scholarly journals Genetic Etiologies for Phenotypic Diversity in Sickle Cell Anemia

2009 ◽  
Vol 9 ◽  
pp. 46-67 ◽  
Author(s):  
Martin H. Steinberg

The clinical course of patients with sickle cell anemia, a Mendelian trait, is characteristically highly variable. HbF concentration and the presence of a thalassemia are established modulators of the disease, but cannot account for all of its clinical heterogeneity. To find additional genetic modulators of disease, genotype-phenotype association studies, where single nucleotide polymorphisms (SNPs) in candidate genes are linked with a particular phenotype, have been informative. SNPs in several genes of the TGF-ß/MP superfamily, and some other genes linked to the endothelial function, and nitric oxide biology are associated with the subphenotypes of stroke, osteonecrosis, priapism, leg ulcers, pulmonary hypertension, and a more general measure of overall disease severity. Genome-wide association studies should help to confirm these observations and also to find hitherto unsuspected genetic modulators. Genetic association studies can have immediate prognostic value; they might also help to identify new pathophysiological pathways that could be susceptible to modulation.

Blood ◽  
2010 ◽  
Vol 115 (9) ◽  
pp. 1815-1822 ◽  
Author(s):  
Nadia Solovieff ◽  
Jacqueline N. Milton ◽  
Stephen W. Hartley ◽  
Richard Sherva ◽  
Paola Sebastiani ◽  
...  

Abstract In a genome-wide association study of 848 blacks with sickle cell anemia, we identified single nucleotide polymorphisms (SNPs) associated with fetal hemoglobin concentration. The most significant SNPs in a discovery sample were tested in a replication set of 305 blacks with sickle cell anemia and in subjects with hemoglobin E or β thalassemia trait from Thailand and Hong Kong. A novel region on chromosome 11 containing olfactory receptor genes OR51B5 and OR51B6 was identified by 6 SNPs (lowest P = 4.7E−08) and validated in the replication set. An additional olfactory receptor gene, OR51B2, was identified by a novel SNP set enrichment analysis. Genome-wide association studies also validated a previously identified SNP (rs766432) in BCL11A, a gene known to affect fetal hemoglobin levels (P = 2.6E−21) and in Thailand and Hong Kong subjects. Elements within the olfactory receptor gene cluster might play a regulatory role in γ-globin gene expression.


Blood ◽  
2008 ◽  
Vol 112 (11) ◽  
pp. 1446-1446
Author(s):  
Paola Sebastiani ◽  
Nadia Timofeev ◽  
Steven H. Hartley ◽  
Daniel Dworkis ◽  
Lindsay Farrer ◽  
...  

