Using Structural Analysis In Silico to Assess the Impact of Missense Variants in MEN1

Compilation of Genotype and Phenotype Data in GCDH-LOVD for Variant Classification and Further Application

Glutaric aciduria type 1 (GA-1) is a rare but treatable autosomal-recessive neurometabolic disorder of lysin metabolism caused by biallelic pathogenic variants in glutaryl-CoA dehydrogenase gene (GCDH) that lead to deficiency of GCDH protein. Without treatment, this enzyme defect causes a neurological phenotype characterized by movement disorder and cognitive impairment. Based on a comprehensive literature search, we established a large dataset of GCDH variants using the Leiden Open Variation Database (LOVD) to summarize the known genotypes and the clinical and biochemical phenotypes associated with GA-1. With these data, we developed a GCDH-specific variation classification framework based on American College of Medical Genetics and Genomics and the Association for Molecular Pathology guidelines. We used this framework to reclassify published variants and to describe their geographic distribution, both of which have practical implications for the molecular genetic diagnosis of GA-1. The freely available GCDH-specific LOVD dataset provides a basis for diagnostic laboratories and researchers to further optimize their knowledge and molecular diagnosis of this rare disease.

Protein modeling and in silico analysis to assess pathogenicity of ABCA4 variants in patients with inherited retinal disease

Purpose

The retina-specific ABCA transporter, ABCA4, plays an essential role in translocating retinoids required by the visual cycle. ABCA4 genetic variants are known to cause a wide range of inherited retinal disorders, including Stargardt disease and cone-rod dystrophy. More than 1,400 ABCA4 missense variants have been identified; however, more than half of these remain variants of uncertain significance (VUS). The purpose of this study was to employ a predictive strategy to assess the pathogenicity of ABCA4 variants in inherited retinal diseases using protein modeling and computational approaches.

Methods

We studied 13 clinically well-defined patients with ABCA4 retinopathies and identified the presence of 10 missense variants, including one novel variant in the ABCA4 gene, by next-generation sequencing (NGS). All variants were structurally analyzed using AlphaFold2 models and existing experimental structures of human ABCA4 protein. The results of these analyses were compared with patient clinical presentations to test the effectiveness of the methods employed in predicting variant pathogenicity.

Results

We conducted a phenotype-genotype comparison of 13 genetically and phenotypically well-defined retinal disease patients. The in silico protein structure analyses we employed successfully detected the deleterious effect of missense variants found in this affected patient cohort. Our study provides American College of Medical Genetics and Genomics (ACMG)-defined supporting evidence of the pathogenicity of nine missense ABCA4 variants, aligning with the observed clinical phenotypes in this cohort.

Conclusions

In this report, we describe a systematic approach to predicting the pathogenicity of ABCA4 variants by means of three-dimensional (3D) protein modeling and in silico structure analysis. Our results demonstrate concordance between disease severity and structural changes in protein models induced by genetic variations. Furthermore, the present study suggests that in silico protein structure analysis can be used as a predictor of pathogenicity and may facilitate the assessment of genetic VUS.

Multiple Metastases of Parathyroid and Papillary Thyroid Carcinoma in a Female Patient Treated with Long-Term Hemodialysis

Parathyroid cancer is a rare, clinically aggressive malignancy with a prevalence of approximately 0.005% relative to all carcinoma cases and 1-5% among patients with primary hyperparathyroidism. Prognosis largely depends on the extent of the primary surgery. Non-radical surgical treatment increases the risk of local and distant metastases of the parathyroid cancer associated with limited treatment options. The combination of thyroid and parathyroid disorders has been described rather well for the general population; however, cases of parathyroid and thyroid carcinoma in the same patient are extremely rare (1 case per 3000 patients with parathyroid disorders). We present a rare clinical case of combination of parathyroid and thyroid cancers with metastases of both tumors to the neck lymph nodes in a woman with a mutation in the MEN1 gene (NM_130799.2): c.658T > C p.Trp220Arg (W220R), who has been exposed to radiation for 20 years before diagnosis of thyroid cancer and received renal replacement therapy with long-term hemodialysis before the diagnosis of parathyroid cancer. The patient underwent several surgeries because of metastases of the parathyroid cancer in the neck lymph nodes. Surgeons used intraoperative navigation methods (single-channel gamma detection probe, Gamma Probe 2, and fluorescence angiography with indocyanine green (ICG)) to clarify the volume of surgery. Currently, the patient is still in laboratory remission, despite the structural recurrence of tumors.

Assessing the clinical utility of protein structural analysis in genomic variant classification: experiences from a diagnostic laboratory

Background

The widespread clinical application of genome-wide sequencing has resulted in many new diagnoses for rare genetic conditions, but testing regularly identifies variants of uncertain significance (VUS). The remarkable rise in the amount of genomic data has been paralleled by a rise in the number of protein structures that are now publicly available, which may have clinical utility for the interpretation of missense and in-frame insertions or deletions.

Methods

Within a UK National Health Service genomic medicine diagnostic laboratory, we investigated the number of VUS over a 5-year period that were evaluated using protein structural analysis and how often this analysis aided variant classification.

