Methods to Improve Molecular Diagnosis in Genomic Cold Cases in Pediatric Neurology

Digenic variant interpretation with hypothesis-driven explainable AI

The digenic inheritance hypothesis holds the potential to enhance diagnostic yield in rare diseases. Computational approaches capable of accurately interpreting and prioritizing digenic combinations of variants based on the proband's phenotypes and family information can provide valuable assistance during the diagnostic process. We developed diVas, a hypothesis-driven machine learning approach that interprets genomic variants across different gene pairs. DiVas demonstrates strong performance in both classifying and prioritizing causative digenic combinations of rare variants within the top positions across 11 cases with the complete list of variants available (73% sensitivity and a median ranking of 3). Furthermore, it achieves a sensitivity of 0.81 when applied to 645 published causative digenic combinations. Additionally, diVas leverages explainable artificial intelligence to elucidate the digenic disease mechanism for predicted positive pairs.

An Extended Phenotype of PPP1R13L Cardiocutaneous Syndrome

Dilated cardiomyopathy (DCM) is a rare disease in children and a leading cause of heart failure. There are numerous causes of DCM including genetic causes leading to isolated or syndromic presentations, with a wide variety of implicated genes. Among them, PPP1R13L is associated with a recessive syndrome leading to cardiac anomalies with skin, teeth, and hair abnormalities. Fifteen patients have been described so far. We report a patient born to unrelated parents with early-onset and progressive DCM, skin appendage anomalies, and an anorectal anomaly. Her late brother shared the same phenotype. Exome sequencing revealed biallelic loss-of-function (LoF) variants of PPP1R13L in the proband, also present in her affected brother. To our knowledge, anorectal anomalies had never been previously described in PPP1R13L mutated individuals. As exome sequencing did not identify any other candidate variant to explain this malformation, this feature may expand the phenotype of PPP1R13L LoF disorder.

Utility of Optical Genome Mapping for Accurate Detection and Fine-Mapping of Structural Variants in Elusive Rare Diseases

Rare diseases (RDs) often have a genetic basis, yet conventional diagnostic techniques fail to identify causative genetic variations in up to 50% of cases. Structural variants (SVs), including balanced rearrangements, frequently evade detection by karyotyping, microarray, and exome sequencing. The present study utilized optical genome mapping (OGM) to investigate two patients with RDs whose genetic etiology remained unresolved despite prior genomic analyses. Patient 1 exhibited a balanced reciprocal translocation disrupting the BCL11A gene, associated with Dias-Logan syndrome. Patient 2 had a mosaic 682 kb deletion near the IHH gene, causing ectopic enhancer-promoter interactions and polydactyly, mirroring phenotypes observed in mouse models and similar human cases. These findings highlight OGM's efficacy in identifying complex SVs and underline novel pathogenic mechanisms in rare genetic disorders. Consequently, the incorporation of OGM into routine diagnostic procedures will enhance genetic diagnosis, discover new syndromes of currently unknown cause, and eventually improve the clinical management of numerous patients with rare diseases.

Case Report of Suspected Gonadal Mosaicism in FOXP1-Related Neurodevelopmental Disorder

Heterozygous mutations in the FOXP1 gene (OMIM#605515) are responsible for a well-characterized neurodevelopmental syndrome known as "intellectual developmental disorder with language impairment with or without autistic features" (OMIM#613670) or FOXP1 syndrome for short. The main features of the condition are global developmental delay/intellectual disability; speech impairment in all individuals, regardless of their level of cognitive abilities; behavioral abnormalities; congenital anomalies, including subtle dysmorphic features; and strabismus, brain, cardiac, and urogenital abnormalities. Here, we present two siblings with a de novo heterozygous FOXP1 variant, namely, a four-year-old boy and 14-month-old girl. Both children have significantly delayed early psychomotor development, hypotonia, and very similar, slightly dysmorphic facial features. A lack of expressive speech was the leading symptom in the case of the four-year-old boy. We performed whole-exome sequencing on the male patient, which identified a pathogenic heterozygous c.1541G>A (p.Arg514His) FOXP1 mutation. His sister's targeted mutation analysis also showed the same heterozygous FOXP1 variant. Segregation analysis revealed the de novo origin of the mutation, suggesting the presence of parental gonadal mosaicism. To the best of our knowledge, this is the first report of gonadal mosaicism in FOXP1-related neurodevelopmental disorders in the medical literature.

