Search

Mobile element insertions (MEIs) are a known cause of genetic disease but have been underexplored due to technical limitations of genetic testing methods. Various bioinformatic tools have been developed to identify MEIs in Next Generation Sequencing data. However, most tools have been developed specifically for genome sequencing (GS) data rather than exome sequencing (ES) data, which remains more widely used for routine diagnostic testing. In this study, we benchmarked six MEI detection tools (ERVcaller, MELT, Mobster, SCRAMble, TEMP2 and xTea) on ES data and on GS data from publicly available genomic samples (HG002, NA12878). For all the tools we evaluated sensitivity and precision of different filtering strategies. Results show that there were substantial differences in tool performance between ES and GS data. MELT performed best with ES data and its combination with SCRAMble increased substantially the detection rate of MEIs. By applying both tools to 10,890 ES samples from Solve-RD and 52,624 samples from Radboudumc we were able to diagnose 10 patients who had remained undiagnosed by conventional ES analysis until now. Our study shows that MELT and SCRAMble can be used reliably to identify clinically relevant MEIs in ES data. This may lead to an additional diagnosis for 1 in 3000 to 4000 patients in routine clinical ES.

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.

Skeletal ciliopathies are a group of disorders caused by dysfunction of the cilium, a small signaling organelle present on nearly every vertebrate cell. This group of disorders is marked by genetic and clinical heterogeneity, which complicates accurate diagnosis. In this study, we developed a robust, standardized immunofluorescence approach to accurately diagnose a subset of these disorders. Hereto we determined and compared the cilium phenotype of healthy individuals to patients from three different ciliopathy subgroups, using skin-derived fibroblasts. The cilium phenotype assay consists of three parameters; (1) ciliogenesis, based on the presence or absence of cilium markers, (2) cilium length, measured by the combined signal of an axonemal and a cilium membrane marker, and (3) retrograde intraflagellar transport (IFT), quantified by the area of the ciliary tip. Analysis of the cilium phenotypic data yielded comparable and reproducible results and in addition, displayed identifiable clusters for healthy individuals and two ciliopathy subgroups, i.e. ATD and CED. Our results illustrate that standardized analysis of the cilium phenotype can be used to discriminate between ciliopathy subgroups. Therefore, we believe that standardization of functional assays analyzing cilium phenotypic data can provide additional proof for conclusive diagnosis of ciliopathies, which is essential for routine diagnostic care.

The genetic etiology of intellectual disability remains elusive in almost half of all affected individuals. Within the Solve-RD consortium, systematic re-analysis of whole exome sequencing (WES) data from unresolved cases with (syndromic) intellectual disability (n= 1,472 probands) was performed. This re-analysis included variant calling of mitochondrial DNA (mtDNA) variants, although mtDNA is not specifically targeted in WES. We identified a functionally relevant mtDNA variant in MT-TL1(NC_012920.1:m.3291T > C; NC_012920.1:n.62T > C), at a heteroplasmy level of 22% in whole blood, in a 23-year-old male with severe intellectual disability, epilepsy, episodic headaches with emesis, spastic tetraparesis, brain abnormalities, and feeding difficulties. Targeted validation in blood and urine supported pathogenicity, with heteroplasmy levels of 23% and 58% in index, and 4% and 17% in mother, respectively. Interestingly, not all phenotypic features observed in the index have been previously linked to this MT-TL1variant, suggesting either broadening of the m.3291T > C-associated phenotype, or presence of a co-occurring disorder. Hence, our case highlights the importance of underappreciated mtDNA variants identifiable from WES data, especially for cases with atypical mitochondrial phenotypes and their relatives in the maternal line.

