Analysis of 72,469 UK Biobank exomes links rare variants to male-pattern hair loss.

Male-pattern hair loss (MPHL) is common and highly heritable. While genome-wide association studies (GWAS) have generated insights into the contribution of common variants to MPHL etiology, the relevance of rare variants remains unclear. To determine the contribution of rare variants to MPHL etiology, we perform gene-based and single-variant analyses in exome-sequencing data from 72,469 male UK Biobank participants. While our population-level risk prediction suggests that rare variants make only a minor contribution to general MPHL risk, our rare variant collapsing tests identified a total of five significant gene associations. These findings provide additional evidence for previously implicated genes (EDA2R, WNT10A) and highlight novel risk genes at and beyond GWAS loci (HEPH, CEPT1, EIF3F). Furthermore, MPHL-associated genes are enriched for genes considered causal for monogenic trichoses. Together, our findings broaden the MPHL-associated allelic spectrum and provide insights into MPHL pathobiology and a shared basis with monogenic hair loss disorders.

VIKING II, a worldwide observational cohort of volunteers with northern isles ancestry.

Introduction: The purpose of VIKING II is to create an observational cohort of volunteers with ancestry from the Northern Isles of Scotland, primarily for identifying genetic variants influencing disease. The new online protocol is separate to, but follows on from, earlier genetic epidemiological clinic-based studies in the isolated populations of Orkney and Shetland. These populations are favourable for the study of rarer genetic variants due to genetic drift, the large number of relatives, and availability of pedigree information. They are known to be genetically distinct from mainland British populations. Methods and analysis: Online methods are being used to recruit ~4,000 people who have Northern Isles ancestry, living anywhere in the world. The option for participants to have actionable genetic results returned is offered. Consent will be taken electronically. Data will be collected at baseline through an online questionnaire and longitudinally through linkage to NHS data in the electronic health record. The questionnaire collects a variety of phenotypes including personal and family health. DNA will be extracted from saliva samples then genome-wide genotyped and exome sequenced. VIKING II aims to capitalise on the special features of the Northern Isles populations to create a research cohort that will facilitate the analysis of genetic variants associated with a broad range of traits and disease endpoints, including otherwise rare variants that have drifted to high frequency in these populations. Ethics and dissemination: The South East Scotland Research Ethics Committee gave the study a favourable opinion. VIKING II is sponsored by the University of Edinburgh and NHS Lothian. Summary research findings will be disseminated to participants and funding bodies, presented at conferences and reported in peer-reviewed publications. Article summary: Strengths and limitations of this studyDetailed data and biological sample collection of research volunteers with unique ancestry.Consent for access to routinely collected clinical EHR data and for future re-contact, providing a longitudinal component.Optional consent for return of actionable genetic results.~4,000 participants is a relatively small number for certain types of genetic analyses, so the cohort is underpowered on its own, in some study designs.Resources to maintain the cohort, and to store data and DNA samples, are significant, with sustainability dependent on infrastructure support and funding.

Lifting of the 1,000 wheat exome project SNPs from Triticum aestivum cv. Chinese Spring assembly RefSeq v1.0 to RefSeq v2.1.

OBJECTIVE: The 1,000 wheat exome project captured the single nucleotide variants in the coding regions of a diverse set of 890 wheat accessions to analyse the contribution of introgression to adaptation of wheat. However, this highly useful single nucleotide polymorphism (SNP) dataset is based on RefSeq v1.0 of the International Wheat Genome Sequencing Consortium (IWGSC) assembly of the bread wheat genome of Chinese Spring. This reference sequence has recently been updated using optical maps and long-read sequencing to produce the improved RefSeq v2.1. Our objective was to develop a reliable high-density SNP dataset positioned onto RefSeq v2.1 because it is the current standard reference sequence used by wheat researchers. RESULTS: The 3,039,822 SNPs originally positioned on RefSeq v1.0 were projected to v2.1 using Liftoff with four different flanking regions, and 2,946,536 SNPs were consistently lifted to the same location irrespective of the flanking region lengths. Of these, 2,799,166 were located on the '+' ve strand. The distribution of the SNPs across the 21 chromosomes on RefSeq v2.1 was similar to that of RefSeq v1.0. Among the SNPs that were based on unanchored scaffolds in RefSeq v1.0, 11,938 were projected to one of the 21 pseudomolecules in the upgraded assembly. This SNP dataset constitutes a much-needed standardized resource for the wheat research community.

Gene-based burden scores identify rare variant associations for 28 blood biomarkers.

