High-throughput splicing assays identify missense and silent splice-disruptive POU1F1 variants underlying pituitary hormone deficiency

Diagnosing and treating anterior pituitary hormone deficiency in pediatric patients

Hypopituitarism, or the failure to secrete hormones produced by the anterior pituitary (adenohypophysis) and/or to release hormones from the posterior pituitary (neurohypophysis), can be congenital or acquired. When more than one pituitary hormone axis is impaired, the condition is known as combined pituitary hormone deficiency (CPHD). The deficiency may be primarily due to a hypothalamic or to a pituitary disorder, or concomitantly both, and has a negative impact on target organ function. This review focuses on the pathophysiology, diagnosis and management of anterior pituitary hormone deficiency in the pediatric age. Congenital hypopituitarism is generally due to genetic disorders and requires early medical attention. Exposure to toxicants or intrauterine infections should also be considered as potential etiologies. The molecular mechanisms underlying the fetal development of the hypothalamus and the pituitary are well characterized, and variants in the genes involved therein may explain the pathophysiology of congenital hypopituitarism: mutations in the genes expressed in the earliest stages are usually associated with syndromic forms whereas variants in genes involved in later stages of pituitary development result in non-syndromic forms with more specific hormone deficiencies. Tumors or lesions of the (peri)sellar region, cranial radiation therapy, traumatic brain injury and, more rarely, other inflammatory or infectious lesions represent the etiologies of acquired hypopituitarism. Hormone replacement is the general strategy, with critical periods of postnatal life requiring specific attention.

Knockout mice with pituitary malformations help identify human cases of hypopituitarism

BACKGROUND

Congenital hypopituitarism (CH) and its associated syndromes, septo-optic dysplasia (SOD) and holoprosencephaly (HPE), are midline defects that cause significant morbidity for affected people. Variants in 67 genes are associated with CH, but a vast majority of CH cases lack a genetic diagnosis. Whole exome and whole genome sequencing of CH patients identifies sequence variants in genes known to cause CH, and in new candidate genes, but many of these are variants of uncertain significance (VUS).

METHODS

The International Mouse Phenotyping Consortium (IMPC) is an effort to establish gene function by knocking-out all genes in the mouse genome and generating corresponding phenotype data. We used mouse embryonic imaging data generated by the Deciphering Mechanisms of Developmental Disorders (DMDD) project to screen 209 embryonic lethal and sub-viable knockout mouse lines for pituitary malformations.

RESULTS

Of the 209 knockout mouse lines, we identified 51 that have embryonic pituitary malformations. These genes not only represent new candidates for CH, but also reveal new molecular pathways not previously associated with pituitary organogenesis. We used this list of candidate genes to mine whole exome sequencing data of a cohort of patients with CH, and we identified variants in two unrelated cases for two genes, MORC2 and SETD5, with CH and other syndromic features.

CONCLUSIONS

The screening and analysis of IMPC phenotyping data provide proof-of-principle that recessive lethal mouse mutants generated by the knockout mouse project are an excellent source of candidate genes for congenital hypopituitarism in children.

Exome Sequencing has a high diagnostic rate in sporadic congenital hypopituitarism and reveals novel candidate genes

CONTEXT

The pituitary gland is key for childhood growth, puberty, and metabolism. Pituitary dysfunction is associated with a spectrum of phenotypes, from mild to severe. Congenital Hypopituitarism (CH) is the most commonly reported pediatric endocrine dysfunction with an incidence of 1:4000, yet low rates of genetic diagnosis have been reported.

OBJECTIVE

We aimed to unveil the genetic etiology of CH in a large cohort of patients from Argentina.

METHODS

We performed whole exome sequencing of 137 unrelated cases of CH, the largest cohort examined with this method to date.

RESULTS

Of the 137 cases, 19.1% and 16% carried pathogenic or likely pathogenic variants in known and new genes, respectively, while 28.2% carried variants of uncertain significance. This high yield was achieved through the integration of broad gene panels (genes described in animal models and/or other disorders), an unbiased candidate gene screen with a new bioinformatics pipeline (including genes high loss of function intolerance), and analysis of copy number variants. Three novel findings emerged. First, the most prevalent affected gene encodes the cell adhesion factor ROBO1. Affected children had a spectrum of phenotypes, consistent with a role beyond pituitary stalk interruption syndrome. Second, we found that CHD7 mutations also produce a phenotypic spectrum, not always associated with full CHARGE syndrome. Third, we add new evidence of pathogenicity in the genes PIBF1 and TBC1D32, and report 13 novel candidate genes associated with CH (e.g. PTPN6, ARID5B).

