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X Demographics
Mendeley readers
Attention Score in Context
| Title |
A study paradigm integrating prospective epidemiologic cohorts and electronic health records to identify disease biomarkers
|
|---|---|
| Published in |
Nature Communications, August 2018
|
| DOI | 10.1038/s41467-018-05624-4 |
| Pubmed ID | |
| Authors |
Jonathan D. Mosley, QiPing Feng, Quinn S. Wells, Sara L. Van Driest, Christian M. Shaffer, Todd L. Edwards, Lisa Bastarache, Wei-Qi Wei, Lea K. Davis, Catherine A. McCarty, Will Thompson, Christopher G. Chute, Gail P. Jarvik, Adam S. Gordon, Melody R. Palmer, David R. Crosslin, Eric B. Larson, David S. Carrell, Iftikhar J. Kullo, Jennifer A. Pacheco, Peggy L. Peissig, Murray H. Brilliant, James G. Linneman, Bahram Namjou, Marc S. Williams, Marylyn D. Ritchie, Kenneth M. Borthwick, Shefali S. Verma, Jason H. Karnes, Scott T. Weiss, Thomas J. Wang, C. Michael Stein, Josh C. Denny, Dan M. Roden |
| Abstract |
Defining the full spectrum of human disease associated with a biomarker is necessary to advance the biomarker into clinical practice. We hypothesize that associating biomarker measurements with electronic health record (EHR) populations based on shared genetic architectures would establish the clinical epidemiology of the biomarker. We use Bayesian sparse linear mixed modeling to calculate SNP weightings for 53 biomarkers from the Atherosclerosis Risk in Communities study. We use the SNP weightings to computed predicted biomarker values in an EHR population and test associations with 1139 diagnoses. Here we report 116 associations meeting a Bonferroni level of significance. A false discovery rate (FDR)-based significance threshold reveals more known and undescribed associations across a broad range of biomarkers, including biometric measures, plasma proteins and metabolites, functional assays, and behaviors. We confirm an inverse association between LDL-cholesterol level and septicemia risk in an independent epidemiological cohort. This approach efficiently discovers biomarker-disease associations. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Italy | 1 | 20% |
| United States | 1 | 20% |
| Canada | 1 | 20% |
| Unknown | 2 | 40% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 76 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 16 | 21% |
| Student > Bachelor | 10 | 13% |
| Researcher | 9 | 12% |
| Student > Master | 7 | 9% |
| Professor > Associate Professor | 5 | 7% |
| Other | 8 | 11% |
| Unknown | 21 | 28% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 20 | 26% |
| Biochemistry, Genetics and Molecular Biology | 9 | 12% |
| Agricultural and Biological Sciences | 5 | 7% |
| Nursing and Health Professions | 5 | 7% |
| Computer Science | 3 | 4% |
| Other | 9 | 12% |
| Unknown | 25 | 33% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 08 April 2019.
All research outputs
#1,688,692
of 23,102,082 outputs
Outputs from Nature Communications
#21,915
of 47,655 outputs
Outputs of similar age
#37,508
of 334,790 outputs
Outputs of similar age from Nature Communications
#684
of 1,448 outputs
Altmetric has tracked 23,102,082 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 47,655 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 55.9. This one has gotten more attention than average, scoring higher than 53% 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 334,790 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 1,448 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 52% of its contemporaries.