Best Practice & Research in Clinical Rheumatology最新文献

{"title":"Genetics of rheumatoid arthritis","authors":"Seema D. Sharma ,&nbsp;Shek H. Leung ,&nbsp;Sebastien Viatte","doi":"10.1016/j.berh.2024.101968","DOIUrl":"10.1016/j.berh.2024.101968","url":null,"abstract":"<div><div>In the past four decades, a plethora of genetic association studies have been carried out in cohorts of patients with rheumatoid arthritis. These studies have highlighted key aspects of disease pathogenesis and suggested causal mechanisms. In this review, we discuss major advances in our understanding of the genetic architecture of rheumatoid arthritis susceptibility, severity and treatment response and explain how genetics supports current models of disease pathogenesis and outcome. We outline future research directions, like Mendelian randomisation, and present a number of potential avenues for clinical translation, including risk and outcome prediction, patient stratification into treatment response groups and pharmacological applications.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101968"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494185","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Insights into the genetic landscape of systemic sclerosis","authors":"Ali El-Halwagi,&nbsp;Sandeep K. Agarwal","doi":"10.1016/j.berh.2024.101981","DOIUrl":"10.1016/j.berh.2024.101981","url":null,"abstract":"<div><div>Systemic sclerosis (SSc) is a complex autoimmune disease that clinically manifests as progressive fibrosis of the skin and internal organs. Autoimmunity and endothelial dysfunction play important roles in the development of SSc but the causes of SSc remain unknown. Accumulating evidence, first from familial aggregation studies and subsequently from candidate gene association studies and genome wide association studies underscore the crucial contributions of genetics to the development of SSc. The identification of polymorphisms in the HLA region as well as non-HLA loci is important for understanding the risks of developing SSc but can also provide important pathogenic insight in SSc. While not translating into clinic practice yet, understanding the genetic landscape of SSc will hopefully assist in the diagnosis and management of patients with and/or at risk of developing SSc in the future. Herein we review the studies that investigate genetic risks of SSc susceptibility.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101981"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141789824","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Preface to genomics of rheumatic disease","authors":"Anne Barton,&nbsp;Proton Rahman","doi":"10.1016/j.berh.2024.102005","DOIUrl":"10.1016/j.berh.2024.102005","url":null,"abstract":"","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 102005"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142300236","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pharmacogenetics of therapies in rheumatoid arthritis: An update","authors":"Mohamed H. Babiker-Mohamed ,&nbsp;Sambhawana Bhandari ,&nbsp;Prabha Ranganathan","doi":"10.1016/j.berh.2024.101974","DOIUrl":"10.1016/j.berh.2024.101974","url":null,"abstract":"<div><div>Rheumatoid arthritis (RA) is a systemic autoimmune inflammatory arthritis. Despite many treatment advances, achieving remission or low-disease activity in RA remains challenging, often requiring trial and error approaches with numerous medications. Precision medicine, particularly pharmacogenomics, explores how genetic factors influence drug response in individual patients, and incorporates such factors to develop personalized treatments for individual patients. Genetic variations in drug-metabolizing enzymes, transporters, and targets may contribute to inter-individual differences in drug efficacy and toxicity. Advancements in molecular sequencing have allowed rapid identification of such variants, including single nucleotide polymorphisms (SNPs). This review highlights recent major findings in the pharmacogenetics of therapies in RA, focusing on key genes and SNPs to provide insights into current trends and developments in this field.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101974"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141735577","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Use of Mendelian randomization to assess the causal status of modifiable exposures for rheumatic diseases","authors":"Sizheng Steven Zhao ,&nbsp;Stephen Burgess","doi":"10.1016/j.berh.2024.101967","DOIUrl":"10.1016/j.berh.2024.101967","url":null,"abstract":"<div><div>The explosion in Mendelian randomization (MR) publications is hard to ignore and shows no signs of slowing. Clinician readers, who may not be familiar with jargon-ridden methods, are expected to discern the good from the many low-quality studies that make overconfident claims of causality or stretch the plausibility of what MR can investigate. We aim to equip readers with foundational concepts, contextualized using examples in rheumatology, to appraise the many MR papers that are or will appear in their journals. We highlight the importance of assessing whether exposures are under plausibly specific genetic influence, whether the hypothesized causal pathways make biological sense, and whether results stand up to replication and use of control outcomes. Quality of research can vary substantially using MR as with any design, and all methods have inherent limitations. MR studies have provided and can still contribute valuable insights in the context of evidence triangulation.