Abstract Genome-wide association studies (GWAS) allow an assessment of associations between single nucleotide polymorphisms (SNPs) and phenotypes or traits of interest in a non-hypothesis driven manner. Previously, based on limited candidate gene association analysis, we showed that survival in sickle cell anemia and exceptional longevity (EL) in the general population share common genetic modifiers (Blood, 52a, 2007). This preliminary result suggested that aging mechanisms and associated genes might play a role in the variability of sickle cell anemia. Using GWAS, we now report strong evidence supporting this conjecture. We conducted a GWAS using an Illumina platform that permits genotyping up to 1 million haplotype-tagging SNPs spread across the genome, as well as other types of genetic variation, in large populations. We used the Illumina 610K SNP array to discover SNPs that are associated with different degrees of severity of sickle cell anemia in 684 patients. Patients were assigned to either a severe or mild disease category based on an integrated measure of sickle cell anemia severity that was determined by a network model that assigns a score predicting the risk of death (Blood110: 272, 2007). In parallel, we used the Illumina 370K SNP and the Illumina 1M SNP arrays to discover SNPs associated with EL in 877 centenarians enrolled in the New England Centenarian Study and 1,850 younger controls. In both studies, each SNP was tested for association with the traits of severe or less severe sickle cell anemia and EL using Bayesian tests of general, dominant and recessive associations (BMC Genet.9, 2008). We then identified those SNPs satisfying these 3 criteria: at least one model of association was 10 times more likely than no association in the GWAS of EL; the same model of association was at least 3 times more likely (because of the smaller sample size) than no association in the GWAS of sickle cell anemia severity, the same allele was more frequent in centenarians and in sickle cell anemia patients with milder disease. This analysis identified 140 SNPs in more than 50 genes and some intergenic regions that showed robust and consistent associations. This number is more than twice the number that would be expected by chance. Among the most ‘significant’ genes with associated SNPs were ARFGEF2, ADAMTS12, DOK5, DPP10, FGF21, KCNQ1, IRF4, MYO3B NAIF1, TNNI3K; more than one SNP was found in ARFGEF2, NAIF1, DPP10, SORCS3, TNNI3K. KCNQ1 has a putative role in blood circulation and regulation of heart contraction. The frequency of the common genotype for SNP rs108961 increases by almost 60% in sickle cell anemia patients with severe disease (27% versus 43%). The same common genotype in random Caucasian controls has frequency 34% that decreases to 29% in centenarians. Mutations in this gene are associated with long and short QT syndrome, with familial atrial fibrillation, heart disease and sudden death. SNPs in 2 of the genes (HAO2, a peroxisome protein involved in fatty acid oxidation, and MAP2K1, a MAP kinase involved in multiple biochemical signals) that were significantly associated with both sickle cell disease severity and EL in our earlier candidate gene studies, were also associated in the GWAS. GWAS also revealed significant association with CDKN2A, a cyclin-dependent kinase that has been associated with Type 2 diabetes, risk of myocardial infarction and triglyceride levels in several GWAS, and with FGF21, the fibroblast growth factor 21 precursor that has been shown to regulate glucose metabolism. CDKN2A has been associated with disease free survival in other studies. Common metabolic pathways are likely to influence the chance of developing complications of Mendelian and multigenic diseases and the likelihood of achieving EL. This might explain the commonality of genes whose SNPs are associated with the vascular complications of sickle cell anemia, arteriosclerosis and diabetes. A new paradigm suggests that hitherto unexpected genetic differences modulate a limited number of pathways that form a common route toward determining good health and disease.


2020 ◽  
Author(s):  
Ronin Sharma

AbstractAllergies are complex conditions involving both environmental and genetic factors. The genetic basis underlying allergic disease is investigated through genetic association studies. Genome-wide association studies (GWAS) leverage sequenced data to identify genetic mutations, such as single-nucleotide polymorphisms (SNPs), associated with phenotypes of interest. Machine learning can be used to analyze large datasets and generate predictive models. In this study, several classification models were created to predict the significance level of SNPs associated with allergies. Summary statistics were obtained from the GWAS Catalog and combined from several studies. Biological features such as chromosomal location, base pair location, effect allele, and odds ratio were used to train the models. The models ranged from simple linear regressions to multi-layer neural networks. The final models reached accuracies of 80% and reflect the features that have the largest impact on a SNP’s association level.


Gut ◽  
2019 ◽  
Vol 69 (8) ◽  
pp. 1460-1471 ◽  
Author(s):  
Zahra Montazeri ◽  
Xue Li ◽  
Christine Nyiraneza ◽  
Xiangyu Ma ◽  
Maria Timofeeva ◽  
...  

ObjectiveTo provide an understanding of the role of common genetic variations in colorectal cancer (CRC) risk, we report an updated field synopsis and comprehensive assessment of evidence to catalogue all genetic markers for CRC (CRCgene2).DesignWe included 869 publications after parallel literature review and extracted data for 1063 polymorphisms in 303 different genes. Meta-analyses were performed for 308 single nucleotide polymorphisms (SNPs) in 158 different genes with at least three independent studies available for analysis. Scottish, Canadian and Spanish data from genome-wide association studies (GWASs) were incorporated for the meta-analyses of 132 SNPs. To assess and classify the credibility of the associations, we applied the Venice criteria and Bayesian False-Discovery Probability (BFDP). Genetic associations classified as ‘positive’ and ‘less-credible positive’ were further validated in three large GWAS consortia conducted in populations of European origin.ResultsWe initially identified 18 independent variants at 16 loci that were classified as ‘positive’ polymorphisms for their highly credible associations with CRC risk and 59 variants at 49 loci that were classified as ‘less-credible positive’ SNPs; 72.2% of the ‘positive’ SNPs were successfully replicated in three large GWASs and the ones that were not replicated were downgraded to ‘less-credible’ positive (reducing the ‘positive’ variants to 14 at 11 loci). For the remaining 231 variants, which were previously reported, our meta-analyses found no evidence to support their associations with CRC risk.ConclusionThe CRCgene2 database provides an updated list of genetic variants related to CRC risk by using harmonised methods to assess their credibility.


