Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Marylyn D. Ritchie is active.

Publication


Featured researches published by Marylyn D. Ritchie.


Clinical Pharmacology & Therapeutics | 2018

Research Directions in the Clinical Implementation of Pharmacogenomics: An Overview of US Programs and Projects

Simona Volpi; Rex L. Chisholm; Patricia A. Deverka; Geoffrey S. Ginsburg; Howard J. Jacob; Melpomeni Kasapi; Howard L. McLeod; Dan M. Roden; Marc S. Williams; Eric D. Green; Laura Lyman Rodriguez; Samuel J. Aronson; Larisa H. Cavallari; Joshua C. Denny; Lynn G. Dressler; Julie A. Johnson; Teri E. Klein; J. Steven Leeder; Micheline Piquette-Miller; Minoli A. Perera; Laura J. Rasmussen-Torvik; Heidi L. Rehm; Marylyn D. Ritchie; Todd C. Skaar; Nikhil Wagle; Richard M. Weinshilboum; Kristin Weitzel; Robert Wildin; John Wilson; Teri A. Manolio

Response to a drug often differs widely among individual patients. This variability is frequently observed not only with respect to effective responses but also with adverse drug reactions. Matching patients to the drugs that are most likely to be effective and least likely to cause harm is the goal of effective therapeutics. Pharmacogenomics (PGx) holds the promise of precision medicine through elucidating the genetic determinants responsible for pharmacological outcomes and using them to guide drug selection and dosing. Here we survey the US landscape of research programs in PGx implementation, review current advances and clinical applications of PGx, summarize the obstacles that have hindered PGx implementation, and identify the critical knowledge gaps and possible studies needed to help to address them.


Pacific Symposium | 2014

Biocomputing 2014: Proceedings of the Pacific Symposium

Russ B. Altman; A. Keith Dunker; Lawrence Hunter; Tiffany Murray; Teri E. Klein; Marylyn D. Ritchie

The Pacific Symposium on Biocomputing (PSB) 2014 is an international, multidisciplinary conference for the presentation and discussion of current research in the theory and application of computational methods in problems of biological significance. Presentations are rigorously peer reviewed and are published in an archival proceedings volume. PSB 2014 will be held from January 3 7, 2014 in Kohala Coast, Hawaii. Tutorials and workshops will be offered prior to the start of the conference. PSB 2014 will bring together top researchers from the US, the Asian Pacific nations, and around the world to exchange research results and address open issues in all aspects of computational biology. It is a forum for the presentation of work in databases, algorithms, interfaces, visualization, modeling, and other computational methods, as applied to biological problems, with emphasis on applications in data-rich areas of molecular biology. The PSB has been designed to be responsive to the need for critical mass in sub-disciplines within biocomputing. For that reason, it is the only meeting whose sessions are defined dynamically each year in response to specific proposals. PSB sessions are organized by leaders of research in biocomputings hot topics. In this way, the meeting provides an early forum for serious examination of emerging methods and approaches in this rapidly changing field.


Circulation | 2018

LPA Variants Are Associated With Residual Cardiovascular Risk in Patients Receiving Statins

Wei-Qi Wei; Xiaohui Li; QiPing Feng; Michiaki Kubo; Iftikhar J. Kullo; Peggy L. Peissig; Elizabeth W. Karlson; Gail P. Jarvik; Ming Ta Michael Lee; Ning Shang; Eric A. Larson; Todd L. Edwards; Christian M. Shaffer; Jonathan D. Mosley; Shiro Maeda; Momoko Horikoshi; Marylyn D. Ritchie; Marc S. Williams; Eric B. Larson; David R. Crosslin; Sarah T. Bland; Jennifer A. Pacheco; Laura J. Rasmussen-Torvik; David Cronkite; George Hripcsak; Nancy J. Cox; Russell A. Wilke; C. Michael Stein; Jerome I. Rotter; Yukihide Momozawa

