ライフサイエンスコーパス: GWAS

1 GWAS analysis of data from RNA, protein, and metabolite-

2 GWAS findings have also been used in mendelian randomisa

3 GWAS for leaf color detects six candidate loci responsib

4 GWAS have identified hundreds of height-associated loci.

5 GWAS heritability analysis suggested that common variant

6 GWAS in a separate cohort of 48 TIH patients and 2,922 c

7 GWAS studies indicates that the CNR2 gene is associated

8 GWAS using more complete reference sets for imputation,

9 e identified 140 coincident cis-eQTLs at 109 GWAS loci, including 93 eQTLs not previously described.

10 simulation studies and joint analysis of 18 GWAS datasets.

11 genome-wide association studies revealed 28 GWAS hits in potential candidate genes likely to affect

12 the MDD PRS and AD in the meta-analysis of 3 GWAS AD samples without MDD cases (best P = .007).

13 We investigated the associations of 46 GWAS-identified SNPs, circulating concentrations of 25-h

14 ssociations of common genetic variants in 57 GWASs with 24 studies of expression quantitative trait l

15 ovide a list of targeted eGenes for 21 of 58 GWAS loci.

16 ent significance threshold (P<7.1 x 10(-9)), GWAS in the AGP revealed an association between 'the deg

17 A GWAS peak on chromosome 7 between LOC_Os07g11020 and LOC

18 ied by a genetic association study such as a GWAS.

19 Here we conducted a GWAS and a replication study in Koreans using a total of

20 ore complete variant catalog, we conducted a GWAS meta-analysis of kidney function based on the estim

21 We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls

22 Here we describe a GWAS using a highly multiplexed aptamer-based affinity p

23 Validation is performed using data from a GWAS and results from three in vitro experiments.

24 port 116 significant independent loci from a GWAS of neuroticism in 329,821 UK Biobank participants;

25 n levels with the presence of mutations in a GWAS FTD-cohort.

26 We carried out a GWAS comparing 73 infants with challenge-proven IgE-medi

27 The authors performed a GWAS of 14,255 AF cases and 374,939 controls, using whol

28 We performed a GWAS on BHR severity in adult asthmatics from the Dutch

29 Here we present a GWAS in 212 nuclear families with pediatric VTE followed

30 g 50 complex traits with publicly accessible GWAS summary statistics (Ntotal approximately 4.5 millio

31 Nearly half of all GWAS CRC risk loci co-localize to recurrently activated

32 Genome-wide association analysis (GWAS) identified genomic regions containing clusters of

33 onducted a genome-wide association analysis (GWAS) to identify genetic variants that predict MS relap

34 mining existing single GWAS or meta-analyzed GWAS data.

35 e discovery rate method, this study analyzed GWAS data from a selection of archetypal autoimmune dise

36 pendence and the largest-ever cross-ancestry GWAS meta-analysis for any smoking phenotype, we reconfi

37 amine the transferability of single-ancestry GWASs, we used published summary statistics to calculate

38 After quality control filters and GWAS imputation, 285 patients and 1,006 controls remaine

39 lung meQTL lists to assess enrichment of ASD GWAS results for tissue-specific meQTLs.

40 ely associated with QT in a prior East Asian GWAS; in contrast BVES and CAP2 murine knockouts caused

41 thelial monolayer integrity, ARDS-associated GWAS genes, and lung pathophysiology.

42 ty in adult asthmatics from the Dutch Asthma GWAS cohort (n = 650), adjusting for smoking and inhaled

43 applied this approach to 2 published asthma GWASs (combined n = 46,044) and used mouse studies to pr

44 sertion variants occur disproportionately at GWAS loci (P = 0.013).

45 However, publicly available GWAS summary-level data are typically stored in differen

46 exome-guided GWAS (EG-GWAS) versus cHD-based GWAS.

47 5 x 10(-8) previously missed by HapMap-based GWAS.

48 nd strong evidence that associations between GWAS-identified SNPs and prostate cancer are modified by

49 This is the first bivariate GWAS meta-analysis to demonstrate genetic factors with p

50 at overlaps significantly with sets found by GWAS of age-related macular degeneration (P=1.4 x 10(-12

51 rpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed mi

52 Studies to date are small by GWAS standards, and cross-study comparisons are hampered

53 46522 in UBE2Z and SNP rs6725887 in WDR12 by GWAS, were found within the 17q21.2 and 2q33.3 loci.

