF Aβ42 could represent false positives, for example people who simply make less Aβ. Palmqvist considered this unlikely because they accumulated brain Aβ as fast as those in the CSF+/PET+ group.
Why would soluble Aβ fall so much sooner than it becomes visible as plaques in the brain? Perhaps CSF and PET ligands are measuring different processes, Palmqvist suggested. Some researchers have proposed that CSF Aβ42 drops as the peptide aggregates into prefibrillary deposits and diffuse plaques, while PET detects more mature neuritic plaques. The data argue for separating the CSF Aβ and amyloid PET curves in biomarker staging models, Palmqvist said (see Jan 2010 webinar; Feb 2013 conference news).
A Bigger Brain Can Be Bad
Other biomarkers change dynamically over the course of the disease as well, providing more clues to underlying processes. Christian Haass of Ludwig-Maximilians University, Munich, had earlier reported that levels of a soluble fragment of the microglial receptor TREM2 rise in the CSF in prodromal AD, but stabilize or even drop later on (see Jan 2016 news; Mar 2016 news). The sTREM2 peak may indicate an inflammatory response early in AD, Haass speculated.
At AAIC, Juan Domingo Gispert of the Barcelonaβeta Brain Research Center, Spain, expanded on this idea. Gispert and colleagues compared 45 cognitively normal controls without brain amyloid, 19 cognitively normal people with brain amyloid, 27 people with MCI due to AD, and 23 with mild AD. His was a cross-sectional study. Among cognitively normal people, CSF sTREM2 levels bore no relationship to brain volume. In the MCI group, however, high sTREM2 associated with relatively larger brain volume after accounting for the expected atrophy due to CSF p-tau levels, particularly in the medial and inferior temporal cortices and the precuneus. The AD group showed a trend in that direction as well. The researchers next looked at diffusion-weighted MRI, which measures water diffusivity in the brain and serves as a marker of edema. High sTREM2 went along with low diffusivity in the temporal lobes and precuneus, suggesting the sTREM2-related volume increase was due to inflammation that peaks at the MCI stage (see Gispert et al., 2016).
The data fit with the idea that in a certain phase of the disease process, neurodegeneration features inflammation and local swelling, Gispert said. Several trials of anti-amyloid antibodies have reported shrinking brain volume in the treatment group. This puzzled researchers at the time, because they usually think of brain shrinkage as indicating atrophy and worsening of the disease (see Jul 2004 conference news; Nov 2012 conference news; Apr 2013 conference news). The new data add more evidence for the presence of edema in AD, and reinforce the idea that a temporary drop in volume could be good under some circumstances (see also Aug 2016 conference news).—Madolyn Bowman Rogers
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- HAI—Sharper Curves: Revamping a Biomarker Staging Model
- TREM2 Goes Up in Spinal Fluid in Early Alzheimer’s
- Microglial Marker TREM2 Rises in Early Alzheimer’s and on Western Diet
- Philadelphia: Can a Shrinking Brain Be Good for You?
- CTAD: New Data on Sola, Bapi, Spark Theragnostics Debate
- Brain Imaging in Trials—How to Make It Work?
- DIAN Longitudinal Data Say Cognition Goes Earlier Than Previously Thought
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