CONCLUSION

Overall, these results provide an unprecedented insight into the diverse genetic etiology of hypopituitarism.

Prioritizing de novo potential non-canonical splicing variants in neurodevelopmental disorders

BACKGROUND

Genomic variants outside of the canonical splicing site (±2) may generate abnormal mRNA splicing, which are defined as non-canonical splicing variants (NCSVs). However, the clinical interpretation of NCSVs in neurodevelopmental disorders (NDDs) is largely unknown.

METHODS

We investigated the contribution of NCSVs to NDDs from 345,787 de novo variants (DNVs) in 47,574 patients with NDDs. We performed functional enrichment and protein-protein interaction analysis to assess the association between genes carrying prioritised NCSVs and NDDs. Minigene was used to validate the impact of NCSVs on mRNA splicing.

FINDINGS

We observed significantly more NCSVs (p = 0.02, odds ratio [OR] = 2.05) among patients with NDD than in controls. Both canonical splicing variants (CSVs) and NCSVs contributed to an equal proportion of patients with NDD (0.76% vs. 0.82%). The candidate genes carrying NCSVs were associated with glutamatergic synapse and chromatin remodelling. Minigene successfully validated 59 of 79 (74.68%) NCSVs that led to abnormal splicing in 40 candidate genes, and 9 of the genes (ARID1B, KAT6B, TCF4, SMARCA2, SHANK3, PDHA1, WDR45, SCN2A, SYNGAP1) harboured recurrent NCSVs with the same variant present in more than two unrelated patients with NDD. Moreover, 36 of 59 (61.02%) NCSVs are novel clinically relevant variants, including 34 unreported and 2 clinically conflicting interpretations or of uncertain significance NCSVs in the ClinVar database.

INTERPRETATION

This study highlights the common pathology and clinical importance of NCSVs in unsolved patients with NDD.

FUNDING

The present study was funded by grants from the National Natural Science Foundation of China, China Postdoctoral Science Foundation, the Hunan Youth Science and Technology Innovation Talent Project, the Provincial Natural Science Foundation of Hunan, The Scientific Research Program of FuRong laboratory, and the Natural Science Project of the University of Anhui Province.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

BACKGROUND

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

RESULTS

We benchmark eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compare experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, is lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieve the best overall performance at distinguishing disruptive and neutral variants, and controlling for overall call rate genome-wide, SpliceAI and Pangolin have superior sensitivity. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues.

CONCLUSION

SpliceAI and Pangolin show the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.

MMP16 as NSCL ± P Susceptible Gene in Western Han Chinese

OBJECTIVE

The role of MMP16 in lip development is unclear. This study aimed to identify nonsyndromic cleft lip with or without palate (NSCL ± P) susceptible loci of MMP16 in western Han Chinese.

DESIGN

We performed targeted sequencing around MMP16 combined with a 2-phase association analysis on common variants. Phase 2 association analysis was performed with NSCL ± P specific subphenotypes (NSCL and NSCLP). Then we used rare variants burden analysis and genotyping, accompanied by motif analysis.

SETTING

This study was completed in a tertiary medical center.

PATIENTS, PARTICIPANTS

Phase 1 targeted sequencing included 159 patients with NSCL ± P and 542 normal controls; phase 2 included 1626 patients with NSCL ± P (1047 NSCL and 579 NSCLP) and 2255 normal controls.

INTERVENTIONS

Venous blood samples were collected from patients and used to extract DNA.

MAIN OUTCOME MEASURES

After Bonferroni correction, phase 1 significant threshold of p-value was 4.28 × 10-5 (0.05/1167 single nucleotide polymorphisms [SNPs]), and phase 2 was .00025 (0.05/200 SNPs). Burden analysis significant threshold p-value was .05.

RESULTS

Common variants phase 1 association analysis identified 11 statistically significant SNPs (lowest p = 1.90 × 10-9, odds ratio (OR) = 0.27, 95% CI: 0.17-0.44), phase 2 replication identified 16 SNPs in NSCL ± P (lowest p = 6.26 × 10-6, OR = 0.77, 95% CI: 0.69-0.86) and 9 in NSCL (lowest p = 8.44 × 10-5, OR = 0.76, 95% CI: 0.66-0.87). Rare variants burden analysis showed no significant results, genotyping results showed they were maternally inherited.

