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Province, Mike

0000-0001-6102-774X

Mayo Clinic

Washington University in St. Louis

Citations 10

Genomic and phenomic landscape of clonal hematopoiesis in over a million ancestrally diverse participants
Uddin, Md Mesbah , Weinstock, Joshua S. , Niroula, Abhishek , Vlasschaert, Caitlyn , Koyama, Satoshi , Nakao, Tetsushi , Urbut, Sarah , Paruchuri, Kaavya , Silver, Alexander J. , Mack, Taralynn , Wong, Megan , Bhattacharya, Romit , Jorshery, Saman Doroodgar , Raddatz, Michael A. , Hornsby, Whitney , Kresge, Hailey A. , Cho, Kelly , Sun, Yan V. , Pyarajan, Saiju , Chen, Yii‐Der Ida , Sheu, Wayne H-H , Hung, Yi‐Jen , Hidalgo, Bertha , Fornage, Myriam , Kaplan, Robert C., Williams, L. Keoki , Province, Mike , Kardia, Sharon, Peyser, Patricia A., Yanek, Lisa R. , Becker, Lewis C. , Meyers, Deborah A. , Naseri, Take, Barnes, Kathleen C. , Redline, S S, Schwartz, D A, Shoemaker, M. Benjamin , Palmer, Nicholette D., Bowden, Donald W., Kumar, Rajesh, Nj, Smith, Floyd, James, Tracy, Russell, Bis, Joshua C. , SS, Rich, Boerwinkle, Eric, Wang, Zhe, Silverman, Edwin K. , Auer, Paul L. , Reiner, Alexander P. , Ebert, Benjamin L. , Natarajan, Pradeep , Uddin, Md M , Niroula, Abhishek , Weinstock, Joshua S , Bhattacharya, Romit , Ebert, Benjamin L , Natarajan, Pradeep , Yu, Zhi , Zekavat, Seyedeh M , Truong, Buu Minh Thanh , Haidermota, Sara , Honigberg, Michael C. , Zhang, Martin Jinye , Dron, Jacqueline S. , Heimlich, Jonathan Brett , Sankaran, Vijay G. , Griffin, Gabriel K. , Gibson, Christopher James , Wilson, Peter W.F. , Genovese, Giulio , Xu, Yaomin , Savona, Michael R. , Raffield, Laura M. , Arnett, Donna K. , Konkle, Barbara A. , Peyser, Patricia A. , Smith, Jennifer A. , Mathias, Rasika A. , Andrade, Mariza de , Darbar, Dawood , He, Jiang , Blangero, John , Weiss, Scott T. , Custer, Brian , Minster, Ryan L , Viali, Satupaitea , Mitchell, Braxton D. , Palmer, Nicholette D , Freedman, Barry I. , Bowden, Donald W. , Albert, Christine M. , Smith, Nicholas, Tracy, Russell P. , Psaty, Bruce M. , Taylor, Kent D. , Rotter, Jerome I. , Boerwinkle, Eric , Vasan, Ramachandran S. , Lubitz, Steven A. , Ellinor, Patrick T. , Loos, Ruth J. F. , Yun, Jeong H. , Cho, Michael H. , Abecasis, Gonçalo R. , Kooperberg, Charles , Reiner, Alex P. , Jaiswal, Siddhartha , Bick, Alexander G.

No container title available | July 31, 2022 | Volume: No volume available | Issue: No issue available | Pages: No page available

