Genetic basis of osteogenesis imperfecta from a single tertiary centre in South Africa.

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 COL1A1 or COL1A2 was 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 FKBP10 variant 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.

B3GALT6-linkeropathy: Three illustrative patients spanning the disease spectrum.

The linkeropathies are a group of rare disorders, characterized by overlapping clinical features involving the skeletal and connective tissues. Each "linker" gene encodes an enzyme responsible for the addition of glycosaminoglycan chains to proteoglycans via a common tertrasaccharine linker region. The original descriptions of the autosomal recessive B3GALT6-related disorder showed that the associated clinical features are pleiotropic, spanning the skeletal dysplasia (Spondyloepimetaphyseal dysplasia with joint laxity) (SEMD-JL1) and connective tissue disorder (Ehlers-Danlos syndrome) (EDS spondylodysplastic Type 2) spectrum. Here, we describe three patients with biallelic B3GALT6 variants: each had different clinical presentations, and the two older patients initially received alternative clinical diagnoses (Larsen syndrome and Osteogenesis imperfecta, respectively). We describe the clinico-radiological features of these patients to highlight the spectrum of disease associated with the B3GALT6-linkeropathy.

Undiagnosed disease program in South Africa: Results from first 100 exomes.

The Undiagnosed Disease Program in South Africa (UDP) sought to prospectively evaluate the clinical utility of exome sequencing (ES) in a phenotypically diverse, multi-ethnic cohort of South African patients with suspected rare genetic disorders. ES was undertaken in 100 sequential patients (93 singletons, 3 duos, and 4 trios) recruited to the UDP at Stellenbosch University. The data were analyzed through two separate bioinformatics pipelines (EVIDENCE from 3 billion and our in-house pipeline). A definitive diagnosis could be reached in 51% (51/100) patients, with 46% (46/100) patients having either pathogenic or likely pathogenic single-nucleotide variants/indels (SNVs/indels), and 5 patients with likely-pathogenic copy number variants (CNVs) (5/100). The CNVs were subsequently confirmed on microarray or MLPA analysis. Detailed phenotyping and HPO terms enabled analysis and variant identification. Twenty-five novel variants in 22 genes are reported here. We provide data from the first year of this UDP and show that even amongst mainly singletons from an understudied, diverse African population, ES is a valuable diagnostic tool, especially if it includes CNV analysis. The remaining undiagnosed patients present a unique opportunity for further research and novel gene discovery.

GestaltMatcher facilitates rare disease matching using facial phenotype descriptors.

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.

Novel hemizygous loss-of-function variant in NONO identified in a South African boy.

Hemizygous loss-of-function variants in the non-POU domain-containing, octamer-binding gene, NONO, cause X-linked mental retardation syndrome 34 (MRXS34). Here, we describe the 12th patient in the literature with this rare syndrome, the first affected male from sub-Saharan Africa. This South African patient presented with dysmorphic features, congenital cardiac abnormalities (Ebstein's anomaly, left ventricular non-compaction, and a VSD), and developmental delay. He was enrolled in our "Undiagnosed Disease Programme." Exome sequencing identified a novel hemizygous 14bp deletion in NONO, which he inherited from his unaffected, healthy mother. His features overlap with the previous patients described, lending more support to the assertion that MRXS34 is a recognizable, albeit rare, syndrome. The cardiac anomalies are particularly distinctive, which combined with a variety of other associated features, should prompt the inclusion of NONO-associated MRXS34 in the differential diagnosis.