A small-sample multivariate kernel machine test for microbiome association studies

2016 ◽  
Vol 41 (3) ◽  
pp. 210-220 ◽  
Author(s):  
Xiang Zhan ◽  
Xingwei Tong ◽  
Ni Zhao ◽  
Arnab Maity ◽  
Michael C. Wu ◽  
...  
Keyword(s):  
Association Studies ◽  
Small Sample ◽  
Kernel Machine

Abstract P260: Large-scale Meta-analysis of Diverse Ancestry Genome-wide Association Studies to Identify Pharmacogenomic Interactions of Sulfonylureas and ECG Phenotypes

Circulation ◽  
2016 ◽  
Vol 133 (suppl_1) ◽  
Author(s):  
James S Floyd ◽  
Colleen Sitlani ◽  
Christy L Avery ◽  
Eric A Whitsel ◽  
Leslie Lange ◽  
...  
Keyword(s):  
Repeated Measures ◽  
Qt Interval ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
European Ancestry ◽  
Genome Wide Association Studies ◽  
Genome Wide ◽  
Meta Analyses

Introduction: Sulfonylureas are a commonly-used class of diabetes medication that can prolong the QT-interval, which is a leading cause of drug withdrawals from the market given the possible risk of life-threatening arrhythmias. Previously, we conducted a meta-analysis of genome-wide association studies of sulfonylurea-genetic interactions on QT interval among 9 European-ancestry (EA) cohorts using cross-sectional data, with null results. To improve our power to identify novel drug-gene interactions, we have included repeated measures of medication use and QT interval and expanded our study to include several additional cohorts, including African-American (AA) and Hispanic-ancestry (HA) cohorts with a high prevalence of sulfonylurea use. To identify potentially differential effects on cardiac depolarization and repolarization, we have also added two phenotypes - the JT and QRS intervals, which together comprise the QT interval. Hypothesis: The use of repeated measures and expansion of our meta-analysis to include diverse ancestry populations will allow us to identify novel pharmacogenomic interactions for sulfonylureas on the ECG phenotypes QT, JT, and QRS. Methods: Cohorts with unrelated individuals used generalized estimating equations to estimate interactions; cohorts with related individuals used mixed effect models clustered on family. For each ECG phenotype (QT, JT, QRS), we conducted ancestry-specific (EA, AA, HA) inverse variance weighted meta-analyses using standard errors based on the t-distribution to correct for small sample inflation in the test statistic. Ancestry-specific summary estimates were combined using MANTRA, an analytic method that accounts for differences in local linkage disequilibrium between ethnic groups. Results: Our study included 65,997 participants from 21 cohorts, including 4,020 (6%) sulfonylurea users, a substantial increase from the 26,986 participants and 846 sulfonylureas users in the previous meta-analysis. Preliminary ancestry-specific meta-analyses have identified genome-wide significant associations (P < 5х10–8) for each ECG phenotype, and analyses with MANTRA are in progress. Conclusions: In the setting of the largest collection of pharmacogenomic studies to date, we used repeated measurements and leveraged diverse ancestry populations to identify new pharmacogenomic loci for ECG traits associated with cardiovascular risk.

scholarly journals Epigenome-wide meta-analysis of blood DNA methylation and its association with subcortical volumes: findings from the ENIGMA Epigenetics Working Group

2019 ◽  
Author(s):  
Tianye Jia ◽  
Congying Chu ◽  
Yun Liu ◽  
Jenny van Dongen ◽  
Evangelos Papastergios ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Nucleus Accumbens ◽  
Large Scale ◽  
Biomarker Discovery ◽  
Association Studies ◽  
Meta Analysis ◽  
Hippocampal Volume ◽  
Small Sample ◽  
Small Sample Sizes ◽  
Meta Analyses

AbstractDNA methylation, which is modulated by both genetic factors and environmental exposures, may offer a unique opportunity to discover novel biomarkers of disease-related brain phenotypes, even when measured in other tissues than brain, such as blood. A few studies of small sample sizes have revealed associations between blood DNA methylation and neuropsychopathology, however, large-scale epigenome-wide association studies (EWAS) are needed to investigate the utility of DNA methylation profiling as a peripheral marker for the brain. Here, in an analysis of eleven international cohorts, totalling 3337 individuals, we report epigenome-wide meta-analyses of blood DNA methylation with volumes of the hippocampus, thalamus and nucleus accumbens (NAcc)—three subcortical regions selected for their associations with disease and heritability and volumetric variability. Analyses of individual CpGs revealed genome-wide significant associations with hippocampal volume at two loci. No significant associations were found for analyses of thalamus and nucleus accumbens volumes. Cluster-based analyses revealed additional differentially methylated regions (DMRs) associated with hippocampal volume. DNA methylation at these loci affected expression of proximal genes involved in learning and memory, stem cell maintenance and differentiation, fatty acid metabolism and type-2 diabetes. These DNA methylation marks, their interaction with genetic variants and their impact on gene expression offer new insights into the relationship between epigenetic variation and brain structure and may provide the basis for biomarker discovery in neurodegeneration and neuropsychiatric conditions.

