The profile of cerebrospinal fluid (CSF) amyloid-β (Aβ), tau, and other biomarkers associated with Alzheimer’s disease depends in part on a family history of AD, and the markers’ trajectory over time depends on the stage of disease. As laid out in two papers in the October Archives of Neurology, the findings strengthen the case for using biomarkers to determine who is at risk for AD before symptoms develop (see ARF related news story on Schott et al., 2010). “This type of research is so important. Everyone believes that Alzheimer’s starts early and we need ways to detect it,” said Henrik Zetterberg at the Sahlgrenska University Hospital in Sweden, who was not involved in the work.

First author Chengjie Xiong and colleagues took a snapshot of the biomarker profiles of more than 260 cognitively normal middle-aged to older people participating in the Adult Children Study (ACS) at Washington University. They found that a family history of the disease influences their levels. “If people have a family history of Alzheimer’s, their biomarker profiles look a bit more like those of people with the disease,” said Zetterberg. In the second paper, Raymond Lo in the laboratory of William Jagust at the University of California, Berkeley, and colleagues describe the changes in biomarkers that occur over the course of two to three years in more than 800 people participating in the Alzheimer’s Disease Neuroimaging Initiative (ADNI). They found that CSF molecules and brain volume not only change over time, but do so at different rates in people who are cognitively normal versus those with mild cognitive impairment (MCI) or AD.

Because some of these changes happen before any noticeable cognitive symptoms, they could be used to identify people in the preclinical stage of AD. The idea of treating patients at this stage has gained momentum in recent years. “It is incumbent on the AD research community to educate our colleagues, the public, and regulatory agencies to accept that it is necessary to treat AD before it is symptomatic,” wrote Archives editor Roger Rosenberg in an accompanying editorial.

When Xiong and colleagues analyzed CSF amyloid-β42 (Aβ42), in the ACS cohort, they found that the amounts were lower in older than in younger people, and this difference was more pronounced for those with a family history of AD. The presence of the ApoE4 allele, the major genetic risk factor for sporadic AD, did not change this relationship. Rather, people with the E4 allele have lower levels of CSF Aβ42 (see Tosun et al., 2010) than those without it, and family history of AD exacerbated this difference. The scientists also found differences in other disease indicators, such as CSF tau levels, and in the amount of brain amyloid detected by positron emission tomography using Pittsburgh compound B, depending on whether people had a family history of AD or not.

The study supports growing evidence that genetic factors beyond ApoE influence biomarker variations (see ARF related news story on Sheline et al., 2010; Kauwe et al., 2010). Genomewide association studies also implicate several genes that predispose to AD (see ARF related news story on Naj et al., 2011 and Hollingworth et al., 2011 and AlzGene GWAS summary). However, people who have a family history share not only genes with their affected forebears. “It is possible that environmental factors and diet may also play a role in these biomarker changes,” said Morris. “It does not negate the role of genetics but raises some additional areas of research.” Xiong cautioned that this cross-sectional study did not determine whether the measured changes predict disease.

Toward that goal, Lo and other ADNI investigators analyzed CSF samples collected from participants 55 to 90 years of age over the course of three years. Surprisingly, perhaps, the scientists found no significant changes in CSF tau measurements in either group. They did find that levels of CSF Aβ42 fell over time, dropping faster in people with normal cognition than in those with MCI or AD. Glucose metabolism and brain hippocampal volume also dropped over time, but did so more slowly in cognitively normal people than in people with MCI and AD. These results suggest that amyloid deposition occurs before hypometabolism or hippocampal atrophy. “Amyloid changes most likely occur before anything else, early in the disease process,” said Zetterberg. The ADNI group had previously reported biomarker changes in the first year of follow-up of participants (Beckett et al., 2010); this study extends the results to up to 36 months.

The findings are largely consistent with the model of biomarker trajectories proposed by Clifford Jack, Mayo Clinic, Rochester, Minnesota, and colleagues (Jack et al., 2010), suggesting that different biomarkers reflect different pathologies at different stages of the disease. Studies are now starting to provide actual numbers for those projections by measuring the slope by which each marker changes at each stage. “It is a good start, but we are still far away from realizing the curvilinear trajectories since we do not have sufficient data to draw a good curve,” wrote Lo. “Jack's model used logistic curves to describe various biomarker trajectories, which were biologically plausible but hard to prove. The model is still mostly valid, except for tau, which did not significantly change over time during the follow-up period.” Lo noted the study was limited by the length of observation.