Reanalysis of inconclusive exome/genome sequencing data increases the diagnosis yield of patients with rare diseases. However, the cost and efforts required for reanalysis prevent its routine implementation in research and clinical environments. The Solve-RD project aims to reveal the molecular causes underlying undiagnosed rare diseases. One of the goals is to implement innovative approaches to reanalyse the exomes and genomes from thousands of well-studied undiagnosed cases. The raw genomic data is submitted to Solve-RD through the RD-Connect Genome-Phenome Analysis Platform (GPAP) together with standardised phenotypic and pedigree data. We have developed a programmatic workflow to reanalyse genome-phenome data. It uses the RD-Connect GPAP’s Application Programming Interface (API) and relies on the big-data technologies upon which the system is built. We have applied the workflow to prioritise rare known pathogenic variants from 4411 undiagnosed cases. The queries returned an average of 1.45 variants per case, which first were evaluated in bulk by a panel of disease experts and afterwards specifically by the submitter of each case. A total of 120 index cases (21.2% of prioritised cases, 2.7% of all exome/genome-negative samples) have already been solved, with others being under investigation. The implementation of solutions as the one described here provide the technical framework to enable periodic case-level data re-evaluation in clinical settings, as recommended by the American College of Medical Genetics.

For the first time in Europe hundreds of rare disease (RD) experts team up to actively share and jointly analyse existing patient’s data. Solve-RD is a Horizon 2020-supported EU flagship project bringing together >300 clinicians, scientists, and patient representatives of 51 sites from 15 countries. Solve-RD is built upon a core group of four European Reference Networks (ERNs; ERN-ITHACA, ERN-RND, ERN-Euro NMD, ERN-GENTURIS) which annually see more than 270,000 RD patients with respective pathologies. The main ambition is to solve unsolved rare diseases for which a molecular cause is not yet known. This is achieved through an innovative clinical research environment that introduces novel ways to organise expertise and data. Two major approaches are being pursued (i) massive data re-analysis of >19,000 unsolved rare disease patients and (ii) novel combined -omics approaches. The minimum requirement to be eligible for the analysis activities is an inconclusive exome that can be shared with controlled access. The first preliminary data re-analysis has already diagnosed 255 cases form 8393 exomes/genome datasets. This unprecedented degree of collaboration focused on sharing of data and expertise shall identify many new disease genes and enable diagnosis of many so far undiagnosed patients from all over Europe.

The Koolen-de Vries syndrome (KdVS) is a multisystem syndrome with variable facial features caused by a 17q21.31 microdeletion or KANSL1truncating variant. As the facial gestalt of KdVS has resemblance with the gestalt of the 22q11.2 deletion syndrome (22q11.2DS), we assessed whether our previously described hybrid quantitative facial phenotyping algorithm could distinguish between these two syndromes, and whether there is a facial difference between the molecular KdVS subtypes. We applied our algorithm to 2D photographs of 97 patients with KdVS (78 microdeletions, 19 truncating variants (likely) causing KdVS) and 48 patients with 22q11.2DS as well as age, gender and ethnicity matched controls with intellectual disability (n= 145). The facial gestalts of KdVS and 22q11.2DS were both recognisable through significant clustering by the hybrid model, yet different from one another (p= 7.5 × 10−10and p= 0.0052, respectively). Furthermore, the facial gestalts of KdVS caused by a 17q21.31 microdeletion and KANSL1truncating variant (likely) causing KdVS were indistinguishable (p= 0.981 and p= 0.130). Further application to three patients with a variant of unknown significance in KANSL1showed that these faces do not match KdVS. Our data highlight quantitative facial phenotyping not only as a powerful tool to distinguish syndromes with overlapping facial dysmorphisms but also to establish pathogenicity of variants of unknown clinical significance.

Unsolicited findings (UFs) are uncovered unintentionally and predispose to a disease unrelated to the clinical question. The frequency and nature of UFs uncovered in clinical practice remain largely unexplored. We here evaluated UFs identified during a 5-year period in which 16,482 index patients received clinical whole-exome sequencing (WES). UFs were identified in 0.58% (95/16,482) of index patients, indicating that the overall frequency of UFs in clinical WES is low. Fewer UFs were identified using restricted disease-gene panels (0.03%) than when using whole-exome/Mendeliome analysis (1.03%). The UF was disclosed to 86 of 95 individuals, for reasons of medical actionability. Only 61% of these UFs reside in a gene that is listed on the “ACMG59”-list, representing a list of 59 genes for which the American College of Medical Genetics recommends UF disclosure. The remaining 39% were grouped into four categories: disorders similar to “ACMG59”-listed disorders (25%); disorders for which disease manifestation could be influenced (7%); UFs providing reproductive options (2%); and UFs with pharmacogenetic implications (5%). Hence, our experience shows that UFs predisposing to medically actionable disorders affect a broader range of genes than listed on the “ACMG59”, advocating that a pre-defined gene list is too restrictive, and that UFs may require ad hoc evaluation of medical actionability. While both the identification and disclosure of UFs depend on local policy, our lessons learned provide general essential insight into the nature and odds of UFs in clinical exome sequencing.

