Toward Clinical Implementation of Next-Generation Sequencing-Based Genetic Testing in Rare Diseases: Where Are We?

The digital revolution in pathology: Towards a smarter approach to research and treatment

Artificial intelligence (AI) applications in oncology are at the forefront of transforming healthcare during the Fourth Industrial Revolution, driven by the digital data explosion. This review provides an accessible introduction to the field of AI, presenting a concise yet structured overview of the foundations of AI, including expert systems, classical machine learning, and deep learning, along with their contextual application in clinical research and healthcare. We delve into the current applications of AI in oncology, with a particular focus on diagnostic imaging and pathology. Numerous AI tools have already received regulatory approval, and more are under active development, bringing clear benefits but not without challenges. We discuss the importance of data security, the need for transparent and interpretable models, and the ethical considerations that must guide AI development in healthcare. By providing a perspective on the opportunities and challenges, this review aims to inform and guide researchers, clinicians, and policymakers in the adoption of AI in oncology.

The promise and challenges of genomics-informed periodontal disease diagnoses

Recent advances in human genomics and the advent of molecular medicine have catapulted our ability to characterize human and health and disease. Scientists and healthcare practitioners can now leverage information on genetic variation and gene expression at the tissue or even individual cell level, and an enormous potential exists to refine diagnostic categories, assess risk in unaffected individuals, and optimize disease management among those affected. This review investigates the progress made in the domains of molecular medicine and genomics as they relate to periodontology. The review summarizes the current evidence of association between genomics and periodontal diseases, including the current state of knowledge that approximately a third of the population variance of periodontitis may be attributable to genetic variation and the management of several monogenic forms of the disease can be augmented by knowledge of the underlying genetic cause. Finally, the paper discusses the potential utility of polygenic risk scores and genetic testing for periodontitis diagnosis now and in the future, in light of applications that currently exist in other areas of medicine and healthcare.

The expanding diagnostic toolbox for rare genetic diseases

Genomic technologies, such as targeted, exome and short-read genome sequencing approaches, have revolutionized the care of patients with rare genetic diseases. However, more than half of patients remain without a diagnosis. Emerging approaches from research-based settings such as long-read genome sequencing and optical genome mapping hold promise for improving the identification of disease-causal genetic variants. In addition, new omic technologies that measure the transcriptome, epigenome, proteome or metabolome are showing great potential for variant interpretation. As genetic testing options rapidly expand, the clinical community needs to be mindful of their individual strengths and limitations, as well as remaining challenges, to select the appropriate diagnostic test, correctly interpret results and drive innovation to address insufficiencies. If used effectively - through truly integrative multi-omics approaches and data sharing - the resulting large quantities of data from these established and emerging technologies will greatly improve the interpretative power of genetic and genomic diagnostics for rare diseases.

GPAD: a natural language processing-based application to extract the gene-disease association discovery information from OMIM

BACKGROUND

Thousands of genes have been associated with different Mendelian conditions. One of the valuable sources to track these gene-disease associations (GDAs) is the Online Mendelian Inheritance in Man (OMIM) database. However, most of the information in OMIM is textual, and heterogeneous (e.g. summarized by different experts), which complicates automated reading and understanding of the data. Here, we used Natural Language Processing (NLP) to make a tool (Gene-Phenotype Association Discovery (GPAD)) that could syntactically process OMIM text and extract the data of interest.

RESULTS

GPAD applies a series of language-based techniques to the text obtained from OMIM API to extract GDA discovery-related information. GPAD can inform when a particular gene was associated with a specific phenotype, as well as the type of validation-whether through model organisms or cohort-based patient-matching approaches-for such an association. GPAD extracted data was validated with published reports and was compared with large language model. Utilizing GPAD's extracted data, we analysed trends in GDA discoveries, noting a significant increase in their rate after the introduction of exome sequencing, rising from an average of about 150-250 discoveries each year. Contrary to hopes of resolving most GDAs for Mendelian disorders by now, our data indicate a substantial decline in discovery rates over the past five years (2017-2022). This decline appears to be linked to the increasing necessity for larger cohorts to substantiate GDAs. The rising use of zebrafish and Drosophila as model organisms in providing evidential support for GDAs is also observed.

CONCLUSIONS

GPAD's real-time analyzing capacity offers an up-to-date view of GDA discovery and could help in planning and managing the research strategies. In future, this solution can be extended or modified to capture other information in OMIM and scientific literature.

Clinical application of next generation sequencing for Mendelian disease diagnosis in the Iranian population

Next-generation sequencing (NGS) has been proven to be one of the most powerful diagnostic tools for rare Mendelian disorders. Several studies on the clinical application of NGS in unselected cohorts of Middle Eastern patients have reported a high diagnostic yield of up to 48%, correlated with a high level of consanguinity in these populations. We evaluated the diagnostic utility of NGS-based testing across different clinical indications in 1436 patients from Iran, representing the first study of its kind in this highly consanguineous population. A total of 1075 exome sequencing and 361 targeted gene panel sequencing were performed over 8 years at a single clinical genetics laboratory, with the majority of cases tested as proband-only (91.6%). The overall diagnostic rate was 46.7%, ranging from 24% in patients with an abnormality of prenatal development to over 67% in patients with an abnormality of the skin. We identified 660 pathogenic or likely pathogenic variants, including 241 novel variants, associated with over 342 known genetic conditions. The highly consanguineous nature of this cohort led to the diagnosis of autosomal recessive disorders in the majority of patients (79.1%) and allowed us to determine the shared carrier status of couples for suspected recessive phenotypes in their deceased child(ren) when direct testing was not possible. We also highlight the observations of recessive inheritance of genes previously associated only with dominant disorders and provide an expanded genotype-phenotype spectrum for multiple less-characterized genes. We present the largest mutational spectrum of known Mendelian disease, including possible founder variants, throughout the Iranian population, which can serve as a unique resource for clinical genomic studies locally and beyond.

A feasible molecular diagnostic strategy for rare genetic disorders within resource-constrained environments

Timely and accurate diagnosis of rare genetic disorders is critical, as it enables improved patient management and prognosis. In a resource-constrained environment such as the South African State healthcare system, the challenge is to design appropriate and cost-effective assays that will enable accurate genetic diagnostic services in patients of African ancestry across a broad disease spectrum. Next-generation sequencing (NGS) has transformed testing approaches for many Mendelian disorders, but this technology is still relatively new in our setting and requires cost-effective ways to implement. As a proof of concept, we describe a feasible diagnostic strategy for genetic disorders frequently seen in our genetics clinics (RASopathies, Cornelia de Lange syndrome, Treacher Collins syndrome, and CHARGE syndrome). The custom-designed targeted NGS gene panel enabled concurrent variant screening for these disorders. Samples were batched during sequencing and analyzed selectively based on the clinical phenotype. The strategy employed in the current study was cost-effective, with sequencing and analysis done at USD849.68 per sample and achieving an overall detection rate of 54.5%. The strategy employed is cost-effective as it allows batching of samples from patients with different diseases in a single run, an approach that can be utilized with rare and less frequently ordered molecular diagnostic tests. The subsequent selective analysis pipeline allowed for timeous reporting back of patients results. This is feasible with a reasonable yield and can be employed for the molecular diagnosis of a wide range of rare monogenic disorders in a resource-constrained environment.

