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Items: 1 to 50 of 85

1.

A phenome-wide association study (PheWAS) in the Population Architecture using Genomics and Epidemiology (PAGE) study reveals potential pleiotropy in African Americans.

Pendergrass SA, Buyske S, Jeff JM, Frase A, Dudek S, Bradford Y, Ambite JL, Avery CL, Buzkova P, Deelman E, Fesinmeyer MD, Haiman C, Heiss G, Hindorff LA, Hsu CN, Jackson RD, Lin Y, Le Marchand L, Matise TC, Monroe KR, Moreland L, North KE, Park SL, Reiner A, Wallace R, Wilkens LR, Kooperberg C, Ritchie MD, Crawford DC.

PLoS One. 2019 Dec 31;14(12):e0226771. doi: 10.1371/journal.pone.0226771. eCollection 2019.

2.

Target genes, variants, tissues and transcriptional pathways influencing human serum urate levels.

Tin A, Marten J, Halperin Kuhns VL, Li Y, Wuttke M, Kirsten H, Sieber KB, Qiu C, Gorski M, Yu Z, Giri A, Sveinbjornsson G, Li M, Chu AY, Hoppmann A, O'Connor LJ, Prins B, Nutile T, Noce D, Akiyama M, Cocca M, Ghasemi S, van der Most PJ, Horn K, Xu Y, Fuchsberger C, Sedaghat S, Afaq S, Amin N, Ärnlöv J, Bakker SJL, Bansal N, Baptista D, Bergmann S, Biggs ML, Biino G, Boerwinkle E, Bottinger EP, Boutin TS, Brumat M, Burkhardt R, Campana E, Campbell A, Campbell H, Carroll RJ, Catamo E, Chambers JC, Ciullo M, Concas MP, Coresh J, Corre T, Cusi D, Felicita SC, de Borst MH, De Grandi A, de Mutsert R, de Vries APJ, Delgado G, Demirkan A, Devuyst O, Dittrich K, Eckardt KU, Ehret G, Endlich K, Evans MK, Gansevoort RT, Gasparini P, Giedraitis V, Gieger C, Girotto G, Gögele M, Gordon SD, Gudbjartsson DF, Gudnason V; German Chronic Kidney Disease Study, Haller T, Hamet P, Harris TB, Hayward C, Hicks AA, Hofer E, Holm H, Huang W, Hutri-Kähönen N, Hwang SJ, Ikram MA, Lewis RM, Ingelsson E, Jakobsdottir J, Jonsdottir I, Jonsson H, Joshi PK, Josyula NS, Jung B, Kähönen M, Kamatani Y, Kanai M, Kerr SM, Kiess W, Kleber ME, Koenig W, Kooner JS, Körner A, Kovacs P, Krämer BK, Kronenberg F, Kubo M, Kühnel B, La Bianca M, Lange LA, Lehne B, Lehtimäki T; Lifelines Cohort Study, Liu J, Loeffler M, Loos RJF, Lyytikäinen LP, Magi R, Mahajan A, Martin NG, März W, Mascalzoni D, Matsuda K, Meisinger C, Meitinger T, Metspalu A, Milaneschi Y; V. A. Million Veteran Program, O'Donnell CJ, Wilson OD, Gaziano JM, Mishra PP, Mohlke KL, Mononen N, Montgomery GW, Mook-Kanamori DO, Müller-Nurasyid M, Nadkarni GN, Nalls MA, Nauck M, Nikus K, Ning B, Nolte IM, Noordam R, O'Connell JR, Olafsson I, Padmanabhan S, Penninx BWJH, Perls T, Peters A, Pirastu M, Pirastu N, Pistis G, Polasek O, Ponte B, Porteous DJ, Poulain T, Preuss MH, Rabelink TJ, Raffield LM, Raitakari OT, Rettig R, Rheinberger M, Rice KM, Rizzi F, Robino A, Rudan I, Krajcoviechova A, Cifkova R, Rueedi R, Ruggiero D, Ryan KA, Saba Y, Salvi E, Schmidt H, Schmidt R, Shaffer CM, Smith AV, Smith BH, Spracklen CN, Strauch K, Stumvoll M, Sulem P, Tajuddin SM, Teren A, Thiery J, Thio CHL, Thorsteinsdottir U, Toniolo D, Tönjes A, Tremblay J, Uitterlinden AG, Vaccargiu S, van der Harst P, van Duijn CM, Verweij N, Völker U, Vollenweider P, Waeber G, Waldenberger M, Whitfield JB, Wild SH, Wilson JF, Yang Q, Zhang W, Zonderman AB, Bochud M, Wilson JG, Pendergrass SA, Ho K, Parsa A, Pramstaller PP, Psaty BM, Böger CA, Snieder H, Butterworth AS, Okada Y, Edwards TL, Stefansson K, Susztak K, Scholz M, Heid IM, Hung AM, Teumer A, Pattaro C, Woodward OM, Vitart V, Köttgen A.

