Association of variants at BCL11A and HBS1L-MYB with hemoglobin F and hospitalization rates among sickle cell patients in Cameroon

BACKGROUND: Genetic variation at loci influencing adult levels of HbF have been shown to modify the clinical course of sickle cell disease (SCD). Data on this important aspect of SCD have not yet been reported from West Africa. We investigated the relationship between HbF levels and the relevant genetic loci in 610 patients with SCD (98% HbSS homozygotes) from Cameroon, and compared the results to a well-characterized African-American cohort. Methods and FINDINGS: Socio-demographic and clinical features were collected and medical records reviewed. Only patients >5 years old, who had not received a blood transfusion or treatment with hydroxyurea were included. Hemoglobin electrophoresis and a full blood count were conducted upon arrival at the hospital. RFLP-PCR was used to describe the HBB gene haplotypes. SNaPshot PCR, Capillary electrophoresis and cycle sequencing were used for the genotyping of 10 selected SNPs. Genetic analysis was performed with PLINK software and statistical models in the statistical package R. Allele frequencies of relevant variants at BCL11A were similar to those detected in African Americans; although the relationships with Hb F were significant (p <.001), they explained substantially less of the variance in HbF than was observed among African Americans (∼ 2% vs 10%). SNPs in HBS1L-MYB region ( HMIP ) likewise had a significant impact on HbF, however, we did not find an association between HbF and the variations in HBB cluster and OR51B5/6 locus on chromosome 11p, due in part to the virtual absence of the Senegal and Indian Arab haplotypes. We also found evidence that selected SNPs in HBS1L-MYB region ( HMIP ) and BCL11A affect both other hematological indices and rates of hospitalization. CONCLUSIONS: This study has confirmed the associations of SNPs in BCL11A and HBS1L-MYB and fetal haemoglobin in Cameroonian SCA patients; hematological indices and hospitalization rates were also associated with specific allelic variants

Strategies to fine-map genetic associations with lipid levels by combining epigenomic annotations and liver-specific transcription profiles

Characterization of the epigenome promises to yield the functional elements buried in the human genome sequence, thus helping to annotate non-coding DNA polymorphisms with regulatory functions. Here, we develop two novel strategies to combine epigenomic data with transcriptomic profiles in humans or mice to prioritize potential candidate SNPs associated with lipid levels by genome-wide association study (GWAS). First, after confirming that lipid-associated loci that are also expression quantitative trait loci (eQTL) in human livers are enriched for ENCODE regulatory marks in the human hepatocellular HepG2 cell line, we prioritize candidate SNPs based on the number of these marks that overlap the variant position. This method recognized the known SORT1 rs12740374 regulatory SNP associated with LDL-cholesterol, and highlighted candidate functional SNPs at 15 additional lipid loci. In the second strategy, we combine ENCODE chromatin immunoprecipitation followed by high-throughput DNA sequencing (ChIP-seq) data and liver expression datasets from knockout mice lacking specific transcription factors. This approach identified SNPs in specific transcription factor binding sites that are located near target genes of these transcription factors. We show that FOXA2 transcription factor binding sites are enriched at lipid-associated loci and experimentally validate that alleles of one such proxy SNP located near the FOXA2 target gene BIRC5 show allelic differences in FOXA2-DNA binding and enhancer activity. These methods can be used to generate testable hypotheses for many non-coding SNPs associated with complex diseases or traits

Harnessing the power of data linkage to enrich the cancer research ecosystem in Canada.

Objectives We will enrich the cancer research ecosystem in Canada through linking cancer registry and administrative health data to the Canadian Partnership for Tomorrow’s Health (CanPath) cohort and biobank. CanPath is Canada’s largest population health study, including 1% of the Canadian population, which seeks to investigate cancer development. Approach We are achieving record-level linkage of the CanPath harmonized dataset to provincial cancer registry data, and hospitalization and ambulatory care data from the Canadian Institutes of Health Information (CIHI). The CanPATH harmonized dataset includes comprehensive genetics, environment, lifestyle, and behaviour data. Our linkage activities will result in interprovincial data sharing, with centrally-held linked data, a first in Canadian history. We will demonstrate the CanPath-cancer registry-CIHI linkage potential by investigating the impact of the COVID-19 pandemic on healthcare utilization and outcomes among those with cancer. Results The linkage is ongoing and anticipated to be completed by September 2022. Linked data will be made available through the CanPath Data Safe Haven, a cloud-based solution that meets the legal requirements of the data sharing agreements and provincial privacy policies, and is accessible to researchers through secure access. The CanPath Data Safe Haven will be a federated data platform for Canadian researchers to access, analyze, and contribute research in a collaborative environment. By linking these datasets, this project will: address concerns related to accessibility of cancer data in Canada; bring more value to existing data; support an enhanced understanding of the impacts of cancer on marginalized populations; and create a more integrated approach to cancer data access and management. Conclusion CanPath will be the first program in Canadian history to combine the wealth of cohort resources with cancer registry and administrative health data in a central location at a national scale. We will provide a single point of access for researchers to conduct novel investigations into cancer development and outcomes

