ライフサイエンスコーパス: disease gene

1 guous truncating mutations of an established disease gene.

2 tients, suggesting that HPSE2 is a candidate disease gene.

3 ultiple DSBR pathways at a single endogenous disease gene.

4 encing is a useful technique for finding the disease gene.

5 , which encodes titin, is also a major human disease gene.

6 mal function of a gene define that gene as a disease gene.

7 , a known split-hand/split-foot malformation disease gene.

8 inding, and allowed interrogation of posited disease genes.

9 r amino acid changing variants and Mendelian disease genes.

10 nd broadened the clinical phenotype of known disease genes.

11 riants from background missense variation in disease genes.

12 unction and identify new pathway members and disease genes.

13 d effectively in the prediction of candidate disease genes.

14 trol through mapping of and visualization of disease genes.

15 diseases, even if they do not share primary disease genes.

16 ined by mutations in known ECM or glomerular disease genes.

17 n metabolites and diseases through annotated disease genes.

18 xpected presentations for mutations in known disease genes.

19 ecific, patient-derived alleles of candidate disease genes.

20 an effective strategy for identifying human disease genes.

21 glucoregulatory, inflammatory, and vascular disease genes.

22 ier deletions affecting 419 unique recessive disease genes.

23 may be used to predict additional candidate disease genes.

24 iology and facilitate the discovery of renal disease genes.

25 letions encompassing or disrupting recessive disease genes.

26 ants, about 96.1% lower than other Mendelian disease genes.

27 ants that are more likely to pinpoint causal disease genes.

28 lung, including hundreds of drug targets and disease genes.

29 latory regions controlling cell identity and disease genes.

30 exts facilitates identification of candidate disease genes.

31 ified causative mutations in currently known disease genes.

32 ients who lack exonic mutations in the known disease genes.

33 variants identified among a growing list of disease genes.

34 egulates the transcription of several cystic disease genes.

35 n-disease-associated variants) from 22 human disease genes.

36 rch and prioritising candidate mitochondrial disease genes.

37 effects was associated with known metabolic disease genes.

38 letions encompassing more than one recessive disease gene (206 deletions).

39 ntification of 45 novel variants in 43 known disease genes, 41 candidate genes, and CNVs in 10 famili

40 ver deleted in our cohort, the 419 recessive disease genes affected by at least one carrier deletion

41 ession proximity between candidate and known disease genes allowed for further understanding of genet

42 selected tissues, the expression patterns of disease genes alone cannot explain the observed tissue s

43 The Parkinson's disease gene alpha-synuclein (SNCA) is selectively expre

44 PLEKHM2 joins LAMP-2 and BAG3 as a disease gene altering autophagy resulting in an isolated

45 l ASD associated with biallelic mutations in disease genes (AMT, PEX7, SYNE1, VPS13B, PAH, and POMGNT

46 derstand the role of EMP2 in the etiology of disease, gene analysis was performed to show transcripts

47 om 29 public resources to connect compounds, diseases, genes, anatomies, pathways, biological process

48 entify NONO as a possible neurodevelopmental disease gene and highlight the key role of the DBHS prot

49 of pathogenic variants in autosomal dominant disease genes and 51.7% (15 of 29) of pathogenic variant

50 fferences between LoF-tolerant and recessive disease genes and a method for using these differences t

51 complex relationships among drugs, targets, disease genes and diseases at a system level.

52 uggests its usefulness in discovery of novel disease genes and dissection of disease pathways.

53 lenge to interpret such data for identifying disease genes and drug targets.

54 to the identification of many new causative disease genes and functional studies have clarified thei

55 lized in a small network neighborhood of the disease genes and highlights efficacy issues for drugs u

56 solution that maximizes the coverage on the disease genes and minimizes the off-target hits at the s

57 We replicated novel SCZ disease genes and pathogenic pathways.

58 already led to tangible discoveries of novel disease genes and pathways as well as improved mechanism

59 analysis is very useful in identifying novel disease genes and potential drug targets.