Zhu–Tokita–Takenouchi–Kim (ZTTK) syndrome, an intellectual disability syndrome first described in 2016, is caused by heterozygous loss-of-function variants in SON. Its encoded protein promotes pre-mRNA splicing of many genes essential for development. Whereas individual phenotypic traits have previously been linked to erroneous splicing of SONtarget genes, the phenotypic spectrum and the pathogenicity of missense variants have not been further evaluated. We present the phenotypic abnormalities in 52 individuals, including 17 individuals who have not been reported before. In total, loss-of-function variants were detected in 49 individuals (de novo in 47, inheritance unknown in 2), and in 3, a missense variant was observed (2 de novo, 1 inheritance unknown). Phenotypic abnormalities, systematically collected and analyzed in Human Phenotype Ontology, were found in all organ systems. Significant inter-individual phenotypic variability was observed, even in individuals with the same recurrent variant (n= 13). SONhaploinsufficiency was previously shown to lead to downregulation of downstream genes, contributing to specific phenotypic features. Similar functional analysis for one missense variant, however, suggests a different mechanism than for heterozygous loss-of-function. Although small in numbers and while pathogenicity of these variants is not certain, these data allow for speculation whether de novo missense variants cause ZTTK syndrome via another mechanism, or a separate overlapping syndrome. In conclusion, heterozygous loss-of-function variants in SONdefine a recognizable syndrome, ZTTK, associated with a broad, severe phenotypic spectrum, characterized by a large inter-individual variability. These observations provide essential information for affected individuals, parents, and healthcare professionals to ensure appropriate clinical management.

Long-read sequencing (LRS) has the potential to comprehensively identify all medically relevant genome variation, including variation commonly missed by short-read sequencing (SRS) approaches. To determine this potential, we performed LRS around 15×–40× genome coverage using the Pacific Biosciences Sequel I System for five trios. The respective probands were diagnosed with intellectual disability (ID) whose etiology remained unresolved after SRS exomes and genomes. Systematic assessment of LRS coverage showed that ~35 Mb of the human reference genome was only accessible by LRS and not SRS. Genome-wide structural variant (SV) calling yielded on average 28,292 SV calls per individual, totaling 12.9 Mb of sequence. Trio-based analyses which allowed to study segregation, showed concordance for up to 95% of these SV calls across the genome, and 80% of the LRS SV calls were not identified by SRS. De novo mutation analysis did not identify any de novo SVs, confirming that these are rare events. Because of high sequence coverage, we were also able to call single nucleotide substitutions. On average, we identified 3 million substitutions per genome, with a Mendelian inheritance concordance of up to 97%. Of these, ~100,000 were located in the ~35 Mb of the genome that was only captured by LRS. Moreover, these variants affected the coding sequence of 64 genes, including 32 known Mendelian disease genes. Our data show the potential added value of LRS compared to SRS for identifying medically relevant genome variation.

Upon the discovery of numerous genes involved in the pathogenesis of neurodevelopmental disorders, several studies showed that a significant proportion of these genes converge on common pathways and protein networks. Here, we used a reversed approach, by screening the AnkyrinG protein-protein interaction network for genetic variation in a large cohort of 1009 cases with neurodevelopmental disorders. We identified a significant enrichment of de novo potentially disease-causing variants in this network, confirming that this protein network plays an important role in the emergence of several neurodevelopmental disorders.

