Demetra Application: An integrated genotype analysis web server for clinical genomics in endometriosis

Professional-Facing Digital Health Technology for the Care of Patients With Chronic Pain: Scoping Review

BACKGROUND

Chronic pain is a highly prevalent condition, estimated to affect as many as 30% of people worldwide. The need for more innovative solutions for chronic pain management is clear, and digital health technology (DHT) may be the best way to address this challenge. Much of the digital health research focusing on chronic pain focuses on patient-facing solutions; however, DHT for health care professionals (HCPs) is equally important to support evidence-based practice, which, in turn, improves patient outcomes. Despite this, no review has investigated the availability of professional-facing DHT for chronic pain management.

OBJECTIVE

This scoping review aims to identify the available professional-facing DHTs for chronic pain management. Specifically, the objectives were to investigate the components of the DHTs as well as development methods, user features, outcomes, and HCP perspectives on DHTs for chronic pain care.

METHODS

Databases, including MEDLINE, Embase, CINAHL, PsycINFO, and Inspec, were searched using comprehensive search strategies. Two independent reviewers screened titles and abstracts for inclusion of studies in the review and conducted full-text screening. Any conflicts in each stage of the screening process were first resolved through discussion and then through a third independent reviewer. Data extraction and quality assessment were completed using the Template for Intervention Description and Replication (TiDIER) checklist and Quality Assessment for Diverse Studies. Qualitative analysis involved inductive content analysis of user features and thematic synthesis of HCP perspectives.

RESULTS

In total, 52 studies were included in the review, reporting on 44 professional-facing DHTs. The included DHTs were intended for remote patient monitoring, clinical decision support, assessment and diagnosis, education of HCPs, or a combination. The most common target population for DHT use was multidisciplinary care teams; the most common setting for implementation was primary care. Approximately half (26/44, 59%) of the professional-facing DHTs had a connected patient-facing system. Inductive content analysis of the user features produced 4 themes: guiding initial consultation, supporting chronic pain management, facilitating ongoing patient management, and supporting routine clinical duties. The thematic synthesis of HCP perspectives produced the following 4 themes, reflecting factors affecting the use of DHTs in chronic pain care: additional value, integration into clinical workflow, ease of navigation, and trust in the DHTs. Most (43/52, 83%) of the included studies did not adequately report appropriate stakeholder involvement in a proper co-design of DHTs; only 7% (3/44) of the DHTs were reported to have been developed with guidance from a system development framework.

CONCLUSIONS

There are various DHTs available for HCPs to use in the management of chronic pain. The included studies neither reported adequate stakeholder involvement in the DHT development nor any specific frameworks to guide rigorous co-design. Therefore, future research should focus on developing professional-facing DHTs with active involvement of stakeholders in the design process.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-10.2196/51311.

Semantic and Population Analysis of the Genetic Targets Related to COVID-19 and Its Association with Genes and Diseases

SARS-CoV-2 is a coronavirus responsible for one of the most serious, modern worldwide pandemics, with lasting and multifaceted effects. By late 2021, SARS-CoV-2 has infected more than 180 million people and has killed more than 3 million. The virus gains entrance to human cells through binding to ACE2 via its surface spike protein and causes a complex disease of the respiratory system, termed COVID-19. Vaccination efforts are being made to hinder the viral spread, and therapeutics are currently under development. Toward this goal, scientific attention is shifting toward variants and SNPs that affect factors of the disease such as susceptibility and severity. This genomic grammar, tightly related to the dark part of our genome, can be explored through the use of modern methods such as natural language processing. We present a semantic analysis of SARS-CoV-2-related publications, which yielded a repertoire of SNPs, genes, and disease ontologies. Population data from the 1000 Genomes Project were subsequently integrated into the pipeline. Data mining approaches of this scale have the potential to elucidate the complex interaction between COVID-19 pathogenesis and host genetic variation; the resulting knowledge can facilitate the management of high-risk groups and aid the efforts toward precision medicine.

Epione application: An integrated web‑toolkit of clinical genomics and personalized medicine in systemic lupus erythematosus

Genome wide association studies (GWAS) have identified autoimmune disease-associated loci, a number of which are involved in numerous disease-associated pathways. However, much of the underlying genetic and pathophysiological mechanisms remain to be elucidated. Systemic lupus erythematosus (SLE) is a chronic, highly heterogeneous auto-immune disease, characterized by differences in autoantibody profile, serum cytokines and a multi-system involvement. This study presents the Epione application, an integrated bioinformatics web-toolkit, designed to assist medical experts and researchers in more accurately diagnosing SLE. The application aims to identify the most credible gene variants and single nucleotide polymorphisms (SNPs) associated with SLE susceptibility, by using patient's genomic data to aid the medical expert in SLE diagnosis. The application contains useful knowledge of >70,000 SLE-related publications that have been analyzed, using data mining and semantic techniques, towards extracting the SLE-related genes and the corresponding SNPs. Probable genes associated with the patient's genomic profile are visualized with several graphs, including chromosome ideograms, statistic bars and regulatory networks through data mining studies with relative publications, to obtain a representative number of the most credible candidate genes and biological pathways associated with the SLE. Furthermore, an evaluation study was performed on a patient diagnosed with SLE and is presented herein. Epione has also been expanded in family-related candidate patients to evaluate its predictive power. All the recognized gene variants that were previously considered to be associated with SLE were accurately identified in the output profile of the patient, and by comparing the results, novel findings have emerged. The Epione application may assist and facilitate in early stage diagnosis by using the patients' genomic profile to compare against the list of the most predictable candidate gene variants related to SLE. Its diagnosis-oriented output presents the user with a structured set of results on variant association, position in genome and links to specific bibliography and gene network associations. The overall aim of the present study was to provide a reliable tool for the most effective study of SLE. This novel and accessible webserver tool of SLE is available at http://geneticslab.aua.gr/epione/.