60 Finally, disease genes and protein complexes have the tendency to

61 We identified known disease genes and their protein complex partners in a hi

62 use [essential genes (EGs)] are enriched for disease genes and under strong purifying selection relat

63 iants that may unmask dispensable regions of disease genes and unrecognized false positives in diagno

64 variant and discover previously unrecognized disease genes and variants while keeping up to 99.7% of

65 ng protein-protein interaction, drug-target, disease-gene and signaling pathways among various cells

66 sing an interactome-based extension of known disease-genes and introduce several measures of function

67 alyze TFs that bind to regulatory regions of diseased genes and regulate their expression.

68 ification of new risk factors, new candidate disease genes, and a better understanding of the molecul

69 ignificant connections between gene sets and disease genes, and apply it to several gene sets related

70 s, functionally annotate genetic variants of disease genes, and inform clinical trials.

71 TASTPM', transgenic for familial Alzheimer's disease genes APP/PSEN1).

72 utilizing network information to prioritize disease genes are based on the 'guilt by association' pr

73 as more cardiomyopathy and congenital heart disease genes are discovered, giving researchers a power

74 In addition, we show that human disease genes are enriched for essential genes, thus pro

75 Although some disease genes are expressed only in selected tissues, th

76 terogeneous, and many, possibly most, of the disease genes are still unknown.

77 Of 1305 human disease genes assayed, 20 genes exhibited strong toxicit

78 The roles of disease genes associated with AD, most importantly the p

79 nding of the range of disease phenotypes and disease genes associated with deficiencies of the GPI-an

80 ith cardiovascular disease as well as unique disease genes associated with inflammatory processes.

81 nalysed and compared four publicly available disease-gene association datasets, then applied three di

82 as an intuitive and versatile method to aid disease-gene association, which naturally lends itself t

83 n the uncertainty of the underlying disorder-disease gene associations contained in the OMIM, on whic

84 vantage of diverse biological data including disease-gene associations and a large-scale molecular ne

85 0 provides an expanded comprehensive list of disease-gene associations based on manual curation from

86 ed methodology is extended to discover novel disease-gene associations by including valuable domain k

87 the number of diseases from 72 to 88 and the disease-gene associations from 216 201 to 679 602.

88 ues and tissue-specific networks to identify disease-gene associations more accurately than GWAS alon

89 ther identify candidate gene lists for which disease-gene associations were not studied previously.

90 < 0.05) is observable for ~67% of 4,549 OMIM disease-gene associations, using a combination of high q

91 tion, with scores reflecting the strength of disease-gene associations.

92 ng roles of genes across tissues and uncover disease-gene associations.

93 ex traits increased the number of associated disease genes at a 5% false discovery rate by an average

94 As in other common diseases, genes at COPD GWAS loci were not differentiall

95 failed to identify mutations in the Wilson's disease gene ATP7B in a significant number of clinically

96 thods for prioritizing Mendelian and complex disease genes, based on disease or phenotype terms enter

97 nes; however, the framework is applicable to disease genes beyond epilepsy.

98 15 of 29) of pathogenic variants in X-linked disease genes; both variants were de novo in 44.7% (17 o

99 cation (p.Trp1088Leufs*16) confirmed AHI1 as disease gene, but based on a more N-terminal missense mu

100 first reported skeletal muscle K(+) channel disease gene, but the requirement for KCNE3 in skeletal

101 ental rare variants in established Mendelian disease genes, but the frequency of related clinical phe

102 Detecting mutations in disease genes by full gene sequence analysis is common i

103 se of interest, GWAB reprioritizes candidate disease genes by integrating the GWAS and network data.

104 ods have been developed to predict potential disease genes by utilizing the disease similarity networ

105 Many new disease genes can be identified through high-throughput

106 Studies in Huntington's disease gene carriers suggest that alterations in the el

107 cohort of 12 early premanifest Huntington's disease gene carriers with a mean estimated 90% probabil

108 DE10A expression in premanifest Huntington's disease gene carriers, which are associated with the pro

109 survival and improve outcome in Huntington's disease gene carriers.