10.1101/2022.07.29.22278015 Get It

Abstract With aging, somatic mutations in hematopoietic stem and progenitor cells (HSPC) can give rise to clonal hematopoiesis of indeterminate potential (CHIP), a premalignant state associated with diverse age-related diseases. Here we report the largest multi-ancestry genome-wide analysis of CHIP to date (N = 1,018,305), including individuals of African (N = 85,978), Admixed American (N = 191,371), East Asian (N = 13,532), European (N = 694,015), and South Asian (N = 13,193) ancestry. Multi-ancestry meta-analyses identified 72 genome-wide significant loci, including 44 novel associations implicating genes such as AFF1 , ATF7IP , ATP8B4 , BCL2 , CEBPA , CYRIA , DNM2 , ELF1 , NKX2-3 , PIK3CB , PRDM16 , RPN1 , TERC , and TRIM4 . Notably, variants at MECOM and PHF20L1 showed opposite allelic effects between DNMT3A - and non- DNMT3A -driven CHIP, highlighting driver-specific germline influences. Implicated loci converge on pathways regulating telomere maintenance, cell-cycle control, hematopoietic transcription, DNA damage response and immune signaling. These findings support a model in which germline variation both expands the HSPC pool and biases clonal selection in a driver-dependent manner, providing a mechanistic basis for inter-individual heterogeneity in CHIP. Phenome-wide association analyses further linked CHIP to hematologic, neoplastic, and circulatory traits, with enrichment across hematopoietic and non-hematopoietic cell types. Together, this work expands the genomic and phenomic landscape of CHIP and reveals germline–somatic interactions that shape clonal evolution during aging.
Clinical Pharmacogenetics Implementation Consortium (CPIC) Guideline for CYP2D6 and Tamoxifen Therapy
Guchelaar, Henk‐Jan , Schwab, Matthias , Province, Michael A. , Symmans, W. Fraser , McLeod, Howard L. , Ratain, Mark J. , Zembutsu, Hitoshi , Schaik, Ron HN van , Caudle, Kelly E. , Ingle, James N. , Symmans, W Fraser , Goetz, Matthew P. , Sangkuhl, Katrin , Whirl‐Carrillo, Michelle , Gaedigk, Andrea , Klein, Teri E. , Schwab, Matthias , Province, Mike

Clinical Pharmacology & Therapeutics | January 31, 2018 | Volume: 103 | Issue: 5 | Pages: 770-777

10.1002/cpt.1007 Get It

Tamoxifen is biotransformed by CYP2D6 to 4‐hydroxytamoxifen and 4‐hydroxy N‐desmethyl tamoxifen (endoxifen), both with greater antiestrogenic potency than the parent drug. Patients with certain CYP2D6 genetic polymorphisms and patients who receive strong CYP2D6 inhibitors exhibit lower endoxifen concentrations and a higher risk of disease recurrence in some studies of tamoxifen adjuvant therapy of early breast cancer. We summarize evidence from the literature and provide therapeutic recommendations for tamoxifen based on CYP2D6 genotype.
Integration of genome-wide association studies with biological knowledge identifies six novel genes related to kidney function
