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355 results on '"Beitelshees, Amber"'

1. The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation

Author: Cavallari, Larisa H., Hicks, J. Kevin, Patel, Jai N., Elchynski, Amanda L., Smith, D. Max, Bargal, Salma A., Fleck, Ashley, Aquilante, Christina L., Killam, Shayna R., Lemke, Lauren, Ochi, Taichi, Ramsey, Laura B., Haidar, Cyrine E., Ho, Teresa, El Rouby, Nihal, Monte, Andrew A., Allen, Josiah D., Beitelshees, Amber L., Bishop, Jeffrey R., Bousman, Chad, Campbell, Ronald, Cicali, Emily J., Cook, Kelsey J., Duong, Benjamin, Tsermpini, Evangelia Eirini, Girdwood, Sonya Tang, Gregornik, David B., Grimsrud, Kristin N., Lamb, Nathan, Lee, James C., Lopez, Rocio Ortiz, Mazhindu, Tinashe Adrian, Morris, Sarah A., Nagy, Mohamed, Nguyen, Jenny, Pasternak, Amy L., Petry, Natasha, van Schaik, Ron H.N., Schultz, April, Skaar, Todd C., Al Alshaykh, Hana, Stevenson, James M., Stone, Rachael M., Tran, Nam K., Tuteja, Sony, Woodahl, Erica L., Yuan, Li-Chi, and Lee, Craig R.
Published: 2025
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2. The Pharmacogenomics Global Research Network Implementation Working Group: global collaboration to advance pharmacogenetic implementation

Author: Cavallari, Larisa H., Hicks, J. Kevin, Patel, Jai N., Elchynski, Amanda L., Smith, D. Max, Bargal, Salma A., Fleck, Ashley, Aquilante, Christina L., Killam, Shayna R., Lemke, Lauren, Ochi, Taichi, Ramsey, Laura B., Haidar, Cyrine E., Ho, Teresa, El Rouby, Nihal, Monte, Andrew A., Allen, Josiah D., Beitelshees, Amber L., Bishop, Jeffrey R., Bousman, Chad, Campbell, Ronald, Cicali, Emily J., Cook, Kelsey J., Duong, Benjamin, Tsermpini, Evangelia Eirini, Girdwood, Sonya Tang, Gregornik, David B., Grimsrud, Kristin N., Lamb, Nathan, Lee, James C., Lopez, Rocio Ortiz, Mazhindu, Tinashe Adrian, Morris, Sarah A., Nagy, Mohamed, Nguyen, Jenny, Pasternak, Amy L., Petry, Natasha, van Schaik, Ron H.N., Schultz, April, Skaar, Todd C., Al Alshaykh, Hana, Stevenson, James M., Stone, Rachael M., Tran, Nam K., Tuteja, Sony, Woodahl, Erica L., Yuan, Li-Chi, and Lee, Craig R.
Published: 2024
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3. Whole genome sequence analysis of apparent treatment resistant hypertension status in participants from the Trans-Omics for Precision Medicine program.

Author: Armstrong, Nicole, Srinivasasainagendra, Vinodh, Ammous, Farah, Assimes, Themistocles, Beitelshees, Amber, Brody, Jennifer, Cade, Brian, Ida Chen, Yii-Der, Chen, Han, de Vries, Paul, Floyd, James, Franceschini, Nora, Guo, Xiuqing, Hellwege, Jacklyn, House, John, Hwu, Chii-Min, Kardia, Sharon, Lange, Ethan, Lange, Leslie, McDonough, Caitrin, Montasser, May, OConnell, Jeffrey, Shuey, Megan, Sun, Xiao, Tanner, Rikki, Wang, Zhe, Zhao, Wei, Carson, April, Edwards, Todd, Kelly, Tanika, Kenny, Eimear, Kooperberg, Charles, Loos, Ruth, Morrison, Alanna, Motsinger-Reif, Alison, Psaty, Bruce, Rao, Dabeeru, Redline, Susan, Rich, Stephen, Rotter, Jerome, Smith, Jennifer, Smith, Albert, Irvin, Marguerite, and Arnett, Donna
Subjects: TOPMed, antihypertensive response, blood pressure, treatment resistant hypertension, whole genome sequencing
Abstract: Introduction: Apparent treatment-resistant hypertension (aTRH) is characterized by the use of four or more antihypertensive (AHT) classes to achieve blood pressure (BP) control. In the current study, we conducted single-variant and gene-based analyses of aTRH among individuals from 12 Trans-Omics for Precision Medicine cohorts with whole-genome sequencing data. Methods: Cases were defined as individuals treated for hypertension (HTN) taking three different AHT classes, with average systolic BP ≥ 140 or diastolic BP ≥ 90 mmHg, or four or more medications regardless of BP (n = 1,705). A normotensive control group was defined as individuals with BP < 140/90 mmHg (n = 22,079), not on AHT medication. A second control group comprised individuals who were treatment responsive on one AHT medication with BP < 140/ 90 mmHg (n = 5,424). Logistic regression with kinship adjustment using the Scalable and Accurate Implementation of Generalized mixed models (SAIGE) was performed, adjusting for age, sex, and genetic ancestry. We assessed variants using SKAT-O in rare-variant analyses. Single-variant and gene-based tests were conducted in a pooled multi-ethnicity stratum, as well as self-reported ethnic/racial strata (European and African American). Results: One variant in the known HTN locus, KCNK3, was a top finding in the multi-ethnic analysis (p = 8.23E-07) for the normotensive control group [rs12476527, odds ratio (95% confidence interval) = 0.80 (0.74-0.88)]. This variant was replicated in the Vanderbilt University Medical Centers DNA repository data. Aggregate gene-based signals included the genes AGTPBP, MYL4, PDCD4, BBS9, ERG, and IER3. Discussion: Additional work validating these loci in larger, more diverse populations, is warranted to determine whether these regions influence the pathobiology of aTRH.
Published: 2023

4. Abstract 4146352: Development and Validation of Machine Learning-based Ischemic Outcome Prediction Using Clinical and Genetic Data in Patients with Percutaneous Coronary Intervention

Author: Grant, Caroline, Kowlgi, Gurukripa, Lennon, Ryan, Cavallari, Larisa, Lee, Craig, Beitelshees, Amber, Angiolillo, Dominick, Franchi, Francesco, Duarte, Julio, Rossi, Joe, Stouffer, George, Klee, Eric, Gulati, Rajiv, Lerman, Amir, Rihal, Charanjit, Farkouh, Michael, Athreya, Arjun, and Pereira, Naveen
Published: 2024
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5. Rare coding variants in RCN3 are associated with blood pressure

Author: He, Karen Y, Kelly, Tanika N, Wang, Heming, Liang, Jingjing, Zhu, Luke, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bielak, Lawrence F, Bress, Adam P, Brody, Jennifer A, Chang, Yen-Pei Christy, Chang, Yi-Cheng, de Vries, Paul S, Duggirala, Ravindranath, Fox, Ervin R, Franceschini, Nora, Furniss, Anna L, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hung, Yi-Jen, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Naseri, Take, Palmas, Walter, Reupena, Muagututi’a Sefuiva, Rice, Kenneth M, Sheu, Wayne H-H, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Zhao, Wei, Blangero, John, Boerwinkle, Eric, Chen, Yii-Der Ida, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Fornage, Myriam, He, Jiang, Hou, Lifang, Kaplan, Robert C, Kardia, Sharon LR, Kenny, Eimear E, Kooperberg, Charles, Lloyd-Jones, Donald, Loos, Ruth JF, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, North, Kari E, Peyser, Patricia A, Psaty, Bruce M, Raffield, Laura M, Rao, DC, Redline, Susan, Reiner, Alex P, Rich, Stephen S, Rotter, Jerome I, Taylor, Kent D, Tracy, Russell, Vasan, Ramachandran S, Morrison, Alanna C, Levy, Daniel, Chakravarti, Aravinda, Arnett, Donna K, and Zhu, Xiaofeng
Subjects: Biological Sciences, Genetics, Hypertension, Human Genome, Precision Medicine, Biotechnology, Cardiovascular, Minority Health, 2.1 Biological and endogenous factors, Good Health and Well Being, Blood Pressure, Genetic Linkage, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Polymorphism, Single Nucleotide, Whole Genome Sequencing, Rare variant analysis, Blood pressure, Whole genome sequencing, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, Information and Computing Sciences, Medical and Health Sciences, Bioinformatics, Biological sciences, Biomedical and clinical sciences
Abstract: BackgroundWhile large genome-wide association studies have identified nearly one thousand loci associated with variation in blood pressure, rare variant identification is still a challenge. In family-based cohorts, genome-wide linkage scans have been successful in identifying rare genetic variants for blood pressure. This study aims to identify low frequency and rare genetic variants within previously reported linkage regions on chromosomes 1 and 19 in African American families from the Trans-Omics for Precision Medicine (TOPMed) program. Genetic association analyses weighted by linkage evidence were completed with whole genome sequencing data within and across TOPMed ancestral groups consisting of 60,388 individuals of European, African, East Asian, Hispanic, and Samoan ancestries.ResultsAssociations of low frequency and rare variants in RCN3 and multiple other genes were observed for blood pressure traits in TOPMed samples. The association of low frequency and rare coding variants in RCN3 was further replicated in UK Biobank samples (N = 403,522), and reached genome-wide significance for diastolic blood pressure (p = 2.01 × 10- 7).ConclusionsLow frequency and rare variants in RCN3 contributes blood pressure variation. This study demonstrates that focusing association analyses in linkage regions greatly reduces multiple-testing burden and improves power to identify novel rare variants associated with blood pressure traits.
Published: 2022

6. Insights From a Large-Scale Whole-Genome Sequencing Study of Systolic Blood Pressure, Diastolic Blood Pressure, and Hypertension

Author: Kelly, Tanika N, Sun, Xiao, He, Karen Y, Brown, Michael R, Taliun, Sarah A Gagliano, Hellwege, Jacklyn N, Irvin, Marguerite R, Mi, Xuenan, Brody, Jennifer A, Franceschini, Nora, Guo, Xiuqing, Hwang, Shih-Jen, de Vries, Paul S, Gao, Yan, Moscati, Arden, Nadkarni, Girish N, Yanek, Lisa R, Elfassy, Tali, Smith, Jennifer A, Chung, Ren-Hua, Beitelshees, Amber L, Patki, Amit, Aslibekyan, Stella, Blobner, Brandon M, Peralta, Juan M, Assimes, Themistocles L, Palmas, Walter R, Liu, Chunyu, Bress, Adam P, Huang, Zhijie, Becker, Lewis C, Hwa, Chii-Min, O’Connell, Jeffrey R, Carlson, Jenna C, Warren, Helen R, Das, Sayantan, Giri, Ayush, Martin, Lisa W, Johnson, W Craig, Fox, Ervin R, Bottinger, Erwin P, Razavi, Alexander C, Vaidya, Dhananjay, Chuang, Lee-Ming, Chang, Yen-Pei C, Naseri, Take, Jain, Deepti, Kang, Hyun Min, Hung, Adriana M, Srinivasasainagendra, Vinodh, Snively, Beverly M, Gu, Dongfeng, Montasser, May E, Reupena, Muagututi A Sefuiva, Heavner, Benjamin D, LeFaive, Jonathon, Hixson, James E, Rice, Kenneth M, Wang, Fei Fei, Nielsen, Jonas B, Huang, Jianfeng, Khan, Alyna T, Zhou, Wei, Nierenberg, Jovia L, Laurie, Cathy C, Armstrong, Nicole D, Shi, Mengyao, Pan, Yang, Stilp, Adrienne M, Emery, Leslie, Wong, Quenna, Hawley, Nicola L, Minster, Ryan L, Curran, Joanne E, Munroe, Patricia B, Weeks, Daniel E, North, Kari E, Tracy, Russell P, Kenny, Eimear E, Shimbo, Daichi, Chakravarti, Aravinda, Rich, Stephen S, Reiner, Alex P, Blangero, John, Redline, Susan, Mitchell, Braxton D, Rao, Dabeeru C, Chen, Yii-Der Ida, Kardia, Sharon LR, Kaplan, Robert C, Mathias, Rasika A, He, Jiang, Psaty, Bruce M, Fornage, Myriam, Loos, Ruth JF, Correa, Adolfo, Boerwinkle, Eric, Rotter, Jerome I, Kooperberg, Charles, and Edwards, Todd L
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Biotechnology, Hypertension, Human Genome, Genetics, 2.1 Biological and endogenous factors, Cardiovascular, Good Health and Well Being, Blood Pressure, Genome-Wide Association Study, Genomics, Humans, Polymorphism, Single Nucleotide, Precision Medicine, allele, blood pressure, genome, hypertension, whole genome sequencing, Samoan Obesity, Lifestyle, and Genetic Adaptations Study (OLaGA) Group, ‡ NHLBI Trans-Omics for Precision Medicine TOPMed) Consortium, Cardiorespiratory Medicine and Haematology, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract: BackgroundThe availability of whole-genome sequencing data in large studies has enabled the assessment of coding and noncoding variants across the allele frequency spectrum for their associations with blood pressure.MethodsWe conducted a multiancestry whole-genome sequencing analysis of blood pressure among 51 456 Trans-Omics for Precision Medicine and Centers for Common Disease Genomics program participants (stage-1). Stage-2 analyses leveraged array data from UK Biobank (N=383 145), Million Veteran Program (N=318 891), and Reasons for Geographic and Racial Differences in Stroke (N=10 643) participants, along with whole-exome sequencing data from UK Biobank (N=199 631) participants.ResultsTwo blood pressure signals achieved genome-wide significance in meta-analyses of stage-1 and stage-2 single variant findings (P
Published: 2022

