Variant Interpretation Guidelines Research Articles

P-566 Addressing ethnic underrepresentation in carrier screening: prioritizing comprehensive variant curation over ClinVar-based automated analysis

Abstract Study question How does the use of a ClinVar-based approach in Carrier Genetic Screening (CGS) affect the efficiency and accuracy of carrier detection analysis? Summary answer For CGS, comprehensive variant curation, not automated analysis alone, addresses risk from under-representation of diverse populations in genetic databases. What is known already Next-generation sequencing (NGS) analyses in Carrier Screening (CS) yield numerous variants per patient requiring interpretation for pathogenicity assessment. Public variant databases aid in the curation process, clinical interpretation, and genomic data sharing, reducing error risks and diagnostic delays. Consequently, an increasing number of genetic laboratories are integrating these databases into their workflows. However, over-representation of certain ethnic groups persists due to genetic inequality, as these databases primarily contain variants previously reported in patients and manually recorded. This lack of ethnic diversity in human genomic studies and databases can lead to inaccurate risk assessment and inadequate interventions in under-studied populations. Study design, size, duration Retrospective analysis involved 3886 patients of various ethnicities examined between June 2021 and March 2023. They were grouped according to self-reported ethnicity: African(54), Asian(43), Mediterranean(689), European/Caucasian(2402), Latino(449) and not reported(249). Participants/materials, setting, methods Patients were categorized based on their self-reported ethnicity after undergoing analysis with a Carrier Screening (CS) panel of 300 genes, which included autosomal recessive and X-linked disorders, using Next-Generation Sequencing (NGS). Complete variant curation (CCV) was conducted using the American College of Medical Genetics and Genomics(ACMG) and ClinGen guidelines for variant interpretation. The average number of variants per patient was calculated for both the automated process using only the ClinVar database and the CCV performed. Main results and the role of chance Upon evaluating the number of variants identified per patient,, 1.51 variants/patient (v/p) were observed when CCV, while 1.27 v/p would have been detected using only ClinVar (automated process). In summary, ClinVar accounted for 88% of all variants identified with CCV. Significant differences in variant detection were observed across ethnicities. The percentage of variants not detected by the automatic process were as follows: 21.95% in Asian ethnicity, 17.84% in African, 13.99% in Latino, 11.88% in Mediterranean, 10.97% in European/Caucasian and 10.70% in patients who did not report ethnicity. Among these, Asian and African ethnic groups had the lowest percentage of variants detected by ClinVar 78.05% and 82.16%, respectively. In the Asian group, 0.95 v/p were identified, while in the African group, 1.70 v/p were identified. Limitations, reasons for caution Data was collected based on self-reported ethnicity, which may not always accurately reflect true ancestry. Additionally, the sample size for certain ethnicities was relatively small. Variant classification relied on information available in databases or literature at the time of the study, potentially subject to updates or revisions in the future. Wider implications of the findings This study underscores the limitations of automated analysis in detecting all variants identified by CCV across ethnicities, highlighting genetic disparities present in mutation databases like ClinVar. The findings emphasize the importance of implementing CCV in Carrier Screening tests to effectively mitigate reproductive risks across diverse ethnic groups. Trial registration number not applicable

The updates of the ACMG variant interpretation guidelines affect the pathogenicity determination of OTOF gene variations in patients with auditory neuropathy

Objective: To compare the differences between the variation interpretation standards and guidelines issued by the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) in 2015 (The 2015ACMG/AMP guideline) and the Deafness Specialist Group of the Clinical Genome Resource (ClinGen) in 2018 for hereditary hearing loss (Healing loss, HL) issued the expert specification of the variation interpretation guide (The 2018 HL-EP guideline) in evaluating the pathogenicity of OTOF gene variation in patients with auditory neuropathy. Methods: Thirty-eight auditory neuropathy patients with OTOF gene variant were selected as the study subjects (23 males and 15 females, aged 0.3-25.9 years). Using whole-genome sequencing, whole exome sequencing or target region sequencing (Panel) combined with Sanger sequencing, 38 cases were found to carry more than two OTOF mutation sites. A total of 59 candidate variants were independently interpreted based on the 2015 ACMG/AMP guideline and 2018 HL-EP guideline. Compared with the judgment results in 2015 ACMG/AMP guideline, the variants interpreted as lower pathogenic classifications in the 2018 HL-EP guideline were defined as downgraded variants, and the variants regarded as higher pathogenic classifications were defined as upgraded variants. Statistical analysis was conducted using SPSS 20.0. Results: The concordance rate of variant classification between the guidelines was 72.9%(43/59). The 13.6%(8/59) of variants were upgraded and 13.6% (8/59) of variants downgraded in the classifications of the 2018 HL-EP guideline. A couple of rules saw significant differences between the guidelines (PVS1, PM3, PP2, PP3 and PP5). The distribution of pathogenicity of splicing mutation was statistically different (P=0.013). Conclusions: The 2018 HL-EP guideline is inconsistent with the 2015 ACMG/AMP guideline, when judging the pathogenicity of OTOF gene variants in patients with auditory neuropathy. Through the deletion and refinement of evidence and the breaking of solidification thinking, the 2018 HL-EP guideline makes the pathogenicity grading more traceable and improves the credibility.

