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John Rice, PhD

Current Position
Professor of Mathematics in Psychiatry

Education and Training
PI of NIMH T32 Training Grant
CO-PI of NIDA R25 Training Grant


Areas of Research Interests
Current research interests in my lab include method development in genetic epidemiology and the collection and analysis of family and population data on bipolar disorder, major depression, schizophrenia and substance abuse. Methodologic work includes: (i) the development of new measures of linkage disequilibrium to define SNPs for association analysis; (ii) assessing the accuracy of imputation; and (iii) developing statistical methods to assess CNV (copy number variation) prediction. I continue to apply these new techniques to a number of currently existing data sets. My emphasis has been shifting from linkage analysis using several hundred repeat markers to association analysis using 1 million SNPs in GWAS (Genome-wide Association Studies). This new trend in the genetics of complex traits represents many challenges in data management and in analysis. My lab also maintains the phenotypic component of the genetic repository for NIMH, NIDA and NIAAA. Future emphasis will be the use of statistical genetics and bioinformatics for the meta-analysis of the genetic data available.


Key Publications
Lin P, Hartz SM, Zhang Z, Saccone SF, Wang J, Tischfield JA, Edenberg HJ, Kramer JR, M Goate A, Bierut LJ, Rice JP, COGA Collaborators COGEND Collaborators, GENEVA (2010 Mar 15). A new statistic to evaluate imputation reliability. PLoS One. 5(3): e9697.  Full Article ->

Lin P, Hartz SM, Wang JC, Krueger RF, Foroud TM, Edenberg HJ, Nurnberger JI Jr, Brooks AI, Tischfield JA, Almasy L, Webb BT, Hesselbrock VM, Porjesz B, Goate AM, Bierut LJ, Rice JP, COGA Collaborators, COGEND Collaborators, GENEVA Investigators (2011). Copy number variation accuracy in genome-wide association studies. Hum Hered. 71(3): 141-7.  Full Article ->

Wang JC, Foroud T, Hinrichs AL, Le NX, Bertelsen S, Budde JP, Harari O, Koller DL, Wetherill L, Agrawal A, Almasy L, Brooks AI, Bucholz K, Dick D, Hesselbrock V, Johnson EO, Kang S, Kapoor M, Kramer J, Kuperman S, Madden PA, Manz N, Martin NG, McClintick JN, Montgomery GW, Nurnberger JI Jr, Rangaswamy M, Rice J, Schuckit M, Tischfield JA, Whitfield JB, Xuei X, Porjesz B, Heath AC, Edenberg HJ, Bierut LJ, Goate AM (2012 Oct 23). A genome-wide association study of alcohol-dependence symptom counts in extended pedigrees identifies C15orf53. Mol Psychiatry.   Full Article ->

Lin P, Hartz SM, Wang JC, Agrawal A, Zhang TX, McKenna N, Bucholz K, Brooks AI, Tischfield JA, Edenberg HJ, Hesselbrock VM, Kramer JR, Kuperman S, Schuckit MA, Goate AM, Bierut LJ, Rice JP, COGA Collaborators, COGEND Collaborators, GENEVA (2012 Sep). Copy number variations in 6q14.1 and 5q13.2 are associated with alcohol dependence. Alcohol Clin Exp Res. 36(9): 1512-8.  Full Article ->

Rice JP, Hartz SM, Agrawal A, Almasy L, Bennett S, Breslau N, Bucholz KK, Doheny KF, Edenberg HJ, Goate AM, Hesselbrock V, Howells WB, Johnson EO, Kramer J, Krueger RF, Kuperman S, Laurie C, Manolio TA, Neuman RJ, Nurnberger JI, Porjesz B, Pugh E, Ramos EM, Saccone N, Saccone S, Schuckit M, Bierut LJ, GENEVA Consortium (2012 Nov). CHRNB3 is more strongly associated with Fagerström test for cigarette dependence-based nicotine dependence than cigarettes per day: phenotype definition changes genome-wide association studies results. Addiction. 107(11): 2019-28.  Full Article ->