Fuchsberger, Christian , Teumer, Alexander , Böger, Carsten A., Endlich, Karlhans , Olden, Matthias , Chen, Ming‐Huei , Li, Man , Gao, Xiaoyi , Gorski, Mathias , Hundertmark, Claudia, Foster, Meredith C., O’Seaghdha, Conall M. , Glazer, Nicole L. , Isaacs, Aaron , Liu, Ching‐Ti , Smith, Albert V. , O’Connell, Jeffrey R. , Struchalin, Maksim , Johnson, Andrew D. , Gierman, Hinco J. , Feitosa, Mary F. , Hwang, Shih-Jen, Atkinson, Elizabeth J. , Lohman, Kurt, Cornelis, Marilyn C., Johansson, Åsa , Tönjes, Anke , Dehghan, Abbas , Lambert, Jean‐Charles , Holliday, Elizabeth G., Sorice, Rossella , Kutalik, Zoltán , Lehtimäki, Terho , Esko, Tõnu , Deshmukh, Harshal , Ulivi, Sheila , Chu, Audrey Y., Murgia, Federico , Trompet, Stella , Imboden, Medea , Coassin, Stefan , Pistis, Giorgio , WTCCC2, Harris, Tamara B., Aspelund, Thor , Eiríksdóttir, Guðný , Mitchell, Braxton D. , Boerwinkle, Eric , Schmidt, Helena , Cavalieri, Margherita, Rao, Madhumathi , Hu, Frank B., Demirkan, Ayşe , Oostra, Ben A., Ding, Jingzhong , Andrews, Jeanette S., Giulianini, Franco, Köenig, Wolfgang , Illig, Thomas, Meisinger, Christa , Gieger, Christian , Zgaga, Lina , Zemunik, Tatijana , Boban, Mladen , Wheeler, Heather E. , Igl, Wilmar , Zaboli, Ghazal, Wright, Alan F., Campbell, Harry, Ellinghaus, David , Nöthlings, Ute , Jacobs, Gunnar, Biffar, Reiner , Ernst, Florian , Kroemer, Heyo K., Stracke, Sylvia , Völker, Uwe , Völzke, Henry , Kovács, Péter , Stümvoll, Michael , Mägi, Reedik , Hofman, Albert , Uitterlinden, André G. , Rivadeneira, Fernando , Aulchenko, Yurii S. , Polašek, Ozren , Hastie, Nick, Vitart, Véronique , Helmer, Catherine , Wang, Jie Jin , Stengel, Bénédicte , Ruggiero, Daniela , Kähönen, Mika , Viikari, Jorma , Nikopensius, Tiit , Province, Michael A. , Ketkar, Shamika , Colhoun, Helen M. , Doney, Alex S. F. , Robino, Antonietta , Krämer, Bernhard K. , Portas, Laura , Ford, Ian, Adam, Martin , Thun, Gian Andri , Paulweber, Bernhard , Haun, Margot, Sala, Cinzia , Mitchell, Paul, Ciullo, Marina , Kim, Stuart K. , Vollenweider, Péter , Raitakari, Olli T., Palmer, Colin, Gasparini, Paolo , Pirastu, Mario, Jukema, J. Wouter , Kronenberg, Florian , Toniolo, Daniela , Guðnason, Vilmundur , Shuldiner, Alan R. , Schmidt, Reinhold, Ferrucci, Luigi , Duijn, Cornelia M. van , Borecki, Ingrid B. , Kardia, Sharon L. R., Rudan, Igor , Pramstaller, Peter P. , Rettig, Rainer, Prokopenko, Inga , Witteman, Jacqueline C.M., Hayward, Caroline , Ridker, Paul M., Parsa, Afshin, Bochud, Murielle , Heid, Iris M. , Kao, W.H. Linda , Fox, Caroline S., Köttgen, Anna , Palmer, Colin N.A. , Chasman, Daniel I. , Pattaro, Cristian , Tin, Adrienne , Taliun, Daniel , Yang, Qiong , Tanaka, Toshiko , Guo, Li , Holliday, Elizabeth G., WTCCC2, Launer, Lenore J. , Andrade, Mariza de , Turner, Stephen T. , Freedman, Barry I. , Minelli, Cosetta , Wild, Sarah H. , Ellinghaus, David , Homuth, Georg , Nauck, Matthias A. , Bergmann, Sven M. , Buckley, Brendan Martin , Metspalu, Andres , Palmer, Colin, Probst-Hensch, Nicole M , Coresh, Josef , Siscovick, David S. , Curhan, Gary C. , Gyllensten, Ulf B , Wilson, James Fox , Franke, André , Palmer, Colin N A , Colhoun, Helen M , Völker, Uwe , Teumer, Alexander , van Duijn, Cornelia M , Smith, Albert V , Mitchell, Braxton D , Shuldiner, Alan R , Ferrucci, Luigi , Koenig, Wolfgang , Kovacs, Peter , Stracke, Sylvia , Liu, Ching-Ti , Wheeler, Heather E , Province, Mike