Background: Coronary heart disease (CHD) is a leading cause of death globally. Although therapy with statins decreases circulating levels of low-density lipoprotein cholesterol and the incidence of CHD, additional events occur despite statin therapy in some individuals. The genetic determinants of this residual cardiovascular risk remain unknown. Methods: We performed a 2-stage genome-wide association study of CHD events during statin therapy. We first identified 3099 cases who experienced CHD events (defined as acute myocardial infarction or the need for coronary revascularization) during statin therapy and 7681 controls without CHD events during comparable intensity and duration of statin therapy from 4 sites in the Electronic Medical Records and Genomics Network. We then sought replication of candidate variants in another 160 cases and 1112 controls from a fifth Electronic Medical Records and Genomics site, which joined the network after the initial genome-wide association study. Finally, we performed a phenome-wide association study for other traits linked to the most significant locus. Results: The meta-analysis identified 7 single nucleotide polymorphisms at a genome-wide level of significance within the LPA/PLG locus associated with CHD events on statin treatment. The most significant association was for an intronic single nucleotide polymorphism within LPA/PLG (rs10455872; minor allele frequency, 0.069; odds ratio, 1.58; 95% confidence interval, 1.35–1.86; P=2.6×10−10). In the replication cohort, rs10455872 was also associated with CHD events (odds ratio, 1.71; 95% confidence interval, 1.14–2.57; P=0.009). The association of this single nucleotide polymorphism with CHD events was independent of statin-induced change in low-density lipoprotein cholesterol (odds ratio, 1.62; 95% confidence interval, 1.17–2.24; P=0.004) and persisted in individuals with low-density lipoprotein cholesterol ⩽70 mg/dL (odds ratio, 2.43; 95% confidence interval, 1.18–4.75; P=0.015). A phenome-wide association study supported the effect of this region on coronary heart disease and did not identify noncardiovascular phenotypes. Conclusions: Genetic variations at the LPA locus are associated with CHD events during statin therapy independently of the extent of low-density lipoprotein cholesterol lowering. This finding provides support for exploring strategies targeting circulating concentrations of lipoprotein(a) to reduce CHD events in patients receiving statins.


Scientific Reports | 2018

Rare variants in drug target genes contributing to complex diseases, phenome-wide

Shefali Setia Verma; Navya Josyula; Anurag Verma; Xinyuan Zhang; Yogasudha Veturi; Frederick E. Dewey; Dustin N. Hartzel; Daniel R. Lavage; Joe Leader; Marylyn D. Ritchie; Sarah A. Pendergrass

The DrugBank database consists of ~800 genes that are well characterized drug targets. This list of genes is a useful resource for association testing. For example, loss of function (LOF) genetic variation has the potential to mimic the effect of drugs, and high impact variation in these genes can impact downstream traits. Identifying novel associations between genetic variation in these genes and a range of diseases can also uncover new uses for the drugs that target these genes. Phenome Wide Association Studies (PheWAS) have been successful in identifying genetic associations across hundreds of thousands of diseases. We have conducted a novel gene based PheWAS to test the effect of rare variants in DrugBank genes, evaluating associations between these genes and more than 500 quantitative and dichotomous phenotypes. We used whole exome sequencing data from 38,568 samples in Geisinger MyCode Community Health Initiative. We evaluated the results of this study when binning rare variants using various filters based on potential functional impact. We identified multiple novel associations, and the majority of the significant associations were driven by functionally annotated variation. Overall, this study provides a sweeping exploration of rare variant associations within functionally relevant genes across a wide range of diagnoses.


Scientific Reports | 2018

Author Correction: Rare variants in drug target genes contributing to complex diseases, phenome-wide

Shefali Setia Verma; Navya Josyula; Anurag Verma; Xinyuan Zhang; Yogasudha Veturi; Frederick E. Dewey; Dustin N. Hartzel; Daniel R. Lavage; Joe Leader; Marylyn D. Ritchie; Sarah A. Pendergrass

A correction to this article has been published and is linked from the HTML and PDF versions of this paper. The error has not been fixed in the paper.


JAMA Network Open | 2018

Exome Sequencing–Based Screening for BRCA1/2 Expected Pathogenic Variants Among Adult Biobank Participants

Kandamurugu Manickam; Adam H. Buchanan; Marci Schwartz; Miranda L. G. Hallquist; Janet Williams; Alanna Kulchak Rahm; Heather Rocha; Juliann M. Savatt; Alyson E. Evans; Loren Butry; Amanda Lazzeri; D’Andra M. Lindbuchler; Carroll N. Flansburg; Rosemary Leeming; Victor G. Vogel; Matthew S. Lebo; Heather Mason-Suares; Derick C. Hoskinson; Noura S. Abul-Husn; Frederick E. Dewey; John D. Overton; Jeffrey G. Reid; Aris Baras; Huntington F. Willard; Cara Z. McCormick; Sarath Krishnamurthy; Dustin N. Hartzel; Korey A. Kost; Daniel R. Lavage; Amy C. Sturm