Undiagnosed RASopathies in infertile men.

RASopathies are syndromes caused by congenital defects in the Ras/mitogen-activated protein kinase (MAPK) pathway genes, with a population prevalence of 1 in 1,000. Patients are typically identified in childhood based on diverse characteristic features, including cryptorchidism (CR) in >50% of affected men. As CR predisposes to spermatogenic failure (SPGF; total sperm count per ejaculate 0-39 million), we hypothesized that men seeking infertility management include cases with undiagnosed RASopathies. Likely pathogenic or pathogenic (LP/P) variants in 22 RASopathy-linked genes were screened in 521 idiopathic SPGF patients (including 155 CR cases) and 323 normozoospermic controls using exome sequencing. All 844 men were recruited to the ESTonian ANDrology (ESTAND) cohort and underwent identical andrological phenotyping. RASopathy-specific variant interpretation guidelines were used for pathogenicity assessment. LP/P variants were identified in PTPN11 (two), SOS1 (three), SOS2 (one), LZTR1 (one), SPRED1 (one), NF1 (one), and MAP2K1 (one). The findings affected six of 155 cases with CR and SPGF, three of 366 men with SPGF only, and one (of 323) normozoospermic subfertile man. The subgroup "CR and SPGF" had over 13-fold enrichment of findings compared to controls (3.9% vs. 0.3%; Fisher's exact test, p = 5.5 × 10-3). All ESTAND subjects with LP/P variants in the Ras/MAPK pathway genes presented congenital genitourinary anomalies, skeletal and joint conditions, and other RASopathy-linked health concerns. Rare forms of malignancies (schwannomatosis and pancreatic and testicular cancer) were reported on four occasions. The Genetics of Male Infertility Initiative (GEMINI) cohort (1,416 SPGF cases and 317 fertile men) was used to validate the outcome. LP/P variants in PTPN11 (three), LZTR1 (three), and MRAS (one) were identified in six SPGF cases (including 4/31 GEMINI cases with CR) and one normozoospermic man. Undiagnosed RASopathies were detected in total for 17 ESTAND and GEMINI subjects, 15 SPGF patients (10 with CR), and two fertile men. Affected RASopathy genes showed high expression in spermatogenic and testicular somatic cells. In conclusion, congenital defects in the Ras/MAPK pathway genes represent a new congenital etiology of syndromic male infertility. Undiagnosed RASopathies were especially enriched among patients with a history of cryptorchidism. Given the relationship between RASopathies and other conditions, infertile men found to have this molecular diagnosis should be evaluated for known RASopathy-linked health concerns, including specific rare malignancies.

An AI-based approach driven by genotypes and phenotypes to uplift the diagnostic yield of genetic diseases.

Identifying disease-causing variants in Rare Disease patients' genome is a challenging problem. To accomplish this task, we describe a machine learning framework, that we called "Suggested Diagnosis", whose aim is to prioritize genetic variants in an exome/genome based on the probability of being disease-causing. To do so, our method leverages standard guidelines for germline variant interpretation as defined by the American College of Human Genomics (ACMG) and the Association for Molecular Pathology (AMP), inheritance information, phenotypic similarity, and variant quality. Starting from (1) the VCF file containing proband's variants, (2) the list of proband's phenotypes encoded in Human Phenotype Ontology terms, and optionally (3) the information about family members (if available), the "Suggested Diagnosis" ranks all the variants according to their machine learning prediction. This method significantly reduces the number of variants that need to be evaluated by geneticists by pinpointing causative variants in the very first positions of the prioritized list. Most importantly, our approach proved to be among the top performers within the CAGI6 Rare Genome Project Challenge, where it was able to rank the true causative variant among the first positions and, uniquely among all the challenge participants, increased the diagnostic yield of 12.5% by solving 2 undiagnosed cases.

