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.

Calibration of additional computational tools expands ClinGen recommendation options for variant classification with PP3/BP4 criteria.

Purpose: We previously developed an approach to calibrate computational tools for clinical variant classification, updating recommendations for the reliable use of variant impact predictors to provide evidence strength up to Strong. A new generation of tools using distinctive approaches have since been released, and these methods must be independently calibrated for clinical application. Method: Using our local posterior probability-based calibration and our established data set of ClinVar pathogenic and benign variants, we determined the strength of evidence provided by three new tools (AlphaMissense, ESM1b, VARITY) and calibrated scores meeting each evidence strength. Results: All three tools reached the Strong level of evidence for variant pathogenicity and Moderate for benignity, though sometimes for few variants. Compared to previously recommended tools, these yielded at best only modest improvements in the tradeoffs of evidence strength and false positive predictions. Conclusion: At calibrated thresholds, three new computational predictors provided evidence for variant pathogenicity at similar strength to the four previously recommended predictors (and comparable with functional assays for some variants). This calibration broadens the scope of computational tools for application in clinical variant classification. Their new approaches offer promise for future advancement of the field.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations.

PURPOSE: To investigate the number of rare missense variants observed in human genome sequences by ACMG/AMP PP3/BP4 evidence strength, following the ClinGen-calibrated PP3/BP4 computational recommendations. METHODS: Missense variants from the genome sequences of 300 probands from the Rare Genomes Project with suspected rare disease were analyzed using computational prediction tools that were able to reach PP3_Strong and BP4_Moderate evidence strengths (BayesDel, MutPred2, REVEL, and VEST4). The numbers of variants at each evidence strength were analyzed across disease-associated genes and genome-wide. RESULTS: From a median of 75.5 rare (≤1% allele frequency) missense variants in disease-associated genes per proband, a median of one reached PP3_Strong, 3-5 PP3_Moderate, and 3-5 PP3_Supporting. Most were allocated BP4 evidence (median 41-49 per proband) or were indeterminate (median 17.5-19 per proband). Extending the analysis to all protein-coding genes genome-wide, the number of variants reaching PP3_Strong score thresholds increased approximately 2.6-fold compared with disease-associated genes, with a median per proband of 1-3 PP3_Strong, 8-16 PP3_Moderate, and 10-17 PP3_Supporting. CONCLUSION: A small number of variants per proband reached PP3_Strong and PP3_Moderate in 3424 disease-associated genes. Although not the intended use of the recommendations, this was also observed genome-wide. Use of PP3/BP4 evidence as recommended from calibrated computational prediction tools in the clinical diagnostic laboratory is unlikely to inappropriately contribute to the classification of an excessive number of variants as pathogenic or likely pathogenic by ACMG/AMP rules.

Assessment of the evidence yield for the calibrated PP3/BP4 computational recommendations.

Purpose: To investigate the number of rare missense variants observed in human genome sequences by ACMG/AMP PP3/BP4 evidence strength, following the calibrated PP3/BP4 computational recommendations. Methods: Missense variants from the genome sequences of 300 probands from the Rare Genomes Project with suspected rare disease were analyzed using computational prediction tools able to reach PP3_Strong and BP4_Moderate evidence strengths (BayesDel, MutPred2, REVEL, and VEST4). The numbers of variants at each evidence strength were analyzed across disease-associated genes and genome-wide. Results: From a median of 75.5 rare (≤1% allele frequency) missense variants in disease-associated genes per proband, a median of one reached PP3_Strong, 3-5 PP3_Moderate, and 3-5 PP3_Supporting. Most were allocated BP4 evidence (median 41-49 per proband) or were indeterminate (median 17.5-19 per proband). Extending the analysis to all protein-coding genes genome-wide, the number of PP3_Strong variants increased approximately 2.6-fold compared to disease-associated genes, with a median per proband of 1-3 PP3_Strong, 8-16 PP3_Moderate, and 10-17 PP3_Supporting. Conclusion: A small number of variants per proband reached PP3_Strong and PP3_Moderate in 3,424 disease-associated genes, and though not the intended use of the recommendations, also genome-wide. Use of PP3/BP4 evidence as recommended from calibrated computational prediction tools in the clinical diagnostic laboratory is unlikely to inappropriately contribute to the classification of an excessive number of variants as Pathogenic or Likely Pathogenic by ACMG/AMP rules.

ClinGen guidance for use of the PP1/BS4 co-segregation and PP4 phenotype specificity criteria for sequence variant pathogenicity classification.