scholarly journals A Network-Based Kernel Machine Test for the Identification of Risk Pathways in Genome-Wide Association Studies

2013 ◽  
Vol 76 (2) ◽  
pp. 64-75 ◽  
Author(s):  
Saskia Freytag ◽  
Juliane Manitz ◽  
Martin Schlather ◽  
Thomas Kneib ◽  
Christopher I. Amos ◽  
...  
Keyword(s):  
Association Studies ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Kernel Machine ◽  
Genome Wide

scholarly journals Power Estimation for Gene-Longevity Association Analysis Using Concordant Twins

2014 ◽  
Vol 2014 ◽  
pp. 1-8
Author(s):  
Qihua Tan ◽  
Jing Hua Zhao ◽  
Torben Kruse ◽  
Kaare Christensen
Keyword(s):  
Association Study ◽  
Genetic Association ◽  
Association Analysis ◽  
Statistical Power ◽  
Association Studies ◽  
Genetic Association Studies ◽  
Small Sample ◽  
Identical Twins ◽  
Human Longevity ◽  
Sample Sizes

Statistical power is one of the major concerns in genetic association studies. Related individuals such as twins are valuable samples for genetic studies because of their genetic relatedness. Phenotype similarity in twin pairs provides evidence of genetic control over the phenotype variation in a population. The genetic association study on human longevity, a complex trait that is under control of both genetic and environmental factors, has been confronted by the small sample sizes of longevity subjects which limit statistical power. Twin pairs concordant for longevity have increased probability for carrying beneficial genes and thus are useful samples for gene-longevity association analysis. We conducted a computer simulation to estimate the power of association study using longevity concordant twin pairs. We observed remarkable power increases in using singletons from longevity concordant twin pairs as cases in comparison with cases of sporadic proband. A similar power would require doubled sample sizes for fraternal twins than for identical twins who are concordant for longevity suggesting that longevity concordant identical twins are more efficient samples than fraternal twins. We also observed an approximate of 2- to 3-fold increase in sample sizes needed for longevity cutoff at age 90 as compared with that at age 95. Overall, our results showed high value of twins in genetic association studies on human longevity.

scholarly journals Genome-wide association studies for canine hip dysplasia in single and multiple populations – implications and potential novel risk loci

BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Shizhi Wang ◽  
Erling Strandberg ◽  
Per Arvelius ◽  
Dylan N. Clements ◽  
Pamela Wiener ◽  
...  
Keyword(s):  
Hip Dysplasia ◽  
Association Studies ◽  
Meta Analysis ◽  
Small Sample ◽  
Genome Wide Association ◽  
Genome Wide Association Studies ◽  
Single Population ◽  
Positional Candidate ◽  
Genome Wide ◽  
Canine Hip Dysplasia

Abstract Background Association mapping studies of quantitative trait loci (QTL) for canine hip dysplasia (CHD) can contribute to the understanding of the genetic background of this common and debilitating disease and might contribute to its genetic improvement. The power of association studies for CHD is limited by relatively small sample numbers for CHD records within countries, suggesting potential benefits of joining data across countries. However, this is complicated due to the use of different scoring systems across countries. In this study, we incorporated routinely assessed CHD records and genotype data of German Shepherd dogs from two countries (UK and Sweden) to perform genome-wide association studies (GWAS) within populations using different variations of CHD phenotypes. As phenotypes, dogs were either classified into cases and controls based on the Fédération Cynologique Internationale (FCI) five-level grading of the worst hip or the FCI grade was treated as an ordinal trait. In a subsequent meta-analysis, we added publicly available data from a Finnish population and performed the GWAS across all populations. Genetic associations for the CHD phenotypes were evaluated in a linear mixed model using 62,089 SNPs. Results Multiple SNPs with genome-wide significant and suggestive associations were detected in single-population GWAS and the meta-analysis. Few of these SNPs overlapped between populations or between single-population GWAS and the meta-analysis, suggesting that many CHD-related QTL are population-specific. More significant or suggestive SNPs were identified when FCI grades were used as phenotypes in comparison to the case-control approach. MED13 (Chr 9) and PLEKHA7 (Chr 21) emerged as novel positional candidate genes associated with hip dysplasia. Conclusions Our findings confirm the complex genetic nature of hip dysplasia in dogs, with multiple loci associated with the trait, most of which are population-specific. Routinely assessed CHD information collected across countries provide an opportunity to increase sample sizes and statistical power for association studies. While the lack of standardisation of CHD assessment schemes across countries poses a challenge, we showed that conversion of traits can be utilised to overcome this obstacle.

