Common genetic variation associated with Mendelian disease severity revealed through cryptic phenotype analysis

Clinical heterogeneity is common in Mendelian disease, but small sample sizes make it difficult to identify specific contributing factors. However, if a rare disease represents the severely affected extreme of a spectrum of phenotypic variation, then modifier effects may be apparent within a larger subset of the population. Analyses that take advantage of this full spectrum could have substantially increased power. To test this, we developed cryptic phenotype analysis (CPA), a model-based approach that uses symptom data to infer latent quantitative traits that capture disease-related phenotypic variability. By applying this approach to 50 Mendelian diseases in two large cohorts of patients, we found that these quantitative traits reliably captured disease severity. We then conducted genome-wide association analyses for five of the inferred cryptic phenotypes, uncovering common variation that was predictive of Mendelian disease-related diagnoses and outcomes. Overall, this study highlights the utility of computationally derived phenotypes and biobank-scale cohorts for investigating the complex genetic architecture of Mendelian diseases.

SvAnna: efficient and accurate pathogenicity prediction for coding and regulatory structural variants in long-read genome sequencing

Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to limitations of existing technology. Recent technological advances such as long-read sequencing (LRS) enable more comprehensive detection of SVs, but approaches for clinical prioritization of candidate SVs are needed. Existing computational approaches do not specifically target LRS data, thereby missing a substantial proportion of candidate SVs, and do not provide a unified computational model for assessing all types of SVs. Structural Variant Annotation and Analysis (SvAnna) assesses all classes of SV and their intersection with transcripts and regulatory sequences in the context of topologically associating domains, relating predicted effects on gene function with clinical phenotype data. We show with a collection of 182 published case reports with pathogenic SVs that SvAnna places over 90% of pathogenic SVs in the top ten ranks. The interpretable prioritizations provided by SvAnna will facilitate the widespread adoption of LRS in diagnostic genomics.

The Impact of Environmental Factors on Monogenic Mendelian Diseases

Environmental factors and gene-environment interactions modify the variable expressivity, progression, severity, and onset of some classic (monogenic) Mendelian-inherited genetic diseases. Cystic fibrosis, Huntington disease, Parkinson’s disease, and sickle cell disease are examples of well-known Mendelian disorders that are influenced by exogenous exposures. Environmental factors may act by direct or indirect mechanisms to modify disease severity, timing, and presentation, including through epigenomic influences, protein misfolding, miRNA alterations, transporter activity, and mitochondrial effects. Because pathological features of early-onset Mendelian diseases can mimic later onset complex diseases, we propose that studies of environmental exposure vulnerabilities using monogenic model systems of rare Mendelian diseases have high potential to provide insight into complex disease phenotypes arising from multi-genetic/multi-toxicant interactions. Mendelian disorders can be modeled by homologous mutations in animal model systems with strong recapitulation of human disease etiology and natural history, providing an important advantage for study of these diseases. Monogenic high penetrant mutations are ideal for toxicant challenge studies with a wide variety of environmental stressors, because background genetic variability may be less able to alter the relatively strong phenotype driving disease-causing mutations. These models promote mechanistic understandings of gene-environment interactions and biological pathways relevant to both Mendelian and related sporadic complex disease outcomes by creating a sensitized background for relevant environmental risk factors. Additionally, rare disease communities are motivated research participants, creating the potential of strong research allies among rare Mendelian disease advocacy groups and disease registries and providing a variety of translational opportunities that are under-utilized in genetic or environmental health science.

A map of copy number variations in the Tunisian population: a valuable tool for medical genomics in North Africa

Copy number variation (CNV) is considered as the most frequent type of structural variation in the human genome. Some CNVs can act on human phenotype diversity, encompassing rare Mendelian diseases and genomic disorders. The North African populations remain underrepresented in public genetic databases in terms of single-nucleotide variants as well as for larger genomic mutations. In this study, we present the first CNV map for a North African population using the Affymetrix Genome-Wide SNP (single-nucleotide polymorphism) array 6.0 array genotyping intensity data to call CNVs in 102 Tunisian healthy individuals. Two softwares, PennCNV and Birdsuite, were used to call CNVs in order to provide reliable data. Subsequent bioinformatic analyses were performed to explore their features and patterns. The CNV map of the Tunisian population includes 1083 CNVs spanning 61.443 Mb of the genome. The CNV length ranged from 1.017 kb to 2.074 Mb with an average of 56.734 kb. Deletions represent 57.43% of the identified CNVs, while duplications and the mixed loci are less represented. One hundred and three genes disrupted by CNVs are reported to cause 155 Mendelian diseases/phenotypes. Drug response genes were also reported to be affected by CNVs. Data on genes overlapped by deletions and duplications segments and the sequence properties in and around them also provided insights into the functional and health impacts of CNVs. These findings represent valuable clues to genetic diversity and personalized medicine in the Tunisian population as well as in the ethnically similar populations from North Africa.

Exploiting the Autozygome to Support Previously Published Mendelian Gene-Disease Associations: An Update

There is a growing interest in standardizing gene-disease associations for the purpose of facilitating the proper classification of variants in the context of Mendelian diseases. One key line of evidence is the independent observation of pathogenic variants in unrelated individuals with similar phenotypes. Here, we expand on our previous effort to exploit the power of autozygosity to produce homozygous pathogenic variants that are otherwise very difficult to encounter in the homozygous state due to their rarity. The identification of such variants in genes with only tentative associations to Mendelian diseases can add to the existing evidence when observed in the context of compatible phenotypes. In this study, we report 20 homozygous variants in 18 genes (ADAMTS18, ARNT2, ASTN1, C3, DMBX1, DUT, GABRB3, GM2A, KIF12, LOXL3, NUP160, PTRHD1, RAP1GDS1, RHOBTB2, SIGMAR1, SPAST, TENM3, and WASHC5) that satisfy the ACMG classification for pathogenic/likely pathogenic if the involved genes had confirmed rather than tentative links to diseases. These variants were selected because they were truncating, founder with compelling segregation or supported by robust functional assays as with the DUT variant that we present its validation using yeast model. Our findings support the previously reported disease associations for these genes and represent a step toward their confirmation.

Pathogenesis of Eosinophilic Esophagitis: A Comprehensive Review of the Genetic and Molecular Aspects

Eosinophilic esophagitis (EoE) is a relatively new condition described as an allergic-mediated disease of the esophagus. Clinically, it is characterized by dysphagia, food impaction, and reflux-like symptoms. Multiple genome-wide association studies (GWAS) have been conducted to identify genetic loci associated with EoE. The integration of numerous studies investigating the genetic polymorphisms in EoE and the Mendelian diseases associated with EoE are discussed to provide insights into the genetic risk of EoE, notably focusing on CCL26 and CAPN14. We focus on the genetic loci investigated thus far, and their classification according to whether the function near the loci is known. The pathophysiology of EoE is described by separately presenting the known function of each cell and molecule, with the major contributors being eosinophils, Th2 cells, thymic stromal lymphopoietin (TSLP), transforming growth factor (TGF)-β1, and interleukin (IL)-13. This review aims to provide detailed descriptions of the genetics and the comprehensive pathophysiology of EoE.