7. Whole Genome Sequence Analysis of the Plasma Proteome in Black Adults Provides Novel Insights Into Cardiovascular Disease

Author: Katz, Daniel H, Tahir, Usman A, Bick, Alexander G, Pampana, Akhil, Ngo, Debby, Benson, Mark D, Yu, Zhi, Robbins, Jeremy M, Chen, Zsu-Zsu, Cruz, Daniel E, Deng, Shuliang, Farrell, Laurie, Sinha, Sumita, Schmaier, Alec A, Shen, Dongxiao, Gao, Yan, Hall, Michael E, Correa, Adolfo, Tracy, Russell P, Durda, Peter, Taylor, Kent D, Liu, Yongmei, Johnson, W Craig, Guo, Xiuqing, Yao, Jie, Ida Chen, Yii-Der, Manichaikul, Ani W, Jain, Deepti, Bouchard, Claude, Sarzynski, Mark A, Rich, Stephen S, Rotter, Jerome I, Wang, Thomas J, Wilson, James G, Natarajan, Pradeep, Gerszten, Robert E, Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April, Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, and Chavan, Sameer
Subjects: Epidemiology, Health Sciences, Genetics, Minority Health, Cardiovascular, Biotechnology, Heart Disease, Prevention, Human Genome, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Black People, Cardiovascular Diseases, Female, Genome-Wide Association Study, Humans, Male, Proteome, cardiovascular disease, genetics, proteomics, race and ethnicity, National Heart, Lung, and Blood Institute TOPMed (Trans-Omics for Precision Medicine) Consortium†, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences, Sports science and exercise
Abstract: BackgroundPlasma proteins are critical mediators of cardiovascular processes and are the targets of many drugs. Previous efforts to characterize the genetic architecture of the plasma proteome have been limited by a focus on individuals of European descent and leveraged genotyping arrays and imputation. Here we describe whole genome sequence analysis of the plasma proteome in individuals with greater African ancestry, increasing our power to identify novel genetic determinants.MethodsProteomic profiling of 1301 proteins was performed in 1852 Black adults from the Jackson Heart Study using aptamer-based proteomics (SomaScan). Whole genome sequencing association analysis was ascertained for all variants with minor allele count ≥5. Results were validated using an alternative, antibody-based, proteomic platform (Olink) as well as replicated in the Multi-Ethnic Study of Atherosclerosis and the HERITAGE Family Study (Health, Risk Factors, Exercise Training and Genetics).ResultsWe identify 569 genetic associations between 479 proteins and 438 unique genetic regions at a Bonferroni-adjusted significance level of 3.8×10-11. These associations include 114 novel locus-protein relationships and an additional 217 novel sentinel variant-protein relationships. Novel cardiovascular findings include new protein associations at the APOE gene locus including ZAP70 (sentinel single nucleotide polymorphism [SNP] rs7412-T, β=0.61±0.05, P=3.27×10-30) and MMP-3 (β=-0.60±0.05, P=1.67×10-32), as well as a completely novel pleiotropic locus at the HPX gene, associated with 9 proteins. Further, the associations suggest new mechanisms of genetically mediated cardiovascular disease linked to African ancestry; we identify a novel association between variants linked to APOL1-associated chronic kidney and heart disease and the protein CKAP2 (rs73885319-G, β=0.34±0.04, P=1.34×10-17) as well as an association between ATTR amyloidosis and RBP4 levels in community-dwelling individuals without heart failure.ConclusionsTaken together, these results provide evidence for the functional importance of variants in non-European populations, and suggest new biological mechanisms for ancestry-specific determinants of lipids, coagulation, and myocardial function.
Published: 2022

8. A genetic association study of circulating coagulation factor VIII and von Willebrand factor levels

Author: Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P, Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J. F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A, Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S, Pleiness, Jacob, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D. C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent D., Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T, Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Lindstrom, Sara, Wang, Lu, Smith, Erin N., Gordon, William, van Hylckama Vlieg, Astrid, Brody, Jennifer A., Pattee, Jack W., Haessler, Jeffrey, Brumpton, Ben M., Chasman, Daniel I., Suchon, Pierre, Chen, Ming-Huei, Turman, Constance, Germain, Marine, Wiggins, Kerri L., MacDonald, James, Braekkan, Sigrid K., Armasu, Sebastian M., Pankratz, Nathan, Jackson, Rabecca D., Nielsen, Jonas B., Giulianini, Franco, Puurunen, Marja K., Ibrahim, Manal, Heckbert, Susan R., Bammler, Theo K., Frazer, Kelly A., McCauley, Bryan M., Taylor, Kent, Pankow, James S., Reiner, Alexander P., Gabrielsen, Maiken E., Deleuze, Jean-François, O'Donnell, Chris J., Kim, Jihye, McKnight, Barbara, Kraft, Peter, Hansen, John-Bjarne, Rosendaal, Frits R., Heit, John A., Psaty, Bruce M., Tang, Weihong, Hveem, Kristian, Ridker, Paul M., Morange, Pierre-Emmanuel, Johnson, Andrew D., Kabrhel, Christopher, AlexandreTrégouët, David, Smith, Nicholas L., de Vries, Paul S., Reventun, Paula, Brown, Michael R., Heath, Adam S., Huffman, Jennifer E., Le, Ngoc-Quynh, Bebo, Allison, Temprano-Sagrera, Gerard, Raffield, Laura M., Ozel, Ayse Bilge, Thibord, Florian, Lewis, Joshua P., Rodriguez, Benjamin A. T., Polasek, Ozren, Yanek, Lisa R., Carrasquilla, German D., Marioni, Riccardo E., Kleber, Marcus E., Trégouët, David-Alexandre, Yao, Jie, Li-Gao, Ruifang, Joshi, Peter K., Trompet, Stella, Martinez-Perez, Angel, Ghanbari, Mohsen, Howard, Tom E., Reiner, Alex P., Arvanitis, Marios, Ryan, Kathleen A., Bartz, Traci M., Rudan, Igor, Faraday, Nauder, Linneberg, Allan, Davies, Gail, Delgado, Graciela E., Klaric, Lucija, Noordam, Raymond, van Rooij, Frank, Curran, Joanne E., Wheeler, Marsha M., Osburn, William O., O'Connell, Jeffrey R., Beswick, Andrew, Kolcic, Ivana, Souto, Juan Carlos, Becker, Lewis C., Hansen, Torben, Doyle, Margaret F., Harris, Sarah E., Moissl, Angela P., Rich, Stephen S., Campbell, Harry, Stott, David J., Soria, Jose Manuel, de Maat, Moniek P. M., Brody, Lawrence C., Auer, Paul L., Ben-Shlomo, Yoav, Hayward, Caroline, Mathias, Rasika A., Kilpeläinen, Tuomas O., Lange, Leslie A., Cox, Simon R., März, Winfried, Rotter, Jerome I., Mook-Kanamori, Dennis O., Wilson, James F., van der Harst, Pim, Jukema, J. Wouter, Ikram, M. Arfan, Desch, Karl C., Sabater-Lleal, Maria, Lowenstein, Charles J., and Morrison, Alanna C.
Published: 2024
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9. Epigenome-wide DNA methylation association study of circulating IgE levels identifies novel targets for asthma

Author: Abe, Namiko, Abecasis, Gonçalo, Aguet, Francois, Albert, Christine, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Ardlie, Kristin, Arking, Dan, Arnett, Donna K., Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Ayas, Najib, Balasubramanian, Adithya, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Barwick, Lucas, Beaty, Terri, Beck, Gerald, Becker, Diane, Becker, Lewis, Beer, Rebecca, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Blue, Nathan, Boerwinkle, Eric, Bowden, Donald W., Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Brown, Deborah, Bunting, Karen, Burchard, Esteban, Bustamante, Carlos, Buth, Erin, Cade, Brian, Cardwell, Jonathan, Carey, Vincent, Carrier, Julie, Carson, April P., Carty, Cara, Casaburi, Richard, Casas Romero, Juan P., Casella, James, Castaldi, Peter, Chaffin, Mark, Chang, Christy, Chang, Yi-Cheng, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Chung, Ren-Hua, Clish, Clary, Comhair, Suzy, Conomos, Matthew, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, de las Fuentes, Lisa, de Vries, Paul, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Dinh, Huyen, Doddapaneni, Harsha, Duan, Qing, Dugan-Perez, Shannon, Duggirala, Ravi, Durda, Jon Peter, Dutcher, Susan K., Eaton, Charles, Ekunwe, Lynette, El Boueiz, Adel, Ellinor, Patrick, Emery, Leslie, Erzurum, Serpil, Farber, Charles, Farek, Jesse, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Frazar, Chris, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Shanshan, Gao, Yan, Gass, Margery, Geiger, Heather, Gelb, Bruce, Geraci, Mark, Germer, Soren, Gerszten, Robert, Ghosh, Auyon, Gibbs, Richard, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Graw, Sharon, Gray, Kathryn J., Grine, Daniel, Gross, Colin, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Gupta, Namrata, Haessler, Jeff, Hall, Michael, Han, Yi, Hanly, Patrick, Harris, Daniel, Hawley, Nicola L., He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hobbs, Brian, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Hu, Jianhong, Hung, Yi-Jen, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Khan, Ziad, Kim, Wonji, Kimoff, John, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Jiwon, Lee, Sandra, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Daniel, Lewis, Joshua, Li, Xiaohui, Li, Yun, Lin, Henry, Lin, Honghuang, Lin, Xihong, Liu, Simin, Liu, Yongmei, Liu, Yu, Loos, Ruth J.F., Lubitz, Steven, Lunetta, Kathryn, Luo, James, Magalang, Ulysses, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manning, Alisa, Manson, JoAnn, Martin, Lisa, Marton, Melissa, Mathai, Susan, Mathias, Rasika, May, Susanne, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, McGoldrick, Daniel, McHugh, Caitlin, McNeil, Becky, Mei, Hao, Meigs, James, Menon, Vipin, Mestroni, Luisa, Metcalf, Ginger, Meyers, Deborah A., Mignot, Emmanuel, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L., Mitchell, Braxton D., Moll, Matt, Momin, Zeineen, Montasser, May E., Montgomery, Courtney, Muzny, Donna, Mychaleckyj, Josyf C., Nadkarni, Girish, Naik, Rakhi, Naseri, Take, Natarajan, Pradeep, Nekhai, Sergei, Nelson, Sarah C., Neltner, Bonnie, Nessner, Caitlin, Nickerson, Deborah, Nkechinyere, Osuji, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Okwuonu, Geoffrey, Pack, Allan, Paik, David T., Palmer, Nicholette, Pankow, James, Papanicolaou, George, Parker, Cora, Peloso, Gina, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S., Pleiness, Jacob, Pollin, Toni, Post, Wendy, Powers Becker, Julia, Preethi Boorgula, Meher, Preuss, Michael, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Rajendran, Mahitha, Ramachandran, Vasan S., Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Reeves, Catherine, Regan, Elizabeth, Reiner, Alex, Reupena, Muagututi‘a Sefuiva, Rice, Ken, Rich, Stephen, Robillard, Rebecca, Robine, Nicolas, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Runnels, Alexi, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sabino, Ester Cerdeira, Saleheen, Danish, Salimi, Shabnam, Salvi, Sejal, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay G., Santibanez, Jireh, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sériès, Frédéric, Sheehan, Vivien, Sherman, Stephanie L., Shetty, Amol, Shetty, Aniket, Sheu, Wayne Hui-Heng, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Skomro, Robert, Smith, Albert Vernon, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Snyder, Michael, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne M., Storm, Garrett, Streeten, Elizabeth, Su, Jessica Lasky, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Matthew, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Threlkeld, Machiko, Tinker, Lesley, Tirschwell, David, Tishkoff, Sarah, Tiwari, Hemant, Tong, Catherine, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, Van Den Berg, David, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wang, Fei Fei, Wang, Heming, Wang, Jiongming, Watson, Karol, Watt, Jennifer, Weeks, Daniel E., Weinstock, Joshua, Weir, Bruce, Weiss, Scott T., Weng, Lu-Chen, Wessel, Jennifer, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Williams, Scott, Wilson, Carla, Wilson, James, Winterkorn, Lara, Wong, Quenna, Wu, Baojun, Wu, Joseph, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yu, Ketian, Zekavat, Seyedeh Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zhu, Xiaofeng, Ziv, Elad, Zody, Michael, Zoellner, Sebastian, Recto, Kathryn, Kachroo, Priyadarshini, Huan, Tianxiao, Lee, Gha Young, Bui, Helena, Lee, Dong Heon, Gereige, Jessica, Yao, Chen, Hwang, Shih-Jen, Joehanes, Roby, O’Connor, George T., and DeMeo, Dawn L.
Published: 2023
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10. De novo mutations across 1,465 diverse genomes reveal mutational insights and reductions in the Amish founder population

