The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app

A Galaxy-based bioinformatics pipeline for optimised, streamlined microsatellite development from Illumina next-generation sequencing data

© 2016, The Author(s). Microsatellites are useful tools for ecologists and conservationist biologists, but are taxa-specific and traditionally expensive and time-consuming to develop. New methods using next-generation sequencing (NGS) have reduced these problems, but the plethora of software available for processing NGS data may cause confusion and difficulty for researchers new to the field of bioinformatics. We developed a bioinformatics pipeline for microsatellite development from Illumina paired-end sequences, which is packaged in the open-source bioinformatics tool Galaxy. This optimises and streamlines the design of a microsatellite panel and provides a user-friendly graphical user interface. The pipeline utilises existing programs along with our own novel program and wrappers to: quality-filter and trim reads (Trimmomatic); generate sequence quality reports (FastQC); identify potentially-amplifiable microsatellite loci (Pal_finder); design primers (Primer3); assemble pairs of reads to enhance marker amplification success rates (PANDAseq); and filter optimal loci (Pal_filter). The complete pipeline is freely available for use via a pre-configured Galaxy instance, accessible at https://palfinder.ls.manchester.ac.uk

The Human Phenotype Ontology in 2024: phenotypes around the world.

The Human Phenotype Ontology (HPO) is a widely used resource that comprehensively organizes and defines the phenotypic features of human disease, enabling computational inference and supporting genomic and phenotypic analyses through semantic similarity and machine learning algorithms. The HPO has widespread applications in clinical diagnostics and translational research, including genomic diagnostics, gene-disease discovery, and cohort analytics. In recent years, groups around the world have developed translations of the HPO from English to other languages, and the HPO browser has been internationalized, allowing users to view HPO term labels and in many cases synonyms and definitions in ten languages in addition to English. Since our last report, a total of 2239 new HPO terms and 49235 new HPO annotations were developed, many in collaboration with external groups in the fields of psychiatry, arthrogryposis, immunology and cardiology. The Medical Action Ontology (MAxO) is a new effort to model treatments and other measures taken for clinical management. Finally, the HPO consortium is contributing to efforts to integrate the HPO and the GA4GH Phenopacket Schema into electronic health records (EHRs) with the goal of more standardized and computable integration of rare disease data in EHRs

Recommendations for early referral of individuals with suspected polymyalgia rheumatica: An initiative from the international giant cell arteritis and polymyalgia rheumatica study group

Objective To develop international consensus-based recommendations for early referral of individuals with suspected polymyalgia rheumatica (PMR). Methods A task force including 29 rheumatologists/ internists, 4 general practitioners, 4 patients and a healthcare professional emerged from the international giant cell arteritis and PMR study group. The task force supplied clinical questions, subsequently transformed into Population, Intervention, Comparator, Outcome format. A systematic literature review was conducted followed by online meetings to formulate and vote on final recommendations. Levels of evidence (LOE) (1–5 scale) and agreement (LOA) (0–10 scale) were evaluated. Results Two overarching principles and five recommendations were developed. LOE was 4–5 and LOA ranged between 8.5 and 9.7. The recommendations suggest that (1) each individual with suspected or recently diagnosed PMR should be considered for specialist evaluation, (2) before referring an individual with suspected PMR to specialist care, a thorough history and clinical examination should be performed and preferably complemented with urgent basic laboratory investigations, (3) individuals with suspected PMR with severe symptoms should be referred for specialist evaluation using rapid access strategies, (4) in individuals with suspected PMR who are referred via rapid access, the commencement of glucocorticoid therapy should be deferred until after specialist evaluation and (5) individuals diagnosed with PMR in specialist care with a good initial response to glucocorticoids and a low risk of glucocorticoid related adverse events can be managed in primary care. Conclusions These are the first international recommendations for referral of individuals with suspected PMR, which complement the European Alliance of Associations for Rheumatology/American College of Rheumatology management guidelines for established PMR

Linkage between fecal androgen and glucocorticoid metabolites, spermaturia, body weight and onset of puberty in male African lions (Panthera leo).

