Deviation Of Allele Frequencies Research Articles

Serum Ace and Ace I/D Polymorphism: Risk of Type 2 Diabetes with and Without Nephropathy in Pakistani Cohort

Objective: To find serum ACE (Angiotensin converting enzyme) level and the role of ACE I/D polymorphism with T2DM (Type 2 Diabetes Mellitus) among the Pakistani cohort.
 Methods: A total of 110 diagnosed T2DM patients and 100 normotensive healthy controls with an agerange of 35-65 years were randomly selected for this study. All cases were screened for the T2DM based on random and fasting blood sugar levels and confirmed by HbA1c test. Genomic DNA was extracted from peripheral blood samples by the Salting out method and ACE I/D polymorphism was genotyped using insertion-deletion polymorphism. A serum level of ACE was also determined. All statistical analysis was conducted using SPSS 16 and all values are significant at a p-value less than 0.05. Hardy Weinberg Equilibrium (HWE) was calculated for any deviation of allele frequencies from predicted. The Chi-square test was used to evaluate the association between ACE polymorphism and the risk of diabetes. The odds ratio along with a 95% confidence interval via binary logistics regression analysis was used to find out the diabetic risk associated with ACE genotyping.
 Results: The analysis showed higher ACE levels among T2DM patients with nephropathy (mean =158 ± 38.9) and without nephropathy (mean = 128.23 ± 46.8) as compared to controls (mean = 94.4± 28.6). No significant association (÷2 = 7.402, p-value=0.116) was observed between ACE genotyping and T2DM. However, those who have DD (O.R= 2.714, 95% CI=0.943-7.809) genotype of ACE polymorphism was at risk of diabetes but the results were non-significant. However, no risk was present at the diabetic nephropathy females.Conclusion: These outcomes propose that the ACE gene may not contribute to T2DM in the Pakistanicohort. However, ACE levels were higher among T2DM with and without nephropathy patients.

Allele frequency deviation (AFD) as a new prognostic model to predict overall survival in lung adenocarcinoma (LUAD)

BackgroundLung adenocarcinoma (LUAD) remains one of the world’s most known aggressive malignancies with a high mortality rate. Molecular biological analysis and bioinformatics are of great importance as they have recently occupied a large area in the studies related to the identification of various biomarkers to predict survival for LUAD patients. In our study, we attempted to identify a new prognostic model by developing a new algorithm to calculate the allele frequency deviation (AFD), which in turn may assist in the early diagnosis and prediction of clinical outcomes in LUAD.MethodFirst, a new algorithm was developed to calculate AFD using the whole-exome sequencing (WES) dataset. Then, AFD was measured for 102 patients, and the predictive power of AFD was assessed using Kaplan–Meier analysis, receiver operating characteristic (ROC) curves, and area under the curve (AUC). Finally, multivariable cox regression analyses were conducted to evaluate the independence of AFD as an independent prognostic tool.ResultThe Kaplan–Meier analysis showed that AFD effectively segregated patients with LUAD into high-AFD-value and low-AFD-value risk groups (hazard ratio HR = 1.125, 95% confidence interval CI 1.001–1.26, p = 0.04) in the training group. Moreover, the overall survival (OS) of patients who belong to the high-AFD-value group was significantly shorter than that of patients who belong to the low-AFD-value group with 42.8% higher risk and 10% lower risk of death for both groups respectively (HR for death = 1.10; 95% CI 1.01–1.2, p = 0.03) in the training group. Similar results were obtained in the validation group (HR = 4.62, 95% CI 1.22–17.4, p = 0.02) with 41.6%, and 5.5% risk of death for patients who belong to the high and low-AFD-value groups respectively. Univariate and multivariable cox regression analyses demonstrated that AFD is an independent prognostic model for patients with LUAD. The AUC for 5-year survival were 0.712 and 0.86 in the training and validation groups, respectively.ConclusionAFD was identified as a new independent prognostic model that could provide a prognostic tool for physicians and contribute to treatment decisions.

Variation in 100 relevant pharmacogenes among emiratis with insights from understudied populations

Genetic variations have an established impact on the pharmacological response. Investigating this variation resulted in a compilation of variants in “pharmacogenes”. The emergence of next-generation sequencing facilitated large-scale pharmacogenomic studies and exhibited the extensive variability of pharmacogenes. Some rare and population-specific variants proved to be actionable, suggesting the significance of population pharmacogenomic research. A profound gap exists in the knowledge of pharmacogenomic variants enriched in some populations, including the United Arab Emirates (UAE). The current study aims to explore the landscape of variations in relevant pharmacogenes among healthy Emiratis. Through the resequencing of 100 pharmacogenes for 100 healthy Emiratis, we identified 1243 variants, of which 63% are rare (minor allele frequency ≤ 0.01), and 30% were unique. Filtering the variants according to Pharmacogenomics Knowledge Base (PharmGKB) annotations identified 27 diplotypes and 26 variants with an evident clinical relevance. Comparison with global data illustrated a significant deviation of allele frequencies in the UAE population. Understudied populations display a distinct allelic architecture and various rare and unique variants. We underscored pharmacogenes with the highest variation frequencies and provided investigators with a list of candidate genes for future studies. Population pharmacogenomic studies are imperative during the pursuit of global pharmacogenomics implementation.

