Other search tools

About this data

The publication data currently available has been vetted by Vanderbilt faculty, staff, administrators and trainees. The data itself is retrieved directly from NCBI's PubMed and is automatically updated on a weekly basis to ensure accuracy and completeness.

If you have any questions or comments, please contact us.

Results: 1 to 10 of 16

Publication Record

Connections

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus.
Lawrenson K, Kar S, McCue K, Kuchenbaeker K, Michailidou K, Tyrer J, Beesley J, Ramus SJ, Li Q, Delgado MK, Lee JM, Aittomäki K, Andrulis IL, Anton-Culver H, Arndt V, Arun BK, Arver B, Bandera EV, Barile M, Barkardottir RB, Barrowdale D, Beckmann MW, Benitez J, Berchuck A, Bisogna M, Bjorge L, Blomqvist C, Blot W, Bogdanova N, Bojesen A, Bojesen SE, Bolla MK, Bonanni B, Børresen-Dale AL, Brauch H, Brennan P, Brenner H, Bruinsma F, Brunet J, Buhari SA, Burwinkel B, Butzow R, Buys SS, Cai Q, Caldes T, Campbell I, Canniotto R, Chang-Claude J, Chiquette J, Choi JY, Claes KB, GEMO Study Collaborators, Cook LS, Cox A, Cramer DW, Cross SS, Cybulski C, Czene K, Daly MB, Damiola F, Dansonka-Mieszkowska A, Darabi H, Dennis J, Devilee P, Diez O, Doherty JA, Domchek SM, Dorfling CM, Dörk T, Dumont M, Ehrencrona H, Ejlertsen B, Ellis S, EMBRACE, Engel C, Lee E, Evans DG, Fasching PA, Feliubadalo L, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Foretova L, Fostira F, Foulkes WD, Fridley BL, Friedman E, Frost D, Gambino G, Ganz PA, Garber J, García-Closas M, Gentry-Maharaj A, Ghoussaini M, Giles GG, Glasspool R, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Goode EL, Goodman MT, Greene MH, Gronwald J, Guénel P, Haiman CA, Hall P, Hallberg E, Hamann U, Hansen TV, Harrington PA, Hartman M, Hassan N, Healey S, Hereditary Breast and Ovarian Cancer Research Group Netherlands (HEBON), Heitz F, Herzog J, Høgdall E, Høgdall CK, Hogervorst FB, Hollestelle A, Hopper JL, Hulick PJ, Huzarski T, Imyanitov EN, KConFab Investigators, Australian Ovarian Cancer Study Group, Isaacs C, Ito H, Jakubowska A, Janavicius R, Jensen A, John EM, Johnson N, Kabisch M, Kang D, Kapuscinski M, Karlan BY, Khan S, Kiemeney LA, Kjaer SK, Knight JA, Konstantopoulou I, Kosma VM, Kristensen V, Kupryjanczyk J, Kwong A, de la Hoya M, Laitman Y, Lambrechts D, Le N, De Leeneer K, Lester J, Levine DA, Li J, Lindblom A, Long J, Lophatananon A, Loud JT, Lu K, Lubinski J, Mannermaa A, Manoukian S, Le Marchand L, Margolin S, Marme F, Massuger LF, Matsuo K, Mazoyer S, McGuffog L, McLean C, McNeish I, Meindl A, Menon U, Mensenkamp AR, Milne RL, Montagna M, Moysich KB, Muir K, Mulligan AM, Nathanson KL, Ness RB, Neuhausen SL, Nevanlinna H, Nord S, Nussbaum RL, Odunsi K, Offit K, Olah E, Olopade OI, Olson JE, Olswold C, O'Malley D, Orlow I, Orr N, Osorio A, Park SK, Pearce CL, Pejovic T, Peterlongo P, Pfeiler G, Phelan CM, Poole EM, Pylkäs K, Radice P, Rantala J, Rashid MU, Rennert G, Rhenius V, Rhiem K, Risch HA, Rodriguez G, Rossing MA, Rudolph A, Salvesen HB, Sangrajrang S, Sawyer EJ, Schildkraut JM, Schmidt MK, Schmutzler RK, Sellers