Author: Kessler, Michael D, Loesch, Douglas P, Perry, James A, Heard-Costa, Nancy L, Taliun, Daniel, Cade, Brian E, Wang, Heming, Daya, Michelle, Ziniti, John, Datta, Soma, Celedón, Juan C, Soto-Quiros, Manuel E, Avila, Lydiana, Weiss, Scott T, Barnes, Kathleen, Redline, Susan S, Vasan, Ramachandran S, Johnson, Andrew D, Mathias, Rasika A, Hernandez, Ryan, Wilson, James G, Nickerson, Deborah A, Abecasis, Goncalo, Browning, Sharon R, Zöllner, Sebastian, O’Connell, Jeffrey R, Mitchell, Braxton D, Lung, and Blood Institute Trans-Omics for Precision Medicine Consortium National Heart, Group, TOPMed Population Genetics Working, O’Connor, Timothy D, Aalbers, Sanne, Abdalla, Moustafa, Abdul-Rahman, Omar, Abecasis, Gonçalo, Abhyankar, Avinash, Adrianto, Indra, Aguet, Francois, Akers, Rachel, Al-Tobasei, Rafet, Albert, Christine, Aldred, Micheala, Almasy, Laura, Almeida, Marcio, Alonso, Alvaro, Ament, Seth, Ampleford, Elizabeth, An, Ping, Anderson, Christopher D, Andersson, Charlotte, Anugu, Pramod, Appelbaum, Elizabeth, Ardlie, Kristin, Arking, Dan, Armasu, Sebastian M, Arnett, Donna K, Arruda, Heather, Arvanitis, Marios, Ashley-Koch, Allison, Ashrani, Aneel, Aslibekyan, Stella, Assimes, Tim, Atkinson, Elizabeth, Auer, Paul, Austin, Thomas R, Avery, Christy, Avila-Pacheco, Julian, Avillach, Paul, Aviv, Abraham, Avramopoulos, Dimitrios, Ballantyne, Christie, Balte, Pallavi, Bamshad, Michael, Bancks, Mike, Barnard, John, Barr, R Graham, Barron-Casella, Emily, Bartz, Traci, Barwick, Lucas, Basu, Saonli, Battle, Alexis, Baumann, Michael, Beame, David, Beaty, Terri, Beck, Gerald, Becker, Lewis, Becker, Diane, Beer, Rebecca, Begum, Ferdouse, Beiser, Alexa, Beitelshees, Amber, Benjamin, Emelia, Benos, Takis, Berk-Rauch, Hanna, Besich, Zachary M, Bezerra, Marcos, Bhatt, Surya, Bi, Wenjian, Bick, Alexander, and Bielak, Larry
Subjects: Biological Sciences, Genetics, Biotechnology, Human Genome, Precision Medicine, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Amish, Cohort Studies, DNA Mutational Analysis, Female, Genetics, Population, Genome, Human, Heterozygote, Humans, Male, Mutation, Pedigree, Whole Genome Sequencing, Young Adult, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Population Genetics Working Group, de novo mutations, diversity, mutation rate, recombination
Abstract: De novo mutations (DNMs), or mutations that appear in an individual despite not being seen in their parents, are an important source of genetic variation whose impact is relevant to studies of human evolution, genetics, and disease. Utilizing high-coverage whole-genome sequencing data as part of the Trans-Omics for Precision Medicine (TOPMed) Program, we called 93,325 single-nucleotide DNMs across 1,465 trios from an array of diverse human populations, and used them to directly estimate and analyze DNM counts, rates, and spectra. We find a significant positive correlation between local recombination rate and local DNM rate, and that DNM rate explains a substantial portion (8.98 to 34.92%, depending on the model) of the genome-wide variation in population-level genetic variation from 41K unrelated TOPMed samples. Genome-wide heterozygosity does correlate with DNM rate, but only explains
Published: 2020

11. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author: Kachroo, Priyadarshini, Hecker, Julian, Chawes, Bo L, Ahluwalia, Tarunveer S, Cho, Michael H, Qiao, Dandi, Kelly, Rachel S, Chu, Su H, Virkud, Yamini V, Huang, Mengna, Barnes, Kathleen C, Burchard, Esteban G, Eng, Celeste, Hu, Donglei, Celedón, Juan C, Daya, Michelle, Levin, Albert M, Gui, Hongsheng, Williams, L Keoki, Forno, Erick, Mak, Angel CY, Avila, Lydiana, Soto-Quiros, Manuel E, Cloutier, Michelle M, Acosta-Pérez, Edna, Canino, Glorisa, Bønnelykke, Klaus, Bisgaard, Hans, Raby, Benjamin A, Lange, Christoph, Weiss, Scott T, Lasky-Su, Jessica A, National Heart, Lung, Abe, Namiko, Abecasis, Goncalo, Albert, Christine, Allred, Nicholette Palmer, Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Barnard, John, Barnes, Kathleen, Barr, R Graham, Barron-Casella, Emily, Beaty, Terri, Becker, Diane, Becker, Lewis, Beer, Rebecca, Begum, Ferdouse, Beitelshees, Amber, Benjamin, Emelia, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Borecki, Ingrid, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Burchard, Esteban, Cardwell, Jonathan, Carty, Cara, Casaburi, Richard, Casella, James, Chaffin, Mark, Chang, Christy, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Chen, Yii-Der Ida, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, and Das, Sayantan
Subjects: Biomedical and Clinical Sciences, Cardiovascular Medicine and Haematology, Clinical Sciences, Biotechnology, Genetics, Lung, Pediatric, Human Genome, Clinical Research, Asthma, 2.1 Biological and endogenous factors, Respiratory, Adolescent, Adult, Cell Adhesion Molecules, Child, Child, Preschool, Costa Rica, Female, Forced Expiratory Volume, Humans, Interferon Regulatory Factors, Male, Middle Aged, Respiratory Physiological Phenomena, Vital Capacity, Whole Genome Sequencing, Young Adult, airway hyperresponsiveness, asthma, lung function, whole genome sequencing, National Heart, Lung, and Blood Institute Trans-Omics for Precision Medicine (TOPMed) Consortium, Respiratory System, Cardiovascular medicine and haematology, Clinical sciences
Abstract: BackgroundAsthma is a common respiratory disorder with a highly heterogeneous nature that remains poorly understood. The objective was to use whole genome sequencing (WGS) data to identify regions of common genetic variation contributing to lung function in individuals with a diagnosis of asthma.MethodsWGS data were generated for 1,053 individuals from trios and extended pedigrees participating in the family-based Genetic Epidemiology of Asthma in Costa Rica study. Asthma affection status was defined through a physician's diagnosis of asthma, and most participants with asthma also had airway hyperresponsiveness (AHR) to methacholine. Family-based association tests for single variants were performed to assess the associations with lung function phenotypes.ResultsA genome-wide significant association was identified between baseline FEV1/FVC ratio and a single-nucleotide polymorphism in the top hit cysteine-rich secretory protein LCCL domain-containing 2 (CRISPLD2) (rs12051168; P = 3.6 × 10-8 in the unadjusted model) that retained suggestive significance in the covariate-adjusted model (P = 5.6 × 10-6). Rs12051168 was also nominally associated with other related phenotypes: baseline FEV1 (P = 3.3 × 10-3), postbronchodilator (PB) FEV1 (7.3 × 10-3), and PB FEV1/FVC ratio (P = 2.7 × 10-3). The identified baseline FEV1/FVC ratio and rs12051168 association was meta-analyzed and replicated in three independent cohorts in which most participants with asthma also had confirmed AHR (combined weighted z-score P = .015) but not in cohorts without information about AHR.ConclusionsThese findings suggest that using specific asthma characteristics, such as AHR, can help identify more genetically homogeneous asthma subgroups with genotype-phenotype associations that may not be observed in all children with asthma. CRISPLD2 also may be important for baseline lung function in individuals with asthma who also may have AHR.
Published: 2019

12. Critical Role for 24-Hydroxylation in Homeostatic Regulation of Vitamin D Metabolism.

Author: Yazdi, Zhinous Shahidzadeh, Streeten, Elizabeth A, Whitlatch, Hilary B, Montasser, May E, Beitelshees, Amber L, and Taylor, Simeon I
Subjects: VITAMIN D metabolism, VITAMIN D deficiency, BODY mass index, CROSSOVER trials, HORMONE regulation
Abstract: Context The body has evolved homeostatic mechanisms to maintain free levels of Ca+2 and 1,25-dihydroxyvitamin D (1,25(OH)2D) within narrow physiological ranges. Clinical guidelines emphasize important contributions of parathyroid hormone (PTH) in maintaining this homeostasis. Objective This work aimed to investigate mechanisms of homeostatic regulation of vitamin D (VitD) metabolism and to apply mechanistic insights to improve clinical assessment of VitD status. Methods This crossover clinical trial studied community participants before and after VitD3 supplementation. Participants included 11 otherwise healthy individuals with VitD deficiency (25-hydroxyvitamin D [25(OH)D] ≤20 ng/mL). VitD3 supplements (50 000 IU once or twice a week depending on body mass index, for 4-6 weeks) were administered to achieve 25(OH)D of 30 ng/mL or greater. Results VitD3 supplementation significantly increased mean 25(OH)D by 2.7-fold and 24,25-dihydroxyvitamin D (24,25(OH)2D) by 4.3-fold. In contrast, mean levels of PTH, fibroblast growth factor-23, and 1,25(OH)2D did not change. Mathematical modeling suggested that 24-hydroxylase activity was maximal for 25(OH)D 50 ng/mL or greater and achieved a minimum (∼90% suppression) with 25(OH)D less than 10 to 20 ng/mL. The 1,25(OH)2D/24,25(OH)2D ratio better predicted modeled 24-hydroxylase activity (h) (ρ = −0.85; P =.001) compared to total plasma 25(OH)D (ρ = 0.51; P =.01) and the 24,25(OH)2D/25(OH)D ratio (ρ = 0.37; P =.3). Conclusion Suppression of 24-hydroxylase provides a first line of defense against symptomatic VitD deficiency by decreasing metabolic clearance of 1,25(OH)2D. The 1,25(OH)2D/24,25(OH)2D ratio provides a useful index of VitD status since it incorporates 24,25(OH)2D levels, and therefore provides insight into 24-hydroxylase activity. When VitD availability is limited, this suppresses 24-hydroxylase activity—thereby decreasing the level of 24,25(OH)2D and increasing the 1,25(OH)2D/24,25(OH)2D ratio. Thus, an increased 1,25(OH)2D/24,25(OH)2D ratio signifies triggering of homeostatic regulation, which occurs at early stages of VitD deficiency. [ABSTRACT FROM AUTHOR]
Published: 2025
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13. Leveraging linkage evidence to identify low-frequency and rare variants on 16p13 associated with blood pressure using TOPMed whole genome sequencing data

Author: He, Karen Y, Li, Xiaoyin, Kelly, Tanika N, Liang, Jingjing, Cade, Brian E, Assimes, Themistocles L, Becker, Lewis C, Beitelshees, Amber L, Bress, Adam P, Chang, Yen-Pei Christy, Chen, Yii-Der Ida, de Vries, Paul S, Fox, Ervin R, Franceschini, Nora, Furniss, Anna, Gao, Yan, Guo, Xiuqing, Haessler, Jeffrey, Hwang, Shih-Jen, Irvin, Marguerite Ryan, Kalyani, Rita R, Liu, Ching-Ti, Liu, Chunyu, Martin, Lisa Warsinger, Montasser, May E, Muntner, Paul M, Mwasongwe, Stanford, Palmas, Walter, Reiner, Alex P, Shimbo, Daichi, Smith, Jennifer A, Snively, Beverly M, Yanek, Lisa R, Boerwinkle, Eric, Correa, Adolfo, Cupples, L Adrienne, He, Jiang, Kardia, Sharon LR, Kooperberg, Charles, Mathias, Rasika A, Mitchell, Braxton D, Psaty, Bruce M, Vasan, Ramachandran S, Rao, DC, Rich, Stephen S, Rotter, Jerome I, Wilson, James G, Chakravarti, Aravinda, Morrison, Alanna C, Levy, Daniel, Arnett, Donna K, Redline, Susan, and Zhu, Xiaofeng
Subjects: Biological Sciences, Genetics, Heart Disease, Biotechnology, Human Genome, Cardiovascular, Minority Health, Precision Medicine, Clinical Research, 2.1 Biological and endogenous factors, Good Health and Well Being, Alternative Splicing, Blood Pressure, Chromosomes, Human, Pair 16, Exome, Female, Follow-Up Studies, Genetic Linkage, Genetic Variation, Genome, Human, Genome-Wide Association Study, High-Throughput Nucleotide Sequencing, Humans, Male, RNA Splicing Factors, Recombinases, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Blood Pressure Working Group, Complementary and Alternative Medicine, Paediatrics and Reproductive Medicine, Genetics & Heredity, Reproductive medicine
Abstract: In this study, we investigated low-frequency and rare variants associated with blood pressure (BP) by focusing on a linkage region on chromosome 16p13. We used whole genome sequencing (WGS) data obtained through the NHLBI Trans-Omics for Precision Medicine (TOPMed) program on 395 Cleveland Family Study (CFS) European Americans (CFS-EA). By analyzing functional coding variants and non-coding rare variants with CADD score > 10 residing within the chromosomal region in families with linkage evidence, we observed 25 genes with nominal statistical evidence (burden or SKAT p
Published: 2019