54 n-depth analysis of the 7p21 locus linked by GWASs to frontotemporal lobar degeneration, nominating a

55 16,838 controls) and another two lung cancer GWASs of Harvard University (984 cases and 970 controls)

56 R-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negati

57 localization with variants identified in CKD GWASs, indicating that MANBA is a potential target gene

58 ypothesis generation and complements classic GWAS interpretation.

59 g ABA accumulation as a basis for a combined GWAS-reverse genetic strategy revealed the broad natural

60 In contrast, GWAS meta-analyses of two other brain diseases associate

61 teractors of the first three identified COPD GWAS genes IREB2, HHIP, and FAM13A, based on gene sets d

62 GB1, which interacts with AGER, a known COPD GWAS gene.

63 We applied our method to an in-depth GWAS of age-related macular degeneration with 33,976 ind

64 ined by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation be

65 The NHGRI-EBI GWAS Catalog has provided data from published genome-wid

66 d mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS.

67 disease-associated variants from an epilepsy GWAS meta-analysis and a febrile seizures (FS) GWAS are

68 Application of MR-MEGA to trans-ethnic GWAS of kidney function in 71,461 individuals indicates

69 ur findings show the utility of trans-ethnic GWASs for discovery and characterization of genetic loci

70 monstrate that scores inferred from European GWASs are biased by genetic drift in other populations e

71 In this largest-ever GWAS meta-analysis for nicotine dependence and the large

72 odontitis-associated variants using existing GWAS data from a German case-control sample of aggressiv

73 orating the summary statistics from existing GWASs of these two traits.

74 Here, the authors report the first GWAS of CP among a large community-based sample of Hispa

75 We report the first GWAS of offspring from preeclamptic pregnancies and disc

76 To our knowledge, this is the first GWAS to link stroke and autophagy.

77 eGenes provide great supporting evidence for GWAS hits and important insights into the regulatory pat

78 asyGWAS is also a public data repository for GWAS data and summary statistics and already includes pu

79 We performed a meta-analysis of four GWAS comprising three Chinese studies and one Malay stud

80 that interrelates starch structure data from GWAS to functional pathways from a gene regulatory netwo

81 he scale and complexity of genetic data from GWAS with time to event outcomes has not been extensivel

82 ize trait-relevant cell types and genes from GWAS summary statistics and gene expression data.

83 to 29 physical and mental health traits from GWAS consortia.

84 AS meta-analysis and a febrile seizures (FS) GWAS are significantly more enriched with epilepsy-eQTLs

85 power and mapping precision of exome-guided GWAS (EG-GWAS) versus cHD-based GWAS.

86 f microbial GWAS, and how lessons from human GWAS can direct the future of the field.

87 proinsulin processing observed at the human GWAS signal.

88 We argue that, similar to human GWASs, it is important to use functional genomics techni

89 y efficient and can meta-analyze one hundred GWASs in one day.

90 in synaptic transmission by (1) identifying GWAS schizophrenia variants whose associated gene functi

91 ludes three steps: (i) re-prioritize imaging GWAS findings by applying machine learning methods to in

92 Many of these clusters are associated in GWAS with multiple phenotypes.

93 and showed that these were more enriched in GWAS associations than other eQTLs.

94 richment for response than constant eQTLs in GWAS signals of several autoimmune diseases.

95 ariants from genome-wide significant loci in GWAS, using SOJO increased the proportion of variance pr

96 Most conventional statistical methods in GWAS only investigate one phenotype at a time.

97 wever, implementation of multilocus model in GWAS is still difficult.

98 f high-density lipoprotein (HDL), and 23% in GWASs of schizophrenia.

99 ith identified AH is 4%-23% in eQTLs, 35% in GWASs of high-density lipoprotein (HDL), and 23% in GWAS

100 ere tested for replication in an independent GWAS of 30 770 cases and 286 913 controls, followed by a

101 with 4 of these replicated in an independent GWAS: B4GALT3, USMG5, P2RY13, and P2RY14, which are gene

102 e 2 diabetes using data from six independent GWAS consortia and the UK Biobank sample (N = 112 151).

