Studies of familial and sporadic Alzheimer’s disease paint a remarkably consistent picture of how biomarkers change in preclinical stages. Now, new cross-sectional biomarker data from the Alzheimer’s Prevention Initiative’s Colombian kindred further solidify these models. Published in the January 12 JAMA Neurology, the data in their broad strokes resemble findings from early onset families in the Dominantly Inherited Alzheimer Network (DIAN). A few intriguing discrepancies emerged as well, although it was unclear if these represented differences in the underlying pathology, or an artifact of how biomarkers are measured. “The next question is whether these data will translate to what is happening longitudinally,” noted Adam Fleisher, who led the study while at Banner Alzheimer’s Institute, Phoenix. He now works at Eli Lilly.
“The results are remarkably consistent with what we have found in DIAN,” Randall Bateman at Washington University in St. Louis wrote to Alzforum. “This further supports a consistent finding of Alzheimer’s biomarker changes 15 to 20 years before symptom onset, and suggests an order of events leading up to cognitive decline. The authors should be congratulated on a heroic effort and analysis—it is a tour de force accomplishment.”
Previously, API reported amyloid imaging data from the same Colombian cohort, comprised of 32 mutation carriers and 22 non-carriers between 20 and 60 years old. Seven of the carriers were diagnosed with mild cognitive impairment, and five with AD, with the remainder cognitively normal. In carriers, fibrillar amyloid became abnormal around 28 years of age, or about 16 years before the expected age of cognitive impairment, and plateaued 10 years later, the researchers found (see Nov 2012 news). In a separate 2012 paper, Banner scientists also described mixed biomarker data from a younger group in the Colombian kindred. In these 18- to 26-year-olds, the researchers saw signs of shrunken brain volume and abnormal brain-activation patterns in the absence of detectable amyloid pathology (see also Dec 2011 conference news; Mar 2012 conference news).
API Biomarker Curves. Biomarkers become progressively more abnormal in mutation carriers; circles represent the age at which each marker deviates significantly from levels in non-carriers. [Copyright © 2015 American Medical Association. All rights reserved.]
The new paper focuses on the 20- to 60-year-old cohort, comparing previous amyloid PET results to structural and functional imaging and fluid biomarkers (see image above). The first biomarker to move was Aβ42 in cerebrospinal fluid (CSF), which deviated from normal levels around 24 years of age, or 20 years before expected cognitive impairment. Amyloid imaging followed at 16 years before symptom onset, then waning brain metabolism was seen with FDG PET at 15 years beforehand. At the same time, levels of CSF total tau shot up, while phosphorylated tau reached abnormal levels shortly thereafter, at 13 years out. Hippocampal volume was the last to budge, becoming abnormal about six years before expected symptom onset. The first subtle cognitive deficits in tests of word recall also appeared at this time.
The findings parallel those from DIAN, which likewise reported CSF Aβ42 moving first, followed by abnormal amyloid imaging and elevated CSF tau, both occurring around 15 years before symptom onset (see Jul 2012 news; Aug 2012 conference news). “We were intrigued to see changes in spinal fluid Aβ before changes in amyloid PET, as the DIAN study did. It was nice to confirm that,” Fleisher told Alzforum.
Nonetheless, some differences cropped up as well. In the DIAN cohort, abnormal brain glucose metabolism came later, at 10 years before symptom onset, while hippocampal volume deviated sooner, as early as 15 years prior. In addition, DIAN participants showed the first signs of cognitive slippage on a logical memory test at 10 years out. “I am rather surprised by the differences,” Gaël Chételat at INSERM-EPHE-University of Caen, France, wrote to Alzforum. “These might partly be due to methodological differences in the way the biomarkers are measured, as this is known to have a considerable impact on the findings. … Of course, this might also reflect differences between the genetic variants.” The Colombian kindred carries a single E280A presenilin 1 mutation, whereas the DIAN cohort includes 51 different mutations in APP or presenilin.
For the metabolic differences, Fleisher agreed that either explanation might fit. However, he believes methodological differences explain other discrepancies. For example, both the API and DIAN datasets record the first changes in hippocampal volume around 15 years before symptom onset, but due to differences in the statistical analysis, the DIAN study reports significance earlier than API, he said. In addition, the two studies calculate age of onset differently, with DIAN using the age at which people first notice memory problems, and API using the age at which doctors formally diagnose mild cognitive impairment. This may also lead to some differences in biomarker staging, Fleisher said.
Fleisher pointed out that although the API cohort is smaller than the DIAN group, it has the advantage of including people only from the same ethnic group and environment and having only a single presenilin 1 mutation, presumably lessening variability in the pathological presentation. “The pathology has a well-described natural history of how it progresses clinically over time. Therefore, what we are seeing in cross-section analysis likely maps to what we would see longitudinally,” Fleisher predicted. Banner collects longitudinal data from this cohort as well, but has not published on this yet. The first longitudinal data from DIAN revealed a surprise, with CSF tau dropping after symptoms appeared (see Mar 2014 news). To date, Banner has not seen this in the API cohort, Fleisher said. “We need to duplicate the finding in other datasets, and gain a better understanding of whether it happens in sporadic AD as well.”
So far, data from both familial studies echo those from longitudinal studies of sporadic AD (see Apr 2013 conference news), and conform well to models of biomarker progression put forth by Clifford Jack at the Mayo Clinic in Rochester, Minnesota, and others (see Feb 2013 conference news). API mainly diverges from the Jack model in showing a much earlier drop in brain metabolism. Otherwise, the data fit closely, including CSF Aβ42 changes preceding those in amyloid PET, Fleisher said. In the API dataset, some of the curves look linear rather than sigmoid, but Fleisher noted that this is likely to be an artifact of the limited data points and age range examined. Other researchers have noted that some biomarkers change in a roughly linear fashion during prodromal disease stages (see Dec 2014 conference news).—Madolyn Bowman Rogers