Will variants of uncertain significance still exist in 2030?

Genetics of Familial Hemophagocytic Lymphohistiocytosis (HLH)

Familial hemophagocytic lymphohistiocytosis (fHLH) represents a group of rare, inherited immune system disorders characterized by uncontrolled inflammatory responses. fHLH results from genetic mutations that impair CD8 T cell and natural killer cell cytotoxicity. Without treatment, fHLH is commonly fatal, but early diagnosis and treatment, including immunosuppressive therapy, and in many cases, an allogeneic hematopoietic stem cell transplant (HSCT), can improve overall outcomes. Genetic testing is critical for confirming the diagnosis, identifying specific gene mutations, assessing family members for carrier status or disease risk, and informing donor selection for HSCT.

Variants of uncertain significance: At the crux of diagnostic odyssey

The variants of uncertain significance (VUS) have caught an immense interest ever since the next-generation sequencing (NGS) capture technologies spanned beyond the vast majority of inferring disease-causing mutations. On the other hand, as genetic variation is best seen in non-coding regions, interpreting the mutations at exon-intron boundaries with large numbers of VUS has gained significance. This allows VUS more interesting and augurs well for pathogenicity even as non-synonymous mutations effectively are to be included among those swaths of genomic variant pool. In this perspective, we provide how VUSs serve as an interface and crux of the diagnostic odyssey.

Reclassification of variants of uncertain significance in neonatal genetic diseases: implications from a clinician's perspective

Although whole-exome sequencing (WES) is now widely used to diagnose neonatal genetic diseases, the genetic causes in over half of the cases remain unresolved, primarily due to variants of uncertain significance (VUS). Therefore, reclassifying VUS may be an effective strategy to improve WES's diagnostic yield. However, not all reclassification approaches are suitable for clinicians. Patients in the neonatal unit of Hebei Provincial Children's Hospital who underwent WES for suspected genetic diseases and demonstrated VUS were re-evaluated from January 2019 to December 2023 using user-friendly methods. A total of 676 individuals were tested, with 101 phenotype-associated VUS identified in 82 patients. Thirty (29.7%) VUS classifications were changed: 24 were upgraded to likely pathogenic or pathogenic, and 6 were downgraded to likely benign. VUS reclassification clarified the molecular diagnosis in 19 cases, increasing the WES diagnostic rate from 30.2% to 33.0%. Computational prediction contributed the most to reclassification, whereas clinical phenotype-related evidence was also particularly significant in upgrading variants. Moreover, phenotype-associated VUS with a score of ≥3 points are more likely to be classified as likely pathogenic or pathogenic, thus requiring more attention. This study provides a practical reference for clinicians in managing VUS reclassification.

Big data and transformative bioinformatics in genomic diagnostics and beyond

The current era of high-throughput analysis-driven research offers invaluable insights into disease etiologies, accurate diagnostics, pathogenesis, and personalized therapy. In the field of movement disorders, investigators are facing an increasing growth in the volume of produced patient-derived datasets, providing substantial opportunities for precision medicine approaches based on extensive information accessibility and advanced annotation practices. Integrating data from multiple sources, including phenomics, genomics, and multi-omics, is crucial for comprehensively understanding different types of movement disorders. Here, we explore formats and analytics of big data generated for patients with movement disorders, including strategies to meaningfully share the data for optimized patient benefit. We review computational methods that are essential to accelerate the process of evaluating the increasing amounts of specialized data collected. Based on concrete examples, we highlight how bioinformatic approaches facilitate the translation of multidimensional biological information into clinically relevant knowledge. Moreover, we outline the feasibility of computer-aided therapeutic target evaluation, and we discuss the importance of expanding the focus of big data research to understudied phenotypes such as dystonia.

Effectiveness and Impact of Transcript Analysis in Clinical Genetics Daily Practice

Broad-spectrum genetic tests often lead to the identification of variants of uncertain significance (VUS), a major issue in modern clinical genetics. A fair proportion of VUS may alter the splicing processes, but their interpretation is challenging. This study aimed at providing a classification approach for VUS potentially-affecting splicing by integrating transcript analysis from peripheral blood mRNA into routine diagnostics. VUS in DICER1, MSH2, MLH1, DYNC1H1, RPS6KA3, and SCN9A, found in patients with phenotypes compatible with the related syndromes, altered splicing, leading to their re-classification as Pathogenic/Likely Pathogenic. This had a significant clinical impact for different diseases, from hereditary tumor predisposition to neurological and congenital syndromic disorders. Transcript analysis is valuable in VUS clinical evaluation, and its incorporation into routine diagnostic workflows facilitates timely and accurate clinical decision-making.