TA, Seynaeve C, Shah M, Shen CY, Shu XO, Sieh W, Singer CF, Sinilnikova OM, Slager S, Song H, Soucy P, Southey MC, Stenmark-Askmalm M, Stoppa-Lyonnet D, Sutter C, Swerdlow A, Tchatchou S, Teixeira MR, Teo SH, Terry KL, Terry MB, Thomassen M, Tibiletti MG, Tihomirova L, Tognazzo S, Toland AE, Tomlinson I, Torres D, Truong T, Tseng CC, Tung N, Tworoger SS, Vachon C, van den Ouweland AM, van Doorn HC, van Rensburg EJ, Van't Veer LJ, Vanderstichele A, Vergote I, Vijai J, Wang Q, Wang-Gohrke S, Weitzel JN, Wentzensen N, Whittemore AS, Wildiers H, Winqvist R, Wu AH, Yannoukakos D, Yoon SY, Yu JC, Zheng W, Zheng Y, Khanna KK, Simard J, Monteiro AN, French JD, Couch FJ, Freedman ML, Easton DF, Dunning AM, Pharoah PD, Edwards SL, Chenevix-Trench G, Antoniou AC, Gayther SA
(2016) Nat Commun 7: 12675
MeSH Terms: African Continental Ancestry Group, Alleles, Asian Continental Ancestry Group, Breast Neoplasms, Chromosomes, Human, Pair 19, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Ovarian Neoplasms, Polymorphism, Single Nucleotide, RNA, Messenger
Show Abstract · Added April 3, 2018
A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10(-20)), ER-negative BC (P=1.1 × 10(-13)), BRCA1-associated BC (P=7.7 × 10(-16)) and triple negative BC (P-diff=2 × 10(-5)). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10(-3)) and ABHD8 (P<2 × 10(-3)). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3'-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk.
0 Communities
1 Members
0 Resources
13 MeSH Terms
Comprehensive, Integrative Genomic Analysis of Diffuse Lower-Grade Gliomas.
Cancer Genome Atlas Research Network, Brat DJ, Verhaak RG, Aldape KD, Yung WK, Salama SR, Cooper LA, Rheinbay E, Miller CR, Vitucci M, Morozova O, Robertson AG, Noushmehr H, Laird PW, Cherniack AD, Akbani R, Huse JT, Ciriello G, Poisson LM, Barnholtz-Sloan JS, Berger MS, Brennan C, Colen RR, Colman H, Flanders AE, Giannini C, Grifford M, Iavarone A, Jain R, Joseph I, Kim J, Kasaian K, Mikkelsen T, Murray BA, O'Neill BP, Pachter L, Parsons DW, Sougnez C, Sulman EP, Vandenberg SR, Van Meir EG, von Deimling A, Zhang H, Crain D, Lau K, Mallery D, Morris S, Paulauskis J, Penny R, Shelton T, Sherman M, Yena P, Black A, Bowen J, Dicostanzo K, Gastier-Foster J, Leraas KM, Lichtenberg TM, Pierson CR, Ramirez NC, Taylor C, Weaver S, Wise L, Zmuda E, Davidsen T, Demchok JA, Eley G, Ferguson ML, Hutter CM, Mills Shaw KR, Ozenberger BA, Sheth M, Sofia HJ, Tarnuzzer R, Wang Z, Yang L, Zenklusen JC, Ayala B, Baboud J, Chudamani S, Jensen MA, Liu J, Pihl T, Raman R, Wan Y, Wu Y, Ally A, Auman JT, Balasundaram M, Balu S, Baylin SB, Beroukhim R, Bootwalla MS, Bowlby R, Bristow CA, Brooks D, Butterfield Y, Carlsen R, Carter S, Chin L, Chu A, Chuah E, Cibulskis K, Clarke A, Coetzee SG, Dhalla N, Fennell T, Fisher S, Gabriel S, Getz G, Gibbs R, Guin R, Hadjipanayis A, Hayes DN, Hinoue T, Hoadley K, Holt RA, Hoyle AP, Jefferys SR, Jones S, Jones CD, Kucherlapati R, Lai PH, Lander E, Lee S, Lichtenstein L, Ma Y, Maglinte DT, Mahadeshwar HS, Marra MA, Mayo M, Meng S, Meyerson ML, Mieczkowski