Factors affecting statistical power in the detection of genetic association

Gordon, Derek; Finch, Stephen J.

doi:10.1172/jci24756

Cited by 118 publications

(103 citation statements)

References 108 publications

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“…Unlike association studies that evaluate presence of a certain allele or a genotype and presence of a disease 24 , we investigated these sites as potential predictors of time to onset of aseptic loosening after THA. Each SNP (site) was assessed with adjustment for the effects of other SNPs and with adjustment for sex, age at surgery and reason for THA 2,7,9 .…”

Section: Discussionmentioning

confidence: 99%

Single nucleotide polymorphisms in the interleukin-6 gene promoter, tumor necrosis factor-α gene promoter, and transforming growth factor-β1 gene signal sequence as predictors of time to onset of aseptic loosening after total hip arthroplasty: preliminary study

Kolundžić

Orlić

Trkulja

et al. 2006

Journal of Orthopaedic Science

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Section: Discussionmentioning

confidence: 99%

Single nucleotide polymorphisms in the interleukin-6 gene promoter, tumor necrosis factor-α gene promoter, and transforming growth factor-β1 gene signal sequence as predictors of time to onset of aseptic loosening after total hip arthroplasty: preliminary study

Kolundžić

Orlić

Trkulja

et al. 2006

Journal of Orthopaedic Science

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“…Power to detect SNPs of small effect across multiple populations is further limited by constraints on trial design. Population sizes of many thousands have been recommended from simulation experiments to be necessary to detect associations in trees (Purcell et al 2003;Ball 2005;Gordon and Finch 2005), and human studies employing large populations commonly detect SNPs with small effects (,2%). Phenotypic variation arising from di- verse gene-by-environment interactions within and between sites was not accounted for in this study, whereas the discovery (Snowy Mountain Range) and validation (coastal valley in Southern Victoria) trials are strongly contrasted with respect to altitude, evapotranspiration, temperature, and soil type (New LocClim V 1.10).…”

Section: ; Dalla-salda Et Al 2009mentioning

confidence: 99%

“…Despite the potential promised from association genetics, several factors have been identified that influence power to detect true associations (Long and Langley 1999;Neale and Savolainen 2004;Gordon and Finch 2005;Newton-Cheh and Hirschhorn 2005). These factors can often be accounted for at the experimental design phase, by considering the extent of genome-wide LD, the candidate genes selected, the effect size, the number of genes affecting the trait, allele frequency, sample size, and rates of genotyping and phenotyping error.…”

Section: Introductionmentioning

confidence: 99%

“…This finding demonstrates the utility of populations harboring low LD in the study of causative polymorphisms. Association genetics has also been applied in model plants to identify SNPs influencing major traits in Arabidopsis and maize (Thornsberry et al 2001;Olsen et al 2004;Aranzana et al 2005) and has been used extensively to dissect complex traits in humans where population structure parallels that of many tree species (Pritchard and Przeworski 2001;Burton et al 2007).Despite the potential promised from association genetics, several factors have been identified that influence power to detect true associations (Long and Langley 1999;Neale and Savolainen 2004;Gordon and Finch 2005;Newton-Cheh and Hirschhorn 2005). These factors can often be accounted for at the experimental design phase, by considering the extent of genome-wide LD, the candidate genes selected, the effect size, the number of genes affecting the trait, allele frequency, sample size, and rates of genotyping and phenotyping error.…”

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confidence: 99%

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Allelic Variation in Cell Wall Candidate Genes Affecting Solid Wood Properties in Natural Populations and Land Races of Pinus radiata

