Genome sequencing in families with congenital limb malformations

Whole genome sequencing in families with oligodontia

BACKGROUND/OBJECTIVES

Tooth agenesis (TA) is among the most common malformations in humans. Although several causative mutations have been described, the genetic cause often remains elusive. Here, we test whether whole genome sequencing (WGS) could bridge this diagnostic gap.

METHODS

In four families with TA, we assessed the dental phenotype using the Tooth Agenesis Code after intraoral examination and radiographic and photographic documentation. We performed WGS of index patients and subsequent segregation analysis.

RESULTS

We identified two variants of uncertain significance (a potential splice variant in PTH1R, and a 2.1 kb deletion abrogating a non-coding element in FGF7) and three pathogenic variants: a novel frameshift in the final exon of PITX2, a novel deletion in PAX9, and a known nonsense variant in WNT10A. Notably, the FGF7 variant was found in the patient, also featuring the WNT10A variant. While mutations in PITX2 are known to cause Axenfeld-Rieger syndrome 1 (ARS1) predominantly featuring ocular findings, accompanied by dental malformations, we found the PITX2 frameshift in a family with predominantly dental and varying ocular findings.

CONCLUSION

Severe TA predicts a genetic cause identifiable by WGS. Final exon PITX2 frameshifts can cause a predominantly dental form of ARS1.

Genome sequencing as a generic diagnostic strategy for rare disease

BACKGROUND

To diagnose the full spectrum of hereditary and congenital diseases, genetic laboratories use many different workflows, ranging from karyotyping to exome sequencing. A single generic high-throughput workflow would greatly increase efficiency. We assessed whether genome sequencing (GS) can replace these existing workflows aimed at germline genetic diagnosis for rare disease.

METHODS

We performed short-read GS (NovaSeq™6000; 150 bp paired-end reads, 37 × mean coverage) on 1000 cases with 1271 known clinically relevant variants, identified across different workflows, representative of our tertiary diagnostic centers. Variants were categorized into small variants (single nucleotide variants and indels < 50 bp), large variants (copy number variants and short tandem repeats) and other variants (structural variants and aneuploidies). Variant calling format files were queried per variant, from which workflow-specific true positive rates (TPRs) for detection were determined. A TPR of ≥ 98% was considered the threshold for transition to GS. A GS-first scenario was generated for our laboratory, using diagnostic efficacy and predicted false negative as primary outcome measures. As input, we modeled the diagnostic path for all 24,570 individuals referred in 2022, combining the clinical referral, the transition of the underlying workflow(s) to GS, and the variant type(s) to be detected.

RESULTS

Overall, 95% (1206/1271) of variants were detected. Detection rates differed per variant category: small variants in 96% (826/860), large variants in 93% (341/366), and other variants in 87% (39/45). TPRs varied between workflows (79-100%), with 7/10 being replaceable by GS. Models for our laboratory indicate that a GS-first strategy would be feasible for 84.9% of clinical referrals (750/883), translating to 71% of all individuals (17,444/24,570) receiving GS as their primary test. An estimated false negative rate of 0.3% could be expected.

CONCLUSIONS

GS can capture clinically relevant germline variants in a 'GS-first strategy' for the majority of clinical indications in a genetics diagnostic lab.

