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Editor’s note iNature is China’s largest academic official account.
It is jointly created by the doctoral team of Tsinghua University, Harvard University, Chinese Academy of Sciences and other units.
The iNature Talent Official Account is now launched, focusing on talent recruitment, academic progress, scientific research information, interested parties can Long press or scan the QR code below to follow us
.
iNature osteoarthritis is one of the main causes of disability and pain worldwide, affecting more than 300 million people
.
There is currently no curative treatment, and management strategies focus on relieving symptoms through pain relief and arthroplasty
.
Therefore, there is an urgent need to understand the cause of the disease and new drug targets in detail
.
On August 26, 2021, the Eleftheria Zeggini team of the Technical University of Munich published a research paper titled "Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations" online in Cell.
The study was conducted on 826,690 individuals (177,517 with osteoarthritis).
A meta-analysis of genome-wide association studies was performed and 100 independently associated risk variants among 11 osteoarthritis phenotypes were identified, 52 of which were not previously associated with the disease
.
The study reported on risk variants for osteoarthritis of the thumb and spine, and determined differences in genetic effects between weight-bearing and non-weight-bearing joints
.
The study identified sex-specific and early age of onset of osteoarthritis risk sites
.
The study integrated functional genomic data from the patient’s primary tissues (including articular cartilage, subchondral bone, and osteophyte cartilage), and identified high-confidence effector genes
.
The study provides evidence of genetic correlation of phenotypes related to pain (main disease symptoms) and identifies possible causal genes related to neuronal processes
.
The results of the study provide insights into key molecular players in the disease process and highlight attractive drug targets to accelerate transformation
.
Osteoarthritis is one of the main causes of disability and pain worldwide, affecting more than 300 million people
.
There is currently no curative treatment, and management strategies focus on relieving symptoms through pain relief and arthroplasty
.
Therefore, there is an urgent need to understand the cause of the disease and new drug targets in detail
.
Osteoarthritis is a complex degenerative disease of the entire joint, which is characterized by cartilage degeneration, subchondral bone thickening, osteophyte formation, synovial inflammation, and structural changes in the joint capsule, ligaments and related muscles
.
Recently, progress has been made in elucidating the genetic background of osteoarthritis using genome-wide association studies (GWAS), with 96 statistically independent risk variants reported to date
.
These variations explain only a small part of the phenotypic variations, mainly related to osteoarthritis affecting the knee and hip joints
.
Article pattern (picture from Cell) Osteoarthritis affects every synovial joint, and the increase in body mass index (BMI) is related to the risk of disease
.
A better understanding of the genetic differences between weight-bearing (knee, hip, and spine) and non-weight-bearing joints (hands, fingers, and thumbs) is needed to help unravel the metabolic and biomechanical effects that lead to disease development
.
Here, the study performed a GWAS meta-analysis of the phenotypes of knee, hip, finger, thumb, and spine osteoarthritis in 826,690 people of European and East Asian descent
.
The research integrates functional genomics analysis of disease-related tissues, including gene expression, protein abundance and whole-genome methylation, mouse gene knockout models and single-gene human disease phenotype data, as well as complementary computational fine mapping, co- Positioning and causal inference methods to identify possible effector genes and promote the conversion of much-needed treatments by enhancing the understanding of the etiology of the disease
.
Reference message: https://#%20
It is jointly created by the doctoral team of Tsinghua University, Harvard University, Chinese Academy of Sciences and other units.
The iNature Talent Official Account is now launched, focusing on talent recruitment, academic progress, scientific research information, interested parties can Long press or scan the QR code below to follow us
.
iNature osteoarthritis is one of the main causes of disability and pain worldwide, affecting more than 300 million people
.
There is currently no curative treatment, and management strategies focus on relieving symptoms through pain relief and arthroplasty
.
Therefore, there is an urgent need to understand the cause of the disease and new drug targets in detail
.
On August 26, 2021, the Eleftheria Zeggini team of the Technical University of Munich published a research paper titled "Deciphering osteoarthritis genetics across 826,690 individuals from 9 populations" online in Cell.
The study was conducted on 826,690 individuals (177,517 with osteoarthritis).
A meta-analysis of genome-wide association studies was performed and 100 independently associated risk variants among 11 osteoarthritis phenotypes were identified, 52 of which were not previously associated with the disease
.
The study reported on risk variants for osteoarthritis of the thumb and spine, and determined differences in genetic effects between weight-bearing and non-weight-bearing joints
.
The study identified sex-specific and early age of onset of osteoarthritis risk sites
.
The study integrated functional genomic data from the patient’s primary tissues (including articular cartilage, subchondral bone, and osteophyte cartilage), and identified high-confidence effector genes
.
The study provides evidence of genetic correlation of phenotypes related to pain (main disease symptoms) and identifies possible causal genes related to neuronal processes
.
The results of the study provide insights into key molecular players in the disease process and highlight attractive drug targets to accelerate transformation
.
Osteoarthritis is one of the main causes of disability and pain worldwide, affecting more than 300 million people
.
There is currently no curative treatment, and management strategies focus on relieving symptoms through pain relief and arthroplasty
.
Therefore, there is an urgent need to understand the cause of the disease and new drug targets in detail
.
Osteoarthritis is a complex degenerative disease of the entire joint, which is characterized by cartilage degeneration, subchondral bone thickening, osteophyte formation, synovial inflammation, and structural changes in the joint capsule, ligaments and related muscles
.
Recently, progress has been made in elucidating the genetic background of osteoarthritis using genome-wide association studies (GWAS), with 96 statistically independent risk variants reported to date
.
These variations explain only a small part of the phenotypic variations, mainly related to osteoarthritis affecting the knee and hip joints
.
Article pattern (picture from Cell) Osteoarthritis affects every synovial joint, and the increase in body mass index (BMI) is related to the risk of disease
.
A better understanding of the genetic differences between weight-bearing (knee, hip, and spine) and non-weight-bearing joints (hands, fingers, and thumbs) is needed to help unravel the metabolic and biomechanical effects that lead to disease development
.
Here, the study performed a GWAS meta-analysis of the phenotypes of knee, hip, finger, thumb, and spine osteoarthritis in 826,690 people of European and East Asian descent
.
The research integrates functional genomics analysis of disease-related tissues, including gene expression, protein abundance and whole-genome methylation, mouse gene knockout models and single-gene human disease phenotype data, as well as complementary computational fine mapping, co- Positioning and causal inference methods to identify possible effector genes and promote the conversion of much-needed treatments by enhancing the understanding of the etiology of the disease
.
Reference message: https://#%20
