| Title |
Harnessing publicly available genetic data to prioritize lipid modifying therapeutic targets for prevention of coronary heart disease based on dysglycemic risk
|
|---|---|
| Published in |
Human Genetics, March 2016
|
| DOI | 10.1007/s00439-016-1647-9 |
| Pubmed ID | |
| Authors |
Vinicius Tragante, Folkert W. Asselbergs, Daniel I. Swerdlow, Tom M. Palmer, Jason H. Moore, Paul I. W. de Bakker, Brendan J. Keating, Michael V. Holmes |
| Abstract |
Therapeutic interventions that lower LDL-cholesterol effectively reduce the risk of coronary artery disease (CAD). However, statins, the most widely prescribed LDL-cholesterol lowering drugs, increase diabetes risk. We used genome-wide association study (GWAS) data in the public domain to investigate the relationship of LDL-C and diabetes and identify loci encoding potential drug targets for LDL-cholesterol modification without causing dysglycemia. We obtained summary-level GWAS data for LDL-C from GLGC, glycemic traits from MAGIC, diabetes from DIAGRAM and CAD from CARDIoGRAMplusC4D consortia. Mendelian randomization analyses identified a one standard deviation (SD) increase in LDL-C caused an increased risk of CAD (odds ratio [OR] 1.63 (95 % confidence interval [CI] 1.55, 1.71), which was not influenced by removing SNPs associated with diabetes. LDL-C/CAD-associated SNPs showed consistent effect directions (binomial P = 6.85 × 10(-5)). Conversely, a 1-SD increase in LDL-C was causally protective of diabetes (OR 0.86; 95 % CI 0.81, 0.91), however LDL-cholesterol/diabetes-associated SNPs did not show consistent effect directions (binomial P = 0.15). HMGCR, our positive control, associated with LDL-C, CAD and a glycemic composite (derived from GWAS meta-analysis of four glycemic traits and diabetes). In contrast, PCSK9, APOB, LPA, CETP, PLG, NPC1L1 and ALDH2 were identified as "druggable" loci that alter LDL-C and risk of CAD without displaying associations with dysglycemia. In conclusion, LDL-C increases the risk of CAD and the relationship is independent of any association of LDL-C with diabetes. Loci that encode targets of emerging LDL-C lowering drugs do not associate with dysglycemia, and this provides provisional evidence that new LDL-C lowering drugs (such as PCSK9 inhibitors) may not influence risk of diabetes. |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 29% |
| Netherlands | 2 | 29% |
| United Kingdom | 1 | 14% |
| Canada | 1 | 14% |
| Unknown | 1 | 14% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 4 | 57% |
| Members of the public | 3 | 43% |
Mendeley readers
The data shown below were compiled from readership statistics for 63 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Netherlands | 1 | 2% |
| Unknown | 61 | 97% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 10 | 16% |
| Student > Bachelor | 10 | 16% |
| Student > Ph. D. Student | 6 | 10% |
| Student > Master | 5 | 8% |
| Other | 4 | 6% |
| Other | 13 | 21% |
| Unknown | 15 | 24% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 23 | 37% |
| Agricultural and Biological Sciences | 9 | 14% |
| Biochemistry, Genetics and Molecular Biology | 5 | 8% |
| Pharmacology, Toxicology and Pharmaceutical Science | 3 | 5% |
| Nursing and Health Professions | 2 | 3% |
| Other | 5 | 8% |
| Unknown | 16 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 13 March 2016.
All research outputs
#7,487,901
of 24,792,414 outputs
Outputs from Human Genetics
#898
of 3,069 outputs
Outputs of similar age
#96,787
of 304,770 outputs
Outputs of similar age from Human Genetics
#13
of 26 outputs
Altmetric has tracked 24,792,414 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 3,069 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one has gotten more attention than average, scoring higher than 70% of its peers.
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 304,770 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 26 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 53% of its contemporaries.