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101967"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7616521/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141477909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Exploring the contribution of genetics on the clinical manifestations of systemic lupus erythematosus","authors":"Ruth D. Rodríguez ,&nbsp;Marta E. Alarcón-Riquelme","doi":"10.1016/j.berh.2024.101971","DOIUrl":"10.1016/j.berh.2024.101971","url":null,"abstract":"<div><div>Systemic lupus erythematosus (SLE) is a complex autoimmune disease characterized by diverse clinical manifestations affecting multiple organs and systems. The understanding of genetic factors underlying the various manifestations of SLE has evolved considerably in recent years. This review provides an overview of the genetic implications in some of the most prevalent manifestations of SLE, including renal involvement, neuropsychiatric, cutaneous, constitutional, musculoskeletal, and cardiovascular manifestations. We discuss the current state of knowledge regarding the genetic basis of these manifestations, highlighting key genetic variants and pathways implicated in their pathogenesis. Additionally, we explore the clinical implications of genetic findings, including their potential role in risk stratification, prognosis, and personalized treatment approaches for patients with SLE. Through a comprehensive examination of the genetic landscape of SLE manifestations, this review aims to provide insights into the underlying mechanisms driving disease heterogeneity and inform future research directions in this field.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101971"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141629257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A review of the advances in understanding the genetic basis of spondylarthritis and emerging clinical benefit","authors":"Michael Stadler ,&nbsp;Sizheng Steven Zhao ,&nbsp;John Bowes","doi":"10.1016/j.berh.2024.101982","DOIUrl":"10.1016/j.berh.2024.101982","url":null,"abstract":"<div><div>Spondyloarthropathies (SpA), including ankylosing spondylitis (AS) and psoriatic arthritis (PsA), have been shown to have a substantial genetic predisposition based on heritability estimates derived from family studies and genome-wide association studies (GWAS). GWAS have uncovered numerous genetic loci associated with susceptibility to SpA, with significant associations to human leukocyte antigen (HLA) genes, which are major genetic risk factors for both AS and PsA. Specific loci differentiating PsA from cutaneous-only psoriasis have been identified, though these remain limited. Further research with larger sample sizes is necessary to identify more PsA-specific genetic markers. Current research focuses on translating these genetic insights into clinical applications. For example, polygenic risk scores are showing promise for the classification of disease risk and diagnosis and future research should focus on refining these risk assessment tools to improve clinical outcomes for individuals with SpA. Addressing these challenges will help integrate genetic testing into patients care and impact clinical practice.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101982"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142121108","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Explainable biology for improved therapies in precision medicine: AI is not enough","authors":"I Jurisica","doi":"10.1016/j.berh.2024.102006","DOIUrl":"10.1016/j.berh.2024.102006","url":null,"abstract":"&lt;div&gt;&lt;div&gt;Technological advances and high-throughput bio-chemical assays are rapidly changing ways how we formulate and test biological hypotheses, and how we treat patients. Most complex diseases arise on a background of genetics, lifestyle and environment factors, and manifest themselves as a spectrum of symptoms. To fathom intricate biological processes and their changes from healthy to disease states, we need to systematically integrate and analyze multi-omics datasets, ontologies, and diverse annotations. Without proper management of such complex biological and clinical data, artificial intelligence (AI) algorithms alone cannot be effectively trained, validated, and successfully applied to provide trustworthy and patient-centric diagnosis, prognosis and treatment. Precision medicine requires to use multi-omics approaches effectively, and offers many opportunities for using AI, “big data” analytics, and integrative computational biology workflows.