Exploring uncertainties regarding unsolicited findings in genetic testing

OBJECTIVES

Non-normative uncertainty (uncertainty about empirical facts) and normative uncertainty (uncertainty about moral values or beliefs) regarding unsolicited findings (UFs) might play an important role in clinical genetics. Identifying normative uncertainty is of special interest since it might guide towards novel directions for counseling practice. This study aims to gain insight into the role of non-normative and normative uncertainty regarding UFs, as expressed by counselees and counselors.

METHODS

We performed a secondary qualitative analysis of interviews with counselees (n = 20) and counselors (n = 20) who had been confronted with UFs. Following a deductive approach, we used Han et al.'s existing theoretical framework of uncertainty, in which we additionally incorporated normative uncertainty.

RESULTS

Major issues of non-normative uncertainty were practical and personal for counselees, whilst counselors' uncertainty pertained mainly to scientific issues. Normative uncertainty was a major theme throughout the interviews. We encountered the moral conflicts of autonomy vs. beneficence and non-maleficence and of autonomy vs. truthfulness.

CONCLUSION

Non-normative uncertainty regarding UFs highlights the need to gain more insight in their penetrance and clinical utility. This study suggests moral conflicts are a major source of feelings of uncertainty in clinical genetics.

PRACTICE IMPLICATIONS

Exploring counselees' non-normative uncertainties and normative conflicts seems a prerequisite to optimize genetic counseling.

Artificial intelligence and database for NGS-based diagnosis in rare disease

Rare diseases (RDs) are rare complex genetic diseases affecting a conservative estimate of 300 million people worldwide. Recent Next-Generation Sequencing (NGS) studies are unraveling the underlying genetic heterogeneity of this group of diseases. NGS-based methods used in RDs studies have improved the diagnosis and management of RDs. Concomitantly, a suite of bioinformatics tools has been developed to sort through big data generated by NGS to understand RDs better. However, there are concerns regarding the lack of consistency among different methods, primarily linked to factors such as the lack of uniformity in input and output formats, the absence of a standardized measure for predictive accuracy, and the regularity of updates to the annotation database. Today, artificial intelligence (AI), particularly deep learning, is widely used in a variety of biological contexts, changing the healthcare system. AI has demonstrated promising capabilities in boosting variant calling precision, refining variant prediction, and enhancing the user-friendliness of electronic health record (EHR) systems in NGS-based diagnostics. This paper reviews the state of the art of AI in NGS-based genetics, and its future directions and challenges. It also compare several rare disease databases.

Knowledge, awareness, and perception on genetic testing for primary immunodeficiency disease among parents in Malaysia: a qualitative study

Background

Primary Immunodeficiency Disease (PID), also known as Inborn Errors of Immunity (IEI), comprises a group of rare genetic disorders that impair the body's immune responses. These conditions result from monogenic germline mutations that affect the function of genes governing the innate and adaptive immune system. Therefore, individuals with PID are more susceptible to infectious diseases, allergies, and autoimmune and autoinflammatory conditions. The prevalence of PID has been on the rise, with the number of classified diseases reaching 404, and 430 genetic defects reported to cause these conditions. However, in Malaysia, genetic testing for PID is currently limited and needs to be outsourced to overseas laboratories, posing financial challenges for families. Moreover, limited research has focused on the knowledge and awareness of genetic testing among parents of children with PID in Malaysia. This study aims to address this gap and provide valuable insights into the knowledge, awareness, and perception of genetic testing among this specific population.

Method

This qualitative cross-sectional study utilised online open-ended, semi-structured focus group interviews to explore the perceptions and experiences of parents of children with Primary Immunodeficiency (PID). Participants were recruited through convenience sampling from the Malaysian Patient Organisation for Primary Immunodeficiencies (MyPOPI), a non-governmental organisation dedicated to providing support and raising awareness about PID. The study spanned from May 2023 to July 2023 and included participants from diverse regions of Malaysia who had undergone different diagnostic journeys in various hospitals.

Result

The focus group discussions yielded 11 sub-themes that highlighted the experiences, understanding and challenges of the participants regarding genetic testing based on the semi-structured questions. These sub-themes were then grouped into four main themes that are awareness and understanding of genetic testing, the journey towards diagnosis and treatment, emotional impact and psychological factors, and the importance of medical experts in diagnosing and managing PID, as well as public perception and awareness.

Conclusion

In conclusion, this study highlights the diverse knowledge, awareness, and perception surrounding genetic testing for PID. Factors such as access to services, family history, and personal circumstances shape individuals' understanding of genetic testing. The importance of healthcare professionals, along with the need for improved accessibility and targeted communication strategies, is underscored to enhance understanding and reduce stigma surrounding genetic testing for rare diseases like PID.

Identification of novel candidate genes associated with non-syndromic tooth agenesis in Mongolian families

OBJECTIVES

This study aimed to identify genetic variants associated with non-syndromic tooth agenesis (TA) in nine families from Mongolia using whole-exome sequencing (WES) and bioinformatics analysis.

MATERIAL AND METHODS

The study enrolled 41 participants, including three inherited and six non-inherited families. WES analysis was performed on 14 saliva samples from individuals with non-syndromic TA. The potential candidate genes were identified through variant filtering and segregation analysis. The filtered variants were then analyzed in silico mutation impact analysis.

RESULTS

WES analysis identified 21 variants associated with TA, and 5 of these variants met all filtering criteria. These variants were located in the exome region of MAST4, ITGA6, PITX2, CACNA1S, and CDON genes. The variant in PITX2 was found in eight participants from inherited and non-inherited families, while the MAST4 variant was identified in 6 participants from inherited families.

CONCLUSIONS

The study identified various genetic variant candidates associated with TA in different family groups, with PITX2 being the most commonly identified. Our findings suggest that MAST4 may also be a novel candidate gene for TA due to its association with the Wnt signaling pathway. Additionally, we found that five candidate genes related to focal adhesion and calcium channel complex were significant and essential in tooth development.

CLINICAL RELEVANCE

Identifying new pathogenic genes associated with TA can improve our understanding of the molecular mechanisms underlying the disease, leading to better diagnosis, prevention, and treatment. Early detection of TA based on biomarkers can improve dental management and facilitate orthodontic and prosthetic treatment.

Genetic Defects in Early-Onset Inflammatory Bowel Disease

Inflammatory bowel disease (IBD) represents a spectrum of disease, which is characterized by chronic gastrointestinal inflammation. Monogenic mutations driving IBD pathogenesis are more highly represented in early-onset compared to adult-onset disease. The pathogenic genes which dysregulate host immune responses in monogenic IBD affect both the innate (ie, intestinal barrier, phagocytes) and adaptive immune systems (ie, T cells, B cells). Advanced genomic and targeted functional testing can improve clinical decision making and present increased opportunities for precision medicine approaches in this important patient population.

