Genomic structural equation modeling of reward-related traits: exploring the genetic factor structure and its relationship with psychopathology.

Reward sensitivity has a partial genetic background, and extreme levels may increase vulnerability to psychopathology. This study explores the genetic factor structure underlying reward-related traits and examines how genetic variance links to psychopathology. We modeled GWAS data from ten reward-related traits: risk tolerance (N = 975,353), extraversion (N = 122,886), sensation seeking (N = 132,395), (lack of) premeditation (N = 132,667), (lack of) perseverance (N = 133,517), positive urgency (N = 132,132), negative urgency (N = 132,559), attentional impulsivity (N = 124,739), motor impulsivity (N = 124,104), and nonplanning impulsivity (N = 123,509) to derive their genetic factor structure.

Unincorporation in counties as a political determinant of health: An exploration of five states.

Local government policies and practices shape the context of the places that can alter a population's life chances through socioeconomic factors, built environments, and healthcare access. County governments, one of the most ubiquitous U.S.

A Cost-effective, High-throughput, Highly Accurate Genotyping Method for Outbred Populations.

Affordable sequencing and genotyping methods are essential for large scale genome-wide association studies. While genotyping microarrays and reference panels for imputation are available for human subjects, non-human model systems often lack such options. Our lab previously demonstrated an efficient and cost-effective method to genotype heterogeneous stock rats using double-digest genotyping-by-sequencing.

Contraceptives or Hormone Replacement Therapy and Associations with Autoimmune Conditions: Exploring Effects of Estrogen Analog Supplementation.

Objective: The aim of this study was to investigate the impact of estrogen and progesterone analog supplementation on the development of autoimmune conditions.

Methods: This retrospective observational study used data from the TriNetX network, which comprised over 100 million patients from 89 health care organizations. We compared patients exposed to estrogen and progesterone analogs to those exposed to progesterone-only therapy, using 1:1 propensity score matching based on age, ethnicity, and additional criteria.