Unraveling synonymous and deep intronic variants causing aberrant splicing in two genetically undiagnosed epilepsy families

Well-differentiated G1 and G2 pancreatic neuroendocrine tumors: a meta-analysis of published expanded DNA sequencing data

Introduction

Well-differentiated pancreatic neuroendocrine tumors (PNETs) can be non-functional or functional, e.g. insulinoma and glucagonoma. The majority of PNETs are sporadic, but PNETs also occur in hereditary syndromes, primarily multiple endocrine neoplasia type 1 (MEN1). The Knudson hypothesis stated a second, somatic hit in MEN1 as the cause of PNETs of MEN1 syndrome. In the recent years, reports on genetic somatic events in both sporadic and hereditary PNETs have emerged, providing a basis for a more detailed molecular understanding of the pathophysiology. In this systematic review and meta-analysis, we made a collation and statistical analysis of aggregated frequent genetic alterations and potential driver events in human grade G1/G2 PNETs.

Methods

A systematic search was performed in concordance with the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA) reporting guidelines of 2020. A search in Pubmed for published studies using whole exome, whole genome, or targeted gene panel (+400 genes) sequencing of human G1/G2 PNETs was conducted at the 25th of September 2023. Fourteen datasets from published studies were included with data on 221 patients and 225 G1/G2 PNETs, which were divided into sporadic tumors, and hereditary tumors with pre-disposing germline variants, and tumors with unknown germline status. Further, non-functioning and functioning PNETs were distinguished into two groups for pathway evaluation. The collated genetical analyses were conducted using the 'maftools' R-package.

Results

Sporadic PNETs accounted 72.0% (162/225), hereditary PNETs 13.3% (30/225), unknown germline status 14.7% (33/225). The most frequently altered gene was MEN1, with somatic variants and copy number variations in overall 42% (95/225); hereditary PNETs (germline variations in MEN1, VHL, CHEK2, BRCA2, PTEN, CDKN1B, and/or MUTYH) 57% (16/30); sporadic PNETs 36% (58/162); unknown germline status 64% (21/33). The MEN1 point mutations/indels were distributed throughout MEN1. Overall, DAXX (16%, 37/225) and ATRX-variants (12%, 27/225) were also abundant with missense mutations clustered in mutational hotspots associated with histone binding, and translocase activity, respectively. DAXX mutations occurred more frequently in PNETs with MEN1 mutations, p<0.05. While functioning PNETs shared few variated genes, non-functioning PNETs had more recurrent variations in genes associated with the Phosphoinositide 3-kinase, Wnt, NOTCH, and Receptor Tyrosine Kinase-Ras signaling onco-pathways.

Discussion

The somatic genetic alterations in G1/G2 PNETs are diverse, but with distinct differences between sporadic vs. hereditary, and functional vs. non-functional PNETs. Increased understanding of the genetic alterations may lead to identification of more drivers and driver hotspots in the tumorigenesis in well-differentiated PNETs, potentially giving a basis for the identification of new drug targets. (Funded by Novo Nordisk Foundation, grant number NNF19OC0057915).

Genetic analysis of 37 cases with primary periodic paralysis in Chinese patients

BACKGROUND

Primary periodic paralysis (PPP) is an inherited disorders of ion channel dysfunction characterized by recurrent episodes of flaccid muscle weakness, which can classified as hypokalemic (HypoPP), normokalemic (NormoPP), or hyperkalemic (HyperPP) according to the potassium level during the paralytic attacks. However, PPP is charactered by remarkable clinical and genetic heterogeneity, and the diagnosis of suspected patients is based on the characteristic clinical presentation then confirmed by genetic testing. At present, there are only limited cohort studies on PPP in the Chinese population.

RESULTS

We included 37 patients with a clinical diagnosis of PPP. Eleven (29.7%) patients were tested using a specific gene panel and 26 (70.3%) by the whole-exome sequencing (WES). Twenty-two cases had a genetic variant identified, representing a diagnostic rate of 59.5% (22/37). All the identified mutations were either in the SCN4A or the CACNA1S gene. The overall detection rate was comparable between the panel (54.5%: 6/11) and WES (61.5%: 16/26). The remaining patients unresolved through panel sequencing were further analyzed by WES, without the detection of any mutation. The novel atypical splicing variant c.2020-5G > A affects the normal splicing of the SCN4A mRNA, which was confirmed by minigene splicing assay. Among 21 patients with HypoPP, 15 patients were classified as HypoPP-2 with SCN4A variants, and 6 HypoPP-1 patients had CACNA1S variants.

CONCLUSIONS

Our results suggest that SCN4A alleles are the main cause in our cohort, with the remainder caused by CACNA1S alleles, which are the predominant cause in Europe and the United States. Additionally, this study identified 3 novel SCN4A and 2 novel CACNA1S variants, broadening the mutation spectrum of genes associated with PPP.

Functional investigation of SCN1A deep-intronic variants activating poison exons inclusion

Dravet syndrome is a devastating epileptic syndrome characterized by intractable epilepsy with an early age of onset, regression of developmental milestones, ataxia, and motor deficits. Loss-of-function pathogenic variants in the SCN1A gene are found in the majority of patients with Dravet syndrome; however, a significant number of patients remain undiagnosed even after comprehensive genetic testing. Previously, it was shown that intronic elements in the SCN1A gene called poison exons can incorporate into SCN1A mRNA, leading to haploinsufficiency and potentially causing Dravet syndrome. Here, we developed a splicing reporter assay for all described poison exons of the SCN1A gene and validated it using previously reported and artificially introduced variants. Overall, we tested 18 deep-intronic single nucleotide variants and one complex allele in the SCN1A gene. Our approach is capable of evaluating the effect of both variants affecting cis-regulatory sequences and splice-site variants, with the potential to functionally annotate every possible variant within these elements. Moreover, using antisense-modified uridine-rich U7 small nuclear RNAs, we were able to block poison exon incorporation in mutant constructs, an approach that could be used as a promising therapeutic intervention in Dravet syndrome patients with deep-intronic variants.