Further delineation of the SCAF4-associated neurodevelopmental disorder

While mostly de novo truncating variants in SCAF4 were recently identified in 18 individuals with variable neurodevelopmental phenotypes, knowledge on the molecular and clinical spectrum is still limited. We assembled data on 50 novel individuals with SCAF4 variants ascertained via GeneMatcher and personal communication. With detailed evaluation of clinical data, in silico predictions and structural modeling, we further characterized the molecular and clinical spectrum of the autosomal dominant SCAF4-associated neurodevelopmental disorder. The molecular spectrum comprises 25 truncating, eight splice-site and five missense variants. While all other truncating variants were classified as pathogenic/likely pathogenic, significance of one C-terminal truncating variant, one splice-site variant and the missense variants remained unclear. Three missense variants in the CTD-interacting domain of SCAF4 were predicted to destabilize the domain. Twenty-three variants occurred de novo, and variants were inherited in 13 cases. Frequent clinical findings were mild developmental delay with speech impairment, seizures, and skeletal abnormalities such as clubfoot, scoliosis or hip dysplasia. Cognitive abilities ranged from normal IQ to severe intellectual disability (ID), with borderline to mild ID in the majority of individuals. Our study confirms the role of SCAF4 variants in neurodevelopmental disorders and further delineates the associated clinical phenotype.

Systematic use of protein free energy changes for classifying variants of uncertain significance: the case of IFT140 in Mainzer-Saldino Syndrome

Introduction

Advanced genetic strategies have transformed our understanding of the genetic basis and diagnosis of many phenotypes, including rare diseases. However, missense variants (MVs) are frequently identified and often classified as variants of uncertain significance (VUS). Although changes in protein free energy (ΔΔG) were recently proposed as a tool for VUS classification, no objective cut-offs exist to distinguish between benign and pathogenic variants.

Methods

We utilized the computational tool mCSM to calculate ΔΔG and predict the impact of MVs on protein stability. Specifically, we systematically analyzed the ΔΔG of MVs in IFT140 to identify those potentially pathogenic and associated with Mainzer-Saldino syndrome (MSS). To this end, we evaluated ΔΔG in IFT140 MVs sourced from ClinVar, gnomAD, and MSS patients, aiming to resolve the diagnosis of MSS in a child with a novel homozygous IFT140 variant, initially reported as a VUS.

Results

IFT140 MVs from MSS patients showed lower ΔΔG values than those reported in gnomAD individuals (-1.389 vs. -0.681 kcal/mol; p = 0.0031). A ROC curve demonstrated strong discriminative ability (AUC = 0.8488; p = 0.0002), and a ΔΔG cut-off of -1.3 kcal/mol achieving 50% sensibility and 90% specificity. The analysis of ClinVar IFT140 variants classified as VUS, showed that 75/323 (23%) presented ΔΔG values below the cut-off. In the child clinically suspicious of MSS, this cut-off allowed the reclassification of the VUS (IFT140:p.W80C; ΔΔG = -1.745 kcal/mol) as likely pathogenic, which confirmed the diagnosis molecularly.

Conclusion

Our findings demonstrate that ΔΔG analysis can effectively distinguish potentially pathogenic variants in IFT140, enabling confirmation of MSS. The established cut-off of -1.3 kcal/mol showed strong discriminative power, aiding in the reclassification of VUS identified in IFT140. This approach highlights the utility of protein stability predictions in resolving diagnostic uncertainty in rare diseases.

Navigating variants of uncertain significance in genetic dyslipidemia: how to assess and counsel patients

PURPOSE OF REVIEW

Genetic testing has become an integral component of clinical care when an inherited condition is suspected. However, the interpretation of variants identified with this testing can be nuanced. Variants of uncertain significance (VUS) are variants for which there is not enough data currently available to determine if the variant is causal for disease (i.e. pathogenic) or is benign. VUS can exist on a spectrum with some leaning towards suspected pathogenicity and others leaning towards likely benign. Clinician understanding of variant interpretation can improve clinical care by providing more context around how suspicious a VUS is, determining whether additional steps should be taken to further evaluate the variant in question, and ensuring patient understanding of these results.

RECENT FINDINGS

Research on this topic highlights the complexities around VUS interpretation and counseling. VUS are not static: interpretations of pathogenicity change as new information is uncovered.

SUMMARY

This review aims to summarize this literature and provide insight into variant interpretation, practical steps clinicians can take to further assess a VUS, and considerations when counseling patients on these results.