CONCLUSIONS

Our study identified MMP16 susceptible SNPs in NSCL ± P and NSCL, emphasizing its potential role in lip development. Our study also highlighted the importance to perform association analysis with subphenotypes divided.

High-Throughput Splicing Assays Identify Known and Novel WT1 Exon 9 Variants in Nephrotic Syndrome

Introduction

Frasier syndrome (FS) is a rare Mendelian form of nephrotic syndrome (NS) caused by variants which disrupt the proper splicing of WT1. This key transcription factor gene is alternatively spliced at exon 9 to produce 2 isoforms ("KTS+" and "KTS-"), which are normally expressed in the kidney at a ∼2:1 (KTS+:KTS-) ratio. FS results from variants that reduce this ratio by disrupting the splice donor of the KTS+ isoform. FS is extremely rare, and it is unclear whether any variants beyond the 8 already known could cause FS.

Methods

To prospectively identify other splicing-disruptive variants, we leveraged a massively parallel splicing assay. We tested every possible single nucleotide variant (n = 519) in and around WT1 exon 9 for effects upon exon inclusion and KTS+/- ratio.

Results

Splice disruptive variants (SDVs) made up 11% of the tested point variants overall and were tightly concentrated near the canonical acceptor and the KTS+/- alternate donors. Our map successfully identified all 8 known FS or focal segmental glomerulosclerosis (FSGS) variants and 16 additional novel variants which were comparably disruptive to these known pathogenic variants. We also identified 19 variants that, conversely, increased the KTS+/KTS- ratio, of which 2 are observed in unrelated individuals with 46,XX ovotesticular disorder of sex development (46,XX OTDSD).

Conclusion

This splicing effect map can serve as functional evidence to guide the clinical interpretation of newly observed variants in and around WT1 exon 9.

Using the ACMG/AMP framework to capture evidence related to predicted and observed impact on splicing: Recommendations from the ClinGen SVI Splicing Subgroup

The American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1, PS3, PP3, BS3, BP4, and BP7. However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. We utilized empirically derived splicing evidence to (1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, (2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and (3) exemplify methodology to calibrate splice prediction tools. We propose repurposing the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely, BP7 may be used to capture RNA results demonstrating no splicing impact for intronic and synonymous variants. We propose that the PS3/BS3 codes are applied only for well-established assays that measure functional impact not directly captured by RNA-splicing assays. We recommend the application of PS1 based on similarity of predicted RNA-splicing effects for a variant under assessment in comparison with a known pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA-assay evidence described aim to help standardize variant pathogenicity classification processes when interpreting splicing-based evidence.

Benchmarking splice variant prediction algorithms using massively parallel splicing assays

Background

Variants that disrupt mRNA splicing account for a sizable fraction of the pathogenic burden in many genetic disorders, but identifying splice-disruptive variants (SDVs) beyond the essential splice site dinucleotides remains difficult. Computational predictors are often discordant, compounding the challenge of variant interpretation. Because they are primarily validated using clinical variant sets heavily biased to known canonical splice site mutations, it remains unclear how well their performance generalizes.

Results

We benchmarked eight widely used splicing effect prediction algorithms, leveraging massively parallel splicing assays (MPSAs) as a source of experimentally determined ground-truth. MPSAs simultaneously assay many variants to nominate candidate SDVs. We compared experimentally measured splicing outcomes with bioinformatic predictions for 3,616 variants in five genes. Algorithms' concordance with MPSA measurements, and with each other, was lower for exonic than intronic variants, underscoring the difficulty of identifying missense or synonymous SDVs. Deep learning-based predictors trained on gene model annotations achieved the best overall performance at distinguishing disruptive and neutral variants. Controlling for overall call rate genome-wide, SpliceAI and Pangolin also showed superior overall sensitivity for identifying SDVs. Finally, our results highlight two practical considerations when scoring variants genome-wide: finding an optimal score cutoff, and the substantial variability introduced by differences in gene model annotation, and we suggest strategies for optimal splice effect prediction in the face of these issues.

Conclusion

SpliceAI and Pangolin showed the best overall performance among predictors tested, however, improvements in splice effect prediction are still needed especially within exons.

