Preliminary assessment of three quantitative approaches for estimating time-since-deposition from autofluorescence and morphological profiles of cell populations from forensic biological samples.

Determining when DNA recovered from a crime scene transferred from its biological source, i.e., a sample's 'time-since-deposition' (TSD), can provide critical context for biological evidence.

Improving the discovery of rare variants associated with alcohol problems by leveraging machine learning phenotype prediction and functional information.

Alcohol use disorder (AUD) is moderately heritable with significant social and economic impact. Genome-wide association studies (GWAS) have identified common variants associated with AUD, however, rare variant investigations have yet to achieve well-powered sample sizes. In this study, we conducted an interval-based exome-wide analysis of the Alcohol Use Disorder Identification Test Problems subscale (AUDIT-P) using both machine learning (ML) predicted risk and empirical functional weights.

Missingness adapted group informed clustered (MAGIC)-LASSO: a novel paradigm for phenotype prediction to improve power for genetic loci discovery.

The availability of large-scale biobanks linking genetic data, rich phenotypes, and biological measures is a powerful opportunity for scientific discovery. However, real-world collections frequently have extensive missingness. While missing data prediction is possible, performance is significantly impaired by block-wise missingness inherent to many biobanks.

Differentiation of vaginal cells from epidermal cells using morphological and autofluorescence properties: Implications for sexual assault casework involving digital penetration.

Analysis of DNA mixtures from sexual assault evidence is an ongoing challenge for DNA casework laboratories. To assist the forensic scientist address source and activity level propositions there is a significant need for new techniques that can provide information as to the source of DNA, particularly for sexual assault samples that do not involve semen. The goal of this study was to develop a new biological signature system that provides additional probative value to samples comprised of mixtures of epidermal and vaginal cells, as may be observed in cases involving digital penetration.

COVID and college: how the pandemic impacted alcohol use disorder status among students.

Alcohol consumption patterns during the COVID-19 pandemic have varied notably. We examined the acute impact of the pandemic on alcohol use disorder (AUD) in a generalizable sample of college students who were surveyed pre-pandemic and re-surveyed in May 2020. Items assessed pre-pandemic included DSM-5 AUD and mental health symptoms.

Determining the stability of genome-wide factors in BMI between ages 40 to 69 years.

Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years.

Differential DNA Methylation and Cardiometabolic Risk in African American Mother-Adolescent Dyads.

Background: Cardiovascular disease disproportionately affects African Americans as the leading cause of morbidity and mortality. Among African Americans, compared to other racial groups, cardiovascular disease onset occurs at an earlier age due to a higher prevalence of cardiometabolic risk factors, particularly obesity, hypertension and type 2 diabetes. Emerging evidence suggests that heritable epigenetic processes are related to increased cardiovascular disease risk, but this is largely unexplored in adolescents or across generations.

Psychometric Evaluation of the Patient-Reported Outcomes Measurement Information System Fatigue-Short Form Across Diverse Populations.

Background: The need for reliable, valid tools to measure patient-reported outcomes (PROs) is critical both for research and for evaluating treatment effects in practice. The Patient-Reported Outcomes Measurement Information System Fatigue-Short Form v1.0-Fatigue 7a (PROMIS F-SF) has had limited psychometric evaluation in various populations.

Penalized Ordinal Regression Methods for Predicting Stage of Cancer in High-Dimensional Covariate Spaces.

The pathological description of the stage of a tumor is an important clinical designation and is considered, like many other forms of biomedical data, an ordinal outcome. Currently, statistical methods for predicting an ordinal outcome using clinical, demographic, and high-dimensional correlated features are lacking. In this paper, we propose a method that fits an ordinal response model to predict an ordinal outcome for high-dimensional covariate spaces.