Predicting the structure-altering mechanisms of disease variants

Missense variants can affect the severity of disease, choice of treatment, and treatment outcomes. While the number of known variants has been increasing at a rapid pace, available evidence of their clinical effect has been lagging behind, constituting a challenge for clinicians and researchers. Multiplexed assays of variant effects (MAVEs) are important to close the gap; nonetheless, computational predictions of pathogenicity are still often the only available data for scoring variants. Such methods are not designed to provide a mechanistic explanation for the effect of amino acid substitutions. To this purpose, we propose structure-based frameworks as ensemble methodologies, with each method tailored to predict a different aspect among those exerted by amino acid substitutions to link predicted pathogenicity to mechanistic indicators. We review available frameworks, as well as advancements in underlying structure-based methods that predict variant effects on several protein features, such as protein stability, biomolecular interactions, allostery, post-translational modifications, and more.

Reassessing the role of the p.(Arg304Gln) missense AIP variant in pituitary tumorigenesis

OBJECTIVE

Heterozygous germline loss-of-function variants in AIP are associated with young-onset growth hormone and/or prolactin-secreting pituitary tumours. However, the pathogenic role of the c.911G > A; p.(Arg304Gln) (R304Q) AIP variant has been controversial. Recent data from public exome/genome databases show this variant is not infrequent. The objective of this work was to reassess the pathogenicity of R304Q based on clinical, genomic, and functional assay data.

DESIGN

Data were collected on published R304Q pituitary neuroendocrine tumour cases and from International Familial Isolated Pituitary Adenoma Consortium R304Q cases (n = 38, R304Q cohort). Clinical features, population cohort frequency, computational analyses, prediction models, presence of loss-of-heterozygosity, and in vitro/in vivo functional studies were assessed and compared with data from pathogenic/likely pathogenic AIP variant patients (AIPmut cohort, n = 184).

RESULTS

Of 38 R304Q patients, 61% (23/38) had growth hormone excess, in contrast to 80% of AIPmut cohort (147/184, P < .001). R304Q cohort was older at disease onset and diagnosis than the AIPmut cohort (median [quartiles] onset: 25 y [16-35] vs 16 y [14-23], P < .001; median [quartiles] diagnosis: 36 y [24-44] vs 21 y [15-29], P < .001). R304Q is present in gnomADv2.1 (0.31%) and UK Biobank (0.16%), including three persons with homozygous R304Q. No loss-of-heterozygosity was detected in four R304Q pituitary neuroendocrine tumour samples. In silico predictions and experimental data were conflicting.

CONCLUSIONS

Evidence suggests that R304Q is not pathogenic for pituitary neuroendocrine tumour. We recommend changing this variant classification to likely benign and do not recommend pre-symptomatic genetic testing of family members or follow-up of already identified unaffected individuals with the R304Q variant.

Identification and Characterization of Novel FSHR Copy Number Variations Causing Premature Ovarian Insufficiency

Follicle stimulating hormone (FSH) is a key pituitary gonadotropic hormone implicated in human fertility and is crucial for folliculogenesis and recruitment of new antral follicles. Variations in its receptor, FSHR, can lead to diverse reproductive phenotypes including ovarian hyperstimulation syndrome (OHSS) and premature ovarian insufficiency (POI). This study reports a novel case of FSHR-related ovarian insufficiency in a patient with primary amenorrhea, subnormal AMH levels, and delayed puberty. Genetic exploration revealed two compound heterozygous intragenic deletions of FSHR. Specifically, the patient inherited a maternally derived deletion spanning exons 5-10 and a paternally derived deletion involving exons 3-6. Through chromosomal microarray analysis (CMA), exome sequencing, long-range PCR, and Sanger sequencing, we characterized the breakpoints and confirmed the compound heterozygous deletions. The findings reveal a complete loss of function of both FSHR alleles, contributing to the patient's POI phenotype. This case emphasizes the complexity of genotype-phenotype correlations in FSHR-related disorders and the role of CNVs in POI phenotypes. Although these events are rare, our results advocate for the inclusion of CNV detection in the diagnostic workup of POI to ensure accurate diagnosis and better patient management.

Calibrated Functional Data Decreases Clinical Uncertainty for Tier 1 Monogenic Disease: Application to Long QT Syndrome

Rare missense variants are often classified as variants of uncertain significance (VUS) due to insufficient evidence for classification. These ambiguous findings create anxiety and frequently lead to inappropriate workup, colloquially referred to as the 'diagnostic odyssey'. Well-validated high-throughput experimental data have the potential to significantly reduce the number of VUS identified by clinical genetic testing, though the extent of this reduction and the optimal strategies to achieve it remain unclear.1.

