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Thomas J, Keels J, Calzone KA, Badzek L, Dewell S, Patch C, Tonkin ET, Dwyer AA. Current State of Genomics in Nursing: A Scoping Review of Healthcare Provider Oriented (Clinical and Educational) Outcomes (2012-2022). Genes (Basel) 2023; 14:2013. [PMID: 38002957 PMCID: PMC10671121 DOI: 10.3390/genes14112013] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/16/2023] [Revised: 10/24/2023] [Accepted: 10/25/2023] [Indexed: 11/26/2023] Open
Abstract
In the 20 years since the initial sequencing of the human genome, genomics has become increasingly relevant to nursing. We sought to chart the current state of genomics in nursing by conducting a systematic scoping review of the literature in four databases (2012-2022). The included articles were categorized according to the Cochrane Collaboration outcome domains/sub-domains, and thematic analysis was employed to identify key topical areas to summarize the state of the science. Of 8532 retrieved articles, we identified 232 eligible articles. The articles primarily reported descriptive studies from the United States and other high-income countries (191/232, 82%). More than half (126/232, 54.3%) aligned with the "healthcare provider oriented outcomes" outcome domain. Three times as many articles related to the "knowledge and understanding" sub-domain compared to the "consultation process" subdomain (96 vs. 30). Five key areas of focus were identified, including "nursing practice" (50/126, 40%), "genetic counseling and screening" (29/126, 23%), "specialist nursing" (21/126, 17%), "nurse preparatory education" (17/126, 13%), and "pharmacogenomics" (9/126, 7%). Only 42/126 (33%) articles reported interventional studies. To further integrate genomics into nursing, study findings indicate there is a need to move beyond descriptive work on knowledge and understanding to focus on interventional studies and implementation of genomics into nursing practice.
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Affiliation(s)
- Joanne Thomas
- Genomics Policy Unit, Faculty of Life Sciences and Education, University of South Wales, Pontypridd CF37 1DL, UK;
| | - Jordan Keels
- William F. Connell School of Nursing, Boston College, Chestnut Hill, MA 02476, USA;
| | - Kathleen A. Calzone
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
- National Institutes of Health, National Cancer Institute, Center for Cancer Research, Genetics Branch, Bethesda, MD 20892, USA
| | - Laurie Badzek
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
- Ross and Carol Nese College of Nursing, Penn State University, University Park, PA 16802, USA
| | - Sarah Dewell
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
- School of Nursing, Thompson Rivers University, Kamloops, BC V2C 0C8, Canada
| | - Christine Patch
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
- Engagement and Society, Wellcome Connecting Science, Hinxton CB10 1RQ, UK
| | - Emma T. Tonkin
- Genomics Policy Unit, Faculty of Life Sciences and Education, University of South Wales, Pontypridd CF37 1DL, UK;
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
| | - Andrew A. Dwyer
- William F. Connell School of Nursing, Boston College, Chestnut Hill, MA 02476, USA;
- Global Genomics Nursing Alliance (G2NA), Pontypridd CF37 1DL, UK; (K.A.C.); (L.B.); (S.D.); (C.P.)
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Identification of Diagnostic Biomarkers, Immune Infiltration Characteristics, and Potential Compounds in Rheumatoid Arthritis. BIOMED RESEARCH INTERNATIONAL 2022; 2022:1926661. [PMID: 35434133 PMCID: PMC9007666 DOI: 10.1155/2022/1926661] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 10/13/2021] [Revised: 01/17/2022] [Accepted: 03/22/2022] [Indexed: 12/12/2022]
Abstract
Aims This study is aimed at investigating the pathogenesis of rheumatoid arthritis (RA) by identifying key biomarkers, associated immune infiltration, and small-molecule compounds using bioinformatic analysis. Methods Six datasets were obtained from the Gene Expression Omnibus database, and the batch effect was adjusted. Functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyse differentially expressed genes (DEGs). Furthermore, candidate small-molecule drugs associated with RA were selected from the Connectivity Map (CMap) database. The least absolute shrinkage and selection operator regression, support vector machine recursive feature elimination, and multivariate logistic regression analyses were performed on DEGs to screen for RA diagnostic markers. The receiver operating characteristic curve, concordance index, and GiViTi calibration band were the metrics used to assess the diagnostic markers of RA identified in this analysis. The single-sample gene set enrichment analysis was performed to calculate the scores of infiltrating immune cells and evaluate the activities of immune-related pathways. Finally, the correlation between screening markers and RA diagnosis was determined. Results A total of 227 DEGs were identified. Functional enrichment analysis and KEGG revealed that DEGs were enriched by the immune response. CMap analysis identified 11 small-molecule compounds with therapeutic potential for RA. In gene expression, the activities of 13 immune cells and 12 immune-related pathways significantly differed between patients with RA and healthy controls. DPYSL3 and SPP1 had the potential to diagnose RA. SPP1 expression was positively correlated with DPYSL3 in 11 immune cells and 10 immune-related pathways. Conclusion This study comprehensively analysed DEGs and immune infiltration and screened for potential diagnostic markers and small-molecule compounds of RA.
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