Nat Genet. 2019 Oct;51(10):1459-1474. doi: 10.1038/s41588-019-0504-x. Epub 2019 Oct 2.

3.

Genome-wide association meta-analyses and fine-mapping elucidate pathways influencing albuminuria.

Teumer A, Li Y, Ghasemi S, Prins BP, Wuttke M, Hermle T, Giri A, Sieber KB, Qiu C, Kirsten H, Tin A, Chu AY, Bansal N, Feitosa MF, Wang L, Chai JF, Cocca M, Fuchsberger C, Gorski M, Hoppmann A, Horn K, Li M, Marten J, Noce D, Nutile T, Sedaghat S, Sveinbjornsson G, Tayo BO, van der Most PJ, Xu Y, Yu Z, Gerstner L, Ärnlöv J, Bakker SJL, Baptista D, Biggs ML, Boerwinkle E, Brenner H, Burkhardt R, Carroll RJ, Chee ML, Chee ML, Chen M, Cheng CY, Cook JP, Coresh J, Corre T, Danesh J, de Borst MH, De Grandi A, de Mutsert R, de Vries APJ, Degenhardt F, Dittrich K, Divers J, Eckardt KU, Ehret G, Endlich K, Felix JF, Franco OH, Franke A, Freedman BI, Freitag-Wolf S, Gansevoort RT, Giedraitis V, Gögele M, Grundner-Culemann F, Gudbjartsson DF, Gudnason V, Hamet P, Harris TB, Hicks AA, Holm H, Foo VHX, Hwang SJ, Ikram MA, Ingelsson E, Jaddoe VWV, Jakobsdottir J, Josyula NS, Jung B, Kähönen M, Khor CC, Kiess W, Koenig W, Körner A, Kovacs P, Kramer H, Krämer BK, Kronenberg F, Lange LA, Langefeld CD, Lee JJ, Lehtimäki T, Lieb W, Lim SC, Lind L, Lindgren CM, Liu J, Loeffler M, Lyytikäinen LP, Mahajan A, Maranville JC, Mascalzoni D, McMullen B, Meisinger C, Meitinger T, Miliku K, Mook-Kanamori DO, Müller-Nurasyid M, Mychaleckyj JC, Nauck M, Nikus K, Ning B, Noordam R, Connell JO, Olafsson I, Palmer ND, Peters A, Podgornaia AI, Ponte B, Poulain T, Pramstaller PP, Rabelink TJ, Raffield LM, Reilly DF, Rettig R, Rheinberger M, Rice KM, Rivadeneira F, Runz H, Ryan KA, Sabanayagam C, Saum KU, Schöttker B, Shaffer CM, Shi Y, Smith AV, Strauch K, Stumvoll M, Sun BB, Szymczak S, Tai ES, Tan NYQ, Taylor KD, Teren A, Tham YC, Thiery J, Thio CHL, Thomsen H, Thorsteinsdottir U, Tönjes A, Tremblay J, Uitterlinden AG, van der Harst P, Verweij N, Vogelezang S, Völker U, Waldenberger M, Wang C, Wilson OD, Wong C, Wong TY, Yang Q, Yasuda M, Akilesh S, Bochud M, Böger CA, Devuyst O, Edwards TL, Ho K, Morris AP, Parsa A, Pendergrass SA, Psaty BM, Rotter JI, Stefansson K, Wilson JG, Susztak K, Snieder H, Heid IM, Scholz M, Butterworth AS, Hung AM, Pattaro C, Köttgen A.

Nat Commun. 2019 Sep 11;10(1):4130. doi: 10.1038/s41467-019-11576-0.

4.

Dissecting genetic factors affecting phenylephrine infusion rates during anesthesia: a genome-wide association study employing EHR data.

Zhang Y, Poler SM, Li J, Abedi V, Pendergrass SA, Williams MS, Lee MTM.

BMC Med. 2019 Aug 28;17(1):168. doi: 10.1186/s12916-019-1405-7.

5.

A Trans-Ethnic Genome-Wide Association Study of Uterine Fibroids.