Blood ◽  
2011 ◽  
Vol 117 (4) ◽  
pp. 1390-1392 ◽  
Author(s):  
Julie Makani ◽  
Stephan Menzel ◽  
Siana Nkya ◽  
Sharon E. Cox ◽  
Emma Drasar ◽  
...  

Abstract Fetal hemoglobin (HbF, α2γ2) is a major contributor to the remarkable phenotypic heterogeneity of sickle cell anemia (SCA). Genetic variation at 3 principal loci (HBB cluster on chromosome 11p, HBS1L-MYB region on chromosome 6q, and BCL11A on chromosome 2p) have been shown to influence HbF levels and disease severity in β-thalassemia and SCA. Previous studies in SCA, however, have been restricted to populations from the African diaspora, which include multiple genealogies. We have investigated the influence of these 3 loci on HbF levels in sickle cell patients from Tanzania and in a small group of African British sickle patients. All 3 loci have a significant impact on the trait in both patient groups. The results suggest the presence of HBS1L-MYB variants affecting HbF in patients who are not tracked well by European-derived markers, such as rs9399137. Additional loci may be identified through independent genome-wide association studies in African populations.


2012 ◽  
Vol 2012 ◽  
pp. 1-6 ◽  
Author(s):  
Xiaobo Guo ◽  
Zhifa Liu ◽  
Xueqin Wang ◽  
Heping Zhang

Many genetic association studies used single nucleotide polymorphisms (SNPs) data to identify genetic variants for complex diseases. Although SNP-based associations are most common in genome-wide association studies (GWAS), gene-based association analysis has received increasing attention in understanding genetic etiologies for complex diseases. While both methods have been used to analyze the same data, few genome-wide association studies compare the results or observe the connection between them. We performed a comprehensive analysis of the data from the Study of Addiction: Genetics and Environment (SAGE) and compared the results from the SNP-based and gene-based analyses. Our results suggest that the gene-based method complements the individual SNP-based analysis, and conceptually they are closely related. In terms of gene findings, our results validate many genes that were either reported from the analysis of the same dataset or based on animal studies for substance dependence.


2018 ◽  
Author(s):  
Susanne Gerber ◽  
David Fournier ◽  
Charlotte Hewel ◽  
Illia Horenko

Genetic association studies have become increasingly important in unraveling the genetics of diseases or complex traits. Despite their value for modern genetics, conflicting conclusions often arise through the difficulty of confirming and replicating experimental results. We argue that this problem is largely based on the application of statistical relation measures that are not appropriate for genomic data analysis and demonstrate that the standard measures used for Genome-wide association studies or genomics linkage analysis bear a statistic bias. This may come from the violation of underlying assumptions (such as independence or stationarity) as well as from other conceptual limitations in the measures or relations, such as missing invariance with respect to coding or the inability to reflect latent factors. Attempts to introduce unbiased relation measures that avoid these limitations are usually computationally expensive and do not scale for large data sizes being typical for genomics applications.To tackle these problems, we propose a straightforwardly computable relation measure called Linkage Probability (LP). This measure provides the posterior probability of a relation between two categorical data sets and considers potential biases from latent variables. We compare several aspects of popular relation measures through an illustrative example and human genomics data. We demonstrate that the application of LP to the analysis of Single Nucleotide Polymorphisms (SNP) reveals latent 3D steric effects within 1D SNP data, that approximate to chromatin loops captured by high resolution Hi-C maps.