Dillon

Nolan

et al. 2010

Genetics

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Forest trees are ideally suited to association mapping due to their high levels of diversity and low genomic linkage disequilibrium. Using an association mapping approach, single-nucleotide polymorphism (SNP) markers influencing quantitative variation in wood quality were identified in a natural population of Pinus radiata. Of 149 sites examined, 10 demonstrated significant associations (P , 0.05, q , 0.1) with one or more traits after accounting for population structure and experimentwise error. Without accounting for marker interactions, phenotypic variation attributed to individual SNPs ranged from 2 to 6.5%. Undesirable negative correlations between wood quality and growth were not observed, indicating potential to break negative correlations by selecting for individual SNPs in breeding programs. Markers that yielded significant associations were reexamined in an Australian land race. SNPs from three genes (PAL1, PCBER, and SUSY) yielded significant associations. Importantly, associations with two of these genes validated associations with density previously observed in the discovery population. In both cases, decreased wood density was associated with the minor allele, suggesting that these SNPs may be under weak negative purifying selection for density in the natural populations. These results demonstrate the utility of LD mapping to detect associations, even when the power to detect SNPs with small effect is anticipated to be low. N UMEROUS traits of agronomic importance are demonstrated to be under genetic control (Keurentjes et al. 2008), and there is considerable interest in characterizing the causative polymorphisms underlying their quantitative variation. In forest trees, quantitative variation in traits such as mechanical and pulping properties of wood, growth, cold hardiness, and drought acclimation are likely to result from allelic variation within multiple genes (Neale and Savolainen 2004;Oraguzie and Wilcox 2007). Because of the commercial importance of radiata pine (Pinus radiata D. Don), we are exploring the molecular basis of variation in its wood properties using an association genetics approach.Radiata pine wood properties are variable in domesticated populations and exhibit a quantitative mode of inheritance with high heritability, indicating a strong underlying genetic component. High heritabilities have been observed for solid wood traits including density, cellulose microfibril angle (MFA), and modulus of elasticy (MOE) (Baltunis et al. 2007) and for carbohydrate composition, pulp yield, fiber length, and perimeter (Evans et al. 1997;Kibblewhite 1999); and genetic control has been established for several important production traits (Kumar 2004;Dungey et al. 2006;Gapare et al. 2006;Wu et al. 2007).It is anticipated that variation in wood quality will be dependent on variation in numerous genes involved in xylogenesis. Studies of gene expression in developing xylem have revealed genes involved in spatially and temporally regulated processes such as cambial division, cell different...

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“…24 A widely used statistical method to assess association is the 2 test of independence, which assumes the null hypothesis of no association between the disease trait and a marker locus, most frequently at a 5% type I error rate. 25 Thus, if the P value corresponding to the 2 statistic is considered significant, the null hypothesis is rejected and an association is surmised. Depending on the marker being tested (often a SNP within a gene), the detected association could directly affect the phenotype (i.e., susceptibility variant) or may be linked to the true phenotypic effector.…”

Section: Genomic Study Of Complex Traitsmentioning

confidence: 99%

Genomics and complex liver disease: Challenges and opportunities

Juran

Lazaridis

2006

Hepatology

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The concept of genetic susceptibility in the contribution to human disease is not new. What is new is the emerging ability of the field of genomics to detect, assess, and interpret genetic variation in the study of susceptibility to development of disease. Deciphering the human genome sequence and the publication of the human haplotype map are key elements of this effort. However, we are only beginning to understand the contribution of genetic predisposition to complex liver disease through its interaction with environmental risk factors. In the coming decade, we anticipate the development of human studies to better dissect the genotype/phenotype relationship of complex liver diseases. This endeavor will require large, well-phenotyped patient populations of each disease of interest and proper study designs aimed at answering important questions of hepatic disease prognosis, pathogenesis, and treatment. Teamwork between patients, physicians, and genomics scientists can ensure that this opportunity leads to important biological discoveries and improved treatment of complex disease. (HEPATOLOGY 2006;44:1380-1390

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Factors affecting statistical power in the detection of genetic association

Cited by 118 publications

References 108 publications

Single nucleotide polymorphisms in the interleukin-6 gene promoter, tumor necrosis factor-α gene promoter, and transforming growth factor-β1 gene signal sequence as predictors of time to onset of aseptic loosening after total hip arthroplasty: preliminary study

Single nucleotide polymorphisms in the interleukin-6 gene promoter, tumor necrosis factor-α gene promoter, and transforming growth factor-β1 gene signal sequence as predictors of time to onset of aseptic loosening after total hip arthroplasty: preliminary study

Allelic Variation in Cell Wall Candidate Genes Affecting Solid Wood Properties in Natural Populations and Land Races of Pinus radiata

Genomics and complex liver disease: Challenges and opportunities

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