Determining pathogenicity of genomic variation identified by next-generation sequencing techniques can be supported by recurrent disruptive variants in the same gene in phenotypically similar individuals. However, interpretation of novel variants in a specific gene in individuals with mild–moderate intellectual disability (ID) without recognizable syndromic features can be challenging and reverse phenotyping is often required. We describe 24 individuals with a de novo disease-causing variant in, or partial deletion of, the F-box only protein 11 gene (FBXO11, also known as VIT1and PRMT9). FBXO11is part of the SCF (SKP1-cullin-F-box) complex, a multi-protein E3 ubiquitin-ligase complex catalyzing the ubiquitination of proteins destined for proteasomal degradation. Twenty-two variants were identified by next-generation sequencing, comprising 2 in-frame deletions, 11 missense variants, 1 canonical splice site variant, and 8 nonsense or frameshift variants leading to a truncated protein or degraded transcript. The remaining two variants were identified by array-comparative genomic hybridization and consisted of a partial deletion of FBXO11. All individuals had borderline to severe ID and behavioral problems (autism spectrum disorder, attention-deficit/hyperactivity disorder, anxiety, aggression) were observed in most of them. The most relevant common facial features included a thin upper lip and a broad prominent space between the paramedian peaks of the upper lip. Other features were hypotonia and hyperlaxity of the joints. We show that de novo variants in FBXO11cause a syndromic form of ID. The current series show the power of reverse phenotyping in the interpretation of novel genetic variances in individuals who initially did not appear to have a clear recognizable phenotype.

Clinical genomic sequencing can identify pathogenic variants unrelated to the initial clinical question, but of medical relevance to the patients and their families. With ongoing discussions on the utility of disclosing or searching for such variants, it is of crucial importance to obtain unbiased insight in the prevalence of these incidental or secondary findings, in order to better weigh potential risks and benefits. Previous studies have reported a broad range of secondary findings ranging from 1 to 9%, merely attributable to differences in study design, cohorts tested, sequence technology used and genes analyzed. Here, we analyzed WES data of 1640 anonymized healthy Dutch individuals to establish the frequency of medically actionable disease alleles in an outbred population of European descent. Our study shows that 1 in 38 healthy individuals (2.7%) has a (likely) pathogenic variant in one of 59 medically actionable dominant disease genes for which the American College of Medical Genetics and Genomics (ACMG) recommends disclosure. Additionally, we identified 36 individuals (2.2%) to be a carrier of a recessive pathogenic disease allele. Whereas these frequencies of secondary findings are in line with what has been reported in the East-Asian population, the pathogenic variants are differently distributed across the 59 ACMG genes. Our results contribute to the debate on genetic risk factor screening in healthy individuals and the discussion whether the potential benefits of this knowledge and related preventive options, outweigh the risk of the emotional impact of the test result and possible stigmatization.

Genotype-first combined with reverse phenotyping has shown to be a powerful tool in human genetics, especially in the era of next generation sequencing. This combines the identification of individuals with mutations in the same gene and linking these to consistent (endo)phenotypes to establish disease causality. We have performed a MIP (molecular inversion probe)-based targeted re-sequencing study in 3,275 individuals with intellectual disability (ID) to facilitate a genotype-first approach for 24 genes previously implicated in ID. Combining our data with data from a publicly available database, we confirmed 11 of these 24 genes to be relevant for ID. Amongst these, PHIPwas shown to have an enrichment of disruptive mutations in the individuals with ID (5 out of 3,275). Through international collaboration, we identified a total of 23 individuals with PHIPmutations and elucidated the associated phenotype. Remarkably, all 23 individuals had developmental delay/ID and the majority were overweight or obese. Other features comprised behavioral problems (hyperactivity, aggression, features of autism and/or mood disorder) and dysmorphisms (full eyebrows and/or synophrys, upturned nose, large ears and tapering fingers). Interestingly, PHIPencodes two protein-isoforms, PHIP/DCAF14 and NDRP, each involved in neurodevelopmental processes, including E3 ubiquitination and neuronal differentiation. Detailed genotype-phenotype analysis points towards haploinsufficiency of PHIP/DCAF14, and not NDRP, as the underlying cause of the phenotype. Thus, we demonstrated the use of large scale re-sequencing by MIPs, followed by reverse phenotyping, as a constructive approach to verify candidate disease genes and identify novel syndromes, highlighted by PHIPhaploinsufficiency causing an ID-overweight syndrome.

