The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants

Fadista, João; Manning, Alisa K.; Florez, José C.; Groop, Leif

doi:10.1038/ejhg.2015.269

Cited by 255 publications

(209 citation statements)

References 16 publications

Supporting

Mentioning

201

Contrasting

Unclassified

Order By: Relevance

“…As reported in Soerensen et al., 2012; tagging SNPs were prioritized by establishing a cutoff of r 2 = .8, LOD = 3, minor allele frequency (MAF)>5% and a minimum distance between SNPs = 60 bp criteria. The selection of common variants (MAF ≥ 5) and a LD r 2 < .8 is widely used in genomewide association studies (Fadista, Manning, Florez & Groop, 2016). Furthermore, we tested LD levels by genomic region in the control sample (data not shown).…”

Section: Methodsmentioning

confidence: 99%

The genetic component of human longevity: New insights from the analysis of pathway‐based SNP‐SNP interactions

et al. 2018

View full text Add to dashboard Cite

SummaryIn human longevity studies, single nucleotide polymorphism (SNP) analysis identified a large number of genetic variants with small effects, yet not easily replicable in different populations. New insights may come from the combined analysis of different SNPs, especially when grouped by metabolic pathway. We applied this approach to study the joint effect on longevity of SNPs belonging to three candidate pathways, the insulin/insulin‐like growth factor signalling (IIS), DNA repair and pro/antioxidant. We analysed data from 1,058 tagging SNPs in 140 genes, collected in 1825 subjects (1,089 unrelated nonagenarians from the Danish 1905 Birth Cohort Study and 736 Danish controls aged 46–55 years) for evaluating synergic interactions by SNPsyn. Synergies were further tested by the multidimensional reduction (MDR) approach, both intra‐ and interpathways. The best combinations (FDR<0.0001) resulted those encompassing IGF1R‐rs12437963 and PTPN1‐rs6067484, TP53‐rs2078486 and ERCC2‐rs50871, TXNRD1‐rs17202060 and TP53‐rs2078486, the latter two supporting a central role of TP53 in mediating the concerted activation of the DNA repair and pro‐antioxidant pathways in human longevity. Results were consistently replicated with both approaches, as well as a significant effect on longevity was found for the GHSR gene, which also interacts with partners belonging to both IIS and DNA repair pathways (PAPPA,PTPN1,PARK7, MRE11A). The combination GHSR‐MREA11, positively associated with longevity by MDR, was further found influencing longitudinal survival in nonagenarian females (p = .026). Results here presented highlight the validity of SNP‐SNP interactions analyses for investigating the genetics of human longevity, confirming previously identified markers but also pointing to novel genes as central nodes of additional networks involved in human longevity.

show abstract

Section: Methodsmentioning

confidence: 99%

The genetic component of human longevity: New insights from the analysis of pathway‐based SNP‐SNP interactions

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Although specific thresholds vary based on non-independence of genetic loci, model assumptions, and use of alternative false discovery rate methods, but a P value of between 1x10 −7 to 1x10 −8 is generally considered necessary for exome-wide significance in NGS studies. [8][9][10][11][12][13][14][15][16][17][18][19][20][21][22][23] Because of these heightened significance requirements, investigators should thoughtfully determine the necessary sample size in the initial stages of study design. Clinicians, statisticians, and bioinformaticians should collaborate in planning the study, each bringing a unique skill set to the design process.…”

Section: Adequate Sample Size For Desired Powermentioning

confidence: 99%

Four study design principles for genetic investigations using next generation sequencing

