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Sociodemographic Factors Associated with Positive Genome Sequencing Results in Infants with Congenital Heart Disease

Clinical Genetics and Therapeutics
  • Primary Categories:
    • Clinical Genetics
  • Secondary Categories:
    • Clinical Genetics
Introduction:
Certain sociodemographic factors are associated with a greater risk of congenital heart disease (CHD) in infants. Furthermore, sociodemographic factors like maternal education, insurance type (private/public), and area-based poverty have been shown to impact outcomes and mortality of infants with CHD. Poor outcomes and mortality are increased in children with genetic disease. The association between sociodemographic factors and genetic disease in CHD are not well known. Rapid genomic sequencing accelerates the rate of diagnosis and positively impacts care of children with CHD. Knowledge of sociodemographic risk factors for genetic disease can facilitate early identification of infants with CHD in need of genetic testing and potentially improve outcomes.

Methods:
We performed a retrospective evaluation of sociodemographic factors in 243 infants with CHD who underwent genomic sequencing at Rady Children’s Hospital San Diego, CA, from 2017 to 2024. Information collected included sex, race/ethnicity, insurance type, primary language spoken, zip code, rapid genomic sequencing results, and mortality rate. Census data, including median income, poverty rate, employment rate, and educational attainment, were used to build profiles for each represented zip code. The rate of genomic disease diagnosis was calculated and its association with various sociodemographic factors was evaluated. Comparison of proportions were conducted using the Chi-square test and a p-value of ≤ 0.05 indicated statistical significance.

Results:
The overall rate of genomic disease diagnosis in the cohort was 34%. There was a trend towards higher diagnostic rate in Hispanic/Latino patients (37%) compared to White/Non-Hispanic (NH) (33%), Black/NH (29%), Asian/Pacific-Islander (22%), and Other (10%) patients. A higher rate of genomic diagnosis was associated with the primary language of Spanish (42%) as compared to English (33%) and female (40%) as compared to male (29%) patients. The proportion of genomic diagnosis was statistically significantly higher in those from areas with a bachelor degree rate <30% (39%) compared to areas with a bachelor degree rate >30% (24%), (p=0.0172). We also saw a trend toward greater proportion of genomic diagnosis associated with public insurance (36%) compared to private insurance (31%); in areas with average income <$100,000 (35%) compared to those from areas with average income >$100,000 (27%); and in areas with employment rate <60% (34%) compared to those from areas with employment rate >60% (27%), although these rates did not reach statistical significance. Mortality rate in the whole cohort was 15.2% and was highest in Black/NH patients with CHD (50%). The Black/NH mortality rate was statistically significantly higher than the rate in White/NH (9%, p=<0.0001), Hispanic/Latino (12%, p=0.0001) and Asian/Pacific Islanders (22%, p=0.0439).

Conclusion:
Genomic sequencing led to a rate of genetic diagnosis of 34% in infants with CHD in a single children’s hospital over an 8-year period. There was a trend towards higher rate of genetic disease diagnosis in Hispanic/Latino patients, female patients, those who primarily spoke Spanish, those with public insurance, and those living in areas with average income of <$100,000 and employment rate of <60%. The rate of genetic diagnosis was statistically significantly higher in those from areas with a bachelor degree rate <30%. Additionally, mortality rate was statistically significantly higher in Black/NH infants compared to White/NH, Hispanic/Latino, and Asian/Pacific Islander infants. More studies are needed to elucidate potential factors leading to the observed differential increased rate of postnatal genetic disease diagnosis associated with certain sociodemographic factors in infants with CHD. Identification of these factors may prove beneficial in determining need for genetic testing postnatally, but more importantly, can inform programs and interventions to eliminate these disparities.

Agenda

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