Prior research in Europe and the U.S. established low CSF Aβ1-42 and elevated CSF tau and phosphorylated tau-181P (p-tau) as early indicators of AD pathogenesis (see, e.g., ARF related news story on Fagan et al., 2007). More recently, the ADNI fluid biochemistry study, led by Leslie Shaw, University of Pennsylvania, Philadelphia, defined threshold concentrations of spinal fluid Aβ42 and tau that associated with disease (Shaw et al., 2009). Shaw and colleagues identified an Aβ42 cut point of 192 pg/ml or lower as diagnostic for AD, by analyzing pre-mortem CSF samples from autopsy-confirmed AD patients and age-matched cognitively normal research participants at the university’s AD research center. Applied to the ADNI dataset, these CSF criteria correctly identified AD patients more than 96 percent of the time.

In the current paper, first author Geert De Meyer, Ghent University, Belgium, and colleagues, including Shaw, chose a different strategy to tackle the same problem of identifying CSF thresholds that discriminate groups of people with and without AD. They capitalized on an uncanny pattern in the data from Shaw’s 2009 study: the normals fell into two fairly distinct subgroups—one with an AD-like CSF profile, the other without. This prompted De Meyer and colleagues to use a statistical approach known as mixture modeling to identify naturally occurring AD signatures, or cut points, based on CSF Aβ42 and p-tau181, in more than 400 ADNI participants, aged 55 to 90, with AD, mild cognitive impairment (MCI), or normal cognition. The novelty here is that De Meyer and colleagues determined their diagnostic cut points without any clinical or diagnostic information on the subjects. They did this to avoid bias-related problems with more commonly used methods for assessing biomarkers.

To validate the CSF threshold values coming from this clinically blind approach, the researchers analyzed two separate populations outside of ADNI: an autopsy-proven cohort in Belgium, and a subset of patients from a different European longitudinal study. In the Belgian cohort, 65 of 73 people had an AD diagnosis at autopsy, and the CSF criteria correctly classified 94 percent of these patients. In the European study (Hansson et al., 2006), 57 of 175 MCI patients converted to AD within five years, and the CSF threshold values identified 100 percent of these converts. Furthermore, 36 percent of cognitively normal ADNI seniors had AD-like CSF reads, which “underscores the presence of AD pathology before the onset of symptoms,” the authors write.

Perhaps as impressive was the fact that the study by De Meyer et al. arrived at a CSF cut point of 188 pg/ml, virtually identical to the 192 pg/ml coming from Shaw’s earlier work, which used a different study design and statistical methods. “What had been a huge issue is that numerical values (for CSF thresholds) varied all over the place,” Shaw told ARF. “We're starting to see better replication of the quantitative results, and that's very important.” Both studies used the same Innogenetics platform for their immunoassays, and each found the CSF data falling neatly into two bins, those with and without an AD signature, even within the normal groups.

At ICAD, Edland reported strikingly similar findings from a CSF biomarkers analysis done in collaboration with Elaine Peskind, University of Washington, Seattle, who served as a panelist in a recent ARF Webinar on the value of CSF analysis (see ARF Live Discussion). Edland and colleagues also used the Innogenetics platform, even applying the same unbiased statistical methods, to analyze 303 cognitively normal volunteers recruited at five AD research centers. These are not ADNI participants. Their CSF Aβ42 cut-off value came out between 190 and 200 pg/ml, Edland told ARF, which is in close proximity to the thresholds reported in the papers by De Meyer et al. and Shaw et al.

Edland’s study was unique in that it included younger adults. Of his volunteers, 125 were between the ages of 20 and 55. “The importance of having all those young normals is that it really nails down what a ‘normal’ CSF profile is,” Edland said in a phone interview. This set the stage for the “dramatic” finding in the older subgroup. “Many might guess that you've got normal CSF Aβ levels as young adults, and as you acquire disease, the [CSF readout] would drift to an AD-like level,” he said. However, CSF Aβ42 levels in the 56-and-older group were clearly bimodal, confirming the results of Shaw’s 2009 paper, which first described this CSF Aβ42 distribution in normals. “One mode looks just like the young normals, and the other looks just like AD,” said Edland. “The fascinating thing about the bimodal distribution is that it suggests the transition between normal and AD CSF profiles happens very quickly. It's not a smear of data. People jump from one distribution to the other. I think that is the most important message here.”

When they considered ApoE genotype, the researchers found that, among cognitively normal E4 carriers ages 70 and up, two-thirds have an AD-like CSF profile, Edland said. By contrast, only a fourth of similarly aged E4 non-carriers had the AD signature.

Taken together, the recent findings should fuel a growing movement to support CSF analysis, which has for years gotten short shrift because of some doctors’ reluctance to perform spinal taps (aka “lumbar punctures”) and patients’ unwillingness to receive the invasive procedure. On this point, an Archives of Neurology commentary on the paper by De Meyer et al. notes that spinal taps are “no more invasive than other outpatient procedures such as endoscopies that millions of Americans tolerate each year.” Moreover, the cost of CSF Aβ and tau readouts pales in comparison to “the consulting physician’s bill, the charge for neuropsychological testing, and the cost of a magnetic resonance brain scan” at most centers, write A. Zara Herskovits of Brigham and Women’s Hospital, and John Growdon of Massachusetts General Hospital, both in Boston.

Routine clinical use is still a way off, partly due to quality control and manufacturing issues. However, experts have launched worldwide initiatives to address these challenges (see ARF related news story), and included CSF measures among a set of biomarkers in a draft revision of AD diagnostic criteria (see ARF related news story).

As biomarker studies in milder populations proceed apace (see ARF coverage of presentations at this year’s International Conference on Alzheimer’s Disease), some think CSF assays warrant more attention in some research settings. “I feel the tests are ready for prime time for inclusion in treatment trials, for example,” Shaw told ARF, noting that CSF biomarkers could help identify participants at high or low disease risk.

Furthermore, “gazing into the future when there are neuroprotective medications for AD, we can envision a recommendation that CSF analyses be implemented as a screening test to identify clinically healthy individuals at risk for MCI and AD,” Herskovits and Growdon write. “The information gained would enable early application of treatments to delay onset of symptoms or slow progression of cognitive impairments.”—Esther Landhuis.

References:
De Meyer G, Shapiro F, Vanderstichele H, Vanmechelen E, Engelborghs S, De Deyn PP, Coart E, Hansson O, Minthon L, Zetterberg H, Blennow K, Shaw L, Trojanowski J for the Alzheimer’s Disease Neuroimaging Initiative. Diagnosis-independent Alzheimer disease biomarker signature in cognitively normal elderly people. Arch Neurol. August 2010;67(8):949-956. Abstract

Herskovits AZ and Growdon JH. Sharpen that needle. Arch Neurol. August 2010;67(8):918-920. Abstract