110 conversion in early premanifest Huntington's disease gene carriers.

111 Our study therefore identifies POPDC1 as a disease gene causing a very rare autosomal recessive car

112 eterious variants in essential and Mendelian disease genes compared to African Americans, consistent

113 n Online Mendelian Inheritance in Man (OMIM) disease genes compared with Africans, Latinos, South Asi

114 significantly across molecular pathways, and disease genes contained a significantly higher proportio

115 e explored intrasplicing in other normal and disease gene contexts and found conservation of intraspl

116 ncogenesis and genome engineering, including disease gene correction.

117 he Online Mendelian Inheritance in Man human disease gene database.

118 nosed Diseases Program, nominating 60% of 30 disease genes determined to be diagnostic by a standard

119 one of two autosomal dominant cystic kidney disease genes, did not show increased risk of developmen

120 as an active area of research for both novel disease gene discovery and drug repositioning.

121 as an active area of research for both novel disease gene discovery and drug repurposing.

122 tial of this newly created knowledge base in disease gene discovery and drug repurposing.

123 using WES data; this tool can be useful for disease gene discovery efforts and clinical WES analyses

124 Our approach may substantially improve disease gene discovery for diseases with many known risk

125 ome a de facto standard method for Mendelian disease gene discovery in recent years, yet identifying

126 y discusses the power of exome sequencing in disease gene discovery within the rare genodermatoses an

127 Here, we review recent developments in disease gene discovery, functional characterization, and

128 ilarities to improve the prediction power of disease gene discovery.

129 of applications in population inference and disease gene discovery.

130 S) provides a powerful new tool for familial disease gene discovery.

131 encing is a powerful technique for Mendelian disease gene discovery.

132 s and whole exome sequencing can be used for disease gene discovery.

133 ocular tissue components will facilitate eye disease gene discovery.

134 neration sequencing (NGS) projects for novel disease-gene discovery or differential diagnostics of Me

135 Using data from Mendelian disease-gene discovery projects, we show that ALoFT can

136 n that can be used to prioritize variants in disease-gene discovery.

137 litate the development of new approaches for disease-gene discovery.

138 Other Mendelian disease genes encode proteins essential for ion channel

139 endogenous reporter gene, the X-chromosomal disease gene encoding hypoxanthine phosphoribosyltransfe

140 error rate and power, depends on underlying disease-gene-environment associations, estimates of whic

141 risk factors and obtaining insight into the disease-gene-environment relationship.

142 Vs combined with the large number of retinal disease genes exceeding that capacity make the developme

143 vel missense variants in recently discovered disease genes exhibiting genetic heterogeneity, by combi

144 ionality and small size of available complex disease gene expression datasets currently used for disc

145 Disease gene expression profiles can be utilized as biom

146 or Cytoscape, for the comparison of drug and disease gene expression profiles from public microarray

147 mouse model expressing the full human ATXN3 disease gene, expression of this alternatively spliced t

148 marking using known disease variants from 88 disease-gene families reveals that the correct gene is r

149 These results define LMOD1 as a disease gene for MMIHS and suggest its role in establish

150 We identified PIEZO1 as the disease gene for pleiotropic DHSt in a large kindred by

151 sibling pair, targeted testing of the known disease gene for Roifman syndrome (RNU4ATAC) provided a

152 rmin network was significantly enriched with disease genes for both T2D and cancer, and that the netw

153 In the proband, 48 disease genes for HCM, selected on the basis of publishe

154 Variants in SCN5A and KCNH2, disease genes for long QT and Brugada syndromes, were as

155 in the embryonic limb buds and ectoderm, are disease genes for these conditions.

