One is the loneliest number: genotypic matchmaking using the electronic health record

MSL2 variants lead to a neurodevelopmental syndrome with lack of coordination, epilepsy, specific dysmorphisms, and a distinct episignature

Epigenetic dysregulation has emerged as an important etiological mechanism of neurodevelopmental disorders (NDDs). Pathogenic variation in epigenetic regulators can impair deposition of histone post-translational modifications leading to aberrant spatiotemporal gene expression during neurodevelopment. The male-specific lethal (MSL) complex is a prominent multi-subunit epigenetic regulator of gene expression and is responsible for histone 4 lysine 16 acetylation (H4K16ac). Using exome sequencing, here we identify a cohort of 25 individuals with heterozygous de novo variants in MSL complex member MSL2. MSL2 variants were associated with NDD phenotypes including global developmental delay, intellectual disability, hypotonia, and motor issues such as coordination problems, feeding difficulties, and gait disturbance. Dysmorphisms and behavioral and/or psychiatric conditions, including autism spectrum disorder, and to a lesser extent, seizures, connective tissue disease signs, sleep disturbance, vision problems, and other organ anomalies, were observed in affected individuals. As a molecular biomarker, a sensitive and specific DNA methylation episignature has been established. Induced pluripotent stem cells (iPSCs) derived from three members of our cohort exhibited reduced MSL2 levels. Remarkably, while NDD-associated variants in two other members of the MSL complex (MOF and MSL3) result in reduced H4K16ac, global H4K16ac levels are unchanged in iPSCs with MSL2 variants. Regardless, MSL2 variants altered the expression of MSL2 targets in iPSCs and upon their differentiation to early germ layers. Our study defines an MSL2-related disorder as an NDD with distinguishable clinical features, a specific blood DNA episignature, and a distinct, MSL2-specific molecular etiology compared to other MSL complex-related disorders.

Integrating non-mammalian model organisms in the diagnosis of rare genetic diseases in humans

Next-generation sequencing technology has rapidly accelerated the discovery of genetic variants of interest in individuals with rare diseases. However, showing that these variants are causative of the disease in question is complex and may require functional studies. Use of non-mammalian model organisms - mainly fruitflies (Drosophila melanogaster), nematode worms (Caenorhabditis elegans) and zebrafish (Danio rerio) - enables the rapid and cost-effective assessment of the effects of gene variants, which can then be validated in mammalian model organisms such as mice and in human cells. By probing mechanisms of gene action and identifying interacting genes and proteins in vivo, recent studies in these non-mammalian model organisms have facilitated the diagnosis of numerous genetic diseases and have enabled the screening and identification of therapeutic options for patients. Studies in non-mammalian model organisms have also shown that the biological processes underlying rare diseases can provide insight into more common mechanisms of disease and the biological functions of genes. Here, we discuss the opportunities afforded by non-mammalian model organisms, focusing on flies, worms and fish, and provide examples of their use in the diagnosis of rare genetic diseases.

Improving child health through Big Data and data science

Child health is defined by a complex, dynamic network of genetic, cultural, nutritional, infectious, and environmental determinants at distinct, developmentally determined epochs from preconception to adolescence. This network shapes the future of children, susceptibilities to adult diseases, and individual child health outcomes. Evolution selects characteristics during fetal life, infancy, childhood, and adolescence that adapt to predictable and unpredictable exposures/stresses by creating alternative developmental phenotype trajectories. While child health has improved in the United States and globally over the past 30 years, continued improvement requires access to data that fully represent the complexity of these interactions and to new analytic methods. Big Data and innovative data science methods provide tools to integrate multiple data dimensions for description of best clinical, predictive, and preventive practices, for reducing racial disparities in child health outcomes, for inclusion of patient and family input in medical assessments, and for defining individual disease risk, mechanisms, and therapies. However, leveraging these resources will require new strategies that intentionally address institutional, ethical, regulatory, cultural, technical, and systemic barriers as well as developing partnerships with children and families from diverse backgrounds that acknowledge historical sources of mistrust. We highlight existing pediatric Big Data initiatives and identify areas of future research. IMPACT: Big Data and data science can improve child health. This review highlights the importance for child health of child-specific and life course-based Big Data and data science strategies. This review provides recommendations for future pediatric-specific Big Data and data science research.

The Challenge of Genetic Variants of Uncertain Clinical Significance : A Narrative Review

Genomic tests expand diagnostic and screening opportunities but also identify genetic variants of uncertain clinical significance (VUSs). Only a minority of VUSs are likely to prove pathogenic when later reassessed, but resolution of the uncertainty is rarely timely. That uncertainty adds complexity to clinical decision making and can result in harms and costs to patients and the health care system, including the time-consuming analysis required to interpret a VUS and the potential for unnecessary treatment and adverse psychological effects. Current efforts to improve variant interpretation will help reduce the scope of the problem, but the high prevalence of rare and novel variants in the human genome points to VUSs as an ongoing challenge. Additional strategies can help mitigate the potential harms of VUSs, including testing protocols that limit identification or reporting of VUSs, subclassification of VUSs according to the likelihood of pathogenicity, routine family-based evaluation of variants, and enhanced counseling efforts. All involve tradeoffs, and the appropriate balance of measures is likely to vary for different test uses and clinical settings. Cross-specialty deliberation and public input could contribute to systematic and broadly supported policies for managing VUSs.

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.

Meeting the needs of patients with ultrarare diseases

Patients with ultrarare diseases present unique challenges to the health care systems of developed economies that demand novel approaches, beginning with achieving a diagnosis and concluding with long-term treatment. The challenges derive from numbers. On the one hand, the rarity of the disease phenotypes means that the vast majority of ultrarare patients are never diagnosed, and for the fortunate few who are diagnosed, the journey to a genetic diagnosis is long and perilous. On the other hand, as more human genomes are sequenced, the number of these patients identified is growing logarithmically. Once patients are diagnosed, personalized medicines must be rapidly developed and delivered. Here I define the problems and propose a nonprofit model to meet the needs of some of these patients.