Combined genotype and haplotype tests for region-based association studies

Lack of Association of Polymorphism Located Upstream of ABCA1 (rs2472493), in FNDC3B (rs7636836), and Near ANKRD55–MAP3K1 Genes (rs61275591) in Primary Open-Angle Glaucoma Patients of Saudi Origin

Polymorphisms rs2472493 near ABCA1, rs7636836 in FNDC3B, and rs61275591 near the ANKRD55–MAP3K1 genes were previously reported to exhibit genome-wide significance in primary open-angle glaucoma (POAG). Since these polymorphisms have not been investigated in the Arab population of Saudi Arabia, we examined their association with POAG in a Saudi cohort. Genotyping was performed in 152 POAG cases and 246 controls using Taqman real-time assays and their associations with POAG and clinical markers, such as intraocular pressure, cup/disc ratio, and the number of antiglaucoma medications, were tested by statistical methods. There was no association observed between POAG and the minor allele frequencies of rs2472493[G], rs7636836[T], or rs61275591[A]. None of the genetic models such as co-dominant, dominant, recessive, over-dominant, and log-additive demonstrated any genotype link. The Rs2472493 genotype showed a modest association (p = 0.044) with the number of antiglaucoma medications in the POAG group, but no significant genotype effect on post hoc analysis. In addition, a G-T allelic haplotype of rs2472493 (ABCA1) and rs7636836 (FNDC3B) did show an over two-fold increased risk of POAG (odds ratio = 2.18), albeit non-significantly (p = 0.092). Similarly, no other allelic haplotype of the three variants showed any significant association with POAG. Our study did not replicate the genetic association of rs2472493 (ABCA1), rs763683 (FNDC3B), and rs61275591 (ANKRD55–MAP3K1) in POAG and related clinical phenotypes, suggesting that these polymorphisms are not associated with POAG in a Saudi cohort of Arab ethnicity. However, large population-based multicenter studies are needed to validate these results.

Evaluation of ABCA1 and FNDC3B Gene Polymorphisms Associated With Pseudoexfoliation Glaucoma and Primary Angle-Closure Glaucoma in a Saudi Cohort

Objective: It is plausible that common disease mechanisms exist in glaucoma pathophysiology. Accordingly, we investigated the genetic association of two previously reported primary open-angle glaucoma (POAG)-related gene polymorphisms, rs2472493 (A > G) in ABCA1 and rs7636836 (C > T) in FNDC3B, in primary angle-closure glaucoma (PACG) and pseudoexfoliation glaucoma (PXG).

Methods: TaqMan genotyping was performed in a total of 442 subjects consisting of 246 healthy controls, 102 PACG patients, and 94 PXG patients. Statistical evaluations were performed to detect allelic and genotype association of the variants with the disease and clinical variables such as intraocular pressure (IOP) and cup/disc ratio.

Results: Overall, there was no allelic or genotype association of these variants in PACG and PXG. However, rs7636836[T] allele significantly increased the risk of PXG among men (p = 0.029, odds ratio [OR] = 2.69, 95% confidence interval = 1.11–6.51). Similarly, rs2472493 and rs7636836 genotypes also showed significant association with PXG among men in over-dominant model (p = 0.031, OR = 1.98, 95% CI = 1.06–3.71) and co-dominant model (p = 0.029, OR = 2.69, 95% CI = 1.11–6.51), respectively. However, none survived Bonferroni’s correction. Besides, the synergic presence of rs2472493[G] and rs7636836[T] alleles (G-T) was found to significantly increase the risk of PACG (p = 0.026, OR = 2.85, 95% CI = 1.09–7.46). No significant genotype influence was observed on IOP and cup/disc ratio.

Conclusion: Our results suggest that the polymorphisms rs2472493 in ABCA1 and rs7636836 in FNDC3B genes may be associated with PXG among men, and a G-T allelic combination may confer an increased risk of PACG in the middle-eastern Saudi cohort. Further research in a larger population-based sample is needed to validate these findings.

Exploring effective approaches for haplotype block phasing

BACKGROUND

Knowledge of phase, the specific allele sequence on each copy of homologous chromosomes, is increasingly recognized as critical for detecting certain classes of disease-associated mutations. One approach for detecting such mutations is through phased haplotype association analysis. While the accuracy of methods for phasing genotype data has been widely explored, there has been little attention given to phasing accuracy at haplotype block scale. Understanding the combined impact of the accuracy of phasing tool and the method used to determine haplotype blocks on the error rate within the determined blocks is essential to conduct accurate haplotype analyses.

