Predicting Diagnostic Conversion From Major Depressive Disorder to Bipolar Disorder: An EHR Based Study From Colombia.

Objectives: Most bipolar disorder (BD) patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study aims to identify features predictive of the conversion from Major Depressive Disorder (MDD) to BD by leveraging electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia.

Methods: We employed a multivariable Cox regression model to identify important predictors of conversion from MDD to BD.

Single-cell stimulus-response gene expression trajectories reveal the stimulus specificities of dynamic responses by single macrophages.

Macrophages induce the expression of hundreds of genes in response to immune threats. However, current technology limits our ability to capture single-cell inducible gene expression dynamics. Here, we generated high-resolution time series single-cell RNA sequencing (scRNA-seq) data from mouse macrophages responding to six stimuli, and imputed ensembles of real-time single-cell gene expression trajectories (scGETs).

Predicting diagnostic conversion from major depressive disorder to bipolar disorder: an EHR based study from Colombia.

Bipolar Disorder (BD) is a severe and chronic disorder characterized by recurrent episodes of depression, mania, and/or hypomania. Most BD patients initially present with depressive symptoms, resulting in a delayed diagnosis of BD and poor clinical outcomes. This study leverages electronic health record (EHR) data from the Clínica San Juan de Dios Manizales in Colombia to identify features predictive of the transition from Major Depressive Disorder (MDD) to BD.

Polygenic scoring accuracy varies across the genetic ancestry continuum.

Polygenic scores (PGSs) have limited portability across different groupings of individuals (for example, by genetic ancestries and/or social determinants of health), preventing their equitable use. PGS portability has typically been assessed using a single aggregate population-level statistic (for example, R), ignoring inter-individual variation within the population. Here, using a large and diverse Los Angeles biobank (ATLAS, n = 36,778) along with the UK Biobank (UKBB, n = 487,409), we show that PGS accuracy decreases individual-to-individual along the continuum of genetic ancestries in all considered populations, even within traditionally labelled 'homogeneous' genetic ancestries.

Dissecting the Regulatory Strategies of NF-κB RelA Target Genes in the Inflammatory Response Reveals Differential Transactivation Logics.

Nuclear factor κB (NF-κB) RelA is the potent transcriptional activator of inflammatory response genes. We stringently defined a list of direct RelA target genes by integrating physical (chromatin immunoprecipitation sequencing [ChIP-seq]) and functional (RNA sequencing [RNA-seq] in knockouts) datasets. We then dissected each gene's regulatory strategy by testing RelA variants in a primary-cell genetic-complementation assay.