The 2015 American College of Medical Genetics and Genomics and the Association for Molecular Pathology variant classification publication established a standard employed internationally to guide laboratories in variant assessment. Those recommendations included both pathogenic (PP1) and benign (BS4) criteria for evaluating the inheritance patterns of variants, but details of how to apply those criteria at appropriate evidence levels were sparse. Several publications have since attempted to provide additional guidance, but anecdotally, this issue is still challenging. Additionally, it is not clear that those prior efforts fully distinguished disease-gene identification considerations from variant pathogenicity considerations nor did they address autosomal-recessive and X-linked inheritance. Here, we have taken a mixed inductive and deductive approach to this problem using real diseases as examples. We have developed a practical heuristic for genetic co-segregation evidence and have also determined that the specific phenotype criterion (PP4) is inseparably coupled to the co-segregation criterion. We have also determined that negative evidence at one locus constitutes positive evidence for other loci for disorders with locus heterogeneity. Finally, we provide a points-based system for evaluating phenotype and co-segregation as evidence types to support or refute a locus and show how that can be integrated into the Bayesian framework now used for variant classification and consistent with the 2015 guidelines.

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

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

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

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

Genomic autopsy to identify underlying causes of pregnancy loss and perinatal death.

Pregnancy loss and perinatal death are devastating events for families. We assessed 'genomic autopsy' as an adjunct to standard autopsy for 200 families who had experienced fetal or newborn death, providing a definitive or candidate genetic diagnosis in 105 families. Our cohort provides evidence of severe atypical in utero presentations of known genetic disorders and identifies novel phenotypes and disease genes. Inheritance of 42% of definitive diagnoses were either autosomal recessive (30.8%), X-linked recessive (3.8%) or autosomal dominant (excluding de novos, 7.7%), with risk of recurrence in future pregnancies. We report that at least ten families (5%) used their diagnosis for preimplantation (5) or prenatal diagnosis (5) of 12 pregnancies. We emphasize the clinical importance of genomic investigations of pregnancy loss and perinatal death, with short turnaround times for diagnostic reporting and followed by systematic research follow-up investigations. This approach has the potential to enable accurate counseling for future pregnancies.

Calibration of computational tools for missense variant pathogenicity classification and ClinGen recommendations for PP3/BP4 criteria.

Recommendations from the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG/AMP) for interpreting sequence variants specify the use of computational predictors as "supporting" level of evidence for pathogenicity or benignity using criteria PP3 and BP4, respectively. However, score intervals defined by tool developers, and ACMG/AMP recommendations that require the consensus of multiple predictors, lack quantitative support. Previously, we described a probabilistic framework that quantified the strengths of evidence (supporting, moderate, strong, very strong) within ACMG/AMP recommendations. We have extended this framework to computational predictors and introduce a new standard that converts a tool's scores to PP3 and BP4 evidence strengths. Our approach is based on estimating the local positive predictive value and can calibrate any computational tool or other continuous-scale evidence on any variant type. We estimate thresholds (score intervals) corresponding to each strength of evidence for pathogenicity and benignity for thirteen missense variant interpretation tools, using carefully assembled independent data sets. Most tools achieved supporting evidence level for both pathogenic and benign classification using newly established thresholds. Multiple tools reached score thresholds justifying moderate and several reached strong evidence levels. One tool reached very strong evidence level for benign classification on some variants. Based on these findings, we provide recommendations for evidence-based revisions of the PP3 and BP4 ACMG/AMP criteria using individual tools and future assessment of computational methods for clinical interpretation.

Pathogenic variants in MDFIC cause recessive central conducting lymphatic anomaly with lymphedema.

Central conducting lymphatic anomaly (CCLA), characterized by the dysfunction of core collecting lymphatic vessels including the thoracic duct and cisterna chyli, and presenting as chylothorax, pleural effusions, chylous ascites, and lymphedema, is a severe disorder often resulting in fetal or perinatal demise. Although pathogenic variants in RAS/mitogen activated protein kinase (MAPK) signaling pathway components have been documented in some patients with CCLA, the genetic etiology of the disorder remains uncharacterized in most cases. Here, we identified biallelic pathogenic variants in MDFIC, encoding the MyoD family inhibitor domain containing protein, in seven individuals with CCLA from six independent families. Clinical manifestations of affected fetuses and children included nonimmune hydrops fetalis (NIHF), pleural and pericardial effusions, and lymphedema. Generation of a mouse model of human MDFIC truncation variants revealed that homozygous mutant mice died perinatally exhibiting chylothorax. The lymphatic vasculature of homozygous Mdfic mutant mice was profoundly mispatterned and exhibited major defects in lymphatic vessel valve development. Mechanistically, we determined that MDFIC controls collective cell migration, an important early event during the formation of lymphatic vessel valves, by regulating integrin ß1 activation and the interaction between lymphatic endothelial cells and their surrounding extracellular matrix. Our work identifies MDFIC variants underlying human lymphatic disease and reveals a crucial, previously unrecognized role for MDFIC in the lymphatic vasculature. Ultimately, understanding the genetic and mechanistic basis of CCLA will facilitate the development and implementation of new therapeutic approaches to effectively treat this complex disease.