APPLICATION OF THE ACMG/AMP FRAMEWORK TO CAPTURE EVIDENCE RELEVANT TO PREDICTED AND OBSERVED IMPACT ON SPLICING: RECOMMENDATIONS FROM THE CLINGEN SVI SPLICING SUBGROUP

The American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) framework for classifying variants uses six evidence categories related to the splicing potential of variants: PVS1 (null variant in a gene where loss-of-function is the mechanism of disease), PS3 (functional assays show damaging effect on splicing), PP3 (computational evidence supports a splicing effect), BS3 (functional assays show no damaging effect on splicing), BP4 (computational evidence suggests no splicing impact), and BP7 (silent change with no predicted impact on splicing). However, the lack of guidance on how to apply such codes has contributed to variation in the specifications developed by different Clinical Genome Resource (ClinGen) Variant Curation Expert Panels. The ClinGen Sequence Variant Interpretation (SVI) Splicing Subgroup was established to refine recommendations for applying ACMG/AMP codes relating to splicing data and computational predictions. Our study utilised empirically derived splicing evidence to: 1) determine the evidence weighting of splicing-related data and appropriate criteria code selection for general use, 2) outline a process for integrating splicing-related considerations when developing a gene-specific PVS1 decision tree, and 3) exemplify methodology to calibrate bioinformatic splice prediction tools. We propose repurposing of the PVS1_Strength code to capture splicing assay data that provide experimental evidence for variants resulting in RNA transcript(s) with loss of function. Conversely BP7 may be used to capture RNA results demonstrating no impact on splicing for both intronic and synonymous variants, and for missense variants if protein functional impact has been excluded. Furthermore, we propose that the PS3 and BS3 codes are applied only for well-established assays that measure functional impact that is not directly captured by RNA splicing assays. We recommend the application of PS1 based on similarity of predicted RNA splicing effects for a variant under assessment in comparison to a known Pathogenic variant. The recommendations and approaches for consideration and evaluation of RNA assay evidence described aim to help standardise variant pathogenicity classification processes and result in greater consistency when interpreting splicing-based evidence.

Saturation-scale functional evidence supports clinical variant interpretation in Lynch syndrome

BACKGROUND

Lynch syndrome (LS) is a cancer predisposition syndrome affecting more than 1 in every 300 individuals worldwide. Clinical genetic testing for LS can be life-saving but is complicated by the heavy burden of variants of uncertain significance (VUS), especially missense changes.

RESULT

To address this challenge, we leverage a multiplexed analysis of variant effect (MAVE) map covering >94% of the 17,746 possible missense variants in the key LS gene MSH2. To establish this map's utility in large-scale variant reclassification, we overlay it on clinical databases of >15,000 individuals with LS gene variants uncovered during clinical genetic testing. We validate these functional measurements in a cohort of individuals with paired tumor-normal test results and find that MAVE-based function scores agree with the clinical interpretation for every one of the MSH2 missense variants with an available classification. We use these scores to attempt reclassification for 682 unique missense VUS, among which 34 scored as deleterious by our function map, in line with previously published rates for other cancer predisposition genes. Combining functional data and other evidence, ten missense VUS are reclassified as pathogenic/likely pathogenic, and another 497 could be moved to benign/likely benign. Finally, we apply these functional scores to paired tumor-normal genetic tests and identify a subset of patients with biallelic somatic loss of function, reflecting a sporadic Lynch-like Syndrome with distinct implications for treatment and relatives' risk.

CONCLUSION

This study demonstrates how high-throughput functional assays can empower scalable VUS resolution and prospectively generate strong evidence for variant classification.

POU1F1/Pou1f1 c.143-83A > G Variant Disrupts the Branch Site in Pre-mRNA and Leads to Dwarfism

