BDNF Val66Met in preclinical Alzheimer's disease is associated with short-term changes in episodic memory and hippocampal volume but not serum mBDNF

ABSTRACTBackground:The brain-derived neurotrophic factor (BDNF) Val66Met polymorphism Met allele exacerbates amyloid (Aβ) related decline in episodic memory (EM) and hippocampal volume (HV) over 36–54 months in preclinical Alzheimer's disease (AD). However, the extent to which Aβ+ and BDNF Val66Met is related to circulating markers of BDNF (e.g. serum) is unknown. We aimed to determine the effect of Aβ and the BDNF Val66Met polymorphism on levels of serum mBDNF, EM, and HV at baseline and over 18-months.Methods:Non-demented older adults (n = 446) underwent Aβ neuroimaging and BDNF Val66Met genotyping. EM and HV were assessed at baseline and 18 months later. Fasted blood samples were obtained from each participant at baseline and at 18-month follow-up. Aβ PET neuroimaging was used to classify participants as Aβ– or Aβ+.Results:At baseline, Aβ+ adults showed worse EM impairment and lower serum mBDNF levels relative to Aβ- adults. BDNF Val66Met polymorphism did not affect serum mBDNF, EM, or HV at baseline. When considered over 18-months, compared to Aβ– Val homozygotes, Aβ+ Val homozygotes showed significant decline in EM and HV but not serum mBDNF. Similarly, compared to Aβ+ Val homozygotes, Aβ+ Met carriers showed significant decline in EM and HV over 18-months but showed no change in serum mBDNF.Conclusion:While allelic variation in BDNF Val66Met may influence Aβ+ related neurodegeneration and memory loss over the short term, this is not related to serum mBDNF. Longer follow-up intervals may be required to further determine any relationships between serum mBDNF, EM, and HV in preclinical AD.

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P3-303: Effects of ab and Bdnf Val66Met on Episodic Memory, Hippocampal Volume and Serum BDNF in Preclinical Alzheimer’S Disease

Alzheimer s & Dementia ◽

10.1016/j.jalz.2016.06.1967 ◽

2016 ◽

Vol 12 ◽

pp. P957-P958

Author(s):

Yen Ying Lim ◽

Stephanie R. Rainey-Smith ◽

Simon M. Laws ◽

Veer Gupta ◽

Tenielle Porter ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Episodic Memory ◽

Hippocampal Volume ◽

Preclinical Alzheimer’S Disease ◽

Serum Bdnf

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Disease progression modelling from preclinical Alzheimer’s disease (AD) to AD dementia

Scientific Reports ◽

10.1038/s41598-021-83585-3 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Soo Hyun Cho ◽

Sookyoung Woo ◽

Changsoo Kim ◽

Hee Jin Kim ◽

Hyemin Jang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Disease Progression ◽

Disease Assessment ◽

Time Interval ◽

Disease Course ◽

Preclinical Alzheimer’S Disease ◽

Apoe Ε4 ◽

Preclinical Ad ◽

Cognitive Subscale

AbstractTo characterize the course of Alzheimer’s disease (AD) over a longer time interval, we aimed to construct a disease course model for the entire span of the disease using two separate cohorts ranging from preclinical AD to AD dementia. We modelled the progression course of 436 patients with AD continuum and investigated the effects of apolipoprotein E ε4 (APOE ε4) and sex on disease progression. To develop a model of progression from preclinical AD to AD dementia, we estimated Alzheimer’s Disease Assessment Scale-Cognitive Subscale 13 (ADAS-cog 13) scores. When calculated as the median of ADAS-cog 13 scores for each cohort, the estimated time from preclinical AD to MCI due to AD was 7.8 years and preclinical AD to AD dementia was 15.2 years. ADAS-cog 13 scores deteriorated most rapidly in women APOE ε4 carriers and most slowly in men APOE ε4 non-carriers (p < 0.001). Our results suggest that disease progression modelling from preclinical AD to AD dementia may help clinicians to estimate where patients are in the disease course and provide information on variation in the disease course by sex and APOE ε4 status.

