Rapid and Sensitive Assessment of Globin Chains for Gene and Cell Therapy of Hemoglobinopathies

The β-hemoglobinopathies sickle cell anemia and β-thalassemia are the focus of many gene-therapy studies. A key disease parameter is the abundance of globin chains because it indicates the level of anemia, likely toxicity of excess or aberrant globins, and therapeutic potential of induced or exogenous β-like globins. Reversed-phase high-performance liquid chromatography (HPLC) allows versatile and inexpensive globin quantification, but commonly applied protocols suffer from long run times, high sample requirements, or inability to separate murine from human β-globin chains. The latter point is problematic for in vivo studies with gene-addition vectors in murine disease models and mouse/human chimeras. This study demonstrates HPLC-based measurements of globin expression (1) after differentiation of the commonly applied human umbilical cord blood-derived erythroid progenitor-2 cell line, (2) in erythroid progeny of CD34+ cells for the analysis of clustered regularly interspaced short palindromic repeats/Cas9-mediated disruption of the globin regulator BCL11A, and (3) of transgenic mice holding the human β-globin locus. At run times of 8 min for separation of murine and human β-globin chains as well as of human γ-globin chains, and with routine measurement of globin-chain ratios for 12 nL of blood (tested for down to 0.75 nL) or of 300,000 in vitro differentiated cells, the methods presented here and any variant-specific adaptations thereof will greatly facilitate evaluation of novel therapy applications for β-hemoglobinopathies

Evaluation of in silico predictors on short nucleotide variants in HBA1, HBA2, and HBB associated with haemoglobinopathies

Haemoglobinopathies are the commonest monogenic diseases worldwide and are caused by variants in the globin gene clusters. With over 2400 variants detected to date, their interpretation using the American College of Medical Genetics and Genomics (ACMG)/Association for Molecular Pathology (AMP) guidelines is challenging and computational evidence can provide valuable input about their functional annotation. While many in silico predictors have already been developed, their performance varies for different genes and diseases. In this study, we evaluate 31 in silico predictors using a dataset of 1627 variants in HBA1, HBA2, and HBB. By varying the decision threshold for each tool, we analyse their performance (a) as binary classifiers of pathogenicity and (b) by using different non-overlapping pathogenic and benign thresholds for their optimal use in the ACMG/AMP framework. Our results show that CADD, Eigen-PC, and REVEL are the overall top performers, with the former reaching moderate strength level for pathogenic prediction. Eigen-PC and REVEL achieve the highest accuracies for missense variants, while CADD is also a reliable predictor of non-missense variants. Moreover, SpliceAI is the top performing splicing predictor, reaching strong level of evidence, while GERP++ and phyloP are the most accurate conservation tools. This study provides evidence about the optimal use of computational tools in globin gene clusters under the ACMG/AMP framework

Adapting the ACMG/AMP variant classification framework: A perspective from the ClinGen Hemoglobinopathy Variant Curation Expert Panel

Accurate and consistent interpretation of sequence variants is integral to the delivery of safe and reliable diagnostic genetic services. To standardize the interpretation process, in 2015, the American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) published a joint guideline based on a set of shared standards for the classification of variants in Mendelian diseases. The generality of these standards and their subjective interpretation between laboratories has prompted efforts to reduce discordance of variant classifications, with a focus on the expert specification of the ACMG/AMP guidelines for individual genes or diseases. Herein, we describe our experience as a ClinGen Variant Curation Expert Panel to adapt the ACMG/AMP criteria for the classification of variants in three globin genes (HBB, HBA2, and HBA1) related to recessively inherited hemoglobinopathies, including five evidence categories, as use cases demonstrating the process of specification and the underlying rationale