POU Class 1 Homeobox1 (POU1F1/Pou1f1) is a well-established pituitary-specific transcription factor, and causes, when mutated, combined pituitary hormone deficiency in humans and mice. POU1F1/Pou1f1 has 2 isoforms: the alpha and beta isoforms. Recently, pathogenic variants in the unique coding region of the beta isoform (beta domain) and the intron near the exon-intron boundary for the beta domain were reported, although their functional consequences remain obscure. In this study, we generated mice carrying the Pou1f1 c.143-83A>G substitution that recapitulates the human intronic variant near the exon-intron boundary for the beta domain. Homozygous mice showed postnatal growth failure, with an average body weight that was 35% of wild-type littermates at 12 weeks, which was accompanied by anterior pituitary hypoplasia and deficiency of circulating insulin-like growth factor 1 and thyroxine. The results of RNA-seq analysis of the pituitary gland were consistent with reduction of somatotrophs, and this was confirmed immunohistochemically. Reverse transcription polymerase chain reaction of pituitary Pou1f1 mRNA showed abnormal splicing in homozygous mice, with a decrease in the alpha isoform, an increase in the beta isoform, and the emergence of the exon-skipped transcript. We further characterized artificial variants in or near the beta domain, which were candidate positions of the branch site in pre-mRNA, using cultured cell-basis analysis and found that only c.143-83A>G produced transcripts similar to the mice model. Our report is the first to show that the c.143-83A>G variant leads to splicing disruption and causes morphological and functional abnormalities in the pituitary gland. Furthermore, our mice will contribute understanding the role of POU1F1/Pou1f1 transcripts in pituitary development.

Functional Assays Reclassify Suspected Splice-Altering Variants of Uncertain Significance in Mendelian Channelopathies

BACKGROUND

Rare protein-altering variants in SCN5A, KCNQ1, and KCNH2 are major causes of Brugada syndrome and the congenital long QT syndrome. While splice-altering variants lying outside 2-bp canonical splice sites can cause these diseases, their role remains poorly described. We implemented 2 functional assays to assess 12 recently reported putative splice-altering variants of uncertain significance and 1 likely pathogenic variant without functional data observed in Brugada syndrome and long QT syndrome probands.

METHODS

We deployed minigene assays to assess the splicing consequences of 10 variants. Three variants incompatible with the minigene approach were introduced into control induced pluripotent stem cells by CRISPR genome editing. We differentiated cells into induced pluripotent stem cell-derived cardiomyocytes and studied splicing outcomes by reverse transcription-polymerase chain reaction. We used the American College of Medical Genetics and Genomics functional assay criteria (PS3/BS3) to reclassify variants.

RESULTS

We identified aberrant splicing, with presumed disruption of protein sequence, in 8/10 variants studied using the minigene assay and 1/3 studied in induced pluripotent stem cell-derived cardiomyocytes. We reclassified 8 variants of uncertain significance to likely pathogenic, 1 variant of uncertain significance to likely benign, and 1 likely pathogenic variant to pathogenic.

CONCLUSIONS

Functional assays reclassified splice-altering variants outside canonical splice sites in Brugada Syndrome- and long QT syndrome-associated genes.

Scalable Functional Assays for the Interpretation of Human Genetic Variation

Scalable sequence-function studies have enabled the systematic analysis and cataloging of hundreds of thousands of coding and noncoding genetic variants in the human genome. This has improved clinical variant interpretation and provided insights into the molecular, biophysical, and cellular effects of genetic variants at an astonishing scale and resolution across the spectrum of allele frequencies. In this review, we explore current applications and prospects for the field and outline the principles underlying scalable functional assay design, with a focus on the study of single-nucleotide coding and noncoding variants.

Performance evaluation of computational methods for splice-disrupting variants and improving the performance using the machine learning-based framework

A critical challenge in genetic diagnostics is the assessment of genetic variants associated with diseases, specifically variants that fall out with canonical splice sites, by altering alternative splicing. Several computational methods have been developed to prioritize variants effect on splicing; however, performance evaluation of these methods is hampered by the lack of large-scale benchmark datasets. In this study, we employed a splicing-region-specific strategy to evaluate the performance of prediction methods based on eight independent datasets. Under most conditions, we found that dbscSNV-ADA performed better in the exonic region, S-CAP performed better in the core donor and acceptor regions, S-CAP and SpliceAI performed better in the extended acceptor region and MMSplice performed better in identifying variants that caused exon skipping. However, it should be noted that the performances of prediction methods varied widely under different datasets and splicing regions, and none of these methods showed the best overall performance with all datasets. To address this, we developed a new method, machine learning-based classification of splice sites variants (MLCsplice), to predict variants effect on splicing based on individual methods. We demonstrated that MLCsplice achieved stable and superior prediction performance compared with any individual method. To facilitate the identification of the splicing effect of variants, we provided precomputed MLCsplice scores for all possible splice sites variants across human protein-coding genes (http://39.105.51.3:8090/MLCsplice/). We believe that the performance of different individual methods under eight benchmark datasets will provide tentative guidance for appropriate method selection to prioritize candidate splice-disrupting variants, thereby increasing the genetic diagnostic yield.