Recurrent de novo missense variants in GNB2 can cause syndromic intellectual disability.

PURPOSE: Binding proteins (G-proteins) mediate signalling pathways involved in diverse cellular functions and comprise Gα and Gßγ units. Human diseases have been reported for all five Gß proteins. A de novo missense variant in GNB2 was recently reported in one individual with developmental delay/intellectual disability (DD/ID) and dysmorphism. We aim to confirm GNB2 as a neurodevelopmental disease gene, and elucidate the GNB2-associated neurodevelopmental phenotype in a patient cohort. METHODS: We discovered a GNB2 variant in the index case via exome sequencing and sought individuals with GNB2 variants via international data-sharing initiatives. In silico modelling of the variants was assessed, along with multiple lines of evidence in keeping with American College of Medical Genetics and Genomics guidelines for interpretation of sequence variants. RESULTS: We identified 12 unrelated individuals with five de novo missense variants in GNB2, four of which are recurrent: p.(Ala73Thr), p.(Gly77Arg), p.(Lys89Glu) and p.(Lys89Thr). All individuals have DD/ID with variable dysmorphism and extraneurologic features. The variants are located at the universally conserved shared interface with the Gα subunit, which modelling suggests weaken this interaction. CONCLUSION: Missense variants in GNB2 cause a congenital neurodevelopmental disorder with variable syndromic features, broadening the spectrum of multisystem phenotypes associated with variants in genes encoding G-proteins.

Compound heterozygous variants in LAMC3 in association with posterior periventricular nodular heterotopia.

BACKGROUND: Periventricular nodular heterotopia (PNH) is a malformation of cortical development characterized by nodules of abnormally migrated neurons. The cause of posteriorly placed PNH is not well characterised and we present a case that provides insights into the cause of posterior PNH. CASE PRESENTATION: We report a fetus with extensive posterior PNH in association with biallelic variants in LAMC3. LAMC3 mutations have previously been shown to cause polymicrogyria and pachygyria in the occipital cortex, but not PNH. The occipital location of PNH in our case and the proposed function of LAMC3 in cortical development suggest that the identified LAMC3 variants may be causal of PNH in this fetus. CONCLUSION: We hypothesise that this finding extends the cortical phenotype associated with LAMC3 and provides valuable insight into genetic cause of posterior PNH.

Paternal mosaicism for a novel PBX1 mutation associated with recurrent perinatal death: Phenotypic expansion of the PBX1-related syndrome.

Autosomal dominant (de novo) mutations in PBX1 are known to cause congenital abnormalities of the kidney and urinary tract (CAKUT), with or without extra-renal abnormalities. Using trio exome sequencing, we identified a PBX1 p.(Arg107Trp) mutation in a deceased one-day-old neonate presenting with CAKUT, asplenia, and severe bilateral diaphragmatic thinning and eventration. Further investigation by droplet digital PCR revealed that the mutation had occurred post-zygotically in the father, with different variant allele frequencies of the mosaic PBX1 mutation in blood (10%) and sperm (20%). Interestingly, the father had subclinical hydronephrosis in childhood. With an expected recurrence risk of one in five, chorionic villus sampling and prenatal diagnosis for the PBX1 mutation identified recurrence in a subsequent pregnancy. The family opted to continue the pregnancy and the second affected sibling was stillborn at 35 weeks, presenting with similar severe bilateral diaphragmatic eventration, microsplenia, and complete sex reversal (46, XY female). This study highlights the importance of follow-up studies for presumed de novo and low-level mosaic variants and broadens the phenotypic spectrum of developmental abnormalities caused by PBX1 mutations.

Posterior Neocortex-Specific Regulation of Neuronal Migration by CEP85L Identifies Maternal Centriole-Dependent Activation of CDK5.