BACKGROUND: A relevant part of the genetic architecture of complex traits is still unknown; despite the discovery of many disease-associated common variants. Polygenic risk score (PRS) models are based on the evaluation of the additive effects attributable to common variants and have been successfully implemented to assess the genetic susceptibility for many phenotypes. In contrast, burden tests are often used to identify an enrichment of rare deleterious variants in specific genes. Both kinds of genetic contributions are typically analyzed independently. Many studies suggest that complex phenotypes are influenced by both low effect common variants and high effect rare deleterious variants. The aim of this paper is to integrate the effect of both common and rare functional variants for a more comprehensive genetic risk modeling. METHODS: We developed a framework combining gene-based scores based on the enrichment of rare functionally relevant variants with genome-wide PRS based on common variants for association analysis and prediction models. We applied our framework on UK Biobank dataset with genotyping and exome data and considered 28 blood biomarkers levels as target phenotypes. For each biomarker, an association analysis was performed on full cohort using gene-based scores (GBS). The cohort was then split into 3 subsets for PRS construction and feature selection, predictive model training, and independent evaluation, respectively. Prediction models were generated including either PRS, GBS or both (combined). RESULTS: Association analyses of the cohort were able to detect significant genes that were previously known to be associated with different biomarkers. Interestingly, the analyses also revealed heterogeneous effect sizes and directionality highlighting the complexity of the blood biomarkers regulation. However, the combined models for many biomarkers show little or no improvement in prediction accuracy compared to the PRS models. CONCLUSION: This study shows that rare variants play an important role in the genetic architecture of complex multifactorial traits such as blood biomarkers. However, while rare deleterious variants play a strong role at an individual level, our results indicate that classical common variant based PRS might be more informative to predict the genetic susceptibility at the population level.

Rare Variants in Primary Immunodeficiency Genes and Their Functional Partners in Severe COVID-19.

The development of severe COVID-19, which is a complex multisystem disease, is thought to be associated with many genes whose action is modulated by numerous environmental and genetic factors. In this study, we focused on the ideas of the omnigenic model of heritability of complex traits, which assumes that a small number of core genes and a large pool of peripheral genes expressed in disease-relevant tissues contribute to the genetics of complex traits through interconnected networks. We hypothesized that primary immunodeficiency disease (PID) genes may be considered as core genes in severe COVID-19, and their functional partners (FPs) from protein-protein interaction networks may be considered as peripheral near-core genes. We used whole-exome sequencing data from patients aged ≤ 45 years with severe (n = 9) and non-severe COVID-19 (n = 11), and assessed the cumulative contribution of rare high-impact variants to disease severity. In patients with severe COVID-19, an excess of rare high-impact variants was observed at the whole-exome level, but maximal association signals were detected for PID + FP gene subsets among the genes intolerant to LoF variants, haploinsufficient and essential. Our exploratory study may serve as a model for new directions in the research of host genetics in severe COVID-19.

Panels, Exomes, Genomes, and More-Finding the Best Path Through the Diagnostic Odyssey.

Selecting the ideal test to evaluate an individual with a suspected genetic disorder can be challenging. While several clinical testing options are available, no single test yet captures all potentially causative genetic variants. Thus, clinicians may order testing in a stepwise fashion, and what to order after non-diagnostic testing can be challenging to determine. Here, we provide an overview of commonly used clinical genetic tests, guidance on when they are best used, and what they may miss. We conclude with a discussion of how new technologies might be used to identify challenging variants and simplify clinical testing in the future.

Interplay of Mendelian and polygenic risk factors in Arab breast cancer patients.

BACKGROUND: Breast cancer patients from the indigenous Arab population present much earlier than patients from Western countries and have traditionally been underrepresented in cancer genomics studies. The contribution of polygenic and Mendelian risk toward the earlier onset of breast cancer in the population remains elusive. METHODS: We performed low-pass whole genome sequencing (lpWGS) and whole-exome sequencing (WES) from 220 female breast cancer patients unselected for positive family history from the indigenous Arab population. Using publicly available resources, we imputed population-specific variants and calculated breast cancer burden-sensitive polygenic risk scores (PRS). Variant pathogenicity was also evaluated on exome variants with high coverage. RESULTS: Variants imputed from lpWGS showed high concordance with paired exome (median dosage correlation: 0.9459, Interquartile range: 0.9410-0.9490). After adjusting the PRS to the Arab population, we found significant associations between PRS performance in risk prediction and first-degree relative breast cancer history prediction (Spearman rho=0.43, p = 0.03), where breast cancer patients in the top PRS decile are 5.53 (95% CI 1.76-17.97, p = 0.003) times more likely also to have a first-degree relative diagnosed with breast cancer compared to those in the middle deciles. In addition, we found evidence for the genetic liability threshold model of breast cancer where among patients with a family history of breast cancer, pathogenic rare variant carriers had significantly lower PRS than non-carriers (p = 0.0205, Mann-Whitney U test) while for non-carriers every standard deviation increase in PRS corresponded to 4.52 years (95% CI 8.88-0.17, p = 0.042) earlier age of presentation. CONCLUSIONS: Overall, our study provides a framework to assess polygenic risk in an understudied population using lpWGS and identifies common variant risk as a factor independent of pathogenic variant carrier status for earlier age of onset of breast cancer among indigenous Arab breast cancer patients.

