Title |
Insight into rheumatological cause and effect through the use of Mendelian randomization
|
---|---|
Published in |
Nature Reviews Rheumatology, July 2016
|
DOI | 10.1038/nrrheum.2016.102 |
Pubmed ID | |
Authors |
Philip C. Robinson, Hyon K. Choi, Ron Do, Tony R. Merriman |
Abstract |
Establishing causality of risk factors is important to determine the pathogenetic mechanisms underlying rheumatic diseases, and can facilitate the design of interventions to improve care for affected patients. The presence of unmeasured confounders, as well as reverse causation, is a challenge to the assignment of causality in observational studies. Alleles for genetic variants are randomly inherited at meiosis. Mendelian randomization analysis uses these genetic variants to test whether a particular risk factor is causal for a disease outcome. In this Review of the Mendelian randomization technique, we discuss published results and potential applications in rheumatology, as well as the general clinical utility and limitations of the approach. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 4 | 16% |
Australia | 4 | 16% |
United States | 2 | 8% |
Japan | 2 | 8% |
Spain | 1 | 4% |
Curaçao | 1 | 4% |
Russia | 1 | 4% |
Singapore | 1 | 4% |
Finland | 1 | 4% |
Other | 2 | 8% |
Unknown | 6 | 24% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 10 | 40% |
Members of the public | 10 | 40% |
Science communicators (journalists, bloggers, editors) | 3 | 12% |
Practitioners (doctors, other healthcare professionals) | 2 | 8% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 2% |
United States | 1 | 2% |
Unknown | 62 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 14 | 22% |
Student > Bachelor | 10 | 16% |
Student > Ph. D. Student | 8 | 13% |
Student > Master | 5 | 8% |
Other | 4 | 6% |
Other | 12 | 19% |
Unknown | 11 | 17% |
Readers by discipline | Count | As % |
---|---|---|
Medicine and Dentistry | 21 | 33% |
Biochemistry, Genetics and Molecular Biology | 12 | 19% |
Agricultural and Biological Sciences | 8 | 13% |
Mathematics | 2 | 3% |
Computer Science | 2 | 3% |
Other | 4 | 6% |
Unknown | 15 | 23% |