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Cognitive Performance and Cerebrospinal Fluid Markers in Preclinical Alzheimer’s Disease: Results from the Gothenburg H70 Birth Cohort Studies

Journal of Alzheimer s Disease ◽

10.3233/jad-200751 ◽

2021 ◽

Vol 79 (1) ◽

pp. 225-235

Author(s):

Maya Arvidsson Rådestig ◽

Johan Skoog ◽

Henrik Zetterberg ◽

Jürgen Kern ◽

Anna Zettergren ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cerebrospinal Fluid ◽

Cohort Studies ◽

Cognitive Performance ◽

Birth Cohort ◽

Population Based ◽

Tau Pathology ◽

Preclinical Alzheimer’S Disease ◽

Preclinical Ad

Background: We have previously shown that older adults with preclinical Alzheimer’s disease (AD) pathology in cerebrospinal fluid (CSF) had slightly worse performance in Mini-Mental State Examination (MMSE) than participants without preclinical AD pathology. Objective: We therefore aimed to compare performance on neurocognitive tests in a population-based sample of 70-year-olds with and without CSF AD pathology. Methods: The sample was derived from the population-based Gothenburg H70 Birth Cohort Studies in Sweden. Participants (n = 316, 70 years old) underwent comprehensive cognitive examinations, and CSF Aβ-42, Aβ-40, T-tau, and P-tau concentrations were measured. Participants were classified according to the ATN system, and according to their Clinical Dementia Rating (CDR) score. Cognitive performance was examined in the CSF amyloid, tau, and neurodegeneration (ATN) categories. Results: Among participants with CDR 0 (n = 259), those with amyloid (A+) and/or tau pathology (T+, N+) showed similar performance on most cognitive tests compared to participants with A-T-N-. Participants with A-T-N+ performed worse in memory (Supra span (p = 0.003), object Delayed (p = 0.042) and Immediate recall (p = 0.033)). Among participants with CDR 0.5 (n = 57), those with amyloid pathology (A+) scored worse in category fluency (p = 0.003). Conclusion: Cognitively normal participants with amyloid and/or tau pathology performed similarly to those without any biomarker evidence of preclinical AD in most cognitive domains, with the exception of slightly poorer memory performance in A-T-N+. Our study suggests that preclinical AD biomarkers are altered before cognitive decline.

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A Polygenic Risk Score Derived From Episodic Memory Weighted Genetic Variants Is Associated With Cognitive Decline in Preclinical Alzheimer’s Disease

Frontiers in Aging Neuroscience ◽

10.3389/fnagi.2018.00423 ◽

2018 ◽

Vol 10 ◽

Cited By ~ 3

Author(s):

Tenielle Porter ◽

Samantha C. Burnham ◽

Greg Savage ◽

Yen Ying Lim ◽

Paul Maruff ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Episodic Memory ◽

Cognitive Decline ◽

Risk Score ◽

Genetic Variants ◽

Polygenic Risk Score ◽

Preclinical Alzheimer’S Disease ◽

Polygenic Risk

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Predicting Brain Amyloid Using Multivariate Morphometry Statistics, Sparse Coding, and Correntropy: Validation in 1,125 Individuals from the ADNI and OASIS Databases

10.1101/2020.10.16.343137 ◽

2020 ◽

Author(s):