Mechanosensitive ion channel gene survey suggests potential roles in primary open angle glaucoma.

Although glaucoma is a disease modulated by eye pressure, the mechanisms of pressure sensing in the eye are not well understood. Here, we investigated associations between mechanosensitive ion channel gene variants and primary open-angle glaucoma (POAG). Common (minor allele frequency > 5%) single nucleotide polymorphisms located within the genomic regions of 20 mechanosensitive ion channel genes in the K2P, TMEM63, PIEZO and TRP channel families were assessed using genotype data from the NEIGHBORHOOD consortium of 3853 cases and 33,480 controls. Rare (minor allele frequency < 1%) coding variants were assessed using exome array genotyping data for 2606 cases and 2606 controls. Association with POAG was analyzed using logistic regression adjusting for age and sex. Two rare PIEZO1 coding variants with protective effects were identified in the NEIGHBOR dataset: R1527H, (OR 0.17, P = 0.0018) and a variant that alters a canonical splice donor site, g.16-88737727-C-G Hg38 (OR 0.38, P = 0.02). Both variants showed similar effects in the UK Biobank and the R1527H also in the FinnGen database. Several common variants also reached study-specific thresholds for association in the NEIGHBORHOOD dataset. These results identify novel variants in several mechanosensitive channel genes that show associations with POAG, suggesting that these channels may be potential therapeutic targets.

Evolutionary signatures of human cancers revealed via genomic analysis of over 35,000 patients.

Recurring sequences of genomic alterations occurring across patients can highlight repeated evolutionary processes with significant implications for predicting cancer progression. Leveraging the ever-increasing availability of cancer omics data, here we unveil cancer's evolutionary signatures tied to distinct disease outcomes, representing "favored trajectories" of acquisition of driver mutations detected in patients with similar prognosis. We present a framework named ASCETIC (Agony-baSed Cancer EvoluTion InferenCe) to extract such signatures from sequencing experiments generated by different technologies such as bulk and single-cell sequencing data. We apply ASCETIC to (i) single-cell data from 146 myeloid malignancy patients and bulk sequencing from 366 acute myeloid leukemia patients, (ii) multi-region sequencing from 100 early-stage lung cancer patients, (iii) exome/genome data from 10,000+ Pan-Cancer Atlas samples, and (iv) targeted sequencing from 25,000+ MSK-MET metastatic patients, revealing subtype-specific single-nucleotide variant signatures associated with distinct prognostic clusters. Validations on several datasets underscore the robustness and generalizability of the extracted signatures.

Systematic evaluation of genome sequencing for the diagnostic assessment of autism spectrum disorder and fetal structural anomalies.

Short-read genome sequencing (GS) holds the promise of becoming the primary diagnostic approach for the assessment of autism spectrum disorder (ASD) and fetal structural anomalies (FSAs). However, few studies have comprehensively evaluated its performance against current standard-of-care diagnostic tests: karyotype, chromosomal microarray (CMA), and exome sequencing (ES). To assess the clinical utility of GS, we compared its diagnostic yield against these three tests in 1,612 quartet families including an individual with ASD and in 295 prenatal families. Our GS analytic framework identified a diagnostic variant in 7.8% of ASD probands, almost 2-fold more than CMA (4.3%) and 3-fold more than ES (2.7%). However, when we systematically captured copy-number variants (CNVs) from the exome data, the diagnostic yield of ES (7.4%) was brought much closer to, but did not surpass, GS. Similarly, we estimated that GS could achieve an overall diagnostic yield of 46.1% in unselected FSAs, representing a 17.2% increased yield over karyotype, 14.1% over CMA, and 4.1% over ES with CNV calling or 36.1% increase without CNV discovery. Overall, GS provided an added diagnostic yield of 0.4% and 0.8% beyond the combination of all three standard-of-care tests in ASD and FSAs, respectively. This corresponded to nine GS unique diagnostic variants, including sequence variants in exons not captured by ES, structural variants (SVs) inaccessible to existing standard-of-care tests, and SVs where the resolution of GS changed variant classification. Overall, this large-scale evaluation demonstrated that GS significantly outperforms each individual standard-of-care test while also outperforming the combination of all three tests, thus warranting consideration as the first-tier diagnostic approach for the assessment of ASD and FSAs.