PA, Moore RA, Mose LE, Mungall AJ, Pantazi A, Parfenov M, Park PJ, Parker JS, Perou CM, Protopopov A, Ren X, Roach J, Sabedot TS, Schein J, Schumacher SE, Seidman JG, Seth S, Shen H, Simons JV, Sipahimalani P, Soloway MG, Song X, Sun H, Tabak B, Tam A, Tan D, Tang J, Thiessen N, Triche T, Van Den Berg DJ, Veluvolu U, Waring S, Weisenberger DJ, Wilkerson MD, Wong T, Wu J, Xi L, Xu AW, Yang L, Zack TI, Zhang J, Aksoy BA, Arachchi H, Benz C, Bernard B, Carlin D, Cho J, DiCara D, Frazer S, Fuller GN, Gao J, Gehlenborg N, Haussler D, Heiman DI, Iype L, Jacobsen A, Ju Z, Katzman S, Kim H, Knijnenburg T, Kreisberg RB, Lawrence MS, Lee W, Leinonen K, Lin P, Ling S, Liu W, Liu Y, Liu Y, Lu Y, Mills G, Ng S, Noble MS, Paull E, Rao A, Reynolds S, Saksena G, Sanborn Z, Sander C, Schultz N, Senbabaoglu Y, Shen R, Shmulevich I, Sinha R, Stuart J, Sumer SO, Sun Y, Tasman N, Taylor BS, Voet D, Weinhold N, Weinstein JN, Yang D, Yoshihara K, Zheng S, Zhang W, Zou L, Abel T, Sadeghi S, Cohen ML, Eschbacher J, Hattab EM, Raghunathan A, Schniederjan MJ, Aziz D, Barnett G, Barrett W, Bigner DD, Boice L, Brewer C, Calatozzolo C, Campos B, Carlotti CG, Chan TA, Cuppini L, Curley E, Cuzzubbo S, Devine K, DiMeco F, Duell R, Elder JB, Fehrenbach A, Finocchiaro G, Friedman W, Fulop J, Gardner J, Hermes B, Herold-Mende C, Jungk C, Kendler A, Lehman NL, Lipp E, Liu O, Mandt R, McGraw M, Mclendon R, McPherson C, Neder L, Nguyen P, Noss A, Nunziata R, Ostrom QT, Palmer C, Perin A, Pollo B, Potapov A, Potapova O, Rathmell WK, Rotin D, Scarpace L, Schilero C, Senecal K, Shimmel K, Shurkhay V, Sifri S, Singh R, Sloan AE, Smolenski K, Staugaitis SM, Steele R, Thorne L, Tirapelli DP, Unterberg A, Vallurupalli M, Wang Y, Warnick R, Williams F, Wolinsky Y, Bell S, Rosenberg M, Stewart C, Huang F, Grimsby JL, Radenbaugh AJ, Zhang J
(2015) N Engl J Med 372: 2481-98
MeSH Terms: Adolescent, Adult, Aged, Chromosomes, Human, Pair 1, Chromosomes, Human, Pair 19, Cluster Analysis, DNA, Neoplasm, Female, Genes, p53, Glioblastoma, Glioma, Humans, Kaplan-Meier Estimate, Male, Middle Aged, Mutation, Neoplasm Grading, Proportional Hazards Models, Sequence Analysis, DNA, Signal Transduction
Show Abstract · Added October 17, 2015
BACKGROUND - Diffuse low-grade and intermediate-grade gliomas (which together make up the lower-grade gliomas, World Health Organization grades II and III) have highly variable clinical behavior that is not adequately predicted on the basis of histologic class. Some are indolent; others quickly progress to glioblastoma. The uncertainty is compounded by interobserver variability in histologic diagnosis. Mutations in IDH, TP53, and ATRX and codeletion of chromosome arms 1p and 19q (1p/19q codeletion) have been implicated as clinically relevant markers of lower-grade gliomas.
METHODS - We performed genomewide analyses of 293 lower-grade gliomas from adults, incorporating exome sequence, DNA copy number, DNA methylation, messenger RNA expression, microRNA expression, and targeted protein expression. These data were integrated and tested for correlation with clinical outcomes.
