Demographic history differences between Hispanics and Brazilians imprint haplotype features.

Admixture is known to greatly impact the genetic landscape of a population and, while genetic variation underlying human phenotypes has been shown to differ among populations, studies on admixed subjects are still scarce. Latin American populations are the result of complex demographic history, such as 2 or 3-way admixing events, bottlenecks and/or expansions, and adaptive events unique to the American continent. To explore the impact of these events on the genetic structure of Latino populations, we evaluated the following haplotype features: linkage disequilibrium, shared identity by descent segments, runs of homozygosity, and extended haplotype homozygosity (integrated haplotype score) in Latinos represented in the 1000 Genome Project along with array data from 171 Brazilians sampled in the South and Southeast regions of Brazil. We found that linkage disequilibrium decay relates to the amount of American and African ancestry. The extent of identity by descent sharing positively correlates with historical effective population sizes, which we found to be steady or growing, except for Puerto Ricans and Colombians. Long runs of homozygosity, a particular instance of autozygosity, was only enriched in Peruvians and Native Americans. We used simulations to account for random sampling and linkage disequilibrium to filter positive selection indexes and found 244 unique markers under selection, 26 of which are common to 2 or more populations. Some markers exhibiting positive selection signals had estimated time to the most recent common ancestor consistent with human adaptation to the American continent. In conclusion, Latino populations present highly divergent haplotype characteristics that impact genetic architecture and underlie complex phenotypes.

Copy number variation in the susceptibility to systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an autoimmune disease with a strong genetic component and etiology characterized by chronic inflammation and autoantibody production. The purpose of this study was to ascertain copy number variation (CNV) in SLE using a case-control design in an admixed Brazilian population. The whole-genome detection of CNV was performed using Cytoscan HD array in SLE patients and healthy controls. The best CNV candidates were then evaluated by quantitative real-time PCR in a larger cohort or validated using droplet digital PCR. Logistic regression models adjusted for sex and ancestry covariates was applied to evaluate the association between CNV with SLE susceptibility. The data showed a synergistic effect between the FCGR3B and ADAM3A loci with the presence of deletions in both loci significantly increasing the risk to SLE (5.9-fold) compared to the deletion in the single FCGR3B locus (3.6-fold). In addition, duplications in these genes were indeed more frequent in healthy subjects, suggesting that high FCGR3B/ADAM3A gene copy numbers are protective factors against to disease development. Overall, 21 rare CNVs were identified in SLE patients using a four-step pipeline created for identification of rare variants. Furthermore, heterozygous deletions overlapping the CFHR4, CFHR5 and HLA-DPB2 genes were described for the first time in SLE patients. Here we present the first genome-wide CNV study of SLE patients in a tri-hybrid population. The results show that novel susceptibility loci to SLE can be found once the distribution of structural variants is analyzed throughout the whole genome.

Pancreatic Insufficiency in Cystic Fibrosis: Influence of Inflammatory Response Genes.

OBJECTIVE: Pancreatic insufficiency (PI) in cystic fibrosis (CF) patients is a crucial clinical marker for severity and disease progression. In our study, 125 modifier genes and their SNPs were associated between CF patients with PI or pancreatic sufficiency. METHODS: We prospectively evaluated 214 CF patients admitted at 1 hospital for a 2-year period. The PI status was associated with clinical variables and SNPs related with inflammatory response considering CFTR mutations. Open Array technique was used to perform the SNPs identification. RESULTS: For PI risk, after correction by multiple test, in CF patients and 2 CFTR mutations class I, II, and/or III, there were 6 SNPs with positive association (P < 0.005). The odds ratio amplitude was 0.087 (95% confidence interval [CI], 0.004-0.544) for rs9870255*CG (CTNNB1 gene) to 11.06 (95% CI, 1.746-252.3) for rs729302*AA (IRF5 gene). For all CF patients at the same time, 9 SNPs showed positive association. The odds ratio amplitude was 0.144 (95% CI, 0.028-0.602) for rs2348071*AA (PSMA3 gene) to 5.809 (95% CI, 1.536-37.54) for rs11702779*AA (RUNX1 gene). In our data, we observed the interaction between CFTR mutations, rs9870255*CTNNB1, rs9378805*IRF4, and rs7664617*KCNIP4 to PI status. CONCLUSIONS: Multiple SNPs in inflammatory response genes showed association with PI considering the CFTR mutations screening.

A multicentric association study between 39 genes and nonsyndromic cleft lip and palate in a Brazilian population.

PURPOSE: The aim of this study was to use the TaqMan OpenArray system to evaluate associations between 39 genes and the etiology of nonsyndromic cleft lip and palate (NSCLP) in a Brazilian population. MATERIAL AND METHODS: This case-control association study was designed with 80.11% statistical power according to logistic regression (GPOWER software). The case group had 182 patients with NSCLP enrolled in the Brazilian Database on Orofacial Clefts. The controls included 355 healthy individuals with no history of oral clefting in the past three generations. All samples were genotyped for 253 tag single nucleotide polymorphisms (tagSNPs) in 39 genes, including two that had recently been associated with this process. The association analysis was performed using logistic regression and stepwise regression. The results were corrected for multiple testing [Bonferroni correction and False Discovery Rate (FDR)]. RESULTS: Twenty-four SNPs in 16 genes were significantly associated with the etiology of NSCLP, including MSX1, SPRY1, MSX2, PRSS35, TFAP2A, SHH, VAX1, TBX10, WNT11, PAX9, BMP4, JAG2, AXIN2, DVL2, KIF7, and TCBE3. Stepwise regression analysis revealed that 11 genes contributed to 15.5% of the etiology of NSCLP in the sample. CONCLUSION: This is the first study to associate KIF7 and TCEB3 with the etiology of NSCLP. New technological approaches using the same design should help to identify further etiological susceptibility variants.