Genes mutated in human neuronal migration disorders encode tubulin proteins and a variety of tubulin-binding and -regulating proteins, but it is very poorly understood how these proteins function together to coordinate migration. Additionally, the way in which regional differences in neocortical migration are controlled is completely unknown. Here we describe a new syndrome with remarkably region-specific effects on neuronal migration in the posterior cortex, reflecting de novo variants in CEP85L. We show that CEP85L is required cell autonomously in vivo and in vitro for migration, that it localizes to the maternal centriole, and that it forms a complex with many other proteins required for migration, including CDK5, LIS1, NDE1, KIF2A, and DYNC1H1. Loss of CEP85L disrupts CDK5 localization and activation, leading to centrosome disorganization and disrupted microtubule cytoskeleton organization. Together, our findings suggest that CEP85L highlights a complex that controls CDK5 activity to promote neuronal migration.

Pseudodiastrophic dysplasia expands the known phenotypic spectrum of defects in proteoglycan biosynthesis.

BACKGROUND: Pseudodiastrophic dysplasia (PDD) is a severe skeletal dysplasia associated with prenatal manifestation and early lethality. Clinically, PDD is classified as a 'dysplasia with multiple joint dislocations'; however, the molecular aetiology of the disorder is currently unknown. METHODS: Whole exome sequencing (WES) was performed on three patients from two unrelated families, clinically diagnosed with PDD, in order to identify the underlying genetic cause. The functional effects of the identified variants were characterised using primary cells and human cell-based overexpression assays. RESULTS: WES resulted in the identification of biallelic variants in the established skeletal dysplasia genes, B3GAT3 (family 1) and CANT1 (family 2). Mutations in these genes have previously been reported to cause 'multiple joint dislocations, short stature, and craniofacial dysmorphism with or without congenital heart defects' ('JDSCD'; B3GAT3) and Desbuquois dysplasia 1 (CANT1), disorders in the same nosological group as PDD. Follow-up of the B3GAT3 variants demonstrated significantly reduced B3GAT3/GlcAT-I expression. Downstream in vitro functional analysis revealed abolished biosynthesis of glycosaminoglycan side chains on proteoglycans. Functional evaluation of the CANT1 variant showed impaired nucleotidase activity, which results in inhibition of glycosaminoglycan synthesis through accumulation of uridine diphosphate. CONCLUSION: For the families described in this study, the PDD phenotype was caused by mutations in the known skeletal dysplasia genes B3GAT3 and CANT1, demonstrating the advantage of genomic analyses in delineating the molecular diagnosis of skeletal dysplasias. This finding expands the phenotypic spectrum of B3GAT3-related and CANT1-related skeletal dysplasias to include PDD and highlights the significant phenotypic overlap of conditions within the proteoglycan biosynthesis pathway.

Identification and targeted management of a neurodegenerative disorder caused by biallelic mutations in SLC5A6.

We describe a sibling pair displaying an early infantile-onset, progressive neurodegenerative phenotype, with symptoms of developmental delay and epileptic encephalopathy developing from 12 to 14 months of age. Using whole exome sequencing, compound heterozygous variants were identified in SLC5A6, which encodes the sodium-dependent multivitamin transporter (SMVT) protein. SMVT is an important transporter of the B-group vitamins biotin, pantothenate, and lipoate. The protein is ubiquitously expressed and has major roles in vitamin uptake in the digestive system, as well as transport of these vitamins across the blood-brain barrier. Pathogenicity of the identified variants was demonstrated by impaired biotin uptake of mutant SMVT. Identification of this vitamin transporter as the genetic basis of this disorder guided targeted therapeutic intervention, resulting clinically in improvement of the patient's neurocognitive and neuromotor function. This is the second report of biallelic mutations in SLC5A6 leading to a neurodegenerative disorder due to impaired biotin, pantothenate and lipoate uptake. The genetic and phenotypic overlap of these cases confirms mutations in SLC5A6 as the genetic cause of this disease phenotype. Recognition of the genetic disorder caused by SLC5A6 mutations is essential for early diagnosis and to facilitate timely intervention by triple vitamin (biotin, pantothenate, and lipoate) replacement therapy.

matchbox: An open-source tool for patient matching via the Matchmaker Exchange.

Rare disease investigators constantly face challenges in identifying additional cases to build evidence for gene-disease causality. The Matchmaker Exchange (MME) addresses this limitation by providing a mechanism for matching patients across genomic centers via a federated network. The MME has revolutionized searching for additional cases by making it possible to query across institutional boundaries, so that what was once a laborious and manual process of contacting researchers is now automated and computable. However, while the MME network is beginning to scale, the growth of additional nodes is limited by the lack of easy-to-use solutions that can be implemented by any rare disease database owner, even one without significant software engineering resources. Here, we describe matchbox, which is an open-source, platform-independent, portable bridge between any given rare disease genomic center and the MME network, which has already led to novel gene discoveries. We also describe how matchbox greatly reduces the barrier to participation by overcoming challenges for new databases to join the MME.