Disease gene identification strategies for exome sequencing

Expanding the phenotypic spectrum of LIG4 pathogenic variations: neuro-histopathological description of 4 fetuses with stenosis of the aqueduct

Severe ventriculomegaly is a rare congenital brain defect, usually detected in utero, of poor neurodevelopmental prognosis. This ventricular enlargement can be the consequence of different mechanisms: either by a disruption of the cerebrospinal fluid circulation or abnormalities of its production/absorption. The aqueduct stenosis is one of the most frequent causes of obstructive ventriculomegaly, however, fewer than 10 genes have been linked to this condition and molecular bases remain often unknown. We report here 4 fetuses from 2 unrelated families presenting with ventriculomegaly at prenatal ultra-sonography as well as an aqueduct stenosis and skeletal abnormalities as revealed by fetal autopsy. Genome sequencing identified biallelic pathogenic variations in LIG4, a DNA-repair gene responsible for the LIG4 syndrome which associates a wide range of clinical manifestations including developmental delay, microcephaly, short stature, radiation hypersensitivity and immunodeficiency. Thus, not only this report expands the phenotype spectrum of LIG4-related disorders, adding ventriculomegaly due to aqueduct stenosis, but we also provide the first neuropathological description of fetuses carrying LIG4 pathogenic biallelic variations.

Global research landscape on the contribution of de novo mutations to human genetic diseases over the past 20 years: bibliometric analysis

As the contribution of de novo mutations (DNMs) to human genetic diseases has been gradually uncovered, analyzing the global research landscape over the past 20 years is essential. Because of the large and rapidly increasing number of publications in this field, understanding the current landscape of the contribution of DNMs in the human genome to genetic diseases remains a challenge. Bibliometric analysis provides an approach for visualizing these studies using information in published records in a specific field. This study aimed to illustrate the current global research status and explore trends in the field of DNMs underlying genetic diseases. Bibliometric analyses were performed using the Bibliometrix Package based on the R language version 4.1.3 and CiteSpace version 6.1.R2 software for publications from 2000 to 2021 indexed under the Web of Science Core Collection (WoSCC) about DNMs underlying genetic diseases on 17 September 2022. We identified 3435 records, which were published in 731 journals by 26,538 authors from 6052 institutes in 66 countries. There was an upward trend in the number of publications since 2013. The USA, China, and Germany contributed the majority of the records included. The University of Washington, Columbia University, and Baylor College of Medicine were the top-producing institutions. Evan E Eichler of the University of Washington, Stephan J Sanders of the Yale University School of Medicine, and Ingrid E Scheffer of the University of Melbourne were the most high-ranked authors. Keyword co-occurrence analysis suggested that DNMs in neurodevelopmental disorders and intellectual disabilities were research hotspots and trends. In conclusion, our data show that DNMs have a significant effect on human genetic diseases, with a noticeable increase in annual publications over the last 5 years. Furthermore, potential hotspots are shifting toward understanding the causative role and clinical interpretation of newly identified or low-frequency DNMs observed in patients.

Most Monogenic Disorders Are Caused by Mutations Altering Protein Folding Free Energy

Revealing the molecular effect that pathogenic missense mutations have on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast targeted drug development at a low cost. Here, we report an updated database of monogenic disorders (MOGEDO), which includes 768 proteins and the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG, but do not make protein over-stable, since over-stable protein may be dysfunctional. We demonstrate that, by using ΔΔG and predicted solvent exposure of the mutation site, one can develop a predictive method that distinguishes pathogenic from benign mutations with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic-hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp, and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.

Next-generation sequencing and bioinformatics in rare movement disorders

The ability to sequence entire exomes and genomes has revolutionized molecular testing in rare movement disorders, and genomic sequencing is becoming an integral part of routine diagnostic workflows for these heterogeneous conditions. However, interpretation of the extensive genomic variant information that is being generated presents substantial challenges. In this Perspective, we outline multidimensional strategies for genetic diagnosis in patients with rare movement disorders. We examine bioinformatics tools and computational metrics that have been developed to facilitate accurate prioritization of disease-causing variants. Additionally, we highlight community-driven data-sharing and case-matchmaking platforms, which are designed to foster the discovery of new genotype-phenotype relationships. Finally, we consider how multiomic data integration might optimize diagnostic success by combining genomic, epigenetic, transcriptomic and/or proteomic profiling to enable a more holistic evaluation of variant effects. Together, the approaches that we discuss offer pathways to the improved understanding of the genetic basis of rare movement disorders.

A novel homozygote nonsense variant of MSH4 leads to primary ovarian insufficiency and non-obstructive azoospermia

BACKGROUND

Both non-obstructive azoospermia (NOA) and primary ovarian insufficiency (POI) are pathological conditions characterized by premature and frequently complete gametogenesis failure. Considering that the conserved meiosis I steps are the same between oogenesis and spermatogenesis, inherited defects in meiosis I may result in common causes for both POI and NOA. The present research is a retrospective investigation on an Iranian family with four siblings of both genders who were affected by primary gonadal failure.

METHODS

Proband, an individual with NOA, was subjected to clinical examination, hormonal assessment, and genetic consultation. After reviewing the medical history of other infertile members of the family, patients with NOA went through genetic investigations including karyotyping and assessment of Y chromosome microdeletions, followed by Whole exome sequencing (WES) on the proband. After analyzing WES data, the candidate variant was validated using Sanger sequencing and traced in the family.

RESULTS

WES analysis of the proband uncovered a novel homozygote nonsense variant, namely c.118C>T in MSH4. This variant resulted in the occurrence of a premature stop codon in residue 40 of MSH4. Notably, the variant was absent in all public exome databases and in the exome data of 400 fertile Iranian individuals. Additionally, the variant was found to co-segregate with infertility in the family. It was also observed that all affected members had homozygous mutations, while their parents were heterozygous and the fertile sister had no mutant allele, corresponding to autosomal recessive inheritance. In addition, we conducted a review of variants reported so far in MSH4, as well as available clinical features related to these variants. The results show that the testicular sperm retrieval and ovarian stimulation cycles have not been successful yet.

CONCLUSION

Overall, the results of this study indicate that the identification of pathogenic variants in this gene will be beneficial in selecting proper therapeutic strategies. Also, the findings of this study demonstrate that clinicians should obtain the history of other family members of the opposite sex when diagnosing for POI and/or NOA.

Genomic insights into heart health: Exploring the genetic basis of cardiovascular disease

Cardiovascular diseases (CVDs) are considered as the leading cause of death worldwide. CVD continues to be a major cause of death and morbidity despite significant improvements in its detection and treatment. Therefore, it is strategically important to be able to precisely characterize an individual's sensitivity to certain illnesses. The discovery of genes linked to cardiovascular illnesses has benefited from linkage analysis and genome-wide association research. The last 20 years have seen significant advancements in the field of molecular genetics, particularly with the development of new tools like genome-wide association studies. In this article we explore the profound impact of genetic variations on disease development, prognosis, and therapeutic responses. And the significance of genetics in cardiovascular risk assessment and the ever-evolving realm of genetic testing, offering insights into the potential for personalized medicine in this domain. Embracing the future of cardiovascular care, the article explores the implications of pharmacogenomics for tailored treatments, the promise of emerging technologies in cardiovascular genetics and therapies, including the transformative influence of nanotechnology. Furthermore, it delves into the exciting frontiers of gene editing, such as CRISPR/Cas9, as a novel approach to combat cardiovascular diseases. And also explore the potential of stem cell therapy and regenerative medicine, providing a holistic view of the dynamic landscape of cardiovascular genomics and its transformative potential for the field of cardiovascular medicine.

