Evidence map›Paper›PMID 20565774›Full record

ArticleBMC genetics2010

Population based allele frequencies of disease associated polymorphisms in the Personalized Medicine Research Project.

Deanna S Cross, Lynn C Ivacic, Elisha L Stefanski, Catherine A McCarty

Abstract readComparative Study
In one paragraph

Article in BMC genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

36 citing papers in PubMed.

  1. Review
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  3. Evaluation ofCancer management and research · 2026
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  17. Catechol-O-methyltransferase (COMT) genotype affects cognitive control during total sleep deprivation.Cortex; a journal devoted to the study of the nervous system and behavior · 2018
    Article
  18. Article
  19. Article
  20. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Deanna S CrossCenter for Human Genetics, Marshfield Clinic Research Foundation, WI, USA. cross.deanna@mcrf.mfldclin.edu
Lynn C Ivacic
Elisha L Stefanski
Catherine A McCarty

Funding

INSTITUTIONAL CTSA (UW-MADISON): CLINICAL TRIALSUL1RR025011 · NCRR · UNIVERSITY OF WISCONSIN-MADISON · PI DREZNER, MARC KENNETH · 2007 to 2011
$29.5M
NCRR NIH HHS 1UL1RR025011
6 · The paper itself

Abstract

backgroundThere is a lack of knowledge regarding the frequency of disease associated polymorphisms in populations and population attributable risk for many populations remains unknown. Factors that could affect the association of the allele with disease, either positively or negatively, such as race, ethnicity, and gender, may not be possible to determine without population based allele frequencies.Here we used a panel of 51 polymorphisms previously associated with at least one disease and determined the allele frequencies within the entire Personalized Medicine Research Project population based cohort. We compared these allele frequencies to those in dbSNP and other data sources stratified by race. Differences in allele frequencies between self reported race, region of origin, and sex were determined.

resultsThere were 19544 individuals who self reported a single racial category, 19027 or (97.4%) self reported white Caucasian, and 11205 (57.3%) individuals were female. Of the 11,208 (57%) individuals with an identifiable region of origin 8337 or (74.4%) were German.41 polymorphisms were significantly different between self reported race at the 0.05 level. Stratification of our Caucasian population by self reported region of origin revealed 19 polymorphisms that were significantly different (p = 0.05) between individuals of different origins. Further stratification of the population by gender revealed few significant differences in allele frequencies between the genders.

conclusionsThis represents one of the largest population based allele frequency studies to date. Stratification by self reported race and region of origin revealed wide differences in allele frequencies not only by race but also by region of origin within a single racial group. We report allele frequencies for our Asian/Hmong and American Indian populations; these two minority groups are not typically selected for population allele frequency detection. Population wide allele frequencies are important for the design and implementation of studies and for determining the relevance of a disease associated polymorphism for a given population.

Indexed as

Gene FrequencyPolymorphism, GeneticEthnicityGenetic Predisposition to DiseaseHumansPopulation GroupsSex Factors

Identifiers

PMID20565774
PMCPMC2908055

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.