103 verage of RNA-Seq and performing integrative GWAS-eQTL analysis against gene, exon, and splice-juncti

104 To gain deeper quantitative insights into GWAS transferability, we developed a complex trait coale

105 corporates known functional information into GWASs can help elucidate the underlying biological mecha

106 tests that are performed and evaluate large GWAS data sets in a reasonable amount of computation tim

107 Analyses of such large GWAS datasets require a consideration of a number of sta

108 e selected variants, reported in the largest GWAS to date, associated with genes involved in synaptic

109 ed an R package rqt, which offers gene-level GWAS meta-analysis.

110 ublished data and results from several major GWAS.

111 After recalculating MDD PRS using MDD GWAS data sets without comorbid MDD-AD cases, significan

112 the current state of the field of microbial GWAS, and how lessons from human GWAS can direct the fut

113 Despite recent advances of modern GWAS methods, it is still remains an important problem o

114 n with empirical Bayes to perform multilocus GWAS under polygenic background control.

115 inally, we uncover reQTL effects in multiple GWAS loci and show a stronger enrichment for response th

116 Here the authors conduct a multivariate GWAS on IgG N-glycosylation phenotypes and identify 5 no

117 or: (i) further benchmarking of multivariate GWAS methods, (ii) power calculations for multivariate g

118 ritize and predict the function of noncoding GWAS SNPs have been developed.

119 rovides an opportunity to re-examine obesity GWAS data to begin elucidating the function of genetic v

120 However, fewer than 40% of GWAS publications from 2015 utilized these tools.

121 lication of graph-GPA to a joint analysis of GWAS datasets for 12 phenotypes shows that graph-GPA imp

122 studies with functional characterization of GWAS findings are warranted to assess the utility of gen

123 gene pairs based on statistical filtering of GWAS results, and text-mining filtering using Gene Relat

124 placental eQTLs may mediate the function of GWAS loci on postnatal disease susceptibility.

125 ythematosus (SLE) through the integration of GWAS and eQTL data from the TwinsUK microarray and RNA-S

126 prediction models and the interpretation of GWAS findings.

127 tions, we hope to help the interpretation of GWAS results and provide improved information for cancer

128 coding SNPs, which represent the majority of GWAS SNPs, present a particular challenge.

129 this Review, we outline the methodologies of GWAS, the current state of the field of microbial GWAS,

130 The number of GWAS catalog SNPs identified as eQTL in the conditional

131 k, graph-GPA, to integrate a large number of GWAS datasets for multiple phenotypes using a hidden Mar

132 atistical methods based on smaller number of GWAS datasets.

133 onal and clinical/behavioral significance of GWAS variants.

134 ndings provide support for the usefulness of GWAS data in guiding drug discovery.

135 e considered methods to integrate results of GWASs into GP models in the context of multiple intercon

136 the application of these methods in ongoing GWAS meta-analyses and large biobank studies.

137 ew also presents perspectives for optimizing GWAS design and analysis.

138 Our GWAS identified two known loci (TCF7L2 and KCNQ1) reachi

139 Our GWAS of the proportion of neurons identified two genome-

140 linkage disequilibrium (LD) and overlapping GWAS samples.

141 Here, we performed GWAS for a major subtype of stroke-small-vessel occlusio

142 Hence, we performed GWAS on 18 FAAs from a 313-ecotype Arabidopsis (Arabidop

143 its particular relevance to pharmacogenetic GWAS, SurvivalGWAS_SV will aid in the identification of

144 The post-GWAS era provides an opportunity for cross-phenotype ana

145 that, in schizophrenia, current well-powered GWAS results can reliably detect known schizophrenia dru

146 is financially prohibitive for well-powered GWAS studies.

