Bayesian Gene Set Benchmark Dose Estimation for "omic" responses.

Motivation: Estimating a toxic reference point using tools like the benchmark dose (BMD) is a critical step in setting policy to regulate pollution and ensure safe environments. Toxicity can be measured for different endpoints, including changes in gene expression and histopathology for various tissues, and is typically explored one gene or tissue at a time in a univariate setting that ignores correlation. In this work, we develop a multivariate estimation procedure to estimate the BMD for specified gene sets.

A multi-ancestry genome-wide association study identifies novel candidate loci in the RARB gene associated with hypertensive disorders of pregnancy.

Genetic factors related to pregnancy-related traits are understudied, especially in ancestrally diverse cohorts. To assess maternal contributions to hypertensive disorders of pregnancy (HDP), we performed a multi-ancestry genome-wide association study (GWAS) of HDP in data from the North Carolina-based Personalized Environment and Genes Study (PEGS) cohort with validation in the UK Biobank (UKBB). The GWAS revealed two maternal loci associated with HDP at the genome-wide significance level.

Geological Net Zero and the need for disaggregated accounting for carbon sinks.

Achieving net zero global emissions of carbon dioxide (CO), with declining emissions of other greenhouse gases, is widely expected to halt global warming. CO emissions will continue to drive warming until fully balanced by active anthropogenic CO removals. For practical reasons, however, many greenhouse gas accounting systems allow some "passive" CO uptake, such as enhanced vegetation growth due to CO fertilisation, to be included as removals in the definition of net anthropogenic emissions.

A genome-wide association study identifies genetic determinants of hemoglobin glycation index with implications across sex and ethnicity.

Introduction: We investigated the genetic determinants of variation in the hemoglobin glycation index (HGI), an emerging biomarker for the risk of diabetes complications.

Methods: We conducted a genome-wide association study (GWAS) for HGI in the Action to Control Cardiovascular Risk in Diabetes (ACCORD) trial ( = 7,913) using linear regression and additive genotype encoding on variants with minor allele frequency greater than 3%. We conducted replication analyses of top findings in the Atherosclerosis Risk in Communities (ARIC) study with inverse variance-weighted meta-analysis.