Heterozygous variants in SIX3 and POU1F1 cause pituitary hormone deficiency in mouse and man

Congenital hypopituitarism is a genetically heterogeneous condition that is part of a spectrum disorder that can include holoprosencephaly. Heterozygous mutations in SIX3 cause variable holoprosencephaly in humans and mice. We identified two children with neonatal hypopituitarism and thin pituitary stalk who were doubly heterozygous for rare, likely deleterious variants in the transcription factors SIX3 and POU1F1. We used genetically engineered mice to understand the disease pathophysiology. Pou1f1 loss-of-function heterozygotes are unaffected; Six3 heterozygotes have pituitary gland dysmorphology and incompletely ossified palate; and the Six3+/-; Pou1f1+/dw double heterozygote mice have a pronounced phenotype, including pituitary growth through the palate. The interaction of Pou1f1 and Six3 in mice supports the possibility of digenic pituitary disease in children. Disruption of Six3 expression in the oral ectoderm completely ablated anterior pituitary development, and deletion of Six3 in the neural ectoderm blocked the development of the pituitary stalk and both anterior and posterior pituitary lobes. Six3 is required in both oral and neural ectodermal tissues for the activation of signaling pathways and transcription factors necessary for pituitary cell fate. These studies clarify the mechanism of SIX3 action in pituitary development and provide support for a digenic basis for hypopituitarism.

Current and Future Approaches to Classify VUSs in LGMD-Related Genes

Next-generation sequencing (NGS) has revealed large numbers of genetic variants in LGMD-related genes, with most of them classified as variants of uncertain significance (VUSs). VUSs are genetic changes with unknown pathological impact and present a major challenge in genetic test interpretation and disease diagnosis. Understanding the phenotypic consequences of VUSs can provide clinical guidance regarding LGMD risk and therapy. In this review, we provide a brief overview of the subtypes of LGMD, disease diagnosis, current classification systems for investigating VUSs, and a potential deep mutational scanning approach to classify VUSs in LGMD-related genes.

Novel genes and variants associated with congenital pituitary hormone deficiency in the era of next-generation sequencing

Combined pituitary hormone deficiency (CPHD) is not a rare disorder, with a frequency of approximately 1 case per 4,000 live births. However, in most cases, a genetic diagnosis is not available. Furthermore, the diagnosis is challenging because no clear correlation exists between the pituitary hormones affected and the gene(s) responsible for the disorder. Next-generation sequencing (NGS) has recently been widely used to identify novel genes that cause (or putatively cause) CPHD. This review outlines causative genes for CPHD that have been newly reported in recent years. Moreover, novel variants of known CPHD-related genes (POU1F1 and GH1 genes) that contribute to CPHD through unique mechanisms are also discussed in this review. From a clinical perspective, variants in some of the recently identified causative genes result in extra-pituitary phenotypes. Clinical research on the related symptoms and basic research on pituitary formation may help in inferring the causative gene(s) of CPHD. Future NGS analysis of a large number of CPHD cases may reveal new genes related to pituitary development. Clarifying the causative genes of CPHD may help to understand the process of pituitary development. We hope that future innovations will lead to the identification of genes responsible for CPHD and pituitary development.

Silent but Not Harmless: A Synonymous SLC5A5 Gene Variant Leading to Dyshormonogenic Congenital Hypothyroidism

BACKGROUND

Congenital iodide transport defect (ITD) is an uncommon cause of dyshormonogenic congenital hypothyroidism characterized by the absence of active iodide accumulation in the thyroid gland. ITD is an autosomal recessive disorder caused by loss-of-function variants in the sodium/iodide symporter (NIS)-coding SLC5A5 gene.

OBJECTIVE

We aimed to identify, and if so to functionally characterize, novel ITD-causing SLC5A5 gene variants in a cohort of five unrelated pediatric patients diagnosed with dyshormonogenic congenital hypothyroidism with minimal to absent ^99mTc-pertechnetate accumulation in the thyroid gland.

METHODS

The coding region of the SLC5A5 gene was sequenced using Sanger sequencing. In silico analysis and functional in vitro characterization of a novel synonymous variant were performed.

