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Are minor alleles more likely to be risk alleles?

Overview of attention for article published in BMC Medical Genomics, January 2018
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (93rd percentile)

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Title
Are minor alleles more likely to be risk alleles?
Published in
BMC Medical Genomics, January 2018
DOI 10.1186/s12920-018-0322-5
Pubmed ID
Authors

Takashi Kido, Weronika Sikora-Wohlfeld, Minae Kawashima, Shinichi Kikuchi, Naoyuki Kamatani, Anil Patwardhan, Richard Chen, Marina Sirota, Keiichi Kodama, Dexter Hadley, Atul J. Butte

Abstract

Genome-wide association studies (GWASs) have revealed relationships between over 57,000 genetic variants and diseases. However, unlike Mendelian diseases, complex diseases arise from the interplay of multiple genetic and environmental factors. Natural selection has led to a high tendency of risk alleles to be enriched in minor alleles in Mendelian diseases. Therefore, an allele that was previously advantageous or neutral may later become harmful, making it a risk allele. Using data in the NHGRI-EBI Catalog and the VARIMED database, we investigated whether (1) GWASs more easily detect risk alleles and (2) facilitate evolutionary insights by comparing risk allele frequencies of different diseases. We conducted computer simulations of P-values for association tests when major and minor alleles were risk alleles. We compared the expected proportion of SNVs whose risk alleles were minor alleles with the observed proportion. Our statistical results revealed that risk alleles were enriched in minor alleles, especially for variants with low minor allele frequencies (MAFs < 0.1). Our computer simulations revealed that > 50% risk alleles were minor alleles because of the larger difference in the power of GWASs to differentiate between minor and major alleles, especially with low MAFs or when the number of controls exceeds the number of cases. However, the observed ratios between minor and major alleles in low MAFs (< 0.1) were much larger than the expected ratios of GWAS's power imbalance, especially for diseases whose average risk allele frequencies were low, such as myopia, sudden cardiac arrest, and systemic lupus erythematosus. Minor alleles are more likely to be risk alleles in the published GWASs on complex diseases. One reason is that minor alleles are more easily detected as risk alleles in GWASs. Even when correcting for the GWAS's power imbalance, minor alleles are more likely to be risk alleles, especially in some diseases whose average risk allele frequencies are low. These analyses serve as a starting point for future studies on quantifying the degree of negative natural selection in various complex diseases.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 132 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 132 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 24 18%
Student > Bachelor 23 17%
Student > Ph. D. Student 17 13%
Student > Doctoral Student 6 5%
Student > Postgraduate 6 5%
Other 15 11%
Unknown 41 31%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 41 31%
Medicine and Dentistry 15 11%
Agricultural and Biological Sciences 14 11%
Neuroscience 4 3%
Computer Science 3 2%
Other 11 8%
Unknown 44 33%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 14. 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 29 September 2022.
All research outputs
#2,433,195
of 24,525,534 outputs
Outputs from BMC Medical Genomics
#76
of 1,326 outputs
Outputs of similar age
#55,886
of 450,770 outputs
Outputs of similar age from BMC Medical Genomics
#3
of 29 outputs
Altmetric has tracked 24,525,534 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,326 research outputs from this source. They receive a mean Attention Score of 4.7. This one has done particularly well, scoring higher than 94% 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 450,770 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 87% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 93% of its contemporaries.