14. Multisite investigation of strategies for the clinical implementation of pre-emptive pharmacogenetic testing

Author: Duarte, Julio D., Dalton, Rachel, Elchynski, Amanda L., Smith, D. Max, Cicali, Emily J., Lee, James C., Duong, Benjamin Q., Petry, Natasha J., Aquilante, Christina L., Beitelshees, Amber L., Empey, Philip E., Johnson, Julie A., Obeng, Aniwaa Owusu, Pasternak, Amy L., Pratt, Victoria M., Ramsey, Laura B., Tuteja, Sony, Van Driest, Sara L., Wiisanen, Kristin, Hicks, J. Kevin, and Cavallari, Larisa H.
Published: 2021
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15. Sphingolipid Metabolic Pathway Impacts Thiazide Diuretics Blood Pressure Response: Insights From Genomics, Metabolomics, and Lipidomics

Author: Shahin, Mohamed H, Gong, Yan, Frye, Reginald F, Rotroff, Daniel M, Beitelshees, Amber L, Baillie, Rebecca A, Chapman, Arlene B, Gums, John G, Turner, Stephen T, Boerwinkle, Eric, Motsinger‐Reif, Alison, Fiehn, Oliver, Cooper‐DeHoff, Rhonda M, Han, Xianlin, Kaddurah‐Daouk, Rima, and Johnson, Julie A
Subjects: Human Genome, Genetics, Hypertension, Biotechnology, 2.1 Biological and endogenous factors, Aetiology, Cardiovascular, Adult, Blood Pressure, Female, Genomics, Humans, Hydrochlorothiazide, Lipid Metabolism, Male, Metabolic Networks and Pathways, Metabolomics, Middle Aged, Nitriles, Pharmacogenetics, Prognosis, Serine C-Palmitoyltransferase, Siloxanes, Sodium Chloride Symporter Inhibitors, Sphingolipids, Treatment Outcome, blood pressure, lipid metabolites, metabolomics, pharmacogenetics, thiazide diuretics, Cardiorespiratory Medicine and Haematology
Abstract: Although hydrochlorothiazide (HCTZ) is a well-established first-line antihypertensive in the United States,
Published: 2018

16. Best–worst scaling methodology to evaluate constructs of the Consolidated Framework for Implementation Research: application to the implementation of pharmacogenetic testing for antidepressant therapy

Author: Salloum, Ramzi G., Bishop, Jeffrey R., Elchynski, Amanda L., Smith, D. Max, Rowe, Elizabeth, Blake, Kathryn V., Limdi, Nita A., Aquilante, Christina L., Bates, Jill, Beitelshees, Amber L., Cipriani, Amber, Duong, Benjamin Q., Empey, Philip E., Formea, Christine M., Hicks, J. Kevin, Mroz, Pawel, Oslin, David, Pasternak, Amy L., Petry, Natasha, Ramsey, Laura B., Schlichte, Allyson, Swain, Sandra M., Ward, Kristen M., Wiisanen, Kristin, Skaar, Todd C., Van Driest, Sara L., Cavallari, Larisa H., and Tuteja, Sony
Published: 2022
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17. An Amish founder population reveals rare-population genetic determinants of the human lipidome

Author: Montasser, May E., Aslibekyan, Stella, Srinivasasainagendra, Vinodh, Tiwari, Hemant K., Patki, Amit, Bagheri, Minoo, Kind, Tobias, Barupal, Dinesh Kumar, Fan, Sili, Perry, James, Ryan, Kathleen A., Shuldiner, Alan R., Arnett, Donna K., Beitelshees, Amber L., Irvin, Marguerite Ryan, and O’Connell, Jeffrey R.
Published: 2022
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18. Evaluating the Effect of Estimating Renal Function With the CKD‐EPI 2021 Equation on the ABCD‐GENE Score for Clopidogrel Response Prediction.

Author: AlSaeed, Maryam Jamal, Thomas, Cameron D., Franchi, Francesco, Keeley, Ellen C., Duarte, Julio D., Gong, Yan, Rossi, Joseph S., Beitelshees, Amber L., Stouffer, George A., Lee, Craig R., Angiolillo, Dominick J., and Cavallari, Larisa H.
Subjects: PERCUTANEOUS coronary intervention, GLOMERULAR filtration rate, CHRONIC kidney failure, BODY mass index, BLACK people
Abstract: The ABCD‐GENE score was developed to predict poor response to clopidogrel and includes Age, Body mass index, Chronic kidney disease (CKD; estimated glomerular filtration rate [eGFR] < 60 mL/min/1.73 m2), Diabetes, and CYP2C19 GENE variants; a score ≥ 10 is predictive of reduced clopidogrel effectiveness after percutaneous coronary intervention (PCI). Estimation of GFR without a race variable via the CKD‐EPI Scr 2021 equation is now recommended. We examined the impact of using the CKD‐EPI Scr 2021 vs. 2009 equation on the ABCD‐GENE score for post‐PCI patients. A total of 4335 adult patients (n = 925 Black) who underwent PCI and CYP2C19 genotyping were included, with GFR estimated for each patient via the CKD‐EPI Scr 2021 and CKD‐EPI 2009 equations. The ABCD‐GENE score, calculated based on each GFR estimation, was compared. With the CKD‐EPI Scr 2021 vs. 2009 equation, median (IQR) eGFR was lower (74 [55–94] vs. 81 [60–103] mL/min/1.73 m2, P < 0.001), and CKD prevalence was higher (31% vs. 25%, P < 0.001) among Black patients, whereas eGFR was higher (85 [65–99] vs. 80 [61–94] mL/min/1.73m2, P < 0.001), and CKD prevalence was lower (20% vs. 24%, P < 0.001) in non‐Black patients. This led to 12 (1%) Black patients being reclassified from low to high risk of poor clopidogrel response and 30 (1%) non‐Black patients being recategorized from high to low risk (P < 0.001 for both comparisons). Removal of the race variable from GFR estimation significantly impacted the prediction of clopidogrel effectiveness via the ABCD‐GENE score. [ABSTRACT FROM AUTHOR]
Published: 2024
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19. Evaluating the extent of reusability of CYP2C19 genotype data among patients genotyped for antiplatelet therapy selection

Author: Beitelshees, Amber L., Stevenson, James M., El Rouby, Nihal, Dillon, Chrisly, Empey, Philip E., Fielstein, Elliot M., Johnson, Julie A., Limdi, Nita A., Ong, Henry H., Franchi, Francesco, Angiolillo, Dominick J., Peterson, Joshua F., Rosenman, Marc B., Skaar, Todd C., Tuteja, Sony, and Cavallari, Larisa H.
Published: 2020
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20. A Genetic Response Score for Hydrochlorothiazide Use

Author: Shahin, Mohamed H, Gong, Yan, McDonough, Caitrin W, Rotroff, Daniel M, Beitelshees, Amber L, Garrett, Timothy J, Gums, John G, Motsinger-Reif, Alison, Chapman, Arlene B, Turner, Stephen T, Boerwinkle, Eric, Frye, Reginald F, Fiehn, Oliver, Cooper-DeHoff, Rhonda M, Kaddurah-Daouk, Rima, and Johnson, Julie A
Subjects: Medical Biochemistry and Metabolomics, Biomedical and Clinical Sciences, Patient Safety, Biotechnology, Hypertension, Genetics, Clinical Research, Human Genome, AMP-Activated Protein Kinases, Adult, Aged, Antihypertensive Agents, Blood Pressure Monitoring, Ambulatory, Cohort Studies, DCC Receptor, Epoxide Hydrolases, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Humans, Hydrochlorothiazide, Male, Metabolomics, Middle Aged, Pharmacogenetics, Polymorphism, Genetic, Prospective Studies, Receptors, Cell Surface, Severity of Illness Index, Signal Transduction, Treatment Outcome, Tumor Suppressor Proteins, White People, hydrochlorothiazide, hypertension, genome-wide association study, metabolomics, pharmacogenetics, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Public Health and Health Services, Cardiovascular System & Hematology, Cardiovascular medicine and haematology, Clinical sciences
Abstract: Hydrochlorothiazide is among the most commonly prescribed antihypertensives; yet,
Published: 2016

21. Novel plasma biomarker of atenolol-induced hyperglycemia identified through a metabolomics-genomics integrative approach

Author: de Oliveira, Felipe A, Shahin, Mohamed H, Gong, Yan, McDonough, Caitrin W, Beitelshees, Amber L, Gums, John G, Chapman, Arlene B, Boerwinkle, Eric, Turner, Stephen T, Frye, Reginald F, Fiehn, Oliver, Kaddurah-Daouk, Rima, Johnson, Julie A, and Cooper-DeHoff, Rhonda M
Subjects: Medical Biochemistry and Metabolomics, Biological Sciences, Biomedical and Clinical Sciences, Genetics, Diabetes, Clinical Research, Biotechnology, Human Genome, Metabolic and endocrine, Pharmacometabolomics, Pharmacogenomics, beta-blockers, Atenolol, Hyperglycemia, beta-alanine, β-alanine, β-blockers, Analytical Chemistry, Biochemistry and Cell Biology, Clinical Sciences, Biochemistry and cell biology, Medical biochemistry and metabolomics, Analytical chemistry
Abstract: While atenolol is an effective antihypertensive agent, its use is also associated with adverse events including hyperglycemia and incident diabetes that may offset the benefits of blood pressure lowering. By combining metabolomic and genomic data acquired from hypertensive individuals treated with atenolol, it may be possible to better understand the pathways that most impact the development of an adverse glycemic state. To identify biomarkers that can help predict susceptibility to blood glucose excursions during exposure to atenolol. Plasma samples acquired from 234 Caucasian participants treated with atenolol in the Pharmacogenomic Evaluation of Antihypertensive Responses trial were analyzed by gas chromatography Time-Of-Flight Mass Spectroscopy. Metabolomics and genomics data were integrated by first correlating participant's metabolomic profiles to change in glucose after treatment with atenolol, and then incorporating genotype information from genes involved in metabolite pathways associated with glucose response. Our findings indicate that the baseline level of β-alanine was associated with glucose change after treatment with atenolol (Q = 0.007, β = 2.97 mg/dL). Analysis of genomic data revealed that carriers of the G allele for SNP rs2669429 in gene DPYS, which codes for dihydropyrimidinase, an enzyme involved in β-alanine formation, had significantly higher glucose levels after treatment with atenolol when compared with non-carriers (Q = 0.05, β = 2.76 mg/dL). This finding was replicated in participants who received atenolol as an add-on therapy (P = 0.04, β = 1.86 mg/dL). These results suggest that β-alanine and rs2669429 may be predictors of atenolol-induced hyperglycemia in Caucasian individuals and further investigation is warranted.
Published: 2016

22. Cost-effectiveness of CYP2C19-guided antiplatelet therapy in patients with acute coronary syndrome and percutaneous coronary intervention informed by real-world data

Author: Limdi, Nita A., Cavallari, Larisa H., Lee, Craig R., Hillegass, William B., Holmes, Ann M., Skaar, Todd C., Pisu, Maria, Dillon, Chrisly, Beitelshees, Amber L., Empey, Philip E., Duarte, Julio D., Diaby, Vakaramoko, Gong, Yan, Johnson, Julie A., Graves, John, Garbett, Shawn, Zhou, Zilu, and Peterson, Josh F.
Published: 2020
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23. SGLT2 inhibitors as adjunctive therapy for type 1 diabetes: balancing benefits and risks

Author: Taylor, Simeon I, Blau, Jenny E, Rother, Kristina I, and Beitelshees, Amber L
Published: 2019
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24. Whole Genome Sequencing Identifies CRISPLD2 as a Lung Function Gene in Children With Asthma