Genomic assessment of local adaptation in dwarf birch to inform assisted gene flow.

When populations of a rare species are small, isolated and declining under climate change, some populations may become locally maladapted. Detecting this maladaptation may allow effective rapid conservation interventions, even if based on incomplete knowledge. Population maladaptation may be estimated by finding genome–environment associations (GEA) between allele frequencies and environmental variables across a local species range, and identifying populations whose allele frequencies do not fit with these trends. We can then design assisted gene flow strategies for maladapted populations, to adjust their allele frequencies, entailing lower levels of intervention than with undirected conservation action. Here, we investigate this strategy in Scottish populations of the montane plant dwarf birch (Betula nana). In genome‐wide restriction site‐associated single nucleotide polymorphism (SNP) data, we found 267 significant associations between SNP loci and environmental variables. We ranked populations by maladaptation estimated using allele frequency deviation from the general trends at these loci; this gave a different prioritization for conservation action than the Shapely Index, which seeks to preserve rare neutral variation. Populations estimated to be maladapted in their allele frequencies at loci associated with annual mean temperature were found to have reduced catkin production. Using an environmental niche modelling (ENM) approach, we found annual mean temperature (35%), and mean diurnal range (15%), to be important predictors of the dwarf birch distribution. Intriguingly, there was a significant correlation between the number of loci associated with each environmental variable in the GEA and the importance of that variable in the ENM. Together, these results suggest that the same environmental variables determine both adaptive genetic variation and species range in Scottish dwarf birch. We suggest an assisted gene flow strategy that aims to maximize the local adaptation of dwarf birch populations under climate change by matching allele frequencies to current and future environments.

16 - MEASURING EVOLUTIONARY PRESSURE IN A POLYGENIC FRAMEWORK FOR COMPLEX DISEASES

Background Although many mental disorders are heritable and result in reproductive disadvantage, they remain relatively common in the population. Different mechanisms have been proposed to explain this so-called ‘evolutionary paradox’, including balancing selection, the mismatch hypothesis and the polygenic mutation-selection balance. Evolutionary analyses of individual genetic loci can be informative for monogenic diseases associated with large selection pressures, but have less utility in the analysis of complex, polygenic disorders due to associations of many low-risk alleles. Taking a polygenic approach to mental disorders, we explore the impact of evolutionary pressure on allele frequency under the hypotheses that lower-than-expected average frequencies of disease risk alleles are indicative of negative selection, while higher-than-expected frequencies are indicative of positive selection. Methods Using the largest available GWAS summary statistics for psychiatric and other disorders and traits, we identified allele frequencies for the disease risk or trait-increasing alleles for all SNPs genome-wide. The SNPs were thinned according to P-value via clumping, using stringent linkage disequilibrium criteria, to ensure their independence. After ordering the clumped SNPs by association P-value or effect size in the GWAS, we tested whether mean trait-increasing allele frequencies differed from 50%, as expected by chance, and investigated whether the effect was greater for those SNPs with largest association signal. Results We found evidence of negative selection on Schizophrenia, Crohn's disease and obesity (BMI) risk alleles and of positive selection for height, education and ADHD alleles. The direction of evolutionary pressure was inconclusive for other traits tested including bipolar disorder, depression and autism. For each trait, we estimated the number of SNPs that maximised the mean trait-increasing allele frequency deviation from 50%. Discussion Our results suggest that evolutionary pressure has had a small but marked impact on the allele frequencies of thousands of SNPs of certain psychiatric disorders and other traits. Unlike measures of fecundity in population cohorts, which are restricted by current environmental pressures, social trends, and changes in reproductive behaviour, evidence of positive or negative selection on the genome provides insights into our understanding of the impact of disease on the population over generations.

Genetic variants associated with gestational diabetes mellitus: a meta-analysis and subgroup analysis.