Key Points Question Can population-level genomic screening identify those at risk for disease? Findings In this cross-sectional study of an unselected population cohort of 50u2009726 adults who underwent exome sequencing, pathogenic and likely pathogenic BRCA1 and BRCA2 variants were found in a higher proportion of patients than was previously reported. Meaning Current methods to identify BRCA1/2 variant carriers may not be sufficient as a screening tool; population genomic screening for hereditary breast and ovarian cancer may better identify patients at high risk and provide an intervention opportunity to reduce mortality and morbidity.


Proceedings of the Pacific Symposium | 2014

ERRATUM: NEXT-GENERATION ANALYSIS OF CATARACTS: DETERMINING KNOWLEDGE DRIVEN GENE-GENE INTERACTIONS USING BIOFILTER, AND GENE-ENVIRONMENT INTERACTIONS USING THE PHENX TOOLKIT

Sarah A. Pendergrass; Shefali S. Verma; Molly A. Hall; Emily Rose Holzinger; Carrie B. Moore; John R. Wallace; Scott M. Dudek; Wayne Huggins; Terrie Kitchner; Carol Waudby; Richard L. Berg; Catherine A. McCarty; Marylyn D. Ritchie

This corrects the above-titled article. There was an error in the case-control label for a subset of samples. This was corrected and analyses were re-run. The thrust of the results and discussion did not change, but these results are more precise and corrected.


Annual Review of Biomedical Data Science | 2018

Large-Scale Analysis of Genetic and Clinical Patient Data

Marylyn D. Ritchie


/data/revues/00028703/unassign/S0002870317303988/ | 2018

Supplementary material : Genome-wide and candidate gene approaches of clopidogrel efficacy using pharmacodynamic and clinical end points—Rationale and design of the International Clopidogrel Pharmacogenomics Consortium (ICPC)

Thomas O. Bergmeijer; Jean-Luc Reny; Ruth Pakyz; Li Gong; Joshua P. Lewis; Eun-Young Kim; Dániel Aradi; Israel Fernandez-Cadenas; Richard B. Horenstein; Ming Ta Michael Lee; Ryan Whaley; Joan Montaner; G.F. Gensini; John H. Cleator; Kiyuk Chang; Lene Holmvang; Willibald Hochholzer; Dan M. Roden; Stefan Winter; Russ B. Altman; Dimitrios Alexopoulos; Ho-Sook Kim; Jean-Pierre Déry; Meinrad Gawaz; Kevin P. Bliden; Marco Valgimigli; Rossella Marcucci; Gianluca Campo; Elke Schaeffeler; Nadia Paarup Dridi


Archive | 2017

Electronic Health Record Phenotype in Subjects with Genetic Variants Associated with Arrhythmogenic Right Ventricular Cardiomyopathy: A Study in 30,716 Subjects with Exome Sequencing: Genotype-Phenotype Association in Incidental ARVC Genetic Findings

Christopher M. Haggerty; Cynthia A. James; Hugh Calkins; Crystal Tichnell; Joseph B. Leader; Dustin N. Hartzel; Christopher D. Nevius; Sarah A. Pendergrass; Thomas N. Person; Marci Schwartz; Marylyn D. Ritchie; David J. Carey; David H. Ledbetter; Marc S. Williams; Frederick E. Dewey; Alexander E. Lopez; John Penn; John D. Overton; Jeffrey G. Reid; Matthew S. Lebo; Heather Mason-Suares; Christina Austin-Tse; Heidi L. Rehm; Brian P. Delisle; Daniel J. Makowski; Vishal C. Mehra; Michael F. Murray; Brandon K Fornwalt

Collaboration


Dive into the Marylyn D. Ritchie's collaboration.

Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Sarah A. Pendergrass

Pennsylvania State University

View shared research outputs
Top Co-Authors

Avatar

Dan M. Roden

Vanderbilt University Medical Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Top Co-Authors

Avatar

Anurag Verma

University of Pennsylvania

View shared research outputs
Top Co-Authors

Avatar

C. Michael Stein

Vanderbilt University Medical Center

View shared research outputs
Top Co-Authors

Avatar
Top Co-Authors

Avatar
Researchain Logo
Decentralizing Knowledge