Author: Abe, Namiko, Abecasis, Goncalo, Albert, Christine, Palmer Allred, Nicholette (Nichole), Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Deborah, Arking, Dan, Arnett, Donna K., Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Barnard, John, Barnes, Kathleen, Barr, R. Graham, Barron-Casella, Emily, Beaty, Terri, Becker, Diane, Becker, Lewis, Beer, Rebecca, Begum, Ferdouse, Beitelshees, Amber, Benjamin, Emelia, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Borecki, Ingrid, Bowler, Russell, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Burchard, Esteban, Cardwell, Jonathan, Carty, Cara, Casaburi, Richard, Casella, James, Chaffin, Mark, Chang, Christy, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Chen, Yii-Der Ida, Cho, Michael H., Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L. Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, Das, Sayantan, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Do, Ron, Duan, Qing, Duggirala, Ravi, Durda, Peter, Dutcher, Susan, Eaton, Charles, Ekunwe, Lynette, Ellinor, Patrick, Emery, Leslie, Farber, Charles, Farnam, Leanna, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Fu, Mao, Fullerton, Stephanie M., Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Yan, Gass, Margery, Gelb, Bruce, Geng, Xiaoqi (Priscilla), Germer, Soren, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Gu, C. Charles, Guan, Yue, Guo, Xiuqing, Haessler, Jeff, Hall, Michael, Harris, Daniel, Hawley, Nicola, He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hokanson, John, Holly, Kramer, Hong, Elliott, Hoth, Karin, (Agnes) Hsiung, Chao, Huston, Haley, Hwu, Chii Min, Irvin, Marguerite Ryan, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Jhun, Min A., Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kachroo, Priyadarshini, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kathiresan, Sekar, Kaufman, Laura, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Krauter, Stephanie, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Seunggeun Shawn, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Yun, Lin, Honghuang, Lin, Keng Han, Liu, Simin, Liu, Yongmei, Loos, Ruth, Lubitz, Steven, Lunetta, Kathryn, Luo, James, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manson, JoAnn, Margolin, Lauren, Martin, Lisa, Mathai, Susan, Mathias, Rasika, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, Mei, Hao, Meyers, Deborah A., Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L., Mitchell, Braxton, Montasser, May E., Musani, Solomon, Mwasongwe, Stanford, Mychaleckyj, Josyf C., Nadkarni, Girish, Naik, Rakhi, Natarajan, Pradeep, Nekhai, Sergei, Nickerson, Deborah, North, Kari, O'Connell, Jeff, O'Connor, Tim, Ochs-Balcom, Heather, Pankow, James, Papanicolaou, George, Parker, Margaret, Parsa, Afshin, Penchev, Sara, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Lawrence S., Phillips, Sam, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Prokopenko, Dmitry, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Ramachandran, Vasan, Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Regan, Elizabeth, Reiner, Alex, Rice, Ken, Rich, Stephen, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sakornsakolpat, Phuwanat, Salimi, Shabnam, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay, Scheller, Christopher, Schmidt, Ellen, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Seidman, Jonathan, Sheehan, Vivien, Shetty, Amol, Shetty, Aniket, Sheu, Wayne Hui-Heng, Shoemaker, M. Benjamin, Silver, Brian, Silverman, Edwin, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne, Streeten, Elizabeth, Sung, Yun Ju, Su-Lasky, Jessica, Sylvia, Jody, Szpiro, Adam, Sztalryd, Carole, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wan, Emily, Wang, Fei Fei, Watson, Karol, Weeks, Daniel E., Weir, Bruce, Weiss, Scott, Weng, Lu-Chen, Willer, Cristen, Williams, Kayleen, Williams, L. Keoki, Wilson, Carla, Wilson, James, Wong, Quenna, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yang, Rongze, Zaghloul, Norann, Zekavat, Maryam, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zheng, Xiuwen, Zhi, Degui, Zhou, Xiang, Zody, Michael, Zoellner, Sebastian, Hecker, Julian, Chawes, Bo L., Ahluwalia, Tarunveer S., Kelly, Rachel S., Chu, Su H., Virkud, Yamini V., Huang, Mengna, Barnes, Kathleen C., Burchard, Esteban G., Eng, Celeste, Hu, Donglei, Celedón, Juan C., Levin, Albert M., Gui, Hongsheng, Forno, Erick, Mak, Angel C.Y., Avila, Lydiana, Soto-Quiros, Manuel E., Cloutier, Michelle M., Acosta-Pérez, Edna, Canino, Glorisa, Bønnelykke, Klaus, Bisgaard, Hans, Raby, Benjamin A., Weiss, Scott T., and Lasky-Su, Jessica A.
Published: 2019
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25. Multi-site investigation of strategies for the clinical implementation of CYP2D6 genotyping to guide drug prescribing

Author: Cavallari, Larisa H., Van Driest, Sara L., Prows, Cynthia A., Bishop, Jeffrey R., Limdi, Nita A., Pratt, Victoria M., Ramsey, Laura B., Smith, D. Max, Tuteja, Sony, Duong, Benjamin Q., Hicks, J. Kevin, Lee, James C., Obeng, Aniwaa Owusu, Beitelshees, Amber L., Bell, Gillian C., Blake, Kathryn, Crona, Daniel J., Dressler, Lynn, Gregg, Ryan A., Hines, Lindsay J., Scott, Stuart A., Shelton, Richard C., Weitzel, Kristin Wiisanen, Johnson, Julie A., Peterson, Josh F., Empey, Philip E., and Skaar, Todd C.
Published: 2019
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26. Effect of plasma MicroRNA on antihypertensive response to beta blockers in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) studies

Author: Solayman, Mohamed H., Langaee, Taimour Y., Gong, Yan, Shahin, Mohamed H., Turner, Stephen T., Chapman, Arlene B., Gums, John G., Boerwinkle, Eric, Beitelshees, Amber L., El-Hamamsy, Manal, El-Wakeel, Lamia, Cooper-DeHoff, Rhonda M., Badary, Osama A., and Johnson, Julie A.
Published: 2019
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27. Is a Diabetes Mellitus–Linked Amino Acid Signature Associated With &bgr;-Blocker–Induced Impaired Fasting Glucose?

Author: Cooper-DeHoff, Rhonda M, Hou, Wei, Weng, Liming, Baillie, Rebecca A, Beitelshees, Amber L, Gong, Yan, Shahin, Mohamed HA, Turner, Stephen T, Chapman, Arlene, Gums, John G, Boyle, Stephen H, Zhu, Hongjie, Wikoff, William R, Boerwinkle, Eric, Fiehn, Oliver, Frye, Reginald F, Kaddurah-Daouk, Rima, and Johnson, Julie A
Subjects: Diabetes, Genetics, Nutrition, Metabolic and endocrine, Adolescent, Adrenergic beta-Antagonists, Adult, Aged, Amino Acids, Atenolol, Blood Glucose, Diabetes Mellitus, Type 2, Fasting, Female, Humans, Hypertension, Male, Middle Aged, Young Adult, amino acids, pharmacogenetics, metabolomics, Medical Biotechnology, Cardiorespiratory Medicine and Haematology, Cardiovascular System & Hematology
Abstract: BackgroundThe 5-amino acid (AA) signature, including isoleucine, leucine, valine, tyrosine, and phenylalanine, has been associated with incident diabetes mellitus and insulin resistance. We investigated whether this same AA signature, single-nucleotide polymorphisms in genes in their catabolic pathway, was associated with development of impaired fasting glucose (IFG) after atenolol treatment.Methods and resultsAmong 234 European American participants enrolled in the Pharmacogenomic Evaluation of Antihypertensive Responses (PEAR) study and treated with atenolol for 9 weeks, we prospectively followed a nested cohort that had both metabolomics profiling and genotype data available for the development of IFG. We assessed the association between baseline circulating levels of isoleucine, leucine, valine, tyrosine, and phenylalanine, as well as single-nucleotide polymorphisms in branched-chain amino-acid transaminase 1 (BCAT1) and phenylalanine hydroxylase (PAH) with development of IFG. All baseline AA levels were strongly associated with IFG development. Each increment in standard deviation of the 5 AAs was associated with the following odds ratio and 95% confidence interval for IFG based on a fully adjusted model: isoleucine 2.29 (1.31-4.01), leucine 1.80 (1.10-2.96), valine 1.77 (1.07-2.92), tyrosine 2.13 (1.20-3.78), and phenylalanine 2.04 (1.16-3.59). The composite P value was 2×10(-5). Those with PAH (rs2245360) AA genotype had the highest incidence of IFG (P for trend=0.0003).ConclusionsOur data provide important insight into the metabolic and genetic mechanisms underlying atenolol-associated adverse metabolic effects. Clinical Trial Registration- http://www.clinicaltrials.gov; Unique Identifier: NCT00246519.
Published: 2014

28. Precision Antiplatelet Therapy after Percutaneous Coronary Intervention (Precision PCI) Registry – Informing optimal antiplatelet strategies.

Author: Cavallari, Larisa H., Lee, Craig R., Franchi, Francesco, Keeley, Ellen C., Rossi, Joseph S., Thomas, Cameron D., Gong, Yan, McDonough, Caitrin W., Starostik, Petr, Al Saeed, Maryam J., Been, Latonya, Kulick, Natasha, Malave, Jean, Mulrenin, Ian R., Nguyen, Anh B., Terrell, Joshua N., Tillotson, Grace, Beitelshees, Amber L., Winterstein, Almut G., and Stouffer, George A.
Subjects: PLATELET aggregation inhibitors, PERCUTANEOUS coronary intervention, PLATELET function tests, CYTOCHROME P-450 CYP2C19, PRASUGREL
Abstract: Dual antiplatelet therapy (DAPT) with aspirin and a P2Y12 receptor inhibitor (clopidogrel, prasugrel, or ticagrelor) is indicated after percutaneous coronary intervention (PCI) to reduce the risk of atherothrombotic events. Approximately 30% of the US population has a CYP2C19 no‐function allele that reduces the effectiveness of clopidogrel, but not prasugrel or ticagrelor, after PCI. We have shown improved outcomes with the integration of CYP2C19 genotyping into clinical care to guide the selection of prasugrel or ticagrelor in CYP2C19 no‐function allele carriers. However, the influence of patient‐specific demographic, clinical, and other genetic factors on outcomes with genotype‐guided DAPT has not been defined. In addition, the impact of genotype‐guided de‐escalation from prasugrel or ticagrelor to clopidogrel in patients without a CYP2C19 no‐function allele has not been investigated in a diverse, real‐world clinical setting. The Precision Antiplatelet Therapy after Percutaneous Coronary Intervention (Precision PCI) Registry is a multicenter US registry of patients who underwent PCI and clinical CYP2C19 testing. The registry is enrolling a diverse population, assessing atherothrombotic and bleeding events over 12 months, collecting DNA samples, and conducting platelet function testing in a subset of patients. The registry aims to define the influence of African ancestry and other patient‐specific factors on clinical outcomes with CYP2C19‐guided DAPT, evaluate the safety and effectiveness of CYP2C19‐guided DAPT de‐escalation following PCI in a real‐world setting, and identify additional genetic influences of clopidogrel response after PCI, with the ultimate goal of establishing optimal strategies for individualized antiplatelet therapy that improves outcomes in a diverse, real‐world population. [ABSTRACT FROM AUTHOR]
Published: 2024
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29. Value of Vitamin D Metabolite Ratios in 3 Patients as Diagnostic Criteria to Assess Vitamin D Status.

Author: Yazdi, Zhinous Shahidzadeh, Streeten, Elizabeth A., Whitlatch, Hilary B., Bargal, Salma A., Beitelshees, Amber L., and Taylor, Simeon I.
Subjects: VITAMIN D, PARATHYROID hormone, CARRIER proteins, HYPERPARATHYROIDISM, DIETARY supplements
Abstract: Although clinical guidelines recommend measuring total plasma 25-hydroxyvitamin D (25[OH]D) to assess vitamin D (VitD) status, this index does not account for 3-fold inter-individual variation in VitD binding protein (VDBP) level. We present 3 individuals with total plasma 25(OH)D levels of 10.8 to 12.3 ng/mL (27-30.7 nmol/L). Because Endocrine Society guidelines define VitD deficiency as 25(OH)D = 20 ng/mL (50 nmol/L), all 3 would be judged to be VitD deficient. VitD3 supplementation increased 25(OH)D to the range of 31.7 to 33.8 ng/mL (79.1-84.4 nmol/L). Patient #1 exhibited secondary hyperparathyroidism; VitD3 supplementation decreased parathyroid hormone (PTH) by 34% without a clinically significant change in PTH levels in the other 2 individuals. Thus, 25(OH)D level did not distinguish between the 1 patient who had secondary hyperparathyroidism and the 2 who did not. We therefore inquired whether VitD metabolite ratios (which are VDBP-independent) might distinguish among these 3 individuals. Of all the assessed ratios, the 1,25(OH)2D/24,25(OH)2D ratio was the most informative, which had a value of 102 pg/ng in the individual with secondary hyperparathyroidism but lower values (41 and 20 pg/ng) in the other 2 individuals. These cases illustrate the value of the 1,25(OH)2D/24,25(OH)2D ratio to provide clinically relevant information about VitD status. [ABSTRACT FROM AUTHOR]
Published: 2024
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30. Purine Pathway Implicated in Mechanism of Resistance to Aspirin Therapy: Pharmacometabolomics‐Informed Pharmacogenomics

Author: Yerges-Armstrong, Laura M, Ellero-Simatos, Sandrine, Georgiades, Anastasia, Zhu, Hongjie, Lewis, Joshua, Horenstein, Richard B, Beitelshees, Amber L, Dane, Adrie, Reijmers, Theo, Hankemeier, Thomas, Fiehn, Oliver, Shuldiner, Alan R, Kaddurah-Daouk, Rima, and Network, Pharmacometabolomics Research
Subjects: Medical Biochemistry and Metabolomics, Pharmacology and Pharmaceutical Sciences, Biomedical and Clinical Sciences, Precision Medicine, Patient Safety, Human Genome, Genetics, Clinical Research, Cardiovascular, Good Health and Well Being, Adenosine Kinase, Adult, Alleles, Aspirin, Drug Resistance, Female, Humans, Male, Metabolomics, Platelet Aggregation Inhibitors, Purines, Pharmacology & Pharmacy, Pharmacology and pharmaceutical sciences
Abstract: Although aspirin is a well-established antiplatelet agent, the mechanisms of aspirin resistance remain poorly understood. Metabolomics allows for measurement of hundreds of small molecules in biological samples, enabling detailed mapping of pathways involved in drug response. We defined the metabolic signature of aspirin exposure in subjects from the Heredity and Phenotype Intervention Heart Study. Many metabolites, including known aspirin catabolites, changed on exposure to aspirin, and pathway enrichment analysis identified purine metabolism as significantly affected by drug exposure. Furthermore, purines were associated with aspirin response, and poor responders had higher postaspirin adenosine and inosine levels than did good responders (n = 76; both P < 4 × 10(-3)). Using our established "pharmacometabolomics-informed pharmacogenomics" approach, we identified genetic variants in adenosine kinase associated with aspirin response. Combining metabolomics and genomics allowed for more comprehensive interrogation of mechanisms of variation in aspirin response--an important step toward personalized treatment approaches for cardiovascular disease.
Published: 2013