RESULTS

We present a systematic study exploring the relationship between seven widely used phasing methods and two common methods for determining haplotype blocks. The evaluation focuses on the number of haplotype blocks that are incorrectly phased. Insights from these results are used to develop a haplotype estimator based on a consensus of three tools. The consensus estimator achieved the most accurate phasing in all applied tests. Individually, EAGLE2, BEAGLE and SHAPEIT2 alternate in being the best performing tool in different scenarios. Determining haplotype blocks based on linkage disequilibrium leads to more correctly phased blocks compared to a sliding window approach. We find that there is little difference between phasing sections of a genome (e.g. a gene) compared to phasing entire chromosomes. Finally, we show that the location of phasing error varies when the tools are applied to the same data several times, a finding that could be important for downstream analyses.

CONCLUSIONS

The choice of phasing and block determination algorithms and their interaction impacts the accuracy of phased haplotype blocks. This work provides guidance and evidence for the different design choices needed for analyses using haplotype blocks. The study highlights a number of issues that may have limited the replicability of previous haplotype analysis.

Genotype combination contributes to psoriasis: An exhaustive algorithm perspective

Researchers have learned that nearly all conditions and diseases have a genetic component. With the benefit of technological advances, many single-nucleotide polymorphisms (SNPs) have been found to be associated with the risk of complex disorders by using genome wide association studies (GWASs). Disease-associated SNPs are sometimes shared by healthy controls and cannot clearly distinguish affected individuals from unaffected ones. The combined effects of multiple independent SNPs contribute to the disease process, but revealing the relationship between genotype and phenotype based on the combinations remains a great challenge. In this study, by considering the disease prevalence rate, we conducted an exhaustive process to identify whether a genotype combination pattern would have a decisive effect on complex disorders. Based on genotype data for 68 reported SNPs in 8,372 psoriasis patients and 8,510 healthy controls, we found that putative causal genotype combination patterns (CGCPs) were only present in psoriasis patients, not in healthy subjects. These results suggested that psoriasis might be contributed by combined genotypes, complementing the traditional modest susceptibility of a single variant in a single gene for a complex disease. This work is the first systematic study to analyze genotype combinations based on the reported susceptibility genes, considering each individual among the cases and controls from the Chinese population, and could potentially advance disease-gene mapping and precision medicine due to the causality relationship between the candidate CGCPs and complex diseases.

Mixture model-based association analysis with case-control data in genome wide association studies

Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated disease penetrances. A theoretical justification of the above model is provided. Furthermore, we introduce a hypothesis test for haplotype inheritance patterns which underpin this model. The performance of the proposed approach is evaluated by simulations and real data analysis. The results show that the proposed approach outperforms an existing multiple testing method.

The pre-mir-27a variant rs895819 may contribute to type 2 diabetes mellitus susceptibility in an Iranian cohort

PURPOSE

The study was aimed at investigating the association between hsa-mir-27a polymorphism rs895819 (T/C) and type 2 diabetes mellitus (T2DM) susceptibility in a large Iranian cohort.

METHODS

In this case-control study, the investigated population consisted of T2DM patients (n = 204) and sex- and age-matched controls (n = 209). We used the polymerase chain reaction and restriction fragment length polymorphism (PCR-RFLP) for genotyping.

RESULTS

We observed significant differences between T2DM patients and controls for weight (p = 0.002), BMI (p < 0.001), systolic blood pressure (p < 0.001), diastolic blood pressure (p < 0.001), fasting plasma glucose (p < 0.001), triglyceride (p = 0.004) and LDL cholesterol (p = 0.051). Moreover, we found that genotype distributions were significantly different between groups (p < 0.05) and that the rs895819-C allele is more frequent in controls (p = 0.030, OR = 0.72, 95 % CI 0.53-0.97).

CONCLUSION

Our study shows that rs895819 in hsa-mir-27a is associated with T2DM susceptibility and that the C allele conveyed a protective role against T2DM. Larger multicentric and specific functional studies will be necessary to obtain a deeper comprehension of the role of rs895819 and hsa-mir-27a and how they are involved in the development of diabetes.