Search

Osteogenesis imperfecta (OI) is a clinically heterogeneous disorder characterised by skeletal fragility and an increased fracture incidence. It occurs in approximately one in every 15–20,000 births and is known to vary considerably in its severity. This report aimed to use next-generation sequencing (NGS) technology to identify disease genes and causal variants in South African patients with clinical-radiological features of OI. A total of 50 affected individuals were recruited at Tygerberg Hospital’s Medical Genetics clinic. Patients were selected for a gene panel test (n= 39), a single variant test (n= 1) or exome sequencing (ES) (n= 12, 7 singletons, 1 affected duo, and 1 trio), depending on funding eligibility. An in-house genomic bioinformatics pipeline was developed for the ES samples using open-source software and tools. This study’s 100% diagnostic yield was largely attributable to an accurate clinical diagnosis. A causal variant in COL1A1or COL1A2was identified in 94% of this patient cohort, which is in line with previous studies. Interestingly, this study was the first to identify the common South African pathogenic FKBP10variant in a patient of mixed ancestry, adding to what was previously known about this variant in our population. Additionally, a recurrent variant in COL1A2: c.1892G>T was discovered in 27 individuals (25 from three large unrelated families and two further individuals), facilitating the establishment of local testing for this variant in South African patients.

Next generation sequencing (NGS)-based tests have become routine first-line investigative modalities in paediatric neurology clinics in many high-income countries (HICs). Studies from these countries show that these tests are both cost-effective and reliable in diagnosing many complex childhood neurological diseases. However, NGS-based testing in low-and middle-income countries (LMICs) is limited due to affordability constraints. The primary objective of this study was to evaluate the diagnostic yield and impact of targeted gene panel sequencing in a selected paediatric cohort attending a tertiary paediatric neurology clinic in the Western Cape Province of South Africa. This retrospective study included 124 consecutive paediatric patients with neurological disease, aged 6 weeks to 17 years, referred for NGS-based multi-gene panel testing over a 41-month period. Twenty-four different disease group-specific panels were utilized. A caregiver experience questionnaire was administered when a pathogenic variant was identified. The overall study diagnostic yield (DY) was 45% (56/124 patients). The diagnostic yield in this study is similar to previously reported paediatric cohorts in HICs. The high yields for neuromuscular disorders (52%) and early epileptic encephalopathies (41%) suggest that NGS-based panels may be more cost-effective as first-line testing in well-defined phenotypes. The latter finding argues for early inclusion of all children with developmental epileptic encephalopathies (DEE), as early diagnosis leads to better treatment and avoidance of unnecessary investigations.

Individuals with ultrarare disorders pose a structural challenge for healthcare systems since expert clinical knowledge is required to establish diagnoses. In TRANSLATE NAMSE, a 3-year prospective study, we evaluated a novel diagnostic concept based on multidisciplinary expertise in Germany. Here we present the systematic investigation of the phenotypic and molecular genetic data of 1,577 patients who had undergone exome sequencing and were partially analyzed with next-generation phenotyping approaches. Molecular genetic diagnoses were established in 32% of the patients totaling 370 distinct molecular genetic causes, most with prevalence below 1:50,000. During the diagnostic process, 34 novel and 23 candidate genotype–phenotype associations were identified, mainly in individuals with neurodevelopmental disorders. Sequencing data of the subcohort that consented to computer-assisted analysis of their facial images with GestaltMatcher could be prioritized more efficiently compared with approaches based solely on clinical features and molecular scores. Our study demonstrates the synergy of using next-generation sequencing and phenotyping for diagnosing ultrarare diseases in routine healthcare and discovering novel etiologies by multidisciplinary teams.

Many monogenic disorders cause a characteristic facial morphology. Artificial intelligence can support physicians in recognizing these patterns by associating facial phenotypes with the underlying syndrome through training on thousands of patient photographs. However, this ‘supervised’ approach means that diagnoses are only possible if the disorder was part of the training set. To improve recognition of ultra-rare disorders, we developed GestaltMatcher, an encoder for portraits that is based on a deep convolutional neural network. Photographs of 17,560 patients with 1,115 rare disorders were used to define a Clinical Face Phenotype Space, in which distances between cases define syndromic similarity. Here we show that patients can be matched to others with the same molecular diagnosis even when the disorder was not included in the training set. Together with mutation data, GestaltMatcher could not only accelerate the clinical diagnosis of patients with ultra-rare disorders and facial dysmorphism but also enable the delineation of new phenotypes.

Skeletal ciliopathies are a heterogenous group of disorders with overlapping clinical and radiographic features including bone dysplasia and internal abnormalities. To date, pathogenic variants in at least 30 genes, coding for different structural cilia proteins, are reported to cause skeletal ciliopathies. Here, we summarize genetic and phenotypic features of 34 affected individuals from 29 families with skeletal ciliopathies. Molecular diagnostic testing was performed using massively parallel sequencing (MPS) in combination with copy number variant (CNV) analyses and in silico filtering for variants in known skeletal ciliopathy genes. We identified biallelic disease-causing variants in seven genes: DYNC2H1, KIAA0753, WDR19, C2CD3, TTC21B, EVC, and EVC2. Four variants located in non-canonical splice sites of DYNC2H1, EVC, and KIAA0753led to aberrant splicing that was shown by sequencing of cDNA. Furthermore, CNV analyses showed an intragenic deletion of DYNC2H1in one individual and a 6.7 Mb de novo deletion on chromosome 1q24q25 in another. In five unsolved cases, MPS was performed in family setting. In one proband we identified a de novo variant in PRKACAand in another we found a homozygous intragenic deletion of IFT74, removing the first coding exon and leading to expression of a shorter message predicted to result in loss of 40 amino acids at the N-terminus. These findings establish IFT74as a new skeletal ciliopathy gene. In conclusion, combined single nucleotide variant, CNV and cDNA analyses lead to a high yield of genetic diagnoses (90%) in a cohort of patients with skeletal ciliopathies.

Sirenomelia, also known as the ‘mermaid malformationsyndrome’, is a rare, serious congenital anomaly characterized by variable degrees of fusion of the lower limbs and associated severe malformations of the lower vertebral and genitourinary systems. In this report, we describe a series of African patients with sirenomelia. We present the clinical and radiological features of four black South African patients and illustrate some of the rarer associated abnormalities, which include asymmetrical upper limb defects, not confined to the radial ray. The clinical phenotypic overlap between caudal dysgenesis, VACTERL association and sirenomelia in our patients is highlighted, lending support to the theory that these entities may be different manifestations of a single pathogenic process.