Abstract 2351: Genomics annotation and interpretation in somatic oncology using structured data from a clinical knowledgebase

Abstract Accurate and comprehensive interpretation of genomic variants has become a bottleneck in clinical sequencing applications due to the accelerating precision oncology and biomedical information explosion. This motivated us to build Ephesus, a framework enabling curation of predictive, prognostic and diagnostic evidence for clinical biomarkers in cancers. Currently Ephesus is the primary content source for Roche navify Mutation Profiler (nMP). The Ephesus’ data model ensures adherence to best practices in clinical genomic content curation. Variant classification follows the AMP guidelines for somatic variant interpretation. Variant interpretations are derived from international regulatory approvals and clinical practice guidelines (FDA, EMA, TGA, eVIQ, etc.) and recommendations (NCCN, ESMO). The data model is mapped to a set of relational tables. To enforce data integrity and validity, strategies such as data normalization based on standard nomenclatural ontologies, a submit-review-approval workflow, and biological constraints are adopted. Ephesus is deployed as a web application used by curators inside and outside Roche. The UI allows users to conduct edits, filtering, sorting and bulk operations on entities by attributes. In order to minimize manual effort and maximize content coverage, inference rules are applied before ingesting into nMP. Currently Ephesus is developed for data collection, browsing and summarizing primary entities such as biomarkers, evidence items, genes, variants, variant groups, and drugs. The content from the 2023-Aug snapshot contains 11,596 directly curated biomarker profiles (including biomarker combinations), and 6M+ expanded profiles for 41 major cancer types. To evaluate the clinical reporting value of the curated knowledge, ~160k real cancer patient samples of the AACR GENIE project were queried on Ephesus. Compared with three other major knowledgebases, Ephesus/NMP is observed showing the highest performance. Table 1. Percentage of patients or biomarkers with at least one interpretation from each knowledgebase CGI (2022-10-17) CIVIC(2023-09-01) ClinVar(2023-09-09) NMP(2023-08-11) AACR-Genie-v14.0 Total patient % with any interpretation 25% (40,545) 46% (73,835) 81% (130,882) 89% (142,905) 160,965 biomarker % (including combos) with any interpretation 0.03% (256) 0.06% (526) 13.26% (122,424) 73.79% (681,128) 923,093 Citation Format: Jian Li, Lili Niu, Shuba krishna, Fnu Kinshuk, Martin Jones, Carlos Hernandez, Michael Clark, Sandra Balladares. Genomics annotation and interpretation in somatic oncology using structured data from a clinical knowledgebase [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 2351.

Disease-specific variant interpretation highlighted the genetic findings in 2325 Japanese patients with retinitis pigmentosa and allied diseases

BackgroundAs gene-specific therapy for inherited retinal dystrophy (IRD) advances, unified variant interpretation across institutes is becoming increasingly important. This study aims to update the genetic findings of 86 retinitis pigmentosa...

ClinGen variant curation expert panel recommendations for classification of variants in GAMT, GATM and SLC6A8 for cerebral creatine deficiency syndromes

Cerebral creatine deficiency syndromes (CCDS) are inherited metabolic phenotypes of creatine synthesis and transport. There are two enzyme deficiencies, guanidinoacetate methyltransferase (GAMT), encoded by GAMT and arginine-glycine amidinotransferase (AGAT), encoded by GATM, which are involved in the synthesis of creatine. After synthesis, creatine is taken up by a sodium-dependent membrane bound creatine transporter (CRTR), encoded by SLC6A8, into all organs. Creatine uptake is very important especially in high energy demanding organs such as the brain, and muscle. To classify the pathogenicity of variants in GAMT, GATM, and SLC6A8, we developed the CCDS Variant Curation Expert Panel (VCEP) in 2018, supported by The Clinical Genome Resource (ClinGen), a National Institutes of Health (NIH)-funded resource. We developed disease-specific variant classification guidelines for GAMT-, GATM-, and SLC6A8-related CCDS, adapted from the American College of Medical Genetics/Association of Molecular Pathology (ACMG/AMP) variant interpretation guidelines. We applied specific variant classification guidelines to 30 pilot variants in each of the three genes that have variants associated with CCDS. Our CCDS VCEP was approved by the ClinGen Sequence Variant Interpretation Working Group (SVI WG) and Clinical Domain Oversight Committee in July 2022. We curated 181 variants including 72 variants in GAMT, 45 variants in GATM, and 64 variants in SLC6A8 and submitted these classifications to ClinVar, a public variant database supported by the National Center for Biotechnology Information. Missense variants were the most common variant type in all three genes. We submitted 32 new variants and reclassified 34 variants with conflicting interpretations. We report specific phenotype (PP4) using a points system based on the urine and plasma guanidinoacetate and creatine levels, brain magnetic resonance spectroscopy (MRS) creatine level, and enzyme activity or creatine uptake in fibroblasts ranging from PP4, PP4_Moderate and PP4_Strong. Our CCDS VCEP is one of the first panels applying disease specific variant classification algorithms for an X-linked disease. The availability of these guidelines and classifications can guide molecular genetics and genomic laboratories and health care providers to assess the molecular diagnosis of individuals with a CCDS phenotype.