Mason

2017

BMJ

View full text Add to dashboard Cite

Proper study design is crucial for obtaining meaningful results and reaching correct conclusions in scientific investigations. How to apply key study design principles to next generation sequencing (NGS) can be unclear and is sometimes overlooked by researchers who are new to this technology. A proper study design in NGS studies can be achieved with awareness of factors that can influence sequencing results and by taking the necessary steps to limit their biasing assessment. These steps include using simultaneously or similarly sequenced controls, randomising, determining the necessary sequencing depth, and performing a power calculation to determine the necessary sample size for testing hypotheses at significance levels adjusted for multiple comparisons. Applying study design principles to NGS studies will increase the likelihood of identifying genetic factors associated with human traits and diseases.Studies using next generation sequencing (NGS) dominate genetic research, contributing to rapid increases in our understanding of nearly all diseases. 1 These studies are highly attractive for investigating the genetic features of almost any trait or malady owing to affordability and breadth of genomic assessment. Although NGS provides a wealth of information, it is not free from biases that can result in incorrect or limited conclusions. Yet potential obstacles can be overcome by correctly applying study design principles.The first steps of planning an NGS study are identifying the hypothesis, the type of study that will test it most efficiently, and the appropriate technology to use. The goal is to limit biases and their resultant false positives, while having adequate power to identify true positive effects. NGS studies can be used to assess DNA variants and mutations, RNA transcript abundance, methylation levels, transcription factor binding, and knockdown or knockout effects through shRNA or CRISPR screens. The advantages and nuances of these applications have been reviewed thoroughly elsewhere, 1-4 but experimental design strategies applied to NGS have received less attention. 5-8 This paper seeks to help clinician investigators apply four key study design principles-similar assessment of controls, randomisation, sufficient evaluation, and adequate sample size-in conducting an NGS experiment, focusing on assessing DNA variants and mutations using targeted sequencing, whole exome sequencing (often abbreviated as WES), and whole genome sequencing (abbreviated as WGS, see box 1 for a glossary of terms) in case-control and cohort studies. Similar assessment of controlsDetermining the genetic variations that are associated with affected cases requires comparison with unaffected controls. Publicly available control databases are sometimes used in NGS studies as replacements for simultaneous controls to save costs. Although DNA mutations are more reproducible than other genetic features, such as expression or methylation, 9-12 simultaneously sequencing DNA from appropriate controls is still very useful, particularl...

show abstract

“…The p value threshold for genelevel significance is commonly set at 2.5 × 10 -6 , accounting for a 5% α risk with Bonferroni correction for about 20,000 tests. At the single variant level, the following exome-wide thresholds have been suggested: 10 -6 for variants with a MAF ≥ 5%, 7 × 10 -7 for variants with a MAF ≥ 1%, 5 × 10 -7 for variants with a MAF ≥ 0.5%, and 3 × 10 -7 for variants with a MAF ≥ 0.1% [56] .…”

Section: From the Variant Level To The Gene Levelmentioning

confidence: 99%

From Common to Rare Variants: The Genetic Component of Alzheimer Disease

Nicolas

Charbonnier²,

Campion³

2016

Hum Hered

View full text Add to dashboard Cite

Alzheimer disease (AD) is a remarkable example of genetic heterogeneity. Extremely rare variants in the APP, PSEN1, or PSEN2 genes, or duplications of the APP gene cause autosomal dominant forms, generally with complete penetrance by the age of 65 years. Nonautosomal dominant forms are considered as a complex disorder with a high genetic component, whatever the age of onset. Although genetically heterogeneous, AD is defined by the same neuropathological criteria in all configurations. According to the amyloid cascade hypothesis, the Aβ peptide, which aggregates in AD brains, is a key player. APP, PSEN1, or PSEN2 gene mutations increase the production of more aggregation-prone forms of the Aβ peptide, triggering the pathological process. Several risk factors identified in association studies hit genes involved in Aβ production/secretion, aggregation, clearance, or toxicity. Among them, the APOE ε4 allele is a rare example of a common allele with a large effect size, the ORs ranging from 4 to 11-14 for heterozygous and homozygous carriers, respectively. In addition, genome-wide association studies have identified more than two dozen loci with a weak but significant association, the OR of the at-risk allele ranging from 1.08 to 1.30. Recently, the use of massive parallel sequencing has enabled the analysis of rare variants in a genome-wide manner. Two rare variants have been nominally associated with AD risk or protection (TREM2 p.R47H, MAF approximately 0.002, OR approximately 4 and APP p.A673T, MAF approximately 0.0005, OR approximately 0.2). Association analyses at the gene level identified rare loss-of-function and missense, predicted damaging, variants (MAF <0.01) in the SORL1 and ABCA7 genes associated with a moderate relative risk (OR approximately 5 and approximately 2.8, respectively). Although the latter analyses revealed association signals with moderately rare variants by collapsing them, the power to detect genes hit by extremely rare variants is still limited. An alternative approach is to consider the de novo paradigm, stating that de novo variants may contribute to AD genetics in sporadic patients. Here, we critically review AD genetics reports with a special focus on rare variants.

show abstract

The (in)famous GWAS P-value threshold revisited and updated for low-frequency variants

Cited by 255 publications

References 16 publications

The genetic component of human longevity: New insights from the analysis of pathway‐based SNP‐SNP interactions

The genetic component of human longevity: New insights from the analysis of pathway‐based SNP‐SNP interactions

Four study design principles for genetic investigations using next generation sequencing

From Common to Rare Variants: The Genetic Component of Alzheimer Disease

Contact Info

Product

Resources

About