Understanding Biases and Disparities in Radiology AI Datasets: A Review

Artificial intelligence (AI) continues to show great potential in disease detection and diagnosis on medical imaging with increasingly high accuracy. An important component of AI model creation is dataset development for training, validation, and testing. Diverse and high-quality datasets are critical to ensure robust and unbiased AI models that maintain validity, especially in traditionally underserved populations globally. Yet publicly available datasets demonstrate problems with quality and inclusivity. In this literature review, the authors evaluate publicly available medical imaging datasets for demographic, geographic, genetic, and disease representation or lack thereof and call for an increase emphasis on dataset development to maximize the impact of AI models.

A Unique Case of Harlequin Ichthyosis in the Tertiary Health Care System in a Rural Area

Harlequin ichthyosis (HI) is a severe and rare genetic anomaly that affects skin development and leads to the formation of thick, diamond-shaped plates of keratinized skin. The adenosine triphosphate binding cassette A 12 (ABCA12) gene, which is essential for the transportation of lipids required for the skin's barrier function, has mutations that result in this condition. The affected individuals exhibit distinct clinical features, including thickened skin, deep cracks, and fissures, which can result in significant physical and functional impairments. HI is usually apparent at birth, with affected infants presenting with tight and rigid skin that restricts movement and normal growth. The condition is associated with various complications, including difficulty breathing, feeding difficulties, and increased susceptibility to infections. Due to the impaired skin barrier, affected individuals are also prone to dehydration and temperature dysregulation. In this case report, we present a unique case of ichthyosis in a nine-month-old child. Despite advances in medical care, HI remains a challenging condition with a high mortality rate, particularly in the neonatal period. However, with early detection, appropriate interventions, and an improved understanding of the underlying molecular mechanisms, there is hope for enhanced management and improved quality of life for individuals living with HI.

In vivo versus in silico assessment of potentially pathogenic missense variants in human reproductive genes

Infertility is a heterogeneous condition, with genetic causes thought to underlie a substantial fraction of cases. Genome sequencing is becoming increasingly important for genetic diagnosis of diseases including idiopathic infertility; however, most rare or minor alleles identified in patients are variants of uncertain significance (VUS). Interpreting the functional impacts of VUS is challenging but profoundly important for clinical management and genetic counseling. To determine the consequences of these variants in key fertility genes, we functionally evaluated 11 missense variants in the genes ANKRD31, BRDT, DMC1, EXO1, FKBP6, MCM9, M1AP, MEI1, MSH4 and SEPT12 by generating genome-edited mouse models. Nine variants were classified as deleterious by most functional prediction algorithms, and two disrupted a protein-protein interaction (PPI) in the yeast two hybrid (Y2H) assay. Though these genes are essential for normal meiosis or spermiogenesis in mice, only one variant, observed in the MCM9 gene of a male infertility patient, compromised fertility or gametogenesis in the mouse models. To explore the disconnect between predictions and outcomes, we compared pathogenicity calls of missense variants made by ten widely used algorithms to 1) those annotated in ClinVar and 2) those evaluated in mice. All the algorithms performed poorly in terms of predicting the effects of human missense variants modeled in mice. These studies emphasize caution in the genetic diagnoses of infertile patients based primarily on pathogenicity prediction algorithms and emphasize the need for alternative and efficient in vitro or in vivo functional validation models for more effective and accurate VUS description to either pathogenic or benign categories.

Resources and tools for rare disease variant interpretation

Collectively, rare genetic disorders affect a substantial portion of the world's population. In most cases, those affected face difficulties in receiving a clinical diagnosis and genetic characterization. The understanding of the molecular mechanisms of these diseases and the development of therapeutic treatments for patients are also challenging. However, the application of recent advancements in genome sequencing/analysis technologies and computer-aided tools for predicting phenotype-genotype associations can bring significant benefits to this field. In this review, we highlight the most relevant online resources and computational tools for genome interpretation that can enhance the diagnosis, clinical management, and development of treatments for rare disorders. Our focus is on resources for interpreting single nucleotide variants. Additionally, we present use cases for interpreting genetic variants in clinical settings and review the limitations of these results and prediction tools. Finally, we have compiled a curated set of core resources and tools for analyzing rare disease genomes. Such resources and tools can be utilized to develop standardized protocols that will enhance the accuracy and effectiveness of rare disease diagnosis.

Advances in point-of-care genetic testing for personalized medicine applications

Breakthroughs within the fields of genomics and bioinformatics have enabled the identification of numerous genetic biomarkers that reflect an individual's disease susceptibility, disease progression, and therapy responsiveness. The personalized medicine paradigm capitalizes on these breakthroughs by utilizing an individual's genetic profile to guide treatment selection, dosing, and preventative care. However, integration of personalized medicine into routine clinical practice has been limited-in part-by a dearth of widely deployable, timely, and cost-effective genetic analysis tools. Fortunately, the last several decades have been characterized by tremendous progress with respect to the development of molecular point-of-care tests (POCTs). Advances in microfluidic technologies, accompanied by improvements and innovations in amplification methods, have opened new doors to health monitoring at the point-of-care. While many of these technologies were developed with rapid infectious disease diagnostics in mind, they are well-suited for deployment as genetic testing platforms for personalized medicine applications. In the coming years, we expect that these innovations in molecular POCT technology will play a critical role in enabling widespread adoption of personalized medicine methods. In this work, we review the current and emerging generations of point-of-care molecular testing platforms and assess their applicability toward accelerating the personalized medicine paradigm.

Evaluation of in silico pathogenicity prediction tools for the classification of small in-frame indels

BACKGROUND

The use of in silico pathogenicity predictions as evidence when interpreting genetic variants is widely accepted as part of standard variant classification guidelines. Although numerous algorithms have been developed and evaluated for classifying missense variants, in-frame insertions/deletions (indels) have been much less well studied.

METHODS

We created a dataset of 3964 small (< 100 bp) indels predicted to result in in-frame amino acid insertions or deletions using data from gnomAD v3.1 (minor allele frequency of 1-5%), ClinVar and the Deciphering Developmental Disorders (DDD) study. We used this dataset to evaluate the performance of nine pathogenicity predictor tools: CADD, CAPICE, FATHMM-indel, MutPred-Indel, MutationTaster2021, PROVEAN, SIFT-indel, VEST-indel and VVP.

RESULTS

Our dataset consisted of 2224 benign/likely benign and 1740 pathogenic/likely pathogenic variants from gnomAD (n = 809), ClinVar (n = 2882) and, DDD (n = 273). We were able to generate scores across all tools for 91% of the variants, with areas under the ROC curve (AUC) of 0.81-0.96 based on the published recommended thresholds. To avoid biases caused by inclusion of our dataset in the tools' training data, we also evaluated just DDD variants not present in either gnomAD or ClinVar (70 pathogenic and 81 benign). Using this subset, the AUC of all tools decreased substantially to 0.64-0.87. Several of the tools performed similarly however, VEST-indel had the highest AUCs of 0.93 (full dataset) and 0.87 (DDD subset).