Utilizing immunogenomic approaches to prioritize targetable neoantigens for personalized cancer immunotherapy

Advancements in sequencing technologies and bioinformatics algorithms have expanded our ability to identify tumor-specific somatic mutation-derived antigens (neoantigens). While recent studies have shown neoantigens to be compelling targets for cancer immunotherapy due to their foreign nature and high immunogenicity, the need for increasingly accurate and cost-effective approaches to rapidly identify neoantigens remains a challenging task, but essential for successful cancer immunotherapy. Currently, gene expression analysis and algorithms for variant calling can be used to generate lists of mutational profiles across patients, but more care is needed to curate these lists and prioritize the candidate neoantigens most capable of inducing an immune response. A growing amount of evidence suggests that only a handful of somatic mutations predicted by mutational profiling approaches act as immunogenic neoantigens. Hence, unbiased screening of all candidate neoantigens predicted by Whole Genome Sequencing/Whole Exome Sequencing may be necessary to more comprehensively access the full spectrum of immunogenic neoepitopes. Once putative cancer neoantigens are identified, one of the largest bottlenecks in translating these neoantigens into actionable targets for cell-based therapies is identifying the cognate T cell receptors (TCRs) capable of recognizing these neoantigens. While many TCR-directed screening and validation assays have utilized bulk samples in the past, there has been a recent surge in the number of single-cell assays that provide a more granular understanding of the factors governing TCR-pMHC interactions. The goal of this review is to provide an overview of existing strategies to identify candidate neoantigens using genomics-based approaches and methods for assessing neoantigen immunogenicity. Additionally, applications, prospects, and limitations of some of the current single-cell technologies will be discussed. Finally, we will briefly summarize some of the recent models that have been used to predict TCR antigen specificity and analyze the TCR receptor repertoire.

Moving the Needle Forward in Genomically-Guided Precision Radiation Treatment

Radiation treatment (RT) is a mainstay treatment for many types of cancer. Recommendations for RT and the radiation plan are individualized to each patient, taking into consideration the patient's tumor pathology, staging, anatomy, and other clinical characteristics. Information on germline mutations and somatic tumor mutations is at present rarely used to guide specific clinical decisions in RT. Many genes, such as ATM, and BRCA1/2, have been identified in the laboratory to confer radiation sensitivity. However, our understanding of the clinical significance of mutations in these genes remains limited and, as individual mutations in such genes can be rare, their impact on tumor response and toxicity remains unclear. Current guidelines, including those from the National Comprehensive Cancer Network (NCCN), provide limited guidance on how genetic results should be integrated into RT recommendations. With an increasing understanding of the molecular underpinning of radiation response, genomically-guided RT can inform decisions surrounding RT dose, volume, concurrent therapies, and even omission to further improve oncologic outcomes and reduce risks of toxicities. Here, we review existing evidence from laboratory, pre-clinical, and clinical studies with regard to how genetic alterations may affect radiosensitivity. We also summarize recent data from clinical trials and explore potential future directions to utilize genetic data to support clinical decision-making in developing a pathway toward personalized RT.

Application of single-cell sequencing to the research of tumor microenvironment

Single-cell sequencing is a technique for detecting and analyzing genomes, transcriptomes, and epigenomes at the single-cell level, which can detect cellular heterogeneity lost in conventional sequencing hybrid samples, and it has revolutionized our understanding of the genetic heterogeneity and complexity of tumor progression. Moreover, the tumor microenvironment (TME) plays a crucial role in the formation, development and response to treatment of tumors. The application of single-cell sequencing has ushered in a new age for the TME analysis, revealing not only the blueprint of the pan-cancer immune microenvironment, but also the heterogeneity and differentiation routes of immune cells, as well as predicting tumor prognosis. Thus, the combination of single-cell sequencing and the TME analysis provides a unique opportunity to unravel the molecular mechanisms underlying tumor development and progression. In this review, we summarize the recent advances in single-cell sequencing and the TME analysis, highlighting their potential applications in cancer research and clinical translation.

Most monogenic disorders are caused by mutations altering protein folding free energy

Revealing the molecular effect that pathogenic missense mutations cause on the corresponding protein is crucial for developing therapeutic solutions. This is especially important for monogenic diseases since, for most of them, there is no treatment available, while typically, the treatment should be provided in the early development stages. This requires fast, targeted drug development at a low cost. Here, we report a database of monogenic disorders (MOGEDO), which includes 768 proteins, the corresponding 2559 pathogenic and 1763 benign mutations, along with the functional classification of the corresponding proteins. Using the database and various computational tools that predict folding free energy change (ΔΔG), we demonstrate that, on average, 70% of pathogenic cases result in decreased protein stability. Such a large fraction indicates that one should aim at in-silico screening for small molecules stabilizing the structure of the mutant protein. We emphasize that knowledge of ΔΔG is essential because one wants to develop stabilizers that compensate for ΔΔG but not to make protein over-stable since over-stable protein may be dysfunctional. We demonstrate that using ΔΔG and predicted solvent exposure of the mutation site; one can develop a predictive method that distinguishes pathogenic from benign mutation with a success rate even better than some of the leading pathogenicity predictors. Furthermore, hydrophobic-hydrophobic mutations have stronger correlations between folding free energy change and pathogenicity compared with others. Also, mutations involving Cys, Gly, Arg, Trp and Tyr amino acids being replaced by any other amino acid are more likely to be pathogenic. To facilitate further detection of pathogenic mutations, the wild type of amino acids in the 768 proteins mentioned above was mutated to other 19 residues (14,847,817 mutations), and the ΔΔG was calculated with SAAFEC-SEQ, and 5,506,051 mutations were predicted to be pathogenic.

Model of neural development by differentiating human induced pluripotent stem cells into neural progenitor cells to study the neurodevelopmental toxicity of lead

Lead (Pb) exposure causes immeasurable damage to multiple human systems, particularly the central nervous system (CNS). In this study, human induced pluripotent stem cells (hiPSCs) were differentiated into neural progenitor cells (NPCs) to investigate the neurotoxic effects of Pb. The hiPSCs were treated with 0, 0.5, 1.0, 2.5, 5.0 and 10.0 μmol/L Pb for 7 days, whereas embryoid bodies (EBs) and NPCs were treated with 0, 0.1, 0.5, and 1.0 μmol/L Pb for 7 days. Pb exposure disrupted the cell cycle and caused apoptosis in hiPSCs, EBs, and NPCs. Besides, Pb inhibited the differentiation of NPCs and EBs. Whole exome sequencing revealed 2509, 2413, and 1984 single nucleotide variants (SNVs) caused by Pb in hiPSCs, EBs, and NPCs, respectively. The common mutation sites in the exon region were mostly nonsynonymous mutations. We identified 18, 19, and 18 common deleterious mutations in hiPSCs, EBs, and NPCs, respectively. Additionally, Online Mendelian Inheritance in Man database analysis revealed 30, 20, and 13 genes related to CNS disorders in hiPSCs, EBs, and NPCs, respectively. Our findings suggest that this in vitro model may supplement animal models and be applied to the study of neurodevelopmental toxicity in the future.

