| Title |
Identification of novel genetic variations affecting osteoarthritis patients
|
|---|---|
| Published in |
BMC Medical Genomics, October 2016
|
| DOI | 10.1186/s12881-016-0330-2 |
| Pubmed ID | |
| Authors |
Mamdooh Abdullah Gari, Mohammed AlKaff, Haneen S. Alsehli, Ashraf Dallol, Abdullah Gari, Muhammad Abu-Elmagd, Roaa Kadam, Mohammed F. Abuzinadah, Mazin Gari, Adel M. Abuzenadah, Kalamegam Gauthaman, Heba Alkhatabi, Mohammed M. Abbas |
| Abstract |
Osteoarthritis (OA) is a progressive joint disease characterized by gradual degradation of extracellular matrix (ECM) components in the cartilage and bone. The ECM of cartilage is a highly specified structure that is mainly composed of type II collagen and provides tensile strength to the tissue via aggrecan and proteoglycans. However, changes in the ECM composition and structure can lead to loss of collagen type II and network integrity. Several risk factors have been correlated with OA including age, genetic predisposition, hereditary factors, obesity, mechanical injuries, and joint trauma. Certain genetic association studies have identified several genes associated with OA using genome-wide association studies (GWASs). We identified several novel genetic variants affecting genes that function in several candidate causative pathways including immune responses, inflammatory and cartilage degradation such as SELP, SPN, and COL6A6. The approach of whole-exome sequencing can be a promising method to identify genetic mutations that can influence the OA disease. |
X Demographics
The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 2 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 46 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 46 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 7 | 15% |
| Researcher | 7 | 15% |
| Professor > Associate Professor | 4 | 9% |
| Student > Master | 3 | 7% |
| Student > Bachelor | 2 | 4% |
| Other | 9 | 20% |
| Unknown | 14 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Biochemistry, Genetics and Molecular Biology | 10 | 22% |
| Medicine and Dentistry | 7 | 15% |
| Agricultural and Biological Sciences | 5 | 11% |
| Nursing and Health Professions | 2 | 4% |
| Computer Science | 1 | 2% |
| Other | 5 | 11% |
| Unknown | 16 | 35% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 25 October 2016.
All research outputs
#17,286,379
of 25,374,647 outputs
Outputs from BMC Medical Genomics
#1,315
of 2,444 outputs
Outputs of similar age
#212,392
of 327,216 outputs
Outputs of similar age from BMC Medical Genomics
#16
of 33 outputs
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