CONCLUSIONS

Algorithms designed for predicting the pathogenicity of in-frame indels perform well enough to aid clinical variant classification in a similar manner to missense prediction tools.

Integration of artificial intelligence and multi-omics in kidney diseases

Kidney disease is a leading cause of death worldwide. Currently, the diagnosis of kidney diseases and the grading of their severity are mainly based on clinical features, which do not reveal the underlying molecular pathways. More recent surge of ∼omics studies has greatly catalyzed disease research. The advent of artificial intelligence (AI) has opened the avenue for the efficient integration and interpretation of big datasets for discovering clinically actionable knowledge. This review discusses how AI and multi-omics can be applied and integrated, to offer opportunities to develop novel diagnostic and therapeutic means in kidney diseases. The combination of new technology and novel analysis pipelines can lead to breakthroughs in expanding our understanding of disease pathogenesis, shedding new light on biomarkers and disease classification, as well as providing possibilities of precise treatment.

Harlequin ichthyosis newborn: A case report

Harlequin ichthyosis is a rare and severe genetic skin disorder that occurs within the developing foetus. Harlequin ichthyosis is the most severe and devastating form of autosomal recessive congenital ichthyoses. It is caused by mutations in the lipid transporter adenosine triphosphate binding cassette A 12. Here, we reported a case of harlequin ichthyosis with no family history. No abnormalities were detected in prenatal sonography. A 24-year-old pregnant woman with premature rupture of membrane and labour pain was referred to a hospital in Shoushtar city, Iran. The mother delivered a male baby with harlequin ichthyosis. The infant baby died on the 5th day. Harlequin ichthyosis is associated with adenosine triphosphate binding cassette A 12 gene mutation; therefore, genetic screening and counselling for susceptible parents should be taken into account. Prenatal diagnosis of harlequin ichthyosis principally via sonographic techniques is important in managing the disorder.

Rare Disease Education Outside of the Classroom and Clinic: Evaluation of the RARE Compassion Program for Undergraduate Medical Students

Launched in 2014, the RARE Compassion Program is the first international educational program to pair medical students with rare disease patients in order to enhance exposure to and comfort with rare diseases. As part of ongoing quality improvement, this study retrospectively reviewed four years of participant registration data to conduct a program evaluation of the RARE Compassion Program between 2014–2018. During the study period, there were 334 student participants, representing 67.3% of Association of American Medical Colleges (AAMC) member medical schools, and 5389 rare disease volunteers. Despite not requiring in-person interaction, 90.64% of student–volunteer interactions were in-person, while only 5.89% and 3.46% were by video messaging or email correspondence, respectively (p = 0.0002). In a limited post participation survey, 91.7% of students, who matched to 19 out of 27 residency specialities, indicated they would recommend the program to their peers. These findings suggest that the RARE Compassion Program, designed to increase medical student engagement with rare disease patients, has broad appeal. It serves as a novel case study of how extracurricular initiatives supported by non-profit organizations can augment the medical training experience and improve understanding of important and often neglected perspectives.

Expanding the genetic spectrum of tooth agenesis using whole-exome sequencing

BACKGROUND

Tooth agenesis is a high genetic heterogeneous disorder with more than eighty genes identified as associated molecular causes. The present study aimed to detect the possible pathogenic variants in a cohort of well-characterized probands with a clinical diagnosis of tooth agenesis.

METHODS

We performed whole-exome sequencing (WES) in 131 tooth agenesis patients with no previously identified molecular diagnosis. All the potential pathogenic variants were verified by Sanger sequencing in patients and their family members. Results Seventy-three patients were genetically diagnosed in 131 unrelated Chinese patients with tooth agenesis, providing a positive molecular diagnostic rate of 55.7%, including 53.8% (49/91) in the non-syndromic tooth agenesis (NSTA) group, and 60.0% (24/40) in syndromic tooth agenesis (STA) group. A total of 75 variants from 13 different genes were identified, including 33 novel variants, and WNT10A and EDA are the most common causative genes associated with non-syndromic and syndromic tooth agenesis, respectively.

CONCLUSIONS

This study further extends the variant spectrum and clinical profiles of tooth agenesis, which has a positive significance for clinical practice, genetic diagnosis, prenatal counseling and future treatment.

Novel mutations of the ABCA12, KRT1 and ST14 genes in three unrelated newborns showing congenital ichthyosis

Background

Congenital ichthyosis (CI) is a heterogeneous group of genetic disorders characterized by generalized dry skin, scaling and hyperkeratosis, often associated to erythroderma. They are rare diseases, with overall incidence of 6.7 in 100,000. Clinical manifestations are due to mutations in genes mostly involved in skin barrier formation. Based on clinical presentation, CI is distinguished in non-syndromic and syndromic forms. To date, mutations of more than 50 genes have been associated to different types of CI.

Cases presentation

We report on three Italian unrelated newborns showing clinical signs compatible with different forms of CI of variable severity, namely Harlequin ichtyosis (HI), epidermolytic ichtyosis (EI) and autosomal recessive ichtyosis with hypotrichosis (ARIH). Target next generation sequencing (NGS) analysis identified three novel mutations of the ABCA12, KRT1 and ST14 genes, respectively associated to such congenital ichtyoses, not reported in literature. Genomic investigation allowed to provide the more appropriate management to each patient, based on an individualized approach.

Conclusions

Our report highlights the wide genetic heterogeneity and phenotypic variability of CI. It expands the current knowledge on such diseases, widening their genomic database, and providing a better clinical characterization. Furthermore, it underlines the clinical relevance of NGS, which is essential to address the management of patients. Indeed, it may guide towards the most adequate approach, preventing clinical obstinacy for subjects with more severe forms and unfavorable outcomes (together with the support, in such situations, of bioethicists included within the multidisciplinary care team), as well as reassuring families in those with milder course and favorable evolution.

A Formative Study of the Implementation of Whole Genome Sequencing in Northern Ireland

Background: The UK 100,000 Genomes Project was a transformational research project which facilitated whole genome sequencing (WGS) diagnostics for rare diseases. We evaluated experiences of introducing WGS in Northern Ireland, providing recommendations for future projects. Methods: This formative evaluation included (1) an appraisal of the logistics of implementing and delivering WGS, (2) a survey of participant self-reported views and experiences, (3) semi-structured interviews with healthcare staff as key informants who were involved in the delivery of WGS and (4) a workshop discussion about interprofessional collaboration with respect to molecular diagnostics. Results: We engaged with >400 participants, with detailed reflections obtained from 74 participants including patients, caregivers, key National Health Service (NHS) informants, and researchers (patient survey n = 42; semi-structured interviews n = 19; attendees of the discussion workshop n = 13). Overarching themes included the need to improve rare disease awareness, education, and support services, as well as interprofessional collaboration being central to an effective, mainstreamed molecular diagnostic service. Conclusions: Recommendations for streamlining precision medicine for patients with rare diseases include administrative improvements (e.g., streamlining of the consent process), educational improvements (e.g., rare disease training provided from undergraduate to postgraduate education alongside genomics training for non-genetic specialists) and analytical improvements (e.g., multidisciplinary collaboration and improved computational infrastructure).