&lt;/div&gt;&lt;div&gt;Advances in optical and biochemical assay technologies including sequencing, mass spectrometry and imaging modalities have transformed research by empowering us to simultaneously view all genes expressed, identify proteome-wide changes, and assess interacting partners of each individual protein within a dynamically changing biological system, at an individual cell level. While such views are already having an impact on our understanding of healthy and disease conditions, it remains challenging to extract useful information comprehensively and systematically from individual studies, ensure that signal is separated from noise, develop models, and provide hypotheses for further research. Data remain incomplete and are often poorly connected using fragmented biological networks. In addition, statistical and machine learning models are developed at a cohort level and often not validated at the individual patient level.&lt;/div&gt;&lt;div&gt;Combining integrative computational biology and AI has the potential to improve understanding and treatment of diseases by identifying biomarkers and building explainable models characterizing individual patients. From systematic data analysis to more specific diagnostic, prognostic and predictive biomarkers, drug mechanism of action, and patient selection, such analyses influence multiple steps from prevention to disease characterization, and from prognosis to drug discovery. Data mining, machine learning, graph theory and advanced visualization may help identify diagnostic, prognostic and predictive biomarkers, and create causal models of disease. Intertwining computational prediction and modeling with biological experiments leads to faster, more biologically and clinically relevant discoveries.&lt;/div&gt;&lt;div&gt;However, computational analysis results and models are going to be only as accurate and useful as correct and comprehensive are the networks, ontologies and datasets used to build them. High quality, curated data portals provide the necessary foundation for translati","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 102006"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142331878","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Genetics of vasculitis","authors":"Miguel Ángel González-Gay ,&nbsp;Elena Heras-Recuero ,&nbsp;Teresa Blázquez-Sánchez ,&nbsp;Claritza Caraballo-Salazar ,&nbsp;Fernando Rengifo-García ,&nbsp;Santos Castañeda ,&nbsp;Javier Martín ,&nbsp;Ana Marquez ,&nbsp;Raquel Largo","doi":"10.1016/j.berh.2024.101969","DOIUrl":"10.1016/j.berh.2024.101969","url":null,"abstract":"<div><div>Systemic vasculitis encompasses a wide range of conditions characterized by varying degrees of inflammation in blood vessels. Although the etiology of vasculitis remains unclear, accumulated data suggest that it is triggered in genetically predisposed individuals by the concurrence of certain environmental factors. The importance of the genetic component has been consistently supported by evidence of familial aggregation, differential prevalence by ethnicity, and multiple genetic associations with disease susceptibility and severity reported in recent years. The strongest association signals in most vasculitides correspond to genetic variants within the <em>HLA</em> region, suggesting an important role of the immune system in its pathophysiology. However, each type of vasculitis has distinct defining <em>HLA</em> association markers, likely due to disease-specific differences in antigenic drivers. Furthermore, other genetic polymorphisms located outside the <em>HLA</em> region play an important role in susceptibility to different vasculitides. More recent research has assessed the shared genetic susceptibility evident across different vasculitides. Future studies should focus on the identification of genetic markers that can serve as reliable biomarkers for early diagnosis, prognosis, and treatment response in systemic vasculitis.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101969"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141494186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The importance of functional genomics studies in precision rheumatology","authors":"Ana Pires Piedade ,&nbsp;Jake Butler ,&nbsp;Stephen Eyre ,&nbsp;Gisela Orozco","doi":"10.1016/j.berh.2024.101988","DOIUrl":"10.1016/j.berh.2024.101988","url":null,"abstract":"<div><div>Rheumatic diseases, those that affect the musculoskeletal system, cause significant morbidity. Among risk factors of these diseases is a significant genetic component. Recent advances in high-throughput omics techniques now allow a comprehensive profiling of patients at a genetic level through genome-wide association studies. Without functional interpretation of variants identified through these studies, clinical insight remains limited. Strategies include statistical fine-mapping that refine the list of variants in loci associated with disease, whilst colocalization techniques attempt to attribute function to variants that overlap a genetically active chromatin annotation. Functional validation using genome editing techniques can be used to further refine genetic signals and identify key pathways in cell types relevant to rheumatic disease biology. Insight gained from the combination of genetic studies and functional validation can be used to improve precision medicine in rheumatic diseases by allowing risk prediction and drug repositioning.</div></div>","PeriodicalId":50983,"journal":{"name":"Best Practice & Research in Clinical Rheumatology","volume":"38 4","pages":"Article 101988"},"PeriodicalIF":4.5,"publicationDate":"2024-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142037692","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}