147 A previous GWAS performed in 300 renal transplant recipients identi

148 risk-associated SNPs identified in previous GWAS studies, we identify 575 SNPs in the fragments that

149 Our primary GWAS meta-analysis identified two novel SNP loci (top SN

150 Using published GWAS datasets with 39,165 single-nucleotide polymorphism

151 our eQTL database in the context of a recent GWAS meta-analysis of coronary artery disease and provid

152 A recent GWAS on 43,566 subjects identified novel loci and pathwa

153 Our approach requires GWAS summary data only and makes no distributional assum

154 ize genes for >40 complex traits with robust GWAS data and found considerable overlap with the result

155 d the hypotheses that, in a very large scale GWAS, we would identify more genetic variants associated

156 ry and valuable for facilitating large-scale GWAS in populations of African ancestry.

157 as not been reported in previous large-scale GWAS of lipid traits.

158 summary association data from a large-scale GWAS of lipids and show that these improvements are larg

159 Integrating large-scale GWAS with regional proteome data identifies the same cor

160 s that summarizing findings from large-scale GWASs may have limited portability to other populations

161 haloperidol-regulated genes in schizophrenia GWAS loci and in schizophrenia-associated biological pat

162 SNPs at 1p22, a locus identified in several GWAS for non-syndromic cleft lip with or without cleft p

163 - or pathway-level by mining existing single GWAS or meta-analyzed GWAS data.

164 ontrast, 4 SNPs were found based on standard GWAS analysis (P < 5 x 10(-8)).

165 analysis of genome-wide association studies (GWAS) across diverse populations can increase power to d

166 twork-based genome-wide association studies (GWAS) aim to identify functional modules from biological

167 onventional genome-wide association studies (GWAS) and the distance correlation sure independence scr

168 entified by genome-wide association studies (GWAS) as a novel regulator of cholesterol metabolism in

169 Genome-wide association studies (GWAS) can serve as strong evidence in correlating biolog

170 ated in the genome-wide association studies (GWAS) catalog.

171 d Caucasian genome-wide association studies (GWAS) data from two of the largest ASD family cohorts, t

172 scores from genome-wide association studies (GWAS) for 127 traits and diseases, and used these to dis

173 Genome-wide association studies (GWAS) for BMI, waist-to-hip ratio, and other adiposity t

174 analysis of genome-wide association studies (GWAS) for psoriasis to date, including data from eight d

175 Genome-wide association studies (GWAS) for schizophrenia have identified over 100 loci en

176 , including genome-wide association studies (GWAS) have accelerated the discovery of genes contributi

177 Multilocus genome-wide association studies (GWAS) have become the state-of-the-art procedure to iden

178 Genome-wide association studies (GWAS) have been successful at identifying associations w

179 ast decade, genome-wide association studies (GWAS) have been used to successfully identify tens of th

180 Recent genome-wide association studies (GWAS) have confirmed known risk mutations for venous thr

181 and recent genome-wide association studies (GWAS) have enabled a deeper understanding of the complex

182 ast decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, r

183 analyses of genome-wide association studies (GWAS) have identified >175 loci associated with fasting

184 Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI

185 Previous genome-wide association studies (GWAS) have identified 18 HbA1c-associated genetic varian

186 Recent genome-wide association studies (GWAS) have identified multiple loci associated with coro

187 Genome-wide association studies (GWAS) have identified multiple, shared allelic associati

188 Previous genome-wide association studies (GWAS) have identified six risk loci for renal cell carci

189 Genome-wide association studies (GWAS) have identified thousands of regions in the genome

190 Genome-wide association studies (GWAS) have not identified maternal sequence variants of

191 Genome-wide association studies (GWAS) have played an important role in identifying genet

192 g data from genome-wide association studies (GWAS) have provided a collection of novel candidate gene

193 Genome-wide association studies (GWAS) have transformed our understanding of glioma susce

194 Genome-wide association studies (GWAS) identify 5311 expression quantitative trait loci (

195 -chip based genome-wide association studies (GWAS) in 2158 cases from nine populations of European or

196 The genome-wide association studies (GWAS) included 17,931 individuals with atrial fibrillati

197 x published genome-wide association studies (GWAS) of 12,160 cases and 16,838 controls.