Rietveld CA, Medland SE, Derringer J, Yang J, Esko T, Martin NW, Westra HJ, Shakhbazov K, Abdellaoui A, Agrawal A, Albrecht E, Alizadeh BZ, Amin N, Barnard J, Baumeister SE, Benke KS, Bielak LF, Boatman JA, Boyle PA, Davies G, de Leeuw C, Eklund N, Evans DS, Ferhmann R, Fischer K, Gieger C, Gjessing HK, Hägg S, Harris JR, Hayward C, Holzapfel C, Ibrahim-Verbaas CA, Ingelsson E, Jacobsson B, Joshi PK, Jugessur A, Kaakinen M, Kanoni S, Karjalainen J, Kolcic I, Kristiansson K, Kutalik Z, Lahti J, Lee SH, Lin P, Lind PA, Liu Y, Lohman K, Loitfelder M, McMahon G, Vidal PM, Meirelles O, Milani L, Myhre R, Nuotio ML, Oldmeadow CJ, Petrovic KE, Peyrot WJ, Polasek O, Quaye L, Reinmaa E, Rice JP, Rizzi TS, Schmidt H, Schmidt R, Smith AV, Smith JA, Tanaka T, Terracciano A, van der Loos MJ, Vitart V, Völzke H, Wellmann J, Yu L, Zhao W, Allik J, Attia JR, Bandinelli S, Bastardot F, Beauchamp J, Bennett DA, Berger K, Bierut LJ, Boomsma DI, Bültmann U, Campbell H, Chabris CF, Cherkas L, Chung MK, Cucca F, de Andrade M, De Jager PL, De Neve JE, Deary IJ, Dedoussis GV, Deloukas P, Dimitriou M, Eiríksdóttir G, Elderson MF, Eriksson JG, Evans DM, Faul JD, Ferrucci L, Garcia ME, Grönberg H, Guðnason V, Hall P, Harris JM, Harris TB, Hastie ND, Heath AC, Hernandez DG, Hoffmann W, Hofman A, Holle R, Holliday EG, Hottenga JJ, Iacono WG, Illig T, Järvelin MR, Kähönen M, Kaprio J, Kirkpatrick RM, Kowgier M, Latvala A, Launer LJ, Lawlor DA, Lehtimäki T, Li J, Lichtenstein P, Lichtner P, Liewald DC, Madden PA, Magnusson PK, Mäkinen TE, Masala M, McGue M, Metspalu A, Mielck A, Miller MB, Montgomery GW, Mukherjee S, Nyholt DR, Oostra BA, Palmer LJ, Palotie A, Penninx BW, Perola M, Peyser PA, Preisig M, Räikkönen K, Raitakari OT, Realo A, Ring SM, Ripatti S, Rivadeneira F, Rudan I, Rustichini A, Salomaa V, Sarin AP, Schlessinger D, Scott RJ, Snieder H, St Pourcain B, Starr JM, Sul JH, Surakka I, Svento R, Teumer A, LifeLines Cohort Study, Tiemeier H, van Rooij FJ, Van Wagoner DR, Vartiainen E, Viikari J, Vollenweider P, Vonk JM, Waeber G, Weir DR, Wichmann HE, Widen E, Willemsen G, Wilson JF, Wright AF, Conley D, Davey-Smith G, Franke L, Groenen PJ, Hofman A, Johannesson M, Kardia SL, Krueger RF, Laibson D, Martin NG, Meyer MN, Posthuma D, Thurik AR, Timpson NJ, Uitterlinden AG, van Duijn CM, Visscher PM, Benjamin DJ, Cesarini D, Koellinger PD (2013 Jun 21). GWAS of 126,559 individuals identifies genetic variants associated with educational attainment. Science. 340(6139): 1467-71.  Full Article ->


Funded Research Projects
NIMH (PI): Research Training in Clinical Sciences

NIDA (Key Personnel): The Genetics of Vulnerability to Nicotine Addictions

NIMH (Key Personnel): NIMH Center for Collaborative Genetic Studies

NIDA (Key Personnel): Case Control Candidate Gene Study of Addiction

NCI (Key Personnel): The Collaborative Genetic Study of Nicotine Dependence

NIDA (Key Personnel): NIDA Center for Genetic Studies

NIAAA (Key Personnel): Collaborative Study on the Genetics of Alcoholism (COGA)

NIDA (Key Personnel): Research Education Program in Aspects of Statistical Genetics and Addiction