Meiotic Chromosome Structure, the Synaptonemal Complex, and Infertility

In meiosis, homologous chromosome synapsis is mediated by a supramolecular protein structure, the synaptonemal complex (SC), that assembles between homologous chromosome axes. The mammalian SC comprises at least eight largely coiled-coil proteins that interact and self-assemble to generate a long, zipper-like structure that holds homologous chromosomes in close proximity and promotes the formation of genetic crossovers and accurate meiotic chromosome segregation. In recent years, numerous mutations in human SC genes have been associated with different types of male and female infertility. Here, we integrate structural information on the human SC with mouse and human genetics to describe the molecular mechanisms by which SC mutations can result in human infertility. We outline certain themes in which different SC proteins are susceptible to different types of disease mutation and how genetic variants with seemingly minor effects on SC proteins may act as dominant-negative mutations in which the heterozygous state is pathogenic.

Comparative yield of molecular diagnostic algorithms for autism spectrum disorder diagnosis in India: evidence supporting whole exome sequencing as first tier test

BACKGROUND

Autism spectrum disorder (ASD) affects 1 in 100 children globally with a rapidly increasing prevalence. To the best of our knowledge, no data exists on the genetic architecture of ASD in India. This study aimed to identify the genetic architecture of ASD in India and to assess the use of whole exome sequencing (WES) as a first-tier test instead of chromosomal microarray (CMA) for genetic diagnosis.

METHODS

Between 2020 and 2022, 101 patient-parent trios of Indian origin diagnosed with ASD according to the Diagnostic and Statistical Manual, 5th edition, were recruited. All probands underwent a sequential genetic testing pathway consisting of karyotyping, Fragile-X testing (in male probands only), CMA and WES. Candidate variant validation and parental segregation analysis was performed using orthogonal methods.

RESULTS

Of 101 trios, no probands were identified with a gross chromosomal anomaly or Fragile-X. Three (2.9%) and 30 (29.7%) trios received a confirmed genetic diagnosis from CMA and WES, respectively. Amongst diagnosis from WES, SNVs were detected in 27 cases (90%) and CNVs in 3 cases (10%), including the 3 CNVs detected from CMA. Segregation analysis showed 66.6% (n = 3 for CNVs and n = 17 for SNVs) and 16.6% (n = 5) of the cases had de novo and recessive variants respectively, which is in concordance with the distribution of variant types and mode of inheritance observed in ASD patients of non-Hispanic white/ European ethnicity. MECP2 gene was the most recurrently mutated gene (n = 6; 20%) in the present cohort. Majority of the affected genes identified in the study cohort are involved in synaptic formation, transcription and its regulation, ubiquitination and chromatin remodeling.

CONCLUSIONS

Our study suggests de novo variants as a major cause of ASD in the Indian population, with Rett syndrome as the most commonly detected disorder. Furthermore, we provide evidence of a significant difference in the diagnostic yield between CMA (3%) and WES (30%) which supports the implementation of WES as a first-tier test for genetic diagnosis of ASD in India.

The causal mutation in ARR3 gene for high myopia and progressive color vision defect

The ARR3 gene, also known as cone arrestin, belongs to the arrestin family and is expressed in cone cells, inactivating phosphorylated-opsins and preventing cone signals. Variants of ARR3 reportedly cause X-linked dominant female-limited early-onset (age < 7 years old) high myopia (< - 6D). Here, we reveal a new mutation (c.228T>A, p.Tyr76*) in ARR3 gene that can cause early-onset high myopia (eoHM) limited to female carriers. Protan/deutan color vision defects were also found in family members, affecting both genders. Using ten years of clinical follow-up data, we identified gradually worsening cone dysfunction/color vision as a key feature among affected individuals. We present a hypothesis that higher visual contrast due to the mosaic of mutated ARR3 expression in cones contributes to the development of myopia in female carriers.

Parkinson's disease - genetic cause

PURPOSE OF REVIEW

Our knowledge of the genetic architecture underlying Parkinson's disease has vastly improved in the past quarter century. About 5-10% of all patients suffer from a monogenic form of Parkinson's disease.

RECENT FINDINGS

Mutations in autosomal dominant genes (e.g. SNCA, LRRK2, VPS35) or autosomal recessive genes (e.g. PRKN, PINK1, DJ-1) can cause genetic Parkinson's disease. Recessive DNAJC6 mutations can present predominantly as atypical parkinsonism, but also rarely as typical Parkinson's disease. Majority of Parkinson's disease is genetically complex. Mutation in RIC3, a chaperone of neuronal nicotinic acetylcholine receptor subunit α-7 (CHRNA7), provides strong evidence for the role of cholinergic pathway, for the first time, in cause of Parkinson's disease. X-linked parkinsonism manifests at a young age accompanied by many (atypical) features such as intellectual disability, spasticity, seizures, myoclonus, dystonia, and have poor response to levodopa.

SUMMARY

This review article aims to provide a comprehensive overview on Parkinson's disease genetics. MAPT, which encodes the microtubule associated protein tau, TMEM230, LRP10, NUS1 and ARSA are the five new putative disease-causing genes in Parkinson's disease. The validation of novel genes and its association with Parkinson's disease remains extremely challenging, as genetically affected families are sparse and globally widespread. In the near future, genetic discoveries in Parkinson's disease will influence our ability to predict and prognosticate the disease, help in defining etiological subtypes that are critical in implementation of precision medicine.

Exome sequencing of choreoacanthocytosis reveals novel mutations in VPS13A and co-mutation in modifier gene(s)

Choreoacanthocytosis, one of the forms of neuroacanthocytosis, is caused by mutations in vacuolar protein sorting-associated protein A (VPS13A), and is often misdiagnosed with other form of neuroacanthocytosis with discrete genetic defects. The phenotypic variations among the patients with VPS13A mutations significantly obfuscates the understanding of the disease and treatment strategies. In this study, two unrelated cases were identified, exhibiting the core phenotype of neuroacanthocytosis but with considerable clinical heterogeneity. Case 1 presented with an additional Parkinsonism phenotype, whereas seizures were evident in case 2. To decipher the genetic basis, whole exome sequencing followed by validation with Sanger sequencing was performed. A known homozygous pathogenic nonsense mutation (c.799C > T; p.R267X) in exon 11 of the VPS13A gene was identified in case 1 that resulted in a truncated protein. A novel missense mutation (c.9263T > G; p.M3088R) in exon 69 of VPS13A identified in case 2 was predicted as pathogenic. In silico analysis of the p.M3088R mutation at the C-terminus of VPS13A suggests a loss of interaction with TOMM40 and may disrupt mitochondrial localization. We also observed an increase in mitochondrial DNA copy numbers in case 2. Mutation analysis revealed benign heterozygous variants in interacting partners of VPS13A such as VAPA in case 1. Our study confirmed the cases as ChAc and identified the novel homozygous variant of VPS13A (c.9263T > G; p.M3088R) within the mutation spectrum of VPS13A-associated ChAc. Furthermore, mutations in VPS13A and co-mutations in its potential interacting partner(s) might contribute to the diverse clinical manifestations of ChAc, which requires further study.