A guide to gene-disease relationships in nephrology

The use of next-generation sequencing technologies such as exome and genome sequencing in research and clinical care has transformed our understanding of the molecular architecture of genetic kidney diseases. Although the capability to identify and rigorously assess genetic variants and their relationship to disease has advanced considerably in the past decade, the curation of clinically relevant relationships between genes and specific phenotypes has received less attention, despite it underpinning accurate interpretation of genomic tests. Here, we discuss the need to accurately define gene-disease relationships in nephrology and provide a framework for appraising genetic and experimental evidence critically. We describe existing international programmes that provide expert curation of gene-disease relationships and discuss sources of discrepancy as well as efforts at harmonization. Further, we highlight the need for alignment of disease and phenotype terminology to ensure robust and reproducible curation of knowledge. These collective efforts to support evidence-based translation of genomic sequencing into practice across clinical, diagnostic and research settings are crucial for delivering the promise of precision medicine in nephrology, providing more patients with timely diagnoses, accurate prognostic information and access to targeted treatments.

MaveDB 2024: a curated community database with over seven million variant effects from multiplexed functional assays

Multiplexed assays of variant effect (MAVEs) are a critical tool for researchers and clinicians to understand genetic variants. Here we describe the 2024 update to MaveDB ( https://www.mavedb.org/ ) with four key improvements to the MAVE community's database of record: more available data including over 7 million variant effect measurements, an improved data model supporting assays such as saturation genome editing, new built-in exploration and visualization tools, and powerful APIs for data federation and streamlined submission and access. Together these changes support MaveDB's role as a hub for the analysis and dissemination of MAVEs now and into the future.

Ensemble and consensus approaches to prediction of recessive inheritance for missense variants in human disease

Mode of inheritance (MOI) is necessary for clinical interpretation of pathogenic variants; however, the majority of variants lack this information. Furthermore, variant effect predictors are fundamentally insensitive to recessive-acting diseases. Here, we present MOI-Pred, a variant pathogenicity prediction tool that accounts for MOI, and ConMOI, a consensus method that integrates variant MOI predictions from three independent tools. MOI-Pred integrates evolutionary and functional annotations to produce variant-level predictions that are sensitive to both dominant-acting and recessive-acting pathogenic variants. Both MOI-Pred and ConMOI show state-of-the-art performance on standard benchmarks. Importantly, dominant and recessive predictions from both tools are enriched in individuals with pathogenic variants for dominant- and recessive-acting diseases, respectively, in a real-world electronic health record (EHR)-based validation approach of 29,981 individuals. ConMOI outperforms its component methods in benchmarking and validation, demonstrating the value of consensus among multiple prediction methods. Predictions for all possible missense variants are provided in the "Data and code availability" section.

Comprehensive evaluation of AlphaMissense predictions by evidence quantification for variants of uncertain significance

Accurate variant classification is critical for genetic diagnosis. Variants without clear classification, known as "variants of uncertain significance" (VUS), pose a significant diagnostic challenge. This study examines AlphaMissense performance in variant classification, specifically for VUS. A systematic comparison between AlphaMissense predictions and predictions based on curated evidence according to the ACMG/AMP classification guidelines was conducted for 5845 missense variants in 59 genes associated with representative Mendelian disorders. A framework for quantifying and modeling VUS pathogenicity was used to facilitate comparison. Manual reviewing classified 5845 variants as 4085 VUS, 1576 pathogenic/likely pathogenic, and 184 benign/likely benign. Pathogenicity predictions based on AlphaMissense and ACMG guidelines were concordant for 1887 variants (1352 pathogenic, 132 benign, and 403 VUS/ambiguous). The sensitivity and specificity of AlphaMissense predictions for pathogenicity were 92% and 78%. Moreover, the quantification of VUS evidence and heatmaps weakly correlated with the AlphaMissense score. For VUS without computational evidence, incorporating AlphaMissense changed the VUS quantification for 878 variants, while 56 were reclassified as likely pathogenic. When AlphaMissense replaced existing computational evidence for all VUS, 1709 variants changed quantified criteria while 63 were reclassified as likely pathogenic. Our research suggests that the augmentation of AlphaMissense with empirical evidence may improve performance by incorporating a quantitative framework to aid in VUS classification.

There will always be variants of uncertain significance. Analysis of VUSs

The ACMG/AMP guidelines include five categories of which variants of uncertain significance (VUSs) have received increasing attention. Recently, Fowler and Rehm claimed that all or most VUSs could be reclassified as pathogenic or benign within few years. To test this claim, we collected validated benign, pathogenic, VUS and conflicting variants from ClinVar and LOVD and investigated differences at gene, protein, structure, and variant levels. The gene and protein features included inheritance patterns, actionability, functional categories for housekeeping, essential, complete knockout, lethality and haploinsufficient proteins, Gene Ontology annotations, and protein network properties. Structural properties included the location at secondary structural elements, intrinsically disordered regions, transmembrane regions, repeats, conservation, and accessibility. Gene features were distributions of nucleotides, their groupings, codons, and location to CpG islands. The distributions of amino acids and their groups were investigated. VUSs did not markedly differ from other variants. The only major differences were the accessibility and conservation of pathogenic variants, and reduced ratio of repeat-locating variants in VUSs. Thus, all VUSs cannot be distinguished from other types of variants. They display one form of natural biological heterogeneity. Instead of concentrating on eradicating VUSs, the community would benefit from investigating and understanding factors that contribute to phenotypic heterogeneity.

