Application of prioritization approaches to optimize environmental monitoring and testing of pharmaceuticals

Pharmaceuticals are ubiquitous in the natural environment with concentrations expected to rise as human population increases. Environmental risk assessments are available for a small portion of pharmaceuticals in use, raising concerns over the potential risks posed by other drugs that have little or no data. With >1900 active pharmaceutical ingredients in use, it would be a major task to test all of the compounds with little or no data. Desk-based prioritization studies provide a potential solution by identifying those substances that are likely to pose the greatest risk to the environment and which, therefore, need to be considered a priority for further study. The aim of this review was to (1) provide an overview of different prioritization exercises performed for pharmaceuticals in the environment and the results obtained; and (2) propose a new holistic risk-based prioritization framework for drugs in the environment. The suggested models to underpin this framework are discussed in terms of validity and applicability. The availability of data required to run the models was assessed and data gaps identified. The implementation of this framework may harmonize pharmaceutical prioritization efforts and ensure that, in the future, experimental resources are focused on molecules, endpoints, and environmental compartments that are biologically relevant

Stepped Care for Maternal Mental Health: A Case Study of the Perinatal Mental Health Project in South Africa

As one article in a series on Global Mental Health Practice, Simone Honikman and colleagues from South Africa provide a case study of the Perinatal Mental Health Project, which delivered mental health care to pregnant women in a collaborative, step-wise manner, making use of existing resources in primary care

Case report: Adult-onset limb girdle muscular dystrophy in sibling pair due to novel homozygous LAMA2 missense variant

Recessive pathogenic variants in the laminin subunit alpha 2 (LAMA2) gene cause a spectrum of disease ranging from severe congenital muscular dystrophy to later-onset limb girdle muscular dystrophy (LGMDR23). The phenotype of LGMDR23 is characterized by slowly progressive proximal limb weakness, contractures, raised creatine kinase, and sometimes distinctive cerebral white matter changes and/or epilepsy. We present two siblings, born to consanguineous parents, who developed adult-onset LGMDR23 associated with typical cerebral white matter changes and who both later developed dementia. The male proband also had epilepsy and upper motor neuron signs when he presented at age 72. Merosin immunohistochemistry and Western blot on muscle biopsies taken from both subjects was normal. Whole exome sequencing revealed a previously unreported homozygous missense variant in LAMA2 [Chr6(GRCh38):g.129297734G>A; NM_000426.3:c.2906G>A; p.(Cys969Tyr)] in the proband. The same homozygous LAMA2 variant was confirmed by Sanger sequencing in the proband's affected sister. These findings expand the genotypic and phenotypic spectrum of LGMDR23

Primate-specific evolution of noncoding element insertion into PLA2G4C and human preterm birth

Background The onset of birth in humans, like other apes, differs from non-primate mammals in its endocrine physiology. We hypothesize that higher primate-specific gene evolution may lead to these differences and target genes involved in human preterm birth, an area of global health significance. Methods We performed a comparative genomics screen of highly conserved noncoding elements and identified PLA2G4C, a phospholipase A isoform involved in prostaglandin biosynthesis as human accelerated. To examine whether this gene demonstrating primate-specific evolution was associated with birth timing, we genotyped and analyzed 8 common single nucleotide polymorphisms (SNPs) in PLA2G4C in US Hispanic (n = 73 preterm, 292 control), US White (n = 147 preterm, 157 control) and US Black (n = 79 preterm, 166 control) mothers. Results Detailed structural and phylogenic analysis of PLA2G4C suggested a short genomic element within the gene duplicated from a paralogous highly conserved element on chromosome 1 specifically in primates. SNPs rs8110925 and rs2307276 in US Hispanics and rs11564620 in US Whites were significant after correcting for multiple tests (p < 0.006). Additionally, rs11564620 (Thr360Pro) was associated with increased metabolite levels of the prostaglandin thromboxane in healthy individuals (p = 0.02), suggesting this variant may affect PLA2G4C activity. Conclusions Our findings suggest that variation in PLA2G4C may influence preterm birth risk by increasing levels of prostaglandins, which are known to regulate labor.Children’s Discovery InstituteMarch of Dimes Birth Defects FoundationNational Institute of General Medical Sciences (U.S.) (grant T32 GM081739)Washington University (Saint Louis, Mo.) (Mr. and Mrs. Spencer T. Olin Fellowship for Women in Graduate Study)Sigrid Jusélius FoundationSigne and Anne Gyllenberg FoundationAcademy of FinlandVanderbilt University (Turner-Hazinski grant award

