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Ecological communities can be stable over multiple generations, or rapidly shift into structurally and functionally different configurations. In kelp forest ecosystems, overgrazing by sea urchins can abruptly shift forests into alternative states that are void of macroalgae and primarily dominated by actively grazing sea urchins. Beginning in 2014, a sea urchin outbreak along the central coast of California resulted in a patchy mosaic of remnant forests interspersed with sea urchin barrens. In this study, we used a 14-year subtidal monitoring dataset of invertebrates, algae, and fishes to explore changes in community structure associated with the loss of forests. We found that the spatial mosaic of barrens and forests resulted in a region-wide shift in community structure. However, the magnitude of kelp forest loss and taxonomic-level consequences were spatially heterogeneous. Taxonomic diversity declined across the region, but there were no declines in richness for any group, suggesting compositional redistribution. Baseline ecological and environmental conditions, and sea urchin behaviour, explained the persistence of forests through multiple stressors. These results indicate that spatial heterogeneity in preexisting ecological and environmental conditions can explain patterns of community change.

Disparities in data underlying clinical genomic interpretation is an acknowledged problem, but there is a paucity of data demonstrating it. The All of Us Research Program is collecting data including whole-genome sequences, health records, and surveys for at least a million participants with diverse ancestry and access to healthcare, representing one of the largest biomedical research repositories of its kind. Here, we examine pathogenic and likely pathogenic variants that were identified in the All of Us cohort. The European ancestry subgroup showed the highest overall rate of pathogenic variation, with 2.26% of participants having a pathogenic variant. Other ancestry groups had lower rates of pathogenic variation, including 1.62% for the African ancestry group and 1.32% in the Latino/Admixed American ancestry group. Pathogenic variants were most frequently observed in genes related to Breast/Ovarian Cancer or Hypercholesterolemia. Variant frequencies in many genes were consistent with the data from the public gnomAD database, with some notable exceptions resolved using gnomAD subsets. Differences in pathogenic variant frequency observed between ancestral groups generally indicate biases of ascertainment of knowledge about those variants, but some deviations may be indicative of differences in disease prevalence. This work will allow targeted precision medicine efforts at revealed disparities.

Coronary artery calcification (CAC) is a measure of atherosclerosis and a well-established predictor of coronary artery disease (CAD) events. Here we describe a genome-wide association study (GWAS) of CAC in 22,400 participants from multiple ancestral groups. We confirmed associations with four known loci and identified two additional loci associated with CAC (ARSE and MMP16), with evidence of significant associations in replication analyses for both novel loci. Functional assays of ARSE and MMP16 in human vascular smooth muscle cells (VSMCs) demonstrate that ARSE is a promoter of VSMC calcification and VSMC phenotype switching from a contractile to a calcifying or osteogenic phenotype. Furthermore, we show that the association of variants near ARSE with reduced CAC is likely explained by reduced ARSE expression with the G allele of enhancer variant rs5982944. Our study highlights ARSE as an important contributor to atherosclerotic vascular calcification, and a potential drug target for vascular calcific disease.

Multi-omics datasets are becoming more common, necessitating better integration methods to realize their revolutionary potential. Here, we introduce multi-set correlation and factor analysis (MCFA), an unsupervised integration method tailored to the unique challenges of high-dimensional genomics data that enables fast inference of shared and private factors. We used MCFA to integrate methylation markers, protein expression, RNA expression, and metabolite levels in 614 diverse samples from the Trans-Omics for Precision Medicine/Multi-Ethnic Study of Atherosclerosis multi-omics pilot. Samples cluster strongly by ancestry in the shared space, even in the absence of genetic information, while private spaces frequently capture dataset-specific technical variation. Finally, we integrated genetic data by conducting a genome-wide association study (GWAS) of our inferred factors, observing that several factors are enriched for GWAS hits and trans-expression quantitative trait loci. Two of these factors appear to be related to metabolic disease. Our study provides a foundation and framework for further integrative analysis of ever larger multi-modal genomic datasets.

