Classic and clinical variant galactosemia (CG/CVG) are allelic, autosomal recessive disorders that result from deficiency of galactose-1-P uridylyltransferase (GALT). CG/CVG has been reported globally among patients of diverse ancestries, but most large studies of outcomes have included, almost exclusively, patients categorized as White or Caucasian. As a first step to explore whether the cohorts studied are representative of the CG/CVG population at large, we sought to define the racial and ethnic makeup of CG/CVG newborns in a diverse population with essentially universal newborn screening (NBS) for galactosemia: the United States (US). First, we estimated the predicted racial and ethnic distribution of CG/CVG by combining the reported demographics of US newborns from 2016 to 2018 with predicted homozygosity or compound heterozygosity of pathogenic, or likely pathogenic, GALT alleles from the relevant ancestral groups. Incorporating some simplifying assumptions, we predicted that of US newborns diagnosed with CG/CVG, 65% should be White (non-Hispanic), 23% should be Black (non-Hispanic), 10% should be Hispanic, and 2% should be Asian (non-Hispanic). Next, we calculated the observed racial and ethnic distribution of US newborns diagnosed with CG/CVG using available de-identified data from state NBS programs from 2016 to 2018. Of the 235 newborns in this cohort, 41 were categorized as other or unknown. Of the remaining 194, 66% were White (non-Hispanic or ethnicity unknown), 16% were Black (non-Hispanic or ethnicity unknown),15% were Hispanic, and 2% were Asian (non-Hispanic or ethnicity unknown). This observed distribution was statistically indistinguishable from the predicted distribution. To the limits of our study, these data confirm the racial and ethnic diversity of newborns with CG/CVG in the US, demonstrate an approach for estimating CG/CVG racial and ethnic diversity in other populations, and raise the troubling possibility that current understanding of long-term outcomes in CG/CVG may be skewed by ascertainment bias of the cohorts studied.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10133179PMC
http://dx.doi.org/10.1016/j.ymgme.2023.107542DOI Listing

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