Variants in Candidate Genes for Phenotype Heterogeneity in Patients with the 22q11.2 Deletion Syndrome.

22q11.2 deletion syndrome (22q11.2DS) is a microdeletion syndrome with a broad and heterogeneous phenotype, even though most of the deletions present similar sizes, involving ∼3 Mb of DNA. In a relatively large population of a Brazilian 22q11.2DS cohort (60 patients), we investigated genetic variants that could act as genetic modifiers and contribute to the phenotypic heterogeneity, using a targeted NGS (Next Generation Sequencing) with a specific Ion AmpliSeq panel to sequence nine candidate genes (CRKL, MAPK1, HIRA, TANGO2, PI4KA, HDAC1, ZDHHC8, ZFPM2, and JAM3), mapped in and outside the 22q11.2 hemizygous deleted region. In silico prediction was performed, and the whole-genome sequencing annotation analysis package (WGSA) was used to predict the possible pathogenic effect of single nucleotide variants (SNVs). For the in silico prediction of the indels, we used the genomic variants filtered by a deep learning model in NGS (GARFIELD-NGS). We identified six variants, 4 SNVs and 2 indels, in MAPK1, JAM3, and ZFPM2 genes with possibly synergistic deleterious effects in the context of the 22q11.2 deletion. Our results provide the opportunity for the discovery of the co-occurrence of genetic variants with 22q11.2 deletions, which may influence the patients´ phenotype.

Genome-wide association study reveals two novel risk alleles for incident obstructive sleep apnea in the EPISONO cohort.

OBJECTIVE/BACKGROUND: Obstructive sleep apnea (OSA) is a sleep-related breathing disorder that has a complex phenotype. Currently, few genes have been linked with OSA. Thus, the aim of this study was to conduct a genome-wide association study (GWAS) of the apnea-hypopnea index (AHI) variation along time (delta-AHI) in a prospective cohort. METHODS: We used data derived from the São Paulo Epidemiologic Sleep Study (EPISONO) (n = 1074) cohort, which was followed over eight years (n = 712). Our phenotype of interest was delta-AHI and incident OSA. Further, we were interested on the time-dependent effect of genetic variants. Our final GWAS model used delta-AHI as a dependent variable and the SNPs and covariates as independent variables. We also performed a gene-set and pathway analysis. RESULTS: The delta-AHI increased on average 6.1 events/hour (standard deviation = 14.9) over the follow-up. We found two significant and 21 suggestive variants associated with delta-AHI. The strongest association (rs12415421) was observed at ST8SIA6 gene and the other significant hit (rs4731117) was in an intergenic region in linkage disequilibrium with our third hit (rs12669165) in the ASB15 gene. We found an effect of the allele rs12415421 for the OSA incidence. Additionally, we observed that individuals with both risk alleles presented a higher incidence of OSA when compared to those with one or without any risk alleles. CONCLUSIONS: This study has identified genes in these associated regions with delta-AHI, which seem to be involved in growth and stability of muscle and bone. We also observed an effect of both allele frequencies in the incidence of OSA.