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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Pharmacogenomic Diversity among Brazilians: Influence of Ancestry, Self-Reported Color, and Geographical Origin
|
|---|---|
| Published in |
Frontiers in Pharmacology, January 2012
|
| DOI | 10.3389/fphar.2012.00191 |
| Pubmed ID | |
| Authors |
Guilherme Suarez-Kurtz, Sergio Danilo Juno Pena, Claudio José Struchiner, Mara Helena Hutz |
| Abstract |
BY VIRTUE OF BEING THE PRODUCT OF THE GENETIC ADMIXTURE OF THREE ANCESTRAL ROOTS: Europeans, Africans, and Amerindians, the present-day Brazilian population displays very high levels of genomic diversity, which have important pharmacogenetic/-genomic (PGx) implications. Recognition of this fact has prompted the creation of the Brazilian Pharmacogenomics Network (Refargen), a nationwide consortium of research groups, with the mission to provide leadership in PGx research and education in Brazil, with a population heath impact. Here, we present original data and review published results from a Refargen comprehensive study of the distribution of PGx polymorphisms in a representative cohort of the Brazilian people, comprising 1,034 healthy, unrelated adults, self-identified as white, brown, or black, according to the Color categories adopted by the Brazilian Census. Multinomial log-linear regression analysis was applied to infer the statistical association between allele, genotype, and haplotype distributions among Brazilians (response variables) and self-reported Color, geographical region, and biogeographical ancestry (explanatory variables), whereas Wright's F(ST) statistics was used to assess the extent of PGx divergence among different strata of the Brazilian population. Major PGx implications of these findings are: first, extrapolation of data from relatively well-defined ethnic groups is clearly not applicable to the majority of Brazilians; second, the frequency distribution of polymorphisms in several pharmacogenes of clinical relevance (e.g., ABCB1, CYP3A5, CYP2C9, VKORC) varies continuously among Brazilians and is not captured by race/Color self-identification; third, the intrinsic heterogeneity of the Brazilian population must be acknowledged in the design and interpretation of PGx studies in order to avoid spurious conclusions based on improper matching of study cohorts. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 85 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 5 | 6% |
| South Africa | 1 | 1% |
| France | 1 | 1% |
| Unknown | 78 | 92% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 14 | 16% |
| Student > Master | 12 | 14% |
| Student > Bachelor | 11 | 13% |
| Student > Ph. D. Student | 10 | 12% |
| Student > Doctoral Student | 7 | 8% |
| Other | 13 | 15% |
| Unknown | 18 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 29% |
| Biochemistry, Genetics and Molecular Biology | 11 | 13% |
| Pharmacology, Toxicology and Pharmaceutical Science | 10 | 12% |
| Medicine and Dentistry | 9 | 11% |
| Immunology and Microbiology | 2 | 2% |
| Other | 5 | 6% |
| Unknown | 23 | 27% |
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 06 November 2012.
All research outputs
#15,205,036
of 22,684,168 outputs
Outputs from Frontiers in Pharmacology
#6,156
of 15,867 outputs
Outputs of similar age
#162,871
of 244,115 outputs
Outputs of similar age from Frontiers in Pharmacology
#65
of 137 outputs
Altmetric has tracked 22,684,168 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 15,867 research outputs from this source. They receive a mean Attention Score of 4.9. This one has gotten more attention than average, scoring higher than 60% 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 244,115 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 137 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 51% of its contemporaries.