Phenotype-tissue expression and exploration (PTEE) resource facilitates the choice of tissue for RNA-seq-based clinical genetics studies

Downstream Assays for Variant Resolution: Epigenetics, RNA Sequnncing, and Metabolomics

As the availability of advanced molecular testing like whole exome and genome sequencing expands, it comes with the added complication of interpreting inconclusive results, including determining the relevance of variants of uncertain significance or failing to find a variant in an otherwise suspected specific genetic disorder. This complication necessitates the use of alternative testing methods to gather more information in support of, or against, a particular genetic diagnosis. Therefore, new genome-wide approaches, including DNA epigenetic testing, RNA sequencing, and metabolomics, are increasingly being used to increase the diagnostic yield when used in conjunction with more conventional genetic tests.

Integrative omics approaches to advance rare disease diagnostics

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

Epilepsies of presumed genetic etiology show enrichment of rare variants that occur in the general population

Previous studies suggested that severe epilepsies, e.g., developmental and epileptic encephalopathies (DEEs), are mainly caused by ultra-rare de novo genetic variants. For milder disease, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 control individuals. Here, we separately analyzed three different groups of epilepsies: severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in control individuals with an allele count ≥ 1 and a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD ≥ 20), and to have an odds ratio in individuals with epilepsy ≥ 2. We identified genes enriched with QRVs primarily in NAFE (n = 72), followed by GGE (n = 32) and DEE (n = 21). This suggests that rare variants may play a more important role for causality of NAFE than for DEE. Moreover, we found that genes harboring QRVs, e.g., HSGP2, FLNA, or TNC, encode proteins that are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE that occur also in the general population, while in DEE and GGE, the contribution of such variants appears more limited.

The role of rare genetic variants enrichment in epilepsies of presumed genetic etiology

Previous studies suggested that severe epilepsies e.g., developmental and epileptic encephalopathies (DEE) are mainly caused by ultra-rare de novo genetic variants. For milder phenotypes, rare genetic variants could contribute to the phenotype. To determine the importance of rare variants for different epilepsy types, we analyzed a whole-exome sequencing cohort of 9,170 epilepsy-affected individuals and 8,436 controls. Here, we separately analyzed three different groups of epilepsies : severe DEEs, genetic generalized epilepsy (GGE), and non-acquired focal epilepsy (NAFE). We required qualifying rare variants (QRVs) to occur in controls at a minor allele frequency ≤ 1:1,000, to be predicted as deleterious (CADD≥20), and to have an odds ratio in epilepsy cases ≥2. We identified genes enriched with QRVs in DEE (n=21), NAFE (n=72), and GGE (n=32) - the number of enriched genes are found greatest in NAFE and least in DEE. This suggests that rare variants may play a more important role for causality of NAFE than in DEE. Moreover, we found that QRV-carrying genes e.g., HSGP2, FLNA or TNC are involved in structuring the brain extracellular matrix. The present study confirms an involvement of rare variants for NAFE, while in DEE and GGE, the contribution of such variants appears more limited.

Phospholipid Scramblase 4 (PLSCR4) Regulates Adipocyte Differentiation via PIP3-Mediated AKT Activation

Phospholipid scramblase 4 (PLSCR4) is a member of a conserved enzyme family with high relevance for the remodeling of phospholipid distribution in the plasma membrane and the regulation of cellular signaling. While PLSCR1 and -3 are involved in the regulation of adipose-tissue expansion, the role of PLSCR4 is so far unknown. PLSCR4 is significantly downregulated in an adipose-progenitor-cell model of deficiency for phosphatase and tensin homolog (PTEN). PTEN acts as a tumor suppressor and antagonist of the growth and survival signaling phosphoinositide 3-kinase (PI3K)/AKT cascade by dephosphorylating phosphatidylinositol-3,4,5-trisphosphate (PIP3). Patients with PTEN germline deletion frequently develop lipomas. The underlying mechanism for this aberrant adipose-tissue growth is incompletely understood. PLSCR4 is most highly expressed in human adipose tissue, compared with other phospholipid scramblases, suggesting a specific role of PLSCR4 in adipose-tissue biology. In cell and mouse models of lipid accumulation, we found PLSCR4 to be downregulated. We observed increased adipogenesis in PLSCR4-knockdown adipose progenitor cells, while PLSCR4 overexpression attenuated lipid accumulation. PLSCR4 knockdown was associated with increased PIP3 levels and the activation of AKT. Our results indicated that PLSCR4 is a regulator of PI3K/AKT signaling and adipogenesis and may play a role in PTEN-associated adipose-tissue overgrowth and lipoma formation.

Altered gene expression profiles impair the nervous system development in individuals with 15q13.3 microdeletion

The 15q13.3 microdeletion has pleiotropic effects ranging from apparently healthy to severely affected individuals. The underlying basis of the variable phenotype remains elusive. We analyzed gene expression using blood from three individuals with 15q13.3 microdeletion and brain cortex tissue from ten mice Df[h15q13]/+. We assessed differentially expressed genes (DEGs), protein–protein interaction (PPI) functional modules, and gene expression in brain developmental stages. The deleted genes’ haploinsufficiency was not transcriptionally compensated, suggesting a dosage effect may contribute to the pathomechanism. DEGs shared between tested individuals and a corresponding mouse model show a significant overlap including genes involved in monogenic neurodevelopmental disorders. Yet, network-wide dysregulatory effects suggest the phenotype is not caused by a single critical gene. A significant proportion of blood DEGs, silenced in adult brain, have maximum expression during the prenatal brain development. Based on DEGs and their PPI partners we identified altered functional modules related to developmental processes, including nervous system development. We show that the 15q13.3 microdeletion has a ubiquitous impact on the transcriptome pattern, especially dysregulation of genes involved in brain development. The high phenotypic variability seen in 15q13.3 microdeletion could stem from an increased vulnerability during brain development, instead of a specific pathomechanism.

Toward transcriptomics as a primary tool for rare disease investigation

In the past 5 years transcriptome or RNA-sequencing (RNA-seq) has steadily emerged as a complementary assay for rare disease diagnosis and discovery. In this perspective, we summarize several recent developments and challenges in the use of RNA-seq for rare disease investigation. Using an accessible patient sample, such as blood, skin, or muscle, RNA-seq enables the assay of expressed RNA transcripts. Analysis of RNA-seq allows the identification of aberrant or outlier gene expression and alternative splicing as functional evidence to support rare disease study and diagnosis. Further, many types of variant effects can be profiled beyond coding variants, as the consequences of noncoding variants that impact gene expression and splicing can be directly observed. This is particularly apparent for structural variants that disproportionately underlie outlier gene expression and for splicing variants in which RNA-seq can both measure aberrant canonical splicing and detect deep intronic effects. However, a major potential limitation of RNA-seq in rare disease investigation is the developmental and cell type specificity of gene expression as a pathogenic variant's effect may be limited to a specific spatiotemporal context and access to a patient's tissue sample from the relevant tissue and timing of disease expression may not be possible. We speculate that as advances in computational methods and emerging experimental techniques overcome both developmental and cell type specificity, there will be broadening use of RNA sequencing and multiomics in rare disease diagnosis and delivery of precision health.