STIGMA: Single-cell tissue-specific gene prioritization using machine learning

Clinical exome and genome sequencing have revolutionized the understanding of human disease genetics. Yet many genes remain functionally uncharacterized, complicating the establishment of causal disease links for genetic variants. While several scoring methods have been devised to prioritize these candidate genes, these methods fall short of capturing the expression heterogeneity across cell subpopulations within tissues. Here, we introduce single-cell tissue-specific gene prioritization using machine learning (STIGMA), an approach that leverages single-cell RNA-seq (scRNA-seq) data to prioritize candidate genes associated with rare congenital diseases. STIGMA prioritizes genes by learning the temporal dynamics of gene expression across cell types during healthy organogenesis. To assess the efficacy of our framework, we applied STIGMA to mouse limb and human fetal heart scRNA-seq datasets. In a cohort of individuals with congenital limb malformation, STIGMA prioritized 469 variants in 345 genes, with UBA2 as a notable example. For congenital heart defects, we detected 34 genes harboring nonsynonymous de novo variants (nsDNVs) in two or more individuals from a set of 7,958 individuals, including the ortholog of Prdm1, which is associated with hypoplastic left ventricle and hypoplastic aortic arch. Overall, our findings demonstrate that STIGMA effectively prioritizes tissue-specific candidate genes by utilizing single-cell transcriptome data. The ability to capture the heterogeneity of gene expression across cell populations makes STIGMA a powerful tool for the discovery of disease-associated genes and facilitates the identification of causal variants underlying human genetic disorders.

Variable clinical presentation of split hand/foot malformation syndrome in a family with microduplication of 10q24.32: a case report

SHFM (Split Hand/Foot Malformation) is a heterogeneous group of disorders characterized by the presence of clefts in the hands and feet, along with syndactyly of the digits. In this article, we describe a family in which two members exhibit characteristic developmental abnormalities associated with SHFM, presenting with variable clinical features. Using whole-genome sequencing, we identified a microduplication of a chromosomal segment on locus 10q24.32, specifically spanning positions 102934495 to 103496555, encompassing genes BTRC, POLL, FBXW4 and LBX1 in the proband. Genomic duplications, including these genes, were previously described in patients diagnosed with the third type of SHFM. We validated the presence of this structural rearrangement in 7 family members, including the proband and the proband's father. Remarkably, further investigation demonstrated that the detected duplication exhibits a mosaic state in the phenotypically normal paternal grandmother of the proband, thereby providing a plausible explanation for the absence of a pathological phenotype in her.

HOXD13-associated synpolydactyly: Extending and validating the genotypic and phenotypic spectrum with 38 new and 49 published families

PURPOSE

HOXD13 is an important regulator of limb development. Pathogenic variants in HOXD13 cause synpolydactyly type 1 (SPD1). How different types and positions of HOXD13 variants contribute to genotype-phenotype correlations, penetrance, and expressivity of SPD1 remains elusive. Here, we present a novel cohort and a literature review to elucidate HOXD13 phenotype-genotype correlations.

METHODS

Patients with limb anomalies suggestive of SPD1 were selected for analysis of HOXD13 by Sanger sequencing, repeat length analysis, and next-generation sequencing. Literature was reviewed for HOXD13 heterozygotes. Variants were annotated for phenotypic data. Severity was calculated, and cluster and decision-tree analyses were performed.

RESULTS

We identified 98 affected members of 38 families featuring 11 different (likely) causative variants and 4 variants of uncertain significance. The most frequent (25/38) were alanine repeat expansions. Phenotypes ranged from unaffected heterozygotes to severe osseous synpolydactyly, with intra- and inter-familial heterogeneity and asymmetry. A literature review provided 160 evaluable affected members of 49 families with SPD1. Computer-aided analysis only corroborated a positive correlation between alanine repeat length and phenotype severity.

CONCLUSION

Our findings support that HOXD13-protein condensation in addition to haploinsufficiency is the molecular pathomechanism of SPD1. Our data may, also, facilitate the interpretation of synpolydactyly radiographs by future automated tools.