31. Loci influencing blood pressure identified using a cardiovascular gene-centric array

Author: Ganesh, Santhi K, Tragante, Vinicius, Guo, Wei, Guo, Yiran, Lanktree, Matthew B, Smith, Erin N, Johnson, Toby, Castillo, Berta Almoguera, Barnard, John, Baumert, Jens, Chang, Yen-Pei Christy, Elbers, Clara C, Farrall, Martin, Fischer, Mary E, Franceschini, Nora, Gaunt, Tom R, Gho, Johannes MIH, Gieger, Christian, Gong, Yan, Isaacs, Aaron, Kleber, Marcus E, Leach, Irene Mateo, McDonough, Caitrin W, Meijs, Matthijs FL, Mellander, Olle, Molony, Cliona M, Nolte, Ilja M, Padmanabhan, Sandosh, Price, Tom S, Rajagopalan, Ramakrishnan, Shaffer, Jonathan, Shah, Sonia, Shen, Haiqing, Soranzo, Nicole, van der Most, Peter J, Van Iperen, Erik PA, Van Setten, Jessic A, Vonk, Judith M, Zhang, Li, Beitelshees, Amber L, Berenson, Gerald S, Bhatt, Deepak L, Boer, Jolanda MA, Boerwinkle, Eric, Burkley, Ben, Burt, Amber, Chakravarti, Aravinda, Chen, Wei, Cooper-DeHoff, Rhonda M, Curtis, Sean P, Dreisbach, Albert, Duggan, David, Ehret, Georg B, Fabsitz, Richard R, Fornage, Myriam, Fox, Ervin, Furlong, Clement E, Gansevoort, Ron T, Hofker, Marten H, Hovingh, G Kees, Kirkland, Susan A, Kottke-Marchant, Kandice, Kutlar, Abdullah, LaCroix, Andrea Z, Langaee, Taimour Y, Li, Yun R, Lin, Honghuang, Liu, Kiang, Maiwald, Steffi, Malik, Rainer, Murugesan, Gurunathan, Newton-Cheh, Christopher, O'Connell, Jeffery R, Onland-Moret, N Charlotte, Ouwehand, Willem H, Palmas, Walter, Penninx, Brenda W, Pepine, Carl J, Pettinger, Mary, Polak, Joseph F, Ramachandran, Vasan S, Ranchalis, Jane, Redline, Susan, Ridker, Paul M, Rose, Lynda M, Scharnag, Hubert, Schork, Nicholas J, Shimbo, Daichi, Shuldiner, Alan R, Srinivasan, Sathanur R, Stolk, Ronald P, Taylor, Herman A, Thorand, Barbara, Trip, Mieke D, van Duijn, Cornelia M, Verschuren, W Monique, Wijmenga, Cisca, Winkelmann, Bernhard R, Wyatt, Sharon, and Young, J Hunter
Subjects: Hypertension, Heart Disease, Human Genome, Genetics, Clinical Research, Cardiovascular, Aetiology, 2.1 Biological and endogenous factors, Adult, Aged, Blood Pressure, Cardiovascular Diseases, Chromosome Mapping, Cohort Studies, Female, Genetic Predisposition to Disease, Genome-Wide Association Study, Genotype, Humans, Male, Middle Aged, Polymorphism, Single Nucleotide, White People, CARDIOGRAM, METASTROKE, LifeLines Cohort Study, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract: Blood pressure (BP) is a heritable determinant of risk for cardiovascular disease (CVD). To investigate genetic associations with systolic BP (SBP), diastolic BP (DBP), mean arterial pressure (MAP) and pulse pressure (PP), we genotyped ∼50 000 single-nucleotide polymorphisms (SNPs) that capture variation in ∼2100 candidate genes for cardiovascular phenotypes in 61 619 individuals of European ancestry from cohort studies in the USA and Europe. We identified novel associations between rs347591 and SBP (chromosome 3p25.3, in an intron of HRH1) and between rs2169137 and DBP (chromosome1q32.1 in an intron of MDM4) and between rs2014408 and SBP (chromosome 11p15 in an intron of SOX6), previously reported to be associated with MAP. We also confirmed 10 previously known loci associated with SBP, DBP, MAP or PP (ADRB1, ATP2B1, SH2B3/ATXN2, CSK, CYP17A1, FURIN, HFE, LSP1, MTHFR, SOX6) at array-wide significance (P < 2.4 × 10(-6)). We then replicated these associations in an independent set of 65 886 individuals of European ancestry. The findings from expression QTL (eQTL) analysis showed associations of SNPs in the MDM4 region with MDM4 expression. We did not find any evidence of association of the two novel SNPs in MDM4 and HRH1 with sequelae of high BP including coronary artery disease (CAD), left ventricular hypertrophy (LVH) or stroke. In summary, we identified two novel loci associated with BP and confirmed multiple previously reported associations. Our findings extend our understanding of genes involved in BP regulation, some of which may eventually provide new targets for therapeutic intervention.
Published: 2013

32. Pharmacometabolomics reveals racial differences in response to atenolol treatment.

Author: Wikoff, William R, Frye, Reginald F, Zhu, Hongjie, Gong, Yan, Boyle, Stephen, Churchill, Erik, Cooper-Dehoff, Rhonda M, Beitelshees, Amber L, Chapman, Arlene B, Fiehn, Oliver, Johnson, Julie A, Kaddurah-Daouk, Rima, and Pharmacometabolomics Research Network
Subjects: Pharmacometabolomics Research Network, Humans, Hypertension, Atenolol, Antihypertensive Agents, Cluster Analysis, Risk Factors, Genomics, Pharmacogenetics, Polymorphism, Single Nucleotide, Adult, Middle Aged, African Americans, European Continental Ancestry Group, Female, Male, Metabolic Networks and Pathways, Metabolomics, Metabolome, Polymorphism, Single Nucleotide, General Science & Technology
Abstract: Antihypertensive drugs are among the most commonly prescribed drugs for chronic disease worldwide. The response to antihypertensive drugs varies substantially between individuals and important factors such as race that contribute to this heterogeneity are poorly understood. In this study we use metabolomics, a global biochemical approach to investigate biochemical changes induced by the beta-adrenergic receptor blocker atenolol in Caucasians and African Americans. Plasma from individuals treated with atenolol was collected at baseline (untreated) and after a 9 week treatment period and analyzed using a GC-TOF metabolomics platform. The metabolomic signature of atenolol exposure included saturated (palmitic), monounsaturated (oleic, palmitoleic) and polyunsaturated (arachidonic, linoleic) free fatty acids, which decreased in Caucasians after treatment but were not different in African Americans (p
Published: 2013

33. Large-Scale Gene-Centric Meta-analysis across 32 Studies Identifies Multiple Lipid Loci

Author: Asselbergs, Folkert W, Guo, Yiran, van Iperen, Erik PA, Sivapalaratnam, Suthesh, Tragante, Vinicius, Lanktree, Matthew B, Lange, Leslie A, Almoguera, Berta, Appelman, Yolande E, Barnard, John, Baumert, Jens, Beitelshees, Amber L, Bhangale, Tushar R, Chen, Yii-Der Ida, Gaunt, Tom R, Gong, Yan, Hopewell, Jemma C, Johnson, Toby, Kleber, Marcus E, Langaee, Taimour Y, Li, Mingyao, Li, Yun R, Liu, Kiang, McDonough, Caitrin W, Meijs, Matthijs FL, Middelberg, Rita PS, Musunuru, Kiran, Nelson, Christopher P, O’Connell, Jeffery R, Padmanabhan, Sandosh, Pankow, James S, Pankratz, Nathan, Rafelt, Suzanne, Rajagopalan, Ramakrishnan, Romaine, Simon PR, Schork, Nicholas J, Shaffer, Jonathan, Shen, Haiqing, Smith, Erin N, Tischfield, Sam E, van der Most, Peter J, van Vliet-Ostaptchouk, Jana V, Verweij, Niek, Volcik, Kelly A, Zhang, Li, Bailey, Kent R, Bailey, Kristian M, Bauer, Florianne, Boer, Jolanda MA, Braund, Peter S, Burt, Amber, Burton, Paul R, Buxbaum, Sarah G, Chen, Wei, Cooper-DeHoff, Rhonda M, Cupples, L Adrienne, deJong, Jonas S, Delles, Christian, Duggan, David, Fornage, Myriam, Furlong, Clement E, Glazer, Nicole, Gums, John G, Hastie, Claire, Holmes, Michael V, Illig, Thomas, Kirkland, Susan A, Kivimaki, Mika, Klein, Ronald, Klein, Barbara E, Kooperberg, Charles, Kottke-Marchant, Kandice, Kumari, Meena, LaCroix, Andrea Z, Mallela, Laya, Murugesan, Gurunathan, Ordovas, Jose, Ouwehand, Willem H, Post, Wendy S, Saxena, Richa, Scharnagl, Hubert, Schreiner, Pamela J, Shah, Tina, Shields, Denis C, Shimbo, Daichi, Srinivasan, Sathanur R, Stolk, Ronald P, Swerdlow, Daniel I, Taylor, Herman A, Topol, Eric J, Toskala, Elina, van Pelt, Joost L, van Setten, Jessica, Yusuf, Salim, Whittaker, John C, Zwinderman, AH, Study, LifeLines Cohort, Anand, Sonia S, Balmforth, Anthony J, and Berenson, Gerald S
Subjects: Biological Sciences, Biomedical and Clinical Sciences, Genetics, Epidemiology, Health Sciences, Human Genome, Atherosclerosis, Cholesterol, HDL, Cholesterol, LDL, Female, Genome-Wide Association Study, Genotype, Humans, Lipids, Male, Phenotype, Polymorphism, Single Nucleotide, Quantitative Trait Loci, Sex Factors, Triglycerides, White People, LifeLines Cohort Study, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract: Genome-wide association studies (GWASs) have identified many SNPs underlying variations in plasma-lipid levels. We explore whether additional loci associated with plasma-lipid phenotypes, such as high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), total cholesterol (TC), and triglycerides (TGs), can be identified by a dense gene-centric approach. Our meta-analysis of 32 studies in 66,240 individuals of European ancestry was based on the custom ∼50,000 SNP genotyping array (the ITMAT-Broad-CARe array) covering ∼2,000 candidate genes. SNP-lipid associations were replicated either in a cohort comprising an additional 24,736 samples or within the Global Lipid Genetic Consortium. We identified four, six, ten, and four unreported SNPs in established lipid genes for HDL-C, LDL-C, TC, and TGs, respectively. We also identified several lipid-related SNPs in previously unreported genes: DGAT2, HCAR2, GPIHBP1, PPARG, and FTO for HDL-C; SOCS3, APOH, SPTY2D1, BRCA2, and VLDLR for LDL-C; SOCS3, UGT1A1, BRCA2, UBE3B, FCGR2A, CHUK, and INSIG2 for TC; and SERPINF2, C4B, GCK, GATA4, INSR, and LPAL2 for TGs. The proportion of explained phenotypic variance in the subset of studies providing individual-level data was 9.9% for HDL-C, 9.5% for LDL-C, 10.3% for TC, and 8.0% for TGs. This large meta-analysis of lipid phenotypes with the use of a dense gene-centric approach identified multiple SNPs not previously described in established lipid genes and several previously unknown loci. The explained phenotypic variance from this approach was comparable to that from a meta-analysis of GWAS data, suggesting that a focused genotyping approach can further increase the understanding of heritability of plasma lipids.
Published: 2012

34. Multisite Investigation of Outcomes With Implementation of CYP2C19 Genotype-Guided Antiplatelet Therapy After Percutaneous Coronary Intervention

Author: Cavallari, Larisa H., Lee, Craig R., Beitelshees, Amber L., Cooper-DeHoff, Rhonda M., Duarte, Julio D., Voora, Deepak, Kimmel, Stephen E., McDonough, Caitrin W., Gong, Yan, Dave, Chintan V., Pratt, Victoria M., Alestock, Tameka D., Anderson, R. David, Alsip, Jorge, Ardati, Amer K., Brott, Brigitta C., Brown, Lawrence, Chumnumwat, Supatat, Clare-Salzler, Michael J., Coons, James C., Denny, Joshua C., Dillon, Chrisly, Elsey, Amanda R., Hamadeh, Issam S., Harada, Shuko, Hillegass, William B., Hines, Lindsay, Horenstein, Richard B., Howell, Lucius A., Jeng, Linda J.B., Kelemen, Mark D., Lee, Yee Ming, Magvanjav, Oyunbileg, Montasser, May, Nelson, David R., Nutescu, Edith A., Nwaba, Devon C., Pakyz, Ruth E., Palmer, Kathleen, Peterson, Josh F., Pollin, Toni I., Quinn, Alison H., Robinson, Shawn W., Schub, Jamie, Skaar, Todd C., Smith, D. Max, Sriramoju, Vindhya B., Starostik, Petr, Stys, Tomasz P., Stevenson, James M., Varunok, Nicholas, Vesely, Mark R., Wake, Dyson T., Weck, Karen E., Weitzel, Kristin W., Wilke, Russell A., Willig, James, Zhao, Richard Y., Kreutz, Rolf P., Stouffer, George A., Empey, Philip E., Limdi, Nita A., Shuldiner, Alan R., Winterstein, Almut G., and Johnson, Julie A.
Published: 2018
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35. CYP2C19 Genotype Is Associated With Adverse Cardiovascular Outcomes in Black Patients Treated With Clopidogrel Undergoing Percutaneous Coronary Intervention.