Phenylbutyrate rescues the transport defect of the Sec61α mutations V67G and T185A for renin

The human Sec61 complex is a widely distributed and abundant molecular machine. It resides in the membrane of the endoplasmic reticulum to channel two types of cargo: protein substrates and calcium ions. The SEC61A1 gene encodes for the pore-forming Sec61α subunit of the Sec61 complex. Despite their ubiquitous expression, the idiopathic SEC61A1 missense mutations p.V67G and p.T185A trigger a localized disease pattern diagnosed as autosomal dominant tubulointerstitial kidney disease (ADTKD-SEC61A1). Using cellular disease models for ADTKD-SEC61A1, we identified an impaired protein transport of the renal secretory protein renin and a reduced abundance of regulatory calcium transporters, including SERCA2. Treatment with the molecular chaperone phenylbutyrate reversed the defective protein transport of renin and the imbalanced calcium homeostasis. Signal peptide substitution experiments pointed at targeting sequences as the cause for the substrate-specific impairment of protein transport in the presence of the V67G or T185A mutations. Similarly, dominant mutations in the signal peptide of renin also cause ADTKD and point to impaired transport of this renal hormone as important pathogenic feature for ADTKD-SEC61A1 patients as well.

Lessons learned: next-generation sequencing applied to undiagnosed genetic diseases

Rare genetic disorders, when considered together, are relatively common. Despite advancements in genetics and genomics technologies as well as increased understanding of genomic function and dysfunction, many genetic diseases continue to be difficult to diagnose. The goal of this Review is to increase the familiarity of genetic testing strategies for non-genetics providers. As genetic testing is increasingly used in primary care, many subspecialty clinics, and various inpatient settings, it is important that non-genetics providers have a fundamental understanding of the strengths and weaknesses of various genetic testing strategies as well as develop an ability to interpret genetic testing results. We provide background on commonly used genetic testing approaches, give examples of phenotypes in which the various genetic testing approaches are used, describe types of genetic and genomic variations, cover challenges in variant identification, provide examples in which next-generation sequencing (NGS) failed to uncover the variant responsible for a disease, and discuss opportunities for continued improvement in the application of NGS clinically. As genetic testing becomes increasingly a part of all areas of medicine, familiarity with genetic testing approaches and result interpretation is vital to decrease the burden of undiagnosed disease.

Pre- and post-treatment blood-based genomic landscape of patients with ROS1 or NTRK fusion-positive solid tumors treated with entrectinib

Genomic tumor profiling informs targeted treatment options. Entrectinib is a tyrosine kinase inhibitor with efficacy in NTRK fusion-positive (-fp) solid tumors and ROS1-fp non-small cell lung cancer. FoundationOne^® Liquid CDx (F1L CDx), a non-invasive in vitro next-generation sequencing (NGS)-based diagnostic, detects genomic alterations in plasma circulating tumor DNA (ctDNA). We evaluated the clinical validity of F1L CDx as an aid in identifying patients with NTRK-fp or ROS1-fp tumors, and assessed the genomic landscape pre- and post-entrectinib treatment. Among evaluable pre-treatment clinical samples (N = 85), positive percentage agreements between F1L CDx and clinical trial assays (CTAs) were 47.4% (NTRK fusions) and 64.5% (ROS1 fusions); positive predictive value was 100% for both. The objective response rate for CTA+ F1L CDx+ patients was 72.2% in both cohorts. The median duration of response significantly differed between F1L CDx+ and F1L CDx- samples in ROS1-fp (5.6 vs. 17.3 months) but not NTRK-fp (9.2 vs. 12.9 months) patients. Fifteen acquired resistance mutations were detected. We conclude that F1L CDx is a clinically valid complement to tissue-based testing to identify patients who may benefit from entrectinib and those with acquired resistance mutations associated with disease progression.

Towards accurate and reliable resolution of structural variants for clinical diagnosis

Structural variants (SVs) are a major source of human genetic diversity and have been associated with different diseases and phenotypes. The detection of SVs is difficult, and a diverse range of detection methods and data analysis protocols has been developed. This difficulty and diversity make the detection of SVs for clinical applications challenging and requires a framework to ensure accuracy and reproducibility. Here, we discuss current developments in the diagnosis of SVs and propose a roadmap for the accurate and reproducible detection of SVs that includes case studies provided from the FDA-led SEquencing Quality Control Phase II (SEQC-II) and other consortium efforts.

Malformations of cerebral development and clues from the peripheral nervous system: A systematic literature review

Clinical manifestations of malformations of cortical development (MCD) are variable and can range from mild to severe intellectual disability, cerebral palsy and drug-resistant epilepsy. Besides common clinical features, non-specific or more subtle clinical symptoms may be present in association with different types of MCD. Especially in severely affected individuals, subtle but specific underlying clinical symptoms can be overlooked or overshadowed by the global clinical presentation. To facilitate the interpretation of genetic variants detailed clinical information is indispensable. Detailed (neurological) examination can be helpful in assisting with the diagnostic trajectory, both when referring for genetic work-up as well as when interpreting data from molecular genetic testing. This systematic literature review focusses on different clues derived from the neurological examination and potential further work-up triggered by these signs and symptoms in genetically defined MCDs. A concise overview of specific neurological findings and their associations with MCD subtype and genotype are presented, easily applicable in daily clinical practice. The following pathologies will be discussed: neuropathy, myopathy, muscular dystrophies and spastic paraplegia. In the discussion section, tips and pitfalls are illustrated to improve clinical outcome in the future.

Therapeutic impact and routine application of next‑generation sequencing: A single institute study

Genomic sequencing of tumor tissues provides information on actionable gene aberrations that have diagnostic and therapeutic significance and may guide clinical management through the use of targeted therapies. The indications for these techniques and their possible limitations for application in daily practice should be established as a priority. In the present study, a group of patients with few suitable therapeutic options who were eligible for a next-generation sequencing (NGS) analysis were analyzed, and the molecular targets identified and their therapeutic impact are described. A series of 26 patients treated at the Virgen Macarena Hospital for whom an NGS study was requested between January 2017 and December 2019 were reviewed. Actionable molecular alterations were identified in 20 of the cases, and 4 patients received NGS-guided treatment. NGS techniques represent a novel opportunity for guiding treatment in cancer patients. Patients with few therapeutic alternatives, either due to diagnosis, atypical evolution or resistance to standard therapy, may be suitable candidates.

Genetic Testing for Rare Diseases: A Systematic Review of Ethical Aspects

Genetic testing is associated with many ethical challenges on the individual, organizational and macro level of health care systems. The provision of genetic testing for rare diseases in particular requires a full understanding of the complexity and multiplicity of related ethical aspects. This systematic review presents a detailed overview of ethical aspects relevant to genetic testing for rare diseases as discussed in the literature. The electronic databases Pubmed, Science Direct and Web of Science were searched, resulting in 55 relevant publications. From the latter, a total of 93 different ethical aspects were identified. These ethical aspects were structured into three main categories (process of testing, consequences of the test outcome and contextual challenges) and 20 subcategories highlighting the diversity and complexity of ethical aspects relevant to genetic testing for rare diseases. This review can serve as a starting point for the further in-depth investigation of particular ethical issues, the education of healthcare professionals regarding this matter and for informing international policy development on genetic testing for rare diseases.