156 fy putative pathogenic variants in candidate disease genes for tooth agenesis in 10 multiplex Turkish

157 d phenotype information may help to identify disease genes from human whole-genome and whole-exome se

158 rs has the potential to rapidly identify new disease genes (genes in which mutations cause disease),

159 s have been applied successfully to identify disease genes, genetic modules and drug targets.

160 More than one-third of these disease genes have been characterized in the past 5 year

161 Over 1200 recessive disease genes have been described in humans.

162 Although tools to prioritize candidate disease genes have been developed, the great majority of

163 Although a number of disease genes have been identified for CMT, the gene dis

164 ion underlie FSGS; however, highly penetrant disease genes have been identified in a small fraction o

165 New disease genes have been identified through whole exome s

166 A total of 17 FA disease genes have been reported, all of which act in a

167 y result in biases, showing that age-related disease genes have faster molecular evolution rates and

168 The CAG repeat expansion in the Huntington's disease gene HTT extends a polyglutamine tract in mutant

169 normal development as an integral part of a disease gene identification and prioritization strategy

170 monstrate the utility of exome sequencing in disease gene identification despite the combined complex

171 This complicates disease-gene identification and efforts to understand th

172 Disease-gene identification is a challenging process tha

173 Here we present pedigree-VAAST (pVAAST), a disease-gene identification tool designed for high-throu

174 as a valuable resource to validate potential disease genes identified by GWAS in human cell lines and

175 -based functional system to screen candidate disease genes identified from Congenital Heart Disease (

176 n vivo validation system to screen candidate disease genes identified from patients.

177 ch we confirmed using a prospective study of disease genes identified in 2012 and PPA data produced b

178 Diagnostic analysis of established disease genes identified pathogenic variants in 21.8% of

179 es from transgenic mice expressing the human disease gene, identified the atypical antipsychotic arip

180 Identifying disease genes implicated in late-onset neurodegenerative

181 We aim to identify the disease gene in a large 3-generation family (n=25) with

182 previously identified GALNT11 as a candidate disease gene in a patient with heterotaxy, and now demon

183 and a repair template to induce repair of a disease gene in adult animals.

184 nt in animals, but whether Piwi is an actual disease gene in human infertility remains unknown.

185 ed personal disease histories with causative disease genes in 18 volunteers.

186 screened mutations in over 200 known retinal disease genes in a cohort of 12 unrelated Uyghur IRD pro

187 To empower the search for Mendelian-disease genes in family-based sequencing studies, we imp

188 a powerful tool for rapid analysis of known disease genes in large patient cohorts.

189 heard of possibilities for identifying novel disease genes in Mendelian disorders, only about half of

190 ological connections between aging genes and disease genes in over three thousand subnetworks corresp

191 is a valuable tool to help prioritize novel disease genes in sequence interpretation.

192 signed, which incorporated 195 known retinal disease genes, including 61 known RP genes.

193 -1beta regulates the transcription of cystic disease genes, including Pkd2 and Pkhd1.

194 sociation studies-identified coronary artery disease genes, including PPAP2B, participate in mechanot

195 ease annotations, placing numerous candidate disease genes into a cellular framework.

196 fied by en masse transformation of the human disease genes into a pool of 4653 homozygous diploid yea

197 tribute to a more complete identification of disease genes involved in cardiomyopathy.

198 Accurately prioritizing candidate disease genes is an important and challenging problem.

199 t of sequencing and the ongoing discovery of disease genes, it is now possible to examine hundreds of

200 zygous variants on chromosome X in two known disease genes, L1CAM and PAK3, and in two novel candidat

201 Parkinson's disease gene leucine-rich repeat kinase 2 (LRRK2) has be

202 argement, suggesting a role for the putative disease gene LIX1 in radial growth of axons.

203 ciated with incomplete coverage of inherited disease genes, low reproducibility of detection of genet

204 y (critical for the delivery of large ocular disease genes) make their further development a research

205 The disease gene mapped to a less than 2-megabase recessive

206 s' genomes is useful in studies ranging from disease gene mapping to speciation genetics.