Clinical genetics of Charcot-Marie-Tooth disease

Recent research in the field of inherited peripheral neuropathies (IPNs) such as Charcot-Marie-Tooth (CMT) disease has helped identify the causative genes provided better understanding of the pathogenesis, and unraveled potential novel therapeutic targets. Several reports have described the epidemiology, clinical characteristics, molecular pathogenesis, and novel causative genes for CMT/IPNs in Japan. Based on the functions of the causative genes identified so far, the following molecular and cellular mechanisms are believed to be involved in the causation of CMTs/IPNs: myelin assembly, cytoskeletal structure, myelin-specific transcription factor, nuclear related, endosomal sorting and cell signaling, proteasome and protein aggregation, mitochondria-related, motor proteins and axonal transport, tRNA synthetases and RNA metabolism, and ion channel-related mechanisms. In this article, we review the epidemiology, genetic diagnosis, and clinicogenetic characteristics of CMT in Japan. In addition, we discuss the newly identified novel causative genes for CMT/IPNs in Japan, namely MME and COA7. Identification of the new causes of CMT will facilitate in-depth characterization of the underlying molecular mechanisms of CMT, leading to the establishment of therapeutic approaches such as drug development and gene therapy.

Genetic Variant Overlap Analysis Identifies Established and Putative Genes Involved in Pulmonary Fibrosis

In only around 40% of families with pulmonary fibrosis (PF) a suspected genetic cause can be found. Genetic overlap analysis of Whole Exome Sequencing (WES) data may be a powerful tool to discover new shared variants in novel genes for PF. As a proof of principle, we first selected unrelated PF patients for whom a genetic variant was detected (n = 125) in established PF genes and searched for overlapping variants. Second, we performed WES (n = 149) and identified novel potentially deleterious variants shared by at least two unrelated PF patients. These variants were genotyped in validation cohorts (n = 2748). In 125 unrelated patients, a potentially deleterious variant was detected in known PF genes of which 15 variants in six genes overlapped, involving 51 patients. Overlap analysis of WES data identified two novel variants of interest: TOM1L2 c.421T > C p.(Y141H) and TDP1c.1373dupG p.(S459fs*5), neither gene had been related to pulmonary fibrosis before. Both proteins were present in the alveolar epithelium. No apparent characteristics of telomere disease were observed. This study underlines the potential of searching for overlapping rare potentially deleterious variants to identify disease-associated variants and genes. A previously unreported variant was found in two putative new PF genes, but further research is needed to determine causality.

Identification of potentially pathogenic variants for autism spectrum disorders using gene-burden analysis

Gene- burden analyses have lately become a very successful way for the identification of genes carrying risk variants underlying the analysed disease. This approach is also suitable for complex disorders like autism spectrum disorder (ASD). The gene-burden analysis using Testing Rare Variants with Public Data (TRAPD) software was conducted on whole exome sequencing data of Slovenian patients with ASD to determine potentially novel disease risk variants in known ASD-associated genes as well as in others. To choose the right control group for testing, principal component analysis based on the 1000 Genomes and ASD cohort samples was conducted. The subsequent protein structure and ligand binding analysis usingI-TASSER package were performed to detect changes in protein structure and ligand binding to determine a potential pathogenic consequence of observed mutation. The obtained results demonstrate an association of two variants-p.Glu198Lys (PPP2R5D:c.592G>A) and p.Arg253Gln (PPP2R5D:c.758G>A) with the ASD. Substitution p.Glu198Lys (PPP2R5D:c.592G>A) is a variant, previously described as pathogenic in association with ASD combined with intellectual disability, whereas p.Arg253Gln (PPP2R5D:c.758G>A) has not been described as an ASD-associated pathogenic variant yet. The results indicate that the filtering process was suitable and could be used in the future for detection of novel pathogenic variants when analysing groups of ASD patients.

Whole exome sequencing identifies two novel variants in PHEX and DMP1 in Malaysian children with hypophosphatemic rickets

BACKGROUND

Hypophosphatemic rickets (HR) is a genetic disease of phosphate wasting that is characterized by defective bone mineralization. The most common cause of the disease is mutations in the phosphate regulating gene with homologies to endopeptidases on the X chromosome (PHEX) gene. The aims of this study were to identify the gene variants responsible for HR in three cases of Malaysian origin from three independent families and to describe their clinical, biochemical, and radiological features.

METHODS

Whole exome sequencing (WES) was performed on all patients and their parents, followed by Sanger sequencing validation. Bioinformatics tools were used to provide supporting evidence for pathogenicity of variants. To confirm that a mutation is de novo, paternity test was carried out. High resolution melting curve analysis was performed to assess the allele frequency in normal controls for mutations that were found in the patients.

RESULTS

The patients showed typical characteristics of HR including lower limb deformity, hypophosphatemia, and elevated alkaline phosphatase. WES revealed two variants in the PHEX gene and one variant in the dentin matrix protein 1 (DMP1) gene. Two of the three variants were novel, including c.1946_1954del (p.Gly649_Arg651del) in PHEX and c.54 + 1G > A in DMP1. Our data suggests that the novel p.Gly649_Arg651del variant is likely pathogenic for HR disease.

CONCLUSIONS

This study extends the variant spectrum of the PHEX and DMP1 genes. Our findings indicate that WES is an advantageous approach for diagnosis of genetic diseases which are heterogeneous.

Whole-Exome Sequencing Revealed New Candidate Genes for Human Dilated Cardiomyopathy

Dilated cardiomyopathy (DCM) is a complex disease affecting young adults. It is a pathological condition impairing myocardium activity that leads to heart failure and, in the most severe cases, transplantation, which is currently the only possible therapy for the disease. DCM can be attributed to many genetic determinants interacting with environmental factors, resulting in a highly variable phenotype. Due to this complexity, the early identification of causative gene mutations is an important goal to provide a genetic diagnosis, implement pre-symptomatic interventions, and predict prognosis. The advent of next-generation sequencing (NGS) has opened a new path for mutation screening, and exome sequencing provides a promising approach for identifying causal variants in known genes and novel disease-associated candidates. We analyzed the whole-exome sequencing (WES) of 15 patients affected by DCM without overloading (hypertension, valvular, or congenital heart disease) or chronic ischemic conditions. We identified 70 pathogenic or likely pathogenic variants and 1240 variants of uncertain clinical significance. Gene ontology enrichment analysis was performed to assess the potential connections between affected genes and biological or molecular function, identifying genes directly related to extracellular matrix organization, transcellular movement through the solute carrier and ATP-binding cassette transporter, and vitamin B12 metabolism. We found variants in genes implicated to a different extent in cardiac function that may represent new players in the complex genetic scenario of DCM.