A Novel GBF1 Variant in a Charcot-Marie-Tooth Type 2: Insights from Familial Analysis

BACKGROUND/OBJECTIVES

Axonal Charcot-Marie-Tooth disease type 2 (CMT2) accounts for 24% of Hereditary Motor/Sensory Peripheral Neuropathies. CMT2 type GG, due to four distinct heterozygous mutations in the Golgi brefeldin A resistant guanine nucleotide exchange factor 1 (GBF1) gene (OMIM 606483), was described in seven cases from four unrelated families with autosomal dominant inheritance. It is characterized by slowly progressive distal muscle weakness and atrophy, primarily affecting the lower limbs. Here, we present two siblings sharing a novel GBF1 variant.

METHODS

Patient II.1 (male, 61 years at onset) presented lower limb hypoesthesia and walking difficulty; the examination revealed a postural tremor, a positive Romberg test, and muscle atrophy in the lower limbs and hands. Patient II.2 (his sister, 59 years at onset) had lower limb dysesthesias, hand paresthesia, and lower-limb stiffness. They underwent clinical evaluations, blood tests, and electroneurography. Their father represents a potentially affected individual, although a genetic analysis was not conducted.

RESULTS

All tests for peripheral neuropathies were unremarkable, including metabolic and autoimmune screening. Both showed a mixed demyelinating-axonal sensory-motor neuropathy. Genetic analysis revealed a new heterozygous GBF1 variant of uncertain significance.

CONCLUSIONS

Based on autosomal dominant inheritance, as well as clinical and physiological features, a possible novel CMT2GG was diagnosed. Further research, including functional assays and in vitro studies, is necessary to confirm this variant's causal link.

Genomic resources, opportunities, and prospects for accelerated improvement of millets

KEY MESSAGE

Genomic resources, alongside the tools and expertise required to leverage them, are essential for the effective improvement of globally significant millet crop species. Millets are essential for global food security and nutrition, particularly in sub-Saharan Africa and South Asia. They are crucial in promoting nutrition, climate resilience, economic development, and cultural heritage. Despite their critical role, millets have historically received less investment in developing genomic resources than major cereals like wheat, maize, and rice. However, recent advancements in genomics, particularly next-generation sequencing technologies, offer unprecedented opportunities for rapid improvement in millet crops. This review paper provides an overview of the status of genomic resources in millets and in harnessing the recent opportunities in artificial intelligence to address challenges in millet crop improvement to boost productivity, nutrition, and end quality. It emphasizes the significance of genomics in tackling global food security issues and underscores the necessity for innovative breeding strategies to translate genomics and AI into effective breeding strategies for millets.

Clinical Variant Reclassification in Hereditary Disease Genetic Testing

Importance

Because accurate and consistent classification of DNA sequence variants is fundamental to germline genetic testing, understanding patterns of initial variant classification (VC) and subsequent reclassification from large-scale, empirical data can help improve VC methods, promote equity among race, ethnicity, and ancestry (REA) groups, and provide insights to inform clinical practice.

Objectives

To measure the degree to which initial VCs met certainty thresholds set by professional guidelines and quantify the rates of, the factors associated with, and the impact of reclassification among more than 2 million variants.

Design, Setting, and Participants

This cohort study used clinical multigene panel and exome sequencing data from diagnostic testing for hereditary disorders, carrier screening, or preventive genetic screening from individuals for whom genetic testing was performed between January 1, 2015, and June 30, 2023.

Exposure

DNA variants were classified into 1 of 5 categories: benign, likely benign, variant of uncertain significance (VUS), likely pathogenic, or pathogenic.

Main Outcomes and Measures

The main outcomes were accuracy of classifications, rates and directions of reclassifications, evidence contributing to reclassifications, and their impact across different clinical areas and REA groups. One-way analysis of variance followed by post hoc pairwise Tukey honest significant difference tests were used to analyze differences among means, and pairwise Pearson χ2 tests with Bonferroni corrections were used to compare categorical variables among groups.