Human Molecular Genetics | September 8, 2012 | Volume: 21 | Issue: 24 | Pages: 5329-5343

10.1093/hmg/dds369 Get It

Next generation analytic tools for large scale genetic epidemiology studies of complex diseases
Mechanic, Leah E. , Chen, Huann‐Sheng , Chatterjee, Nilanjan , Cox, Nancy J. , Divi, Rao L., Fan, Ruzong , Harris, Emily , McAllister, Kimberly A. , Moore, Jason H. , Paltoo, Dina N., Province, Michael A. , Ramos, Erin M. , Ritchie, Marylyn D. , Roeder, Kathryn , Schaid, Daniel J. , Thomas, Duncan C. , Weinberg, Clarice R. , Witte, John S. , Zhang, Shunpu, Zöllner, Sebastian , Feuer, Eric J. , Gillanders, Elizabeth M. , Amos, Christopher I. , Jacobs, Kevin B. , Kraft, Peter , Leal, Suzanne M. , Stephens, Matthew , Weinberg, Clarice R , Province, Mike

Genetic Epidemiology | December 6, 2011 | Volume: 36 | Issue: 1 | Pages: 22-35

10.1002/gepi.20652 Get It

AbstractOver the past several years, genome‐wide association studies (GWAS) have succeeded in identifying hundreds of genetic markers associated with common diseases. However, most of these markers confer relatively small increments of risk and explain only a small proportion of familial clustering. To identify obstacles to future progress in genetic epidemiology research and provide recommendations to NIH for overcoming these barriers, the National Cancer Institute sponsored a workshop entitled “Next Generation Analytic Tools for Large‐Scale Genetic Epidemiology Studies of Complex Diseases” on September 15–16, 2010. The goal of the workshop was to facilitate discussions on (1) statistical strategies and methods to efficiently identify genetic and environmental factors contributing to the risk of complex disease; and (2) how to develop, apply, and evaluate these strategies for the design, analysis, and interpretation of large‐scale complex disease association studies in order to guide NIH in setting the future agenda in this area of research. The workshop was organized as a series of short presentations covering scientific (gene‐gene and gene‐environment interaction, complex phenotypes, and rare variants and next generation sequencing) and methodological (simulation modeling and computational resources and data management) topic areas. Specific needs to advance the field were identified during each session and are summarized.Genet. Epidemiol. 36 : 22–35, 2012. © 2011 Wiley Periodicals, Inc.
Peroxisome Proliferator-Activated Receptor Pathway Gene Polymorphism Associated With Extent of Coronary Artery Disease in Patients With Type 2 Diabetes in the Bypass Angioplasty Revascularization Investigation 2 Diabetes Trial
Wu, Jun , Province, Michael A. , Spertus, John A. , Steffes, Michael W. , Alderman, Edwin L., Brooks, Maria M. , Kelsey, Sheryl F., Frye, Robert L. , Bach, Richard G. , Cresci, Sharon , McGill, Janet B. , Spertus, John A , Province, Mike

Circulation | September 13, 2011 | Volume: 124 | Issue: 13 | Pages: 1426-1434

10.1161/circulationaha.111.029173 Get It

Background— Coronary artery disease (CAD) is the major cause of death in patients with type 2 diabetes mellitus. Although demographic and clinical factors associated with extent of CAD in patients with diabetes mellitus have been described, genetic factors have not. We hypothesized that genetic variation in peroxisome proliferator-activated receptor (PPAR) pathway genes, important in diabetes mellitus and atherosclerosis, would be associated with extent of CAD in patients with diabetes mellitus. Methods and Results— We genotyped 1043 patients (702 white, 175 blacks) from the Bypass Angioplasty Revascularization Investigation 2 Diabetes (BARI 2D) genetic cohort for 3351 variants in 223 PPAR pathway genes using a custom targeted-genotyping array. Angiographic end points were determined by a core laboratory. In whites, a single variant (rs1503298) in TLL1 was significantly ( P =5.5×10 −6 ) associated with extent of CAD, defined as number of lesions with percent diameter stenosis ≥20%, after stringent Bonferroni correction for all 3351 single nucleotide polymorphisms. This association was validated in the diabetic subgroups of 2 independent cohorts, the Translational Research Investigating Underlying Disparities in Acute Myocardial Infarction Patients' Health Status (TRIUMPH) post–myocardial infarction registry and the prospective Family Heart Study (FHS) of individuals at risk for CAD. TLL1 rs1503298 was also significantly associated with extent of severe CAD (≥70% diameter stenosis; P =3.7×10 −2 ) and myocardial jeopardy index ( P =8.7×10 −4 ). In general linear regression modeling, TLL1 rs1503298 explained more variance of extent of CAD than the previously determined clinical factors. Conclusions— We identified a variant in a single PPAR pathway gene, TLL1 , that is associated with the extent of CAD independently of clinical predictors, specifically in patients with type 2 diabetes mellitus and CAD. Clinical Trial Registration— URL: http://www.clinicaltrials.gov . Unique identifier: NCT00006305.
A Bivariate Genome-Wide Approach to Metabolic Syndrome
Kraja, Aldi T., Vaidya, Dhananjay , Pankow, James S. , Goodarzi, Mark O., Assimes, Themistocles L. , Sovio, Ulla , Mathias, Rasika A. , Sun, Yan V. , Franceschini, Nora , Absher, Devin , Zhang, Qunyuan, Feitosa, Mary F. , Glazer, Nicole L. , Hartikainen, Anna-Liisa, Knowles, Joshua W. , Iribarren, Carlos , Kral, Brian G. , Yanek, Lisa R. , O’Reilly, Paul F. , McCarthy, Mark I. , Jaquish, Cashell E. , Couper, David , Chakravarti, Aravinda , Becker, Lewis C. , Province, Michael A. , Boerwinkle, Eric , Quertermous, Thomas , Palotie, L, Järvelin, Marjo‐Riitta , Becker, Diane M. , Kardia, Sharon L. R., Rotter, Jerome I. , Chen, Yii-Der Ida , Borecki, Ingrid B. , Goodarzi, Mark O. , Kullo, Iftikhar J. , Guo, Li , Haritunians, Talin , Hartikainen, Anna‐Liisa, North, Kari E. , Psaty, Bruce M. , McCarthy, Mark I , Assimes, Themistocles L , Rotter, Jerome I , Mathias, Rasika A , Pankow, James S , Couper, David , Province, Mike

Diabetes | March 9, 2011 | Volume: 60 | Issue: 4 | Pages: 1329-1339

10.2337/db10-1011 Get It

OBJECTIVE The metabolic syndrome (MetS) is defined as concomitant disorders of lipid and glucose metabolism, central obesity, and high blood pressure, with an increased risk of type 2 diabetes and cardiovascular disease. This study tests whether common genetic variants with pleiotropic effects account for some of the correlated architecture among five metabolic phenotypes that define MetS. RESEARCH DESIGN AND METHODS Seven studies of the STAMPEED consortium, comprising 22,161 participants of European ancestry, underwent genome-wide association analyses of metabolic traits using a panel of ∼2.5 million imputed single nucleotide polymorphisms (SNPs). Phenotypes were defined by the National Cholesterol Education Program (NCEP) criteria for MetS in pairwise combinations. Individuals exceeding the NCEP thresholds for both traits of a pair were considered affected. RESULTS Twenty-nine common variants were associated with MetS or a pair of traits. Variants in the genes LPL, CETP, APOA5 (and its cluster), GCKR (and its cluster), LIPC, TRIB1, LOC100128354/MTNR1B, ABCB11, and LOC100129150 were further tested for their association with individual qualitative and quantitative traits. None of the 16 top SNPs (one per gene) associated simultaneously with more than two individual traits. Of them 11 variants showed nominal associations with MetS per se. The effects of 16 top SNPs on the quantitative traits were relatively small, together explaining from ∼9% of the variance in triglycerides, 5.8% of high-density lipoprotein cholesterol, 3.6% of fasting glucose, and 1.4% of systolic blood pressure. CONCLUSIONS Qualitative and quantitative pleiotropic tests on pairs of traits indicate that a small portion of the covariation in these traits can be explained by the reported common genetic variants.
Methods for Analysis in Pharmacogenomics: Lessons from the Pharmacogenetics Research Network Analysis Group
Srinivasan, Balaji S., Conti, David V. , Gu, Xiangjun, Haines, Jonathan L., Jorgenson, Eric , Kraja, Aldi T., Lasky‐Su, Jessica , Li, Lang , Rodin, Andréi S. , Province, Mike, Ritchie, Marylyn D. , Province, Michael A. , Chen, Jinbo , Cheng, Cheng , Duan, Shiwei , Fridley, Brooke L. , Wang, Dai , Conti, David V , Lasky-Su, Jessica , Province, Mike

Pharmacogenomics | February 10, 2009 | Volume: 10 | Issue: 2 | Pages: 243-251

10.2217/14622416.10.2.243 Get It

Genome-Wide Linkage Analysis for Loci Affecting Pulse Pressure
Lynch, Amy I., Miller, Michael B., Weder, Alan B., Cooper, Richard , Oberman, Albert, Chen, Yii-Der Ida , Fornage, Myriam , Province, Michael A. , Arnett, Donna K. , Bielinski, Suzette J. , Turner, Stephen T. , Arnett, Donna K , Province, Mike

Hypertension | November 14, 2005 | Volume: 46 | Issue: 6 | Pages: 1286-1293

10.1161/01.hyp.0000191706.41980.29 Get It

Pulse pressure, the difference between systolic and diastolic blood pressure, is an independent risk factor for cardiovascular disease. Increased pulse pressure reflects reduced compliance of arteries and is a marker of atherosclerosis. To locate genes that affect pulse pressure, a genome-wide linkage scan for quantitative trait loci influencing pulse pressure was performed using variance components methods as implemented in sequential oligogenic linkage analysis routines. The analysis sample included 10 798 participants in 3320 families who were recruited as part of the Family Blood Pressure Program and were phenotyped with an oscillometric blood pressure measurement device using a consistent protocol across centers. Pulse pressure was adjusted for the effects of sex, age, age 2 , age-by-sex interaction, age 2 -by-sex interaction, body mass index, and field center to remove sources of variation other than the genetic effects related to pulse pressure. Significant linkage was observed on chromosome 18 (logarithm of odds [LOD]=3.2) in a combined racial sample, chromosome 20 (LOD=4.4), and 17 (LOD=3.6) in Hispanics, chromosome 21 (LOD=4.3) in whites, chromosome 19 (LOD=3.1) in a combined sample of blacks and whites, and chromosome 7 (logarithm of odds [LOD]=3.1) in blacks from the GenNet Network. Our genome scan shows significant evidence for linkage for pulse pressure in multiple areas of the genome, supporting previous published linkage studies. The identification of these loci for pulse pressure and the apparent congruence with other blood pressure phenotypes provide increased support that these regions contain genes influencing blood pressure phenotypes.
Two Major QTLs and Several Others Relate to Factors of Metabolic Syndrome in the Family Blood Pressure Program
Kraja, Aldi T., Weder, Alan B., Cooper, Richard, Curb, J. David, Hanis, Craig L. , Hsiung, Chao A. , Quertermous, Thomas , Zhu, Xiaofeng , Province, Michael A. , Rao, D. C. , Cooper, Richard, Turner, Stephen T. , Andrade, Mariza de , Province, Mike