Previous studies have demonstrated that gestational diabetes mellitus (GDM) and Type 2 diabetes mellitus (T2D) share common genetic polymorphisms. We conducted meta-analysis and subgroup analysis of all available variants and determined the effects of confounding and experimental components on the genetic association of GDM. Any case-controlled or cohort studies with genotype distribution compared GDM cases with controls were included. In total, 28 articles including 8,204 cases and 15,221 controls for 6 polymorphisms were studied. rs10830963(MTNR1B), rs7903146(TCF7L2), and rs1801278(IRS1) were significantly associated with the increased GDM risk. The association of rs4402960(IGF2BP2) and rs1800629(TNF-α) was significant only when the studies with control allele frequency deviation and publication bias were excluded. Further subgroup analysis showed the risk alleles of rs7903146(TCF7L2) and rs1801282(PPARG) were significantly associated with the GDM risk only in Asian, but not in Caucasian population. The OGTT test using 100 g, but not 75 g; and genotype detection by other assays, but not Taqman method, were also significantly associated with increased GDM risk in rs1801278(IRS1) and rs7903146(TCF7L2). Overall GDM was associated with rs10830963(MTNR1B), rs7903146(TCF7L2), and rs1801278(IRS1), but only rs7903146(TCF7L2) and rs1801282(PPARG) were significant in Asian populations. While rs1801278(IRS1) and rs7903146(TCF7L2) were significantly affected by OGTT protocol and genotyping methods.

A Novel and Quantitative Assay To Detect JAK2 V617F Allele by Real-Time AS-PCR and Its Applicability to PV Initiating Mutation.

Polycythemia vera (PV) arises due to a somatic mutation(s) of a single hematopoietic stem cell leading to clonal hematopoiesis. Greater than 80% of PV patients carry a somatic mutation in JAK2 (V617F). Growing evidence suggests that increased frequency of the JAK2V617F allele may have a prognostic impact on certain clinical aspects of PV, and, possibly, in other myeloproliferative disorders associated with this mutation. We have developed a novel approach to primer design for Real-Time quantitative allele-specific PCR. Allelic discrimination is enhanced by the combined synergistic effects of an artificial mismatch introduced in the −1 position, starting from the 3′ end of the primer, and the use of a locked nucleic acid (LNA) modified nucleoside placed at the −2 position. We provide evidence that the −2 LNA assists in stabilizing the 3′ end, while the −1 mismatch provides specificity but not stability. The difference in cycle number between the two allele-specific reactions is used to calculate the relative allele frequencies. We demonstrate the robustness, sensitivity and reproducibility of our design. The proportion of mutant JAK2 allele determined by pyrosequencing and kinetic allele-specific PCR was highly concordant with an average allele frequency deviation of 2.6%. Repeated determination of allelic ratios in multiple patient samples was highly reproducible with a standard deviation of 1.5%. We have also determined that the design and assay is highly sensitive; as little as 0.1% mutant allele in 40–50 ng of genomic DNA can be detected. We further tested the applicability of this technique to the analysis of individual BFU-E colonies in order to address the question whether the JAK2V617F is the disease initiating mutation. Less than 10% of a single isolated BFU-E colony, originating from a single progenitor, is sufficient for determination of allele frequency. The remainder of the colony may be used for other analyses. A proportion of 0 or 50 or 100 percent JAK2 mutant allele is expected from each individual BFU-E colony, which was indeed observed. However, when we tested granulocytes from PV females, wherein the granulocytes were found to be clonal by the X-chromosome transcriptionally based clonality assay, we found 3 females <50 (27.5 ±11) and 7 females >50 (75 ±10.5)percent mutant JAK2 allele frequencies. This result suggests the presence of a heterogeneous population of cells with differing genotypes regarding the JAK2 mutant allele, and is further supported by our genotyping results with individual BFU-E colonies as described above. Our PV data suggest that the JAK2V617F may not be the PV initiating mutation. This novel primer design is simple, does not require tedious optimization of reaction conditions, and can be applied to any kinetic PCR platform for reliable and sensitive determination of allele frequencies. Potential applications are varied, such as, quantitative determination of mosaicism, proportion of fetal cells in maternal circulation, detection of minimal residual disease associated with known somatic mutation (such as reduction of malignant cells by chemotherapy or reappearance of resistant clone), rapid monitoring of efficacy of new drugs in both “in vitro” systems as well as clinical trials, and many others that require quantitation of allele frequencies.

Epistatic control of non-Mendelian inheritance in mouse interspecific crosses.

Strong deviation of allele frequencies from Mendelian inheritance favoring Mus spretus-derived alleles has been described previously for X-linked loci in four mouse interspecific crosses. We reanalyzed data for three of these crosses focusing on the location of the gene(s) controlling deviation on the X chromosome and the genetic basis for incomplete deviation. At least two loci control deviation on the X chromosome, one near Xist (the candidate gene controlling X inactivation) and the other more centromerically located. In all three crosses, strong epistasis was found between loci near Xist and marker loci on the central portion of chromosome 2. The mechanism for this deviation from Mendelian expectations is not yet known but it is probably based on lethality of embryos carrying particular combinations of alleles rather than true segregation distortion during oogenesis in F1 hybrid females.