2021 ◽  
Vol 14 (4) ◽  
pp. 287
Author(s):  
Courtney M. Vecera ◽  
Gabriel R. Fries ◽  
Lokesh R. Shahani ◽  
Jair C. Soares ◽  
Rodrigo Machado-Vieira

Despite being the most widely studied mood stabilizer, researchers have not confirmed a mechanism for lithium’s therapeutic efficacy in Bipolar Disorder (BD). Pharmacogenomic applications may be clinically useful in the future for identifying lithium-responsive patients and facilitating personalized treatment. Six genome-wide association studies (GWAS) reviewed here present evidence of genetic variations related to lithium responsivity and side effect expression. Variants were found on genes regulating the glutamate system, including GAD-like gene 1 (GADL1) and GRIA2 gene, a mutually-regulated target of lithium. In addition, single nucleotide polymorphisms (SNPs) discovered on SESTD1 may account for lithium’s exceptional ability to permeate cell membranes and mediate autoimmune and renal effects. Studies also corroborated the importance of epigenetics and stress regulation on lithium response, finding variants on long, non-coding RNA genes and associations between response and genetic loading for psychiatric comorbidities. Overall, the precision medicine model of stratifying patients based on phenotype seems to derive genotypic support of a separate clinical subtype of lithium-responsive BD. Results have yet to be expounded upon and should therefore be interpreted with caution.


Genes ◽  
2021 ◽  
Vol 12 (8) ◽  
pp. 1175
Author(s):  
Amarni L. Thomas ◽  
Judith Marsman ◽  
Jisha Antony ◽  
William Schierding ◽  
Justin M. O’Sullivan ◽  
...  

The RUNX1/AML1 gene encodes a developmental transcription factor that is an important regulator of haematopoiesis in vertebrates. Genetic disruptions to the RUNX1 gene are frequently associated with acute myeloid leukaemia. Gene regulatory elements (REs), such as enhancers located in non-coding DNA, are likely to be important for Runx1 transcription. Non-coding elements that modulate Runx1 expression have been investigated over several decades, but how and when these REs function remains poorly understood. Here we used bioinformatic methods and functional data to characterise the regulatory landscape of vertebrate Runx1. We identified REs that are conserved between human and mouse, many of which produce enhancer RNAs in diverse tissues. Genome-wide association studies detected single nucleotide polymorphisms in REs, some of which correlate with gene expression quantitative trait loci in tissues in which the RE is active. Our analyses also suggest that REs can be variant in haematological malignancies. In summary, our analysis identifies features of the RUNX1 regulatory landscape that are likely to be important for the regulation of this gene in normal and malignant haematopoiesis.


2021 ◽  
Author(s):  
Robin N Beaumont ◽  
Isabelle K Mayne ◽  
Rachel M Freathy ◽  
Caroline F Wright

Abstract Birth weight is an important factor in newborn survival; both low and high birth weights are associated with adverse later-life health outcomes. Genome-wide association studies (GWAS) have identified 190 loci associated with maternal or fetal effects on birth weight. Knowledge of the underlying causal genes is crucial to understand how these loci influence birth weight and the links between infant and adult morbidity. Numerous monogenic developmental syndromes are associated with birth weights at the extreme ends of the distribution. Genes implicated in those syndromes may provide valuable information to prioritize candidate genes at the GWAS loci. We examined the proximity of genes implicated in developmental disorders (DDs) to birth weight GWAS loci using simulations to test whether they fall disproportionately close to the GWAS loci. We found birth weight GWAS single nucleotide polymorphisms (SNPs) fall closer to such genes than expected both when the DD gene is the nearest gene to the birth weight SNP and also when examining all genes within 258 kb of the SNP. This enrichment was driven by genes causing monogenic DDs with dominant modes of inheritance. We found examples of SNPs in the intron of one gene marking plausible effects via different nearby genes, highlighting the closest gene to the SNP not necessarily being the functionally relevant gene. This is the first application of this approach to birth weight, which has helped identify GWAS loci likely to have direct fetal effects on birth weight, which could not previously be classified as fetal or maternal owing to insufficient statistical power.


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