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The Meta-Analysis of Genetic Studies
Published in Christopher H. Schmid, Theo Stijnen, Ian R. White, Handbook of Meta-Analysis, 2020
Cosetta Minelli, John Thompson
Study-level quality control typically involves excluding SNPs or participants that have a high level of missing values and excluding SNPs that deviate a long way from HWE. SNPs where the frequency of the less common allele (minor allele frequency, MAF) is below some agreed threshold are also usually excluded, not only because of lack of power, but also because of increased misclassification due to genotyping error. Finally, since genome-wide data are available, they can be used to measure the degree of relatedness between participants making it possible to remove duplicates, participants whose gender does not match that reported, or participants who are unexpectedly closely related (Laurie et al., 2010).
Case-Control Designs for Modern Genome-Wide Association Studies: Basic Principles and Overview
Published in Ørnulf Borgan, Norman E. Breslow, Nilanjan Chatterjee, Mitchell H. Gail, Alastair Scott, Christopher J. Wild, Handbook of Statistical Methods for Case-Control Studies, 2018
These studies allowed studying association of a trait simultaneously with hundreds of thousands to millions of genetic markers across the genome by studying large number of individuals from the general population. Most GWAS to date have focused on common single nucleotide polymorphisms (SNPs), which are bi-allelic genetic markers that have minor allele frequency (MAF) 5% or higher in at least one major ethnic population. These studies have already led to the discovery of thousands of genetic susceptibility loci across a large variety of complex traits (MacArthur et al., 2016); visscher201710. With the decreasing cost of sequencing technologies, GWAS are now beginning to shift its focus to low frequency () and rare variants () .
PCR primer design for detection of SNPs in SLC22A1 rs683369 encoding OCT1 as the main transporter of metformin
Published in Elida Zairina, Junaidi Khotib, Chrismawan Ardianto, Syed Azhar Syed Sulaiman, Charles D. Sands, Timothy E. Welty, Unity in Diversity and the Standardisation of Clinical Pharmacy Services, 2017
A.A. Mukminatin, V.D.A. Ningrum, R. Istikharah
Metformin is a strong base and exists as >99.9% cation at physiological pH (Christensen et al. 2011). Therefore, it needs a transporter to penetrate the hepatocyte membrane as its action target (Graham et al. 2011). It is widely acknowledged that the main transporter of metformin is Organic Cation Transporter 1 (OCT1) encoded by the SLC22A1 gene located on chromosome 6 and consisting of 11 exons spanning 37 kb. Polymorphisms of SLC22A1 gene are known to cause varied mechanisms of the body response to metformin, which is one of the substrates of the transporter (Jacobs et al. 2014), and can increase diabetes risk factors by 31% (Jablonski et al. 2010). One of the SLC22A1 genetic polymorphisms is the missense SNP rs68339 that leads to the conversion of guanine base into cytosine (Jablonski et al. 2010). These genetic variations affect the effectiveness of metformin pharmacokinetics and appear as one of the biomarkers of metformin efficacy and tolerability. The calculated MAF (Minor Allele Frequency) from few researches 0.339 (Schweighofer et al. 2014), 0.217 (Kim et al. 2009), and 0.22 (Kerb et al. 2002). This variation has also been identified and located in all ethnic groups (African American, European American, Asian American, Mexican American, Pacific Islander) with 13% frequency (Shu et al. 2003).
The common variant of rs6214 in insulin like growth factor 1 (IGF1) gene: a potential protective factor for non-alcoholic fatty liver disease
Published in Archives of Physiology and Biochemistry, 2023
Mohammad Sabzikarian, Touraj Mahmoudi, Seidamir Pasha Tabaeian, Gholamreza Rezamand, Asadollah Asadi, Hamid Farahani, Hossein Nobakht, Reza Dabiri, Fariborz Mansour-Ghanaei, Faramarz Derakhshan, Mohammad Reza Zali
In this study, genomic DNA was isolated from 5 ml EDTA-anti-coagulated whole blood using standard methods, and IGF1 rs6214 and IGFBP3 rs3110697 gene variants were genotyped using PCR-RFLP method. These two SNPs were selected based on their relatively high minor allele frequency (MAF), commonly use in the previous genetic studies, and functional importance. Laboratory personnel who performed the genotyping were blinded to the subjects’ clinical data including their case or control status. Characteristics of the studied gene variants, PCR primers, and PCR and RFLP conditions are summarised in Table 1. The PCR products were digested by corresponding restriction enzymes (Fermentas, Leon-Rot, Germany), and then, the digested products were electrophoresed on 2 to 3.5% agarose gels and stained with ethidium bromide for visualisation under UV light. IGF1 and IGFBP3 genotypes of each subject were identified according to the digestion pattern and the presence or absence of the Hin1II and BtsI sites, respectively. For quality control reasons, we repeated the genotyping analysis of approximately 20% of all the subjects, and all the results were concordant.
Correlation of CLEC1B haplotypes with plasma levels of soluble CLEC-2 in healthy individuals
Published in Platelets, 2021
Mani Etemad, Foteini Christodoulou, Christel Weiss, Harald Klüter, Peter Bugert
Genomic DNA isolated from EDTA blood samples (QIAamp DNA Blood Mini Kit; Qiagen, Hilden, Germany) was used for SNV genotyping. The SNP database (dbSNP) was screened for SNVs in the CLEC1B gene region considering the following criteria: 1) diallelic SNV in the promoter or coding region; 2) minor allele frequency (MAF) >0.01 in the European population; 3) no significant linkage between the SNVs. Accordingly, we selected 7 SNVs and genotyping was performed using commercial TaqMan® assays (Applied Biosystems, Weiterstadt, Germany) for 6 of the SNVs (Table I). For rs2273987 we established a PCR method with sequence-specific primers (PCR-SSP) according to our standard protocol [5]. A 164 bp PCR product was obtained by using the CLEC1B-specific forward primer (5ʹ-gatctgccagcaaagctctttc-3ʹ) and the rs2273987G-specific reverse primer (5ʹ-ccatcacacgccaccagg-3ʹ) or the rs2273987A-specific reverse primer (5ʹ-ccatcacacgccaccaga-3ʹ). Haplotypes were calculated based on the genotypes of the 7 SNVs applying the PHASE software version 2.1 [6].
Genetic polymorphism of Arg213His variant in the SULT1A1 gene is associated with reduced susceptibility to lung cancer in North Indian population
Published in Xenobiotica, 2021
Harleen Kaur Walia, Navneet Singh, Siddharth Sharma
Table 2 demonstrates the distribution of both the allelic and genotypic frequencies of SULT1A1 polymorphic variant Arg213His. The frequencies of Arg/Arg, Arg/His, and His/His were 61.09, 32.36, and 6.55%, respectively, in controls, and 66.18, 29.27, and 4.55% in cases. Thus, in both cases and controls, the genotypic frequencies of SULT1A1 did not exhibit any significant difference (χ2 = 3.96; df = 2; p = 0.14) as shown in Table 2. No significant departure was observed from Hardy-Weinberg equilibrium (HWE) for SULT1A1 genotype among cases (χ2=1.72; df = 1; p = 0.19) and controls (χ2=3.40; df = 1; p = 0.07), signifying no sample bias. Our data shows that the His/His genotype was found to be more pronounced in controls as compared to cases (6.55% vs. 4.55%). The minor allele frequency (MAF) was found to be 0.23 and 0.19 for controls and cases, respectively.