RESULTS

Sanger sequencing revealed a novel homozygous synonymous SLC5A5 gene variant (c.1326A>C in exon 11). In silico analysis revealed that the c.1326A>C variant is potentially deleterious for NIS pre-mRNA splicing. The c.1326A>C variant was predicted to lie within a putative exonic splicing enhancer reducing the binding of splicing regulatory trans-acting protein SRSF5. Splicing minigene reporter assay revealed that c.1326A>C causes exon 11 or exon 11 and 12 skipping during NIS pre-mRNA splicing leading to the NIS pathogenic variants p.G415_P443del and p.G415Lfs*32, respectively. Significantly, the frameshift variant p.G415Lfs*32 is predicted to be subjected to degradation by nonsense-mediated decay.

CONCLUSIONS

We identified the first exonic synonymous SLC5A5 gene variant causing aberrant NIS pre-mRNA splicing, thus expanding the mutational landscape of the SLC5A5 gene leading to dyshormonogenic congenital hypothyroidism.

Linking genome variants to disease: scalable approaches to test the functional impact of human mutations

The application of genomics to medicine has accelerated the discovery of mutations underlying disease and has enhanced our knowledge of the molecular underpinnings of diverse pathologies. As the amount of human genetic material queried via sequencing has grown exponentially in recent years, so too has the number of rare variants observed. Despite progress, our ability to distinguish which rare variants have clinical significance remains limited. Over the last decade, however, powerful experimental approaches have emerged to characterize variant effects orders of magnitude faster than before. Fueled by improved DNA synthesis and sequencing and, more recently, by CRISPR/Cas9 genome editing, multiplex functional assays provide a means of generating variant effect data in wide-ranging experimental systems. Here, I review recent applications of multiplex assays that link human variants to disease phenotypes and I describe emerging strategies that will enhance their clinical utility in coming years.

The CDH1 c.1901C>T Variant: A Founder Variant in the Portuguese Population with Severe Impact in mRNA Splicing

Simple Summary

An unexpectedly high number of early-onset diffuse gastric and lobular breast cancer in apparently unrelated families carrying the same CDH1 c.1901C>T variant (formerly known as missense p.A634V) in Northern Portugal suggested a founder effect in this region. We demonstrated that c.1901C>T is a truncating variant triggered by cryptic splicing, calculated its mutational age, and characterized the tumour spectrum and age of onset in affected families.

Abstract

Hereditary diffuse gastric cancer (HDGC) caused by CDH1 variants predisposes to early-onset diffuse gastric (DGC) and lobular breast cancer (LBC). In Northern Portugal, the unusually high number of HDGC cases in unrelated families carrying the c.1901C>T variant (formerly known as p.A634V) suggested this as a CDH1-founder variant. We aimed to demonstrate that c.1901C>T is a bona fide truncating variant inducing cryptic splicing, to calculate the timing of a potential founder effect, and to characterize tumour spectrum and age of onset in carrying families. The impact in splicing was proven by using carriers’ RNA for PCR-cloning sequencing and allelic expression imbalance analysis with SNaPshot. Carriers and noncarriers were haplotyped for 12 polymorphic markers, and the decay of haplotype sharing (DHS) method was used to estimate the time to the most common ancestor of c.1901C>T. Clinical information from 58 carriers was collected and analysed. We validated the cryptic splice site within CDH1-exon 12, which was preferred over the canonical one in 100% of sequenced clones. Cryptic splicing induced an out-of-frame 37bp deletion in exon 12, premature truncation (p.Ala634ProfsTer7), and consequently RNA mediated decay. The haplotypes carrying the c.1901C>T variant were found to share a common ancestral estimated at 490 years (95% Confidence Interval 445–10,900). Among 58 carriers (27 males (M)–31 females (F); 13–83 years), DGC occurred in 11 (18.9%; 4M–7F; average age 33 ± 12) and LBC in 6 females (19.4%; average age 50 ± 8). Herein, we demonstrated that the c.1901C>T variant is a loss-of-function splice-site variant that underlies the first CDH1-founder effect in Portugal. Knowledge on this founder effect will drive genetic testing of this specific variant in HDGC families in this geographical region and allow intrafamilial penetrance analysis and better estimation of variant-associated tumour risks, disease age of onset, and spectrum.