Edwards TL, Giri A, Hellwege JN, Hartmann KE, Stewart EA, Jeff JM, Bray MJ, Pendergrass SA, Torstenson ES, Keaton JM, Jones SH, Gogoi RP, Kuivaniemi H, Jackson KL, Kho AN, Kullo IJ, McCarty CA, Im HK, Pacheco JA, Pathak J, Williams MS, Tromp G, Kenny EE, Peissig PL, Denny JC, Roden DM, Velez Edwards DR.

Front Genet. 2019 Jun 12;10:511. doi: 10.3389/fgene.2019.00511. eCollection 2019.

6.

A catalog of genetic loci associated with kidney function from analyses of a million individuals.

Wuttke M, Li Y, Li M, Sieber KB, Feitosa MF, Gorski M, Tin A, Wang L, Chu AY, Hoppmann A, Kirsten H, Giri A, Chai JF, Sveinbjornsson G, Tayo BO, Nutile T, Fuchsberger C, Marten J, Cocca M, Ghasemi S, Xu Y, Horn K, Noce D, van der Most PJ, Sedaghat S, Yu Z, Akiyama M, Afaq S, Ahluwalia TS, Almgren P, Amin N, Ärnlöv J, Bakker SJL, Bansal N, Baptista D, Bergmann S, Biggs ML, Biino G, Boehnke M, Boerwinkle E, Boissel M, Bottinger EP, Boutin TS, Brenner H, Brumat M, Burkhardt R, Butterworth AS, Campana E, Campbell A, Campbell H, Canouil M, Carroll RJ, Catamo E, Chambers JC, Chee ML, Chee ML, Chen X, Cheng CY, Cheng Y, Christensen K, Cifkova R, Ciullo M, Concas MP, Cook JP, Coresh J, Corre T, Sala CF, Cusi D, Danesh J, Daw EW, de Borst MH, De Grandi A, de Mutsert R, de Vries APJ, Degenhardt F, Delgado G, Demirkan A, Di Angelantonio E, Dittrich K, Divers J, Dorajoo R, Eckardt KU, Ehret G, Elliott P, Endlich K, Evans MK, Felix JF, Foo VHX, Franco OH, Franke A, Freedman BI, Freitag-Wolf S, Friedlander Y, Froguel P, Gansevoort RT, Gao H, Gasparini P, Gaziano JM, Giedraitis V, Gieger C, Girotto G, Giulianini F, Gögele M, Gordon SD, Gudbjartsson DF, Gudnason V, Haller T, Hamet P, Harris TB, Hartman CA, Hayward C, Hellwege JN, Heng CK, Hicks AA, Hofer E, Huang W, Hutri-Kähönen N, Hwang SJ, Ikram MA, Indridason OS, Ingelsson E, Ising M, Jaddoe VWV, Jakobsdottir J, Jonas JB, Joshi PK, Josyula NS, Jung B, Kähönen M, Kamatani Y, Kammerer CM, Kanai M, Kastarinen M, Kerr SM, Khor CC, Kiess W, Kleber ME, Koenig W, Kooner JS, Körner A, Kovacs P, Kraja AT, Krajcoviechova A, Kramer H, Krämer BK, Kronenberg F, Kubo M, Kühnel B, Kuokkanen M, Kuusisto J, La Bianca M, Laakso M, Lange LA, Langefeld CD, Lee JJ, Lehne B, Lehtimäki T, Lieb W; Lifelines Cohort Study, Lim SC, Lind L, Lindgren CM, Liu J, Liu J, Loeffler M, Loos RJF, Lucae S, Lukas MA, Lyytikäinen LP, Mägi R, Magnusson PKE, Mahajan A, Martin NG, Martins J, März W, Mascalzoni D, Matsuda K, Meisinger C, Meitinger T, Melander O, Metspalu A, Mikaelsdottir EK, Milaneschi Y, Miliku K, Mishra PP; V. A. Million Veteran Program, Mohlke KL, Mononen N, Montgomery GW, Mook-Kanamori DO, Mychaleckyj JC, Nadkarni GN, Nalls MA, Nauck M, Nikus K, Ning B, Nolte IM, Noordam R, O'Connell J, O'Donoghue ML, Olafsson I, Oldehinkel AJ, Orho-Melander M, Ouwehand WH, Padmanabhan S, Palmer ND, Palsson R, Penninx BWJH, Perls T, Perola M, Pirastu M, Pirastu N, Pistis G, Podgornaia AI, Polasek O, Ponte B, Porteous DJ, Poulain T, Pramstaller PP, Preuss MH, Prins BP, Province MA, Rabelink TJ, Raffield LM, Raitakari OT, Reilly DF, Rettig R, Rheinberger M, Rice KM, Ridker PM, Rivadeneira F, Rizzi F, Roberts DJ, Robino A, Rossing P, Rudan I, Rueedi R, Ruggiero D, Ryan KA, Saba Y, Sabanayagam C, Salomaa V, Salvi E, Saum KU, Schmidt H, Schmidt R, Schöttker B, Schulz CA, Schupf N, Shaffer CM, Shi Y, Smith AV, Smith BH, Soranzo N, Spracklen CN, Strauch K, Stringham HM, Stumvoll M, Svensson PO, Szymczak S, Tai ES, Tajuddin SM, Tan NYQ, Taylor KD, Teren A, Tham YC, Thiery J, Thio CHL, Thomsen H, Thorleifsson G, Toniolo D, Tönjes A, Tremblay J, Tzoulaki I, Uitterlinden AG, Vaccargiu S, van Dam RM, van der Harst P, van Duijn CM, Velez Edward DR, Verweij N, Vogelezang S, Völker U, Vollenweider P, Waeber G, Waldenberger M, Wallentin L, Wang YX, Wang C, Waterworth DM, Bin Wei W, White H, Whitfield JB, Wild SH, Wilson JF, Wojczynski MK, Wong C, Wong TY, Xu L, Yang Q, Yasuda M, Yerges-Armstrong LM, Zhang W, Zonderman AB, Rotter JI, Bochud M, Psaty BM, Vitart V, Wilson JG, Dehghan A, Parsa A, Chasman DI, Ho K, Morris AP, Devuyst O, Akilesh S, Pendergrass SA, Sim X, Böger CA, Okada Y, Edwards TL, Snieder H, Stefansson K, Hung AM, Heid IM, Scholz M, Teumer A, Köttgen A, Pattaro C.

