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Functional SNP allele discovery (fSNPd): an approach to find highly penetrant, environmental-triggered genotypes underlying complex human phenotypes

Overview of attention for article published in BMC Genomics, December 2017
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Title
Functional SNP allele discovery (fSNPd): an approach to find highly penetrant, environmental-triggered genotypes underlying complex human phenotypes
Published in
BMC Genomics, December 2017
DOI 10.1186/s12864-017-4325-y
Pubmed ID
Authors

Kaitlin Stouffer, Michael Nahorski, Pablo Moreno, Nivedita Sarveswaran, David Menon, Michael Lee, C. Geoffrey Woods

Abstract

Significant human diseases/phenotypes exist which require both an environmental trigger event and a genetic predisposition before the disease/phenotype emerges, e.g. Carbamazepine with the rare SNP allele of rs3909184 causing Stevens Johnson syndrome, and aminoglycosides with rs267606617 causing sensory neural deafness. The underlying genotypes are fully penetrant only when the correct environmental trigger(s) occur, otherwise they are silent and harmless. Such diseases/phenotypes will not appear to have a Mendelian inheritance pattern, unless the environmental trigger is very common (>50% per lifetime). The known causative genotypes are likely to be protein-altering SNPs with dominant/semi-dominant effect. We questioned whether other diseases and phenotypes could have a similar aetiology. We wrote the fSNPd program to analyse multiple exomes from a test cohort simultaneously with the purpose of identifying SNP alleles at a significantly different frequency to that of the general population. fSNPd was tested on trial cohorts, iteratively improved, and modelled for performance against an idealised association study under mutliple parameters. We also assessed the seqeuncing depath of all human exons to determine which were sufficiently well sequenced in an exome to be sued by fSNPd - by assessing forty exomes base by base. We describe a simple methodology for the detection of SNPs capable of causing a phenotype triggered by an environmental event. This uses cohorts of relatively small size (30-100 individuals) with the phenotype being investigated, their exomes, and thence seeks SNP allele frequencies significantly different from expected to identify potentially clinically important, protein altering SNP alleles. The strengths and weaknesses of this approach for discovering significant genetic causes of human disease are comparable to Mendelian disease mutation detection and Association Studies. The fSNPd methodology is another approach, and has potentially significant advantage over Association studies in needing far fewer individuals, to detect genes involved in the pathogenesis of a diseases/phenotypes. Furthermore, the SNP alleles identified alter amino acids, potentially making it easier to devise functional assays of protein function to determine pathogenicity.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 5 21%
Other 3 13%
Student > Master 3 13%
Researcher 3 13%
Student > Ph. D. Student 2 8%
Other 3 13%
Unknown 5 21%
Readers by discipline Count As %
Medicine and Dentistry 5 21%
Agricultural and Biological Sciences 5 21%
Biochemistry, Genetics and Molecular Biology 4 17%
Business, Management and Accounting 1 4%
Chemical Engineering 1 4%
Other 3 13%
Unknown 5 21%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 December 2017.
All research outputs
#19,395,796
of 24,703,339 outputs
Outputs from BMC Genomics
#8,002
of 11,048 outputs
Outputs of similar age
#320,038
of 449,847 outputs
Outputs of similar age from BMC Genomics
#144
of 212 outputs
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So far Altmetric has tracked 11,048 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 22nd percentile – i.e., 22% of its peers scored the same or lower than it.
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We're also able to compare this research output to 212 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.