Aberrant phase separation and nucleolar dysfunction in rare genetic diseases

Thousands of genetic variants in protein-coding genes have been linked to disease. However, the functional impact of most variants is unknown as they occur within intrinsically disordered protein regions that have poorly defined functions^1-3. Intrinsically disordered regions can mediate phase separation and the formation of biomolecular condensates, such as the nucleolus^4,5. This suggests that mutations in disordered proteins may alter condensate properties and function^6-8. Here we show that a subset of disease-associated variants in disordered regions alter phase separation, cause mispartitioning into the nucleolus and disrupt nucleolar function. We discover de novo frameshift variants in HMGB1 that cause brachyphalangy, polydactyly and tibial aplasia syndrome, a rare complex malformation syndrome. The frameshifts replace the intrinsically disordered acidic tail of HMGB1 with an arginine-rich basic tail. The mutant tail alters HMGB1 phase separation, enhances its partitioning into the nucleolus and causes nucleolar dysfunction. We built a catalogue of more than 200,000 variants in disordered carboxy-terminal tails and identified more than 600 frameshifts that create arginine-rich basic tails in transcription factors and other proteins. For 12 out of the 13 disease-associated variants tested, the mutation enhanced partitioning into the nucleolus, and several variants altered rRNA biogenesis. These data identify the cause of a rare complex syndrome and suggest that a large number of genetic variants may dysregulate nucleoli and other biomolecular condensates in humans.

The performance of genome sequencing as a first-tier test for neurodevelopmental disorders

Genome sequencing (GS) can identify novel diagnoses for patients who remain undiagnosed after routine diagnostic procedures. We tested whether GS is a better first-tier genetic diagnostic test than current standard of care (SOC) by assessing the technical and clinical validity of GS for patients with neurodevelopmental disorders (NDD). We performed both GS and exome sequencing in 150 consecutive NDD patient-parent trios. The primary outcome was diagnostic yield, calculated from disease-causing variants affecting exonic sequence of known NDD genes. GS (30%, n = 45) and SOC (28.7%, n = 43) had similar diagnostic yield. All 43 conclusive diagnoses obtained with SOC testing were also identified by GS. SOC, however, required integration of multiple test results to obtain these diagnoses. GS yielded two more conclusive diagnoses, and four more possible diagnoses than ES-based SOC (35 vs. 31). Interestingly, these six variants detected only by GS were copy number variants (CNVs). Our data demonstrate the technical and clinical validity of GS to serve as routine first-tier genetic test for patients with NDD. Although the additional diagnostic yield from GS is limited, GS comprehensively identified all variants in a single experiment, suggesting that GS constitutes a more efficient genetic diagnostic workflow.

Spectrum of fetal limb anomalies

PURPOSE

Antenatal detection of limb anomalies is not uncommon, and pregnancies are usually terminated in view of the expected physical handicap. The aim of this retrospective observational study is to delineate the spectrum of fetal limb anomalies and provide evidence in support of complete postnatal evaluation in establishing recurrence risk.

METHODS

We present 54 cases of limb malformations detected antenatally and discuss the spectrum of abnormalities, the utility of fetal autopsy, and genetic testing to establish recurrence risk in subsequent pregnancies.

RESULTS

16/54 cases were isolated radial ray anomalies. There were five cases of amniotic band syndrome, five limb body wall complex cases, three VACTERL (vertebral defects, anal atresia, cardiac defects, tracheo-esophageal fistula, renal anomalies, and limb abnormalities) associations, one case of sirenomelia, two cases of limb pelvis hypoplasia, and one case of OEIS (Omphalocele Exstrophy Imperforate anus and spinal defects). Four fetuses with non-isolated radial ray anomaly had trisomy 18. One case with bilateral radial ray defect had a mutation in the FANC-E gene confirming fanconi anemia. Twelve cases were unclassified.

CONCLUSION

Autopsy is the most important investigation in fetuses with limb anomalies. We suggest chromosomal microarray (CMA) as a first-tier test after autopsy. However, in cases of bilaterally symmetrical limb anomalies, in case of previous similarly affected child, or history of consanguinity, whole exome sequencing (WES) can be offered as the primary investigation, followed by CMA if WES is normal.