A Retrospective Review of 18 Patients With Childhood-Onset Hereditary Spastic Paraplegia, Nine With Novel Variants

BackgroundHereditary spastic paraplegias (HSPs) are a group of genetically heterogeneous neurodegenerative disorders. Our objective was to determine the clinical and molecular characteristics of patients with genetically confirmed childhood-onset HSPs and to expand the genetic spectrum for some rare subtypes of HSP. MethodsWe reviewed the charts of subjects with genetically confirmed childhood-onset HSP. The age at the disease onset was defined as the point at which the delayed motor milestones were observed. Delayed motor milestones were defined as being unable to hold the head up by four months, sitting unassisted by nine months, and walking independently by 17 months. If there were no delayed motor milestones, age at disease onset was determined by leg stiffness, frequent falls, or unsteady gait. Genetic testing was performed based on delayed motor milestones, progressive leg spasticity, and gait difficulty. The variant classification was determined based on the American College of Medical Genetics standard guidelines for variant interpretation. Variants of uncertain significance (VUS) were considered disease-associated when clinical findings were consistent with the previously described disease phenotypes for pathogenic variants. In addition, in the absence of another pathogenic, likely pathogenic, or VUS variant that could explain the phenotype of our cases, we concluded that the disease is associated with VUS in the HSP-causing gene. Segregation analysis was also performed on the parents of some patients to demonstrate the inheritance model. ResultsThere were a total of 18 patients from 17 families. The median age of symptom onset was 18 months (2 to 84 months). The mean delay between symptom onset and genetic diagnosis was 5.8 years (5 months to 17 years). All patients had gait difficulty caused by progressive leg spasticity and weakness. Independent walking was not achieved at 17 months for 67% of patients (n = 12). In our cohort, there were two subjects each with SPG11, SPG46, and SPG 50 followed by single subject each with SPG3A, SPG4, SPG7, SPG8, SPG30, SPG35, SPG43, SPG44, SPG57, SPG62, infantile-onset ascending spastic paralysis (IAHSP), and spastic paraplegia and psychomotor retardation with or without seizures (SPPRS). Eight novel variants in nine patients were described. Two affected siblings had a novel variant in the GBA2 gene (SPG46), and one subject each had a novel variant in WASHC5 (SPG8), SPG11 (SPG11), KIF1A (SPG30), GJC2 (SPG44), ERLIN1 (SPG62), ALS2 (IAHSP), and HACE1 (SPPRS). Among the novel variants, the variant in the SPG11 was pathogenic and the variants in the KIF1A, GJC2, and HACE1 were likely pathogenic. The variants in the GBA2, ALS2, ERLIN1, and WASHC5 were classified as VUS. ConclusionsThere was a significant delay between symptom onset and genetic diagnosis of HSP. An early diagnosis may be possible by examining patients with delayed motor milestones, progressive spasticity, gait difficulties, and neuromuscular weakness in the context of HSP. Eight novel variants in nine patients were described, clinically similar to the previously described disease phenotype associated with pathogenic variants. This study contributes to expanding the genetic spectrum of some rare subtypes of HSP.

Tracking updates in clinical databases increases efficiency for variant reanalysis

PurposeVariant interpretation, guided by American College of Medical Genetics and Genomics guidelines, can inform clinical decision-making. However, interpretations may change over time for a variety of reasons. Periodic reanalysis of previous variant interpretations is important to ensure that reported genetic findings remain accurate according to current knowledge. MethodsWe performed automated filtering by comparing ClinVar variants available in August 2020 with those from August 2021 to screen for potential reanalysis candidates from 3 projects. These variants were subsequently interpreted based on the American College of Medical Genetics and Genomics/Association for Molecular Pathology variant interpretation guideline or ClinGen revised gene-specific guidelines if applicable. ResultsOur method annotated 241 unique variants requiring reanalysis, from 3 projects containing 3,832,210 previously interpreted variants, including those filtered automatically. Among these 241 variants, 43 variants changed interpretation, including 55.81% (N = 24) with upgraded and 44.19% (N = 19) with downgraded classifications. An efficiency study showed that our strategy increased the reanalysis efficiency and saved reviewing time. ConclusionWe demonstrated an effective high-throughput method, initiating from external data updates, to achieve variant reanalysis in a clinical laboratory. This filtering method reduced the number of variants that need to be reanalyzed, screened potential variants, and saved time and cost for clinical laboratories.