Jianfeng Wu ◽

Qunxi Dong ◽

Jie Gui ◽

Jie Zhang ◽

Yi Su ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Sparse Coding ◽

Hippocampal Volume ◽

Amyloid Pet ◽

Individual Subject ◽

Max Pooling ◽

Preclinical Ad ◽

The Individual ◽

Low Dimensional

ABSTRACTBiomarker assisted preclinical/early detection and intervention in Alzheimer’s disease (AD) may be the key to therapeutic breakthroughs. One of the presymptomatic hallmarks of AD is the accumulation of beta-amyloid (Aβ) plaques in the human brain. However, current methods to detect Aβ pathology are either invasive (lumbar puncture) or quite costly and not widely available (amyloid PET). Our prior studies show that MRI-based hippocampal multivariate morphometry statistics (MMS) are an effective neurodegenerative biomarker for preclinical AD. Here we attempt to use MRI-MMS to make inferences regarding brain amyloid burden at the individual subject level. As MMS data has a larger dimension than the sample size, we propose a sparse coding algorithm, Patch Analysis-based Surface Correntropy-induced Sparse coding and max-pooling (PASCS-MP), to generate a low-dimensional representation of hippocampal morphometry for each individual subject. Then we apply these individual representations and a binary random forest classifier to predict brain Aβ positivity for each person. We test our method in two independent cohorts, 841 subjects from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) and 260 subjects from the Open Access Series of Imaging Studies (OASIS). Experimental results suggest that our proposed PASCS-MP method and MMS can discriminate Aβ positivity in people with mild cognitive impairment (MCI) (Accuracy (ACC)=0.89 (ADNI)) and in cognitively unimpaired (CU) individuals (ACC=0.79 (ADNI) and ACC=0.82 (OASIS)). These results compare favorably relative to measures derived from traditional algorithms, including hippocampal volume and surface area, shape measures based on spherical harmonics (SPHARM) and our prior Patch Analysis-based Surface Sparse-coding and Max-Pooling (PASS-MP) methods.

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Neurofilament Light Predicts Decline in Attention but Not Episodic Memory in Preclinical Alzheimer’s Disease

Journal of Alzheimer s Disease ◽

10.3233/jad-200018 ◽

2020 ◽

Vol 74 (4) ◽

pp. 1119-1129

Author(s):

Andrew J. Aschenbrenner ◽

Brian A. Gordon ◽

Anne M. Fagan ◽

Suzanne E. Schindler ◽

David A. Balota ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Episodic Memory ◽

Preclinical Alzheimer’S Disease ◽

Neurofilament Light

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Evidence of a Relation Between Hippocampal Volume, White Matter Hyperintensities, and Cognition in Subjective Cognitive Decline and Mild Cognitive Impairment

The Journals of Gerontology Series B ◽

10.1093/geronb/gbz120 ◽

2019 ◽

Vol 75 (7) ◽

pp. 1382-1392 ◽

Cited By ~ 4

Author(s):

Marie Caillaud ◽

Carol Hudon ◽

Benjamin Boller ◽

Simona Brambati ◽

Simon Duchesne ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

White Matter ◽

Episodic Memory ◽

Cognitive Decline ◽

White Matter Hyperintensities ◽

Hippocampal Volume ◽

Subjective Cognitive Decline

Abstract Objective The concepts of mild cognitive impairment (MCI) and subjective cognitive decline (SCD) have been proposed to identify individuals in the early stages of Alzheimer’s disease (AD), or other neurodegenerative diseases. One approach to validate these concepts is to investigate the relationship between pathological brain markers and cognition in those individuals. Method We included 126 participants from the Consortium for the Early Identification of Alzheimer’s disease-Quebec (CIMA-Q) cohort (67 SCD, 29 MCI, and 30 cognitively healthy controls [CH]). All participants underwent a complete cognitive assessment and structural magnetic resonance imaging. Group comparisons were done using cognitive data, and then correlated with hippocampal volumes and white matter hyperintensities (WMHs). Results Significant differences were found between participants with MCI and CH on episodic and executive tasks, but no differences were found when comparing SCD and CH. Scores on episodic memory tests correlated with hippocampal volumes in both MCI and SCD, whereas performance on executive tests correlated with WMH in all of our groups. Discussion As expected, the SCD group was shown to be cognitively healthy on tasks where MCI participants showed impairment. However, SCD’s hippocampal volume related to episodic memory performances, and WMH to executive functions. Thus, SCD represents a valid research concept and should be used, alongside MCI, to better understand the preclinical/prodromal phase of AD.

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