There is limited physiological information on onset of puberty in male lions. The aim of this study was to use longitudinal non-invasive monitoring to: 1) assess changes in steroid metabolite excretory patterns as a function of age and body weight; 2) determine correlations between fecal androgen (FAM) and glucocorticoid (FGM) metabolite concentrations; and 3) confirm spermiogenesis non-invasively through urinalysis. Specifically, FAM and FGM metabolites were analyzed in samples collected twice weekly from 21 male lions at 17 institutions (0.9-16 years of age) for 3.8 months- 2.5 years to assess longitudinal hormone patterns. In addition, body weights were obtained approximately monthly from 10 individuals at five zoos (0.0-3.0 years), and urine was collected from six males at two facilities (1.2-6.3 years) and evaluated for the presence of spermatozoa. An increase in overall mean FAM occurred at 2.0 years of age, at which point concentrations remained similar throughout adulthood. The onset of puberty occurred earlier in captive-born males (<1.2 years of age) compared to wild-born counterparts (<2.5 years of age). Additionally, males in captivity gained an average of 7.3 kg/month compared to 3.9 kg/month for wild males over the first 2-2.5 years of age. Sperm (spermaturia) was observed in males as young as 1.2 years in captivity compared to 2.5 years in the wild (ejaculates). There was no difference in FAM or FGM concentrations with regards to age or season. Overall, this study demonstrates that: 1) captive male lions attain puberty at an earlier age than wild counterparts; 2) onset of puberty is influenced by body weight (growth rate); and 3) spermiogenesis can be confirmed via urinalysis. Knowledge about the linkage between body weight and onset of puberty could facilitate improved reproductive management of ex situ populations via mitigating the risk of unintended breedings in young animals

Reproductive steroid hormone profiles (μg/g feces, FEM: filled squares, FPM: open circles, dashed line) before and after Suprelorin or MGA treatment and before and after MGA removal.

<p>Suprelorin treatment indicated with black arrows in panel A (SB244) and panel B (SB341), MGA treatment represented with a grey arrow in panel C (SB124) and MGA removal denoted with an open arrow in panel D (SB224). Green data points indicate estrous peaks, vertical blue bars correspond with breeding, black horizontal bars represent non-pregnant luteal phases and orange horizontal bars signify pregnancies. In panel A, the vertical grey bar shows a 9 d contraception-induced estrous event. In panel B, the horizontal grey bar denotes a 14 d oral megestrol acetate (MA) treatment prior to Suprelorin placement.</p

Fecal steroid hormone profiles (μg/g, FEM: filled squares, FPM: open circles) for three females contracepted with Suprelorin.

<p>Panel A (SB200), Panel B (SB283), Panel C (SB218). Baseline and threshold estrogen concentrations are denoted by dashed and dotted lines, respectively. Green data points, a blue vertical bar and an orange horizontal bar indicate estrous peaks, breeding and pregnancy, respectively.</p

Fecal estrogen metabolite (μg/g) profiles of six females of diverse ages.

<p>Panel A: SB408, blue diamonds and SB247, orange circles; Panel B: SB205, purple squares and SB235, red diamonds; Panel C: SB140, grey circles and SB76, pink triangles. Baseline (dashed line) and threshold (dotted line) concentrations were calculated for each female. Estrous peaks are denoted with green data points.</p

Overall and baseline mean (± SE) concentrations of fecal estrogens before and after Suprelorin and MGA contraception treatments.

<p>^a,b,c Within each animal, hormones are compared by column and different subscripts indicate significant difference before and after treatment (<i>P</i> < 0.05).</p><p>*Months post-contraceptive treatment</p><p>^{^}Months after MGA removal</p><p>⁺SB109 was previously treated with DMPA– 10/27/1999 and Suprelorin– 12/1/1999: 2 x 6mg (older formulation). SB109 gave birth 5/23/2002, a reversal 2.5 yr after treatment with the old Suprelorin formulation.</p><p>^ɣSB341 was given oral MA for 14 days around the day of Suprelorin implant placement and the data from those samples are not included in the average hormone values.</p><p>^θSB124 was previously treated with MGA—7/21/1998, 1/21/1999 and 12/17/2003. SB124 gave birth 6/14/2002 and 12/5/2004, reversals of the previous two MGA treatments.</p><p>Overall and baseline mean (± SE) concentrations of fecal estrogens before and after Suprelorin and MGA contraception treatments.</p