Nat Genet. 2019 Jun;51(6):957-972. doi: 10.1038/s41588-019-0407-x. Epub 2019 May 31.

7.

Detecting potential pleiotropy across cardiovascular and neurological diseases using univariate, bivariate, and multivariate methods on 43,870 individuals from the eMERGE network.

Zhang X, Veturi Y, Verma S, Bone W, Verma A, Lucas A, Hebbring S, Denny JC, Stanaway IB, Jarvik GP, Crosslin D, Larson EB, Rasmussen-Torvik L, Pendergrass SA, Smoller JW, Hakonarson H, Sleiman P, Weng C, Fasel D, Wei WQ, Kullo I, Schaid D, Chung WK, Ritchie MD.

Pac Symp Biocomput. 2019;24:272-283.

8.

A phenome-wide association study to discover pleiotropic effects of PCSK9, APOB, and LDLR.

Safarova MS, Satterfield BA, Fan X, Austin EE, Ye Z, Bastarache L, Zheng N, Ritchie MD, Borthwick KM, Williams MS, Larson EB, Scrol A, Jarvik GP, Crosslin DR, Leppig K, Rasmussen-Torvik LJ, Pendergrass SA, Sturm AC, Namjou B, Shah AS, Carroll RJ, Chung WK, Wei WQ, Feng Q, Stein CM, Roden DM, Manolio TA, Schaid DJ, Denny JC, Hebbring SJ, de Andrade M, Kullo IJ.

NPJ Genom Med. 2019 Feb 11;4:3. doi: 10.1038/s41525-019-0078-7. eCollection 2019.

9.

Real world scenarios in rare variant association analysis: the impact of imbalance and sample size on the power in silico.

Zhang X, Basile AO, Pendergrass SA, Ritchie MD.

BMC Bioinformatics. 2019 Jan 22;20(1):46. doi: 10.1186/s12859-018-2591-6.

10.

The importance of buprenorphine research in the opioid crisis.

Pendergrass SA, Crist RC, Jones LK, Hoch JR, Berrettini WH.

Mol Psychiatry. 2019 May;24(5):626-632. doi: 10.1038/s41380-018-0329-5. Epub 2019 Jan 7.

PMID:
30617273
11.

Human-Disease Phenotype Map Derived from PheWAS across 38,682 Individuals.

Verma A, Bang L, Miller JE, Zhang Y, Lee MTM, Zhang Y, Byrska-Bishop M, Carey DJ, Ritchie MD, Pendergrass SA, Kim D; DiscovEHR Collaboration.