scholarly journals Association between PRDM16, MEF2D, TRPM8, LRP1 gene polymorphisms and migraine susceptibility in the She ethnic population in China

2019 ◽  
Vol 42 (1) ◽  
pp. E21-E30 ◽  
Author(s):  
Xianguo Fu ◽  
Jing Yang ◽  
Xiaoyang Wu ◽  
Qifang Lin ◽  
Yuli Zeng ◽  
...  
Keyword(s):  
Association Studies ◽  
Direct Sequencing ◽  
Significant Risk ◽  
Significant Risk Factor ◽  
Han Chinese ◽  
Small Sample ◽  
Genome Wide Association Studies ◽  
Healthy Controls ◽  
Nucleotide Polymorphisms ◽  
Asian Populations

Background: The prevalence of migraines in the She population, a minority in China, is significantly higher than that in Han Chinese and other Asian populations. Two single nucleotide polymorphisms (SNPs) have been found to be associated with migraine susceptibility in the She population. Purpose: This study investigated four SNPs, identified in genome-wide association studies, within migraine-susceptible loci in Han Chinese for their association with migraine susceptibility in the She population. Methods: Two-hundred unrelated migraine patients and 200 healthy controls were recruited. The SNPs examined included rs2651899 (PRDM16 ), rs2274316 (MEF2D ), rs7577262 (TRPM8) and rs11172113 (LRP1). Genotyping of the SNPs was performed by allele-specific polymerase chain reaction and direct sequencing. Results: No significant differences between the participants with migraines and controls (participants without migraines) were demonstrated in genotypes, alleles and allele carriage frequencies for the four SNPs. A subgroup analysis found that migraine with aura had a lower frequency of C allele positivity in rs2651899 than in healthy controls (59.6% vs. 74.5%, respectively; P < 0.034). Univariate analyses indicated that no genotype of the four SNPs had a significant association with migraines. Males had a lower risk of migraines, and advanced age was a significant risk factor for migraines in females. Conclusion: The SNPs in four migraine susceptible loci in Han Chinese were not risk factors for migraines in a relatively small sample of the She population.

Association between restless legs syndrome and other movement disorders

Neurology ◽  
2019 ◽  
Vol 92 (20) ◽  
pp. 948-964 ◽  
Author(s):  
Hortensia Alonso-Navarro ◽  
Elena García-Martín ◽  
José A.G. Agúndez ◽  
Félix Javier Jiménez-Jiménez
Keyword(s):  
Essential Tremor ◽  
Tourette Syndrome ◽  
Restless Legs Syndrome ◽  
Movement Disorders ◽  
Association Studies ◽  
Friedreich Ataxia ◽  
Small Sample ◽  
Spinocerebellar Ataxia Type ◽  
Clinical Feature ◽  
Restless Legs

ObjectiveThis review focuses on the possible association between restless legs syndrome (RLS) and movement disorders, including Parkinson disease (PD), other parkinsonian syndromes, essential tremor, choreic and dystonic syndromes, Tourette syndrome, and heredodegenerative ataxias.MethodsReview of PubMed from 1966 to September 2018 and identification of references of interest for the topic. A meta-analysis of eligible studies on the frequency of RLS in patients with PD and controls using Meta-DiSc1.1.1 software and using the PRISMA guidelines was performed.Results and conclusionsAlthough there are substantial clinical, neuroimaging, neuropathologic, and genetic differences between RLS and PD, many reports describe a higher than expected prevalence of RLS in patients with PD, when compared with the general population or with matched control groups; several studies have also suggested that RLS could be an early clinical feature of PD. RLS symptoms are frequent in multiple system atrophy, essential tremor, Tourette syndrome, Friedreich ataxia, and spinocerebellar ataxia type 3 as well. Finally, possible genetic links between PD and RLS (the presence of allele 2 of the complex microsatellite repeat Rep1 within the α-synuclein gene promoter) and between Tourette syndrome and RLS (several variants in theBTBD9gene) have been reported in 2 case–control association studies, although these data, based on preliminary data with small sample sizes, need to be replicated in further studies.

