Maria Leon-Camarena

Figure S1 shows a cross-validation plot to determine ‘k’ number of populations for the REDIAL dataset. Note the elbow of the scree plot at k = 4. This indicates that the genetic structure of the dataset is best explained by four ancestral populations, as adding more populations provides diminishing returns in reducing cross-validation error.

Supplementary Table S2 shows demographics and clinical characteristics of the 593 genetically analyzed REDIAL patients.

Figure S2 shows correlation matrices of (A) inferred global genetic ancestry within each ancestry cluster defined by K-means classification (AFR, EUR, AS, AMR), and (B) inferred genetic ancestry by self-reported racial/ethnic categories.

Supplementary Table S3 shows mean genetic ancestry by self-reported race/ethnicity.

Supplementary Table S1 shows mean genetic ancestry by k-means clustering of inferred global genetic ancestry.

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.