Hundreds of variants clustered in genomic loci and biological pathways affect human height

Most common human traits and diseases have a polygenic pattern of inheritance: DNA sequence variants at many genetic loci influence the phenotype. Genome-wide association (GWA) studies have identified more than 600 variants associated with human traits, but these typically explain small fractions of phenotypic variation, raising questions about the use of further studies. Here, using 183,727 individuals, we show that hundreds of genetic variants, in at least 180 loci, influence adult height, a highly heritable and classic polygenic trait. The large number of loci reveals patterns with important implications for genetic studies of common human diseases and traits. First, the 180 loci are not random, but instead are enriched for genes that are connected in biological pathways (P = 0.016) and that underlie skeletal growth defects (P < 0.001). Second, the likely causal gene is often located near the most strongly associated variant: in 13 of 21 loci containing a known skeletal growth gene, that gene was closest to the associated variant. Third, at least 19 loci have multiple independently associated variants, suggesting that allelic heterogeneity is a frequent feature of polygenic traits, that comprehensive explorations of already-discovered loci should discover additional variants and that an appreciable fraction of associated loci may have been identified. Fourth, associated variants are enriched for likely functional effects on genes, being over-represented among variants that alter amino-acid structure of proteins and expression levels of nearby genes. Our data explain approximately 10% of the phenotypic variation in height, and we estimate that unidentified common variants of similar effect sizes would increase this figure to approximately 16% of phenotypic variation (approximately 20% of heritable variation). Although additional approaches are needed to dissect the genetic architecture of polygenic human traits fully, our findings indicate that GWA studies can identify large numbers of loci that implicate biologically relevant genes and pathways.

Genetic association analysis highlights new loci that modulate hematological trait variation in Caucasians and African Americans

Red blood cell, white blood cell, and platelet measures, including their count, sub-type and volume, are important diagnostic and prognostic clinical parameters for several human diseases. To identify novel loci associated with hematological traits, and compare the architecture of these phenotypes between ethnic groups, the CARe Project genotyped 49,094 single nucleotide polymorphisms (SNPs) that capture variation in ~2,100 candidate genes in DNA of 23,439 Caucasians and 7,112 African Americans from five population-based cohorts. We found strong novel associations between erythrocyte phenotypes and the glucose-6 phosphate dehydrogenase (G6PD) A-allele in African Americans (rs1050828, P < 2.0 × 10−13, T-allele associated with lower red blood cell count, hemoglobin, and hematocrit, and higher mean corpuscular volume), and between platelet count and a SNP at the tropomyosin-4 (TPM4) locus (rs8109288, P = 3.0 × 10−7 in Caucasians; P = 3.0 × 10−7 in African Americans, T-allele associated with lower platelet count). We strongly replicated many genetic associations to blood cell phenotypes previously established in Caucasians. A common variant of the α-globin (HBA2-HBA1) locus was associated with red blood cell traits in African Americans, but not in Caucasians (rs1211375, P < 7 × 10−8, A-allele associated with lower hemoglobin, mean corpuscular hemoglobin, and mean corpuscular volume). Our results show similarities but also differences in the genetic regulation of hematological traits in European- and African-derived populations, and highlight the role of natural selection in shaping these differences