Results

We found 99 novel missense and in-frame variants across 67 genes that were initially classified as VUS by our diagnostic laboratory using standard variant classification guidelines and for which further analysis of protein structure was requested. Evidence from protein structural analysis was used in the re-assessment of 64 variants, of which 47 were subsequently reclassified as pathogenic or likely pathogenic and 17 remained as VUS. We identified several case studies where protein structural analysis aided variant interpretation by predicting disease mechanisms that were consistent with the observed phenotypes, including loss-of-function through thermodynamic destabilisation or disruption of ligand binding, and gain-of-function through de-repression or escape from proteasomal degradation.

Conclusions

We have shown that using in silico protein structural analysis can aid classification of VUS and give insights into the mechanisms of pathogenicity. Based on our experience, we propose a generic evidence-based workflow for incorporating protein structural information into diagnostic practice to facilitate variant classification.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13073-022-01082-2.

Approach to the patient with a variant of uncertain significance on genetic testing

Establishing a genetic diagnosis may lead to major health benefits for the patient and their wider family, but is dependent on the accurate interpretation of test results. The processes of variant interpretation are by their nature imprecise such that the potential for uncertain test results (i.e., variant(s) of uncertain significance [VUS]) are an inevitable consequence of genomic testing. With an increased responsibility for diagnostic testing in the hands of the specialty physician (e.g., endocrinologist) rather than clinical geneticist, it is essential that they are familiar with the possible outcomes of testing including an understanding of the VUS category. While uncertainty is endemic to many aspects of clinical medicine, receiving a VUS result may pose a considerable challenge to both the clinician and the patient. In this article, a framework to support decision-making when confronted with a VUS variant is provided, focusing on the key components of the genetic testing pathway. This highlights the importance of assessing the VUS result in the context of the clinical presentation and genetic testing strategy, the value of multidisciplinary team working and ensuring good communication with the patient.

Multi-omics analyses of MEN1 missense mutations identify disruption of menin-MLL and menin-JunD interactions as critical requirements for molecular pathogenicity

Background

Loss-of-function mutations of the multiple endocrine neoplasia type 1 (MEN1) gene are causal to the MEN1 tumor syndrome, but they are also commonly found in sporadic pancreatic neuroendocrine tumors and other types of cancers. The MEN1 gene product, menin, is involved in transcriptional and chromatin regulation, most prominently as an integral component of KMT2A/MLL1 and KMT2B/MLL2 containing COMPASS-like histone H3K4 methyltransferase complexes. In a mutually exclusive fashion, menin also interacts with the JunD subunit of the AP-1 and ATF/CREB transcription factors.

Results

Here, we applied and in silico screening approach for 253 disease-related MEN1 missense mutations in order to select a set of nine menin mutations in surface-exposed residues. The protein interactomes of these mutants were assessed by quantitative mass spectrometry, which indicated that seven of the nine mutants disrupt interactions with both MLL1/MLL2 and JunD complexes. Interestingly, we identified three missense mutations, R52G, E255K and E359K, which predominantly reduce the MLL1 and MLL2 interactions when compared with JunD. This observation was supported by a pronounced loss of binding of the R52G, E255K and E359K mutant proteins at unique MLL1 genomic binding sites with less effect on unique JunD sites.

Conclusions

Our results underline the effects of MEN1 gene mutations in both familial and sporadic tumors of endocrine origin on the interactions of menin with the MLL1 and MLL2 histone H3K4 methyltransferase complexes and with JunD-containing transcription factors. Menin binding pocket mutants R52G, E255K and E359K have differential effects on MLL1/MLL2 and JunD interactions, which translate into differential genomic binding patterns. Our findings encourage future studies addressing the pathophysiological relevance of the separate MLL1/MLL2- and JunD-dependent functions of menin mutants in MEN1 disease model systems.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13072-022-00461-8.

In-silico analysis of nonsynonymous genomic variants within CCM2 gene reaffirm the existence of dual cores within typical PTB domain

Purpose

The objective of this study is to validate the existence of dual cores within the typical phosphotyrosine binding (PTB) domain and to identify potentially damaging and pathogenic nonsynonymous coding single nuclear polymorphisms (nsSNPs) in the canonical PTB domain of the CCM2 gene that causes cerebral cavernous malformations (CCMs).

Methods

The nsSNPs within the coding sequence for PTB domain of human CCM2 gene, retrieved from exclusive database searches, were analyzed for their functional and structural impact using a series of bioinformatic tools. The effects of mutations on the tertiary structure of the PTB domain in human CCM2 protein were predicted to examine the effect of nsSNPs on the tertiary structure of PTB Cores.

Results

Our mutation analysis, through alignment of protein structures between wildtype CCM2 and mutant, predicted that the structural impacts of pathogenic nsSNPs is biophysically limited to only the spatially adjacent substituted amino acid site with minimal structural influence on the adjacent core of the PTB domain, suggesting both cores are independently functional and essential for proper CCM2 PTB function.

