Combination of white matter hyperintensities and Aβ burden is related to cognitive composites domain scores in subjective cognitive decline: the FACEHBI cohort

BACKGROUND

To explore whether the combination of white matter hyperintensities (WMHs) and amyloid-beta (Aβ) deposition is associated with worse cognitive performance on cognitive composites (CCs) domain scores in individuals with subjective cognitive decline (SCD).

METHODS

Two hundred participants from the FACEHBI cohort underwent structural magnetic resonance imaging (MRI), 18F-florbetaben positron emission tomography (FBB-PET), and neuropsychological assessment. WMHs were addressed through the Fazekas scale, the Age-Related White Matter Changes (ARWMC) scale, and the FreeSurfer pipeline. Eight CCs domain scores were created using the principal component analysis (PCA). Age, sex, education, and apolipoprotein E (APOE) were used as adjusting variables.

RESULTS

Adjusted multiple linear regression models showed that FreeSurfer (B - .245; 95% CI - .1.676, - .393, p = .016) and β burden (SUVR) (B - .180; 95% CI - 2.140, - .292; p = .070) were associated with face-name associative memory CCs domain score, although the latest one was not statistically significant after correction for multiple testing (p = .070). There was non-significant interaction of these two factors on this same CCs domain score (p = .54). However, its cumulative effects on face-name associative performance indicated that those individuals with either higher WMH load or higher Aβ burden showed the worst performance on the face-name associative memory CCs domain score.

CONCLUSIONS

Our results suggest that increased WMH load and increased Aβ are independently associated with poorer episodic memory performance in SCD individuals, indicating a cumulative effect of the combination of these two pathological conditions in promoting lower cognitive performance, an aspect that could help in terms of treatment and prevention.

Correlations between plasma and PET beta-amyloid levels in individuals with subjective cognitive decline: the Fundació ACE Healthy Brain Initiative (FACEHBI)

BACKGROUND

Peripheral biomarkers that identify individuals at risk of developing Alzheimer's disease (AD) or predicting high amyloid beta (Aβ) brain burden would be highly valuable. To facilitate clinical trials of disease-modifying therapies, plasma concentrations of Aβ species are good candidates for peripheral AD biomarkers, but studies to date have generated conflicting results.

METHODS

The Fundació ACE Healthy Brain Initiative (FACEHBI) study uses a convenience sample of 200 individuals diagnosed with subjective cognitive decline (SCD) at the Fundació ACE (Barcelona, Spain) who underwent amyloid florbetaben(18F) (FBB) positron emission tomography (PET) brain imaging. Baseline plasma samples from FACEHBI subjects (aged 65.9 ± 7.2 years) were analyzed using the ABtest (Araclon Biotech). This test directly determines the free plasma (FP) and total plasma (TP) levels of Aβ40 and Aβ42 peptides. The association between Aβ40 and Aβ42 plasma levels and FBB-PET global standardized uptake value ratio (SUVR) was determined using correlations and linear regression-based methods. The effect of the APOE genotype on plasma Aβ levels and FBB-PET was also assessed. Finally, various models including different combinations of demographics, genetics, and Aβ plasma levels were constructed using logistic regression and area under the receiver operating characteristic curve (AUROC) analyses to evaluate their ability for discriminating which subjects presented brain amyloidosis.

RESULTS

FBB-PET global SUVR correlated weakly but significantly with Aβ42/40 plasma ratios. For TP42/40, this observation persisted after controlling for age and APOE ε4 allele carrier status (R2 = 0.193, p = 1.01E-09). The ROC curve demonstrated that plasma Aβ measurements are not superior to APOE and age in combination in predicting brain amyloidosis. It is noteworthy that using a simple preselection tool (the TP42/40 ratio with an empirical cut-off value of 0.08) optimizes the sensitivity and reduces the number of individuals subjected to Aβ FBB-PET scanners to 52.8%. No significant dependency was observed between APOE genotype and plasma Aβ measurements (p value for interaction = 0.105).

