ABSTRACT
INTRODUCTION: The study of our genome has played an important role in the field of personalized medicine and clinical practice becoming a useful tool to assist the medical community in the early diagnosis and treatment of countless diseases; osteoarthritis (OA) is a complex chronic degenerative joint disease, despite the high prevalence of this disease and its great impact on public health, little is currently known about its etiology and risk of progression. The purpose of this review is to show the advances in genetics in the study of osteoartrosis. METHODS: The present is a review of the literature of the different aspects in which genetics has developed in the study of osteoartrosis, its scopes and its possible impact on prevention and treatment. CONCLUSION: The identification of a high number of candidate genes confirms the complex nature of the disease, it seems clear that the degree of expression of different genes is altered between an arthrosic patient and a healthy one. A deeper understanding of the link between the entire genome sequence and the association with well-characterized OA phenotypes will enable the development of biomarkers, report the risk of disease progression and allow better guidance of treatments.
INTRODUCCIÓN: El estudio de nuestro genoma ha jugado un papel importante en el campo de la medicina personalizada y la práctica clínica, lo que la convierte en una herramienta útil para ayudar a la comunidad médica en el diagnóstico y tratamiento temprano de innumerables enfermedades. La osteoartrosis (OA) es una enfermedad articular degenerativa crónica compleja; a pesar de su alta prevalencia y gran impacto en la salud pública, actualmente se sabe poco sobre su etiología y riesgo de progresión. El objeto de la presente revisión es mostrar los avances de la genética en el estudio de la osteoartrosis. MÉTODOS: Revisión de la literatura sobre los diferentes aspectos en donde la genética se ha desarrollado en el estudio de la osteoartrosis, sus alcances y sus posibles repercusiones en la prevención y tratamiento. CONCLUSIÓN: La identificación de un elevado número de genes candidatos nos confirma la compleja naturaleza de la enfermedad, parece claro que el grado de expresión de diferentes genes está alterado entre un paciente artrósico y uno sano. Una comprensión más profunda del vínculo entre la secuencia de todo el genoma y la asociación con fenotipos bien caracterizados de la OA, permitirá el desarrollo de biomarcadores, informar el riesgo de progresión de la enfermedad y permitir una mejor orientación de los tratamientos.
Subject(s)
Osteoarthritis , Biomarkers , Disease Progression , Humans , Osteoarthritis/genetics , PhenotypeABSTRACT
In the last fifteen years, published reports have described KIR gene-content frequency distributions in more than 120 populations worldwide. However, there have been limited studies examining these data in aggregate to detect overall patterns of variation at regional and global levels. Here, we present a summary of the collection of KIR gene-content data for 105 worldwide populations collected as part of the 15th and 16th International Histocompatibility and Immunogenetics Workshops, and preliminary results for data analysis.
Subject(s)
Genetic Variation , Histocompatibility/genetics , Receptors, KIR/genetics , Ethnicity/genetics , Gene Frequency , Genetics, Population , Haplotypes , Humans , Immunoglobulins/genetics , LigandsABSTRACT
Continuing a project presented at the 15th International HLA and Immunogenetics Workshop (IHIWS) on the rarity of HLA alleles, we sought to expand the number of data sources and bioinformatics tools available in the Allele Frequencies Net Database website (AFND, www.allelefrequencies.net). In this 16th IHIWS Rare Alleles project, HLA alleles described in the latest IMGT/HLA Database (release 3.8.0) were queried against different sources including data from registries (stem cell) and from 74 different laboratories around the world. We demonstrated that approximately 40% of the alleles officially named in the IMGT/HLA Database have been reported only once across all different sources. To facilitate the large-scale analysis of rare alleles, we have produced an online tool called the Rare Allele Detector that simplifies the detection of alleles that are considered to be 'very rare', 'rare' or 'frequent'. Tools and associated data can be accessed via the www.allelefrequencies.net website.