Phenotyping and genotyping of CYP2C19 using comparative metabolism of proguanil in sickle‐cell disease patients and healthy controls in Nigeria

Polymorphic expression of metabolic enzymes have been identified as one of the key factors responsible for the interindividual/ethnic/racial variability in drug metabolism and effect. In Nigeria, there is a disproportionately high incidence of sickle‐cell disease (SCD), a condition characterized by painful crisis frequently triggered by malaria. Proguanil, a substrate of the polymorphic CYP2C19, is a chemoprophylactic antimalarial drug widely used among SCD patients in Nigeria. This study aimed to conduct a comparative CYP2C19 phenotyping among SCD patients and healthy controls and to compare the results with those previously reported. One hundred seventy‐seven unrelated subjects comprising 131 SCD patients and 46 non‐SCD volunteers were phenotyped. This was carried out by collecting pooled urine samples over 8 h following PG administration. Proguanil and its major CYP2C19‐dependent metabolites were measured by high‐performance liquid chromatography. Metabolic ratios (MRs) were computed and employed in classifying subjects into poor or extensive metabolizers. Among SCD group, 130 (99.2%) were extensive metabolizers (EMs) and 1 (0.8%) was poor metabolizer (PM) of PG, while 95.7 and 4.3% non‐SCDs were EMs and PMs, respectively. MRs ranged from 0.02 to 8.70 for SCD EMs and from 0.22 to 8.33 for non‐SCD EMs. Two non‐SCDs with MRs of 18.18 and 25.76 and the SCD with MR of 16.77 regarded as PMs had earlier been genotyped as CYP2C19*2/*2. Poor metabolizers of proguanil in SCD patients are reported for the first time. Regardless of clinical significance, a difference in metabolic disposition of proguanil and CYP2C19 by SCDs and non‐SCDs was established

Characterizing Genetic Susceptibility to Breast Cancer in Women of African Ancestry

Background: Genome-wide association studies have identified approximately 100 common genetic variants associated with breast cancer risk, the majority of which were discovered in women of European ancestry. Because of different patterns of linkage disequilibrium, many of these genetic markers may not represent signals in populations of African ancestry. Methods: We tested 74 breast cancer risk variants and conducted fine-mapping of these susceptibility regions in 6,522 breast cancer cases and 7,643 controls of African ancestry from three genetic consortia (AABC, AMBER, and ROOT). Results: Fifty-four of the 74 variants (73%) were found to have ORs that were directionally consistent with those previously reported, of which 12 were nominally statistically significant ( P < 0.05). Through fine-mapping, in six regions ( 3p24, 12p11, 14q13, 16q12/FTO, 16q23, 19p13 ), we observed seven markers that better represent the underlying risk variant for overall breast cancer or breast cancer subtypes, whereas in another two regions ( 11q13, 16q12/TOX3 ), we identified suggestive evidence of signals that are independent of the reported index variant. Overlapping chromatin features and regulatory elements suggest that many of the risk alleles lie in regions with biological functionality. Conclusions: Through fine-mapping of known susceptibility regions, we have revealed alleles that better characterize breast cancer risk in women of African ancestry. Impact: The risk alleles identified represent genetic markers for modeling and stratifying breast cancer risk in women of African ancestry. Cancer Epidemiol Biomarkers Prev; 26(7); 1-11. ©2017 AACR

Genome-wide association studies in women of African ancestry identified 3q26.21 as a novel susceptibility locus for oestrogen receptor negative breast cancer

Multiple breast cancer loci have been identified in previous genome-wide association studies, but they were mainly conducted in populations of European ancestry. Women of African ancestry are more likely to have young-onset and oestrogen receptor (ER) negative breast cancer for reasons that are unknown and understudied. To identify genetic risk factors for breast cancer in women of African descent, we conducted a meta-analysis of two genome-wide association studies of breast cancer; one study consists of 1,657 cases and 2,029 controls genotyped with Illumina's HumanOmni2.5 BeadChip and the other study included 3,016 cases and 2,745 controls genotyped using Illumina Human1M-Duo BeadChip. The top 18,376 single nucleotide polymorphisms (SNP) from the meta-analysis were replicated in the third study that consists of 1,984 African Americans cases and 2,939 controls. We found that SNP rs13074711, 26.5 Kb upstream of TNFSF10 at 3q26.21, was significantly associated with risk of oestrogen receptor (ER)-negative breast cancer (odds ratio [OR]=1.29, 95% CI: 1.18-1.40; P = 1.8 × 10 (-) (8)). Functional annotations suggest that the TNFSF10 gene may be involved in breast cancer aetiology, but further functional experiments are needed. In addition, we confirmed SNP rs10069690 was the best indicator for ER-negative breast cancer at 5p15.33 (OR = 1.30; P = 2.4 × 10 (-) (10)) and identified rs12998806 as the best indicator for ER-positive breast cancer at 2q35 (OR = 1.34; P = 2.2 × 10 (-) (8)) for women of African ancestry. These findings demonstrated additional susceptibility alleles for breast cancer can be revealed in diverse populations and have important public health implications in building race/ethnicity-specific risk prediction model for breast cancer

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women.

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants

Cross-ancestry GWAS meta-analysis identifies six breast cancer loci in African and European ancestry women

Our study describes breast cancer risk loci using a cross-ancestry GWAS approach. We first identify variants that are associated with breast cancer at P < 0.05 from African ancestry GWAS meta-analysis (9241 cases and 10193 controls), then meta-analyze with European ancestry GWAS data (122977 cases and 105974 controls) from the Breast Cancer Association Consortium. The approach identifies four loci for overall breast cancer risk [1p13.3, 5q31.1, 15q24 (two independent signals), and 15q26.3] and two loci for estrogen receptor-negative disease (1q41 and 7q11.23) at genome-wide significance. Four of the index single nucleotide polymorphisms (SNPs) lie within introns of genes (KCNK2, C5orf56, SCAMP2, and SIN3A) and the other index SNPs are located close to GSTM4, AMPD2, CASTOR2, and RP11-168G16.2. Here we present risk loci with consistent direction of associations in African and European descendants. The study suggests that replication across multiple ancestry populations can help improve the understanding of breast cancer genetics and identify causal variants