BackgroundAflatoxin (AF) exposure is associated with child growth faltering in cross-sectional studies, with limited findings from longitudinal studies.ObjectivesTo evaluate the relationship between maternal AF B1-lysine adduct concentration, child AF B1-lysine adduct concentration, and child growth in the first 30 mo of life.MethodsAF B1-lysine adduct was measured in mother-child dyad plasma samples using isotope dilution mass spectrometry. Using linear regression, we assessed the relationship between AF B1-lysine adduct concentration and child weight, height, and head and mid-upper arm circumferences at 1 wk, 6, 12, 18, 24, and 30 mo of age.ResultsIn adjusted models, maternal prenatal AF B1-lysine adduct (pg/μL) was positively associated with newborn anthropometric outcomes; largest beta coefficients for associations between standardized values were for newborn weight-for-age z-score [β = 0.13; 95% confidence interval (CI): 0.02, 0.24; P < 0.05 and β = 0.11; 95% CI: 0.00, 0.22; P < 0.05 for second and third trimester AF, respectively]. Child AF B1-lysine adduct (pg/μL) at 6 mo was negatively associated with head circumference-for-age z-score at 6, 18, 24, and 30 mo, with beta coefficients ranging from β = -0.15; 95% CI: -0.28, -0.02 to β = -0.17; 95% CI: -0.31, -0.03; P < 0.05); 18-mo AF was negatively associated with anthropometric outcomes at 18, 24, and 30 mo, most consistently with length-for-age z-score (β = -0.18; 95% CI: -0.32, -0.04, β = -0.21; 95% CI: -0.35, -0.07, β = -0.18; 95% CI: -0.32, -0.03 at 18, 24 and 30 mo, respectively).ConclusionsChild AF exposure was associated with impaired child growth, but maternal AF exposure was not. Exposure during infancy was linked to persistent deficit in head circumference, implying reduced brain size lasting beyond the age of 2 years. Exposure at 18 mo was linked to persistent linear growth deficit. Further research should elucidate mechanisms through which AF affects child growth.

Background/objectivesObesity, defined as excessive fat accumulation that represents a health risk, is increasing in adults and children, reaching global epidemic proportions. Body mass index (BMI) correlates with body fat and future health risk, yet differs in prediction by fat distribution, across populations and by age. Nonetheless, few genetic studies of BMI have been conducted in ancestrally diverse populations. Gene expression association with BMI was assessed in the Multi-Ethnic Study of Atherosclerosis (MESA) in four self-identified race and ethnicity (SIRE) groups to identify genes associated with obesity.Subjects/methodsRNA-sequencing was performed on 1096 MESA participants (37.8% white, 24.3% Hispanic, 28.4% African American, and 9.5% Chinese American) and linear models were used to assess the association of expression from each gene for its effect on BMI, adjusting for age, sex, sequencing center, study site, five expression and four genetic principal components in each self-identified race group. Sample-size-weighted meta-analysis was performed to identify genes with BMI-associated expression across ancestry groups.ResultsWithin individual SIRE groups, there were zero to three genes whose expression is significantly (p

Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.

OBJECTIVES: In an evolving era of immunotherapeutic options for persistent or recurrent laryngeal squamous cell carcinoma (LSCC), there is a need for improved biomarkers of treatment response and survival to inform optimal treatment selection and prognostication. Herein, our primary objective was to explore correlations between tumor infiltrating lymphocytes (TILs) and PD-L1 Combined Positive Score (CPS). Secondarily, we sought to explore their combined association with survival outcomes in patients with persistent or recurrent LSCC treated with salvage surgery. MATERIALS AND METHODS: This was a retrospective cohort study at a single academic medical center. Immunohistochemistry staining for TILs and PD-L1 was performed on a tissue microarray of persistent or recurrent LSCC pathologic specimens. Correlations between TIL subsets and PD-L1 CPS were examined using Pearsons correlation coefficient and survival outcomes were analyzed with the Kaplan-Meier method and log-rank tests. RESULTS: Only CD103+ TILs showed a statistically significant, weakly-positive correlation with PD-L1 CPS (r2 = 0.264, p

The doctoral degree in counselor education and supervision is increasingly sought after by students, with the Council for Accreditation of Counseling and Related Educational Programs (CACREP) reporting a 27% enrollment increase in just a 4-year span. As new programs are started and existing programs sustained, administrators and faculty may be seeking guidance in how to build a high-quality program. Yet no literature currently exists for how doctoral counseling faculty define a high-quality program. This study used a basic qualitative research design to examine faculty perceptions of high-quality doctoral programs (N = 15). The authors analyzed data from in-depth interviews with core faculty members at CACREP-accredited doctoral programs. Five themes emerged from the data: relationships, mission alignment, development of a counselor educator identity, inclusiveness of diversity, and Carnegie classification. The findings of this study can be important for faculty and administrators to consider when establishing and maintaining a counselor education and supervision doctoral program.