The researchers found that all biomarker changes correlated with declines in cognitive function in people with MCI and AD but not in cognitively normal people (see ARF related news story on Fjell et al., 2010 and Stomrud et al., 2010). Why this association does not apply to healthy people is not clear. “One possibility is that our assessment tools are designed to measure overt cognitive impairment, but are not sensitive enough to capture the decline in cognitively normal people,” wrote Lo. Research does predict that normal people in the ADNI cohort do begin to lose cognitive function if they test positive for brain amyloid at baseline (see ARF related news story and ARF news story.—Laura Bonetta


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News Citations

  1. Research Brief: How Normal Is Normal? ADNI Data Begs The Question
  2. A Foreshadowing? ApoE4 Disrupts Brain Connectivity in Absence of Aβ
  3. Large Genetic Analysis Pays Off With New AD Risk Genes
  4. CSF Biomarkers Track With Atrophy, Cognition in Normal Aging
  5. Miami: Is Human Amyloid Imaging Ready for Clinical Trials?
  6. Detecting Familial AD Ever Earlier: Subtle Memory Signs 15 Years Before

Paper Citations

  1. . Increased brain atrophy rates in cognitively normal older adults with low cerebrospinal fluid Aβ1-42. Ann Neurol. 2010 Dec;68(6):825-34. PubMed.
  2. . Relations between brain tissue loss, CSF biomarkers, and the ApoE genetic profile: a longitudinal MRI study. Neurobiol Aging. 2010 Aug;31(8):1340-54. PubMed.
  3. . APOE4 allele disrupts resting state fMRI connectivity in the absence of amyloid plaques or decreased CSF Aβ42. J Neurosci. 2010 Dec 15;30(50):17035-40. PubMed.
  4. . Validating predicted biological effects of Alzheimer's disease associated SNPs using CSF biomarker levels. J Alzheimers Dis. 2010;21(3):833-42. PubMed.
  5. . Common variants at MS4A4/MS4A6E, CD2AP, CD33 and EPHA1 are associated with late-onset Alzheimer's disease. Nat Genet. 2011 May;43(5):436-41. Epub 2011 Apr 3 PubMed.
  6. . Common variants at ABCA7, MS4A6A/MS4A4E, EPHA1, CD33 and CD2AP are associated with Alzheimer's disease. Nat Genet. 2011 May;43(5):429-35. PubMed.
  7. . The Alzheimer's Disease Neuroimaging Initiative: Annual change in biomarkers and clinical outcomes. Alzheimers Dement. 2010 May;6(3):257-64. PubMed.
  8. . Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol. 2010 Jan;9(1):119-28. PubMed.
  9. . CSF biomarkers in prediction of cerebral and clinical change in mild cognitive impairment and Alzheimer's disease. J Neurosci. 2010 Feb 10;30(6):2088-101. PubMed.
  10. . Correlation of longitudinal cerebrospinal fluid biomarkers with cognitive decline in healthy older adults. Arch Neurol. 2010 Feb;67(2):217-23. PubMed.

External Citations

  1. Adult Children Study
  2. Alzheimer’s Disease Neuroimaging Initiative
  3. AlzGene GWAS summary

Further Reading


  1. . Evidence for ordering of Alzheimer disease biomarkers. Arch Neurol. 2011 Dec;68(12):1526-35. PubMed.

Primary Papers

  1. . Longitudinal change of biomarkers in cognitive decline. Arch Neurol. 2011 Oct;68(10):1257-66. PubMed.
  2. . Role of family history for Alzheimer biomarker abnormalities in the adult children study. Arch Neurol. 2011 Oct;68(10):1313-9. PubMed.
  3. . Treat Alzheimer disease before it is symptomatic. Arch Neurol. 2011 Oct;68(10):1237-8. PubMed.