Identifying the Steps Required to Effectively Implement Next-Generation Sequencing in Oncology at a National Level in Europe

Next-generation sequencing (NGS) may enable more focused and highly personalized cancer treatment, with the National Comprehensive Cancer Network and European Society for Medical Oncology guidelines now recommending NGS for daily clinical practice for several tumor types. However, NGS implementation, and therefore patient access, varies across Europe; a multi-stakeholder collaboration is needed to establish the conditions required to improve this discrepancy. In that regard, we set up European Alliance for Personalised Medicine (EAPM)-led expert panels during the first half of 2021, including key stakeholders from across 10 European countries covering medical, economic, patient, industry, and governmental expertise. We describe the outcomes of these panels in order to define and explore the necessary conditions for NGS implementation into routine clinical care to enable patient access, identify specific challenges in achieving them, and make short- and long-term recommendations. The main challenges identified relate to the demand for NGS tests (governance, clinical standardization, and awareness and education) and supply of tests (equitable reimbursement, infrastructure for conducting and validating tests, and testing access driven by evidence generation). Recommendations made to resolve each of these challenges should aid multi-stakeholder collaboration between national and European initiatives, to complement, support, and mutually reinforce efforts to improve patient care.

Identification and quantification of oligogenic loss-of-function disorders

PURPOSE

Monogenic disorders can present clinically heterogeneous symptoms. We hypothesized that in patients with a monogenic disorder caused by a large deletion, frequently additional loss-of-function (LOF)-intolerant genes are affected, potentially contributing to the phenotype.

METHODS

We investigated the LOF-intolerant gene distribution across the genome and its association with benign population and pathogenic classified deletions from individuals with presumably monogenic disorders. For people with presumably monogenic epilepsy, we compared Human Phenotype Ontology terms in people with large and small deletions.

RESULTS

We identified LOF-intolerant gene dense regions that were enriched for ClinVar and depleted for population copy number variants. Analysis of data from >143,000 individuals with a suspected monogenic disorder showed that 2.5% of haploinsufficiency disorder-associated deletions can affect at least 1 other LOF-intolerant gene. Focusing on epilepsy, we observed that 13.1% of pathogenic and likely pathogenic ClinVar deletions <3 megabase pair, covering the diagnostically most relevant genes, affected at least 1 additional LOF-intolerant gene. Those patients have potentially more complex phenotypes with increasing deletion size.

CONCLUSION

We could systematically show that large deletions frequently affected admditional LOF-intolerant genes in addition to the established disease gene. Further research is needed to understand how additional potential disease-relevant genes influence monogenic disorders to improve clinical care and the efficacy of targeted therapies.

The diagnostic protocol for hereditary spherocytosis-2021 update

Background

Hereditary spherocytosis (HS), a commonly encountered hereditary hemolytic disease, is mostly inherited in an autosomal dominant manner. The clinical manifestations in patients with HS show obvious heterogeneity. Moreover, the sensitivity or specificity of some HS diagnostic tests are not ideal and may easily result in misdiagnosis or missed diagnosis in some patients. The objective of this study was to propose a simple and practical diagnostic protocol, which can contribute to the diagnosis of HS and its differential diagnosis with different types of hemolytic anemia such as thalassemia (THAL), autoimmune hemolytic anemia (AIHA), and glucose‐6‐phosphate dehydrogenase (G6PD) deficiency, thus, to provide an alternative simple and reliable method for better clinical diagnosis of HS.

Methods

Through combing our research with existing experimental technologies and studies, we propose a simple and practical protocol for HS diagnosis, which will help clinicians to improve HS diagnosis.

Results

Compared with the existing HS diagnostic protocols, the HS diagnostic protocol we proposed is simpler. In this new protocol, some experimental tests with ideal diagnostic efficiency are added, such as mean reticulocyte volume (MRV), mean sphered cell volume (MSCV), mean corpuscular volume (MCV), in combination with the observation of clinical manifestations, family investigation, routine tests for hemolytic anemia, genetic testing, and other screening tests.

Conclusion

The HS diagnostic protocol we proposed could improve the clinical practice and efficiency of HS diagnosis.

Evaluation of the parents' anxiety levels before and after the diagnosis of their child with a rare genetic disease: the necessity of psychological support

Background

The diagnosis of the rare genetic diseases has great importance in treating multisystemic conditions, preventing potential complications, and estimating disease risk for family members. The duration of obtaining genetic test results is varies. The demand to learn the diagnosis of a possible untreatable illness involves a struggle between uncertainty and a lifetime chronic disease. The current uncertainty of their child's condition and the long wait for a diagnosis may increase the parents' anxiety level and cause difficulties in the continuation of diagnostic procedures in some families. This study aimed to investigate the prediagnosis and postdiagnosis anxiety levels of parents who have a child with a rare genetic disease.

Method

The parents in this study, mothers or fathers, admitted their children to the Bezmialem Vakıf University Medical Genetics Clinic due to a suspected rare genetic disease (n = 40). Researchers created “The Sociodemographic Questionnaire” and used it to analyze the parents' sociodemographic status. In addition, they used the State-Trait Anxiety Inventory (STAI) to determine the anxiety levels of the parents.

Results

The state anxiety levels of parents decreased significantly after learning the diagnosis. However, there was no statistically significant decrease observed in trait anxiety levels.

Conclusion

Data from this study revealed that informing parents about their child's disease and properly explaining to them the expected difficulties might help to reduce their anxiety levels. Psychological support for parents is necessary to reduce their long-term stress, thus increasing the patient's compliance with treatment.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13023-021-02046-2.

Current status of use of high throughput nucleotide sequencing in rheumatology

OBJECTIVE

Here, we assess the usage of high throughput sequencing (HTS) in rheumatic research and the availability of public HTS data of rheumatic samples.

METHODS

We performed a semiautomated literature review on PubMed, consisting of an R-script and manual curation as well as a manual search on the Sequence Read Archive for public available HTS data.

RESULTS

Of the 699 identified articles, rheumatoid arthritis (n=182 publications, 26%), systemic lupus erythematous (n=161, 23%) and osteoarthritis (n=152, 22%) are among the rheumatic diseases with the most reported use of HTS assays. The most represented assay is RNA-Seq (n=457, 65%) for the identification of biomarkers in blood or synovial tissue. We also find, that the quality of accompanying clinical characterisation of the sequenced patients differs dramatically and we propose a minimal set of clinical data necessary to accompany rheumatological-relevant HTS data.

CONCLUSION

HTS allows the analysis of a broad spectrum of molecular features in many samples at the same time. It offers enormous potential in novel personalised diagnosis and treatment strategies for patients with rheumatic diseases. Being established in cancer research and in the field of Mendelian diseases, rheumatic diseases are about to become the third disease domain for HTS, especially the RNA-Seq assay. However, we need to start a discussion about reporting of clinical characterisation accompany rheumatological-relevant HTS data to make clinical meaningful use of this data.

