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Attention Score in Context
| Title |
Evaluation of pleiotropic effects among common genetic loci identified for cardio-metabolic traits in a Korean population
|
|---|---|
| Published in |
Cardiovascular Diabetology, February 2016
|
| DOI | 10.1186/s12933-016-0337-1 |
| Pubmed ID | |
| Authors |
Yun Kyoung Kim, Mi Yeong Hwang, Young Jin Kim, Sanghoon Moon, Sohee Han, Bong-Jo Kim |
| Abstract |
The genetic contribution to complex diseases or traits, including cardio-metabolic traits, has been elucidated recently by large-scale genome-wide association studies. These genome-wide association studies have indicated that most pleiotropic loci contain genes associated with lipids. Clinically, lipid related abnormalities are strongly associated with other diseases such as type 2 diabetes, coronary artery disease and hypertension. The aim of this study was to evaluate the shared genetic background of lipids and other cardio-metabolic traits. We conducted meta-analyses of the association between 157 published lipid-associated loci and 10 cardio-metabolic traits in 14,028 Korean individuals genotyped using the Exome chip (Illumina HumanExome BeadChip). We also examined whether the pleiotropic effects of such loci constituted independent (i.e., biological) pleiotropy or mediated pleiotropy in these metabolic pathways. Eighteen lipid-associated loci were significantly associated with one of six cardio-metabolic traits after correction for multiple testing (P < 3.70 × 10(-4)). Region 12q24.12 had pleiotropic effects on fasting plasma glucose, blood pressure and obesity-related traits (body mass index and waist-hip ratio) independent of its effects on the lipid profile. Lipid risk scores, calculated according to whether or not subjects carried the risk allele for lipid traits, were significantly associated with fasting plasma glucose, blood pressure and obesity-related traits. The 12q24.12 region showed ethnic-specific genetic pleiotropy among cardio-metabolic traits in this study. Our findings may help to account for molecular mechanisms based on shared genetic background underlying not only dyslipidemia, but also cardiovascular disease and type 2 diabetes. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 6 | 21% |
| Student > Ph. D. Student | 5 | 17% |
| Student > Bachelor | 4 | 14% |
| Professor > Associate Professor | 4 | 14% |
| Researcher | 3 | 10% |
| Other | 3 | 10% |
| Unknown | 4 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 10 | 34% |
| Biochemistry, Genetics and Molecular Biology | 5 | 17% |
| Agricultural and Biological Sciences | 3 | 10% |
| Pharmacology, Toxicology and Pharmaceutical Science | 1 | 3% |
| Computer Science | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 6 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 2. 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 10 June 2016.
All research outputs
#14,854,433
of 22,876,619 outputs
Outputs from Cardiovascular Diabetology
#782
of 1,384 outputs
Outputs of similar age
#221,745
of 397,463 outputs
Outputs of similar age from Cardiovascular Diabetology
#26
of 34 outputs
Altmetric has tracked 22,876,619 research outputs across all sources so far. This one is in the 33rd percentile – i.e., 33% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,384 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 8.8. This one is in the 39th percentile – i.e., 39% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 397,463 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 34 others from the same source and published within six weeks on either side of this one. This one is in the 20th percentile – i.e., 20% of its contemporaries scored the same or lower than it.