Results

The cohort comprised 3 272 035 individuals (median [range] age, 44 [0-89] years; 2 240 506 female [68.47%] and 1 030 729 male [31.50%]; 216 752 Black [6.62%]; 336 414 Hispanic [10.28%]; 1 804 273 White [55.14%]). Among 2 051 736 variants observed over 8 years in this cohort, 94 453 (4.60%) were reclassified. Some variants were reclassified more than once, resulting in 105 172 total reclassification events. The majority (64 752 events [61.65%]) were changes from VUS to either likely benign, benign, likely pathogenic, or pathogenic categories. An additional 37.66% of reclassifications (39 608 events) were gains in classification certainty to terminal categories (ie, likely benign to benign and likely pathogenic to pathogenic). Only a small fraction (663 events [0.63%]) moved toward less certainty, or very rarely (61 events [0.06%]) were classification reversals. When normalized by the number of individuals tested, VUS reclassification rates were higher among specific underrepresented REA populations (Ashkenazi Jewish, Asian, Black, Hispanic, Pacific Islander, and Sephardic Jewish). Approximately one-half of VUS reclassifications (37 074 of 64 840 events [57.18%]) resulted from improved use of data from computational modeling.

Conclusions and Relevance

In this cohort study of individuals undergoing genetic testing, the empirically estimated accuracy of pathogenic, likely pathogenic, benign, and likely benign classifications exceeded the certainty thresholds set by current VC guidelines, suggesting the need to reevaluate definitions of these classifications. The relative contribution of various strategies to resolve VUS, including emerging machine learning-based computational methods, RNA analysis, and cascade family testing, provides useful insights that can be applied toward further improving VC methods, reducing the rate of VUS, and generating more definitive results for patients.

Generating Cytokines and Growth Factors for Functional Activity: Feasibility of Method Using MIF Protein

Cytokines and growth factors are signaling molecules that regulate a variety of biological processes. Understanding their role is essential for basic research and clinical utilization. Thus, cytokines and growth factors are widely used throughout research labs in a significant number of applications. Additionally, genetic polymorphisms result in variant forms of cytokines and growth factors, which can alter their function. Becoming more common, researchers will need to generate these important proteins and their variants themselves in functional forms for activity studies. The expression systems used to generate these proteins can have a major impact on their function. In some instances, post-translational modifications are needed to produce a functionally active protein, which can only be conducted using eukaryotic expression systems. Ideally, for functional relevance, a human expression system should be used for human-related research and applications. Most human cell-based expression systems primarily use HEK (Human Embryonic Kidney) cells; however, relying on just one cell type can lead to several issues, considering the variety of proteins derived from various cell sources. Here, we provide a protocol to effectively and efficiently generate functional recombinant proteins, taking into consideration the diverse range of proteins from different cell types throughout the human body.

Genetic testing in early-onset atrial fibrillation

Atrial fibrillation (AF) is a globally prevalent cardiac arrhythmia with significant genetic underpinnings, as highlighted by recent large-scale genetic studies. A prominent clinical and genetic overlap exists between AF, heritable ventricular cardiomyopathies, and arrhythmia syndromes, underlining the potential of AF as an early indicator of severe ventricular disease in younger individuals. Indeed, several recent studies have demonstrated meaningful yields of rare pathogenic variants among early-onset AF patients (∼4%-11%), most notably for cardiomyopathy genes in which rare variants are considered clinically actionable. Genetic testing thus presents a promising opportunity to identify monogenetic defects linked to AF and inherited cardiac conditions, such as cardiomyopathy, and may contribute to prognosis and management in early-onset AF patients. A first step towards recognizing this monogenic contribution was taken with the Class IIb recommendation for genetic testing in AF patients aged 45 years or younger by the 2023 American College of Cardiology/American Heart Association guidelines for AF. By identifying pathogenic genetic variants known to underlie inherited cardiomyopathies and arrhythmia syndromes, a personalized care pathway can be developed, encompassing more tailored screening, cascade testing, and potentially genotype-informed prognosis and preventive measures. However, this can only be ensured by frameworks that are developed and supported by all stakeholders. Ambiguity in test results such as variants of uncertain significance remain a major challenge and as many as ∼60% of people with early-onset AF might carry such variants. Patient education (including pretest counselling), training of genetic teams, selection of high-confidence genes, and careful reporting are strategies to mitigate this. Further challenges to implementation include financial barriers, insurability issues, workforce limitations, and the need for standardized definitions in a fast-moving field. Moreover, the prevailing genetic evidence largely rests on European descent populations, underscoring the need for diverse research cohorts and international collaboration. Embracing these challenges and the potential of genetic testing may improve AF care. However, further research-mechanistic, translational, and clinical-is urgently needed.