Intronic position +9 and -9 are potentially splicing sites boundary from intronic variants analysis of whole exome sequencing data

Whole exome sequencing (WES) can also detect some intronic variants, which may affect splicing and gene expression, but how to use these intronic variants, and the characteristics about them has not been reported. This study aims to reveal the characteristics of intronic variant in WES data, to further improve the clinical diagnostic value of WES. A total of 269 WES data was analyzed, 688,778 raw variants were called, among these 367,469 intronic variants were in intronic regions flanking exons which was upstream/downstream region of the exon (default is 200 bps). Contrary to expectation, the number of intronic variants with quality control (QC) passed was the lowest at the +2 and -2 positions but not at the +1 and -1 positions. The plausible explanation was that the former had the worst effect on trans-splicing, whereas the latter did not completely abolish splicing. And surprisingly, the number of intronic variants that passed QC was the highest at the +9 and -9 positions, indicating a potential splicing site boundary. The proportion of variants which could not pass QC filtering (false variants) in the intronic regions flanking exons generally accord with "S"-shaped curve. At +5 and -5 positions, the number of variants predicted damaging by software was most. This was also the position at which many pathogenic variants had been reported in recent years. Our study revealed the characteristics of intronic variant in WES data for the first time, we found the +9 and -9 positions might be a potentially splicing sites boundary and +5 and -5 positions were potentially important sites affecting splicing or gene expression, the +2 and -2 positions seem more important splicing site than +1 and -1 positions, and we found variants in intronic regions flanking exons over ± 50 bps may be unreliable. This result can help researchers find more useful variants and demonstrate that WES data is valuable for intronic variants analysis.

SpliceAI-visual: a free online tool to improve SpliceAI splicing variant interpretation

SpliceAI is an open-source deep learning splicing prediction algorithm that has demonstrated in the past few years its high ability to predict splicing defects caused by DNA variations. However, its outputs present several drawbacks: (1) although the numerical values are very convenient for batch filtering, their precise interpretation can be difficult, (2) the outputs are delta scores which can sometimes mask a severe consequence, and (3) complex delins are most often not handled. We present here SpliceAI-visual, a free online tool based on the SpliceAI algorithm, and show how it complements the traditional SpliceAI analysis. First, SpliceAI-visual manipulates raw scores and not delta scores, as the latter can be misleading in certain circumstances. Second, the outcome of SpliceAI-visual is user-friendly thanks to the graphical presentation. Third, SpliceAI-visual is currently one of the only SpliceAI-derived implementations able to annotate complex variants (e.g., complex delins). We report here the benefits of using SpliceAI-visual and demonstrate its relevance in the assessment/modulation of the PVS1 classification criteria. We also show how SpliceAI-visual can elucidate several complex splicing defects taken from the literature but also from unpublished cases. SpliceAI-visual is available as a Google Colab notebook and has also been fully integrated in a free online variant interpretation tool, MobiDetails ( https://mobidetails.iurc.montp.inserm.fr/MD ).

The Power of Clinical Diagnosis for Deciphering Complex Genetic Mechanisms in Rare Diseases

Complex genetic disease mechanisms, such as structural or non-coding variants, currently pose a substantial difficulty in frontline diagnostic tests. They thus may account for most unsolved rare disease patients regardless of the clinical phenotype. However, the clinical diagnosis can narrow the genetic focus to just a couple of genes for patients with well-established syndromes defined by prominent physical and/or unique biochemical phenotypes, allowing deeper analyses to consider complex genetic origin. Then, clinical-diagnosis-driven genome sequencing strategies may expedite the development of testing and analytical methods to account for complex disease mechanisms as well as to advance functional assays for the confirmation of complex variants, clinical management, and the development of new therapies.

IRIDA Phenotype in TMPRSS6 Monoallelic-Affected Patients: Toward a Better Understanding of the Pathophysiology

Iron-refractory iron deficiency anemia (IRIDA) is an autosomal recessive inherited form of iron deficiency anemia characterized by discrepantly high hepcidin levels relative to body iron status. However, patients with monoallelic exonic TMPRSS6 variants have also been reported to express the IRIDA phenotype. The pathogenesis of an IRIDA phenotype in these patients is unknown and causes diagnostic uncertainty. Therefore, we retrospectively summarized the data of 16 patients (4 men, 12 women) who expressed the IRIDA phenotype in the presence of only a monoallelic TMPRSS6 variant. Eight unaffected relatives with identical exonic TMPRSS6 variants were used as controls. Haplotype analysis was performed to assess the (intra)genetic differences between patients and relatives. The expression and severity of the IRIDA phenotype were highly variable. Compared with their relatives, patients showed lower Hb, MCV, and TSAT/hepcidin ratios and inherited a different wild-type allele. We conclude that IRIDA in monoallelic TMPRSS6-affected patients is a phenotypically and genotypically heterogeneous disease that is more common in female patients. We hypothesize that allelic imbalance, polygenetic inheritance, or modulating environmental factors and their complex interplay are possible causes. This explorative study is the first step toward improved insights into the pathophysiology and improved diagnostic accuracy for patients presenting with IRIDA and a monoallelic exonic TMPRSS6 variant.