Improvement of variant reclassification in genetic neurodevelopmental conditions

PurposeLimited knowledge about disease mechanisms, few published cases, and the lack of functional assessment of variants for neurodevelopmental genetic disorders challenge diagnostic classification for variants and increase the frequency of variants of uncertain significance (VUS). Because inheritance patterns aid in variant interpretation for neurodevelopmental conditions, genetic testing including only the proband leads to larger numbers of VUS than testing strategies that include the parents. MethodsWe reinterpreted genetic variants submitted to the Simons Searchlight research registry using American College of Medical Genetics and Genomics variant interpretation guidelines, familial cascade testing, and literature curation with annual VUS reevaluation. ResultsSimons Searchlight has independently evaluated 2834 genetic laboratory reports; 20.4% of variants (1.7% copy-number variants and 18.7% monogenic variants) were reclassified with 230 upgrades and 173 downgrades in pathogenicity. Of 351 monogenic VUS on the original clinical test report, 25.4% were reclassified as likely pathogenic or pathogenic. VUS in SCN2A, SLC6A1, or STXBP1 were more likely to have VUS reclassified compared with variants in other genes. ConclusionRegular reevaluation of neurodevelopmental genetic variants can be helpful because relevant variant reclassifications occur frequently and may affect clinical care. Simons Searchlight contributes to the international neurodevelopmental community by systematically reviewing uncertain variants annually and providing reclassified variants to participants, researchers, and ClinVar.

Whole-Exome Sequencing in Turkish Patients with Inherited Retinal Dystrophies Reveals Novel Variants in Ten Genes

Introduction: Inherited retinal dystrophies (IRDs) associated with more than 300 genes are a clinically and genetically heterogeneous group of retinal diseases. This study aimed to identify causative gene variants and molecular basis of Turkish patients with IRD. Methods: Whole-exome sequencing was performed in 28 unrelated patients. The potential pathogenicity of variants was evaluated using the American College of Medical Genetics variant interpretation guidelines, in silico prediction tools, published literature or Human Gene Mutation Database, and compatibility with inheritance patterns or known phenotypes. Results: Causative variants in 21 genes, including MERTK, SNRP200, MYO7A, AIPL1, RDH12, OTX2, ADGRV1, RPGRIP1, SPATA7, USH2A, MFSD8, CDHR1, EYS, CACNA1F, CNGA3, RDH5, TULP1, BBS2, BEST1, RS1, GUCY2D were detected in 26 (92.9%) of 28 patients. The most prevalent causative variants were observed MERTK (10.7% of cases), followed by CDHR1, AIPL1, RDH12, SPATA7, CNGA3, TULP1 (7.1% of cases, each). The most common variant type in this study was missense variants (53%), followed by frameshift (21%), nonsense (20%), and splice (6%). Twelve novel variants, 6 of frameshift and 6 of missense, were detected in ten genes. Retinitis pigmentosa was the most common phenotype followed by Leber congenital amaurosis. Conclusion: This study provides an overview of causative gene variants in Turkish patients with IRD. Variants identified in this study expand the variant spectrum of IRD genes. We believe it is essential to combine molecular and clinical data to diagnose IRD patients, especially with the emergence of therapeutic options.

The hospital Israelita Albert Einstein standards for constitutional sequence variants classification: version 2023

BackgroundNext-generation sequencing has had a significant impact on genetic disease diagnosis, but the interpretation of the vast amount of genomic data it generates can be challenging. To address this, the American College of Medical Genetics and Genomics and the Association for Molecular Pathology have established guidelines for standardized variant interpretation. In this manuscript, we present the updated Hospital Israelita Albert Einstein Standards for Constitutional Sequence Variants Classification, incorporating modifications from leading genetics societies and the ClinGen initiative.ResultsFirst, we standardized the scientific publications, documents, and other reliable sources for this document to ensure an evidence-based approach. Next, we defined the databases that would provide variant information for the classification process, established the terminology for molecular findings, set standards for disease-gene associations, and determined the nomenclature for classification criteria. Subsequently, we defined the general rules for variant classification and the Bayesian statistical reasoning principles to enhance this process. We also defined bioinformatics standards for automated classification. Our workgroup adhered to gene-specific rules and workflows curated by the ClinGen Variant Curation Expert Panels whenever available. Additionally, a distinct set of specifications for criteria modulation was created for cancer genes, recognizing their unique characteristics.ConclusionsThe development of an internal consensus and standards for constitutional sequence variant classification, specifically adapted to the Brazilian population, further contributes to the continuous refinement of variant classification practices. The aim of these efforts from the workgroup is to enhance the reliability and uniformity of variant classification.