Preconception carrier screening and preimplantation genetic testing in the infertility management

BACKGROUND

Genetic testing serves as a valuable element of reproductive care, applicable at various stages of the reproductive journey: (i) before pregnancy, when a couple's genetic reproductive risk can be evaluated; (ii) before embryo implantation, as part of in vitro fertilization (IVF) treatment, to ascertain several inherited or de novo genetic/chromosomal diseases of the embryo before transfer; (iii) during the prenatal period, to assess the genetic costitution of the fetus. Preconception carrier screening (CS) is a genetic test typically performed on couples planning a pregnancy. The primary purpose of CS is to identify couples at-risk of conceiving a child affected by a severe genetic disorder with autosomal recessive or X-linked inheritance. Detection of high reproductive risk through CS allows prospective parents to be informed of their predisposition and improve reproductive decision-making. These include undergoing IVF with preimplantation genetic testing (PGT) or donor gametes, prenatal diagnosis, adoption, remaining childless, taking no actions. Both the presence of the affected gene (PGT-M) and chromosomal status (PGT-A) of the embryo can be comprehensively assessed through modern approaches.

OBJECTIVES

We provide a review of CS and PGT applications to equip healthcare providers with up-to-date information regarding their opportunities and complexities.

RESULTS AND DISCUSSION

The use of CS and PGT is currently considered the most effective intervention for avoiding both an affected pregnancy whilst using autologous gametes in couples with known increased risk, and chromosomal abnormalities. As our understanding in the genetic component in pathological conditions increases, the number of tested disorders will expand, offering a more thorough assessment of one's genetic inheritance. Nevertheless, implementation and development in this field must be accompanied by scientific and ethical considerations to ensure this approach serves the best long-term interests of individuals and society, promoting justice and autonomy and preserving parenthood and the healthcare system.

CONCLUSION

The combination of CS and PGT aligns with principles of personalized medicine by offering reproductive care tailored to the individual's genetic makeup.

Functional characterization of 2,832 JAG1 variants supports reclassification for Alagille syndrome and improves guidance for clinical variant interpretation

Pathogenic variants in the JAG1 gene are a primary cause of the multi-system disorder Alagille syndrome. Although variant detection rates are high for this disease, there is uncertainty associated with the classification of missense variants that leads to reduced diagnostic yield. Consequently, up to 85% of reported JAG1 missense variants have uncertain or conflicting classifications. We generated a library of 2,832 JAG1 nucleotide variants within exons 1-7, a region with a high number of reported missense variants, and designed a high-throughput assay to measure JAG1 membrane expression, a requirement for normal function. After calibration using a set of 175 known or predicted pathogenic and benign variants included within the variant library, 486 variants were characterized as functionally abnormal (n = 277 abnormal and n = 209 likely abnormal), of which 439 (90.3%) were missense. We identified divergent membrane expression occurring at specific residues, indicating that loss of the wild-type residue itself does not drive pathogenicity, a finding supported by structural modeling data and with broad implications for clinical variant classification both for Alagille syndrome and globally across other disease genes. Of 144 uncertain variants reported in patients undergoing clinical or research testing, 27 had functionally abnormal membrane expression, and inclusion of our data resulted in the reclassification of 26 to likely pathogenic. Functional evidence augments the classification of genomic variants, reducing uncertainty and improving diagnostics. Inclusion of this repository of functional evidence during JAG1 variant reclassification will significantly affect resolution of variant pathogenicity, making a critical impact on the molecular diagnosis of Alagille syndrome.

Scalable approaches for generating, validating and incorporating data from high-throughput functional assays to improve clinical variant classification

As the adoption and scope of genetic testing continue to expand, interpreting the clinical significance of DNA sequence variants at scale remains a formidable challenge, with a high proportion classified as variants of uncertain significance (VUSs). Genetic testing laboratories have historically relied, in part, on functional data from academic literature to support variant classification. High-throughput functional assays or multiplex assays of variant effect (MAVEs), designed to assess the effects of DNA variants on protein stability and function, represent an important and increasingly available source of evidence for variant classification, but their potential is just beginning to be realized in clinical lab settings. Here, we describe a framework for generating, validating and incorporating data from MAVEs into a semi-quantitative variant classification method applied to clinical genetic testing. Using single-cell gene expression measurements, cellular evidence models were built to assess the effects of DNA variation in 44 genes of clinical interest. This framework was also applied to models for an additional 22 genes with previously published MAVE datasets. In total, modeling data was incorporated from 24 genes into our variant classification method. These data contributed evidence for classifying 4043 observed variants in over 57,000 individuals. Genetic testing laboratories are uniquely positioned to generate, analyze, validate, and incorporate evidence from high-throughput functional data and ultimately enable the use of these data to provide definitive clinical variant classifications for more patients.

