Amyloid-β (Aβ) plaques are a neuropathological hallmark of Alzheimer’s disease (AD); however, a significant number of cognitively normal older adults can also have Aβ plaques. Thus, distinguishing AD from cognitively normal individuals with Aβ plaques (NwAβ) based on Aβ plaque detection is challenging. It has been observed that butyrylcholinesterase (BChE) accumulates in plaques preferentially in AD. Thus, detecting BChE-associated plaques has the potential as an improved AD biomarker. We present Aβ, thioflavin-S, and BChE quantification of 26 postmortem brain tissues; AD ( n = 8), NwAβ ( n = 6), cognitively normal without plaques ( n = 8), and other common dementias including corticobasal degeneration, frontotemporal dementia with tau, dementia with Lewy bodies, and vascular dementia. Pathology burden in the orbitofrontal cortex, entorhinal cortex, amygdala, and hippocampal formation was determined and compared. The predictive value of Aβ and BChE quantification was determined, via receiver-operating characteristic plots, to evaluate their AD diagnostic performance using sensitivity, specificity, and area under curve (AUC) metrics. In general, Aβ and BChE-associated pathology were greater in AD, particularly in the orbitofrontal cortex. In this region, the largest increase (9.3-fold) was in BChE-associated pathology, observed between NwAβ and AD, due to the virtual absence of BChE-associated plaques in NwAβ brains. Furthermore, BChE did not associate with pathology of the other dementias. In this sample, BChE-associated pathology provided better diagnostic performance (AUC = 1.0, sensitivity/specificity = 100% /100%) when compared to Aβ (AUC = 0.98, 100% /85.7%). These findings highlight the predictive value of BChE as a biomarker for AD that could facilitate timely disease diagnosis and management.

Retinoids, derivatives of vitamin A, are key physiological molecules with regulatory effects on cell differentiation, proliferation and apoptosis. As a result, they are of interest for cancer therapy. Specifically, models of breast cancer have varied responses to manipulations of retinoid signaling. This study characterizes the transcriptional response of MDA-MB-231 and MDA-MB-468 breast cancer cells to retinaldehyde dehydrogenase 1A3 (ALDH1A3) and all-trans retinoic acid (atRA). We demonstrate limited overlap between ALDH1A3-induced gene expression and atRA-induced gene expression in both cell lines, suggesting that the function of ALDH1A3 in breast cancer progression extends beyond its role as a retinaldehyde dehydrogenase. Our data reveals divergent transcriptional responses to atRA, which are largely independent of genomic retinoic acid response elements (RAREs) and consistent with the opposing responses of MDA-MB-231 and MDA-MB-468 to in vivo atRA treatment. We identify transcription factors associated with each gene set. Manipulation of the IRF1 transcription factor demonstrates that it is the level of atRA-inducible and epigenetically regulated transcription factors that determine expression of target genes (e.g. CTSS, cathepsin S). This study provides a paradigm for complex responses of breast cancer models to atRA treatment, and illustrates the need to characterize RARE-independent responses to atRA in a variety of models.

The Osteoarthritis Initiative (OAI) evaluates the development and progression of osteoarthritis. Frailty captures the heterogeneity in aging. Use of this resource-intensive dataset to answer aging-related research questions could be enhanced by a frailty measure. To: (i) develop a deficit accumulation frailty index (FI) for the OAI; (ii) examine its relationship with age and compare between sexes, (iii) validate the FI versus all-cause mortality and (iv) compare this association with mortality with a modified frailty phenotype. OAI cohort study. North America. An FI was determined for 4,755/4,796 and 4,149/4,796 who had a valid FI and frailty phenotype. Fifty-nine-variables were screened for inclusion. Multivariate Cox regression evaluated the impact of FI or phenotype on all-cause mortality at follow-up (up to 146 months), controlling for age and sex. Thirty-one items were included. FI scores (0.16 ± 0.09) were higher in older adults and among females (both, P < 0.001). By follow-up, 264 people had died (6.4%). Older age, being male, and greater FI were associated with a higher risk of all-cause mortality (all, P < 0.001). The model including FI was a better fit than the model including the phenotype (AIC: 4,167 vs. 4,178) and was a better predictor of all-cause mortality than the phenotype with an area under receiver operating characteristic curve: 0.652 vs. 0.581. We developed an FI using the OAI and validated it in relation to all-cause mortality. The FI may be used to study aging on clinical, functional and structural aspects of osteoarthritis included in the OAI.

Frailty increasingly is recognized as a factor that modifies the relationship between disease biomarkers, including neuropathology, and dementia expression. The mechanisms underlying the relationship between frailty and dementia remain unclear, but blood biomarkers can offer insight into these mechanisms. We completed a scoping review of research examining the associations between blood biomarkers, frailty, and cognition. Three online databases were searched to identify original research examining blood biomarkers in the context of frailty and/or cognitive decline that accounted for the other condition in the analysis through stratification or inclusion in the model. Five of the 76 unique biomarkers identified -A disintegrin and Metalloproteinase 10 (ADAM10), fibrinogen, interleukin (IL)-6, neurofilament light chain (NfL) and vitamin D- were significantly and independently associated with both frailty and cognition. All five biomarkers could contribute to aging mechanisms, including disrupted proteostasis, chronic inflammation, dysregulated metabolism and/or deregulated nutrient sensing. These biomarkers could thus be common pathways of frailty and cognitive decline. Despite the Alzheimer-defining roles of β-amyloid and phosphorylated tau, these biomarkers typically are reported without considering the degree of frailty. Future biomarker research in cognitive decline and frailty should seek a clearer understanding of their relationship.