207 Clinical diagnosis of CORD, disease gene mapping, and mutation identification.

208 y evolving loci, and be an important tool in disease gene mapping.

209 3 M patients from the Medicare database with disease-gene maps that we derived from several resources

210 Results suggest that Ashkenazi-associated disease genes may be components of population-specific g

211 As clinically significant disease genes may be subject to negative selection, we d

212 zygous deletions spanning multiple recessive disease genes may confer carrier status for multiple sin

213 The disease gene median rank was 22.

214 ls and patients, this principle assumes that disease genes more likely undergo rewiring in patients,

215 duals in the TRACK-HD cohort of Huntington's disease gene mutation carriers (data collected 2008-11).

216 dding new arenas in which neurodevelopmental disease gene mutation could disrupt corticogenesis.

217 ation sequencing assay for detecting cardiac disease gene mutations with improved accuracy, flexibili

218 ough yielding few, usually highly penetrant, disease gene mutations, these discoveries provided 3 not

219 ilico analysis of the architecture of the PH disease gene network coupled with molecular experimentat

220 t into the systems-level regulation of miRNA-disease gene networks in PH with broad implications for

221 s based on shared systems of disease and non-disease gene networks may have broad implications for fu

222 When compared with recessive disease genes never deleted in our cohort, the 419 reces

223 d the gene set enrichment analysis using the disease genes of type 2 diabetes (T2D) and cancer, one T

224 Direct sequencing of all retinal disease genes on chromosome 6 revealed a novel pathogeni

225 no mutations were detected in other retinal disease genes on chromosome 6.

226 etic defects such as loss of the Parkinson's disease genes Pink or Parkin in Drosophila.

227 tes that two autosomal recessive Parkinson's disease genes, PINK1 (PARK6) and Parkin (PARK2), coopera

228 Knockout of the polycystic kidney disease genes PKD1 or PKD2 induces cyst formation from k

229 d-2 (homologs of the human polycystic kidney disease genes, PKD1 and PKD2), which are expressed in ma

230 in the autosomal recessive polycystic kidney disease gene PKHD1, indicating that adult PKHD1 carriers

231 filing from healthy human brain to develop a disease gene prediction model and this generic methodolo

232 hich was a widely used phenotype database in disease gene prediction studies.

233 d the impact of mutations affecting AP1S3, a disease gene previously identified by our group and vali

234 vealed de novo dominant mutations, validated disease genes previously described in isolated families,

235 are our methods with 7 popular network-based disease gene prioritization algorithms on diseases from

236 sue-specific molecular networks for studying disease gene prioritization and show the superiority of

237 ed inference traditionally used in candidate disease gene prioritization applications with experiment

238 In this manuscript, we present a method for disease gene prioritization based on comparing phenotype

239 iology, with protein function prediction and disease gene prioritization gaining wide recognition.

240 applications in protein function prediction, disease gene prioritization, and patient stratification.

241 applications include functional annotation, disease gene prioritization, comparative analysis of bio

242 grate tissue-specific molecular networks for disease gene prioritization.

243 s coupled to the co-recruitment of FMRP, the disease gene product in fragile X mental retardation syn

244 ncing has accelerated the discovery of human disease genes, progress has been largely limited to the

245 in mice also display altered splicing of the disease gene, promoting expression of an alternative iso

246 ession information and organized knowledge - disease gene/protein network topology information, which

247 named entities including Anatomy, Chemical, Disease, Gene/Protein and Species.

248 volutionized the use of genetics to identify disease genes, provide insights into human evolution, an

249 ods that screen on the basis of the marginal disease-gene relationship are more robust to exposure mi

250 Most existing methods for predicting causal disease genes rely on specific type of evidence, and are

251 Still, thousands of childhood disease genes remain to be identified, and given their i

252 of the positive cases harbored mutations in disease genes reported since 2011.

