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Interplay between Genetic Ancestry, Self-reported Race and Ethnicity, and Clinical Factors in Pediatric Acute
Pragati Kore1, Jennifer M Geris2, Maria Leon-Camarena3
1Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas.
Insights
Pediatric acute lymphoblastic leukemia (ALL) disparities are linked to genetic ancestry and neighborhood factors. Latino children show different genetic profiles and live in disadvantaged areas, impacting ALL subtypes and outcomes.
Area of Science:
- Oncology
- Genetics
- Epidemiology
Background:
- Pediatric acute lymphoblastic leukemia (ALL) is a leading childhood cancer with known variations in incidence and outcomes across racial and ethnic groups.
- Understanding these disparities is crucial for developing equitable treatment strategies.
Purpose of the Study:
- To investigate the influence of genetic ancestry and neighborhood-level socioeconomic and geographic factors on acute lymphoblastic leukemia (ALL) outcome disparities in children.
- To examine socio-demographic and cytogenetic factors associated with ALL outcome disparities within the Reducing Ethnic Disparities in Acute Leukemia (REDIAL) cohort.
Main Methods:
- Analysis of a cohort of 2,512 patients under 25 years diagnosed with ALL between 2005 and 2020.
- Examination of self-reported race/ethnicity, genetic ancestry proportions (Amerindigenous, European), and neighborhood characteristics.
- Cytogenetic profiling of 551 patients to identify specific ALL subtypes and their association with demographic factors.
Main Results:
- Significant differences in genetic ancestry and residential characteristics were observed across racial and ethnic groups.
- Latino children, comprising 55.3% of the cohort, had higher Amerindigenous ancestry and were more likely to reside in socioeconomically disadvantaged neighborhoods.
- Favorable ALL subtypes like ETV6::RUNX1 were less common in Latino children, who had higher rates of CRLF2 overexpression and IGH rearrangements compared to non-Latino White children.
Conclusions:
- Genetic ancestry and neighborhood factors interact to influence the distribution of ALL cytogenetic subtypes, contributing to observed outcome disparities.
- These findings provide insights into the underlying causes of ALL outcome disparities and can inform targeted interventions for more equitable risk stratification and treatment.
Background:
Pediatric acute lymphoblastic leukemia (ALL) is the most common cancer in children, and its incidence and outcomes vary by race and ethnicity.
Methods:
The Reducing Ethnic Disparities in Acute Leukemia (REDIAL) Consortium has assembled a cohort of patients <25 years at diagnosis to examine genetic and neighborhood-level factors influencing ALL. As the cohort is ongoing, for this report, we examined sociodemographic and cytogenetic factors that might be associated with ALL outcome disparities.
Results:
Among 2,512 patients diagnosed between 2005 and 2020, we observed distinct patterns of genetic ancestry and residential characteristics across self-reported race and ethnicity. Latino children, who comprised 55.3% of the cohort, had a mean Amerindigenous ancestry proportion of 50.9%, whereas non-Latino White children exhibited a predominantly European ancestry (mean = 78%). Neighborhood-level analysis revealed significant socioeconomic and geographic differences by race/ethnicity, with Latino children more frequently residing in Latino enclaves or economically disadvantaged neighborhoods. Cytogenetic profiling of 551 patients showed that favorable subtypes (double trisomies and ETV6::RUNX1) predominated overall, but ETV6::RUNX1 was significantly less common in Latino than in non-Latino White children; conversely, CRLF2 overexpression and immunoglobulin heavy chain (IGH) rearrangements were more frequent among Latino children.
Conclusions:
This first REDIAL cohort analysis reveals how genetic ancestry and neighborhood-level factors jointly shape the distribution of ALL cytogenetic subtypes, advancing our understanding of contributors to disparities in ALL outcomes.
Impact:
This analysis offers insights into factors underlying disparities in ALL outcomes that may be targeted for mitigation, ultimately guiding more equitable approaches to risk stratification and intervention.
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