Prevalence of cerebrospinal fluid AT biomarker profiles according to APOE genotype and across age in persons without dementia

Abstract Background Amyloid‐b deposition and tau tangle formation are the key pathologies of Alzheimer’s disease (AD). The presence of these pathologies in cerebrospinal fluid (CSF) biomarkers is used for a biological diagnosis of AD. It remains unclear how the prevalence of AT biomarker profiles depends on apolipoprotein E (APOE) genotype. A better understanding of the AT biomarker profiles across APOE genotypes and age in the pre‐dementia stages will help inform strategies to prevent or delay AD progression in those with different APOE genotypes. Methods Participants with normal cognition (NC; n = 4356) or mild cognitive impairment (MCI; n = 3997) were selected from 45 studies that participated in the Amyloid Biomarker Study based on availability of data on age, CSF amyloid‐b 42 (A), CSF phosphorylated tau 181 (T), and APOE genotype (e2e2, e2e3, e2e4, e3e3, e3e4, e4e4). Based on (ab)normal values for A (data‐driven) and T (center‐specific cutoffs) participants were placed into one of four AT biomarker profiles: A‐T‐, A+T‐, A‐T+, or A+T+. A Markov‐Chain‐Monte‐Carlo generalized linear mixed model was performed separately for NC and MCI to evaluate the association of AT profile frequency with age and APOE genotype. Center was included as random effect. Results The NC and MCI groups had an average age of 65.1 years (SD = 10.8; 59% female) and 69.3 years (SD = 8.4; 48% female) respectively. Most participants had APOE e3e3 genotype (NC 56%, MCI 45%; Table 1). In both groups, the association of AT profiles with APOE genotype changed across age (both p < .001; Figure 1), except for participants with NC and APOE e2e2 genotype. For NC with APOE e2e3 and e3e3 genotypes, A‐T+ was more frequent in older age than A+T‐ or A+T+. In APOE e3e4 and e4e4 genotypes A+T‐ frequency plateaued around 65 years of age, while A+T+ frequency strongly increased. For MCI, A+T+ was most frequent with aging across APOE e2e4, e3e3, e3e4, and e4e4 genotypes. Conclusion Frequencies of AT biomarker profiles changed substantially across APOE genotypes and age in NC and MCI. Studies recruiting participants based on AT biomarker profiles should take age and APOE genotype into account.

Authors

Institutions

Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.091306
Primary Topic
Health, Environment, Cognitive Aging
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prevalence of cerebrospinal fluid AT biomarker profiles according to APOE genotype and across age in persons without dementia

Pieter Jelle Visser, Betty Marije Tijms, Nancy N. Maserejian, Julie Elisabeth Oomens et al.
Alzheimer s & Dementia
Health, Environment, Cognitive Aging
article

Prevalence of cerebrospinal fluid AT biomarker profiles according to APOE genotype and across age in persons without dementia

Pieter Jelle Visser, Betty Marije Tijms, Nancy N. Maserejian, Julie Elisabeth Oomens, Stephanie J. B. Vos, Willemijn J. Jansen, Jacob van de Velden
article en

Abstract

Abstract Background Amyloid‐b deposition and tau tangle formation are the key pathologies of Alzheimer’s disease (AD). The presence of these pathologies in cerebrospinal fluid (CSF) biomarkers is used for a biological diagnosis of AD. It remains unclear how the prevalence of AT biomarker profiles depends on apolipoprotein E (APOE) genotype. A better understanding of the AT biomarker profiles across APOE genotypes and age in the pre‐dementia stages will help inform strategies to prevent or delay AD progression in those with different APOE genotypes. Methods Participants with normal cognition (NC; n = 4356) or mild cognitive impairment (MCI; n = 3997) were selected from 45 studies that participated in the Amyloid Biomarker Study based on availability of data on age, CSF amyloid‐b 42 (A), CSF phosphorylated tau 181 (T), and APOE genotype (e2e2, e2e3, e2e4, e3e3, e3e4, e4e4). Based on (ab)normal values for A (data‐driven) and T (center‐specific cutoffs) participants were placed into one of four AT biomarker profiles: A‐T‐, A+T‐, A‐T+, or A+T+. A Markov‐Chain‐Monte‐Carlo generalized linear mixed model was performed separately for NC and MCI to evaluate the association of AT profile frequency with age and APOE genotype. Center was included as random effect. Results The NC and MCI groups had an average age of 65.1 years (SD = 10.8; 59% female) and 69.3 years (SD = 8.4; 48% female) respectively. Most participants had APOE e3e3 genotype (NC 56%, MCI 45%; Table 1). In both groups, the association of AT profiles with APOE genotype changed across age (both p < .001; Figure 1), except for participants with NC and APOE e2e2 genotype. For NC with APOE e2e3 and e3e3 genotypes, A‐T+ was more frequent in older age than A+T‐ or A+T+. In APOE e3e4 and e4e4 genotypes A+T‐ frequency plateaued around 65 years of age, while A+T+ frequency strongly increased. For MCI, A+T+ was most frequent with aging across APOE e2e4, e3e3, e3e4, and e4e4 genotypes. Conclusion Frequencies of AT biomarker profiles changed substantially across APOE genotypes and age in NC and MCI. Studies recruiting participants based on AT biomarker profiles should take age and APOE genotype into account.

Alzheimer s & DementiaVol. 20(S2)
Biogen (United States) (US), Maastricht University (NL), Amsterdam Neuroscience (NL), Amsterdam University Medical Centers (NL), Vrije Universiteit Amsterdam (NL)
Good health and well-being
Openalex Percentile: Top 65%
Health, Environment, Cognitive Aging
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.