Genome-Wide Insights into Internalizing Symptoms in Admixed Latin American Children

Abstract

Background/objectives: Internalizing disorders, including depression and anxiety, are major contributors to the global burden of disease. While the genetic architecture of these disorders in adults has been extensively studied, their early-life genetic mechanisms remain underexplored, especially in non-European populations. This study investigated the genetic mechanisms underlying internalizing symptoms in a cohort of Latin American children.

Methods: This study included 1244 Brazilian children whose legal guardians completed the Child Behavior Checklist (CBCL) questionnaire. Genotyping was performed using the Illumina HumanOmni 2.5-8v1 BeadChip.

Results: The genome-wide association analysis revealed a significant association of rs7196970 (p = 4.5 × 10^-8, OR = 0.61), in the ABCC1 gene, with internalizing symptoms. Functional annotation highlighted variants in epigenetically active regulatory regions, with multiple variants linked to differential expression of ABCC1 across several human tissues. Pathway enrichment analysis identified 42 significant pathways, with notable involvement in neurobiological processes such as glutamatergic, GABAergic, and dopaminergic synapses.

Conclusions: This study identifies ABCC1 variants as novel genetic factors potentially associated with early-life internalizing symptoms. These results may contribute to future research on targeted interventions for childhood internalizing conditions.

Keywords: GWAS; Latin Americans; childhood; internalizing symptoms.

Figure 1

Ancestry analyses of children from the SCAALA cohort. (A) Principal Component Analysis (PCA) comparing children from the SCAALA cohort with reference populations from the 1000 Genomes Project. (B) Bar plots showing the individual ancestries of the participants (N-INT, n = 794 individuals; INT, n = 450), as determined by the ADMIXTURE method. Abbreviations: N-INT, CBCL T score < 64. INT, CBCL T score ≥ 64; Europeans (EUR), Native Americans (NAT), South Asians (SAS), East Asians (EAS), and Africans (AFR); IQR, interquartile range (first–third quartiles); p, the p-value for the Mann–Whitney test; ns, not significant.

Figure 2

Genome-wide association analysis of internalizing symptoms in children from the SCAALA cohort. (A) Quantile–Quantile (QQ) plot showing observed and expected p-values. (B) Manhattan plot of association statistics obtained from multivariate logistic regression (additive model), with sex and seven principal components included as covariates. The red line represents the genomic significance threshold (p < 5 × 10⁻⁸), while the blue line indicates the threshold for suggestive associations (5 × 10⁻⁸ < p < 10⁻⁵). (C) Regional association plot at the ABCC1 locus. The plot shows linkage disequilibrium (LD, r²) between the lead variant rs7196970 (purple diamond) and other variants (circles) within the region 16:15503151–16239180 (RefSeq: GRCh38). The positions of coding genes within this region are shown at the bottom of the figure.

Figure 3

Functional annotation of variants in linkage disequilibrium with rs7196970 (ABCC1 locus). (A) Schematic diagram of the locus containing the ABCC1 gene. The green solid lines and rectangles represent introns and exons, respectively. This region was cross-referenced with DNA sequence annotations, including short variants from the gnomAD consortium, previous associations with human traits (as recorded in the GWAS catalog platform), regulatory elements, and expression Quantitative Trait Locus (eQTL) data from the GTEx multi-tissue meta-analysis (p-value). (B) Magnified view of a region within the ABCC1 gene, highlighting SNVs in moderate to high linkage disequilibrium (r² > 0.6) with rs7196970. Image generated using the Ensembl Genome Browser (http://www.ensembl.org, accessed on 15 July 2024).

Figure 4

Pathway enrichment analysis for internalizing symptoms in children from the SCAALA cohort. Overrepresentation analysis was conducted on 2122 genes, which were matched with the canonical KEGG pathways. Volcano plot showing the pathways. The red line represents the significance threshold [p-value from the false discovery ratio (pFDR) < 0.05]. The size of the dots corresponds to the pathway’s gene set size. The ratio of enrichment is the number of observed genes divided by the number of expected genes from KEGG (according to the WebGestalt tool, www.webgestalt.org/, accessed on 20 October 2024).