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 2776

Publication Record

Connections

Predictive Accuracy of a Polygenic Risk Score Compared With a Clinical Risk Score for Incident Coronary Heart Disease.
Mosley JD, Gupta DK, Tan J, Yao J, Wells QS, Shaffer CM, Kundu S, Robinson-Cohen C, Psaty BM, Rich SS, Post WS, Guo X, Rotter JI, Roden DM, Gerszten RE, Wang TJ
(2020) JAMA 323: 627-635
MeSH Terms: Aged, Cohort Studies, Coronary Disease, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Incidence, Male, Middle Aged, Multifactorial Inheritance, Myocardial Infarction, Odds Ratio, Phenotype, Polymorphism, Single Nucleotide, Predictive Value of Tests, Proportional Hazards Models, Retrospective Studies, Risk, Risk Assessment
Show Abstract · Added March 24, 2020
Importance - Polygenic risk scores comprising millions of single-nucleotide polymorphisms (SNPs) could be useful for population-wide coronary heart disease (CHD) screening.
Objective - To determine whether a polygenic risk score improves prediction of CHD compared with a guideline-recommended clinical risk equation.
Design, Setting, and Participants - A retrospective cohort study of the predictive accuracy of a previously validated polygenic risk score was assessed among 4847 adults of white European ancestry, aged 45 through 79 years, participating in the Atherosclerosis Risk in Communities (ARIC) study and 2390 participating in the Multi-Ethnic Study of Atherosclerosis (MESA) from 1996 through December 31, 2015, the final day of follow-up. The performance of the polygenic risk score was compared with that of the 2013 American College of Cardiology and American Heart Association pooled cohort equations.
Exposures - Genetic risk was computed for each participant by summing the product of the weights and allele dosage across 6 630 149 SNPs. Weights were based on an international genome-wide association study.
Main Outcomes and Measures - Prediction of 10-year first CHD events (including myocardial infarctions, fatal coronary events, silent infarctions, revascularization procedures, or resuscitated cardiac arrest) assessed using measures of model discrimination, calibration, and net reclassification improvement (NRI).
Results - The study population included 4847 adults from the ARIC study (mean [SD] age, 62.9 [5.6] years; 56.4% women) and 2390 adults from the MESA cohort (mean [SD] age, 61.8 [9.6] years; 52.2% women). Incident CHD events occurred in 696 participants (14.4%) and 227 participants (9.5%), respectively, over median follow-up of 15.5 years (interquartile range [IQR], 6.3 years) and 14.2 (IQR, 2.5 years) years. The polygenic risk score was significantly associated with 10-year CHD incidence in ARIC with hazard ratios per SD increment of 1.24 (95% CI, 1.15 to 1.34) and in MESA, 1.38 (95% CI, 1.21 to 1.58). Addition of the polygenic risk score to the pooled cohort equations did not significantly increase the C statistic in either cohort (ARIC, change in C statistic, -0.001; 95% CI, -0.009 to 0.006; MESA, 0.021; 95% CI, -0.0004 to 0.043). At the 10-year risk threshold of 7.5%, the addition of the polygenic risk score to the pooled cohort equations did not provide significant improvement in reclassification in either ARIC (NRI, 0.018, 95% CI, -0.012 to 0.036) or MESA (NRI, 0.001, 95% CI, -0.038 to 0.076). The polygenic risk score did not significantly improve calibration in either cohort.
Conclusions and Relevance - In this analysis of 2 cohorts of US adults, the polygenic risk score was associated with incident coronary heart disease events but did not significantly improve discrimination, calibration, or risk reclassification compared with conventional predictors. These findings suggest that a polygenic risk score may not enhance risk prediction in a general, white middle-aged population.
0 Communities
1 Members
0 Resources
MeSH Terms
Surveillance of Gastric Intestinal Metaplasia.
Shah SC, Gawron AJ, Li D
(2020) Am J Gastroenterol 115: 641-644
MeSH Terms: Cause of Death, Gastric Mucosa, Global Health, Humans, Morbidity, Patient Selection, Population Surveillance, Precancerous Conditions, Risk Assessment, Stomach Neoplasms, Survival Rate
Added March 3, 2020
0 Communities
1 Members
0 Resources
11 MeSH Terms
Spotlight: Gastric Intestinal Metaplasia.
