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Genetics and exercise: an introduction
Published in Adam P. Sharples, James P. Morton, Henning Wackerhage, Molecular Exercise Physiology, 2022
Claude Bouchard, Henning Wackerhage
In 2004, the first papers reporting the development of SNP chips allowing the genotyping of thousands of DNA variants in a single experiment were published. In 2007, a research consortium used SNP microarrays to genotype half a million SNPs in 14,000 patients covering seven common diseases and compared the allele frequencies with those of 3,000 controls. This led to the identification of 24 SNP loci that were significantly associated with these diseases (41). Since then, hundreds of GWASs have been reported, and their findings can be accessed (https://www.ebi.ac.uk/gwas/). Typically, the global results of a GWAS are presented as a Manhattan plot, where the x-axis shows the genomic location (i.e. lists all the chromosomes) and the y-axis the association p-value of each SNP with the trait investigated. Importantly, because of the large number of statistical tests performed, the association between a SNP and a trait needs to reach a p-value of 5 x 10−8 or less to be considered significant. Figure 3.14 shows an example of a Manhattan plot from a study where the authors searched for SNPs associated with sleep duration and found one locus near the PAX8 gene on chromosome 2 that reached the significance threshold.
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
The whole set of meta-analysis results gives us a way of assessing whether or not our meta-analysis model was appropriate. The analysis was conducted to identify a relatively small number of genetic variants that are associated with the disease, but it is assumed that the over-whelming mass of variants will show no association. If this is the case, most variants will have p-values that will be randomly distributed between zero and one. Results of both primary GWAS and meta-analyses of GWAS are often graphically presented using a Manhattan plot, where association (−log10) p-values for all variants are plotted against their location in the genome (Figure 17.1). The strict level for genome-wide significance ensures that very few of these null variants are identified as true associations (“hits”). Further visualization of the results can be provided using a regional association plot (Figure 17.2), which shows (−log10) p-values for SNPs within a specific region against their genomic position, together with gene annotations, estimated recombination rates, i.e., rates at which linkage is broken (Attia et al., 2009), and linkage disequilibrium (pairwise correlation) between the top hit and the surrounding SNPs.
Several clock genes polymorphisms are meaningful risk factors in the development and severity of cannabis addiction
Published in Chronobiology International, 2019
Raphael Saffroy, Genevieve Lafaye, Christophe Desterke, Elisabeth Ortiz-Tudela, Ammar Amirouche, Pasquale Innominato, Patrick Pham, Amine Benyamina, Antoinette Lemoine
SNPs which passed quality control (supplemental Table 1) were used to perform genotypic multitesting. This analysis identified 27 SNPs preferentially associated with the cannabis-abusing group (see Table 2). Chromosomes 12 and 17 contained the most relevant genomic regions associated with significant differences in the cannabis-dependent group, as well as regions on chromosomes 11, 10, and 8. The gene locus HES7/PER1 on chromosome 17 (8 genotypes) and TPH2 gene locus on chromosome 12 (7 genotypes) are hotspots (Table 2). The Manhattan plot (Figure 2a) shows that the most significant p-values, both quantitatively and qualitatively, concerned the HES7/PER1 gene locus.
Genome-wide association study of white-coat effect in hypertensive patients
Published in Blood Pressure, 2019
Jenni M Rimpelä, Teemu Niiranen, Antti Jula, Ilkka H Pörsti, Antti Tikkakoski, Aki Havulinna, Terho Lehtimäki, Veikko Salomaa, Kimmo K Kontula, Timo P Hiltunen
The Q-Q plot from the discovery GWAS of diastolic WCE showed little evidence of genomic inflation, suggesting that some of the associations may be significant (Supplementary Figure 2(B)). The Manhattan plot (Figure 1(B)) shows seven loci with p < 1 × 10−5, but no genome-wide significant SNPs were identified. The results of the discovery GWAS are summarized in in Table 4 and Supplementary Figure 4(A–G). Like for systolic WCE, we also tested if the top diastolic WCE associations derived from the placebo periods were similar when WCE data during the four different drug periods were analyzed. As shown in the Supplementary Table 2, all the associations were consistently in the same direction and mostly statistically significant.
The project MinE databrowser: bringing large-scale whole-genome sequencing in ALS to researchers and the public
Published in Amyotrophic Lateral Sclerosis and Frontotemporal Degeneration, 2019
Rick A.A. van der Spek, Wouter van Rheenen, Sara L. Pulit, Kevin P. Kenna, Leonard H. van den Berg, Jan H. Veldink
Geneset burden results (Figure 3(c)). Here, we show burden test results for genesets such as protein families and druggable targets to which the selected gene belongs. This includes a mini-Manhattan plot generated to indicate which genes might be driving an association signal in the geneset by plotting their individual genic burden results.