Optical genome mapping unveils hidden structural variants in neurodevelopmental disorders

While short-read sequencing currently dominates genetic research and diagnostics, it frequently falls short of capturing certain structural variants (SVs), which are often implicated in the etiology of neurodevelopmental disorders (NDDs). Optical genome mapping (OGM) is an innovative technique capable of capturing SVs that are undetectable or challenging-to-detect via short-read methods. This study aimed to investigate NDDs using OGM, specifically focusing on cases that remained unsolved after standard exome sequencing. OGM was performed in 47 families using ultra-high molecular weight DNA. Single-molecule maps were assembled de novo, followed by SV and copy number variant calling. We identified 7 variants of interest, of which 5 (10.6%) were classified as likely pathogenic or pathogenic, located in BCL11A, OPHN1, PHF8, SON, and NFIA. We also identified an inversion disrupting NAALADL2, a gene which previously was found to harbor complex rearrangements in two NDD cases. Variants in known NDD genes or candidate variants of interest missed by exome sequencing mainly consisted of larger insertions (> 1kbp), inversions, and deletions/duplications of a low number of exons (1-4 exons). In conclusion, in addition to improving molecular diagnosis in NDDs, this technique may also reveal novel NDD genes which may harbor complex SVs often missed by standard sequencing techniques.

Systematic reanalysis of genomic data by diagnostic laboratories: a scoping review of ethical, economic, legal and (psycho)social implications

With the introduction of Next Generation Sequencing (NGS) techniques increasing numbers of disease-associated variants are being identified. This ongoing progress might lead to diagnoses in formerly undiagnosed patients and novel insights in already solved cases. Therefore, many studies suggest introducing systematic reanalysis of NGS data in routine diagnostics. Introduction will, however, also have ethical, economic, legal and (psycho)social (ELSI) implications that Genetic Health Professionals (GHPs) from laboratories should consider before possible implementation of systematic reanalysis. To get a first impression we performed a scoping literature review. Our findings show that for the vast majority of included articles ELSI aspects were not mentioned as such. However, often these issues were raised implicitly. In total, we identified nine ELSI aspects, such as (perceived) professional responsibilities, implications for consent and cost-effectiveness. The identified ELSI aspects brought forward necessary trade-offs for GHPs to consciously take into account when considering responsible implementation of systematic reanalysis of NGS data in routine diagnostics, balancing the various strains on their laboratories and personnel while creating optimal results for new and former patients. Some important aspects are not well explored yet. For example, our study shows GHPs see the values of systematic reanalysis but also experience barriers, often mentioned as being practical or financial only, but in fact also being ethical or psychosocial. Engagement of these GHPs in further research on ELSI aspects is important for sustainable implementation.

The Diagnostic Landscape of Adult Neurogenetic Disorders

Neurogenetic diseases affect individuals across the lifespan, but accurate diagnosis remains elusive for many patients. Adults with neurogenetic disorders often undergo a long diagnostic odyssey, with multiple specialist evaluations and countless investigations without a satisfactory diagnostic outcome. Reasons for these diagnostic challenges include: (1) clinical features of neurogenetic syndromes are diverse and under-recognized, particularly those of adult-onset, (2) neurogenetic syndromes may manifest with symptoms that span multiple neurological and medical subspecialties, and (3) a positive family history may not be present or readily apparent. Furthermore, there is a large gap in the understanding of how to apply genetic diagnostic tools in adult patients, as most of the published literature focuses on the pediatric population. Despite these challenges, accurate genetic diagnosis is imperative to provide affected individuals and their families guidance on prognosis, recurrence risk, and, for an increasing number of disorders, offer targeted treatment. Here, we provide a framework for recognizing adult neurogenetic syndromes, describe the current diagnostic approach, and highlight studies using next-generation sequencing in different neurological disease cohorts. We also discuss diagnostic pitfalls, barriers to achieving a definitive diagnosis, and emerging technology that may increase the diagnostic yield of testing.

Attitudes towards genetic testing: The role of genetic literacy, motivated cognition, and socio-demographic characteristics

Understanding reasons for why people choose to have or not to have a genetic test is essential given the ever-increasing use of genetic technologies in everyday life. The present study explored the multiple drivers of people's attitudes towards genetic testing. Using the International Genetic Literacy and Attitudes Survey (iGLAS), we collected data on: (1) willingness to undergo testing; (2) genetic literacy; (3) motivated cognition; and (4) demographic and cultural characteristics. The 37 variables were explored in the largest to-date sample of 4311 participants from diverse demographic and cultural backgrounds. The results showed that 82% of participants were willing to undergo genetic testing for improved treatment; and over 73%-for research. The 35 predictor variables together explained only a small proportion of variance: 7%-in the willingness to test for Treatment; and 6%-for Research. The strongest predictors of willingness to undergo genetic testing were genetic knowledge and deterministic beliefs. Concerns about data misuse and about finding out unwanted health-related information were weakly negatively associated with willingness to undergo genetic testing. We also found some differences in factors linked to attitudes towards genetic testing across the countries included in this study. Our study demonstrates that decision-making regarding genetic testing is influenced by a large number of potentially interacting factors. Further research into these factors may help consumers to make decisions regarding genetic testing that are right for their specific circumstances.