Shah SC, Gupta S, Li D, Morgan D, Mustafa RA, Gawron AJ
(2020) Gastroenterology 158: 704
MeSH Terms: Algorithms, Biopsy, Endoscopy, Gastrointestinal, Gastric Mucosa, Helicobacter Infections, Helicobacter pylori, Humans, Metaplasia, Population Surveillance, Practice Guidelines as Topic, Precancerous Conditions, Risk Factors, Stomach Neoplasms
Added March 3, 2020
0 Communities
1 Members
0 Resources
13 MeSH Terms
Cardiovascular Effects of Androgen Deprivation Therapy in Prostate Cancer: Contemporary Meta-Analyses.
Hu JR, Duncan MS, Morgans AK, Brown JD, Meijers WC, Freiberg MS, Salem JE, Beckman JA, Moslehi JJ
(2020) Arterioscler Thromb Vasc Biol 40: e55-e64
MeSH Terms: Androgen Antagonists, Antineoplastic Agents, Hormonal, Cardiotoxicity, Cardiovascular Diseases, Cardiovascular System, Humans, Male, Prostatic Neoplasms, Risk Assessment, Risk Factors, Treatment Outcome
Show Abstract · Added May 29, 2020
Androgen deprivation therapy is a cornerstone of prostate cancer treatment. Pharmacological androgen deprivation includes gonadotropin-releasing hormone agonism and antagonism, androgen receptor inhibition, and CYP17 (cytochrome P450 17A1) inhibition. Studies in the past decade have raised concerns about the potential for androgen deprivation therapy to increase the risk of adverse cardiovascular events such as myocardial infarction, stroke, and cardiovascular mortality, possibly by exacerbating cardiovascular risk factors. In this review, we summarize existing data on the cardiovascular effects of androgen deprivation therapy. Among the therapies, abiraterone stands out for increasing risk of cardiac events in meta-analyses of both randomized controlled trials and observational studies. We find a divergence between observational studies, which show consistent positive associations between androgen deprivation therapy use and cardiovascular disease, and randomized controlled trials, which do not show these associations reproducibly.
0 Communities
1 Members
0 Resources
11 MeSH Terms
Proton minibeams-a springboard for physics, biology and clinical creativity.
Dilmanian FA, Venkatesulu BP, Sahoo N, Wu X, Nassimi JR, Herchko S, Lu J, Dwarakanath BS, Eley JG, Krishnan S
(2020) Br J Radiol 93: 20190332
MeSH Terms: Absorption, Radiation, Algorithms, Creativity, Dose Fractionation, Radiation, Feasibility Studies, Humans, Monte Carlo Method, Neoplasms, Organ Sparing Treatments, Organs at Risk, Proton Therapy, Radiobiology, Radiometry
Show Abstract · Added March 30, 2020
Proton minibeam therapy (PMBT) is a form of spatially fractionated radiotherapy wherein broad beam radiation is replaced with segmented minibeams-either parallel, planar minibeam arrays generated by a multislit collimator or scanned pencil beams that converge laterally at depth to create a uniform dose layer at the tumor. By doing so, the spatial pattern of entrance dose is considerably modified while still maintaining tumor dose and efficacy. Recent studies using computational modeling, phantom experiments, and preclinical models, and early clinical feasibility assessments suggest that unique physical and biological attributes of PMBT can be exploited for future clinical benefit. We outline some of the guiding principle of PMBT in this concise overview of this emerging area of preclinical and clinical research inquiry.
0 Communities
1 Members
0 Resources
MeSH Terms
Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes.
Fachal L, Aschard H, Beesley J, Barnes DR, Allen J, Kar S, Pooley KA, Dennis J, Michailidou K, Turman C, Soucy P, Lemaçon A, Lush M, Tyrer JP, Ghoussaini M, Moradi Marjaneh M, Jiang X, Agata S, Aittomäki K, Alonso MR, Andrulis IL, Anton-Culver H, Antonenkova NN, Arason A, Arndt V, Aronson KJ, Arun BK, Auber B, Auer PL, Azzollini J, Balmaña J, Barkardottir RB, Barrowdale D, Beeghly-Fadiel A, Benitez J, Bermisheva M, Białkowska K, Blanco AM, Blomqvist C, Blot W, Bogdanova NV, Bojesen SE, Bolla MK, Bonanni B, Borg A, Bosse K, Brauch H, Brenner H, Briceno I, Brock IW, Brooks-Wilson A, Brüning T, Burwinkel B, Buys SS, Cai Q, Caldés T, Caligo MA, Camp NJ, Campbell I, Canzian F, Carroll JS, Carter BD, Castelao JE, Chiquette J, Christiansen H, Chung WK, Claes KBM, Clarke CL, GEMO Study Collaborators, EMBRACE Collaborators, Collée JM, Cornelissen S, Couch FJ, Cox A, Cross SS, Cybulski C, Czene K, Daly MB, de la Hoya M, Devilee P, Diez O, Ding YC, Dite GS, Domchek SM, Dörk T, Dos-Santos-Silva I, Droit A, Dubois S, Dumont M, Duran M, Durcan L, Dwek M, Eccles DM, Engel C, Eriksson M, Evans DG, Fasching PA, Fletcher O, Floris G, Flyger H, Foretova L, Foulkes WD, Friedman E, Fritschi L, Frost D, Gabrielson M, Gago-Dominguez M, Gambino G, Ganz PA, Gapstur SM, Garber J, García-Sáenz JA, Gaudet MM, Georgoulias V, Giles GG, Glendon G, Godwin AK, Goldberg MS, Goldgar DE, González-Neira A, Tibiletti MG, Greene MH, Grip M, Gronwald J, Grundy A, Guénel P, Hahnen E, Haiman CA, Håkansson N, Hall P, Hamann U, Harrington PA, Hartikainen JM, Hartman M, He W, Healey CS, Heemskerk-Gerritsen BAM, Heyworth J, Hillemanns P, Hogervorst FBL, Hollestelle A, Hooning MJ, Hopper JL, Howell A, Huang G, Hulick PJ, Imyanitov EN, KConFab Investigators, HEBON Investigators, ABCTB Investigators, Isaacs C, Iwasaki M, Jager A, Jakimovska M, Jakubowska A, James PA, Janavicius R, Jankowitz RC, John EM, Johnson N, Jones ME, Jukkola-Vuorinen A, Jung A, Kaaks R, Kang D, Kapoor PM, Karlan BY, Keeman R, Kerin MJ, Khusnutdinova E, Kiiski JI, Kirk J, Kitahara CM, Ko YD, Konstantopoulou I, Kosma VM, Koutros S, Kubelka-Sabit K, Kwong A, Kyriacou K, Laitman Y, Lambrechts D, Lee E, Leslie G, Lester J, Lesueur F, Lindblom A, Lo WY, Long J, Lophatananon A, Loud JT, Lubiński J, MacInnis RJ, Maishman T, Makalic E, Mannermaa A, Manoochehri M, Manoukian S, Margolin S, Martinez ME, Matsuo K, Maurer T, Mavroudis D, Mayes R, McGuffog L, McLean C, Mebirouk N, Meindl A, Miller A, Miller N, Montagna M, Moreno F, Muir K, Mulligan AM, Muñoz-Garzon VM, Muranen TA, Narod SA, Nassir R, Nathanson KL, Neuhausen SL, Nevanlinna H, Neven P, Nielsen FC, Nikitina-Zake L, Norman A, Offit K, Olah E, Olopade OI, Olsson H, Orr N, Osorio A, Pankratz VS, Papp J, Park SK, Park-Simon TW, Parsons MT, Paul J, Pedersen IS, Peissel B, Peshkin B, Peterlongo P, Peto J, Plaseska-Karanfilska D, Prajzendanc K, Prentice R, Presneau N, Prokofyeva D, Pujana MA, Pylkäs K, Radice P, Ramus SJ, Rantala J, Rau-Murthy R, Rennert G, Risch HA, Robson M, Romero A, Rossing M, Saloustros E, Sánchez-Herrero E, Sandler DP, Santamariña M, Saunders C, Sawyer EJ, Scheuner MT, Schmidt DF, Schmutzler RK, Schneeweiss A, Schoemaker MJ, Schöttker B, Schürmann P, Scott C, Scott RJ, Senter L, Seynaeve CM, Shah M, Sharma P, Shen CY, Shu XO, Singer CF, Slavin TP, Smichkoska S, Southey MC, Spinelli JJ, Spurdle AB, Stone J, Stoppa-Lyonnet D, Sutter C, Swerdlow AJ, Tamimi RM, Tan YY, Tapper WJ, Taylor JA, Teixeira MR, Tengström M, Teo SH, Terry MB, Teulé A, Thomassen M, Thull DL, Tischkowitz M, Toland AE, Tollenaar RAEM, Tomlinson I, Torres D, Torres-Mejía G, Troester MA, Truong T, Tung N, Tzardi M, Ulmer HU, Vachon CM, van Asperen CJ, van der Kolk LE, van Rensburg EJ, Vega A, Viel A, Vijai J, Vogel MJ, Wang Q, Wappenschmidt B, Weinberg CR, Weitzel JN, Wendt C, Wildiers H, Winqvist R, Wolk A, Wu AH, Yannoukakos D, Zhang Y, Zheng W, Hunter D, Pharoah PDP, Chang-Claude J, García-Closas M, Schmidt MK, Milne RL, Kristensen VN, French JD, Edwards SL, Antoniou AC, Chenevix-Trench G, Simard J, Easton DF, Kraft P, Dunning AM
(2020) Nat Genet 52: 56-73
MeSH Terms: Bayes Theorem, Biomarkers, Tumor, Breast Neoplasms, Chromosome Mapping, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Linkage Disequilibrium, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Regulatory Sequences, Nucleic Acid, Risk Factors
Show Abstract · Added March 3, 2020
Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.