Mortality Among Adults With Cancer Undergoing Chemotherapy or Immunotherapy and Infected With COVID-19

Importance: Large cohorts of patients with active cancers and COVID-19 infection are needed to provide evidence of the association of recent cancer treatment and cancer type with COVID-19 mortality. // Objective: To evaluate whether systemic anticancer treatments (SACTs), tumor subtypes, patient demographic characteristics (age and sex), and comorbidities are associated with COVID-19 mortality. // Design, Setting, and Participants: The UK Coronavirus Cancer Monitoring Project (UKCCMP) is a prospective cohort study conducted at 69 UK cancer hospitals among adult patients (≥18 years) with an active cancer and a clinical diagnosis of COVID-19. Patients registered from March 18 to August 1, 2020, were included in this analysis. // Exposures: SACT, tumor subtype, patient demographic characteristics (eg, age, sex, body mass index, race and ethnicity, smoking history), and comorbidities were investigated. // Main Outcomes and Measures: The primary end point was all-cause mortality within the primary hospitalization. // Results: Overall, 2515 of 2786 patients registered during the study period were included; 1464 (58%) were men; and the median (IQR) age was 72 (62-80) years. The mortality rate was 38% (966 patients). The data suggest an association between higher mortality in patients with hematological malignant neoplasms irrespective of recent SACT, particularly in those with acute leukemias or myelodysplastic syndrome (OR, 2.16; 95% CI, 1.30-3.60) and myeloma or plasmacytoma (OR, 1.53; 95% CI, 1.04-2.26). Lung cancer was also significantly associated with higher COVID-19–related mortality (OR, 1.58; 95% CI, 1.11-2.25). No association between higher mortality and receiving chemotherapy in the 4 weeks before COVID-19 diagnosis was observed after correcting for the crucial confounders of age, sex, and comorbidities. An association between lower mortality and receiving immunotherapy in the 4 weeks before COVID-19 diagnosis was observed (immunotherapy vs no cancer therapy: OR, 0.52; 95% CI, 0.31-0.86). // Conclusions and Relevance: The findings of this study of patients with active cancer suggest that recent SACT is not associated with inferior outcomes from COVID-19 infection. This has relevance for the care of patients with cancer requiring treatment, particularly in countries experiencing an increase in COVID-19 case numbers. Important differences in outcomes among patients with hematological and lung cancers were observed

An expanded evaluation of protein function prediction methods shows an improvement in accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent. Keywords: Protein function prediction, Disease gene prioritizationpublishedVersio

An Expanded Evaluation of Protein Function Prediction Methods Shows an Improvement In Accuracy

Background: A major bottleneck in our understanding of the molecular underpinnings of life is the assignment of function to proteins. While molecular experiments provide the most reliable annotation of proteins, their relatively low throughput and restricted purview have led to an increasing role for computational function prediction. However, assessing methods for protein function prediction and tracking progress in the field remain challenging. Results: We conducted the second critical assessment of functional annotation (CAFA), a timed challenge to assess computational methods that automatically assign protein function. We evaluated 126 methods from 56 research groups for their ability to predict biological functions using Gene Ontology and gene-disease associations using Human Phenotype Ontology on a set of 3681 proteins from 18 species. CAFA2 featured expanded analysis compared with CAFA1, with regards to data set size, variety, and assessment metrics. To review progress in the field, the analysis compared the best methods from CAFA1 to those of CAFA2. Conclusions: The top-performing methods in CAFA2 outperformed those from CAFA1. This increased accuracy can be attributed to a combination of the growing number of experimental annotations and improved methods for function prediction. The assessment also revealed that the definition of top-performing algorithms is ontology specific, that different performance metrics can be used to probe the nature of accurate predictions, and the relative diversity of predictions in the biological process and human phenotype ontologies. While there was methodological improvement between CAFA1 and CAFA2, the interpretation of results and usefulness of individual methods remain context-dependent

The genetic architecture of the human cerebral cortex

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder