Jansen WJ, Ossenkoppele R, Tijms BM, Fagan AM, Hansson O, Klunk WE, van der Flier WM, Villemagne VL, Frisoni GB, Fleisher AS, Lleó A, Mintun MA, Wallin A, Engelborghs S, Na DL, Chételat G, Molinuevo JL, Landau SM, Mattsson N, Kornhuber J, Sabri O, Rowe CC, Parnetti L, Popp J, Fladby T, Jagust WJ, Aalten P, Lee DY, Vandenberghe R, Resende de Oliveira C, Kapaki E, Froelich L, Ivanoiu A, Gabryelewicz T, Verbeek MM, Sanchez-Juan P, Hildebrandt H, Camus V, Zboch M, Brooks DJ, Drzezga A, Rinne JO, Newberg A, de Mendonça A, Sarazin M, Rabinovici GD, Madsen K, Kramberger MG, Nordberg A, Mok V, Mroczko B, Wolk DA, Meyer PT, Tsolaki M, Scheltens P, Verhey FR, Visser PJ, Amyloid Biomarker Study Group, Aarsland D, Alcolea D, Alexander M, Almdahl IS, Arnold SE, Baldeiras I, Barthel H, van Berckel BN, Blennow K, van Buchem MA, Cavedo E, Chen K, Chipi E, Cohen AD, Förster S, Fortea J, Frederiksen KS, Freund-Levi Y, Gkatzima O, Gordon MF, Grimmer T, Hampel H, Hausner L, Hellwig S, Herukka SK, Johannsen P, Klimkowicz-Mrowiec A, Köhler S, Koglin N, van Laere K, de Leon M, Lisetti V, Maier W, Marcusson J, Meulenbroek O, Møllergård HM, Morris JC, Nordlund A, Novak GP, Paraskevas GP, Perera G, Peters O, Ramakers IH, Rami L, Rodríguez-Rodríguez E, Roe CM, Rot U, Rüther E, Santana I, Schröder J, Seo SW, Soininen H, Spiru L, Stomrud E, Struyfs H, Teunissen CE, Vos SJ, van Waalwijk van Doorn LJ, Waldemar G, Wallin ÅK, Wiltfang J, Zetterberg H. Association of Cerebral Amyloid-β Aggregation With Cognitive Functioning in Persons Without Dementia. JAMA Psychiatry. 2018 Jan 1;75(1):84-95. PubMed.

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Comments

  1. After having read the manuscript, I am struck (again!) by the powerful predictive effect of age and ApoE4 on the likelihood of high amyloid burden in clinically normal (CN) older adults. Time and again this has been shown, however, it is interesting to see another demonstration of the importance of these factors in such a large multicenter study.

    Another important component of this study that deserves a remark up front (although, Jansen and colleagues have previously published from these data in 2015), is the sheer size of the sample. Even with ~20 percent missing data across the cohorts, this study reports on ~2000 CN individuals with a memory score, which is quite staggering. The strength of this type of study is the ability to have the statistical power to detect relatively small effects, which is arguably the case with the cross-sectional relationship between amyloid and cognition, as accurately acknowledged by the authors. With this large dataset, it is clear that the MMSE screening tool does not perform as well as other memory tests to predict high amyloid burden, however, it is slightly disheartening to see that “low performance” on the combined aggregate memory tests did not survive forward selection to be included as a sensitive predictor of high amyloid. I agree with the authors, however, in that I don’t think that this throws out the idea of a cognitive test being a useful screening tool in clinical trials; the current analyses are attempting to determine the effect of “low memory” rather than the effect of a neuropsychological task per se. The rather large limitation of big data analysis is that cruder data gradients need to be applied in order to make conservative estimates about an effect across a range of different memory tests. Here, the authors have been somewhat limited in their ability to make a final statement about the efficacy of using a memory test as a screening tool, particularly those that are sensitive and challenging neuropsychological measures of memory. In this case, more sophisticated data harmonization techniques will need to be applied (i.e., item response theory or latent factor analysis, Gross et al., 2015) in order to better align cognitive test performance across studies.