VarCards2: an integrated genetic and clinical database for ACMG-AMP variant-interpretation guidelines in the human whole genome.

VarCards, an online database, combines comprehensive variant- and gene-level annotation data to streamline genetic counselling for coding variants. Recognising the increasing clinical relevance of non-coding variations, there has been an accelerated development of bioinformatics tools dedicated to interpreting non-coding variations, including single-nucleotide variants and copy number variations. Regrettably, most tools remain as either locally installed databases or command-line tools dispersed across diverse online platforms. Such a landscape poses inconveniences and challenges for genetic counsellors seeking to utilise these resources without advanced bioinformatics expertise. Consequently, we developed VarCards2, which incorporates nearly nine billion artificially generated single-nucleotide variants (including those from mitochondrial DNA) and compiles vital annotation information for genetic counselling based on ACMG-AMP variant-interpretation guidelines. These annotations include (I) functional effects; (II) minor allele frequencies; (III) comprehensive function and pathogenicity predictions covering all potential variants, such as non-synonymous substitutions, non-canonical splicing variants, and non-coding variationsand (IV) gene-level information. Furthermore, VarCards2 incorporates 368820266 documented short insertions and deletions and 2773555 documented copy number variations, complemented by their corresponding annotation and prediction tools. In conclusion, VarCards2, by integrating over 150 variant- and gene-level annotation sources, significantly enhances the efficiency of genetic counselling and can be freely accessed at http://www.genemed.tech/varcards2/.

Identification and functional characterization of a novel truncating splicing variant in COL4A5 gene causes X-linked Alport syndrome with astigmatism.

Identification and functional characterization of a novel truncating splicing variant in COL4A5 gene causes X-linked Alport syndrome with astigmatism.

Re-evaluation of a Fibrillin-1 Gene Variant of Uncertain Significance Using the ClinGen Guidelines.

Marfan syndrome (MFS) is caused by fibrillin-1 gene (FBN1) variants. Mutational hotspots and/or well-established critical functional domains of FBN1 include cysteine residues, calcium-binding consensus sequences, and amino acids related to interdomain packaging. Previous guidelines for variant interpretation do not reflect the features of genes or related diseases. Using the Clinical Genome Resource (ClinGen) FBN1 variant curation expert panel (VCEP), we re-evaluated FBN1 germline variants reported as variants of uncertain significance (VUSs). We re-evaluated 26 VUSs in FBN1 reported in 161 patients with MFS. We checked the variants in the Human Genome Mutation Database, ClinVar, and VarSome databases and assessed their allele frequencies using the gnomAD database. Patients' clinical information was reviewed. Four missense variants affecting cysteines (c.460T>C, c.1006T>C, c.5330G>C, and c.8020T>C) were reclassified as likely pathogenic and were assigned PM1_strong or PM1. Two intronic variants were reclassified as benign by granting BA1 (stand-alone). Four missense variants were reclassified as likely benign. BP5 criteria were applied in cases with an alternate molecular basis for disease, one of which (c.7231G>A) was discovered alongside a pathogenic de novo COL3A1 variant (c.1988G>T, p.Gly633Val). Considering the high penetrance of FBN1 variants and clinical variability of MFS, the detection of pathogenic variants is important. The ClinGen FBN1 VCEP encompasses mutational hotspots and/or well-established critical functional domains and adjusts the criteria specifically for MFS; therefore, it is beneficial not only for identifying pathogenic FBN1 variants but also for distinguishing these variants from those that cause other connective tissue disorders with overlapping clinical features.

Constructing and interpreting a large-scale variant effect map for an ultrarare disease gene: Comprehensive prediction of the functional impact of PSAT1 genotypes.

