Epistatic interactions between genetic disorders of hemoglobin can explain why the sickle-cell gene is uncommon in the Mediterranean.
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ABSTRACT:
SUBMITTER: Penman BS
PROVIDER: S-EPMC2786893 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Intravascular hemolysis and hemoglobinuria are associated with sickle cell nephropathy. ApoL1 is involved in cell-free hemoglobin scavenging through association with haptoglobin-related protein. APOL1 G1/G2 variants are the strongest genetic predictors of kidney disease in the general African-American population. A single report associated APOL1 G1/G2 with sickle cell nephropathy. In 221 patients with sickle cell disease at the University of Illinois at Chicago, we replicated the finding of an association of APOL1 G1/G2 with proteinuria, specifically with urine albumin concentration (?=1.1, P=0.003), observed an even stronger association with hemoglobinuria (OR=2.5, P=4.3×10(-6)), and also replicated the finding of an association with hemoglobinuria in 487 patients from the Walk-Treatment of Pulmonary Hypertension and Sickle cell Disease with Sildenafil Therapy study (OR=2.6, P=0.003). In 25 University of Illinois sickle cell disease patients, concentrations of urine kidney injury molecule-1 correlated with urine cell-free hemoglobin concentrations (r=0.59, P=0.002). Exposing human proximal tubular cells to increasing cell-free hemoglobin led to increasing concentrations of supernatant kidney injury molecule-1 (P=0.01), reduced viability (P=0.01) and induction of HMOX1 and SOD2. HMOX1 rs743811 associated with chronic kidney disease stage (OR=3.0, P=0.0001) in the University of Illinois cohort and end-stage renal disease (OR=10.0, P=0.0003) in the Walk-Treatment of Pulmonary Hypertension and Sickle cell Disease with Sildenafil Therapy cohort. Longer HMOX1 GT-tandem repeats (>25) were associated with lower estimated glomerular filtration rate in the University of Illinois cohort (P=0.01). Our findings point to an association of APOL1 G1/G2 with kidney disease in sickle cell disease, possibly through increased risk of hemoglobinuria, and associations of HMOX1 variants with kidney disease, possibly through reduced protection of the kidney from hemoglobin-mediated toxicity.
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Project description:ObjectiveGlycated hemoglobin (HbA(1c)) values are higher in African Americans than whites, raising the question of whether classification of diabetes status by HbA(1c) should differ for African Americans. We investigated the relative contribution of genetic ancestry and nongenetic factors to HbA(1c) values and the effect of genetic ancestry on diabetes classification by HbA(1c) in African Americans.Research design and methodsWe performed a cross-sectional analysis of data from the community-based Atherosclerosis Risk in Communities (ARIC) Study. We estimated percentage of European genetic ancestry (PEA) for each of the 2,294 African Americans without known diabetes using 1,350 ancestry-informative markers. HbA(1c) was measured from whole-blood samples and categorized using American Diabetes Association diagnostic cut points (<5.7, 5.7-6.4, and ?6.5%).ResultsPEA was inversely correlated with HbA(1c) (adjusted r = -0.07; P < 0.001) but explained <1% of its variance. Age and socioeconomic and metabolic factors, including fasting glucose, explained 13.8% of HbA(1c) variability. Eleven percent of participants were classified as having diabetes; adjustment for fasting glucose decreased this to 4.4%. Additional adjustment for PEA did not significantly reclassify diabetes status (net reclassification index = 0.034; P = 0.94) nor did further adjustment for demographic, socioeconomic, and metabolic risk factors.ConclusionsThe relative contribution of demographic and metabolic factors far outweighs the contribution of genetic ancestry to HbA(1c) values in African Americans. Moreover, the impact of adjusting for genetic ancestry when classifying diabetes by HbA(1c) is minimal after taking into account fasting glucose levels, thus supporting the use of currently recommended HbA(1c) categories for diagnosis of diabetes in African Americans.
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Project description:BACKGROUND: Although numerous candidate gene and genome-wide association studies have been performed on blood pressure, a small number of regulating genetic variants having a limited effect have been identified. This phenomenon can partially be explained by possible gene-gene/epistasis interactions that were little investigated so far. METHODS: We performed a pre-planned two-phase investigation: in phase 1, one hundred single nucleotide polymorphisms (SNPs) in 65 candidate genes were genotyped in 1,912 French unrelated adults in order to study their two-locus combined effects on blood pressure (BP) levels. In phase 2, the significant epistatic interactions observed in phase 1 were tested in an independent population gathering 1,755 unrelated European adults. RESULTS: Among the 9 genetic variants significantly associated with systolic and diastolic BP in phase 1, some may act through altering the corresponding protein levels: SNPs rs5742910 (Padjusted?0.03) and rs6046 (Padjusted =0.044) in F7 and rs1800469 (Padjusted ?0.036) in TGFB1; whereas some may be functional through altering the corresponding protein structure: rs1800590 (Padjusted =0.028, SE=0.088) in LPL and rs2228570 (Padjusted ?9.48×10-4) in VDR. The two epistatic interactions found for systolic and diastolic BP in the discovery phase: VCAM1 (rs1041163) * APOB (rs1367117), and SCGB1A1 (rs3741240) * LPL (rs1800590), were tested in the replication population and we observed significant interactions on DBP. In silico analyses yielded putative functional properties of the SNPs involved in these epistatic interactions trough the alteration of corresponding protein structures. CONCLUSIONS: These findings support the hypothesis that different pathways and then different genes may act synergistically in order to modify BP. This could highlight novel pathophysiologic mechanisms underlying hypertension.
