Miami: Longitudinal Amyloid PET Data Start Converging

Series - Human Amyloid Imaging 2012:

At the 6th Annual Human Amyloid Imaging Conference, held 12-13 January 2012 in Miami, Florida, researchers updated each other on what their respective longitudinal studies were showing. By and large, their studies appear to support the notion that amyloid deposition heralds future cognitive decline.

Chris Rowe of the University of Melbourne, Australia, presented two-year data on 45 people who had mild cognitive impairment at baseline and were followed with clinical and neuropsychological testing every six months and an amyloid PET scan every year (Ong et al., 2012). This study used florbetaben, an 18F radiotracer that is roughly equivalent to florbetapir and flutemetamol, according to scientists. At baseline, half of the participants had high florbetaben retention; at that time, their composite memory scores, even their MMSE, tended to be lower. Two years later, their florbetaben retention had grown by 3.1 percent, Rowe noted. Importantly, 79 percent of them had progressed to Alzheimer’s dementia, whereas 24 percent of the people with low florbetaben retention at baseline had progressed to other diseases such as frontotemporal dementia or progressive supranuclear palsy. “We see a very strong correlation between baseline florbetaben levels and subsequent memory decline,” Rowe said.

In this study, Rowe directly compared MRI and florbetaben PET for their ability to predict progression from mild cognitive impairment (MCI) to Alzheimer’s dementia (AD). Besides their amyloid scans, the study participants also received an MRI scan, and the Australian researchers visually scored those with two published academic methods and an FDA-approved commercial program called NeuroQuant. The upshot? The amyloid scan outperformed all three ways of reading the MRI in specificity and in overall accuracy, Rowe reported. Within the methods of MRI interpretation, the commercial program was most accurate, Rowe added.

This study addressed one more wrinkle about MCI. When splitting the group into early (eMCI) and late patients, a gap opened up. Of the late MCI cases, 79 percent were amyloid positive at baseline, and of the eMCI cases, only 40 percent. When applying the same comparison of prediction by florbetaben versus by MRI to these groups separately, the researchers found that amyloid PET outdid the MRI measures in eMCI by far more than in late MCI. Amyloid PET is more valuable in the early MCI group, largely because late MCI itself already appears highly specific for AD, Rowe said. This mirrors similar data by Cliff Jack’s group at the Mayo Clinic in Rochester, Minnesota, who previously reported that the predictive ability of amyloid scans flattens out somewhat as it nears its plateau (Jack et al., 2010). Trialists at HAI said that amyloid imaging still should be included in selecting patients at all stages of MCI for multicenter trials, because clinics vary widely in how they apply MCI criteria, and some have low conversion rates.

Similar results came out of a different two-year study presented by Michael Pontecorvo of Avid Radiopharmaceuticals. All coauthors of this study are employees of Avid. Thirty-six people with MCI and 49 cognitively normal people underwent a florbetapir scan at baseline and once again some 23 months later. First author Abhinay Joshi and colleagues found that, at baseline, 44 percent of the former and 20 percent of the latter were amyloid positive (Joshi et al., 2012). The cognitively impaired participants in this study are eMCI, with a CDR of 0.5 and an MMSE above 24, and hence match up well with the 40 percent florbetaben positivity Rowe found in the Australian eMCI volunteers, Pontecorvo noted in his talk. The amyloid-positive people had about 3 percent more amyloid the second time around, a small increase that cannot be seen visually but requires quantification. No amyloid-positive person reverted. Most amyloid-negative MCI patients stayed negative two years later. “They are not on the path to AD,” Pontecorvo told the audience.

On a poster with three- to five-year data from AIBL, Rowe’s colleague Victor Villemagne showed that among 118 cognitively normal participants, those with faster amyloid deposition as measured by PIB declined significantly faster on memory tests than did fellow participants with slower or no amyloid deposition (Villemagne et al., 2012). The same was true for people with MCI and, interestingly, AD patients. Similarly, Miranka Wirth of the University of California, Berkeley, presented a poster suggesting that, among 38 cognitively normal older people undergoing three annual neuropsychological exams, those who were positive for PIB declined on memory. Susan Landau at UC Berkeley looked at amyloid deposition and subsequent cognitive function in 325 ADNI participants across the spectrum of normal, early, and late MCI and AD who had had florbetapir scans. In this sample, too, numbers were similar, that is, amyloid positivity in 30 percent of normal, 43 percent eMCI, 66 percent late MCI. Florbetapir-positive volunteers declined more steeply on episodic memory than florbetapir-negative fellow volunteers. The decline was pronounced in people with MCI and subtle but detectable in cognitively normal people with amyloid deposition, Landau reported (Landau and Jagust, 2012).