Am J Hum Genet. 2019 Jan 3;104(1):55-64. doi: 10.1016/j.ajhg.2018.11.006. Epub 2018 Dec 29.

12.

Using Electronic Health Records To Generate Phenotypes For Research.

Pendergrass SA, Crawford DC.

Curr Protoc Hum Genet. 2019 Jan;100(1):e80. doi: 10.1002/cphg.80. Epub 2018 Dec 5.

13.

Unfolding of hidden white blood cell count phenotypes for gene discovery using latent class mixed modeling.

Hall TO, Stanaway IB, Carrell DS, Carroll RJ, Denny JC, Hakonarson H, Larson EB, Mentch FD, Peissig PL, Pendergrass SA, Rosenthal EA, Jarvik GP, Crosslin DR.

Genes Immun. 2019 Sep;20(7):555-565. doi: 10.1038/s41435-018-0051-y. Epub 2018 Nov 21.

14.

Using Adipose Measures from Health Care Provider-Based Imaging Data for Discovery.

Cha EDK, Veturi Y, Agarwal C, Patel A, Arbabshirani MR, Pendergrass SA.

J Obes. 2018 Sep 27;2018:3253096. doi: 10.1155/2018/3253096. eCollection 2018.

15.

Healthcare Utilization and Patients' Perspectives After Receiving a Positive Genetic Test for Familial Hypercholesterolemia.

Jones LK, Kulchak Rahm A, Manickam K, Butry L, Lazzeri A, Corcoran T, Komar D, Josyula NS, Pendergrass SA, Sturm AC, Murray MF.

Circ Genom Precis Med. 2018 Aug;11(8):e002146. doi: 10.1161/CIRCGEN.118.002146.

PMID:
30354341
16.

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

Verma SS, Josyula N, Verma A, Zhang X, Veturi Y, Dewey FE, Hartzel DN, Lavage DR, Leader J, Ritchie MD, Pendergrass SA.

Sci Rep. 2018 Oct 23;8(1):15911. doi: 10.1038/s41598-018-27936-7.

17.

The eMERGE genotype set of 83,717 subjects imputed to ~40 million variants genome wide and association with the herpes zoster medical record phenotype.

Stanaway IB, Hall TO, Rosenthal EA, Palmer M, Naranbhai V, Knevel R, Namjou-Khales B, Carroll RJ, Kiryluk K, Gordon AS, Linder J, Howell KM, Mapes BM, Lin FTJ, Joo YY, Hayes MG, Gharavi AG, Pendergrass SA, Ritchie MD, de Andrade M, Croteau-Chonka DC, Raychaudhuri S, Weiss ST, Lebo M, Amr SS, Carrell D, Larson EB, Chute CG, Rasmussen-Torvik LJ, Roy-Puckelwartz MJ, Sleiman P, Hakonarson H, Li R, Karlson EW, Peterson JF, Kullo IJ, Chisholm R, Denny JC, Jarvik GP; eMERGE Network, Crosslin DR.

Genet Epidemiol. 2019 Feb;43(1):63-81. doi: 10.1002/gepi.22167. Epub 2018 Oct 8.

18.

A Phenome-Wide Association Study Uncovers a Role for Autoimmunity in the Development of Chronic Obstructive Pulmonary Disease.

Ji X, Niu X, Qian J, Martucci V, Pendergrass SA, Gorlov IP, Amos CI, Denny JC, Massion PP, Aldrich MC.

Am J Respir Cell Mol Biol. 2018 Jun;58(6):777-779. doi: 10.1165/rcmb.2017-0409LE. No abstract available.

19.

A simulation study investigating power estimates in phenome-wide association studies.

Verma A, Bradford Y, Dudek S, Lucas AM, Verma SS, Pendergrass SA, Ritchie MD.

BMC Bioinformatics. 2018 Apr 4;19(1):120. doi: 10.1186/s12859-018-2135-0.

20.

PheWAS and Beyond: The Landscape of Associations with Medical Diagnoses and Clinical Measures across 38,662 Individuals from Geisinger.

Verma A, Lucas A, Verma SS, Zhang Y, Josyula N, Khan A, Hartzel DN, Lavage DR, Leader J, Ritchie MD, Pendergrass SA.

Am J Hum Genet. 2018 Apr 5;102(4):592-608. doi: 10.1016/j.ajhg.2018.02.017. Epub 2018 Mar 29.

21.

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

Verma SS, Josyula N, Verma A, Zhang X, Veturi Y, Dewey FE, Hartzel DN, Lavage DR, Leader J, Ritchie MD, Pendergrass SA.

