Increased detection of primary carnitine deficiency through second-tier newborn genetic screening

Abstract

BACKGROUND: Newborn screening for primary carnitine deficiency (NBS) is commonly implemented worldwide; however, it has poor sensitivity. This study aimed to evaluate the feasibility of improving screening by including a second-tier genetic assay. RESULTS: An Agena iPLEX assay was developed to identify 17 common SLC22A5 mutations in Chinese populations and was applied in NBS as a second-tier screening. From January 2017 to December 2018, 204,777 newborns were screened for PCD using tandem mass spectrometry. A total of 316 (0.15%) residual NBS-positive specimens with low free carnitine (C0) levels were subjected to this second-tier screening. The screening identified 20 screen-positive newborns who harboured biallelic mutations in theSLC22A5 gene, 99 carriers with one mutation, and 197 screen-negative newborns with no mutations. Among the 99 carriers, four newborns were found to have a second disease-causing SLC22A5mutation by further genetic analysis. Among the 197 screen-negatives were four newborns with persistently low C0 levels, and further genetic analysis revealed that one newborn had two novel SLC22A5 pathogenic variants. In total, 25 newborns were diagnosed with PCD, for a positive predictive value of 7.91% (25/316). Based on these data, we estimate the incidence of PCD in Quanzhou is estimated to be 1:8191.Thirteen distinct SLC22A5 variants were identified, and the most common was c.760C > T, with an allelic frequency of 32% (16/50), followed by c.1400C > G (7/50, 14%), and c.51C > G (7/50, 14%). CONCLUSION: Data from this study revealed that 24% (6/25) of PCD cases would have been missed by conventional NBS. This high-throughput iPLEX assay is a powerful tool for PCD genotyping. The addition of this second-tier genetic screening to the current NBS program could identify missed PCD cases, thereby increasing PCD detection. However, further studies are needed to optimise the workflow of the new screening algorithm and to evaluate the cost-effectiveness of this screening approach.