Developmental genomics of limb malformations: Allelic series in association with gene dosage effects contribute to the clinical variability

Genetic heterogeneity, reduced penetrance, and variable expressivity, the latter including asymmetric body axis plane presentations, have all been described in families with congenital limb malformations (CLMs). Interfamilial and intrafamilial heterogeneity highlight the complexity of the underlying genetic pathogenesis of these developmental anomalies. Family-based genomics by exome sequencing (ES) and rare variant analyses combined with whole-genome array-based comparative genomic hybridization were implemented to investigate 18 families with limb birth defects. Eleven of 18 (61%) families revealed explanatory variants, including 7 single-nucleotide variant alleles and 3 copy number variants (CNVs), at previously reported "disease trait associated loci": BHLHA9, GLI3, HOXD cluster, HOXD13, NPR2, and WNT10B. Breakpoint junction analyses for all three CNV alleles revealed mutational signatures consistent with microhomology-mediated break-induced replication, a mechanism facilitated by Alu/Alu-mediated rearrangement. Homozygous duplication of BHLHA9 was observed in one Turkish kindred and represents a novel contributory genetic mechanism to Gollop-Wolfgang Complex (MIM: 228250), where triplication of the locus has been reported in one family from Japan (i.e., 4n = 2n + 2n versus 4n = 3n + 1n allelic configurations). Genes acting on limb patterning are sensitive to a gene dosage effect and are often associated with an allelic series. We extend an allele-specific gene dosage model to potentially assist, in an adjuvant way, interpretations of interconnections among an allelic series, clinical severity, and reduced penetrance of the BHLHA9-related CLM spectrum.

Computational and experimental methods for classifying variants of unknown clinical significance

The increase in sequencing capacity, reduction in costs, and national and international coordinated efforts have led to the widespread introduction of next-generation sequencing (NGS) technologies in patient care. More generally, human genetics and genomic medicine are gaining importance for more and more patients. Some communities are already discussing the prospect of sequencing each individual's genome at time of birth. Together with digital health records, this shall enable individualized treatments and preventive measures, so-called precision medicine. A central step in this process is the identification of disease causal mutations or variant combinations that make us more susceptible for diseases. Although various technological advances have improved the identification of genetic alterations, the interpretation and ranking of the identified variants remains a major challenge. Based on our knowledge of molecular processes or previously identified disease variants, we can identify potentially functional genetic variants and, using different lines of evidence, we are sometimes able to demonstrate their pathogenicity directly. However, the vast majority of variants are classified as variants of uncertain clinical significance (VUSs) with not enough experimental evidence to determine their pathogenicity. In these cases, computational methods may be used to improve the prioritization and an increasing toolbox of experimental methods is emerging that can be used to assay the molecular effects of VUSs. Here, we discuss how computational and experimental methods can be used to create catalogs of variant effects for a variety of molecular and cellular phenotypes. We discuss the prospects of integrating large-scale functional data with machine learning and clinical knowledge for the development of accurate pathogenicity predictions for clinical applications.

Combining callers improves the detection of copy number variants from whole-genome sequencing

Copy Number Variants (CNVs) are deletions, duplications or insertions larger than 50 base pairs. They account for a large percentage of the normal genome variation and play major roles in human pathology. While array-based approaches have long been used to detect them in clinical practice, whole-genome sequencing (WGS) bears the promise to allow concomitant exploration of CNVs and smaller variants. However, accurately calling CNVs from WGS remains a difficult computational task, for which a consensus is still lacking. In this paper, we explore practical calling options to reach the best compromise between sensitivity and sensibility. We show that callers based on different signal (paired-end reads, split reads, coverage depth) yield complementary results. We suggest approaches combining four selected callers (Manta, Delly, ERDS, CNVnator) and a regenotyping tool (SV2), and show that this is applicable in everyday practice in terms of computation time and further interpretation. We demonstrate the superiority of these approaches over array-based Comparative Genomic Hybridization (aCGH), specifically regarding the lack of resolution in breakpoint definition and the detection of potentially relevant CNVs. Finally, we confirm our results on the NA12878 benchmark genome, as well as one clinically validated sample. In conclusion, we suggest that WGS constitutes a timely and economically valid alternative to the combination of aCGH and whole-exome sequencing.