RESULTS - Unsupervised clustering of mutations and data from RNA, DNA-copy-number, and DNA-methylation platforms uncovered concordant classification of three robust, nonoverlapping, prognostically significant subtypes of lower-grade glioma that were captured more accurately by IDH, 1p/19q, and TP53 status than by histologic class. Patients who had lower-grade gliomas with an IDH mutation and 1p/19q codeletion had the most favorable clinical outcomes. Their gliomas harbored mutations in CIC, FUBP1, NOTCH1, and the TERT promoter. Nearly all lower-grade gliomas with IDH mutations and no 1p/19q codeletion had mutations in TP53 (94%) and ATRX inactivation (86%). The large majority of lower-grade gliomas without an IDH mutation had genomic aberrations and clinical behavior strikingly similar to those found in primary glioblastoma.
CONCLUSIONS - The integration of genomewide data from multiple platforms delineated three molecular classes of lower-grade gliomas that were more concordant with IDH, 1p/19q, and TP53 status than with histologic class. Lower-grade gliomas with an IDH mutation either had 1p/19q codeletion or carried a TP53 mutation. Most lower-grade gliomas without an IDH mutation were molecularly and clinically similar to glioblastoma. (Funded by the National Institutes of Health.).
0 Communities
1 Members
0 Resources
20 MeSH Terms
A genome-wide sib-pair scan for quantitative language traits reveals linkage to chromosomes 10 and 13.
Evans PD, Mueller KL, Gamazon ER, Cox NJ, Tomblin JB
(2015) Genes Brain Behav 14: 387-97
MeSH Terms: Child, Chromosomes, Human, Pair 13, Chromosomes, Human, Pair 16, Chromosomes, Human, Pair 19, Female, Genetic Linkage, Genome-Wide Association Study, Humans, Language Development, Male, Phenotype, Quantitative Trait Loci
Show Abstract · Added February 22, 2016
Although there is considerable evidence that individual differences in language development are highly heritable, there have been few genome-wide scans to locate genes associated with the trait. Previous analyses of language impairment have yielded replicable evidence for linkage to regions on chromosomes 16q, 19q, 13q (within lab) and at 13q (between labs). Here we report the first linkage study to screen the continuum of language ability, from normal to disordered, as found in the general population. 383 children from 147 sib-ships (214 sib-pairs) were genotyped on the Illumina(®) Linkage IVb Marker Panel using three composite language-related phenotypes and a measure of phonological memory (PM). Two regions (10q23.33; 13q33.3) yielded genome-wide significant peaks for linkage with PM. A peak suggestive of linkage was also found at 17q12 for the overall language composite. This study presents two novel genetic loci for the study of language development and disorders, but fails to replicate findings by previous groups. Possible reasons for this are discussed.
© 2015 John Wiley & Sons Ltd and International Behavioural and Neural Genetics Society.
0 Communities
2 Members
0 Resources
12 MeSH Terms
Whole genome sequencing of Ethiopian highlanders reveals conserved hypoxia tolerance genes.
Udpa N, Ronen R, Zhou D, Liang J, Stobdan T, Appenzeller O, Yin Y, Du Y, Guo L, Cao R, Wang Y, Jin X, Huang C, Jia W, Cao D, Guo G, Claydon VE, Hainsworth R, Gamboa JL, Zibenigus M, Zenebe G, Xue J, Liu S, Frazer KA, Li Y, Bafna V, Haddad GG
(2014) Genome Biol 15: R36
MeSH Terms: Acclimatization, Altitude, Animals, Chromosomes, Human, Pair 19, Drosophila, Ethiopia, Ethnic Groups, Genetic Variation, Genetics, Population, Genome, Human, High-Throughput Nucleotide Sequencing, Humans, Hypoxia, Oxygen, Polymorphism, Single Nucleotide, Sequence Homology, Amino Acid
Show Abstract · Added April 25, 2016
BACKGROUND - Although it has long been proposed that genetic factors contribute to adaptation to high altitude, such factors remain largely unverified. Recent advances in high-throughput sequencing have made it feasible to analyze genome-wide patterns of genetic variation in human populations. Since traditionally such studies surveyed only a small fraction of the genome, interpretation of the results was limited.