Discovering mechanisms of human genetic variation and controlling cell states at scale

Population-scale sequencing efforts have catalogued substantial genetic variation in humans such that variant discovery dramatically outpaces interpretation. We discuss how single-cell sequencing is poised to reveal genetic mechanisms at a rate that may soon approach that of variant discovery. The functional genomics toolkit is sufficiently modular to systematically profile almost any type of variation within increasingly diverse contexts and with molecularly comprehensive and unbiased readouts. As a result, we can construct deep phenotypic atlases of variant effects that span the entire regulatory cascade. The same conceptual approach to interpreting genetic variation should be applied to engineering therapeutic cell states. In this way, variant mechanism discovery and cell state engineering will become reciprocating and iterative processes towards genomic medicine.

Genetic diagnosis in acromegaly and gigantism: From research to clinical practice

It is usually considered that only 5% of all pituitary neuroendocrine tumours are due to inheritable causes. Since this estimate was reported, however, multiple genetic defects driving syndromic and nonsyndromic somatotrophinomas have been unveiled. This heterogeneous genetic background results in overlapping phenotypes of GH excess. Genetic tests should be part of the approach to patients with acromegaly and gigantism because they can refine the clinical diagnoses, opening the possibility to tailor the clinical conduct to each patient. Even more, genetic testing and clinical screening of at-risk individuals have a positive impact on disease outcomes, by allowing for the timely detection and treatment of somatotrophinomas at early stages. Future research should focus on determining the actual frequency of novel genetic drivers of somatotrophinomas in the general population, developing up-to-date disease-specific multi-gene panels for clinical use, and finding strategies to improve access to modern genetic testing worldwide.

Current genetic diagnostics in inborn errors of immunity

New technologies in genetic diagnostics have revolutionized the understanding and management of rare diseases. This review highlights the significant advances and latest developments in genetic diagnostics in inborn errors of immunity (IEI), which encompass a diverse group of disorders characterized by defects in the immune system, leading to increased susceptibility to infections, autoimmunity, autoinflammatory diseases, allergies, and malignancies. Various diagnostic approaches, including targeted gene sequencing panels, whole exome sequencing, whole genome sequencing, RNA sequencing, or proteomics, have enabled the identification of causative genetic variants of rare diseases. These technologies not only facilitated the accurate diagnosis of IEI but also provided valuable insights into the underlying molecular mechanisms. Emerging technologies, currently mainly used in research, such as optical genome mapping, single cell sequencing or the application of artificial intelligence will allow even more insights in the aetiology of hereditary immune defects in the near future. The integration of genetic diagnostics into clinical practice significantly impacts patient care. Genetic testing enables early diagnosis, facilitating timely interventions and personalized treatment strategies. Additionally, establishing a genetic diagnosis is necessary for genetic counselling and prognostic assessments. Identifying specific genetic variants associated with inborn errors of immunity also paved the way for the development of targeted therapies and novel therapeutic approaches. This review emphasizes the challenges related with genetic diagnosis of rare diseases and provides future directions, specifically focusing on IEI. Despite the tremendous progress achieved over the last years, several obstacles remain or have become even more important due to the increasing amount of genetic data produced for each patient. This includes, first and foremost, the interpretation of variants of unknown significance (VUS) in known IEI genes and of variants in genes of unknown significance (GUS). Although genetic diagnostics have significantly contributed to the understanding and management of IEI and other rare diseases, further research, exchange between experts from different clinical disciplines, data integration and the establishment of comprehensive guidelines are crucial to tackle the remaining challenges and maximize the potential of genetic diagnostics in the field of rare diseases, such as IEI.

Past as Prologue: Predicting Potential Psychosocial-Ethical Burdens of Positive Newborn Screens as Conditions Propagate

We look to the past as prologue for guidance in predicting and circumventing potential psychosocial-ethical challenges, including those that may influence the attachment process for some parents. We consider the evolution of bioethics and developmental psychology as they intersect with newborn screening while exploring potential implications of positive findings, be they false positives, true positives, or secondary as well as incidental findings. We reflect on navigating the complex landscape that may be significantly impacted by variable phenotypes, the age of onset, and uncertain prognoses, mindful of the diagnostic odyssey continuum. We explore select facets of ethical and psychological challenges encountered with positive newborn screening findings by highlighting enduring debates to improve the policy process in public health and medicine. We believe substantive empirical research is needed, including long-term follow-up, routine prenatal assessment of tolerance for uncertainties, and especially innovative methodologies to better evaluate potential psychological distress that may be present in some at-risk individuals during the perinatal period preceding and following reports of positive findings. Mitigation strategies building on lessons learned from NBS and clinical follow-up should be implemented and studied. We conclude by pondering why we remain far afield from providing these services. Research directed towards understanding the implications of positive NBS findings will further reduce the burdens on families and care providers alike and should lead to improved communication.