Association between Patient Characteristics and HPV Vaccination Recommendation for Postpartum Patients: A National Survey of Obstetrician/Gynecologists

Human papillomavirus (HPV) vaccination rates in the U.S. are relatively low. Provider recommendation rates for HPV vaccination often vary by patient age and relationship status. Obstetrician/gynecologists (OB/GYNs) represent a key provider group that can recommend the HPV vaccine. This study examined differences in OB/ GYN recommendation of HPV vaccination for inpatient postpartum patients by age, parity, and marital status. Data were collected from OB/GYNs nationally via a cross-sectional survey. Participants were randomized to two vignette groups (23-year-old patient or 33-year-old patient). Within each group, participants received 4 vignettes that were identical except for patient marital status (married/not in a committed relationship) and number of children (first/third child), and were asked to indicate HPV vaccination recommendation likelihood on a scale of 0 (definitely would not) to 100 (definitely would). A 2 × 2 × 2 general linear model with repeated measures was used to examine main and interaction effects of patient age, relationship status, and parity. 207 OB/GYNs were included in the final analyses. Recommendation was high for 23-year-old patients (range: 64.5–84.6 out of 100). When marital status and parity were held constant, recommendation likelihood was higher for the younger vs. older patient and was also higher for patients not in a committed relationship, compared to married patients (all p-values \u3c 0.001). Differences in recommendation exist when considering age and relationship status, which provides insight into OB/GYN clinical decision-making. Findings highlight the need to address barriers to HPV vaccination recommendation, including awareness of risk factors to consider when recommending the vaccine

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genome-wide significant loci (P < 5 × 10−8) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10−9). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P < 5 × 10−8), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture

Distinct germline genetic susceptibility profiles identified for common non-Hodgkin lymphoma subtypes

Lymphoma risk is elevated for relatives with common non-Hodgkin lymphoma (NHL) subtypes, suggesting shared genetic susceptibility across subtypes. To evaluate the extent of mutual heritability among NHL subtypes and discover novel loci shared among subtypes, we analyzed data from eight genome-wide association studies within the InterLymph Consortium, including 10,629 cases and 9505 controls. We utilized Association analysis based on SubSETs (ASSET) to discover loci for subsets of NHL subtypes and evaluated shared heritability across the genome using Genome-wide Complex Trait Analysis (GCTA) and polygenic risk scores. We discovered 17 genome-wide significant loci (P &lt; 5 × 10 ) for subsets of NHL subtypes, including a novel locus at 10q23.33 (HHEX) (P = 3.27 × 10 ). Most subset associations were driven primarily by only one subtype. Genome-wide genetic correlations between pairs of subtypes varied broadly from 0.20 to 0.86, suggesting substantial heterogeneity in the extent of shared heritability among subtypes. Polygenic risk score analyses of established loci for different lymphoid malignancies identified strong associations with some NHL subtypes (P &lt; 5 × 10 ), but weak or null associations with others. Although our analyses suggest partially shared heritability and biological pathways, they reveal substantial heterogeneity among NHL subtypes with each having its own distinct germline genetic architecture. [Abstract copyright: © 2022. This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply.