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 160

Publication Record

Connections

Identification of ten variants associated with risk of estrogen-receptor-negative breast cancer.
Milne RL, Kuchenbaecker KB, Michailidou K, Beesley J, Kar S, Lindström S, Hui S, Lemaçon A, Soucy P, Dennis J, Jiang X, Rostamianfar A, Finucane H, Bolla MK, McGuffog L, Wang Q, Aalfs CM, ABCTB Investigators, Adams M, Adlard J, Agata S, Ahmed S, Ahsan H, Aittomäki K, Al-Ejeh F, Allen J, Ambrosone CB, Amos CI, Andrulis IL, Anton-Culver H, Antonenkova NN, Arndt V, Arnold N, Aronson KJ, Auber B, Auer PL, Ausems MGEM, Azzollini J, Bacot F, Balmaña J, Barile M, Barjhoux L, Barkardottir RB, Barrdahl M, Barnes D, Barrowdale D, Baynes C, Beckmann MW, Benitez J, Bermisheva M, Bernstein L, Bignon YJ, Blazer KR, Blok MJ, Blomqvist C, Blot W, Bobolis K, Boeckx B, Bogdanova NV, Bojesen A, Bojesen SE, Bonanni B, Børresen-Dale AL, Bozsik A, Bradbury AR, Brand JS, Brauch H, Brenner H, Bressac-de Paillerets B, Brewer C, Brinton L, Broberg P, Brooks-Wilson A, Brunet J, Brüning T, Burwinkel B, Buys SS, Byun J, Cai Q, Caldés T, Caligo MA, Campbell I, Canzian F, Caron O, Carracedo A, Carter BD, Castelao JE, Castera L, Caux-Moncoutier V, Chan SB, Chang-Claude J, Chanock SJ, Chen X, Cheng TD, Chiquette J, Christiansen H, Claes KBM, Clarke CL, Conner T, Conroy DM, Cook J, Cordina-Duverger E, Cornelissen S, Coupier I, Cox A, Cox DG, Cross SS, Cuk K, Cunningham JM, Czene K, Daly MB, Damiola F, Darabi H, Davidson R, De Leeneer K, Devilee P, Dicks E, Diez O, Ding YC, Ditsch N, Doheny KF, Domchek SM, Dorfling CM, Dörk T, Dos-Santos-Silva I, Dubois S, Dugué PA, Dumont M, Dunning AM, Durcan L, Dwek M, Dworniczak B, Eccles D, Eeles R, Ehrencrona H, Eilber U, Ejlertsen B, Ekici AB, Eliassen AH, EMBRACE, Engel C, Eriksson M, Fachal L, Faivre L, Fasching PA, Faust U, Figueroa J, Flesch-Janys D, Fletcher O, Flyger H, Foulkes WD, Friedman E, Fritschi L, Frost D, Gabrielson M, Gaddam P, Gammon MD, Ganz PA, Gapstur SM, Garber J, Garcia-Barberan V, García-Sáenz JA, Gaudet MM, Gauthier-Villars M, Gehrig A, GEMO Study Collaborators, Georgoulias V, Gerdes AM, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Goodfellow P, Greene MH, Alnæs GIG, Grip M, Gronwald J, Grundy A, Gschwantler-Kaulich D, Guénel P, Guo Q, Haeberle L, Hahnen E, Haiman CA, Håkansson N, Hallberg E, Hamann U, Hamel N, Hankinson S, Hansen TVO, Harrington P, Hart SN, Hartikainen JM, Healey CS, HEBON, Hein A, Helbig S, Henderson A, Heyworth J, Hicks B, Hillemanns P, Hodgson S, Hogervorst FB, Hollestelle A, Hooning MJ, Hoover B, Hopper JL, Hu C, Huang G, Hulick PJ, Humphreys K, Hunter DJ, Imyanitov EN, Isaacs C, Iwasaki M, Izatt L, Jakubowska A, James P, Janavicius R, Janni W, Jensen UB, John EM, Johnson N, Jones K, Jones M, Jukkola-Vuorinen A, Kaaks R, Kabisch M, Kaczmarek K, Kang D, Kast K, kConFab/AOCS Investigators, Keeman R, Kerin MJ, Kets CM, Keupers M, Khan S, Khusnutdinova E, Kiiski JI, Kim SW, Knight JA, Konstantopoulou I, Kosma VM, Kristensen VN, Kruse TA, Kwong A, Lænkholm AV, Laitman Y, Lalloo F, Lambrechts D, Landsman K, Lasset C, Lazaro C, Le Marchand L, Lecarpentier J, Lee A, Lee E, Lee JW, Lee MH, Lejbkowicz F, Lesueur F, Li J, Lilyquist J, Lincoln A, Lindblom A, Lissowska J, Lo WY, Loibl S, Long J, Loud JT, Lubinski J, Luccarini C, Lush M, MacInnis RJ, Maishman T, Makalic E, Kostovska IM, Malone KE, Manoukian S, Manson JE, Margolin S, Martens JWM, Martinez ME, Matsuo K, Mavroudis D, Mazoyer S, McLean C, Meijers-Heijboer H, Menéndez P, Meyer J, Miao H, Miller A, Miller N, Mitchell G, Montagna M, Muir K, Mulligan AM, Mulot C, Nadesan S, Nathanson KL, NBSC Collaborators, Neuhausen SL, Nevanlinna H, Nevelsteen I, Niederacher D, Nielsen SF, Nordestgaard BG, Norman A, Nussbaum RL, Olah E, Olopade OI, Olson JE, Olswold C, Ong KR, Oosterwijk JC, Orr N, Osorio A, Pankratz VS, Papi L, Park-Simon TW, Paulsson-Karlsson Y, Lloyd R, Pedersen IS, Peissel B, Peixoto A, Perez JIA, Peterlongo P, Peto J, Pfeiler G, Phelan CM, Pinchev M, Plaseska-Karanfilska D, Poppe B, Porteous ME, Prentice R, Presneau N, Prokofieva D, Pugh E, Pujana MA, Pylkäs K, Rack B, Radice P, Rahman N, Rantala J, Rappaport-Fuerhauser C, Rennert G, Rennert HS, Rhenius V, Rhiem K, Richardson A, Rodriguez GC, Romero A, Romm J, Rookus MA, Rudolph A, Ruediger T, Saloustros E, Sanders J, Sandler DP, Sangrajrang S, Sawyer EJ, Schmidt DF, Schoemaker MJ, Schumacher F, Schürmann P, Schwentner L, Scott C, Scott RJ, Seal S, Senter L, Seynaeve C, Shah M, Sharma P, Shen CY, Sheng X, Shimelis H, Shrubsole MJ, Shu XO, Side LE, Singer CF, Sohn C, Southey MC, Spinelli JJ, Spurdle AB, Stegmaier C, Stoppa-Lyonnet D, Sukiennicki G, Surowy H, Sutter C, Swerdlow A, Szabo CI, Tamimi RM, Tan YY, Taylor JA, Tejada MI, Tengström M, Teo SH, Terry MB, Tessier DC, Teulé A, Thöne K, Thull DL, Tibiletti MG, Tihomirova L, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Tong L, Torres D, Tranchant M, Truong T, Tucker K, Tung N, Tyrer J, Ulmer HU, Vachon C, van Asperen CJ, Van Den Berg D, van den Ouweland AMW, van Rensburg EJ, Varesco L, Varon-Mateeva R, Vega A, Viel A, Vijai J, Vincent D, Vollenweider J, Walker L, Wang Z, Wang-Gohrke S, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wesseling J, Whittemore AS, Wijnen JT, Willett W, Winqvist R, Wolk A, Wu AH, Xia L, Yang XR, Yannoukakos D, Zaffaroni D, Zheng W, Zhu B, Ziogas A, Ziv E, Zorn KK, Gago-Dominguez M, Mannermaa A, Olsson H, Teixeira MR, Stone J, Offit K, Ottini L, Park SK, Thomassen M, Hall P, Meindl A, Schmutzler RK, Droit A, Bader GD, Pharoah PDP, Couch FJ, Easton DF, Kraft P, Chenevix-Trench G, García-Closas M, Schmidt MK, Antoniou AC, Simard J
(2017) Nat Genet 49: 1767-1778
MeSH Terms: BRCA1 Protein, Breast Neoplasms, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Heterozygote, Humans, Mutation, Polymorphism, Single Nucleotide, Receptors, Estrogen, Risk Factors
Show Abstract · Added April 3, 2018
Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
0 Communities
3 Members
0 Resources
MeSH Terms
The discrepancy among single nucleotide variants detected by DNA and RNA high throughput sequencing data.
Guo Y, Zhao S, Sheng Q, Samuels DC, Shyr Y
(2017) BMC Genomics 18: 690
MeSH Terms: Databases, Nucleic Acid, Genotype, Heterozygote, High-Throughput Nucleotide Sequencing, Mutation, Polymorphism, Single Nucleotide, Probability, Sequence Analysis, DNA, Sequence Analysis, RNA
Show Abstract · Added March 21, 2018
BACKGROUND - High throughput sequencing technology enables the both the human genome and transcriptome to be screened at the single nucleotide resolution. Tools have been developed to infer single nucleotide variants (SNVs) from both DNA and RNA sequencing data. To evaluate how much difference can be expected between DNA and RNA sequencing data, and among tissue sources, we designed a study to examine the single nucleotide difference among five sources of high throughput sequencing data generated from the same individual, including exome sequencing from blood, tumor and adjacent normal tissue, and RNAseq from tumor and adjacent normal tissue.
RESULTS - Through careful quality control and analysis of the SNVs, we found little difference between DNA-DNA pairs (1%-2%). However, between DNA-RNA pairs, SNV differences ranged anywhere from 10% to 20%.
CONCLUSIONS - Only a small portion of these differences can be explained by RNA editing. Instead, the majority of the DNA-RNA differences should be attributed to technical errors from sequencing and post-processing of RNAseq data. Our analysis results suggest that SNV detection using RNAseq is subject to high false positive rates.
0 Communities
2 Members
0 Resources
9 MeSH Terms
Heterozygous loss of TSC2 alters p53 signaling and human stem cell reprogramming.
Armstrong LC, Westlake G, Snow JP, Cawthon B, Armour E, Bowman AB, Ess KC
(2017) Hum Mol Genet 26: 4629-4641
MeSH Terms: Adolescent, Adult, Alleles, Cellular Reprogramming, Child, Child, Preschool, Female, Fibroblasts, Genes, p53, Heterozygote, Humans, Induced Pluripotent Stem Cells, Infant, Loss of Heterozygosity, Male, Mutation, RNA, Small Interfering, Signal Transduction, TOR Serine-Threonine Kinases, Tuberous Sclerosis, Tuberous Sclerosis Complex 1 Protein, Tuberous Sclerosis Complex 2 Protein, Tumor Suppressor Protein p53, Tumor Suppressor Proteins
Show Abstract · Added April 11, 2018
Tuberous sclerosis complex (TSC) is a pediatric disorder of dysregulated growth and differentiation caused by loss of function mutations in either the TSC1 or TSC2 genes, which regulate mTOR kinase activity. To study aberrations of early development in TSC, we generated induced pluripotent stem cells using dermal fibroblasts obtained from patients with TSC. During validation, we found that stem cells generated from TSC patients had a very high rate of integration of the reprogramming plasmid containing a shRNA against TP53. We also found that loss of one allele of TSC2 in human fibroblasts is sufficient to increase p53 levels and impair stem cell reprogramming. Increased p53 was also observed in TSC2 heterozygous and homozygous mutant human stem cells, suggesting that the interactions between TSC2 and p53 are consistent across cell types and gene dosage. These results support important contributions of TSC2 heterozygous and homozygous mutant cells to the pathogenesis of TSC and the important role of p53 during reprogramming.
© The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.
0 Communities
1 Members
0 Resources
24 MeSH Terms
A case of severe acquired hypertriglyceridemia in a 7-year-old girl.
Lilley JS, Linton MF, Kelley JC, Graham TB, Fazio S, Tavori H
(2017) J Clin Lipidol 11: 1480-1484
MeSH Terms: Autoantibodies, Autoimmunity, Child, Female, Heterozygote, Humans, Hyperlipoproteinemia Type I, Lipoprotein Lipase, Mutation, Prednisone, Sjogren's Syndrome, Triglycerides
Show Abstract · Added April 10, 2018
We report a case of severe type I hyperlipoproteinemia caused by autoimmunity against lipoprotein lipase (LPL) in the context of presymptomatic Sjögren's syndrome. A 7-year-old mixed race (Caucasian/African American) girl was admitted to the intensive care unit at Vanderbilt Children's Hospital with acute pancreatitis and shock. She was previously healthy aside from asthma and history of Hashimoto's thyroiditis. Admission triglycerides (TGs) were 2191 mg/dL but returned to normal during the hospital stay and in the absence of food intake. At discharge, she was placed on a low-fat, low-sugar diet. She did not respond to fibrates, prescription fish oil, metformin, or orlistat, and during the following 2 years, she was hospitalized several times with recurrent pancreatitis. Except for a heterozygous mutation in the promoter region of LPL, predicted to have no clinical significance, she had no further mutations in genes known to affect TG metabolism and to cause inherited type I hyperlipoproteinemia, such as APOA5, APOC2, GPIHBP1, or LMF1. When her TG levels normalized after incidental use of prednisone, an autoimmune mechanism was suspected. Immunoblot analyses showed the presence of autoantibodies to LPL in the patient's plasma. Autoantibodies to LPL decreased by 37% while patient was on prednisone, and by 68% as she subsequently transitioned to hydroxychloroquine monotherapy. While on hydroxychloroquine, she underwent a supervised high-fat meal challenge and showed normal ability to metabolize TG. For the past 3 years and 6 months, she has had TG consistently <250 mg/dL, and no symptoms of, or readmissions for, pancreatitis.
Copyright © 2017 National Lipid Association. Published by Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
12 MeSH Terms
Mitochondrial dysfunction in the APP/PSEN1 mouse model of Alzheimer's disease and a novel protective role for ascorbate.
Dixit S, Fessel JP, Harrison FE
(2017) Free Radic Biol Med 112: 515-523
MeSH Terms: Adenosine Diphosphate, Adenosine Triphosphate, Alzheimer Disease, Amyloid beta-Protein Precursor, Animals, Antioxidants, Ascorbic Acid, Biological Transport, Disease Models, Animal, Female, Gene Expression Regulation, Heterozygote, Humans, Male, Membrane Potential, Mitochondrial, Mice, Mice, Transgenic, Mitochondria, Mutation, Oxidative Stress, Oxygen Consumption, Presenilin-1, Reactive Oxygen Species, Signal Transduction, Sodium-Coupled Vitamin C Transporters
Show Abstract · Added March 14, 2018
Mitochondrial dysfunction is elevated in very early stages of Alzheimer's disease and exacerbates oxidative stress, which contributes to disease pathology. Mitochondria were isolated from 4-month-old wild-type mice, transgenic mice carrying the APP and PSEN1 mutations, mice with decreased brain and mitochondrial ascorbate (vitamin C) via heterozygous knockout of the sodium dependent vitamin C transporter (SVCT2) and transgenic APP/PSEN1 mice with heterozygous SVCT2 expression. Mitochondrial isolates from SVCT2 mice were observed to consume less oxygen using high-resolution respirometry, and also exhibited decreased mitochondrial membrane potential compared to wild type isolates. Conversely, isolates from young (4 months) APP/PSEN1 mice consumed more oxygen, and exhibited an increase in mitochondrial membrane potential, but had a significantly lower ATP/ADP ratio compared to wild type isolates. Greater levels of reactive oxygen species were also produced in mitochondria isolated from both APP/PSEN1 and SVCT2 mice compared to wild type isolates. Acute administration of ascorbate to mitochondria isolated from wild-type mice increased oxygen consumption compared with untreated mitochondria suggesting ascorbate may support energy production. This study suggests that both presence of amyloid and ascorbate deficiency can contribute to mitochondrial dysfunction, even at an early, prodromal stage of Alzheimer's disease, although occurring via different pathways. Ascorbate may, therefore, provide a useful preventative strategy against neurodegenerative disease, particularly in populations most at risk for Alzheimer's disease in which stores are often depleted through mitochondrial dysfunction and elevated oxidative stress.
Copyright © 2017 Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
25 MeSH Terms
Type 2 Diabetes Variants Disrupt Function of SLC16A11 through Two Distinct Mechanisms.
Rusu V, Hoch E, Mercader JM, Tenen DE, Gymrek M, Hartigan CR, DeRan M, von Grotthuss M, Fontanillas P, Spooner A, Guzman G, Deik AA, Pierce KA, Dennis C, Clish CB, Carr SA, Wagner BK, Schenone M, Ng MCY, Chen BH, MEDIA Consortium, SIGMA T2D Consortium, Centeno-Cruz F, Zerrweck C, Orozco L, Altshuler DM, Schreiber SL, Florez JC, Jacobs SBR, Lander ES
(2017) Cell 170: 199-212.e20
MeSH Terms: Basigin, Cell Membrane, Chromosomes, Human, Pair 17, Diabetes Mellitus, Type 2, Gene Knockdown Techniques, Haplotypes, Hepatocytes, Heterozygote, Histone Code, Humans, Liver, Models, Molecular, Monocarboxylic Acid Transporters
Show Abstract · Added September 20, 2017
Type 2 diabetes (T2D) affects Latinos at twice the rate seen in populations of European descent. We recently identified a risk haplotype spanning SLC16A11 that explains ∼20% of the increased T2D prevalence in Mexico. Here, through genetic fine-mapping, we define a set of tightly linked variants likely to contain the causal allele(s). We show that variants on the T2D-associated haplotype have two distinct effects: (1) decreasing SLC16A11 expression in liver and (2) disrupting a key interaction with basigin, thereby reducing cell-surface localization. Both independent mechanisms reduce SLC16A11 function and suggest SLC16A11 is the causal gene at this locus. To gain insight into how SLC16A11 disruption impacts T2D risk, we demonstrate that SLC16A11 is a proton-coupled monocarboxylate transporter and that genetic perturbation of SLC16A11 induces changes in fatty acid and lipid metabolism that are associated with increased T2D risk. Our findings suggest that increasing SLC16A11 function could be therapeutically beneficial for T2D. VIDEO ABSTRACT.
Copyright © 2017 Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
13 MeSH Terms
Power and sample size calculations for high-throughput sequencing-based experiments.
Li CI, Samuels DC, Zhao YY, Shyr Y, Guo Y
(2018) Brief Bioinform 19: 1247-1255
MeSH Terms: Chromatin Immunoprecipitation, Genome-Wide Association Study, Heterozygote, High-Throughput Nucleotide Sequencing, Humans, Microbiota, Mutation, Poisson Distribution, Sequence Analysis, RNA
Show Abstract · Added April 3, 2018
Power/sample size (power) analysis estimates the likelihood of successfully finding the statistical significance in a data set. There has been a growing recognition of the importance of power analysis in the proper design of experiments. Power analysis is complex, yet necessary for the success of large studies. It is important to design a study that produces statistically accurate and reliable results. Power computation methods have been well established for both microarray-based gene expression studies and genotyping microarray-based genome-wide association studies. High-throughput sequencing (HTS) has greatly enhanced our ability to conduct biomedical studies at the highest possible resolution (per nucleotide). However, the complexity of power computations is much greater for sequencing data than for the simpler genotyping array data. Research on methods of power computations for HTS-based studies has been recently conducted but is not yet well known or widely used. In this article, we describe the power computation methods that are currently available for a range of HTS-based studies, including DNA sequencing, RNA-sequencing, microbiome sequencing and chromatin immunoprecipitation sequencing. Most importantly, we review the methods of power analysis for several types of sequencing data and guide the reader to the relevant methods for each data type.
0 Communities
1 Members
0 Resources
9 MeSH Terms
Patient-Specific iPSC-Derived Endothelial Cells Uncover Pathways that Protect against Pulmonary Hypertension in BMPR2 Mutation Carriers.
Gu M, Shao NY, Sa S, Li D, Termglinchan V, Ameen M, Karakikes I, Sosa G, Grubert F, Lee J, Cao A, Taylor S, Ma Y, Zhao Z, Chappell J, Hamid R, Austin ED, Gold JD, Wu JC, Snyder MP, Rabinovitch M
(2017) Cell Stem Cell 20: 490-504.e5
MeSH Terms: Base Sequence, Bone Morphogenetic Protein 4, Bone Morphogenetic Protein Receptors, Type II, Cell Adhesion, Cell Movement, Cell Shape, Cell Survival, Endothelial Cells, Gene Editing, Gene Expression Regulation, Heterozygote, Humans, Hypertension, Pulmonary, Induced Pluripotent Stem Cells, Mutation, Neovascularization, Physiologic, Phosphorylation, Sequence Analysis, RNA, Signal Transduction, Smad Proteins, p38 Mitogen-Activated Protein Kinases
Show Abstract · Added February 21, 2017
In familial pulmonary arterial hypertension (FPAH), the autosomal dominant disease-causing BMPR2 mutation is only 20% penetrant, suggesting that genetic variation provides modifiers that alleviate the disease. Here, we used comparison of induced pluripotent stem cell-derived endothelial cells (iPSC-ECs) from three families with unaffected mutation carriers (UMCs), FPAH patients, and gender-matched controls to investigate this variation. Our analysis identified features of UMC iPSC-ECs related to modifiers of BMPR2 signaling or to differentially expressed genes. FPAH-iPSC-ECs showed reduced adhesion, survival, migration, and angiogenesis compared to UMC-iPSC-ECs and control cells. The "rescued" phenotype of UMC cells was related to an increase in specific BMPR2 activators and/or a reduction in inhibitors, and the improved cell adhesion could be attributed to preservation of related signaling. The improved survival was related to increased BIRC3 and was independent of BMPR2. Our findings therefore highlight protective modifiers for FPAH that could help inform development of future treatment strategies.
Copyright © 2017 Elsevier Inc. All rights reserved.
0 Communities
1 Members
0 Resources
21 MeSH Terms
Heterozygosity Ratio, a Robust Global Genomic Measure of Autozygosity and Its Association with Height and Disease Risk.
Samuels DC, Wang J, Ye F, He J, Levinson RT, Sheng Q, Zhao S, Capra JA, Shyr Y, Zheng W, Guo Y
(2016) Genetics 204: 893-904
MeSH Terms: Body Height, Gene Frequency, Genetic Predisposition to Disease, Genome, Human, Heterozygote, Humans, Polymorphism, Genetic
Show Abstract · Added April 18, 2017
Greater genetic variability in an individual is protective against recessive disease. However, existing quantifications of autozygosity, such as runs of homozygosity (ROH), have proved highly sensitive to genotyping density and have yielded inconclusive results about the relationship of diversity and disease risk. Using genotyping data from three data sets with >43,000 subjects, we demonstrated that an alternative approach to quantifying genetic variability, the heterozygosity ratio, is a robust measure of diversity and is positively associated with the nondisease trait height and several disease phenotypes in subjects of European ancestry. The heterozygosity ratio is the number of heterozygous sites in an individual divided by the number of nonreference homozygous sites and is strongly affected by the degree of genetic admixture of the population and varies across human populations. Unlike quantifications of ROH, the heterozygosity ratio is not sensitive to the density of genotyping performed. Our results establish the heterozygosity ratio as a powerful new statistic for exploring the patterns and phenotypic effects of different levels of genetic variation in populations.
Copyright © 2016 by the Genetics Society of America.
0 Communities
2 Members
0 Resources
7 MeSH Terms
Identification of independent association signals and putative functional variants for breast cancer risk through fine-scale mapping of the 12p11 locus.
Zeng C, Guo X, Long J, Kuchenbaecker KB, Droit A, Michailidou K, Ghoussaini M, Kar S, Freeman A, Hopper JL, Milne RL, Bolla MK, Wang Q, Dennis J, Agata S, Ahmed S, Aittomäki K, Andrulis IL, Anton-Culver H, Antonenkova NN, Arason A, Arndt V, Arun BK, Arver B, Bacot F, Barrowdale D, Baynes C, Beeghly-Fadiel A, Benitez J, Bermisheva M, Blomqvist C, Blot WJ, Bogdanova NV, Bojesen SE, Bonanni B, Borresen-Dale AL, Brand JS, Brauch H, Brennan P, Brenner H, Broeks A, Brüning T, Burwinkel B, Buys SS, Cai Q, Caldes T, Campbell I, Carpenter J, Chang-Claude J, Choi JY, Claes KB, Clarke C, Cox A, Cross SS, Czene K, Daly MB, de la Hoya M, De Leeneer K, Devilee P, Diez O, Domchek SM, Doody M, Dorfling CM, Dörk T, Dos-Santos-Silva I, Dumont M, Dwek M, Dworniczak B, Egan K, Eilber U, Einbeigi Z, Ejlertsen B, Ellis S, Frost D, Lalloo F, EMBRACE, Fasching PA, Figueroa J, Flyger H, Friedlander M, Friedman E, Gambino G, Gao YT, Garber J, García-Closas M, Gehrig A, Damiola F, Lesueur F, Mazoyer S, Stoppa-Lyonnet D, behalf of GEMO Study Collaborators, Giles GG, Godwin AK, Goldgar DE, González-Neira A, Greene MH, Guénel P, Haeberle L, Haiman CA, Hallberg E, Hamann U, Hansen TV, Hart S, Hartikainen JM, Hartman M, Hassan N, Healey S, Hogervorst FB, Verhoef S, HEBON, Hendricks CB, Hillemanns P, Hollestelle A, Hulick PJ, Hunter DJ, Imyanitov EN, Isaacs C, Ito H, Jakubowska A, Janavicius R, Jaworska-Bieniek K, Jensen UB, John EM, Joly Beauparlant C, Jones M, Kabisch M, Kang D, Karlan BY, Kauppila S, Kerin MJ, Khan S, Khusnutdinova E, Knight JA, Konstantopoulou I, Kraft P, Kwong A, Laitman Y, Lambrechts D, Lazaro C, Le Marchand L, Lee CN, Lee MH, Lester J, Li J, Liljegren A, Lindblom A, Lophatananon A, Lubinski J, Mai PL, Mannermaa A, Manoukian S, Margolin S, Marme F, Matsuo K, McGuffog L, Meindl A, Menegaux F, Montagna M, Muir K, Mulligan AM, Nathanson KL, Neuhausen SL, Nevanlinna H, Newcomb PA, Nord S, Nussbaum RL, Offit K, Olah E, Olopade OI, Olswold C, Osorio A, Papi L, Park-Simon TW, Paulsson-Karlsson Y, Peeters S, Peissel B, Peterlongo P, Peto J, Pfeiler G, Phelan CM, Presneau N, Radice P, Rahman N, Ramus SJ, Rashid MU, Rennert G, Rhiem K, Rudolph A, Salani R, Sangrajrang S, Sawyer EJ, Schmidt MK, Schmutzler RK, Schoemaker MJ, Schürmann P, Seynaeve C, Shen CY, Shrubsole MJ, Shu XO, Sigurdson A, Singer CF, Slager S, Soucy P, Southey M, Steinemann D, Swerdlow A, Szabo CI, Tchatchou S, Teixeira MR, Teo SH, Terry MB, Tessier DC, Teulé A, Thomassen M, Tihomirova L, Tischkowitz M, Toland AE, Tung N, Turnbull C, van den Ouweland AM, van Rensburg EJ, Ven den Berg D, Vijai J, Wang-Gohrke S, Weitzel JN, Whittemore AS, Winqvist R, Wong TY, Wu AH, Yannoukakos D, Yu JC, Pharoah PD, Hall P, Chenevix-Trench G, KConFab, AOCS Investigators, Dunning AM, Simard J, Couch FJ, Antoniou AC, Easton DF, Zheng W
(2016) Breast Cancer Res 18: 64
MeSH Terms: Alleles, BRCA1 Protein, Breast Neoplasms, Case-Control Studies, Chromosome Mapping, Chromosomes, Human, Pair 12, Computational Biology, Databases, Genetic, Enhancer Elements, Genetic, Epigenesis, Genetic, European Continental Ancestry Group, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Haplotypes, Heterozygote, Humans, Mutation, Odds Ratio, Polymorphism, Single Nucleotide, Population Surveillance, Promoter Regions, Genetic, Quantitative Trait Loci, Risk
Show Abstract · Added April 18, 2017
BACKGROUND - Multiple recent genome-wide association studies (GWAS) have identified a single nucleotide polymorphism (SNP), rs10771399, at 12p11 that is associated with breast cancer risk.
METHOD - We performed a fine-scale mapping study of a 700 kb region including 441 genotyped and more than 1300 imputed genetic variants in 48,155 cases and 43,612 controls of European descent, 6269 cases and 6624 controls of East Asian descent and 1116 cases and 932 controls of African descent in the Breast Cancer Association Consortium (BCAC; http://bcac.ccge.medschl.cam.ac.uk/ ), and in 15,252 BRCA1 mutation carriers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Stepwise regression analyses were performed to identify independent association signals. Data from the Encyclopedia of DNA Elements project (ENCODE) and the Cancer Genome Atlas (TCGA) were used for functional annotation.
RESULTS - Analysis of data from European descendants found evidence for four independent association signals at 12p11, represented by rs7297051 (odds ratio (OR) = 1.09, 95 % confidence interval (CI) = 1.06-1.12; P = 3 × 10(-9)), rs805510 (OR = 1.08, 95 % CI = 1.04-1.12, P = 2 × 10(-5)), and rs1871152 (OR = 1.04, 95 % CI = 1.02-1.06; P = 2 × 10(-4)) identified in the general populations, and rs113824616 (P = 7 × 10(-5)) identified in the meta-analysis of BCAC ER-negative cases and BRCA1 mutation carriers. SNPs rs7297051, rs805510 and rs113824616 were also associated with breast cancer risk at P < 0.05 in East Asians, but none of the associations were statistically significant in African descendants. Multiple candidate functional variants are located in putative enhancer sequences. Chromatin interaction data suggested that PTHLH was the likely target gene of these enhancers. Of the six variants with the strongest evidence of potential functionality, rs11049453 was statistically significantly associated with the expression of PTHLH and its nearby gene CCDC91 at P < 0.05.
CONCLUSION - This study identified four independent association signals at 12p11 and revealed potentially functional variants, providing additional insights into the underlying biological mechanism(s) for the association observed between variants at 12p11 and breast cancer risk.
0 Communities
3 Members
0 Resources
25 MeSH Terms