Author: Tunehag, Kayla R., Thomas, Cameron D., Franchi, Francesco, Rossi, Joseph S., Keeley, Ellen C., Anderson, R. David, Beitelshees, Amber L., Duarte, Julio D., Yan Gong, Kerensky, Richard A., McDonough, Caitrin W., Nguyen, Anh B., Paz, Luis Ortega, Venkatesh, Sanjay, Wang, Yehua, Johnson, Julie A., Winterstein, Almut G., Stouffer, George A., Angiolillo, Dominick J., and Cavallari, Larisa H.
Published: 2024
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36. Acute pharmacodynamic responses to sitagliptin: Drug‐induced increase in early insulin secretion in oral glucose tolerance test.

Author: Beitelshees, Amber L., Streeten, Elizabeth A., Shahidzadeh Yazdi, Zhinous, Whitlatch, Hilary B., Mitchell, Braxton D., Shuldiner, Alan R., Montasser, May E., and Taylor, Simeon I.
Subjects: *SITAGLIPTIN, *GLUCOSE tolerance tests, *GESTATIONAL diabetes, *DRUG side effects, *INSULIN, *SECRETION, *TYPE 2 diabetes
Abstract: DPP4 inhibitors are widely prescribed as treatments for type 2 diabetes. Because drug responses vary among individuals, we initiated investigations to identify genetic variants associated with the magnitude of drug responses. Sitagliptin (100 mg) was administered to 47 healthy volunteers. Several endpoints were measured to assess clinically relevant responses – including the effect of sitagliptin on glucose and insulin levels during an oral glucose tolerance test (OGTT). This pilot study confirmed that sitagliptin (100 mg) decreased the area under the curve for glucose during an OGTT (p = 0.0003). Furthermore, sitagliptin promoted insulin secretion during the early portion of the OGTT as reflected by an increase in the ratio of plasma insulin at 30 min divided by plasma insulin at 60 min (T30:T60) from mean ± SEM 0.87 ± 0.05 to 1.62 ± 0.36 mU/L (p = 0.04). The magnitude of sitagliptin's effect on insulin secretion (as judged by the increase in the T30:T60 ratio for insulin) was correlated with the magnitude of sitagliptin‐induced increase in the area under the curve for intact plasma GLP1 levels during the first hour of the OGTT. This study confirmed previously reported sex differences in glucose and insulin levels during an OGTT. Specifically, females exhibited higher levels of glucose and insulin at the 90–180 min time points. However, we did not detect significant sex‐associated differences in the magnitude of sitagliptin‐induced changes in T30:T60 ratios for either glucose or insulin. In conclusion, T30:T60 ratios for insulin and glucose during an OGTT provide useful indices to assess pharmacodynamic responses to DPP4 inhibitors. [ABSTRACT FROM AUTHOR]
Published: 2024
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37. Vitamin D Deficiency Increases Vulnerability to Canagliflozin-induced Adverse Effects on 1,25-Dihydroxyvitamin D and PTH.

Author: Yazdi, Zhinous Shahidzadeh, Streeten, Elizabeth A, Whitlatch, Hilary B, Montasser, May E, Beitelshees, Amber L, and Taylor, Simeon I
Subjects: VITAMIN D deficiency, CANAGLIFLOZIN, PARATHYROID hormone
Abstract: Context Canagliflozin has been reported to increase the risk of bone fracture—possibly mediated by decreasing 1,25-dihydroxyvitamin D (1,25(OH)2D) and increasing parathyroid hormone (PTH). Objective This work investigated whether baseline vitamin D (VitD) deficiency renders individuals vulnerable to this adverse effect and whether VitD3 supplementation is protective. Methods This community-based, outpatient study had a paired design comparing individual participants before and after VitD3 supplementation. Eleven VitD-deficient (25-hydroxyvitamin D [25(OH)D] ≤ 20 ng/mL) individuals were recruited from the Amish population in Lancaster, Pennsylvania. Participants underwent 2 canagliflozin challenge protocols (300 mg daily for 5 days): the first before and the second after VitD3 supplementation. In the VitD3 supplementation protocol, participants received VitD3 supplementation (50 000 IU once or twice a week depending on body mass index for 4-6 weeks) to achieve 25(OH)D of 30 ng/mL or greater. Two coprimary end points were identified: effects of VitD3 supplementation on canagliflozin-induced changes in 1,25(OH)2D and PTH. Secondary end points included effects of VitD3 supplementation on baseline levels of VitD metabolites and PTH. Results VitD3 supplementation increased mean 25(OH)D from 16.5 ± 1.6 to 44.3 ± 5.5 ng/mL (P =.0006) and 24,25-dihydroxyvitamin D (24,25(OH)2D) from 1.0 ± 0.1 to 4.3 ± 0.6 ng/mL (P =.0002). Mean 1,25(OH)2D and PTH were unchanged. VitD3 supplementation decreased the magnitude of canagliflozin-induced changes in 1,25(OH)2D (from −31.3%±4.7% to −9.3%±8.3%; P =.04) and PTH (from +36.2%±6.2% to +9.7%±3.7%; P =.005). Conclusion VitD deficiency rendered individuals more vulnerable to adverse effects of canagliflozin on biomarkers associated with bone health. VitD3 supplementation was protective against canagliflozin's short-term adverse effects on 1,25(OH)2D and PTH. [ABSTRACT FROM AUTHOR]
Published: 2024
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38. Pharmacological treatment of hyperglycemia in type 2 Diabetes

Author: Taylor, Simeon I., Yazdi, Zhinous Shahidzadeh, and Beitelshees, Amber L.
Subjects: Drug therapy, Complications and side effects, Usage, Risk factors, Hypoglycemic agents -- Usage, Type 2 diabetes -- Complications and side effects -- Drug therapy, Hyperglycemia -- Risk factors -- Drug therapy
Abstract: Diabetes mellitus is a major public health problem, affecting about 10% of the population (1). Chronic complications of diabetes cause enormous human suffering, including blindness, kidney failure, amputations, myocardial infarction, [...], Diabetes mellitus is a major public health problem, affecting about 10% of the population. Pharmacotherapy aims to protect against microvascular complications, including blindness, end-stage kidney disease, and amputations. Landmark clinical trials have demonstrated that intensive glycemic control slows progression of microvascular complications (retinopathy, nephropathy, and neuropathy). Long-term follow-up has demonstrated that intensive glycemic control also decreases risk of macrovascular disease, albeit rigorous evidence of macrovascular benefit did not emerge for over a decade. The US FDA's recent requirement for dedicated cardiovascular outcome trials ushered in a golden age for understanding the clinical profiles of new type 2 diabetes drugs. Some clinical trials with sodium-glucose cotransporter-2 (SGLT2) inhibitors and glucagon- like peptide 1 (GLP1) receptor agonists reported data demonstrating cardiovascular benefit (decreased risk of major adverse cardiovascular events and hospitalization for heart failure) and slower progression of diabetic kidney disease. This Review discusses current guidelines for use of the 12 classes of drugs approved to promote glycemic control in patients with type 2 diabetes. The Review also anticipates future developments with potential to improve the standard of care: availability of generic dipeptidylpeptidase-4 (DPP4) inhibitors and SGLT2 inhibitors; precision medicine to identify the best drugs for individual patients; and new therapies to protect against chronic complications of diabetes.
Published: 2021
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39. Targeted sequencing identifies a missense variant in the BEST3 gene associated with antihypertensive response to hydrochlorothiazide

Author: Singh, Sonal, Wang, Zhiying, Shahin, Mohamed H., Langaee, Taimour Y., Gong, Yan, Turner, Stephen T., Chapman, Arlene B., Gums, John G., McDonough, Caitrin W., Bailey, Kent R., Beitelshees, Amber L., Cooper-DeHoff, Rhonda M., Scherer, Steve, Boerwinkle, Eric, and Johnson, Julie A.
Published: 2018
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40. An APOO Pseudogene on Chromosome 5q Is Associated With Low-Density Lipoprotein Cholesterol Levels

Author: Montasser, May E., O’Hare, Elizabeth A., Wang, Xiaochun, Howard, Alicia D., McFarland, Rebecca, Perry, James A., Ryan, Kathleen A., Rice, Kenneth, Jaquish, Cashell E., Shuldiner, Alan R., Miller, Michael, Mitchell, Braxton D., Zaghloul, Norann A., Chang, Yen-Pei C., Abe, Namiko, Abecasis, Goncalo, Albert, Christine, Allred, Nicholette P., Almasy, Laura, Alonso, Alvaro, Ament, Seth, Anderson, Peter, Anugu, Pramod, Applebaum-Bowden, Debora, Arking, Dan, Arnett, Donna K, Ashley-Koch, Allison, Aslibekyan, Stella, Assimes, Tim, Auer, Paul, Avramopoulos, Dimitrios, Barnard, John, Barnes, Kathleen, Graham Barr, R., Barron-Casella, Emily, Beaty, Terri, Becker, Diane, Becker, Lewis, Beer, Rebecca, Begum, Ferdouse, Beitelshees, Amber, Benjamin, Emelia, Bezerra, Marcos, Bielak, Larry, Bis, Joshua, Blackwell, Thomas, Blangero, John, Boerwinkle, Eric, Borecki, Ingrid, Bowler, Russel, Brody, Jennifer, Broeckel, Ulrich, Broome, Jai, Bunting, Karen, Burchard, Esteban, Cardwell, Jonathan, Carlson, Sara, Carty, Cara, Casaburi, Richard, Casella, James, Chaffin, Mark, Chang, Christy, Chasman, Daniel, Chavan, Sameer, Chen, Bo-Juen, Chen, Wei-Min, Ida Chen, Yii-Der, Cho, Michael, Choi, Seung Hoan, Chuang, Lee-Ming, Chung, Mina, Cornell, Elaine, Correa, Adolfo, Crandall, Carolyn, Crapo, James, Cupples, L Adrienne, Curran, Joanne, Curtis, Jeffrey, Custer, Brian, Damcott, Coleen, Darbar, Dawood, Das, Sayantan, David, Sean, Davis, Colleen, Daya, Michelle, de Andrade, Mariza, DeBaun, Michael, Deka, Ranjan, DeMeo, Dawn, Devine, Scott, Do, Ron, Duan, Qing, Duggirala, Ravi, Durda, Peter, Dutcher, Susan, Eaton, Charles, Ekunwe, Lynette, Ellinor, Patrick, Emery, Leslie, Farber, Charles, Farnam, Leanna, Fingerlin, Tasha, Flickinger, Matthew, Fornage, Myriam, Franceschini, Nora, Fu, Mao, Fullerton, Malia, Fulton, Lucinda, Gabriel, Stacey, Gan, Weiniu, Gao, Yan, Gass, Margery, Gelb, Bruce, Geng, Xiaoqi (Priscilla), Germer, Soren, Gignoux, Chris, Gladwin, Mark, Glahn, David, Gogarten, Stephanie, Gong, Da-Wei, Goring, Harald, Charles Gu, C., Guan, Yue, Guo, Xiuqing, Haessler, Jeff, Hall, Michael, Harris, Daniel, Hawley, Nicola, He, Jiang, Heavner, Ben, Heckbert, Susan, Hernandez, Ryan, Herrington, David, Hersh, Craig, Hidalgo, Bertha, Hixson, James, Hokanson, John, Hong, Elliott, Hoth, Karin, Hsiung, Chao (Agnes), Huston, Haley, Hwu, Chii Min, Irvin, Marguerite, Jackson, Rebecca, Jain, Deepti, Jaquish, Cashell, Jhun, Min A, Johnsen, Jill, Johnson, Andrew, Johnson, Craig, Johnston, Rich, Jones, Kimberly, Kang, Hyun Min, Kaplan, Robert, Kardia, Sharon, Kathiresan, Sekar, Kaufman, Laura, Kelly, Shannon, Kenny, Eimear, Kessler, Michael, Khan, Alyna, Kinney, Greg, Konkle, Barbara, Kooperberg, Charles, Kramer, Holly, Krauter, Stephanie, Lange, Christoph, Lange, Ethan, Lange, Leslie, Laurie, Cathy, Laurie, Cecelia, LeBoff, Meryl, Lee, Seunggeun, Lee, Wen-Jane, LeFaive, Jonathon, Levine, David, Levy, Dan, Lewis, Joshua, Li, Yun, Lin, Honghuang, Lin, Keng Han, Liu, Simin, Liu, Yongmei, Loos, Ruth, Lunetta, Kathryn, Luo, James, Mahaney, Michael, Make, Barry, Manichaikul, Ani, Manson, JoAnn, Margolin, Lauren, Martin, Lisa, Mathai, Susan, Mathias, Rasika, McArdle, Patrick, McDonald, Merry-Lynn, McFarland, Sean, McGarvey, Stephen, Mei, Hao, Meyers, Deborah, Mikulla, Julie, Min, Nancy, Minear, Mollie, Minster, Ryan L, Mitchell, Braxton, Musani, Solomon, Mwasongwe, Stanford, Mychaleckyj, Josyf C, Nadkarni, Girish, Naik, Rakhi Johns, Natarajan, Pradeep, Nekhai, Sergei, Nickerson, Deborah, North, Kari, O’Connell, Jeff, O’Connor, Tim, Heather, Ochs-Balcom, Pankow, James, Papanicolaou, George, Parker, Margaret, Parsa, Afshin, Pattison, Jessica Tangarone, Penchev, Sara, Peralta, Juan Manuel, Perez, Marco, Perry, James, Peters, Ulrike, Peyser, Patricia, Phillips, Larry, Phillips, Sam, Pollin, Toni, Post, Wendy, Becker, Julia Powers, Boorgula, Meher Preethi, Preuss, Michael, Prokopenko, Dmitry, Psaty, Bruce, Qasba, Pankaj, Qiao, Dandi, Qin, Zhaohui, Rafaels, Nicholas, Raffield, Laura, Ramachandran, Vasan, Rao, D.C., Rasmussen-Torvik, Laura, Ratan, Aakrosh, Redline, Susan, Reed, Robert, Regan, Elizabeth, Reiner, Alex, Rice, Ken, Rich, Stephen, Roden, Dan, Roselli, Carolina, Rotter, Jerome, Ruczinski, Ingo, Russell, Pamela, Ruuska, Sarah, Ryan, Kathleen, Sakornsakolpat, Phuwanat, Salimi, Shabnam, Salzberg, Steven, Sandow, Kevin, Sankaran, Vijay, Scheller, Christopher, Schmidt, Ellen, Schwander, Karen, Schwartz, David, Sciurba, Frank, Seidman, Christine, Sheehan, Vivien, Shetty, Amol, Shetty, Aniket, Hui-Heng Sheu, Wayne, Benjamin Shoemaker, M., Silver, Brian, Silverman, Edwin, Smith, Jennifer, Smith, Josh, Smith, Nicholas, Smith, Tanja, Smoller, Sylvia, Snively, Beverly, Sofer, Tamar, Sotoodehnia, Nona, Stilp, Adrienne, Streeten, Elizabeth, Sung, Yun Ju, Sylvia, Jody, Szpiro, Adam, Sztalryd, Carole, Taliun, Daniel, Tang, Hua, Taub, Margaret, Taylor, Kent, Taylor, Simeon, Telen, Marilyn, Thornton, Timothy A., Tinker, Lesley, Tirschwell, David, Tiwari, Hemant, Tracy, Russell, Tsai, Michael, Vaidya, Dhananjay, VandeHaar, Peter, Vrieze, Scott, Walker, Tarik, Wallace, Robert, Walts, Avram, Wan, Emily, Fei Wang, Fei, Watson, Karol, Weeks, Daniel E., Weir, Bruce, Weiss, Scott, Weng, Lu-Chen, Willer, Cristen, Williams, Kayleen, Keoki Williams, L., Wilson, Carla, Wilson, James, Wong, Quenna, Xu, Huichun, Yanek, Lisa, Yang, Ivana, Yang, Rongze, Zaghloul, Norann, Zhang, Yingze, Zhao, Snow Xueyan, Zhao, Wei, Zheng, Xiuwen, Zhi, Degui, Zhou, Xiang, Zody, Michael, and Zoellner, Sebastian
Published: 2018
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41. Gene-centric Meta-analysis in 87,736 Individuals of European Ancestry Identifies Multiple Blood-Pressure-Related Loci