CONCLUSION

Brain and plasma Aβ levels are partially correlated in individuals diagnosed with SCD. Aβ plasma measurements, particularly the TP42/40 ratio, could generate a new recruitment strategy independent of the APOE genotype that would improve identification of SCD subjects with brain amyloidosis and reduce the rate of screening failures in preclinical AD studies. Independent replication of these findings is warranted.

FACEHBI: A Prospective Study of Risk Factors, Biomarkers and Cognition in a Cohort of Individuals with Subjective Cognitive Decline. Study Rationale and Research Protocols

BACKGROUND

Long-term longitudinal studies with multimodal biomarkers are needed to delve into the knowledge of preclinical AD. Subjective cognitive decline has been proposed as a risk factor for the development of cognitive impairment. Thus, including individuals with SCD in observational studies may be a cost-effective strategy to increase the prevalence of preclinical AD in the sample.

OBJECTIVES

To describe the rationale, research protocols and baseline characteristics of participants in the Fundació ACE Healthy Brain Initiative (FACEHBI).

DESIGN

FACEHBI is a clinical trial (EudraCT: 2014-000798-38) embedded within a long-term observational study of individuals with SCD.

SETTING

Participants have been recruited at the memory clinic of Fundació ACE (Barcelona) from two different sources: patients referred by a general practitioner and individuals from an Open House Initiative.

PARTICIPANTS

200 individuals diagnosed with SCD with a strictly normal performance in a comprehensive neuropsychological battery.

MEASUREMENTS

Individuals will undergo an extensive neuropsychological protocol, risk factor assessment and a set of multimodal biomarkers including florbetaben PET, structural and functional MRI, diffusion tensor imaging, determination of amyloid species in plasma and neurophthalmologic assessment with optical coherence tomography.

RESULTS

Two hundred individuals have been recruited in 15 months. Mean age was 65.9 years; mean MMSE was 29.2 with a mean of 14.8 years of education.

CONCLUSIONS

FACEHBI is a long-term study of cognition, biomarkers and lifestyle that has been designed upon an innovative symptom-based approach using SCD as target population. It will shed light on the pathophysiology of preclinical AD and the role of SCD as a risk marker for the development of cognitive impairment.

A physical model for dementia

Aging associated brain decline often result in some kind of dementia. Even when this is a complex brain disorder a physical model can be used in order to describe its general behavior. A probabilistic model for the development of dementia is obtained and fitted to some experimental data obtained from the Alzheimer's Disease Neuroimaging Initiative. It is explained how dementia appears as a consequence of aging and why it is irreversible.

Follow-up of loci from the International Genomics of Alzheimer's Disease Project identifies TRIP4 as a novel susceptibility gene

To follow-up loci discovered by the International Genomics of Alzheimer's Disease Project, we attempted independent replication of 19 single nucleotide polymorphisms (SNPs) in a large Spanish sample (Fundació ACE data set; 1808 patients and 2564 controls). Our results corroborate association with four SNPs located in the genes INPP5D, MEF2C, ZCWPW1 and FERMT2, respectively. Of these, ZCWPW1 was the only SNP to withstand correction for multiple testing (P=0.000655). Furthermore, we identify TRIP4 (rs74615166) as a novel genome-wide significant locus for Alzheimer's disease risk (odds ratio=1.31; confidence interval 95% (1.19-1.44); P=9.74 × 10(-)(9)).

Tissue radiation response with maximum Tsallis entropy

The expression of survival factors for radiation damaged cells is currently based on probabilistic assumptions and experimentally fitted for each tumor, radiation, and conditions. Here, we show how the simplest of these radiobiological models can be derived from the maximum entropy principle of the classical Boltzmann-Gibbs expression. We extend this derivation using the Tsallis entropy and a cutoff hypothesis, motivated by clinical observations. The obtained expression shows a remarkable agreement with the experimental data found in the literature.