Establishing a baseline for developmental disorder diagnosis by evaluating current processes and mapping common benign copy number variation in Africa

Abstract

Developmental disorders (DDs) are life altering and debilitating conditions believed to be present at high rates in sub-Saharan Africa. The non-specific presentation of DDs and their heterogenous genetic aetiologies make them challenging to diagnose. Guidelines to assist in diagnosing DDs currently recommend whole exome sequencing (WES) as the first-line investigation, as WES can detect various types of genetic variants including copy number variants (CNVs). The high cost of WES means strong motivation for its necessity is required, but little research has been conducted and published in Africa about patients with DD and their diagnostic process. Baseline population variants are required for interpretation of WES results, but baseline population CNVs in African individuals have not been well characterised. We therefore aimed to address these two knowledge gaps. To address the first, a file audit was performed on 934 patient records, presenting over a year period, to a medical genetics clinic in South Africa. We found that 83% of patients presented with DDs. The largest group of patients (57%) presented with rare, less recognizable conditions and 92% of these patients remained undiagnosed after available testing was performed. Patients with DDs are the largest group of patients seen, and diagnostic testing approaches are limited, so where clinical features are not distinct, the diagnostic yield is low. Therefore, a significant number of these patients would benefit from a higher yield test like WES. To address the second gap, 1027 high coverage whole genome sequences of individuals from west, central, southern and east Africa, were analysed using Manta and Graphtyper2, and 919 of the samples with Genome STRiP. A high confidence set of 9001 variants called by both tools was produced, conforming to expected parameters for population CNVs. CNVs were found to differ between African regions. 17% of variants were novel, and a number of these were high copy number multi-allelic CNVs. CNVs involving DD genes uncovered African specific allele frequencies and some novel CNVs. This dataset, and continued work, will serve to enrich reference databases with African CNVs that are important for genetic research in African ancestry individuals.