Quality Control Procedures for Genome-Wide Association Studies.

Genome-wide association studies (GWAS) are being conducted at an unprecedented rate in population-based cohorts and have increased our understanding of the pathophysiology of many complex diseases. Regardless of the context, the practical utility of this information ultimately depends upon the quality of the data used for statistical analyses. Quality control (QC) procedures for GWAS are constantly evolving. Here, we enumerate some of the challenges in QC of genotyped GWAS data and describe the approaches involving genotype imputation of a sample dataset along with post-imputation quality assurance, thereby minimizing potential bias and error in GWAS results. We discuss common issues associated with QC of the GWAS data (genotyped and imputed), including data file formats, software packages for data manipulation and analysis, sex chromosome anomalies, sample identity, sample relatedness, population substructure, batch effects, and marker quality. We provide detailed guidelines along with a sample dataset to suggest current best practices and discuss areas of ongoing and future research. © 2022 Wiley Periodicals LLC.

Dissociable neural correlates of uncertainty underlie different exploration strategies.

Most real-world decisions involve a delicate balance between exploring unfamiliar alternatives and committing to the best known option. Previous work has shown that humans rely on different forms of uncertainty to negotiate this "explore-exploit" trade-off, yet the neural basis of the underlying computations remains unclear. Using fMRI (n = 31), we find that relative uncertainty is represented in right rostrolateral prefrontal cortex and drives directed exploration, while total uncertainty is represented in right dorsolateral prefrontal cortex and drives random exploration. The decision value signal combining relative and total uncertainty to compute choice is reflected in motor cortex activity. The variance of this signal scales with total uncertainty, consistent with a sampling mechanism for random exploration. Overall, these results are consistent with a hybrid computational architecture in which different uncertainty computations are performed separately and then combined by downstream decision circuits to compute choice.

Targeting psychologic stress signaling pathways in Alzheimer's disease.

Alzheimer's Disease (AD) is the most prevalent progressive neurodegenerative disease; to date, no AD therapy has proven effective in delaying or preventing the disease course. In the search for novel therapeutic targets in AD, it has been shown that increased chronic psychologic stress is associated with AD risk. Subsequently, biologic pathways underlying psychologic stress have been identified and shown to be able to exacerbate AD relevant pathologies. In this review, we summarize the literature relevant to the association between psychologic stress and AD, focusing on studies investigating the effects of stress paradigms on transgenic mouse models of Amyloid-ß (Aß) and tau pathologies. In recent years, a substantial amount of research has been done investigating a key stress-response mediator, corticotropin-releasing hormone (CRH), and its interactions with AD relevant processes. We highlight attempts to target the CRH signaling pathway as a therapeutic intervention in these transgenic mouse models and discuss how targeting this pathway is a promising avenue for further investigation.