Reduced activity of the enzymes encoded by PHGDH, PSAT1, and PSPH causes a set of ultrarare, autosomal recessive diseases known as serine biosynthesis defects. These diseases present in a broad phenotypic spectrum: at the severe end is Neu-Laxova syndrome, in the intermediate range are infantile serine biosynthesis defects with severe neurological manifestations and growth deficiency, and at the mild end is childhood disease with intellectual disability. However, L-serine supplementation, especially if started early, can ameliorate and in some cases even prevent symptoms. Therefore, knowledge of pathogenic variants can improve clinical outcomes. Here, we use a yeast-based assay to individually measure the functional impact of 1,914 SNV-accessible amino acid substitutions in PSAT. Results of our assay agree well with clinical interpretations and protein structure-function relationships, supporting the inclusion of our data as functional evidence as part of the ACMG variant interpretation guidelines. We use existing ClinVar variants, disease alleles reported in the literature and variants present as homozygotes in the primAD database to define assay ranges that could aid clinical variant interpretation for up to 98% of the tested variants. In addition to measuring the functional impact of individual variants in yeast haploid cells, we also assay pairwise combinations of PSAT1 alleles that recapitulate human genotypes, including compound heterozygotes, in yeast diploids. Results from our diploid assay successfully distinguish the genotypes of affected individuals from those of healthy carriers and agree well with disease severity. Finally, we present a linear model that uses individual allele measurements to predict the biallelic function of ~1.8 million allele combinations corresponding to potential human genotypes. Taken together, our work provides an example of how large-scale functional assays in model systems can be powerfully applied to the study of ultrarare diseases.

The mutational profile in a South African cohort with inherited neuropathies and spastic paraplegia.

Limited diagnostics are available for inherited neuromuscular diseases (NMD) in South Africa and (excluding muscle disease) are mainly aimed at the most frequent genes underlying genetic neuropathy (GN) and spastic ataxias in Europeans. In this study, we used next-generation sequencing to screen 61 probands with GN, hereditary spastic paraplegia (HSP), and spastic ataxias for a genetic diagnosis. After identifying four GN probands with PMP22 duplication and one spastic ataxia proband with SCA1, the remaining probands underwent whole exome (n = 26) or genome sequencing (n = 30). The curation of coding/splice region variants using gene panels was guided by allele frequencies from internal African-ancestry control genomes (n = 537) and the Clinical Genome Resource's Sequence Variant Interpretation guidelines. Of 32 GN probands, 50% had African-genetic ancestry, and 44% were solved: PMP22 (n = 4); MFN2 (n = 3); one each of MORC2, ATP1A1, ADPRHL2, GJB1, GAN, MPZ, and ATM. Of 29 HSP probands (six with predominant ataxia), 66% had African-genetic ancestry, and 48% were solved: SPG11 (n = 3); KIF1A (n = 2); and one each of SPAST, ATL1, SPG7, PCYT2, PSEN1, ATXN1, ALDH18A1, CYP7B1, and RFT1. Structural variants in SPAST, SPG11, SPG7, MFN2, MPZ, KIF5A, and GJB1 were excluded by computational prediction and manual visualisation. In this preliminary cohort screening panel of disease genes using WES/WGS data, we solved ~50% of cases, which is similar to diagnostic yields reported for global cohorts. However, the mutational profile among South Africans with GN and HSP differs substantially from that in the Global North.

Interpretation of SLC3A1 and SLC7A9 variants in cystinuria patients: The significance of the PM3 criterion and protein stability

Cystinuria is a genetic disorder caused by defects in the b0,+ transporter system, which is composed of rBAT and b0,+AT coded by SLC3A1 and SLC7A9, respectively. Variants in SLC3A1 and SLC7A9 follow autosomal recessive inheritance and autosomal dominant inheritance with reduced penetrance, respectively, which complicates the interpretation of cystinuria-related variants. Here, we report seven different SLC3A1 variants and six different SLC7A9 variants. Among these variants were two novel variants previously not reported: SLC3A1 c.223C > T and SLC7A9 c.404A > G. In silico analysis using REVEL correlated well with the functional loss upon SLC7A9 variants with scores of 0.8560–0.9200 and 0.4970–0.5239 for severe and mild decrease in transport activity, respectively. In addition, DynaMut2 was able to predict a decreased protein expression level resulting from the SLC7A9 variant c.313G > A with a ΔΔGStability −2.93 kcal/mol. Our study adds to the literature as additional cases of a variant allow applying the PM3 criterion with higher strength level. In addition, we suggest the clinical utility of REVEL and DynaMut2 in interpreting SLC3A1 and SLC7A9 variants. While a decreased protein expression level is not embraced in the current variant interpretation guidelines, we believe in silico protein stability predicting tools could serve as evidence of protein function loss.

Protein structural insights into a rare PCSK9 gain-of-function variant (R496W) causing familial hypercholesterolemia in a Saudi family: whole exome sequencing and computational analysis.

