Understanding Biomarker Discordance: MRI and PET Phenotypes Shed Light on Alzheimer’s Pathology

Abstract Background Plasma biomarkers for Alzheimer’s disease (AD) are indicators of neuropathological changes. Biomarker cutoffs may not consistently indicate the presence or absence of a pathology. Discrepant biomarker levels are observed in some cognitively normal subjects and patients with clinically diagnosed AD, with some asymptomatic individuals having biomarker evidence of AD pathophysiology and some symptomatic individuals without evidence of AD pathophysiology. The purpose of this study is to understand the discordant biomarker levels among CN and AD using phenotypes from MRI and PET images. Method We measured phosphorylated tau 181 (P‐tau181) in plasma from 685 individuals in the Washington Heights Inwood Columbia Aging Project (WHICAP; Mean age = 76.52; women = 64.59%; non‐Hispanic Whites = 29.61%, African Americans = 30.62%; Caribbean Hispanics = 37.30%) and characterized them as biomarker positive based on a ptau181 cutoff of 2.648 pg/mL: 556 cognitively normal (CN, 241 biomarker+), 59 mild cognitively impaired (MCI, 26 biomarker+), and 70 had clinical AD (40 biomarker+). We used MRI (n = 685) and [18F] Florbetaben (FBB) Aβ PET in 167 (24.2%) individuals, and [18F]‐MK‐6420 tau PET 23 (3.36%) individuals) to compare white matter hyperintensity volume (WMH), hippocampus volume, number of silent brain infarcts (SBI), Aβ standard uptake value ratios (SUVR), and tau SUVR among the six biomarker groups (CN‐, CN+, MCI‐, MCI+, AD‐, AD+) with ANCOVA model adjusting for age, sex, and ethnicity. Result The AD+ group had larger WMH volume ( P = 2.81×10 −26 ), smaller hippocampus volume ( P = 5.34×10 −04 ), higher Aβ SUVR ( P = 2.26×10 −03 ) and tau SUVR ( P = 8.11×10 −04 ) compared to the CN‐. The AD‐ group had larger WMH volumes ( P = 1.96×10 −04 ) and smaller hippocampal volume ( P = 0.039) to CN‐. When compared to the AD‐ group, the AD+ group had larger WMH volume ( P = 4.34×10 −03 ). The CN+ group had a larger WMH volume ( P = 4.17×10 −03 ) and smaller hippocampal volume ( P = 4.13×10 −05 ) than CN‐ group. Both MCI+ ( P = 0.048) and MCI‐ ( P = 0.022) groups showed smaller hippocampal volume compared with the CN‐ group. Except for hippocampal volume, no other phenotypes demonstrated statistical significance in the MCI+ and MCI‐ groups. Conclusion MRI and PET phenotypes exhibited a strong association with pathophysiological changes in the AD+ group. Specifically, MRI phenotypes such as WMH volume and hippocampal volume could be instrumental in characterizing AD pathophysiology, even with discrepancies in biomarker profiles.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.095708
Primary Topic
Bioinformatics and Genomic Networks
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article
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article

Understanding Biomarker Discordance: MRI and PET Phenotypes Shed Light on Alzheimer’s Pathology

Lawrence S. Honig, Adam M. Brickman, Tamil Iniyan Gunasekaran, Patrick J. Lao et al.
Alzheimer s & Dementia
Bioinformatics and Genomic Networks
article

Understanding Biomarker Discordance: MRI and PET Phenotypes Shed Light on Alzheimer’s Pathology

Lawrence S. Honig, Adam M. Brickman, Tamil Iniyan Gunasekaran, Patrick J. Lao, Yian Gu, José Gutierrez, Jennifer J. Manly, Annie Lee, Badri Narayan Vardarajan, Richard Mayeux
article en

Abstract

Abstract Background Plasma biomarkers for Alzheimer’s disease (AD) are indicators of neuropathological changes. Biomarker cutoffs may not consistently indicate the presence or absence of a pathology. Discrepant biomarker levels are observed in some cognitively normal subjects and patients with clinically diagnosed AD, with some asymptomatic individuals having biomarker evidence of AD pathophysiology and some symptomatic individuals without evidence of AD pathophysiology. The purpose of this study is to understand the discordant biomarker levels among CN and AD using phenotypes from MRI and PET images. Method We measured phosphorylated tau 181 (P‐tau181) in plasma from 685 individuals in the Washington Heights Inwood Columbia Aging Project (WHICAP; Mean age = 76.52; women = 64.59%; non‐Hispanic Whites = 29.61%, African Americans = 30.62%; Caribbean Hispanics = 37.30%) and characterized them as biomarker positive based on a ptau181 cutoff of 2.648 pg/mL: 556 cognitively normal (CN, 241 biomarker+), 59 mild cognitively impaired (MCI, 26 biomarker+), and 70 had clinical AD (40 biomarker+). We used MRI (n = 685) and [18F] Florbetaben (FBB) Aβ PET in 167 (24.2%) individuals, and [18F]‐MK‐6420 tau PET 23 (3.36%) individuals) to compare white matter hyperintensity volume (WMH), hippocampus volume, number of silent brain infarcts (SBI), Aβ standard uptake value ratios (SUVR), and tau SUVR among the six biomarker groups (CN‐, CN+, MCI‐, MCI+, AD‐, AD+) with ANCOVA model adjusting for age, sex, and ethnicity. Result The AD+ group had larger WMH volume ( P = 2.81×10 −26 ), smaller hippocampus volume ( P = 5.34×10 −04 ), higher Aβ SUVR ( P = 2.26×10 −03 ) and tau SUVR ( P = 8.11×10 −04 ) compared to the CN‐. The AD‐ group had larger WMH volumes ( P = 1.96×10 −04 ) and smaller hippocampal volume ( P = 0.039) to CN‐. When compared to the AD‐ group, the AD+ group had larger WMH volume ( P = 4.34×10 −03 ). The CN+ group had a larger WMH volume ( P = 4.17×10 −03 ) and smaller hippocampal volume ( P = 4.13×10 −05 ) than CN‐ group. Both MCI+ ( P = 0.048) and MCI‐ ( P = 0.022) groups showed smaller hippocampal volume compared with the CN‐ group. Except for hippocampal volume, no other phenotypes demonstrated statistical significance in the MCI+ and MCI‐ groups. Conclusion MRI and PET phenotypes exhibited a strong association with pathophysiological changes in the AD+ group. Specifically, MRI phenotypes such as WMH volume and hippocampal volume could be instrumental in characterizing AD pathophysiology, even with discrepancies in biomarker profiles.

Alzheimer s & DementiaVol. 20(S8)
NewYork–Presbyterian Hospital (US), Columbia University Irving Medical Center (US), New York Hospital Queens (US), Columbia University (US)
Openalex Percentile: Top 78%
Bioinformatics and Genomic Networks
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