Hypertension | September 20, 2005 | Volume: 46 | Issue: 4 | Pages: 751-757

10.1161/01.hyp.0000184249.20016.bb Get It

Genome-wide variance components linkage analysis was performed on 4 latent factors underlying metabolic syndrome derived from 10 risk factors. The latent factors represent obesity and insulin, blood pressure, lipids and insulin, and central obesity. The metabolic syndrome factor scores were derived in 4 ethnic groups recruited in 3 Networks of the Family Blood Pressure Program: GENOA (blacks, Hispanics, and whites), HyperGEN (blacks and whites), SAPPHIRe (Asians). Heritabilities of metabolic syndrome factors ranged from 66% for obesity and insulin to 11% for blood pressure factor. We observed higher heritabilities for obesity and insulin, and lipids and insulin, whereas those for blood pressure and central obesity were smaller. Linkage analysis detected two major quantitative trait loci. One of them linked to the obesity and insulin factor with a lod score of 3.94 ( P =0.00001, marker GATA11A06, D18S53, 41.24 cM) at marker positions linkage (lod 4.71, at 46.84 cM at 1-cM-apart distances linkage), located on chromosome 18p11.21 in GENOA black. The other linked to the blood pressure factor with a lod score of 3.22 ( P =0.000059, marker GATA49C09, D17S1290, 82 cM) at marker positions linkage (lod 3.56, at 84.63 cM for 1 cM apart distances linkage) located on chromosome 17q23.1 in Hispanics. These quantitative trait loci, together with 4 additional ones with lod scores >2.5, and 30 additional ones with lod score >1.7, offer hope for dissecting the genetic architecture of metabolic syndrome with beneficial implications for molecular diagnosis, prognosis, and in potential medical intervention.
A Genome-Wide Scan for Urinary Albumin Excretion in Hypertensive Families
Beck, Stephanie R., Rich, Stephen S. , Heiss, Gerardo , Lewis, Cora E. , Province, Michael A. , Schwander, Karen , Arnett, Donna K. , Mellen, Beverly G., Freedman, Barry I. , Turner, Stephen T. , Rich, Stephen S , Arnett, Donna K , Province, Mike

Hypertension | August 19, 2003 | Volume: 42 | Issue: 3 | Pages: 291-296

10.1161/01.hyp.0000087890.33245.41 Get It

Albuminuria increases the risk of cardiovascular events in patients with essential hypertension and diabetic subjects. The heritability (h 2 ) of albuminuria in multiplex hypertensive families is unknown. We calculated the familial aggregation of urine albumin:creatinine ratio (ACR) and performed a genome-wide scan to assess for loci contributing to ACR in participants enrolled in the Hyper tension G enetic E pidemiology N etwork (HyperGEN). To perform the genome scan, we analyzed genotype results from 2589 individuals from 805 families in the Family Blood Pressure Program. ACR and covariates were available in 1727 individuals (mean age, 57.1 years). Estimates of h 2 were obtained by using variance component methodology as implemented in the SOLAR software package. Linkage was tested between 387 markers spanning the genome at an average interval of 9.32 cM, using SOLAR multipoint analysis. The h 2 of log urine ACR was 0.49 ( P <1×10 −7 ) after controlling for significant main and interactive effects of age, gender, race, body mass index, blood pressure, and use of ACE inhibitors or angiotensin-2 receptor blockers. The genome-wide scan revealed a maximum LOD score of 2.73 on chromosome 19 (robust corrected LOD, 2.40; P =0.0009) at marker D19S591 and a LOD score of 2.0 on chromosome 12 (robust corrected LOD, 1.75; P =0.005) at marker PAH. These analyses demonstrate the marked heritability of urine ACR in families enriched for the presence of members with essential hypertension. They suggest that a gene(s) associated with urinary ACR may be present on human chromosomes 19 and 12.