253 Functional characterization of the disease gene revealed that nonmutant protein encoded by

254 nal testing of this model on two known human disease genes revealed discrete cis amino acid residues

255 ison of aging-related genes with age-related disease genes reveals species-specific effects with stro

256 MOTSC seeks a full coverage on the disease gene set while minimizing the off-target set.

257 Given a disease gene set, BTSC seeks a balanced solution that ma

258 d measure of closeness between the query and disease gene sets capable of detecting associations unde

259 When applied to real disease gene sets, our algorithms not only identified kn

260 The aging gene signatures and complex disease genes show a complex overlapping pattern and onl

261 ay the downstream genes of drug targets with disease gene signatures to display the potential therape

262 To develop broader clinical relevance from disease gene signatures, Inkeles et al. demonstrate how

263 otor neuron protein, the main product of the disease gene SMN1.

264 y and decreased expression of several cystic disease genes, some of which we identified as novel Hnf1

265 an ENS due to a mutation in the Hirschsprung disease gene, sox10, develop microbiota-dependent inflam

266 nifest carriers of the abnormal Huntington's disease gene (subjects with pre-manifest Huntington's di

267 richment Analysis, Gene Ontology Enrichment, Disease-Gene Subnetwork Compactness), we show that our p

268 icity is increased in neurons that express a disease gene, such as mutant FUS or TDP-43.

269 nger and located farther from known dominant disease genes, suggesting that the formation and/or prev

270 se of dominantly inherited neurodegenerative diseases, gene suppression strategies can target the und

271 factor MEF2C and the human congenital heart disease gene TDGF1.

272 ch nonspecific risk by identifying Mendelian disease genes that are associated with multiple diseases

273 Moreover, the disease genes that overlap these two innate immunity pat

274 sequencing facilitates the identification of disease genes, the large number of detected genetic vari

275 isease and drug hierarchies; (ii) integrated disease-gene, therapy-drug and drug-target association t

276 ly of computational techniques for inferring disease genes through a set of training genes and carefu

277 To promote the identification of disease genes through confirmation of previously describ

278 ation between the counts of links connecting disease genes through PPI and links connecting diseases

279 gorithm for ranking phenolog-based candidate disease genes through the integration of predictions fro

280 sease genes through PPI and links connecting diseases genes through FANs, separating diseases into tw

281 h that is discovering the mechanisms linking disease genes to epilepsy syndromes.

282 human limb-girdle muscular dystrophy type 2H disease gene Trim32.

283 ovo mutations in three previously identified disease genes (TUBA1A (n=2), SCN8A (n=1) and KDM5C (n=1)

284 ment to the state of the art for curation of disease-gene-variant relationships.

285 We extract disease-gene-variant triplets from all abstracts in PubM

286 rning approach to automate the extraction of disease-gene-variant triplets from biomedical literature

287 iseases, our approach returned 272 triplets (disease-gene-variant) that overlapped with entries in Un

288 novel mutations in 4 possible mitochondrial disease genes (VARS2, GARS, FLAD1, and PTCD1).

289 tween cellular targets of viral proteins and disease genes was exploited to uncover a novel pathway l

290 To identify new disease genes, we performed whole-exome sequencing of 26

291 Eighty-nine cardiac disease genes were evaluated.

292 sequencing platform, 10% to 19% of inherited disease genes were not covered to accepted standards for

293 Mutations in non-cancer-related Mendelian disease genes were seen in 55 of 1566 cases (3.5%; 95% C

294 l for creating a targeted panel of potential disease genes while supporting different forms of input.

295 The X-chromosome harbors hundreds of disease genes whose associated diseases predominantly af

296 leterious and whether they occurred in known disease genes whose clinical spectrum overlaps CP.

297 e receptor RET represents the most important disease gene, whose mutations account for half of the fa

298 ases, there is compelling evidence that many disease genes will map to a much smaller number of biolo

299 Its proximity to a disease gene with numerous founder mutations, BRCA1, wit

300 stematic study of the expression patterns of disease genes within the human interactome.