AI-based language models powering drug discovery and development

The discovery and development of new medicines is expensive, time-consuming, and often inefficient, with many failures along the way. Powered by artificial intelligence (AI), language models (LMs) have changed the landscape of natural language processing (NLP), offering possibilities to transform treatment development more effectively. Here, we summarize advances in AI-powered LMs and their potential to aid drug discovery and development. We highlight opportunities for AI-powered LMs in target identification, clinical design, regulatory decision-making, and pharmacovigilance. We specifically emphasize the potential role of AI-powered LMs for developing new treatments for Coronavirus 2019 (COVID-19) strategies, including drug repurposing, which can be extrapolated to other infectious diseases that have the potential to cause pandemics. Finally, we set out the remaining challenges and propose possible solutions for improvement.

Comparative Analysis for the Performance of Long-Read-Based Structural Variation Detection Pipelines in Tandem Repeat Regions

There has been growing recognition of the vital links between structural variations (SVs) and diverse diseases. Research suggests that, with much longer DNA fragments and abundant contextual information, long-read technologies have advantages in SV detection even in complex repetitive regions. So far, several pipelines for calling SVs from long-read sequencing data have been proposed and used in human genome research. However, the performance of these pipelines is still lack of deep exploration and adequate comparison. In this study, we comprehensively evaluated the performance of three commonly used long-read SV detection pipelines, namely PBSV, Sniffles and PBHoney, especially the performance on detecting the SVs in tandem repeat regions (TRRs). Evaluated by using a robust benchmark for germline SV detection as the gold standard, we thoroughly estimated the precision, recall and F1 score of insertions and deletions detected by the pipelines. Our results revealed that all these pipelines clearly exhibited better performance outside TRRs than that in TRRs. The F1 scores of Sniffles in and outside TRRs were 0.60 and 0.76, respectively. The performance of PBSV was similar to that of Sniffles, and was generally higher than that of PBHoney. In conclusion, our findings can be benefit for choosing the appropriate pipelines in real practice and are good complementary to the application of long-read sequencing technologies in the research of rare diseases.

Unraveling Gene Fusions for Drug Repositioning in High-Risk Neuroblastoma

High-risk neuroblastoma (NB) remains a significant therapeutic challenge facing current pediatric oncology patients. Structural variants such as gene fusions have shown an initial promise in enhancing mechanistic understanding of NB and improving survival rates. In this study, we performed a comprehensive in silico investigation on the translational ability of gene fusions for patient stratification and treatment development for high-risk NB patients. Specifically, three state-of-the-art gene fusion detection algorithms, including ChimeraScan, SOAPfuse, and TopHat-Fusion, were employed to identify the fusion transcripts in a RNA-seq data set of 498 neuroblastoma patients. Then, the 176 high-risk patients were further stratified into four different subgroups based on gene fusion profiles. Furthermore, Kaplan-Meier survival analysis was performed, and differentially expressed genes (DEGs) for the redefined high-risk group were extracted and functionally analyzed. Finally, repositioning candidates were enriched in each patient subgroup with drug transcriptomic profiles from the LINCS L1000 Connectivity Map. We found the number of identified gene fusions was increased from clinical the low-risk stage to the high-risk stage. Although the technical concordance of fusion detection algorithms was suboptimal, they have a similar biological relevance concerning perturbed pathways and regulated DEGs. The gene fusion profiles could be utilized to redefine high-risk patient subgroups with significant onset age of NB, which yielded the improved survival curves (Log-rank p value ≤ 0.05). Out of 48 enriched repositioning candidates, 45 (93.8%) have antitumor potency, and 24 (50%) were confirmed with either on-going clinical trials or literature reports. The gene fusion profiles have a discrimination power for redefining patient subgroups in high-risk NB and facilitate precision medicine-based drug repositioning implementation.

The Increasing Impact of Translational Research in the Molecular Diagnostics of Neuromuscular Diseases

The diagnosis of neuromuscular diseases (NMDs) has been progressively evolving from the grouping of clinical symptoms and signs towards the molecular definition. Optimal clinical, biochemical, electrophysiological, electrophysiological, and histopathological characterization is very helpful to achieve molecular diagnosis, which is essential for establishing prognosis, treatment and genetic counselling. Currently, the genetic approach includes both the gene-targeted analysis in specific clinically recognizable diseases, as well as genomic analysis based on next-generation sequencing, analyzing either the clinical exome/genome or the whole exome or genome. However, as of today, there are still many patients in whom the causative genetic variant cannot be definitely established and variants of uncertain significance are often found. In this review, we address these drawbacks by incorporating two additional biological omics approaches into the molecular diagnostic process of NMDs. First, functional genomics by introducing experimental cell and molecular biology to analyze and validate the variant for its biological effect in an in-house translational diagnostic program, and second, incorporating a multi-omics approach including RNA-seq, metabolomics, and proteomics in the molecular diagnosis of neuromuscular disease. Both translational diagnostics programs and omics are being implemented as part of the diagnostic process in academic centers and referral hospitals and, therefore, an increase in the proportion of neuromuscular patients with a molecular diagnosis is expected. This improvement in the process and diagnostic performance of patients will allow solving aspects of their health problems in a precise way and will allow them and their families to take a step forward in their lives.

Next-Generation Sequencing Technologies and Neurogenetic Diseases

Next-generation sequencing (NGS) technology has led to great advances in understanding the causes of Mendelian and complex neurological diseases. Owing to the complexity of genetic diseases, the genetic factors contributing to many rare and common neurological diseases remain poorly understood. Selecting the correct genetic test based on cost-effectiveness, coverage area, and sequencing range can improve diagnosis, treatments, and prevention. Whole-exome sequencing and whole-genome sequencing are suitable methods for finding new mutations, and gene panels are suitable for exploring the roles of specific genes in neurogenetic diseases. Here, we provide an overview of the classifications, applications, advantages, and limitations of NGS in research on neurological diseases. We further provide examples of NGS-based explorations and insights of the genetic causes of neurogenetic diseases, including Charcot-Marie-Tooth disease, spinocerebellar ataxias, epilepsy, and multiple sclerosis. In addition, we focus on issues related to NGS-based analyses, including interpretations of variants of uncertain significance, de novo mutations, congenital genetic diseases with complex phenotypes, and single-molecule real-time approaches.