    Further, and in the same vein, it will be nice to see big data analyses being reported with a continuous measure of amyloid rather than amyloid status alone. While harmonizing across CSF and PET measures is perhaps a future endeavor, more and more PET studies are being aggregated to allow for much larger analyses. Reprocessing of PET data, and transformations across different PET tracers, will allow for greater ease when analyzing and interpreting this data, which will be very exciting, and will give greater insights into gradients of amyloidosis and cognitive decline that are more likely to represent the insidious nature of the disease. 

    With regard to age, that low memory performance doubled the likelihood of high amyloid over the age of 80 is fascinating. One issue that is not an easy one to handle is related to survivor bias. At what point does the low memory/high amyloid group become so sparse with survivors that it becomes an entirely different group from the low memory/low amyloid group altogether? Clearly, the next stage in this project will be to look ahead to longitudinal and survival analyses—which I am looking forward to reading!

    References:

    Jansen WJ, Ossenkoppele R, Knol DL, Tijms BM, Scheltens P, Verhey FR, Visser PJ, Amyloid Biomarker Study Group, Aalten P, Aarsland D, Alcolea D, Alexander M, Almdahl IS, Arnold SE, Baldeiras I, Barthel H, van Berckel BN, Bibeau K, Blennow K, Brooks DJ, van Buchem MA, Camus V, Cavedo E, Chen K, Chetelat G, Cohen AD, Drzezga A, Engelborghs S, Fagan AM, Fladby T, Fleisher AS, van der Flier WM, Ford L, Förster S, Fortea J, Foskett N, Frederiksen KS, Freund-Levi Y, Frisoni GB, Froelich L, Gabryelewicz T, Gill KD, Gkatzima O, Gómez-Tortosa E, Gordon MF, Grimmer T, Hampel H, Hausner L, Hellwig S, Herukka SK, Hildebrandt H, Ishihara L, Ivanoiu A, Jagust WJ, Johannsen P, Kandimalla R, Kapaki E, Klimkowicz-Mrowiec A, Klunk WE, Köhler S, Koglin N, Kornhuber J, Kramberger MG, Van Laere K, Landau SM, Lee DY, de Leon M, Lisetti V, Lleó A, Madsen K, Maier W, Marcusson J, Mattsson N, de Mendonça A, Meulenbroek O, Meyer PT, Mintun MA, Mok V, Molinuevo JL, Møllergård HM, Morris JC, Mroczko B, Van der Mussele S, Na DL, Newberg A, Nordberg A, Nordlund A, Novak GP, Paraskevas GP, Parnetti L, Perera G, Peters O, Popp J, Prabhakar S, Rabinovici GD, Ramakers IH, Rami L, Resende de Oliveira C, Rinne JO, Rodrigue KM, Rodríguez-Rodríguez E, Roe CM, Rot U, Rowe CC, Rüther E, Sabri O, Sanchez-Juan P, Santana I, Sarazin M, Schröder J, Schütte C, Seo SW, Soetewey F, Soininen H, Spiru L, Struyfs H, Teunissen CE, Tsolaki M, Vandenberghe R, Verbeek MM, Villemagne VL, Vos SJ, van Waalwijk van Doorn LJ, Waldemar G, Wallin A, Wallin ÅK, Wiltfang J, Wolk DA, Zboch M, Zetterberg H. Prevalence of cerebral amyloid pathology in persons without dementia: a meta-analysis. JAMA. 2015 May 19;313(19):1924-38. PubMed.

    Gross AL, Mungas DM, Crane PK, Gibbons LE, MacKay-Brandt A, Manly JJ, Mukherjee S, Romero H, Sachs B, Thomas M, Potter GG, Jones RN. Effects of education and race on cognitive decline: An integrative study of generalizability versus study-specific results. Psychol Aging. 2015 Dec;30(4):863-80. Epub 2015 Nov 2 PubMed.

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