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Brain PET amyloid and neurodegeneration biomarkers in the context of the 2018 NIA-AA research framework: an individual approach exploring clinical-biomarker mismatches and sociodemographic parameters

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A Correction to this article was published on 26 June 2020

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Abstract

Purpose

[18F]FDG-PET and [11C]PIB-PET are validated as neurodegeneration and amyloid biomarkers of Alzheimer’s disease (AD). We used a PET staging system based on the 2018 NIA-AA research framework to compare the proportion of amyloid positivity (A+) and hypometabolism ((N)+) in cases of mild probable AD, amnestic mild cognitive impairment (aMCI), and healthy controls, incorporating an additional classification of abnormal [18F]FDG-PET patterns and investigating the co-occurrence of such with A+, exploring [18F]FDG-PET to generate hypotheses in cases presenting with clinical-biomarker “mismatches.”

Methods

Elderly individuals (N = 108) clinically classified as controls (N = 27), aMCI (N = 43) or mild probable AD (N = 38) were included. Authors assessed their A(N) profiles and classified [18F]FDG-PET neurodegenerative patterns as typical or non-typical of AD, performing re-assessments of images whenever clinical classification was in disagreement with the PET staging (clinical-biomarker “mismatches”). We also investigated associations between “mismatches” and sociodemographic and educational characteristics.

Results

AD presented with higher rates of A+ and (N)+. There was also a higher proportion of A+ and (N)+ individuals in the aMCI group in comparison to controls, however without statistical significance regarding the A staging. There was a significant association between amyloid positivity and AD (N)+ hypometabolic patterns typical of AD. Non-AD (N)+ hypometabolism was seen in all A− (N)+ cases in the mild probable AD and control groups and [18F]FDG-PET patterns classified such individuals as “SNAP” and one as probable frontotemporal lobar degeneration. All A− (N)− cases in the probable AD group had less than 4 years of formal education and lower socioeconomic status (SES).

Conclusion

The PET-based staging system unveiled significant A(N) differences between AD and the other groups, whereas aMCI and controls had different (N) staging, explaining the cognitive impairment in aMCI. [18F]FDG-PET could be used beyond simple (N) staging, since it provided alternative hypotheses to cases with clinical-biomarker “mismatches.” An AD hypometabolic pattern correlated with amyloid positivity. Low education and SES were related to dementia in the absence of biomarker changes.

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Change history

  • 26 June 2020

    In the last paragraph of the subsession “Recruitment of the study population and clinical Evaluation” (Material and methods session).

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Acknowledgments

This work was supported by the São Paulo Research Foundation (FAPESP) in Brazil, reference number 2012/50239-6. The authors thank the staff of the Departments of Neurology and Psychiatry of the University of Sao Paulo Medical School for the selection and referral of the patients, and the staff of the Nuclear Medicine Center of the Institute of Radiology for the technical support.

Funding

This study was funded by the São Paulo Research Foundation (FAPESP) in Brazil, reference number 2012/50239-6.

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Authors and Affiliations

  1. Laboratory of Nuclear Medicine (LIM 43), Department of Radiology and Oncology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil

    Artur Martins Coutinho, Daniele de Paula Faria, Carla Rachel Ono, Alexandre Teles Garcez & Carlos Alberto Buchpiguel

  2. Nucleo de Apoio a Pesquisa em Neurociência Aplicada (NAPNA), Universidade de Sao Paulo, Sao Paulo, SP, Brazil

    Artur Martins Coutinho, Geraldo F. Busatto, Fábio Henrique de Gobbi Porto, Daniele de Paula Faria, Alexandre Teles Garcez, Paula Squarzoni, Fábio Luiz de Souza Duran & Carlos Alberto Buchpiguel

  3. Centro de Medicina Nuclear do Instituto de Radiologia, Hospital das Clínicas da Faculdade de Medicina da Universidade de São Paulo, 2° andar, Rua Doutor Ovídio Pires de Campos, 872, Cerqueira Cesar, São Paulo, SP, Brazil

    Artur Martins Coutinho, Carla Rachel Ono & Carlos Alberto Buchpiguel

  4. Laboratory of Psychiatric Neuroimaging (LIM 21), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil

    Geraldo F. Busatto, Fábio Henrique de Gobbi Porto, Paula Squarzoni & Fábio Luiz de Souza Duran

  5. Department of Neurology, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil

    Maira Okada de Oliveira, Eduardo Sturzeneker Tres, Sonia Maria Dozzi Brucki & Ricardo Nitrini

  6. Laboratory of Neuroscience (LIM 27), Department of Psychiatry, Faculdade de Medicina FMUSP, Universidade de Sao Paulo, Sao Paulo, SP, Brazil

    Orestes Vicente Forlenza

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  1. Artur Martins Coutinho
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Correspondence to Artur Martins Coutinho.

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Conflict of interest

Artur Martins Coutinho declares that he has no conflicts of interest.

Fábio Henrique de Gobbi Porto has received a speaker honorarium from Libbs, Lundbeck, and Sandoz-Novartis.

Daniele de Paula Faria declares that she has no conflicts of interest.

Carla Rachel Ono declares that she has no conflicts of interest.

Alexandre Teles Garcez declares that he has no conflicts of interest.

Paula Squarzoni declares that she has no conflicts of interest.

Fábio Luiz de Souza Duran declares that he has no conflicts of interest.

Maira Okada de Oliveira declares that she has no conflicts of interest.

Eduardo Sturzeneker Tres declares that he has no conflicts of interest.

Sonia Maria Dozzi Brucki declares that she has no conflicts of interest.

Orestes Vicente Forlenza declares that he has no conflicts of interest.

Ricardo Nitrini declares that he has no conflicts of interest.

Geraldo Busatto Filho declares that he has no conflicts of interest.

Carlos Alberto Buchpiguel declares that he has no conflicts of interest.

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Coutinho, A.M., Busatto, G.F., de Gobbi Porto, F.H. et al. Brain PET amyloid and neurodegeneration biomarkers in the context of the 2018 NIA-AA research framework: an individual approach exploring clinical-biomarker mismatches and sociodemographic parameters. Eur J Nucl Med Mol Imaging 47, 2666–2680 (2020). https://doi.org/10.1007/s00259-020-04714-0

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