0 Communities
1 Members
0 Resources
13 MeSH Terms
Advancing the Science in Gastric Pre-Neoplasia: Study Design Considerations.
Davitkov P, Altayar O, Shah SC, Gawron AJ, Mustafa RA, Sultan S, Morgan DR
(2020) Gastroenterology 158: 751-759
MeSH Terms: Biomedical Research, Biopsy, Endoscopy, Gastrointestinal, Gastric Mucosa, Humans, Incidence, Metaplasia, Population Surveillance, Precancerous Conditions, Prevalence, Research Design, Risk Factors, Stomach Neoplasms
Added March 3, 2020
0 Communities
1 Members
0 Resources
13 MeSH Terms
AGA Technical Review on Gastric Intestinal Metaplasia-Epidemiology and Risk Factors.
Altayar O, Davitkov P, Shah SC, Gawron AJ, Morgan DR, Turner K, Mustafa RA
(2020) Gastroenterology 158: 732-744.e16
MeSH Terms: Ethnic Groups, European Continental Ancestry Group, Gastric Mucosa, Helicobacter Infections, Helicobacter pylori, Humans, Metaplasia, Precancerous Conditions, Risk Factors, Stomach Neoplasms, United States
Added March 3, 2020
0 Communities
1 Members
0 Resources
11 MeSH Terms
AGA Technical Review on Gastric Intestinal Metaplasia-Natural History and Clinical Outcomes.
Gawron AJ, Shah SC, Altayar O, Davitkov P, Morgan D, Turner K, Mustafa RA
(2020) Gastroenterology 158: 705-731.e5
MeSH Terms: Biopsy, Disease Progression, Endoscopy, Gastrointestinal, Gastric Mucosa, Helicobacter Infections, Helicobacter pylori, Humans, Metaplasia, Population Surveillance, Precancerous Conditions, Prevalence, Risk Factors, Stomach Neoplasms, United States
Added March 3, 2020
0 Communities
1 Members
0 Resources
14 MeSH Terms
Cancer Treatment-Associated Pericardial Disease: Epidemiology, Clinical Presentation, Diagnosis, and Management.
Ala CK, Klein AL, Moslehi JJ
(2019) Curr Cardiol Rep 21: 156
MeSH Terms: Antineoplastic Agents, Immunological, Cardiotoxicity, Cardiovascular Diseases, Humans, Immunotherapy, Neoplasms, Pericarditis, Pericardium, Risk Factors
Show Abstract · Added January 15, 2020
PURPOSE OF REVIEW - Cancer therapeutics have seen tremendous growth in the last decade and have been effective in the treatment of several cancer types. However, with advanced therapies like kinase inhibitors and immunotherapies, there have been unintended consequences of cardiotoxicities. While traditional chemotherapy and radiation-induced cardiotoxicity have been well studied, further research is needed to understand the adverse effects of newer regimens.
RECENT FINDINGS - Both immune-mediated and non-immune-medicated cytotoxicity have been noted with targeted therapies such as tyrosine kinase inhibitors and immune checkpoint inhibitors. In this manuscript, we describe the pericardial syndromes associated with cancer therapies and propose management strategies. Pericardial effusion and pericarditis are common presentations in cancer patients and often difficult to diagnose. Concomitant myocarditis may also present with pericardial toxicity, especially with immunotherapies. In addition to proper history and physical, additional testing such as cardiovascular imaging and tissue histology need to be obtained as appropriate. Holding the offending oncology drug, and institution of anti-inflammatory medications, and immunosuppressants such as steroids are indicated. A high index of suspicion, use of standardized definitions, and comprehensive evaluation are needed for early identification, appropriate treatment, and better outcomes for patients with cancer treatment-associated pericardial disease. Further research is needed to understand the pathophysiology and to evaluate how the management of pericardial conditions in these patients differ from traditional management and also evaluate new therapies.
0 Communities
1 Members
0 Resources
9 MeSH Terms