Recognition of individuals with a genetic predisposition to gastric cancer (GC) enables preventive measures. However, the underlying cause of genetic susceptibility to gastric cancer remains largely unexplained. We performed germline whole-exome sequencing on leukocyte DNA of 54 patients from 53 families with genetically unexplained diffuse-type and intestinal-type GC to identify novel GC-predisposing candidate genes. As young age at diagnosis and familial clustering are hallmarks of genetic tumor susceptibility, we selected patients that were diagnosed below the age of 35, patients from families with two cases of GC at or below age 60 and patients from families with three GC cases at or below age 70. All included individuals were tested negative for germline CDH1 mutations before or during the study. Variants that were possibly deleterious according to in silico predictions were filtered using several independent approaches that were based on gene function and gene mutation burden in controls. Despite a rigorous search, no obvious candidate GC predisposition genes were identified. This negative result stresses the importance of future research studies in large, homogeneous cohorts.

Glucose transporter type 1 deficiency syndrome (GLUT1DS) is a neurometabolic disorder with a complex phenotypic spectrum but simple biomarkers in cerebrospinal fluid. The disorder is caused by impaired glucose transport into the brain resulting from variants in SCL2A1. In 10% of GLUT1DS patients, a genetic diagnosis can not be made. Using whole-genome sequencing, we identified a de novo 5′-UTR variant in SLC2A1, generating a novel translation initiation codon, severely compromising SLC2A1 function. This finding expands our understanding of the disease mechanisms underlying GLUT1DS and encourages further in-depth analysis of SLC2A1 non-coding regions in patients without variants in the coding region.

Recently WAC was reported as a candidate gene for intellectual disability (ID) based on the identification of a de novo mutation in an individual with severe ID. WAC regulates transcription-coupled histone H2B ubiquitination and has previously been implicated in the 10p12p11 contiguous gene deletion syndrome. In this study, we report on 10 individuals with de novo WAC mutations which we identified through routine (diagnostic) exome sequencing and targeted resequencing of WAC in 2326 individuals with unexplained ID. All but one mutation was expected to lead to a loss-of-function of WAC. Clinical evaluation of all individuals revealed phenotypic overlap for mild ID, hypotonia, behavioral problems and distinctive facial dysmorphisms, including a square-shaped face, deep set eyes, long palpebral fissures, and a broad mouth and chin. These clinical features were also previously reported in individuals with 10p12p11 microdeletion syndrome. To investigate the role of WAC in ID, we studied the importance of the Drosophila WAC orthologue (CG8949) in habituation, a non-associative learning paradigm. Neuronal knockdown of Drosophila CG8949 resulted in impaired learning, suggesting that WAC is required in neurons for normal cognitive performance. In conclusion, we defined a clinically recognizable ID syndrome, caused by de novo loss-of-function mutations in WAC. Independent functional evidence in Drosophila further supported the role of WAC in ID. On the basis of our data WAC can be added to the list of ID genes with a role in transcription regulation through histone modification.

AIMP1/p43 is a multifunctional non-catalytic component of the multisynthetase complex. The complex consists of nine catalytic and three non-catalytic proteins, which catalyze the ligation of amino acids to their cognate tRNA isoacceptors for use in protein translation. To date, two allelic variants in the AIMP1 gene have been reported as the underlying cause of autosomal recessive primary neurodegenerative disorder. Here, we present two consanguineous families from Pakistan and Iran, presenting with moderate to severe intellectual disability, global developmental delay, and speech impairment without neurodegeneration. By the combination of homozygosity mapping and next generation sequencing, we identified two homozygous missense variants, p.(Gly299Arg) and p.(Val176Gly), in the gene AIMP1 that co-segregated with the phenotype in the respective families. Molecular modeling of the variants revealed deleterious effects on the protein structure that are predicted to result in reduced AIMP1 function. Our findings indicate that the clinical spectrum for AIMP1 defects is broader than witnessed so far.

A Correction to this paper has been published: https://doi.org/10.1038/s41431-021-00868-z