Conclusion

Utilizing a combination of protein conservation and structure-based analysis, we analyzed the structural effects of inherited pathogenic mutations within the CCM2 PTB domain. Our results predicted that the pathogenic amino acid substitutions lead to only subtle changes locally, confined to the surrounding tertiary structure of the PTB core within which it resides, while no structural disturbance to the neighboring PTB core was observed, reaffirming the presence of independently functional dual cores in the CCM2 typical PTB domain.

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The pathogenic amino acid mutants lead to subtle structural changes in the PTB core.

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No structural disturbance to the neighboring PTB core was observed.

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Data reaffirm the presence of dual functional cores in the CCM2 PTB domain.

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More new genetic variants leading to CCM pathogenesis were suggested.

Multiple Endocrine Neoplasia Type 1: Latest Insights

Multiple endocrine neoplasia type 1 (MEN1), a rare tumor syndrome that is inherited in an autosomal dominant pattern, is continuing to raise great interest for endocrinology, gastroenterology, surgery, radiology, genetics, and molecular biology specialists. There have been 2 major clinical practice guidance papers published in the past 2 decades, with the most recent published 8 years ago. Since then, several new insights on the basic biology and clinical features of MEN1 have appeared in the literature, and those data are discussed in this review. The genetic and molecular interactions of the MEN1-encoded protein menin with transcription factors and chromatin-modifying proteins in cell signaling pathways mediated by transforming growth factor β/bone morphogenetic protein, a few nuclear receptors, Wnt/β-catenin, and Hedgehog, and preclinical studies in mouse models have facilitated the understanding of the pathogenesis of MEN1-associated tumors and potential pharmacological interventions. The advancements in genetic diagnosis have offered a chance to recognize MEN1-related conditions in germline MEN1 mutation-negative patients. There is rapidly accumulating knowledge about clinical presentation in children, adolescents, and pregnancy that is translatable into the management of these very fragile patients. The discoveries about the genetic and molecular signatures of sporadic neuroendocrine tumors support the development of clinical trials with novel targeted therapies, along with advancements in diagnostic tools and surgical approaches. Finally, quality of life studies in patients affected by MEN1 and related conditions represent an effort necessary to develop a pharmacoeconomic interpretation of the problem. Because advances are being made both broadly and in focused areas, this timely review presents and discusses those studies collectively.

Folliculin variants linked to Birt-Hogg-Dubé syndrome are targeted for proteasomal degradation

Germline mutations in the folliculin (FLCN) tumor suppressor gene are linked to Birt-Hogg-Dubé (BHD) syndrome, a dominantly inherited genetic disease characterized by predisposition to fibrofolliculomas, lung cysts, and renal cancer. Most BHD-linked FLCN variants include large deletions and splice site aberrations predicted to cause loss of function. The mechanisms by which missense variants and short in-frame deletions in FLCN trigger disease are unknown. Here, we present an integrated computational and experimental study that reveals that the majority of such disease-causing FLCN variants cause loss of function due to proteasomal degradation of the encoded FLCN protein, rather than directly ablating FLCN function. Accordingly, several different single-site FLCN variants are present at strongly reduced levels in cells. In line with our finding that FLCN variants are protein quality control targets, several are also highly insoluble and fail to associate with the FLCN-binding partners FNIP1 and FNIP2. The lack of FLCN binding leads to rapid proteasomal degradation of FNIP1 and FNIP2. Half of the tested FLCN variants are mislocalized in cells, and one variant (ΔE510) forms perinuclear protein aggregates. A yeast-based stability screen revealed that the deubiquitylating enzyme Ubp15/USP7 and molecular chaperones regulate the turnover of the FLCN variants. Lowering the temperature led to a stabilization of two FLCN missense proteins, and for one (R362C), function was re-established at low temperature. In conclusion, we propose that most BHD-linked FLCN missense variants and small in-frame deletions operate by causing misfolding and degradation of the FLCN protein, and that stabilization and resulting restoration of function may hold therapeutic potential of certain disease-linked variants. Our computational saturation scan encompassing both missense variants and single site deletions in FLCN may allow classification of rare FLCN variants of uncertain clinical significance.

Identification of pathogenic missense mutations using protein stability predictors

Attempts at using protein structures to identify disease-causing mutations have been dominated by the idea that most pathogenic mutations are disruptive at a structural level. Therefore, computational stability predictors, which assess whether a mutation is likely to be stabilising or destabilising to protein structure, have been commonly used when evaluating new candidate disease variants, despite not having been developed specifically for this purpose. We therefore tested 13 different stability predictors for their ability to discriminate between pathogenic and putatively benign missense variants. We find that one method, FoldX, significantly outperforms all other predictors in the identification of disease variants. Moreover, we demonstrate that employing predicted absolute energy change scores improves performance of nearly all predictors in distinguishing pathogenic from benign variants. Importantly, however, we observe that the utility of computational stability predictors is highly heterogeneous across different proteins, and that they are all inferior to the best performing variant effect predictors for identifying pathogenic mutations. We suggest that this is largely due to alternate molecular mechanisms other than protein destabilisation underlying many pathogenic mutations. Thus, better ways of incorporating protein structural information and molecular mechanisms into computational variant effect predictors will be required for improved disease variant prioritisation.