Sci Rep. 2018 Mar 15;8(1):4624. doi: 10.1038/s41598-018-22834-4. Erratum in: Sci Rep. 2018 Oct 23;8(1):15911.

22.

Characterizing and Managing Missing Structured Data in Electronic Health Records: Data Analysis.

Beaulieu-Jones BK, Lavage DR, Snyder JW, Moore JH, Pendergrass SA, Bauer CR.

JMIR Med Inform. 2018 Feb 23;6(1):e11. doi: 10.2196/medinform.8960.

23.

PLATO software provides analytic framework for investigating complexity beyond genome-wide association studies.

Hall MA, Wallace J, Lucas A, Kim D, Basile AO, Verma SS, McCarty CA, Brilliant MH, Peissig PL, Kitchner TE, Verma A, Pendergrass SA, Dudek SM, Moore JH, Ritchie MD.

Nat Commun. 2017 Oct 27;8(1):1167. doi: 10.1038/s41467-017-00802-2.

24.

Electronic health record phenotype in subjects with genetic variants associated with arrhythmogenic right ventricular cardiomyopathy: a study of 30,716 subjects with exome sequencing.

Haggerty CM, James CA, Calkins H, Tichnell C, Leader JB, Hartzel DN, Nevius CD, Pendergrass SA, Person TN, Schwartz M, Ritchie MD, Carey DJ, Ledbetter DH, Williams MS, Dewey FE, Lopez A, Penn J, Overton JD, Reid JG, Lebo M, Mason-Suares H, Austin-Tse C, Rehm HL, Delisle BP, Makowski DJ, Mehra VC, Murray MF, Fornwalt BK.

Genet Med. 2017 Nov;19(11):1245-1252. doi: 10.1038/gim.2017.40. Epub 2017 May 4.

25.

Multiphenotype association study of patients randomized to initiate antiretroviral regimens in AIDS Clinical Trials Group protocol A5202.

Verma A, Bradford Y, Verma SS, Pendergrass SA, Daar ES, Venuto C, Morse GD, Ritchie MD, Haas DW.

Pharmacogenet Genomics. 2017 Mar;27(3):101-111. doi: 10.1097/FPC.0000000000000263.

26.

Distribution and clinical impact of functional variants in 50,726 whole-exome sequences from the DiscovEHR study.

Dewey FE, Murray MF, Overton JD, Habegger L, Leader JB, Fetterolf SN, O'Dushlaine C, Van Hout CV, Staples J, Gonzaga-Jauregui C, Metpally R, Pendergrass SA, Giovanni MA, Kirchner HL, Balasubramanian S, Abul-Husn NS, Hartzel DN, Lavage DR, Kost KA, Packer JS, Lopez AE, Penn J, Mukherjee S, Gosalia N, Kanagaraj M, Li AH, Mitnaul LJ, Adams LJ, Person TN, Praveen K, Marcketta A, Lebo MS, Austin-Tse CA, Mason-Suares HM, Bruse S, Mellis S, Phillips R, Stahl N, Murphy A, Economides A, Skelding KA, Still CD, Elmore JR, Borecki IB, Yancopoulos GD, Davis FD, Faucett WA, Gottesman O, Ritchie MD, Shuldiner AR, Reid JG, Ledbetter DH, Baras A, Carey DJ.

Science. 2016 Dec 23;354(6319). pii: aaf6814. doi: 10.1126/science.aaf6814.

PMID:
28008009
27.

IDENTIFYING GENETIC ASSOCIATIONS WITH VARIABILITY IN METABOLIC HEALTH AND BLOOD COUNT LABORATORY VALUES: DIVING INTO THE QUANTITATIVE TRAITS BY LEVERAGING LONGITUDINAL DATA FROM AN EHR.

Verma SS, Lucas AM, Lavage DR, Leader JB, Metpally R, Krishnamurthy S, Dewey F, Borecki I, Lopez A, Overton J, Penn J, Reid J, Pendergrass SA, Breitwieser G, Ritchie MD.

Pac Symp Biocomput. 2017;22:533-544. doi: 10.1142/9789813207813_0049.

28.

OPENING THE DOOR TO THE LARGE SCALE USE OF CLINICAL LAB MEASURES FOR ASSOCIATION TESTING: EXPLORING DIFFERENT METHODS FOR DEFINING PHENOTYPES.

Bauer CR, Lavage D, Snyder J, Leader J, Mahoney JM, Pendergrass SA.