A Study on the Prediction of Cancer Using Whole-Genome Data and Deep Learning

The number of patients diagnosed with cancer continues to increasingly rise, and has nearly doubled in 20 years. Therefore, predicting cancer occurrence has a significant impact on reducing medical costs, and preventing cancer early can increase survival rates. In the data preprocessing step, since individual genome data are used as input data, they are classified as individual genome data. Subsequently, data embedding is performed in character units, so that it can be used in deep learning. In the deep learning network schema, using preprocessed data, a character-based deep learning network learns the correlation between individual feature data and predicts cancer occurrence. To evaluate the objective reliability of the method proposed in this study, various networks published in other studies were compared and evaluated using the TCGA dataset. As a result of comparing various networks published in other studies using the same data, excellent results were obtained in terms of accuracy, sensitivity, and specificity. Thus, the superiority of the effectiveness of deep learning networks in predicting cancer occurrence using individual whole-genome data was demonstrated. From the results of the confusion matrix, the validity of the model for predicting the cancer using an individual’s whole-genome data and the deep learning proposed in this study was proven. In addition, the AUC, which is the area under the ROC curve, which judges the efficiency of diagnosis as a performance evaluation index of the model, was found to be 90% or more, good classification results were derived. The objectives of this study were to use individual genome data for 12 cancers as input data to analyze the whole genome pattern, and to not separately use reference genome sequence data of normal individuals. In addition, several mutation types, including SNV, DEL, and INS, were applied.

A performance evaluation study: Variant annotation tools - The enigma of clinical next generation sequencing (NGS) based genetic testing

Dramatically expanding our ability for clinical genetic testing for inherited conditions and complex diseases such as cancer, next generation sequencing (NGS) technologies are allowing for rapid interrogation of thousands of genes and identification of millions of variants. Variant annotation, the process of assigning functional information to DNA variants based on the standardized Human Genome Variation Society (HGVS) nomenclature, is a fundamental challenge in the analysis of NGS data that has led to the development of many bioinformatic algorithms. In this study, we evaluated the performance of 3 variant annotation tools: Alamut® Batch, Ensembl Variant Effect Predictor (VEP), and ANNOVAR, benchmarked by a manually curated ground-truth set of 298 variants from the medical exome database at the Molecular Diagnostics Laboratory at Lurie Children's Hospital. Of the 3 tools, VEP produces the most accurate variant annotations (HGVS nomenclature for 297 of the 298 variants) due to usage of updated gene transcript versions within the algorithm. Alamut® Batch called 296 of the 298 variants correctly; strikingly, ANNOVAR exhibited the greatest number of discrepancies (20 of the 298 variants, 93.3% concordance with ground-truth set). Adoption of validated methods of variant annotation is critical in post-analytical phases of clinical testing.

Whole-exome sequencing identified genes known to be responsible for retinitis pigmentosa in 28 Chinese families

PURPOSE

Retinitis pigmentosa (RP) is a group of highly heterogenetic inherited retinal degeneration diseases. Molecular genetic diagnosis of RP is quite challenging because of the complicated disease-causing mutation spectrum. The aim of this study was to explore the mutation spectrum in Chinese RP patients using next-generation sequencing technology and to explore the genotype-phenotype relationship.

METHOD

In this study, a cost-effective strategy using whole-exome sequencing (WES) was employed to address the genetic diagnosis of 28 RP families in China. One to two patients and zero to two healthy relatives were sequenced in each family. All mutations in WES data that passed through the filtering procedure were searched in relation to 662 gene defects that can cause vision-associated phenotypes (including 89 RP genes in the RetNet Database). All patients visiting the outpatient department received comprehensive ophthalmic examinations.

RESULT

Twenty-five putative pathogenic mutations of 12 genes were detected by WES and were all confirmed by Sanger sequencing in 20 (20/28, 71.4%) families, including the 12 following genes: USH2A, CYP4V2, PRPF31, RHO, RP1, CNGA1, CNGB1, EYS, PRPF3, RP2, RPGR, and TOPORS. Three families were rediagnosed as having Bietti crystalline dystrophy (BCD). USH2A (4/20, 20%) and CYP4V2 (3/20, 15%) were found to be the most frequent mutated genes. Seven novel mutations were identified in this research, including mutations in USH2A1, USH2A2, PRPF31, RP2, TOPORS, CNGB1, and RPGR. Phenotype and genotype relationships in the 12 RP genes were analyzed, which revealed later disease onset and more severe visual function defects in CYP4V2.

CONCLUSION

Twenty-five putative pathogenic mutations of 12 genes were detected by WES, and these were all confirmed by Sanger sequencing in 20 (20/28, 71.4%) families, including seven novel mutations. USH2A and CYP4V2 were found to be the most frequent genes in this research. Phenotype and genotype relationships were revealed, and the mutation spectrum of RP in Chinese populations was expanded in this research, which may benefit future cutting-edge therapies.

Genetic and Clinical Approach To Microcephaly: A 5-Year Single Center Experience

Microcephaly is a dysmorphic feature characterized by small head size more than two standard deviations below the mean for age, sex, and ethnicity. There are several etiological factors ranging from environmental toxins or infections to genetic disorders. We report clinical, radiological, and molecular genetic investigations of patients with microcephaly from a single center over 5-year period. There were 92 patients with a genetic diagnosis. Based on their genetic diagnosis, we grouped patients into three categories: (1) microcephaly with copy number variations (CNVs), (2) microcephaly with single gene disorders, and (3) microcephaly with aneuploidies. The most common category was aneuploidy in 59% of the patients, followed by single gene disorders in 23% of the patients and CNVs in 18% of the patients. We think that history and physical examination guide physicians to choose the most appropriate genetic testing to identify underlying diagnosis.

Synonymous mutations in representative yeast genes are mostly strongly non-neutral

Synonymous mutations in protein-coding genes do not alter protein sequences and are thus generally presumed to be neutral or nearly neutral^1-5. Here, to experimentally verify this presumption, we constructed 8,341 yeast mutants each carrying a synonymous, nonsynonymous or nonsense mutation in one of 21 endogenous genes with diverse functions and expression levels and measured their fitness relative to the wild type in a rich medium. Three-quarters of synonymous mutations resulted in a significant reduction in fitness, and the distribution of fitness effects was overall similar-albeit nonidentical-between synonymous and nonsynonymous mutations. Both synonymous and nonsynonymous mutations frequently disturbed the level of mRNA expression of the mutated gene, and the extent of the disturbance partially predicted the fitness effect. Investigations in additional environments revealed greater across-environment fitness variations for nonsynonymous mutants than for synonymous mutants despite their similar fitness distributions in each environment, suggesting that a smaller proportion of nonsynonymous mutants than synonymous mutants are always non-deleterious in a changing environment to permit fixation, potentially explaining the common observation of substantially lower nonsynonymous than synonymous substitution rates. The strong non-neutrality of most synonymous mutations, if it holds true for other genes and in other organisms, would require re-examination of numerous biological conclusions about mutation, selection, effective population size, divergence time and disease mechanisms that rely on the assumption that synoymous mutations are neutral.

Extended genetic analysis of exome sequencing for primary hyperoxaluria in pediatric urolithiasis patients with hyperoxaluria

PURPOSE

Next generation sequencing-based exome sequencing can be used to identify genetic abnormalities in patients believed to be suffering from primary hyperoxaluria. We outline our efforts to improve the diagnostic capacity of exome sequencing for these patients.

METHODS

We conducted a retrospective analysis of exome sequencing data from 77 pediatric urolithiasis patients with hyperoxaluria of unknown origin. Canonical exome sequencing analysis was performed to identify pathogenic variants in three known primary hyperoxaluria-related genes (AGXT, GRHPR, HOGA1) as per the guidelines of the American College of Medical Genetics. Then, extended exome sequencing analyses of 5'-untranslated region, non-canonical splicing site and copy number variant were performed on patients with negative diagnostic results in these three genes.