198 erogeneity, genome-wide association studies (GWAS) of chronic periodontitis (CP) have been unsuccessf

199 ied through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive d

200 Most genome-wide association studies (GWAS) of QT were performed in European ancestral populat

201 Genome-wide association studies (GWAS) of single nucleotide polymorphisms (SNPs) have bee

202 Few genome-wide association studies (GWAS) of type 2 diabetes (T2D) have been conducted in U.

203 Genome-wide association studies (GWAS) on FTD identified only a few risk loci.

204 g data from Genome-Wide Association Studies (GWAS) provide insights into the interplay among multiple

205 ave powered genome-wide association studies (GWAS) that have mapped nearly 450 genetic risk loci in 2

206 nalysis and genome-wide association studies (GWAS) using the MAGIC population suggests that omega-6 d

207 Analysis of genome-wide association studies (GWAS) with "time to event" outcomes have become increasi

208 Genome-wide association studies (GWAS) with intermediate phenotypes, like changes in meta

209 m conducted genome-wide association studies (GWAS) with standard multi-study analytical methodology a

210 (SNP)-based genome-wide association studies (GWAS) would identify groups of patients of differing com

211 nts through genome wide association studies (GWAS), genetic risk prediction accuracy remains moderate

212 mparison to genome-wide association studies (GWAS), there has been poor replication of gene expressio

213 etail using genome-wide association studies (GWAS).

214 entified in genome-wide association studies (GWAS).

215 measure in genome-wide association studies (GWAS).

216 f microbial genome-wide association studies (GWAS).

217 uggested by genome-wide association studies (GWAS).

218 rom genome-wide association mapping studies (GWAS) along with the development of new population genet

219 discuss how genome-wide association studies (GWASs) and recent developments in islet (epi)genome and

220 entified by genome-wide association studies (GWASs) and specific environmental exposures, controlling

221 Recent Genome-wide Association Studies (GWASs) for eye diseases/traits have delivered a number o

222 Genome-wide association studies (GWASs) have been performed extensively in diverse popula

223 Genome-wide association studies (GWASs) have identified a multitude of genetic loci invol

224 Genome-wide association studies (GWASs) have identified sequence variants, localized to n

225 analysis of genome-wide association studies (GWASs) identified multiple bone mineral density (BMD) an

226 Genome-wide association studies (GWASs) implicate the PHACTR1 locus (6p24) in risk for fi

227 by previous genome-wide association studies (GWASs) in Europeans only.

228 l design of genome-wide association studies (GWASs) is now 10 years old (young), and here we review t

229 uccesses in genome-wide association studies (GWASs) make it possible to address important questions a

230 entified in genome-wide association studies (GWASs) of complex traits are thought to act by affecting

231 x published genome-wide association studies (GWASs) of Transdisciplinary Research in Cancer of the Lu

232 he power of genome-wide association studies (GWASs) to identify risk-associated variants are needed.

233 analysis in genome-wide association studies (GWASs), conditional and joint multiple-SNP analysis (GCT

234 scovered in genome-wide association studies (GWASs), is to estimate individual-specific genetic prope

235 an aggregated genome-wide association study (GWAS) analysis of lung cancer in 29,266 cases and 56,450

236 Genome-wide association study (GWAS) has become a widely accepted strategy for decoding

237 The initial genome-wide association study (GWAS) included 174 Finnish preterm infants of gestationa

238 comprehensive genome-wide association study (GWAS) including low-frequency variants (minor allele fre

239 ely 680 known genome-wide association study (GWAS) loci for cardio-metabolic traits, we identified 14

240 m a recent CF genome-wide association study (GWAS) meta-analysis to determine modulators of ER stress

241 scovery using genome-wide association study (GWAS) methods.

242 we perform a genome-wide association study (GWAS) of 33,536 individuals and discover six independent

243 e undertook a genome-wide association study (GWAS) of 6,337 AF individuals and 61,607 AF-free individ

244 e conducted a genome-wide association study (GWAS) of alcohol consumption in the large Genetic Epidem

245 fied through a genomewide association study (GWAS) of debranched starch structure from grains of a 32

246 carried out a genome-wide association study (GWAS) of responses to the question, 'Over the last two w

247 n our initial genome-wide association study (GWAS) on esophageal squamous cell carcinoma (ESCC) in Ha

248 e performed a genome-wide association study (GWAS) on resting-state fast beta EEG power.

249 erity, using a genomewide association study (GWAS) on the slope of BHR in adult asthmatics.