Pac Symp Biocomput. 2017;22:356-367. doi: 10.1142/9789813207813_0034.

29.

PATTERNS IN BIOMEDICAL DATA-HOW DO WE FIND THEM?

Basile AO, Verma A, Byrska-Bishop M, Pendergrass SA, Darabos C, Lester Kirchner H.

Pac Symp Biocomput. 2017;22:177-183. doi: 10.1142/9789813207813_0018.

30.

eMERGE Phenome-Wide Association Study (PheWAS) identifies clinical associations and pleiotropy for stop-gain variants.

Verma A, Verma SS, Pendergrass SA, Crawford DC, Crosslin DR, Kuivaniemi H, Bush WS, Bradford Y, Kullo I, Bielinski SJ, Li R, Denny JC, Peissig P, Hebbring S, De Andrade M, Ritchie MD, Tromp G.

BMC Med Genomics. 2016 Aug 12;9 Suppl 1:32. doi: 10.1186/s12920-016-0191-8.

31.

Phenome-Wide Association Study to Explore Relationships between Immune System Related Genetic Loci and Complex Traits and Diseases.

Verma A, Basile AO, Bradford Y, Kuivaniemi H, Tromp G, Carey D, Gerhard GS, Crowe JE Jr, Ritchie MD, Pendergrass SA.

PLoS One. 2016 Aug 10;11(8):e0160573. doi: 10.1371/journal.pone.0160573. eCollection 2016.

32.

Evidence for extensive pleiotropy among pharmacogenes.

Oetjens MT, Bush WS, Denny JC, Birdwell K, Kodaman N, Verma A, Dilks HH, Pendergrass SA, Ritchie MD, Crawford DC.

Pharmacogenomics. 2016 Jun;17(8):853-66. doi: 10.2217/pgs-2015-0007. Epub 2016 Jun 1.

33.

Pathway analysis by randomization incorporating structure-PARIS: an update.

Butkiewicz M, Cooke Bailey JN, Frase A, Dudek S, Yaspan BL, Ritchie MD, Pendergrass SA, Haines JL.

Bioinformatics. 2016 Aug 1;32(15):2361-3. doi: 10.1093/bioinformatics/btw130. Epub 2016 Mar 7.

34.

INTEGRATING CLINICAL LABORATORY MEASURES AND ICD-9 CODE DIAGNOSES IN PHENOME-WIDE ASSOCIATION STUDIES.

Verma A, Leader JB, Verma SS, Frase A, Wallace J, Dudek S, Lavage DR, Van Hout CV, Dewey FE, Penn J, Lopez A, Overton JD, Carey DJ, Ledbetter DH, Kirchner HL, Ritchie MD, Pendergrass SA.

Pac Symp Biocomput. 2016;21:168-79.

35.

PHENOME-WIDE INTERACTION STUDY (PheWIS) IN AIDS CLINICAL TRIALS GROUP DATA (ACTG).

Verma SS, Frase AT, Verma A, Pendergrass SA, Mahony S, Haas DW, Ritchie MD.

Pac Symp Biocomput. 2016;21:57-68.

36.

Towards a phenome-wide catalog of human clinical traits impacted by genetic ancestry.

Dumitrescu L, Restrepo NA, Goodloe R, Boston J, Farber-Eger E, Pendergrass SA, Bush WS, Crawford DC.

BioData Min. 2015 Nov 11;8:35. doi: 10.1186/s13040-015-0068-y. eCollection 2015.

37.

The detection and characterization of pleiotropy: discovery, progress, and promise.

Tyler AL, Crawford DC, Pendergrass SA.

Brief Bioinform. 2016 Jan;17(1):13-22. doi: 10.1093/bib/bbv050. Epub 2015 Jul 28. Review.

PMID:
26223525
38.

Leveraging Epidemiologic and Clinical Collections for Genomic Studies of Complex Traits.

Crawford DC, Goodloe R, Farber-Eger E, Boston J, Pendergrass SA, Haines JL, Ritchie MD, Bush WS.

Hum Hered. 2015;79(3-4):137-46. doi: 10.1159/000381805. Epub 2015 Jul 28.

39.

Phenome-Wide Association Studies: Embracing Complexity for Discovery.

Pendergrass SA, Verma A, Okula A, Hall MA, Crawford DC, Ritchie MD.

Hum Hered. 2015;79(3-4):111-23. doi: 10.1159/000381851. Epub 2015 Jul 28. Review.

40.
41.

Biology-Driven Gene-Gene Interaction Analysis of Age-Related Cataract in the eMERGE Network.