RESULTS

Canonical exome sequencing analyses led to the diagnosis of primary hyperoxaluria in 20/77 (26%) patients, including eight, four, and eight patients diagnosed with type 1, 2 and 3 primary hyperoxaluria, respectively. Non-canonical splicing site analyses discovered a pathogenic variant in the HOGA1 gene, which led to the diagnosis of six additional patients with type 3 primary hyperoxaluria, while copy number variant analyses from exome sequencing data identified a 1.8 kb copy number loss that impacted the AGXT gene, resulting in the diagnosis of an additional type 1 primary hyperoxaluria case.

CONCLUSIONS

Extended non-canonical splicing site and copy number variant analyses improve the diagnostic yield of canonical exome sequencing analysis for primary hyperoxaluria from 26% (20/77) to 35% (27/77) in 77 pediatric urolithiasis patients with hyperoxaluria.

Clinical exome sequencing - mistakes and caveats

Massive parallel sequencing technology has become the predominant technique for genetic diagnostics and research. Many genetic laboratories have wrestled with the challenges of setting up genetic testing workflows based on a completely new technology. The learning curve we went through as a laboratory was accompanied by growing pains while we gained new knowledge and expertise. Here we discuss some important mistakes that have been made in our laboratory through 10 years of clinical exome sequencing but that have given us important new insights on how to adapt our working methods. We provide these examples and the lessons that we learned to help other laboratories avoid to make the same mistakes.

Genetic models and approaches to study orofacial clefts

INTRODUCTION

Orofacial clefts (OFCs) are common craniofacial birth defects with heterogeneous phenotype and etiology. Geneticists have applied nearly every available method and technology to further our understanding of the genetic architectures of OFCs.

OBJECTIVE

This review describes the evidence for a genetic etiology in OFCs, statistical genetic approaches employed to identify genetic causes, and how the results have shaped our current understanding of the genetic architectures of syndromic and nonsyndromic OFCs.

CONCLUSION

There has been rapid progress towards elucidating the genetic architectures of OFCs due to the availability of large collections of DNA samples from cases, controls, and families with OFCs and the consistent adoption of new methodologies and novel statistical approaches as they are developed. Genetic studies have identified rare and common variants influencing risk of OFCs in both Mendelian and complex forms of OFCs, blurring the distinctions traditional categories used in genetic studies and clinical medicine.

Whole-exome sequencing of the mummified remains of Cangrande della Scala (1291-1329 CE) indicates the first known case of late-onset Pompe disease

Mummified remains of relevant historical figures are nowadays an important source of information to retrace data concerning their private life and health, especially when historical archives are not available. Next-generation-sequencing was proved to be a valuable tool to unravel the characteristics of these individuals through their genetic heritage. Using the strictest criteria currently available for the validation of ancient DNA sequences, whole-genome and whole-exome sequencing were generated from the mummy remains of an Italian nobleman died almost 700 years ago, Cangrande della Scala. While its genome sequencing could not yield sufficient coverage for in depth investigation, exome sequencing could overcome the limitations of this approach to achieve significantly high coverage on coding regions, thus allowing to perform the first extensive exome analysis of a mummy genome. Similar to a standard "clinical exome analysis" conducted on modern DNA, an in-depth variant annotation, high-quality filtering and interpretation was performed, leading to the identification of a genotype associated with late-onset Pompe disease (glycogen storage disease type II). This genetic diagnosis was concordant with the limited clinical history available for Cangrande della Scala, who likely represents the earliest known case of this autosomal recessive metabolic disorder.

Lessons learned from unsolicited findings in clinical exome sequencing of 16,482 individuals

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.

Next-Generation Sequencing in the Field of Primary Immunodeficiencies: Current Yield, Challenges, and Future Perspectives

Primary immunodeficiencies comprise a group of inborn errors of immunity that display significant clinical and genetic heterogeneity. Next-generation sequencing techniques and predominantly whole exome sequencing have revolutionized the understanding of the genetic and molecular basis of genetic diseases, thereby also leading to a sharp increase in the discovery of new genes associated with primary immunodeficiencies. In this review, we discuss the current diagnostic yield of this generic diagnostic approach by evaluating the studies that have employed next-generation sequencing techniques in cohorts of patients with primary immunodeficiencies. The average diagnostic yield for primary immunodeficiencies is determined to be 29% (range 10-79%) and 38% specifically for whole-exome sequencing (range 15-70%). The significant variation between studies is mainly the result of differences in clinical characteristics of the studied cohorts but is also influenced by varying sequencing approaches and (in silico) gene panel selection. We further discuss other factors contributing to the relatively low yield, including the inherent limitations of whole-exome sequencing, challenges in the interpretation of novel candidate genetic variants, and promises of exploring the non-coding part of the genome. We propose strategies to improve the diagnostic yield leading the way towards expanded personalized treatment in PIDs.

3Cnet: pathogenicity prediction of human variants using multitask learning with evolutionary constraints

Motivation

Improvements in next-generation sequencing have enabled genome-based diagnosis for patients with genetic diseases. However, accurate interpretation of human variants requires knowledge from a number of clinical cases. In addition, manual analysis of each variant detected in a patient's genome requires enormous time and effort. To reduce the cost of diagnosis, various computational tools have been developed to predict the pathogenicity of human variants, but the shortage and bias of available clinical data can lead to overfitting of algorithms.

Results

We developed a pathogenicity predictor, 3Cnet, that uses recurrent neural networks to analyze the amino acid context of human variants. As 3Cnet is trained on simulated variants reflecting evolutionary conservation and clinical data, it can find disease-causing variants in patient genomes with 2.2 times greater sensitivity than currently available tools, more effectively discovering pathogenic variants and thereby improving diagnosis rates.

Availability and implementation

Codes (https://github.com/KyoungYeulLee/3Cnet/) and data (https://zenodo.org/record/4716879#.YIO-xqkzZH1) are freely available to non-commercial users.

Supplementary information

Supplementary data are available at Bioinformatics online.

CNVIntegrate: the first multi-ethnic database for identifying copy number variations associated with cancer

Human copy number variations (CNVs) and copy number alterations (CNAs) are DNA segments (>1000 base pairs) of duplications or deletions with respect to the reference genome, potentially causing genomic imbalance leading to diseases such as cancer. CNVs further cause genetic diversity in healthy populations and are predominant drivers of gene/genome evolution. Initiatives have been taken by the research community to establish large-scale databases to comprehensively characterize CNVs in humans. Exome Aggregation Consortium (ExAC) is one such endeavor that catalogs CNVs, of nearly 60 000 healthy individuals across five demographic clusters. Furthermore, large projects such as the Catalogue of Somatic Mutations in Cancer (COSMIC) and the Cancer Cell Line Encyclopedia (CCLE) combine CNA data from cancer-affected individuals and large panels of human cancer cell lines, respectively. However, we lack a structured and comprehensive CNV/CNA resource including both healthy individuals and cancer patients across large populations. CNVIntegrate is the first web-based system that hosts CNV and CNA data from both healthy populations and cancer patients, respectively, and concomitantly provides statistical comparisons between copy number frequencies of multiple ethnic populations. It further includes, for the first time, well-cataloged CNV and CNA data from Taiwanese healthy individuals and Taiwan Breast Cancer data, respectively, along with imported resources from ExAC, COSMIC and CCLE. CNVIntegrate offers a CNV/CNA-data hub for structured information retrieval for clinicians and scientists towards important drug discoveries and precision treatments. Database URL: http://cnvintegrate.cgm.ntu.edu.tw/.

