Role of Pharmacogenomics in Individualizing Treatment for Alzheimer's Disease

Selenization of Small Molecule Drugs: A New Player on the Board

There is an urgent need to develop safer and more effective modalities for the treatment of a wide range of pathologies due to the increasing rates of drug resistance, undesired side effects, poor clinical outcomes, etc. Throughout the years, selenium (Se) has attracted a great deal of attention due to its important role in human health. Besides, a growing body of work has unveiled that the inclusion of Se motifs into a great number of molecules is a promising strategy for obtaining novel therapeutic agents. In the current Perspective, we have gathered the most recent literature related to the incorporation of different Se moieties into the scaffolds of a wide range of known drugs and their feasible pharmaceutical applications. In addition, we highlight different representative examples as well as provide our perspective on Se drugs and the possible future directions, promises, opportunities, and challenges of this ground-breaking area of research.

A review of neuroimaging-based data-driven approach for Alzheimer's disease heterogeneity analysis

Alzheimer's disease (AD) is a complex form of dementia and due to its high phenotypic variability, its diagnosis and monitoring can be quite challenging. Biomarkers play a crucial role in AD diagnosis and monitoring, but interpreting these biomarkers can be problematic due to their spatial and temporal heterogeneity. Therefore, researchers are increasingly turning to imaging-based biomarkers that employ data-driven computational approaches to examine the heterogeneity of AD. In this comprehensive review article, we aim to provide health professionals with a comprehensive view of past applications of data-driven computational approaches in studying AD heterogeneity and planning future research directions. We first define and offer basic insights into different categories of heterogeneity analysis, including spatial heterogeneity, temporal heterogeneity, and spatial-temporal heterogeneity. Then, we scrutinize 22 articles relating to spatial heterogeneity, 14 articles relating to temporal heterogeneity, and five articles relating to spatial-temporal heterogeneity, highlighting the strengths and limitations of these strategies. Furthermore, we discuss the importance of understanding spatial heterogeneity in AD subtypes and their clinical manifestations, biomarkers for abnormal orderings and AD stages, the recent advancements in spatial-temporal heterogeneity analysis for AD, and the emerging role of omics data integration in advancing personalized diagnosis and treatment for AD patients. By emphasizing the significance of understanding AD heterogeneity, we hope to stimulate further research in this field to facilitate the development of personalized interventions for AD patients.

Iron metabolism: An emerging therapeutic target underlying the anti-Alzheimer's disease effect of ginseng

Finding neuroprotective drugs with fewer side effects and more efficacy has become a major problem as the global prevalence of Alzheimer's disease (AD) rises. Natural drugs have risen to prominence as potential medication candidates. Ginseng has a long history of use in China, and it has a wide range of pharmacological actions that can help with neurological issues. Iron loaded in the brain has been linked to AD pathogenesis. We reviewed the regulation of iron metabolism and its studies in AD and explored how ginseng might regulate iron metabolism and prevent or treat AD. Researchers utilized network pharmacology analysis to identify key factive components of ginseng that protect against AD by regulating ferroptosis. Ginseng and its active ingredients may benefit AD by regulating iron metabolism and targeting ferroptosis genes to inhibit the ferroptosis process. The results present new ideas for ginseng pharmacological studies and initiatives for further research into AD-related drugs. To provide comprehensive information on the neuroprotective use of ginseng to modulate iron metabolism, reveal its potential to treat AD, and provide insights for future research opportunities.

Handgrip Strength Is Related to Hippocampal and Lobar Brain Volumes in a Cohort of Cognitively Impaired Older Adults with Confirmed Amyloid Burden

BACKGROUND

Strength and mobility are essential for activities of daily living. With aging, weaker handgrip strength, mobility, and asymmetry predict poorer cognition. We therefore sought to quantify the relationship between handgrip metrics and volumes quantified on brain magnetic resonance imaging (MRI).

OBJECTIVE

To model the relationships between handgrip strength, mobility, and MRI volumetry.

METHODS

We selected 38 participants with Alzheimer's disease dementia: biomarker evidence of amyloidosis and impaired cognition. Handgrip strength on dominant and non-dominant hands was measured with a hand dynamometer. Handgrip asymmetry was calculated. Two-minute walk test (2MWT) mobility evaluation was combined with handgrip strength to identify non-frail versus frail persons. Brain MRI volumes were quantified with Neuroreader. Multiple regression adjusting for age, sex, education, handedness, body mass index, and head size modeled handgrip strength, asymmetry and 2MWT with brain volumes. We modeled non-frail versus frail status relationships with brain structures by analysis of covariance.

RESULTS

Higher non-dominant handgrip strength was associated with larger volumes in the hippocampus (p = 0.02). Dominant handgrip strength was related to higher frontal lobe volumes (p = 0.02). Higher 2MWT scores were associated with larger hippocampal (p = 0.04), frontal (p = 0.01), temporal (p = 0.03), parietal (p = 0.009), and occipital lobe (p = 0.005) volumes. Frailty was associated with reduced frontal, temporal, and parietal lobe volumes.

CONCLUSION

Greater handgrip strength and mobility were related to larger hippocampal and lobar brain volumes. Interventions focused on improving handgrip strength and mobility may seek to include quantified brain volumes on MR imaging as endpoints.