RESULTS - We report here the results of the first whole genome resequencing-based analysis identifying genes that likely modulate high altitude adaptation in native Ethiopians residing at 3,500 m above sea level on Bale Plateau or Chennek field in Ethiopia. Using cross-population tests of selection, we identify regions with a significant loss of diversity, indicative of a selective sweep. We focus on a 208 kbp gene-rich region on chromosome 19, which is significant in both of the Ethiopian subpopulations sampled. This region contains eight protein-coding genes and spans 135 SNPs. To elucidate its potential role in hypoxia tolerance, we experimentally tested whether individual genes from the region affect hypoxia tolerance in Drosophila. Three genes significantly impact survival rates in low oxygen: cic, an ortholog of human CIC, Hsl, an ortholog of human LIPE, and Paf-AHα, an ortholog of human PAFAH1B3.
CONCLUSIONS - Our study reveals evolutionarily conserved genes that modulate hypoxia tolerance. In addition, we show that many of our results would likely be unattainable using data from exome sequencing or microarray studies. This highlights the importance of whole genome sequencing for investigating adaptation by natural selection.
0 Communities
1 Members
0 Resources
16 MeSH Terms
Genome-wide association study identifies 25 known breast cancer susceptibility loci as risk factors for triple-negative breast cancer.
Purrington KS, Slager S, Eccles D, Yannoukakos D, Fasching PA, Miron P, Carpenter J, Chang-Claude J, Martin NG, Montgomery GW, Kristensen V, Anton-Culver H, Goodfellow P, Tapper WJ, Rafiq S, Gerty SM, Durcan L, Konstantopoulou I, Fostira F, Vratimos A, Apostolou P, Konstanta I, Kotoula V, Lakis S, Dimopoulos MA, Skarlos D, Pectasides D, Fountzilas G, Beckmann MW, Hein A, Ruebner M, Ekici AB, Hartmann A, Schulz-Wendtland R, Renner SP, Janni W, Rack B, Scholz C, Neugebauer J, Andergassen U, Lux MP, Haeberle L, Clarke C, Pathmanathan N, Rudolph A, Flesch-Janys D, Nickels S, Olson JE, Ingle JN, Olswold C, Slettedahl S, Eckel-Passow JE, Anderson SK, Visscher DW, Cafourek VL, Sicotte H, Prodduturi N, Weiderpass E, Bernstein L, Ziogas A, Ivanovich J, Giles GG, Baglietto L, Southey M, Kosma VM, Fischer HP, GENICA Network, Reed MW, Cross SS, Deming-Halverson S, Shrubsole M, Cai Q, Shu XO, Daly M, Weaver J, Ross E, Klemp J, Sharma P, Torres D, Rüdiger T, Wölfing H, Ulmer HU, Försti A, Khoury T, Kumar S, Pilarski R, Shapiro CL, Greco D, Heikkilä P, Aittomäki K, Blomqvist C, Irwanto A, Liu J, Pankratz VS, Wang X, Severi G, Mannermaa A, Easton D, Hall P, Brauch H, Cox A, Zheng W, Godwin AK, Hamann U, Ambrosone C, Toland AE, Nevanlinna H, Vachon CM, Couch FJ
(2014) Carcinogenesis 35: 1012-9
MeSH Terms: Adult, Aged, Aged, 80 and over, Case-Control Studies, Chromosomes, Human, Pair 19, Estrogen Receptor alpha, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Middle Aged, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Triple Negative Breast Neoplasms, Young Adult
Show Abstract · Added March 10, 2014
Triple-negative (TN) breast cancer is an aggressive subtype of breast cancer associated with a unique set of epidemiologic and genetic risk factors. We conducted a two-stage genome-wide association study of TN breast cancer (stage 1: 1529 TN cases, 3399 controls; stage 2: 2148 cases, 1309 controls) to identify loci that influence TN breast cancer risk. Variants in the 19p13.1 and PTHLH loci showed genome-wide significant associations (P < 5 × 10(-) (8)) in stage 1 and 2 combined. Results also suggested a substantial enrichment of significantly associated variants among the single nucleotide polymorphisms (SNPs) analyzed in stage 2. Variants from 25 of 74 known breast cancer susceptibility loci were also associated with risk of TN breast cancer (P < 0.05). Associations with TN breast cancer were confirmed for 10 loci (LGR6, MDM4, CASP8, 2q35, 2p24.1, TERT-rs10069690, ESR1, TOX3, 19p13.1, RALY), and we identified associations with TN breast cancer for 15 additional breast cancer loci (P < 0.05: PEX14, 2q24.1, 2q31.1, ADAM29, EBF1, TCF7L2, 11q13.1, 11q24.3, 12p13.1, PTHLH, NTN4, 12q24, BRCA2, RAD51L1-rs2588809, MKL1). Further, two SNPs independent of previously reported signals in ESR1 [rs12525163 odds ratio (OR) = 1.15, P = 4.9 × 10(-) (4)] and 19p13.1 (rs1864112 OR = 0.84, P = 1.8 × 10(-) (9)) were associated with TN breast cancer. A polygenic risk score (PRS) for TN breast cancer based on known breast cancer risk variants showed a 4-fold difference in risk between the highest and lowest PRS quintiles (OR = 4.03, 95% confidence interval 3.46-4.70, P = 4.8 × 10(-) (69)). This translates to an absolute risk for TN breast cancer ranging from 0.8% to 3.4%, suggesting that genetic variation may be used for TN breast cancer risk prediction.