Whole genome sequencing identifies novel structural variant in a large Indian family affected with X-linked agammaglobulinemia

X-linked agammaglobulinemia (XLA, OMIM #300755) is a primary immunodeficiency disorder caused by pathogenic variations in the BTK gene, characterized by failure of development and maturation of B lymphocytes. The estimated prevalence worldwide is 1 in 190,000 male births. Recently, genome sequencing has been widely used in difficult to diagnose and familial cases. We report a large Indian family suffering from XLA with five affected individuals. We performed complete blood count, immunoglobulin assay, and lymphocyte subset analysis for all patients and analyzed Btk expression for one patient and his mother. Whole exome sequencing (WES) for four patients, and whole genome sequencing (WGS) for two patients have been performed. Carrier screening was done for 17 family members using Multiplex Ligation-dependent Probe Amplification (MLPA) and haplotype ancestry mapping using fineSTRUCTURE was performed. All patients had hypogammaglobulinemia and low CD19+ B cells. One patient who underwent Btk estimation had low expression and his mother showed a mosaic pattern. We could not identify any single nucleotide variants or small insertion/ deletions from the WES dataset that correlates with the clinical feature of the patient. Structural variant analysis through WGS data identifies a novel large deletion of 5,296 bp at loci chrX:100,624,323-100,629,619 encompassing exons 3-5 of the BTK gene. Family screening revealed seven carriers for the deletion. Two patients had a successful HSCT. Haplotype mapping revealed a South Asian ancestry. WGS led to identification of the accurate genetic mutation which could help in early diagnosis leading to improved outcomes, prevention of permanent organ damage and improved quality of life, as well as enabling genetic counselling and prenatal diagnosis in the family.

Seventeen primary malignant neoplasms involving the skin, ovary, esophagus, colon, oral cavity, and ear canal: a case report and review of the literature

Multiple primary malignant neoplasm (MPMN) is a rare disease with two or more malignant neoplasms in one patient. In less than 0.1% of cancer patients, four or more occur. MPMN is frequently associated with hereditary cancer syndrome, although in rare cases, it is not. A female patient developed 17 MPMNs. Although they were successfully treated with surgery, radiation, and adjuvant chemotherapy, the patient died from the recurrence of ovarian cancer. To explore genetic susceptibility to MPMN, immunohistochemical analysis, microsatellite instability analysis, germ line exome sequencing, and unscheduled DNA synthesis assays were performed. However, the results of immunohistochemical analysis and microsatellite instability indicated that there were no known hereditary cancer syndromes, and exome sequencing with 88 representative genes associated with hereditary cancer syndrome revealed no variants. An unscheduled DNA synthesis assay to rule out xeroderma pigmentosum was also performed, but the result was negative. While the presence of multiple neoplasms is rare, the present case represents 17 primary neoplasms with no associations with hereditary cancer syndrome. Although the cause of MPMN was not detected in this patient, careful follow-up and deliberate cancer screening enabled successful disease management over 17 years from the appearance of the first neoplasm.

An Overview of Molecular Genetic Diagnosis Techniques

Our understanding of genetic disease(s) has increased exponentially since the completion of human genome sequencing and the development of numerous techniques to detect genetic variants. These techniques have not only allowed us to diagnose genetic disease, but in so doing, also provide increased understanding of the pathogenesis of these diseases to aid in developing appropriate therapeutic options. Additionally, the advent of next-generation or massively parallel sequencing (NGS/MPS) is increasingly being used in the clinical setting, as it can detect a number of abnormalities from point mutations to chromosomal rearrangements as well as aberrations within the transcriptome. In this article, we will discuss the use of multiple techniques that are used in genetic diagnosis. © 2020 by John Wiley & Sons, Inc.

A resource to explore the discovery of rare diseases and their causative genes

Here, we describe a dataset with information about monogenic, rare diseases with a known genetic background, supplemented with manually extracted provenance for the disease itself and the discovery of the underlying genetic cause. We assembled a collection of 4166 rare monogenic diseases and linked them to 3163 causative genes, annotated with OMIM and Ensembl identifiers and HGNC symbols. The PubMed identifiers of the scientific publications, which for the first time described the rare diseases, and the publications, which found the genes causing the diseases were added using information from OMIM, PubMed, Wikipedia, whonamedit.com, and Google Scholar. The data are available under CC0 license as spreadsheet and as RDF in a semantic model modified from DisGeNET, and was added to Wikidata. This dataset relies on publicly available data and publications with a PubMed identifier, but by our effort to make the data interoperable and linked, we can now analyse this data. Our analysis revealed the timeline of rare disease and causative gene discovery and links them to developments in methods.

The importance of genetic testing for dystonia patients and translational research

Genetic testing through a variety of methods is a fundamental but underutilized approach for establishing the precise genetic diagnosis in patients with heritable forms of dystonia. Our knowledge of numerous dystonia-related genes, variants that they may contain, associated clinical presentations, and molecular disease mechanism may have significant translational potential for patients with genetically confirmed dystonia or their family members. Importantly, genetic testing permits the assembly of patient cohorts pertinent for dystonia-related research and developing therapeutics. Here we review the genetic testing approaches relevant to dystonia patients, and summarize and illustrate the multifold benefits of establishing an accurate molecular diagnosis for patients imminently or for translational research in the long run.

Race and Genetics in Congenital Heart Disease: Application of iPSCs, Omics, and Machine Learning Technologies

Congenital heart disease (CHD) is a multifaceted cardiovascular anomaly that occurs when there are structural abnormalities in the heart before birth. Although various risk factors are known to influence the development of this disease, a full comprehension of the etiology and treatment for different patient populations remains elusive. For instance, racial minorities are disproportionally affected by this disease and typically have worse prognosis, possibly due to environmental and genetic disparities. Although research into CHD has highlighted a wide range of causal factors, the reasons for these differences seen in different patient populations are not fully known. Cardiovascular disease modeling using induced pluripotent stem cells (iPSCs) is a novel approach for investigating possible genetic variants in CHD that may be race specific, making it a valuable tool to help solve the mystery of higher incidence and mortality rates among minorities. Herein, we first review the prevalence, risk factors, and genetics of CHD and then discuss the use of iPSCs, omics, and machine learning technologies to investigate the etiology of CHD and its connection to racial disparities. We also explore the translational potential of iPSC-based disease modeling combined with genome editing and high throughput drug screening platforms.