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Project description:Maps of genetic interactions can dissect functional redundancies in cellular networks. Gene expression profiles as high-dimensional molecular readouts of combinatorial perturbations provide a detailed view of genetic interactions, but can be hard to interpret if different gene sets respond in different ways (called mixed epistasis). Here we test the hypothesis that mixed epistasis between a gene pair can be explained by the action of a third gene that modulates the interaction. We have extended the framework of Nested Effects Models (NEMs), a type of graphical model specifically tailored to analyze high-dimensional gene perturbation data, to incorporate logical functions that describe interactions between regulators on downstream genes and proteins. We benchmark our approach in the controlled setting of a simulation study and show high accuracy in inferring the correct model. In an application to data from deletion mutants of kinases and phosphatases in S. cerevisiae we show that epistatic NEMs can point to modulators of genetic interactions. Our approach is implemented in the R-package 'epiNEM' available from https://github.com/cbg-ethz/epiNEM and https://bioconductor.org/packages/epiNEM/.
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Project description:Fetal hemoglobin (HbF) is a strong modifier of sickle cell disease (SCD) severity and is associated with 3 common genetic loci. Quantifying the genetic effects of the 3 loci would specifically address the benefits of HbF increases in patients. Here, we have applied statistical methods using the most representative variants: rs1427407 and rs6545816 in BCL11A, rs66650371 (3-bp deletion) and rs9376090 in HMIP-2A, rs9494142 and rs9494145 in HMIP-2B, and rs7482144 (Xmn1-HBG2 in the ?-globin locus) to create g(HbF), a genetic quantitative variable for HbF in SCD. Only patients aged ?5 years with complete genotype and HbF data were studied. Five hundred eighty-one patients with hemoglobin SS (HbSS) or HbS?0 thalassemia formed the "discovery" cohort. Multiple linear regression modeling rationalized the 7 variants down to 4 markers (rs6545816, rs1427407, rs66650371, and rs7482144) each independently contributing HbF-boosting alleles, together accounting for 21.8% of HbF variability (r2) in the HbSS or HbS?0 patients. The model was replicated with consistent r2 in 2 different cohorts: 27.5% in HbSC patients (N = 186) and 23% in 994 Tanzanian HbSS patients. g(HbF), our 4-variant model, provides a robust approach to account for the genetic component of HbF in SCD and is of potential utility in sickle genetic and clinical studies.
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Project description:The aim of the present work is to investigate the existence of epistatic interactions possibly influencing psychotropic agents' response between rs6740584 within Cyclic adenosine monophosphate Response Element Binding (CREB) and rs12775799 within cAMP response element-modulator (CREM) variants in bipolar disorder (BD) and major depressive disorder (MDD). All BD and MDD patients were administered with the Young Mania Rating Scale (YMRS) and Hamilton Depression Rating Scale (HAMD) at baseline and at endpoint, respectively. A multiple regression model was employed to investigate the existence of possible epistatic interactions between the two variants and diverse clinical factors including drug response in affective disorders. No significant epistatic interaction was observed between rs6740584 within CREB and rs12775799 within CREM on both symptom improvement and other clinical factors in affective disorders. Our preliminary results suggest that no epistatic interaction between rs6740584 within CREB and rs12775799 within CREM should exist on clinical improvement and clinical factors in affective disorders.
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2021-01-31 | GSE164996 | GEO
Project description:BackgroundHigh-throughput genomics has enabled the global mapping of genetic interactions based on the phenotypic impact of combinatorial genetic perturbations. An important next step is to understand how these networks are dynamically remodelled in response to environmental stimuli. Here, we report on the development and testing of a method to identify such interactions. The method was developed from first principles by treating the impact on cellular growth of environmental perturbations equivalently to that of gene deletions. This allowed us to establish a novel neutrality function marking the absence of epistasis in terms of sensitivity phenotypes rather than fitness. We tested the method by identifying fitness- and sensitivity-based interactions involved in the response to drug-induced DNA-damage of budding yeast Saccharomyces cerevisiae using two mutant libraries - one containing transcription factor deletions, and the other containing deletions of DNA repair genes.ResultsWithin the library of transcription factor deletion mutants, we observe significant differences in the sets of genetic interactions identified by the fitness- and sensitivity-based approaches. Notably, among the most likely interactions, only ~50% were identified by both methods. While interactions identified solely by the sensitivity-based approach are modulated in response to drug-induced DNA damage, those identified solely by the fitness-based method remained invariant to the treatment. Comparison of the identified interactions to transcriptional profiles and protein-DNA interaction data indicate that the sensitivity-based method improves the identification of interactions involved in the DNA damage response. Additionally, for the library containing DNA repair mutants, we observe that the sensitivity-based method improves the grouping of functionally related genes, as well as the identification of protein complexes, involved in DNA repair.ConclusionOur results show that the identification of response-modulated genetic interactions can be improved by incorporating the effect of a changing environment directly into the neutrality function marking the absence of epistasis. We expect that this extension of conventional epistatic analysis will facilitate the development of dynamic models of gene networks from quantitative measurements of genetic interactions. While the method was developed for growth phenotype, it should apply equally well for other phenotypes, including the expression of fluorescent reporters.
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