0 Communities
3 Members
0 Resources
15 MeSH Terms
Primate-specific evolution of noncoding element insertion into PLA2G4C and human preterm birth.
Plunkett J, Doniger S, Morgan T, Haataja R, Hallman M, Puttonen H, Menon R, Kuczynski E, Norwitz E, Snegovskikh V, Palotie A, Peltonen L, Fellman V, DeFranco EA, Chaudhari BP, Oates J, Boutaud O, McGregor TL, McElroy JJ, Teramo K, Borecki I, Fay JC, Muglia LJ
(2010) BMC Med Genomics 3: 62
MeSH Terms: Animals, Biosynthetic Pathways, Chromosomes, Human, Pair 19, Evolution, Molecular, Group IV Phospholipases A2, Humans, Introns, Mutagenesis, Insertional, Parturition, Phylogeny, Premature Birth, Primates, Prostaglandins
Show Abstract · Added March 7, 2014
BACKGROUND - The onset of birth in humans, like other apes, differs from non-primate mammals in its endocrine physiology. We hypothesize that higher primate-specific gene evolution may lead to these differences and target genes involved in human preterm birth, an area of global health significance.
METHODS - We performed a comparative genomics screen of highly conserved noncoding elements and identified PLA2G4C, a phospholipase A isoform involved in prostaglandin biosynthesis as human accelerated. To examine whether this gene demonstrating primate-specific evolution was associated with birth timing, we genotyped and analyzed 8 common single nucleotide polymorphisms (SNPs) in PLA2G4C in US Hispanic (n = 73 preterm, 292 control), US White (n = 147 preterm, 157 control) and US Black (n = 79 preterm, 166 control) mothers.
RESULTS - Detailed structural and phylogenic analysis of PLA2G4C suggested a short genomic element within the gene duplicated from a paralogous highly conserved element on chromosome 1 specifically in primates. SNPs rs8110925 and rs2307276 in US Hispanics and rs11564620 in US Whites were significant after correcting for multiple tests (p < 0.006). Additionally, rs11564620 (Thr360Pro) was associated with increased metabolite levels of the prostaglandin thromboxane in healthy individuals (p = 0.02), suggesting this variant may affect PLA2G4C activity.
CONCLUSIONS - Our findings suggest that variation in PLA2G4C may influence preterm birth risk by increasing levels of prostaglandins, which are known to regulate labor.
0 Communities
2 Members
0 Resources
13 MeSH Terms
Loss of Phosphatase and Tensin homologue deleted on chromosome 10 engages ErbB3 and insulin-like growth factor-I receptor signaling to promote antiestrogen resistance in breast cancer.