Multiple Testing in Candidate Gene Situations: A Comparison of Classical, Discrete, and Resampling-Based Procedures

2011 ◽  
Vol 10 (1) ◽  
Author(s):  
Amelie Elsäßer ◽  
Anja Victor ◽  
Gerhard Hommel
Keyword(s):  
Sample Size ◽  
Candidate Gene ◽  
Multiple Testing ◽  
Small Sample Size ◽  
Association Studies ◽  
Correlated Data ◽  
Small Sample ◽  
Testing Procedures ◽  
Multiple Testing Procedures ◽  
Resampling Procedure

In candidate gene association studies, usually several elementary hypotheses are tested simultaneously using one particular set of data. The data normally consist of partly correlated SNP information. Every SNP can be tested for association with the disease, e.g., using the Cochran-Armitage test for trend. To account for the multiplicity of the test situation, different types of multiple testing procedures have been proposed. The question arises whether procedures taking into account the discreteness of the situation show a benefit especially in case of correlated data. We empirically evaluate several different multiple testing procedures via simulation studies using simulated correlated SNP data. We analyze FDR and FWER controlling procedures, special procedures for discrete situations, and the minP-resampling-based procedure. Within the simulation study, we examine a broad range of different gene data scenarios. We show that the main difference in the varying performance of the procedures is due to sample size. In small sample size scenarios, the minP-resampling procedure though controlling the stricter FWER even had more power than the classical FDR controlling procedures. In contrast, FDR controlling procedures led to more rejections in higher sample size scenarios.

scholarly journals Leveraging expression from multiple tissues using sparse canonical correlation analysis and aggregate tests improves the power of transcriptome-wide association studies

PLoS Genetics ◽  
2021 ◽  
Vol 17 (4) ◽  
pp. e1008973
Author(s):  
Helian Feng ◽  
Nicholas Mancuso ◽  
Alexander Gusev ◽  
Arunabha Majumdar ◽  
Megan Major ◽  
...  
Keyword(s):  
Gene Expression ◽  
Correlation Analysis ◽  
Canonical Correlation Analysis ◽  
Canonical Correlation ◽  
Association Studies ◽  
Expression Patterns ◽  
Small Sample ◽  
Type I ◽  
Sparse Canonical Correlation Analysis ◽  
Eqtl Data

Transcriptome-wide association studies (TWAS) test the association between traits and genetically predicted gene expression levels. The power of a TWAS depends in part on the strength of the correlation between a genetic predictor of gene expression and the causally relevant gene expression values. Consequently, TWAS power can be low when expression quantitative trait locus (eQTL) data used to train the genetic predictors have small sample sizes, or when data from causally relevant tissues are not available. Here, we propose to address these issues by integrating multiple tissues in the TWAS using sparse canonical correlation analysis (sCCA). We show that sCCA-TWAS combined with single-tissue TWAS using an aggregate Cauchy association test (ACAT) outperforms traditional single-tissue TWAS. In empirically motivated simulations, the sCCA+ACAT approach yielded the highest power to detect a gene associated with phenotype, even when expression in the causal tissue was not directly measured, while controlling the Type I error when there is no association between gene expression and phenotype. For example, when gene expression explains 2% of the variability in outcome, and the GWAS sample size is 20,000, the average power difference between the ACAT combined test of sCCA features and single-tissue, versus single-tissue combined with Generalized Berk-Jones (GBJ) method, single-tissue combined with S-MultiXcan, UTMOST, or summarizing cross-tissue expression patterns using Principal Component Analysis (PCA) approaches was 5%, 8%, 5% and 38%, respectively. The gain in power is likely due to sCCA cross-tissue features being more likely to be detectably heritable. When applied to publicly available summary statistics from 10 complex traits, the sCCA+ACAT test was able to increase the number of testable genes and identify on average an additional 400 additional gene-trait associations that single-trait TWAS missed. Our results suggest that aggregating eQTL data across multiple tissues using sCCA can improve the sensitivity of TWAS while controlling for the false positive rate.

scholarly journals Taking population stratification into account by local permutations in rare-variant association studies on small samples

2020 ◽  
Author(s):  
J. Mullaert ◽  
M. Bouaziz ◽  
Y. Seeleuthner ◽  
B. Bigio ◽  
J-L. Casanova ◽  
...  
Keyword(s):  
Sample Size ◽  
Rare Variant ◽  
Population Stratification ◽  
Type I Error ◽  
Small Sample Size ◽  
Association Studies ◽  
Small Sample ◽  
Small Samples ◽  
Type I ◽  
Rare Variant Association

AbstractMany methods for rare variant association studies require permutations to assess the significance of tests. Standard permutations assume that all individuals are exchangeable and do not take population stratification (PS), a known confounding factor in genetic studies, into account. We propose a novel strategy, LocPerm, in which individuals are permuted only with their closest ancestry-based neighbors. We performed a simulation study, focusing on small samples, to evaluate and compare LocPerm with standard permutations and classical adjustment on first principal components. Under the null hypothesis, LocPerm was the only method providing an acceptable type I error, regardless of sample size and level of stratification. The power of LocPerm was similar to that of standard permutation in the absence of PS, and remained stable in different PS scenarios. We conclude that LocPerm is a method of choice for taking PS and/or small sample size into account in rare variant association studies.

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