Congenital disorders of glycosylation: narration of a story through its patents.

Congenital disorders of glycosylation are a group of more than 160 rare genetic defects in protein and lipid glycosylation. Since the first clinical report in 1980 of PMM2-CDG, the most common CDG worldwide, research made great strides, but nearly all of them are still missing a cure. CDG diagnosis has been at a rapid pace since the introduction of whole-exome/whole-genome sequencing as a diagnostic tool. Here, we retrace the history of CDG by analyzing all the patents associated with the topic. To this end, we explored the Espacenet database, extracted a list of patents, and then divided them into three major groups: (1) Drugs/therapeutic approaches for CDG, (2) Drug delivery tools for CDG, (3) Diagnostic tools for CDG. Despite the enormous scientific progress experienced in the last 30 years, diagnostic tools, drugs, and biomarkers are still urgently needed.

Analytic validation of NeXT Dx™, a comprehensive genomic profiling assay.

We describe the analytic validation of NeXT Dx, a comprehensive genomic profiling assay to aid therapy and clinical trial selection for patients diagnosed with solid tumor cancers. Proprietary methods were utilized to perform whole exome and whole transcriptome sequencing for detection of single nucleotide variants (SNVs), insertions/deletions (indels), copy number alterations (CNAs), and gene fusions, and determination of tumor mutation burden and microsatellite instability. Variant calling is enhanced by sequencing a patient-specific normal sample from, for example, a blood specimen. This provides highly accurate somatic variant calls as well as the incidental reporting of pathogenic and likely pathogenic germline alterations. Fusion detection via RNA sequencing provides more extensive and accurate fusion calling compared to DNA-based tests. NeXT Dx features the proprietary Accuracy and Content Enhanced technology, developed to optimize sequencing and provide more uniform coverage across the exome. The exome was validated at a median sequencing depth of >500x. While variants from 401 cancer-associated genes are currently reported from the assay, the exome/transcriptome assay is broadly validated to enable reporting of additional variants as they become clinically relevant. NeXT Dx demonstrated analytic sensitivities as follows: SNVs (99.4%), indels (98.2%), CNAs (98.0%), and fusions (95.8%). The overall analytic specificity was >99.0%.

Whole-Exome and Transcriptome Sequencing Expands the Genotype of Majewski Osteodysplastic Primordial Dwarfism Type II.

Microcephalic Osteodysplastic Primordial Dwarfism type II (MOPDII) represents the most common form of primordial dwarfism. MOPD clinical features include severe prenatal and postnatal growth retardation, postnatal severe microcephaly, hypotonia, and an increased risk for cerebrovascular disease and insulin resistance. Autosomal recessive biallelic loss-of-function genomic variants in the centrosomal pericentrin (PCNT) gene on chromosome 21q22 cause MOPDII. Over the past decade, exome sequencing (ES) and massive RNA sequencing have been effectively employed for both the discovery of novel disease genes and to expand the genotypes of well-known diseases. In this paper we report the results both the RNA sequencing and ES of three patients affected by MOPDII with the aim of exploring whether differentially expressed genes and previously uncharacterized gene variants, in addition to PCNT pathogenic variants, could be associated with the complex phenotype of this disease. We discovered a downregulation of key factors involved in growth, such as IGF1R, IGF2R, and RAF1, in all three investigated patients. Moreover, ES identified a shortlist of genes associated with deleterious, rare variants in MOPDII patients. Our results suggest that Next Generation Sequencing (NGS) technologies can be successfully applied for the molecular characterization of the complex genotypic background of MOPDII.

Beyond the exome: What's next in diagnostic testing for Mendelian conditions.