Familial Hypercholesterolemia: Update and Review

Knowledge of epidemiology, genetic etiopathogenesis, diagnostic criteria, and management of familial hypercholesterolemia have increased in the last two decades. Several population studies have shown that familial hypercholesterolemia is more frequent than previously thought, making this entity the most common metabolic disease with monogenic inheritence in the world. Identification of causal heterozygous pathogenic variants in LDLR, APOB, and PCSK9 genes have increased diagnostic accuracy of classical criteria (extreme hypercholesterolemia, personal / family history of premature coronary artery disease or other cardiovascular disease). Genetic screening has been recently introduced in many European countries to detect patients with familial hypercholesterolemia, mainly affected pediatric subjects, asymptomatic or those at the beggining of their disease, with the purpose of increasing surveillance and avoiding complications such as cardiovascular diseases. Cholesterol-lowering drugs should be started as soon as the diagnosis is made. Various combinations between drugs can be used when the goal is not achieved. New therapies, including small interference ribonucleic acids (siRNA) are being tested in different clinical trials.

Elongated axial length and myopia-related fundus changes associated with the Arg130Cys mutation in the LIM2 gene in four Chinese families with congenital cataracts

Background

Congenital cataract (CC) is a congenital abnormality characterized by lens opacity present at birth and is associated with highly heterogeneous clinical manifestations. Lens-specific integral membrane protein (LIM2) gene expression is localized to tight junctional domains of different lens fiber membranes. To date, only four mutations in LIM2 have been reported to be associated with congenital or presenile cataracts. Due to the rarity of variants detected in the gene, there is limited progress in understanding the correlation between the genotype and phenotype of patients with mutations in LIM2.

Methods

A total of four Chinese families with CCs were recruited for this study, including three families inheriting in an autosomal dominant (AD) pattern and one sporadic case. Genomic DNA was extracted from the leukocytes of peripheral blood collected from all available patients. Whole-exome sequencing (WES) was performed on all probands and at least one of their parents. Bioinformatics analysis was performed to evaluate the pathogenicity of the candidate variants. Exon 4 of LIM2 was amplified by polymerase chain reaction and directly sequenced. All patients underwent full ocular examinations. This was an observational study to explore the genotype-phenotype relationships in the four families with a common candidate variant.

Results

Various ocular phenotypes were detected in these families, mainly including CCs, elongated axial length, and myopia-related fundus changes. The LIM2 gene mutation, p.Arg130Cys, was detected in all patients. This was further confirmed by Sanger sequencing. The proportion of probands with this mutation in our CCs database was 3.1% (4/130), which indicated that this mutation appears to be a frequent cause of cataracts in the Han Chinese population. This variation has been reported by other investigators before and was correlated with isolated cataracts.

Conclusions

This is the first study that reports various ocular phenotypes associated with the p.Arg130Cys mutation in the LIM2 gene, which indicated the phenotypic heterogeneity of this gene. LIM2 might not only function as an integral membrane protein in lens fiber cells but also be associated with the axial development of the eyeball. Functional studies of the LIM2 gene are important and should receive more attention.

Selection of Optimal Bioinformatic Tools and Proper Reference for Reducing the Alignment Error in Targeted Sequencing Data

Background

Careful design in the primary steps of a next-generation sequencing study is critical for obtaining successful results in downstream analysis.

Methods

In this study, a framework is proposed to evaluate and improve the sequence mapping in targeted regions of the reference genome. In this regard, simulated short reads were produced from the coding regions of the human genome and mapped to a Customized Target-Based Reference (CTBR) by the alignment tools that have been introduced recently. The short reads produced by different sequencing technologies aligned to the standard genome and also CTBR with and without well-defined mutation types where the amount of unmapped and misaligned reads and runtime was measured for comparison.

Results

The results showed that the mapping accuracy of the reads generated from Illumina Hiseq2500 using Stampy as the alignment tool whenever the CTBR was used as reference was significantly better than other evaluated pipelines. Using CTBR for alignment significantly decreased the mapping error in comparison to other expanded or more limited references. While intentional mutations were imported in the reads, Stampy showed the minimum error of 1.67% using CTBR. However, the lowest error obtained by stampy too using whole genome and one chromosome as references was 3.78% and 20%, respectively. Maximum and minimum misalignment errors were observed on chromosome Y and 20, respectively.

Conclusion

Therefore using the proposed framework in a clinical targeted sequencing study may lead to predict the error and improve the performance of variant calling regarding the genomic regions targeted in a clinical study.

Updates on Clinical and Genetic Heterogeneity of ASPM in 12 Autosomal Recessive Primary Microcephaly Families in Pakistani Population

Microcephaly (MCPH) is a genetically heterogeneous disorder characterized by non-progressive intellectual disability, small head circumference, and small brain size compared with the age- and sex-matched population. MCPH manifests as an isolated condition or part of another clinical syndrome; so far, 25 genes have been linked with MCPH. Many of these genes are reported in Pakistani population, but due to a high rate of consanguinity, a significant proportion of MCPH cohort is yet to be explored. MCPH5 is the most frequently reported type, accounting for up to 68.75% alone in a genetically constrained population like Pakistan. In the current study, whole exome sequencing (WES) was performed on probands from 10 families sampled from South Waziristan and two families from rural areas of the Pakistani Punjab. Candidate variants were validated through Sanger sequencing in all available family members. Variant filtering and in silico analysis identified three known mutations in ASPM, a MCPH5-associated gene. The founder mutation p.Trp1326^* was segregating in 10 families, which further confirmed the evidence that it is the most prominent mutation in Pashtun ethnicity living in Pakistan and Afghanistan. Furthermore, the previously known mutations p.Arg3244^* and p.Arg1019^* were inherited in two families with Punjab ethnic profile. Collectively, this study added 12 more families to the mutational paradigm of ASPM and expanded the Pakistani MCPH cohort.

Genetics of Parkinson's disease

Less than a quarter century after the discovery of SNCA as the first attributable gene in Parkinson's disease (PD), our knowledge of the genetic architecture underlying this disease has improved by leaps and bounds. About 5-10% of all patients suffer from a monogenic form of PD where mutations in autosomal-dominant (AD) genes-SNCA, LRRK2, and VPS35 and autosomal recessive (AR) genes-PINK1, DJ-1, and Parkin cause the disease. Whole-exome sequencing has described AR DNAJC6 mutations not only in predominantly atypical, but also in patients with typical PD. Majority of PD is genetically complex, caused by the combination of common genetic variants in concert with environmental factors. Genome-wide association studies have identified twenty six PD risk loci till date; however, these show only moderate effects on the risk for PD. The validation of novel genes and its association with PD remains extremely challenging as families harboring rare genetic variants are sparse and globally widespread. This review article aims to provide a comprehensive overview on PD genetics.

The Impact of Next-Generation Sequencing on the Diagnosis, Treatment, and Prevention of Hereditary Neuromuscular Disorders

The impact of high-throughput sequencing in genetic neuromuscular disorders cannot be overstated. The ability to rapidly and affordably sequence multiple genes simultaneously has enabled a second golden age of Mendelian disease gene discovery, with flow-on impacts for rapid genetic diagnosis, evidence-based treatment, tailored therapy development, carrier-screening, and prevention of disease recurrence in families. However, there are likely many more neuromuscular disease genes and mechanisms to be discovered. Many patients and families remain without a molecular diagnosis following targeted panel sequencing, clinical exome sequencing, or even genome sequencing. Here we review how massively parallel, or next-generation, sequencing has changed the field of genetic neuromuscular disorders, and anticipate future benefits of recent technological innovations such as RNA-seq implementation and detection of tandem repeat expansions from short-read sequencing.