ArticleHuman genomics2017
In silico prioritization and further functional characterization of SPINK1 intronic variants.
Article in Human genomics, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 16 citations in OpenAlex.
- SPINK1-related chronic pancreatitis: A model that encapsulates the spectrum of variant effects, genetic complexity, and classificatory challenges.American journal of human genetics · 2025Article
- Genetics and clinical implications of SPINK1 in the pancreatitis continuum and pancreatic cancer.Human genomics · 2025Review
- Combining full-length gene assay and SpliceAI to interpret the splicing impact of all possible SPINK1 coding variants.Human genomics · 2024Article
- Analysis of the impact of DGAT1 p.M435L and p.K232A variants on pre-mRNA splicing in a full-length gene assay.Scientific reports · 2023Article
- Toward a clinical diagnostic pipeline for SPINK1 intronic variants.Human genomics · 2019Article
- Leveraging splice-affecting variant predictors and a minigene validation system to identify Mendelian disease-causing variants among exon-captured variants of uncertain significance.Human mutation · 2017Article
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Authors and funding
8 authors at 5 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundSPINK1 (serine protease inhibitor, kazal-type, 1), which encodes human pancreatic secretory trypsin inhibitor, is one of the most extensively studied genes underlying chronic pancreatitis. Recently, based upon data from qualitative reverse transcription-PCR (RT-PCR) analyses of transfected HEK293T cells, we concluded that 24 studied SPINK1 intronic variants were not of pathological significance, the sole exceptions being two canonical splice site variants (i.e., c.87 + 1G > A and c.194 + 2T > C). Herein, we employed the splicing prediction tools included within the Alamut software suite to prioritize the 'non-pathological' SPINK1 intronic variants for further quantitative RT-PCR analysis.
resultsAlthough our results demonstrated the utility of in silico prediction in classifying and prioritizing intronic variants, we made two observations worth noting. First, we established that most of the prediction tools employed ignored the general rule that GC is a weaker donor splice site than the canonical GT site. This finding is potentially important because for a given disease gene, a GC variant donor splice site may be associated with a milder clinical manifestation. Second, the non-pathological c.194 + 13T > G variant was consistently predicted by different programs to generate a new and viable donor splice site, the prediction scores being comparable to those for the physiological c.194 + 2T donor splice site and even higher than those for the physiological c.87 + 1G donor splice site. We do however provide convincing in vitro evidence that the predicted donor splice site was not entirely spurious.
conclusionsOur findings, taken together, serve to emphasize the importance of functional analysis in helping to establish or refute the pathogenicity of specific intronic variants.
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