Despite advances in clinical genetic testing, including the introduction of exome sequencing (ES), more than 50% of individuals with a suspected Mendelian condition lack a precise molecular diagnosis. Clinical evaluation is increasingly undertaken by specialists outside of clinical genetics, often occurring in a tiered fashion and typically ending after ES. The current diagnostic rate reflects multiple factors, including technical limitations, incomplete understanding of variant pathogenicity, missing genotype-phenotype associations, complex gene-environment interactions, and reporting differences between clinical labs. Maintaining a clear understanding of the rapidly evolving landscape of diagnostic tests beyond ES, and their limitations, presents a challenge for non-genetics professionals. Newer tests, such as short-read genome or RNA sequencing, can be challenging to order, and emerging technologies, such as optical genome mapping and long-read DNA sequencing, are not available clinically. Furthermore, there is no clear guidance on the next best steps after inconclusive evaluation. Here, we review why a clinical genetic evaluation may be negative, discuss questions to be asked in this setting, and provide a framework for further investigation, including the advantages and disadvantages of new approaches that are nascent in the clinical sphere. We present a guide for the next best steps after inconclusive molecular testing based upon phenotype and prior evaluation, including when to consider referral to research consortia focused on elucidating the underlying cause of rare unsolved genetic disorders.

Uncovering the phenotypic consequences of multi-locus imprinting disturbances using genome-wide methylation analysis in genomic imprinting disorders.

Imprinted genes are regulated by DNA methylation of imprinted differentially methylated regions (iDMRs). An increasing number of patients with congenital imprinting disorders (IDs) exhibit aberrant methylation at multiple imprinted loci, multi-locus imprinting disturbance (MLID). We examined MLID and its possible impact on clinical features in patients with IDs. Genome-wide DNA methylation analysis (GWMA) using blood leukocyte DNA was performed on 13 patients with Beckwith-Wiedemann syndrome (BWS), two patients with Silver-Russell syndrome (SRS), and four controls. HumanMethylation850 BeadChip analysis for 77 iDMRs (809 CpG sites) identified three patients with BWS and one patient with SRS showing additional hypomethylation, other than the disease-related iDMRs, suggestive of MLID. Two regions were aberrantly methylated in at least two patients with BWS showing MLID: PPIEL locus (chromosome 1: 39559298 to 39559744), and FAM50B locus (chromosome 6: 3849096 to 3849469). All patients with BWS- and SRS-MLID did not show any other clinical characteristics associated with additional involved iDMRs. Exome analysis in three patients with BWS who exhibited multiple hypomethylation did not identify any causative variant related to MLID. This study indicates that a genome-wide approach can unravel MLID in patients with an apparently isolated ID. Patients with MLID showed only clinical features related to the original IDs. Long-term follow-up studies in larger cohorts are warranted to evaluate any possible phenotypic consequences of other disturbed imprinted loci.

Uncovering a new SASH1 mutation associated with dyschromatosis universalis hereditaria using whole-exome-sequencing: A case report.

RATIONALE: Dyschromatosis universalis hereditaria (DUH) is an uncommon form of pigmented genodermatosis that is typically inherited autosomally and dominantly. In the previous study, the pathogenic genes of DUH have been identified in ATP-binding cassette subfamily B, member 6 and SASH1. However, the mutational screening of the causative gene remains incomplete and still lacks sufficient proof in the etiology. PATIENT CONCERNS: A 2-generation Chinese family clinically diagnosed with DUH were enrolled. They showed pigmented spots from their childhood and came to the hospital for medical advice and genetic analysis. We found a novel mutation c.1757T > C (p.I586T) of SASH1 in 3 affected family members by whole-exome sequencing. DIAGNOSES: Genetic outcomes and clinical examinations confirmed the diagnosis of DUH in 3 family members with lentiginous syndrome. INTERVENTIONS AND OUTCOMES: Using whole-exome sequencing and sanger sequencing technologies, we identified a novel mutation c.1757T > C (p.I586T) of SASH1 that co-segregated in 3 afflicted family members but not in the normal individuals. Significantly, c.1757T > C (p.I586T) is a novel mutation which had not been previously reported. The same codon position in SASH1 (c.1758C > G, p.I586M) has been reported in a Japanese man, and he showed identical phenotype compared to our study participants. LESSONS: Our study broadens the spectrum of DUH mutations and provides more genetic characteristics of DUH in understanding its etiology. Furthermore, we demonstrated the diagnostic accuracy of whole-exome sequencing for inherited skin diseases and provided new information for etiological study.

Evaluation of an optimized germline exomes pipeline using BWA-MEM2 and Dragen-GATK tools.