Familial hypercholesterolemia (FH) is a globally underdiagnosed genetic condition associated with premature cardiovascular death. The genetic etiology data on Arab FH patients is scarce. Therefore, this study aimed to identify the genetic basis of FH in a Saudi family using whole exome sequencing (WES) and multidimensional bioinformatic analysis. Our WES findings revealed a rare heterozygous gain-of-function variant (R496W) in the exon 9 of the PCSK9 gene as a causal factor for FH in this family. This variant was absent in healthy relatives of the proband and 200 healthy normolipidemic controls from Saudi Arabia. Furthermore, this variant has not been previously reported in various regional and global population genomic variant databases. Interestingly, this variant is classified as "likely pathogenic" (PP5) based on the variant interpretation guidelines of the American College of Medical Genetics (ACMG). Computational functional characterization suggested that this variant could destabilize the native PCSK9 protein and alter its secondary and tertiary structural features. In addition, this variant was predicted to negatively influence its ligand-binding ability with LDLR and Alirocumab antibody molecules. This rare PCSK9 (R496W) variant is likely to expand our understanding of the genetic basis of FH in Saudi Arabia. This study also provides computational structural insights into the genotype-protein phenotype relationship of PCSK9 pathogenic variants and contributes to the development of personalized medicine for FH patients in the future.

P-746 Carrier Screening analysis in more than 20.000 patients. Is complete analysis important vs genotyping analysis?

Abstract Study question How comprehensive gene sequencing analysis impacts on carrier screening (CS) results and couple risk reduction? Summary answer Comprehensive genetic sequencing analysis facilitates more accurate carrier rates and provides better information for final panel design and partner risk reduction. What is known already Since CS began in the 1970s, it has helped millions of couples at risk of affected offspring affected by genetic diseases.From the first panels for Ashkenazi Jewish to today’s pan-ethnic CS panels, genetic testing has improved from analysis of a few known pathogenic variants to full sequence analysis. The American College of Medical Genetics and Genomics (ACMG) published Standards and Guidelines for the Interpretation of Sequence Variants in 2015, providing an important tool for full sequence analysis for CS. CS analyses can report only already known mutations (genotyping) or screen for all variants with ACMG-guidelines and laboratory experience (full sequencing). Study design, size, duration This study includes 20774 patients screened with an expanded carrier screening panel of 301 genes, including autosomal recessive (AR) and X-linked (XL) disorders by next-generation sequencing (NGS). ACMG guidelines for variant interpretation were followed in 13954 patients and only pathogenic and likely pathogenic variants were reported. 6820 patients were analyzed with genotyping analysis. 15758 matching analyses were performed for couples and gamete donors. The study has been conducted between August 2018 and December 2022. Participants/materials, setting, methods DNA was extracted from saliva and blood samples and sequenced. The data obtained were processed by means of computer tools. The carrier frequency (CFR) was obtained from the full sequencing analyses. The observed CFRs was compared with the expected CFRs obtained from databases and literature.To define its similarity a range of +-25% was accepted as similar CFR. For matching analyses, high at-risk couples were divided for autosomal recessive diseases(both carriers) and X-linked diseases (female carriers). Main results and the role of chance For the 301 genes analyzed, 34%(103) had a similar CF than the expected one and, more importantly, 65%(198) showed different CFR. In some cases this difference is due to the lack of complete information on the CFR on bibliography and databases like the CFR associated a diseases with more than one gene associated or genes related with more than one disease, some of which with low clinical implications, usually underdiagnosed. One of the genes on which the CFR was not similar to the expected was SMN1. For this well-known gene, related to spinal muscular atrophy, the CFR was higher than expected, probably due to the analysis of the variants c.*3 + 80T>G(p.?),c.*211_*212del(p.?) that indicate a higher risk of 0 + 2 configuration. The patients with these variants and 2 SMN1-exon8 copies are at higher risk to be silent carriers, but they may not be carriers. For the 15758 performed, if one or both patients were analyzed by genotyping analysis, 3,6% (432/12055 matchings) identified had high risk of affected offspring for autosomal or X-Linked recessive diseases. When both patients were analyzed by sequencing, 6% (223/3703 matchings) were identified at high risk of affected offspring of the diseases analyzed allowing a higher identification of couples at risk. Limitations, reasons for caution The analysis was performed on 301 genes, in order to have a better understanding of CFR for panel designs or patients genetic counseling, a larger cohort of genes should be taken into account, these results show the importance of complete analysis to assess the carrier risks. Wider implications of the findings It is important to have wider genetic databases for CFR but also for variant pathogenicity in order to have better results on CFR analyses and panel designs, in order to provide proper genetic counseling to patients looking to improve the chances of healthy offspring. Trial registration number Not applicable