250 A genome-wide association study (GWAS) predicted additional modifier genes.

251 ailability of genome-wide association study (GWAS) results and national biobank data has led to growi

252 e majority of genome-wide association study (GWAS) risk variants reside in non-coding DNA sequences.

253 e performed a genome-wide association study (GWAS) that included 8,180 atrial fibrillation cases and

254 t of a recent genome wide association study (GWAS) to identify novel loci that alter the expression o

255 e conducted a genome-wide association study (GWAS) with replication in 36,180 Chinese individuals and

256 n contrast to genome-wide association study (GWAS), genomic prediction (GP) is typically based on mod

257 orphism (SNP) genome-wide association study (GWAS), the selection of related gene pairs based on stat

258 case-control genome-wide association study (GWAS), we did a genome-wide scan of gallbladder cancer c

259 acial/ethnic, genome-wide association study (GWAS).

260 34 loci in a genome-wide association study (GWAS).

261 s in the post-genome-wide-association-study (GWAS) era.

262 ments from 45 expression panels with summary GWAS data to perform 30 multi-tissue transcriptome-wide

263 ieve disease-associated reference genes than GWAS could alone.

264 These analyses indicate that GWAS of single heritable features of genetically complex

265 The GWAS uncovered five and 32 significant SNPs for SET, and

266 h lies outside the main TAD encompassing the GWAS signal.

267 ent in genome-wide significant SNPs from the GWAS catalog, and are also more likely to be tissue spec

268 s candidate disease genes by integrating the GWAS and network data.

269 ide the detailed molecular mechanisms of the GWAS association for serum acylcarnitines at the SLC22A1

270 cation cohort and did a meta-analysis of the GWAS discovery and replication sets to get combined esti

271 ies have investigated the association of the GWAS-identified SNPs with BC risk in Indian population.

272 ding RNA (lncRNA) LINC00305 by searching the GWAS database.

273 Applying this approach to the GWAS summary statistics of putamen volume in the ENIGMA

274 otypically relevant epigenomes to weight the GWAS single-nucleotide polymorphisms, we improve the sta

275 the reference panel needs to scale with the GWAS sample size; this has important consequences for th

276 ions for the association of the SNP with the GWAS-related phenotype.

277 Despite this, GWASs alone are unable to pinpoint disease-causing singl

278 In the discovery stage, we combined three GWAS datasets (EU-RLS GENE, INTERVAL, and 23andMe) with

279 ighlight the inherent value in sub-threshold GWAS associations, which are often not publicly released

280 The methods are generally applicable to GWAS data and are not specific to radiotherapy endpoints

281 The traditional approach to GWAS analysis is to consider each phenotype separately,

282 y phenotype-relevant modules enriched by top GWAS findings.

283 biological networks that are enriched by top GWAS findings.

284 e of the relative performance of multi-trait GWAS methods and act as a guide for method selection.

285 Numerous multi-trait GWAS methods that exploit either summary statistics or i

286 g that genetic variation identified by trait GWASs partially captures environmental risk factors or p

287 Application of SCOPA to two GWAS of high-and low-density lipoprotein cholesterol, tr

288 Here, we used GWAS to explore whether single nucleotide polymorphisms

289 Using GWAS summary statistics (P-values) for SNPs along with r

290 pathway analysis and drug repurposing using GWAS results.

291 s harboring 11q deletion (rs10895322), using GWAS in 113 European-American cases and 5109 ancestry-ma

292 AnnoPred is trained using GWAS summary statistics in a Bayesian framework in which

293 fied genetic covariance between traits using GWAS summary statistics.

294 e these barriers, the current study utilized GWAS meta-analysis to examine the association of common

295 we show that most haplotypes associated with GWAS or eQTL phenotypes are located outside of DNase-seq

296 of variable DNA methylation associated with GWAS variants for a range of complex traits, demonstrati

297 Of those, we found 65 associations with GWAS traits and provide examples in which genes implicat

298 kin cancers are also being investigated with GWAS.

299 variants in linkage disequilibrium (LD) with GWAS identified SU/gout associated variants were analyze

300 association analysis of multiple traits with GWAS summary statistics.