Identification of a novel SPINK1 deletion in a teenager with idiopathic chronic pancreatitis

Genetics and clinical implications of SPINK1 in the pancreatitis continuum and pancreatic cancer

Serine peptidase inhibitor, Kazal type 1 (SPINK1), a 56-amino-acid protein in its mature form, was among the first pancreatic enzymes to be extensively characterized biochemically and functionally. Synthesized primarily in pancreatic acinar cells and traditionally known as pancreatic secretory trypsin inhibitor, SPINK1 protects the pancreas by inhibiting prematurely activated trypsin. Since 2000, interest in SPINK1 has resurged following the discovery of genetic variants linked to chronic pancreatitis (CP). This review provides a historical overview of SPINK1's discovery, function, and gene structure before examining key genetic findings. We highlight three variants with well-characterized pathogenic mechanisms: c.-4141G > T, a causative enhancer variant linked to the extensively studied p.Asn34Ser (c.101A > G), which disrupts a PTF1L-binding site within an evolutionarily conserved HNF1A-PTF1L cis-regulatory module; c.194 + 2T > C, a canonical 5' splice site GT > GC variant that retains 10% of wild-type transcript production; and an Alu insertion in the 3'-untranslated region, which causes complete loss of function by forming extended double-stranded RNA structures with pre-existing Alu elements in deep intronic regions. We emphasize the integration of a full-length gene splicing assay (FLGSA) with SpliceAI's predictive capabilities, establishing SPINK1 the first disease gene for which the splicing impact of all possible coding variants was prospectively determined. Findings from both mouse models and genetic association studies support the sentinel acute pancreatitis event (SAPE) model, which explains the progression from acute pancreatitis to CP. Additionally, SPINK1 variants may contribute to an increased risk of pancreatic ductal adenocarcinoma (PDAC). Finally, we discuss the therapeutic potential of SPINK1, particularly through adeno-associated virus type 8 (AAV8)-mediated overexpression of SPINK1 as a strategy for treating and preventing pancreatitis, and highlight key areas for future research.

Integrated transcriptomic analysis and machine learning for characterizing diagnostic biomarkers and immune cell infiltration in fetal growth restriction

Background

Fetal growth restriction (FGR) occurs in 10% of pregnancies worldwide. Placenta dysfunction, as one of the most common causes of FGR, is associated with various poor perinatal outcomes. The main objectives of this study were to screen potential diagnostic biomarkers for FGR and to evaluate the function of immune cell infiltration in the process of FGR.

Methods

Firstly, differential expression genes (DEGs) were identified in two Gene Expression Omnibus (GEO) datasets, and gene set enrichment analysis was performed. Diagnosis-related key genes were identified by using three machine learning algorithms (least absolute shrinkage and selection operator, random forest, and support vector machine model), and the nomogram was then developed. The receiver operating characteristic curve, calibration curve, and decision curve analysis curve were used to verify the validity of the diagnostic model. Using cell-type identification by estimating relative subsets of RNA transcripts (CIBERSORT), the characteristics of immune cell infiltration in placental tissue of FGR were evaluated and the candidate key immune cells of FGR were screened. In addition, this study also validated the diagnostic efficacy of TREM1 in the real world and explored associations between TREM1 and various clinical features.

Results

By overlapping the genes selected by three machine learning algorithms, four key genes were identified from 290 DEGs, and the diagnostic model based on the key genes showed good predictive performance (AUC = 0.971). The analysis of immune cell infiltration indicated that a variety of immune cells may be involved in the development of FGR, and nine candidate key immune cells of FGR were screened. Results from real-world data further validated TREM1 as an effective diagnostic biomarker (AUC = 0.894) and TREM1 expression was associated with increased uterine artery PI (UtA-PI) (p-value = 0.029).

Conclusion

Four candidate hub genes (SCD, SPINK1, TREM1, and HIST1H2BB) were identified, and the nomogram was constructed for FGR diagnosis. TREM1 was not only associated with a variety of key immune cells but also correlated with increased UtA-PI. The results of this study could provide some new clues for future research on the prediction and treatment of FGR.

Clinical interpretation of SPINK1 and CTRC variants in pancreatitis

Since the description of the SPINK1 gene encoding the serine protease inhibitor Kazal type 1 and the CTRC gene encoding the Chymotrypsin C as being involved in chronic pancreatitis, more than 56 SPINK1 and 87 CTRC variants have been reported. Assessing the clinical relevance of SPINK1 and CTRC variants is often complicated in the absence of functional evidence and interpretation of rare variants is not very easy in clinical practice. The aim of this study was to review the different variants identified in these two genes and to classify them according to their degree of damaging effect. This classification was based on the results of in vitro experiments, in silico analysis using different prediction tools, and on population data, in comparing the allelic frequency of each variant in patients with pancreatitis and in unaffected control individuals. This review should help geneticists and clinicians in charge of patient's care and genetic counseling to interpret the results of genetic studies.