Hall MA, Verma SS, Wallace J, Lucas A, Berg RL, Connolly J, Crawford DC, Crosslin DR, de Andrade M, Doheny KF, Haines JL, Harley JB, Jarvik GP, Kitchner T, Kuivaniemi H, Larson EB, Carrell DS, Tromp G, Vrabec TR, Pendergrass SA, McCarty CA, Ritchie MD.

Genet Epidemiol. 2015 Jul;39(5):376-84. doi: 10.1002/gepi.21902. Epub 2015 May 17.

42.

Next-generation analysis of cataracts: determining knowledge driven gene-gene interactions using biofilter, and gene-environment interactions using the Phenx Toolkit*.

Pendergrass SA, Verma SS, Hall MA, Holzinger ER, Moore CB, Wallace JR, Dudek SM, Huggins W, Kitchner T, Waudby C, Berg R, Mccarty CA, Ritchie MD.

Pac Symp Biocomput. 2015:495-505. Erratum in: Pac Symp Biocomput. 2015 ;20:493.

PMID:
25741542
43.

Methods of integrating data to uncover genotype-phenotype interactions.

Ritchie MD, Holzinger ER, Li R, Pendergrass SA, Kim D.

Nat Rev Genet. 2015 Feb;16(2):85-97. doi: 10.1038/nrg3868. Epub 2015 Jan 13. Review.

PMID:
25582081
44.

Contrasting Association Results between Existing PheWAS Phenotype Definition Methods and Five Validated Electronic Phenotypes.

Leader JB, Pendergrass SA, Verma A, Carey DJ, Hartzel DN, Ritchie MD, Kirchner HL.

AMIA Annu Symp Proc. 2015 Nov 5;2015:824-32. eCollection 2015.

45.

Genomic architecture of pharmacological efficacy and adverse events.

Chhibber A, Kroetz DL, Tantisira KG, McGeachie M, Cheng C, Plenge R, Stahl E, Sadee W, Ritchie MD, Pendergrass SA.

Pharmacogenomics. 2014 Dec;15(16):2025-48. doi: 10.2217/pgs.14.144. Review.

46.

Detection of pleiotropy through a Phenome-wide association study (PheWAS) of epidemiologic data as part of the Environmental Architecture for Genes Linked to Environment (EAGLE) study.

Hall MA, Verma A, Brown-Gentry KD, Goodloe R, Boston J, Wilson S, McClellan B, Sutcliffe C, Dilks HH, Gillani NB, Jin H, Mayo P, Allen M, Schnetz-Boutaud N, Crawford DC, Ritchie MD, Pendergrass SA.

PLoS Genet. 2014 Dec 4;10(12):e1004678. doi: 10.1371/journal.pgen.1004678. eCollection 2014 Dec.

47.

Regulatory polymorphisms in human DBH affect peripheral gene expression and sympathetic activity.

Barrie ES, Weinshenker D, Verma A, Pendergrass SA, Lange LA, Ritchie MD, Wilson JG, Kuivaniemi H, Tromp G, Carey DJ, Gerhard GS, Brilliant MH, Hebbring SJ, Cubells JF, Pinsonneault JK, Norman GJ, Sadee W.

Circ Res. 2014 Dec 5;115(12):1017-25. doi: 10.1161/CIRCRESAHA.116.304398. Epub 2014 Oct 17.

48.

Knowledge-driven genomic interactions: an application in ovarian cancer.

Kim D, Li R, Dudek SM, Frase AT, Pendergrass SA, Ritchie MD.

BioData Min. 2014 Sep 9;7:20. doi: 10.1186/1756-0381-7-20. eCollection 2014.

49.

Phenome-wide association studies demonstrating pleiotropy of genetic variants within FTO with and without adjustment for body mass index.

Cronin RM, Field JR, Bradford Y, Shaffer CM, Carroll RJ, Mosley JD, Bastarache L, Edwards TL, Hebbring SJ, Lin S, Hindorff LA, Crane PK, Pendergrass SA, Ritchie MD, Crawford DC, Pathak J, Bielinski SJ, Carrell DS, Crosslin DR, Ledbetter DH, Carey DJ, Tromp G, Williams MS, Larson EB, Jarvik GP, Peissig PL, Brilliant MH, McCarty CA, Chute CG, Kullo IJ, Bottinger E, Chisholm R, Smith ME, Roden DM, Denny JC.

Front Genet. 2014 Aug 5;5:250. doi: 10.3389/fgene.2014.00250. eCollection 2014.

50.

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