Abstract
Today in Aotearoa there are potential inequities in the provision of our genomic healthcare. Genomic tools whose design is reliant on population datasets may have reduced performance in underrepresented populations due to differing allele frequencies. Chromosomal microarrays (CMA) are one such tool, used by clinicians to diagnose chromosomal imbalances and homozygous segments of potential diagnostic significance. Clinicians performing CMA in Aotearoa have observed elevated rates of homozygosity in Māori patients, but this has not been systematically studied. Elevated homozygosity may result from shared ancestral tīpuna (homozygosity by descent (HBD)). Large contiguous homozygous segments arise from recent parental relatedness, with segment size decreasing in proportion to increased ancestral distance. Additionally, failure to capture genetic variability in underrepresented populations due to non-representative marker selection may artificially inflate genome-wide levels of homozygosity (homozygosity by state (HBS)). We retrospectively analysed three years of CMA data (3050 patients) from a major diagnostic centre, aiming to quantify genome-wide homozygosity and segment distribution. Comparison of homozygous segments by self-declared ethnicity revealed that homozygosity in Māori patients was consistent with distant ancestral HBD. In addition, several homozygous segments appear to result from HBS, with a subset showing increased prevalence in Māori.
Recent ancestral HBD is known to increase risk of rare recessive disorders. However, it is poorly understood if a similar effect occurs due to distant shared ancestry. Capturing population specific pathogenic recessive variation will improve diagnostic care for Māori. Additionally, evaluating HBS in underrepresented populations will improve current CMA platform design. This study has defined differential performance of CMA by self-declared ethnicity, opening opportunities to improve healthcare in Aotearoa.