Alex Becker of Massachusetts General Hospital is working to parse out how amyloid deposition affects synaptic activity over time by analyzing both amyloid and FDG-PET scans taken about two years apart in cognitively normal and mildly impaired study participants. Becker analyzed data from ADNI1 and the Harvard Aging Brain sample, for a total of 105 cognitively normal and 166 mildly impaired people. Becker looked not at group differences but at declines within a given person from baseline to two years later. He found that, in cognitively normal people, whether a person had amyloid deposits did not affect their age-related decline in glucose metabolism over the next two years. In contrast, people with MCI not only started out with lower metabolism if they had amyloid than if they did not, but their glucose metabolism also declined more steeply over the next two years. Becker suspects that the apparent lack of a relationship in cognitive normals at this point in the analysis may be an artificial null result that results from increases in some brain areas and decreases in others (Becker et al., 2012).

Overall, most available longitudinal studies to date of normal and mildly impaired people appear to tell the same story. “One big thing I learned is that, with the longitudinal studies, we are getting much better convergence between studies than when we looked at cross-sectional data before. That is a great development,” said Sue Resnick of the National Institute on Aging.—Gabrielle Strobel.

This is Part 7 of a nine-part series. See also Part 1, Part 2, Part 3, Part 4, Part 5, Part 6, Part 8, Part 9. Download a PDF of the entire series.

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References

News Citations

  1. News Focus: 2012 Human Amyloid Imaging Conference
  2. Miami: Amyloid PET in the Clinic: What Are the Issues?
  3. Miami: Scan and Tell? Amyloid Imaging Confronts Disclosure Dilemma
  4. Miami: Can the Naked Eye Tell When a Scan Is Positive?
  5. Miami: When Does Amyloid Deposition Start in Familial Alzheimer’s?
  6. Miami: Age and Amyloid—What Has ApoE Got to Do With It?
  7. Miami: Diagnosis and Amyloid Scan Can Be at Odds
  8. Miami: Scientists Angle for Way to Image Tangle

Paper Citations

  1. Ong K, Villemagne VL, Bahar-Fuchs A, Lamb F, Reininger C, Putz B, Rohde B, Masters CL, Rowe CC. A Two-Year Longitudinal Assessment of Aβ Deposition in Late MCI with8F-Florbetaben. Human Amyloid Imaging Abstract. 2012 Jan 1;
  2. Jack CR, Wiste HJ, Vemuri P, Weigand SD, Senjem ML, Zeng G, Bernstein MA, Gunter JL, Pankratz VS, Aisen PS, Weiner MW, Petersen RC, Shaw LM, Trojanowski JQ, Knopman DS, . Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease. Brain. 2010 Nov;133(11):3336-48. PubMed.
  3. Joshi A, Pontecorvo M, Breault C, Lu M, Mintun M, Carpenter A, Skorvonsky D. Use of Florbetapir-PET to Assess Progression of Amyloid Burden over Time. Human Amyloid Imaging Abstract. 2012 Jan 1;
  4. Villemagne VL, Ellis KA, Chetelat G, Bourgeat P, Jones G, Salvado O, Martins R, Ames D, Masters CL, Rowe CC. Relation between Rates of Aβ Deposition, Apoe Genotype and Cognition: Results from-5 Year Longitudinal Study. Human Amyloid Imaging Abstract. 2012 Jan 1;
  5. Landau S, Jagust W. Amyloid Deposition, Hypometabolism, and Cognitive Trajectories in the ADNI Population. Human Amyloid Imaging Abstract. 2012 Jan 1;
  6. Becker JA, Gidicsin C, Maye J, Pepin L, Sperling R, Johnson K. Amyloid-Modulated Age-Related Changes in FDG Metabolism in Normal and Mildly Impaired Elderly. Human Amyloid Imaging Abstract. 2012 Jan 1;

Other Citations

  1. Download a PDF of the entire series.

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