Multi-Ethnic Analysis of Lipid-Associated Loci: The NHLBI CARe Project

Background: Whereas it is well established that plasma lipid levels have substantial heritability within populations, it remains unclear how many of the genetic determinants reported in previous studies (largely performed in European American cohorts) are relevant in different ethnicities. Methodology/Principal Findings: We tested a set of $\sim$50,000 polymorphisms from $\sim$2,000 candidate genes and genetic loci from genome-wide association studies (GWAS) for association with low-density lipoprotein cholesterol (LDL-C), high-density lipoprotein cholesterol (HDL-C), and triglycerides (TG) in 25,000 European Americans and 9,000 African Americans in the National Heart, Lung, and Blood Institute (NHLBI) Candidate Gene Association Resource (CARe). We replicated associations for a number of genes in one or both ethnicities and identified a novel lipid-associated variant in a locus harboring ICAM1. We compared the architecture of genetic loci associated with lipids in both African Americans and European Americans and found that the same genes were relevant across ethnic groups but the specific associated variants at each gene often differed. Conclusions/Significance: We identify or provide further evidence for a number of genetic determinants of plasma lipid levels through population association studies. In many loci the determinants appear to differ substantially between African Americans and European Americans

A Meta-Analysis and Genome-Wide Association Study of Platelet Count and Mean Platelet Volume in African Americans

Several genetic variants associated with platelet count and mean platelet volume (MPV) were recently reported in people of European ancestry. In this meta-analysis of 7 genome-wide association studies (GWAS) enrolling African Americans, our aim was to identify novel genetic variants associated with platelet count and MPV. For all cohorts, GWAS analysis was performed using additive models after adjusting for age, sex, and population stratification. For both platelet phenotypes, meta-analyses were conducted using inverse-variance weighted fixed-effect models. Platelet aggregation assays in whole blood were performed in the participants of the GeneSTAR cohort. Genetic variants in ten independent regions were associated with platelet count (N = 16,388) with p<5×10−8 of which 5 have not been associated with platelet count in previous GWAS. The novel genetic variants associated with platelet count were in the following regions (the most significant SNP, closest gene, and p-value): 6p22 (rs12526480, LRRC16A, p = 9.1×10−9), 7q11 (rs13236689, CD36, p = 2.8×10−9), 10q21 (rs7896518, JMJD1C, p = 2.3×10−12), 11q13 (rs477895, BAD, p = 4.9×10−8), and 20q13 (rs151361, SLMO2, p = 9.4×10−9). Three of these loci (10q21, 11q13, and 20q13) were replicated in European Americans (N = 14,909) and one (11q13) in Hispanic Americans (N = 3,462). For MPV (N = 4,531), genetic variants in 3 regions were significant at p<5×10−8, two of which were also associated with platelet count. Previously reported regions that were also significant in this study were 6p21, 6q23, 7q22, 12q24, and 19p13 for platelet count and 7q22, 17q11, and 19p13 for MPV. The most significant SNP in 1 region was also associated with ADP-induced maximal platelet aggregation in whole blood (12q24). Thus through a meta-analysis of GWAS enrolling African Americans, we have identified 5 novel regions associated with platelet count of which 3 were replicated in other ethnic groups. In addition, we also found one region associated with platelet aggregation that may play a potential role in atherothrombosis

Ultraconserved Elements in the Human Genome: Association and Transmission Analyses of Highly Constrained Single-Nucleotide Polymorphisms

Ultraconserved elements in the human genome likely harbor important biological functions as they are dosage sensitive and are able to direct tissue-specific expression. Because they are under purifying selection, variants in these elements may have a lower frequency in the population but a higher likelihood of association with complex traits. We tested a set of highly constrained SNPs (hcSNPs) distributed genome-wide among ultraconserved and nearly ultraconserved elements for association with seven traits related to reproductive (age at natural menopause, number of children, age at first child, and age at last child) and overall [longevity, body mass index (BMI), and height] fitness. Using up to 24,047 European-American samples from the National Heart, Lung, and Blood Institute Candidate Gene Association Resource (CARe), we observed an excess of associations with BMI and height. In an independent replication panel the most strongly associated SNPs showed an 8.4-fold enrichment of associations at the nominal level, including three variants in previously identified loci and one in a locus (DENND1A) previously shown to be associated with polycystic ovary syndrome. Finally, using 1430 family trios, we showed that the transmissions from heterozygous parents to offspring of the derived alleles of rare (frequency ≤0.5%) hcSNPs are not biased, particularly after adjusting for the rates of genotype missingness and error in the data. The lack of transmission bias ruled out an immediately and strongly deleterious effect due to the rare derived alleles, consistent with the observation that mice homozygous for the deletion of ultraconserved elements showed no overt phenotype. Our study also illustrated the importance of carefully modeling potential technical confounders when analyzing genotype data of rare variants