Comparison of the diagnostic yield of aCGH and genome-wide sequencing across different neurodevelopmental disorders

Most consensus recommendations for the genetic diagnosis of neurodevelopmental disorders (NDDs) do not include the use of next generation sequencing (NGS) and are still based on chromosomal microarrays, such as comparative genomic hybridization array (aCGH). This study compares the diagnostic yield obtained by aCGH and clinical exome sequencing in NDD globally and its spectrum of disorders. To that end, 1412 patients clinically diagnosed with NDDs and studied with aCGH were classified into phenotype categories: global developmental delay/intellectual disability (GDD/ID); autism spectrum disorder (ASD); and other NDDs. These categories were further subclassified based on the most frequent accompanying signs and symptoms into isolated forms, forms with epilepsy; forms with micro/macrocephaly and syndromic forms. Two hundred and forty-five patients of the 1412 were subjected to clinical exome sequencing. Diagnostic yield of aCGH and clinical exome sequencing, expressed as the number of solved cases, was compared for each phenotype category and subcategory. Clinical exome sequencing was superior than aCGH for all cases except for isolated ASD, with no additional cases solved by NGS. Globally, clinical exome sequencing solved 20% of cases (versus 5.7% by aCGH) and the diagnostic yield was highest for all forms of GDD/ID and lowest for Other NDDs (7.1% versus 1.4% by aCGH) and ASD (6.1% versus 3% by aCGH). In the majority of cases, diagnostic yield was higher in the phenotype subcategories than in the mother category. These results suggest that NGS could be used as a first-tier test in the diagnostic algorithm of all NDDs followed by aCGH when necessary.

GPCards: An integrated database of genotype-phenotype correlations in human genetic diseases

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The patient-level genotype-phenotype correlations in GPCards accelerated the development of medical genetics.

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The integrated 62 genomic sources provide comprehensive information for interpreting pathogenicity.

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Analysis function in GPCards would help users to decipher their data of genotype-phenotype correlations.

Genotype–phenotype correlations are the basis of precision medicine of human genetic diseases. However, it remains a challenge for clinicians and researchers to conveniently access detailed individual-level clinical phenotypic features of patients with various genetic variants. To address this urgent need, we manually searched for genetic studies in PubMed and catalogued 8,309 genetic variants in 1,288 genes from 17,738 patients with detailed clinical phenotypic features from 1,855 publications. Based on genotype–phenotype correlations in this dataset, we developed an user-friendly online database called GPCards (http://genemed.tech/gpcards/), which not only provided the association between genetic diseases and disease genes, but also the prevalence of various clinical phenotypes related to disease genes and the patient-level mapping between these clinical phenotypes and genetic variants. To accelerate the interpretation of genetic variants, we integrated 62 well-known variant-level and gene-level genomic data sources, including functional predictions, allele frequencies in different populations, and disease-related information. Furthermore, GPCards enables automatic analyses of users’ own genetic data, comprehensive annotation, prioritization of candidate functional variants, and identification of genotype–phenotype correlations using custom parameters. In conclusion, GPCards is expected to accelerate the interpretation of genotype–phenotype correlations, subtype classification, and candidate gene prioritisation in human genetic diseases.

Clinical Genomics for the Diagnosis of Monogenic Forms of Inflammatory Bowel Disease: A Position Paper From the Paediatric IBD Porto Group of European Society of Paediatric Gastroenterology, Hepatology and Nutrition

BACKGROUND

It is important to identify patients with monogenic IBD as management may differ from classical IBD. In this position statement we formulate recommendations for the use of genomics in evaluating potential monogenic causes of IBD across age groups.

METHODS

The consensus included paediatric IBD specialists from the Paediatric IBD Porto group of the European Society of Paediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) and specialists from several monogenic IBD research consortia. We defined key topics and performed a systematic literature review to cover indications, technologies (targeted panel, exome and genome sequencing), gene panel setup, cost-effectiveness of genetic screening, and requirements for the clinical care setting. We developed recommendations that were voted upon by all authors and Porto group members (32 voting specialists).

RESULTS

We recommend next-generation DNA-sequencing technologies to diagnose monogenic causes of IBD in routine clinical practice embedded in a setting of multidisciplinary patient care. Routine genetic screening is not recommended for all IBD patients. Genetic testing should be considered depending on age of IBD-onset (infantile IBD, very early-onset IBD, paediatric or young adult IBD), and further criteria, such as family history, relevant comorbidities, and extraintestinal manifestations. Genetic testing is also recommended in advance of hematopoietic stem cell transplantation. We developed a diagnostic algorithm that includes a gene panel of 75 monogenic IBD genes. Considerations are provided also for low resource countries.

CONCLUSIONS

Genomic technologies should be considered an integral part of patient care to investigate patients at risk for monogenic forms of IBD.

Strategies to Identify Genetic Variants Causing Infertility

Genetic causes are thought to underlie about half of infertility cases, but understanding the genetic bases has been a major challenge. Modern genomics tools allow more sophisticated exploration of genetic causes of infertility through population, family-based, and individual studies. Nevertheless, potential therapies based on genetic diagnostics will be limited until there is certainty regarding the causality of genetic variants identified in an individual. Genome modulation and editing technologies have revolutionized our ability to functionally test such variants, and also provide a potential means for clinical correction of infertility variants. This review addresses strategies being used to identify causative variants of infertility.

An antibody-free liver cancer screening approach based on nanoplasmonics biosensing chips via spectrum-based deep learning

The clinical needs of rapidly screening liver cancer in large populations have asked for a facile and low-cost point-of-care testing (POCT) method. We present a nanoplasmonics biosensing chip (NBC) that would empower antibody-free detection with simplified analysis procedures for POCT. The cheaply fabricable NBC consists of multiple silver nanoparticle-decorated ZnO nanorods on cellulose filter paper and would enable one-drop blood tests through surface-enhanced Raman spectroscopy (SERS) detection. In this work, utilizing such an NBC and deep neural network (DNN) modeling, a direct serological detection platform was constructed for automatically identifying liver cancer within minutes. This chip could enhance Raman signals enough to be applied to POCT. A classification DNN model was established by spectrum-based deep learning with 1140 serum SERS spectra in equal proportions from hepatocellular carcinoma (HCC) patients and healthy individuals, achieving an identification accuracy of 91% on an external validation set of 100 spectra (50 HCC versus 50 healthy). The intelligent platform, based on the biosensing chip and DNN, has the potential for clinical applications and generalizable use in quickly screening or detecting other types of cancer.

Multi-Gene Next-Generation Sequencing for Molecular Diagnosis of Autosomal Recessive Congenital Ichthyosis: A Genotype-Phenotype Study of Four Italian Patients

Autosomal recessive congenital ichthyoses (ARCI) are rare genodermatosis disorders characterized by phenotypic and genetic heterogeneity. At least fourteen genes so far have been related to ARCI; however, despite genetic heterogeneity, phenotypes associated with mutation of different ARCI genes may overlap, thereby making difficult their clinical and molecular classification. In addition, molecular tests for diagnosis of such an extremely rare heterogeneous inherited disease are not easily available in clinical settings. In the attempt of identifying the genetic cause of the disease in four Italian patients with ARCI, we performed next-generation sequencing (NGS) analysis targeting 4811 genes that have been previously linked to human genetic diseases; we focused our analysis on the 13 known ARCI genes comprised in the panel. Nine different variants including three novel small nucleotide changes and two novel large deletions have been identified and validated in the ABCA12, ALOX12B, CYP4F22, and SULT2B1 genes. Notably, two patients had variants in more than one gene. The identification and validation of new pathogenic ABCA12, ALOX12B, CYP4F22, and SULT2B1 variants through multi-gene NGS in four cases of ARCI further highlight the importance of these genes in proper skin function and development.