The next-generation sequencing (NGS) technology represents a significant advance in genomics and medical diagnosis. Nevertheless, the time it takes to perform sequencing, data analysis, and variant interpretation is a bottleneck in using next-generation sequencing in precision medicine. For accurate and efficient performance in clinical diagnostic lab practice, a consistent data analysis pipeline is necessary to avoid false variant calls and achieve optimum accuracy. This study aims to compare the performance of two NGS data analysis pipeline compartments, including short-read mapping (BWA-MEM and BWA-MEM2) and variant calling (GATK-HaplotypeCaller and DRAGEN-GATK). On Whole Exome Sequencing (WES) data, computational performance was assessed using several criteria, including mapping efficiency, variant calling performance, false positive calls rate, and time. We examined four gold-standard WES data sets: Ashkenazim father (NA24149), Ashkenazim mother (NA24143), Ashkenazim son (NA24385), and Asian son (NA25631). In addition, eighteen exome samples were analyzed based on different read counts, and coverage was used precisely in the run-time assessment. By using BWA-MEM 2 and Dragen-GATK, this study achieved faster and more accurate detection for SNVs and indels than the standard GATK Best Practices workflow. This systematic comparison will enable the bioinformatics community to develop a more efficient and faster solution for analyzing NGS data.

Whole exome data prioritization unveils the hidden weight of Mendelian causes of male infertility. A report from the first Italian cohort.

Almost 40% of infertile men cases are classified as idiopathic when tested negative to the current diagnostic routine based on the screening of karyotype, Y chromosome microdeletions and CFTR mutations in men with azoospermia or oligozoospermia. Rare monogenic forms of infertility are not routinely evaluated. In this study we aim to investigate the unknown potential genetic causes in couples with pure male idiopathic infertility by applying variant prioritization to whole exome sequencing (WES) in a cohort of 99 idiopathic Italian patients. The ad-hoc manually curated gene library prioritizes genes already known to be associated with more common and rare syndromic and non-syndromic male infertility forms. Twelve monogenic cases (12.1%) were identified in the whole cohort of patients. Of these, three patients had variants related to mild androgen insensitivity syndrome, two in genes related to hypogonadotropic hypogonadism, and six in genes related to spermatogenic failure, while one patient is mutant in PKD1. These results suggest that NGS combined with our manually curated pipeline for variant prioritization and classification can uncover a considerable number of Mendelian causes of infertility even in a small cohort of patients.

Diagnostic implications of pitfalls in causal variant identification based on 4577 molecularly characterized families.

Despite large sequencing and data sharing efforts, previously characterized pathogenic variants only account for a fraction of Mendelian disease patients, which highlights the need for accurate identification and interpretation of novel variants. In a large Mendelian cohort of 4577 molecularly characterized families, numerous scenarios in which variant identification and interpretation can be challenging are encountered. We describe categories of challenges that cover the phenotype (e.g. novel allelic disorders), pedigree structure (e.g. imprinting disorders masquerading as autosomal recessive phenotypes), positional mapping (e.g. double recombination events abrogating candidate autozygous intervals), gene (e.g. novel gene-disease assertion) and variant (e.g. complex compound inheritance). Overall, we estimate a probability of 34.3% for encountering at least one of these challenges. Importantly, our data show that by only addressing non-sequencing-based challenges, around 71% increase in the diagnostic yield can be expected. Indeed, by applying these lessons to a cohort of 314 cases with negative clinical exome or genome reports, we could identify the likely causal variant in 54.5%. Our work highlights the need to have a thorough approach to undiagnosed diseases by considering a wide range of challenges rather than a narrow focus on sequencing technologies. It is hoped that by sharing this experience, the yield of undiagnosed disease programs globally can be improved.

Integrative omics approaches to advance rare disease diagnostics.

Over the past decade high-throughput DNA sequencing approaches, namely whole exome and whole genome sequencing became a standard procedure in Mendelian disease diagnostics. Implementation of these technologies greatly facilitated diagnostics and shifted the analysis paradigm from variant identification to prioritisation and evaluation. The diagnostic rates vary widely depending on the cohort size, heterogeneity and disease and range from around 30% to 50% leaving the majority of patients undiagnosed. Advances in omics technologies and computational analysis provide an opportunity to increase these unfavourable rates by providing evidence for disease-causing variant validation and prioritisation. This review aims to provide an overview of the current application of several omics technologies including RNA-sequencing, proteomics, metabolomics and DNA-methylation profiling for diagnostics of rare genetic diseases in general and inborn errors of metabolism in particular.