Miller TW, Pérez-Torres M, Narasanna A, Guix M, Stål O, Pérez-Tenorio G, Gonzalez-Angulo AM, Hennessy BT, Mills GB, Kennedy JP, Lindsley CW, Arteaga CL
(2009) Cancer Res 69: 4192-201
MeSH Terms: Breast Neoplasms, Cell Division, Cell Line, Tumor, Chromosome Deletion, Chromosomes, Human, Pair 19, Drug Resistance, Neoplasm, Estrogen Receptor Modulators, Female, Genes, Reporter, Humans, PTEN Phosphohydrolase, Receptor, ErbB-2, Receptor, ErbB-3, Receptor, IGF Type 1, Transcription, Genetic
Show Abstract · Added March 5, 2014
Knockdown of the tumor suppressor phosphatase Phosphatase and tensin homologue deleted on chromosome 10 (PTEN) with shRNA in three estrogen receptor (ER)-positive breast cancer cell lines resulted in increased phosphatidylinositol-3 kinase (PI3K) and AKT activities, resistance to tamoxifen and fulvestrant, and hormone-independent growth. PTEN knockdown induced the up-regulation of ER transcriptional activity in MCF-7 cells but decreased ER protein levels and transcriptional activity in T47D and MDA-361 cells. Tamoxifen and fulvestrant treatment inhibited estradiol-induced ER transcriptional activity in all shPTEN cell lines but did not abrogate the increased cell proliferation induced by PTEN knockdown. PTEN knockdown increased basal and ligand-induced activation of the insulin-like growth factor-I (IGF-I) and ErbB3 receptor tyrosine kinases, and prolonged the association of the p85 PI3K subunit with the IGF-I receptor (IGF-IR) effector insulin receptor substrate-1 and with ErbB3, implicating PTEN in the modulation of signaling upstream of PI3K. Consistent with these data, PTEN levels inversely correlated with levels of tyrosine-phosphorylated IGF-IR in tissue lysate arrays of primary breast cancers. Inhibition of IGF-IR and/or ErbB2-mediated activation of ErbB3 with tyrosine kinase inhibitors restored hormone dependence and the growth inhibitory effect of tamoxifen and fulvestrant on shPTEN cells, suggesting that cotargeting both ER and receptor tyrosine kinase pathways holds promise for the treatment of patients with ER+, PTEN-deficient breast cancers.
1 Communities
2 Members
0 Resources
15 MeSH Terms
Genome-wide and Ordered-Subset linkage analyses provide support for autism loci on 17q and 19p with evidence of phenotypic and interlocus genetic correlates.
McCauley JL, Li C, Jiang L, Olson LM, Crockett G, Gainer K, Folstein SE, Haines JL, Sutcliffe JS
(2005) BMC Med Genet 6: 1
MeSH Terms: Adolescent, Adult, Autistic Disorder, Child, Child, Preschool, Chromosomes, Human, Pair 17, Chromosomes, Human, Pair 19, Female, Genetic Linkage, Genetic Predisposition to Disease, Genome, Human, Humans, Male, Middle Aged, Phenotype
Show Abstract · Added February 20, 2014
BACKGROUND - Autism is a neurobehavioral spectrum of phenotypes characterized by deficits in the development of language and social relationships and patterns of repetitive, rigid and compulsive behaviors. Twin and family studies point to a significant genetic etiology, and several groups have performed genomic linkage screens to identify susceptibility loci.
METHODS - We performed a genome-wide linkage screen in 158 combined Tufts, Vanderbilt and AGRE (Autism Genetics Research Exchange) multiplex autism families using parametric and nonparametric methods with a categorical autism diagnosis to identify loci of main effect. Hypothesizing interdependence of genetic risk factors prompted us to perform exploratory studies applying the Ordered-Subset Analysis (OSA) approach using LOD scores as the trait covariate for ranking families. We employed OSA to test for interlocus correlations between loci with LOD scores > or =1.5, and empirically determined significance of linkage in optimal OSA subsets using permutation testing. Exploring phenotypic correlates as the basis for linkage increases involved comparison of mean scores for quantitative trait-based subsets of autism between optimal subsets and the remaining families.
RESULTS - A genome-wide screen for autism loci identified the best evidence for linkage to 17q11.2 and 19p13, with maximum multipoint heterogeneity LOD scores of 2.9 and 2.6, respectively. Suggestive linkage (LOD scores > or =1.5) at other loci included 3p, 6q, 7q, 12p, and 16p. OSA revealed positive correlations of linkage between the 19p locus and 17q, between 19p and 6q, and between 7q and 5p. While potential phenotypic correlates for these findings were not identified for the chromosome 7/5 combination, differences indicating more rapid achievement of "developmental milestones" was apparent in the chromosome 19 OSA-defined subsets for 17q and 6q. OSA was used to test the hypothesis that 19p linkage involved more rapid achievement of these milestones and it revealed significantly increased LOD* scores at 19p13.
CONCLUSIONS - Our results further support 19p13 as harboring an autism susceptibility locus, confirm other linkage findings at 17q11.2, and demonstrate the need to analyze more discreet trait-based subsets of complex phenotypes to improve ability to detect genetic effects.
0 Communities
1 Members
0 Resources
15 MeSH Terms
Genome scan for loci linked to mite sensitivity: the Collaborative Study on the Genetics of Asthma (CSGA).
Blumenthal MN, Ober C, Beaty TH, Bleecker ER, Langefeld CD, King RA, Lester L, Cox N, Barnes K, Togias A, Mathias R, Meyers DA, Oetting W, Rich SS, CSGA
(2004) Genes Immun 5: 226-31
MeSH Terms: Animals, Antigens, Dermatophagoides, Asthma, Chromosome Mapping, Chromosomes, Human, Pair 19, Chromosomes, Human, Pair 20, Disease Susceptibility, Ethnic Groups, Female, Genetic Linkage, Genome, Human, Genotype, Humans, Hypersensitivity, Immediate, Lod Score, Male, Mites, Phenotype, Polymorphism, Genetic, Skin Tests
Show Abstract · Added February 22, 2016
Mite sensitivity has been reported to be a major risk factor for asthma. As part of the Collaborative Study on the Genetics of Asthma (CSGA), a genome scan using mite reactivity (Dermatophagoides Pteronyssinus (Der p) and Dermatophagoides farinae (Der f)) as the phenotype was conducted. In 287 CSGA families, 122 were informative for linkage. Evidence supporting linkage was observed for regions on chromosome 19 (D19S591, lod=2.43, P=0.0008; D19S1037, lod=1.57, P=0.007) and chromosome 20 (D20S473/D20S604, lod=1.41, P=0.01). All three ethnic groups appeared to contribute to the evidence for linkage on chromosome 20. African-American families gave strongest support for linkage on chromosomes 3 (D3S2409, lod=1.33, P=0.01), 12 (D12S373, lod=1.51, P=0.008) and 18 (ATA82B02, lod=1.32, P=0.01). Caucasian families showed strong evidence for linkage on chromosome 19 (D19S591, lod=3.51, P=0.00006). Hispanic families supported linkage on chromosomes 11 (D11S1984, lod=1.56, P=0.007), 13 (D13S787, lod=1.30, P=0.01) and 20 (D20S470, lod=1.71, P=0.005). These results suggest that multiple genes may be involved in controlling skin reactivity to Dermatophoigoies.
0 Communities
1 Members
0 Resources
20 MeSH Terms
Neighboring-nucleotide effects on single nucleotide polymorphisms: a study of 2.6 million polymorphisms across the human genome.
Zhao Z, Boerwinkle E
(2002) Genome Res 12: 1679-86
MeSH Terms: Base Composition, Chromosomes, Human, Pair 19, Chromosomes, Human, Pair 22, Genome, Human, Humans, Nucleotides, Polymorphism, Single Nucleotide, Sequence Analysis, DNA
Show Abstract · Added March 5, 2014
We investigated substitution patterns and neighboring-nucleotide effects for 2,576,903 single nucleotide polymorphisms (SNPs) publicly available through the National Center for Biotechnology Information (NCBI). The proportions of substitutions were A/G, 32.77%; C/T, 32.81%; A/C, 8.98%; G/T, 9.06%; A/T, 7.46%; and C/G, 8.92%. The two nucleotides immediately neighboring the variable site showed major deviation from genome-wide and chromosome-specific expectations, although lesser biases extended as far as 200 bp. On the 5' side, the biases for A, C, G, and T were 1.43%, 4.91%, -1.70%, and -4.62%, respectively. These biases were -4.44%, -1.59%, 5.05%, and 0.99%, respectively, on the 3' side. The neighboring-nucleotide patterns for transitions were dominated by the hypermutability effects of CpG dinucleotides. Transitions were more common than transversions, and the probability of a transversion increased with increasing A + T content at the two adjacent sites. Neighboring-nucleotide biases were not consistent among chromosomes, with Chromosomes 19 and 22 standing out as different from the others. These data provide genome-wide information about the effects of neighboring nucleotides on mutational and evolutionary processes giving rise to contemporary patterns of nucleotide occurrence surrounding SNPs.
0 Communities
1 Members
0 Resources
8 MeSH Terms