Author: Tragante, Vinicius, Barnes, Michael R., Ganesh, Santhi K., Lanktree, Matthew B., Guo, Wei, Franceschini, Nora, Smith, Erin N., Johnson, Toby, Holmes, Michael V., Padmanabhan, Sandosh, Karczewski, Konrad J., Almoguera, Berta, Barnard, John, Baumert, Jens, Chang, Yen-Pei Christy, Elbers, Clara C., Farrall, Martin, Fischer, Mary E., Gaunt, Tom R., Gho, Johannes M.I.H., Gieger, Christian, Goel, Anuj, Gong, Yan, Isaacs, Aaron, Kleber, Marcus E., Leach, Irene Mateo, McDonough, Caitrin W., Meijs, Matthijs F.L., Melander, Olle, Nelson, Christopher P., Nolte, Ilja M., Pankratz, Nathan, Price, Tom S., Shaffer, Jonathan, Shah, Sonia, Tomaszewski, Maciej, van der Most, Peter J., Van Iperen, Erik P.A., Vonk, Judith M., Witkowska, Kate, Wong, Caroline O.L., Zhang, Li, Beitelshees, Amber L., Berenson, Gerald S., Bhatt, Deepak L., Brown, Morris, Burt, Amber, Cooper-DeHoff, Rhonda M., Connell, John M., Cruickshanks, Karen J., Curtis, Sean P., Davey-Smith, George, Delles, Christian, Gansevoort, Ron T., Guo, Xiuqing, Haiqing, Shen, Hastie, Claire E., Hofker, Marten H., Hovingh, G. Kees, Kim, Daniel S., Kirkland, Susan A., Klein, Barbara E., Klein, Ronald, Li, Yun R., Maiwald, Steffi, Newton-Cheh, Christopher, O’Brien, Eoin T., Onland-Moret, N. Charlotte, Palmas, Walter, Parsa, Afshin, Penninx, Brenda W., Pettinger, Mary, Vasan, Ramachandran S., Ranchalis, Jane E., M Ridker, Paul, Rose, Lynda M., Sever, Peter, Shimbo, Daichi, Steele, Laura, Stolk, Ronald P., Thorand, Barbara, Trip, Mieke D., van Duijn, Cornelia M., Verschuren, W. Monique, Wijmenga, Cisca, Wyatt, Sharon, Young, J. Hunter, Zwinderman, Aeilko H., Bezzina, Connie R., Boerwinkle, Eric, Casas, Juan P., Caulfield, Mark J., Chakravarti, Aravinda, Chasman, Daniel I., Davidson, Karina W., Doevendans, Pieter A., Dominiczak, Anna F., FitzGerald, Garret A., Gums, John G., Fornage, Myriam, Hakonarson, Hakon, Halder, Indrani, Hillege, Hans L., Illig, Thomas, Jarvik, Gail P., Johnson, Julie A., Kastelein, John J.P., Koenig, Wolfgang, Kumari, Meena, März, Winfried, Murray, Sarah S., O’Connell, Jeffery R., Oldehinkel, Albertine J., Pankow, James S., Rader, Daniel J., Redline, Susan, Reilly, Muredach P., Schadt, Eric E., Kottke-Marchant, Kandice, Snieder, Harold, Snyder, Michael, Stanton, Alice V., Tobin, Martin D., Uitterlinden, André G., van der Harst, Pim, van der Schouw, Yvonne T., Samani, Nilesh J., Watkins, Hugh, Johnson, Andrew D., Reiner, Alex P., Zhu, Xiaofeng, de Bakker, Paul I.W., Levy, Daniel, Asselbergs, Folkert W., Munroe, Patricia B., and Keating, Brendan J.
Published: 2014
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42. Pharmacogenetics of sodium‐glucose co‐transporter‐2 inhibitors: Validation of a sex‐agnostic pharmacodynamic biomarker.

Author: Taylor, Simeon I., Cherng, Hua‐Ren, Shahidzadeh Yazdi, Zhinous, Montasser, May E., Whitlatch, Hilary B., Mitchell, Braxton D., Shuldiner, Alan R., Streeten, Elizabeth A., and Beitelshees, Amber L.
Subjects: CREATININE, PHARMACOGENOMICS, KIDNEY physiology, BLOOD sugar, GLOMERULAR filtration rate, BODY surface area
Abstract: Aim: To validate pharmacodynamic responses to sodium‐glucose co‐transporter‐2 (SGLT2) inhibitors and test for association with genetic variants in SLC5A4, SLC5A9, and SLC2A9. Methods: Canagliflozin (300 mg), a SGLT2 inhibitor, was administered to 30 healthy volunteers. Several endpoints were measured to assess clinically relevant responses, including drug‐induced increases in urinary excretion of glucose, sodium and uric acid. Results: This pilot study confirmed that canagliflozin (300 mg) triggered acute changes in mean levels of several biomarkers: fasting plasma glucose (−4.1 mg/dL; P = 6 × 10−5), serum creatinine (+0.05 mg/dL; P = 8 × 10−4) and serum uric acid (−0.90 mg/dL; P = 5 × 10−10). The effects of sex on glucosuria depended upon how data were normalized. Whereas males' responses were ~60% greater when data were normalized to body surface area, males and females exhibited similar responses when glucosuria was expressed as grams of urinary glucose per gram‐creatinine. The magnitude of glucosuria was not significantly correlated with fasting plasma glucose, estimated glomerular filtration rate or age in those healthy individuals without diabetes with an estimated glomerular filtration rate of more than 60 mL/min/1.73m2. Conclusions: Normalizing data relative to creatinine excretion will facilitate including data from males and females in a single analysis. Furthermore, because our ongoing pharmacogenomic study (NCT02891954) is conducted in healthy individuals, this will facilitate detection of genetic associations with limited confounding by other factors such as HbA1c and renal function. [ABSTRACT FROM AUTHOR]
Published: 2023
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43. Predicting Heterogeneity in Patient Response to Morphine Treatment for Neonatal Opioid Withdrawal Syndrome.

Author: Smolyak, Daniel, Humphries, Elizabeth M., Parikh, Abhinav, Gopalakrishnan, Mathangi, Aycan, Fulden, Bjarnadóttir, Margrét, Ament, Seth A., El‐Metwally, Dina, Beitelshees, Amber, and Agarwal, Ritu
Subjects: NEONATAL abstinence syndrome, TERMINATION of treatment, DISEASE risk factors, MORPHINE, MONOGENIC & polygenic inheritance (Genetics), OPIOID analgesics, OPIOIDS
Abstract: Infants with neonatal opioid withdrawal syndrome commonly receive morphine treatment to manage their withdrawal signs. However, the effectiveness of this pharmacotherapy in managing the infants' withdrawal signs vary widely. We sought to understand how information available early in infant monitoring can anticipate this treatment response, focusing on early modified Finnegan Neonatal Abstinence Scoring System (FNASS) scores, polygenic risk for opioid dependence (polygenic risk score (PRS)), and drug exposure. Using k‐means clustering, we divided the 213 infants in our cohort into 3 groups based on their FNASS scores in the 12 hours before and after the initiation of pharmacotherapy. We found that these groups were pairwise significantly different for risk factors, including methadone exposure, and for in‐hospital outcomes, including total morphine received, length of stay, and highest FNASS score. Whereas PRS was not predictive of receipt of treatment, PRS was pairwise significantly different between a subset of the groups. Using tree‐based machine learning methods, we then constructed network graphs of the relationships among these groups, FNASS scores, PRS, drug exposures, and in‐hospital outcomes. The resulting networks also showed meaningful connection between early FNASS scores and PRS, as well as between both of those and later in‐hospital outcomes. These analyses present clinicians with the opportunity to better anticipate infant withdrawal progression and prepare accordingly, whether with expedited morphine treatment or non‐pharmacotherapeutic alternative treatments. [ABSTRACT FROM AUTHOR]
Published: 2023
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44. Blood pressure signature genes and blood pressure response to thiazide diuretics: results from the PEAR and PEAR-2 studies

Author: Sá, Ana Caroline C., Webb, Amy, Gong, Yan, McDonough, Caitrin W., Shahin, Mohamed H., Datta, Somnath, Langaee, Taimour Y., Turner, Stephen T., Beitelshees, Amber L., Chapman, Arlene B., Boerwinkle, Eric, Gums, John G., Scherer, Steven E., Cooper-DeHoff, Rhonda M., Sadee, Wolfgang, and Johnson, Julie A.
Published: 2018
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45. Presence of arachidonoyl-carnitine is associated with adverse cardiometabolic responses in hypertensive patients treated with atenolol

Author: Weng, Liming, Gong, Yan, Culver, Jeffrey, Gardell, Stephen J., Petucci, Christopher, Morse, Alison M., Frye, Reginald F., Turner, Stephen T., Chapman, Arlene, Boerwinkle, Eric, Gums, John, Beitelshees, Amber L., Borum, Peggy R., Johnson, Julie A., Garrett, Timothy J., McIntyre, Lauren M., and Cooper-DeHoff, Rhonda M.
Published: 2016
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46. Acute pharmacodynamic responses to exenatide: Drug‐induced increases in insulin secretion and glucose effectiveness.

Author: Taylor, Simeon I., Montasser, May E., Yuen, Ashley H., Fan, Hubert, Yazdi, Zhinoosossadat Shahidzadeh, Whitlatch, Hilary B., Mitchell, Braxton D., Shuldiner, Alan R., Muniyappa, Ranganath, Streeten, Elizabeth A., and Beitelshees, Amber L.
Subjects: INSULIN, WEIGHT loss, GLUCAGON-like peptide-1 receptor, INSULIN sensitivity, DRUG side effects, EXENATIDE, MAJOR adverse cardiovascular events, SECRETION
Abstract: Aim: Glucagon‐like peptide‐1 receptor agonists provide multiple benefits to patients with type 2 diabetes, including improved glycaemic control, weight loss and decreased risk of major adverse cardiovascular events. Because drug responses vary among individuals, we initiated investigations to identify genetic variants associated with the magnitude of drug responses. Methods: Exenatide (5 μg, subcutaneously) or saline (0.2 ml, subcutaneously) was administered to 62 healthy volunteers. Frequently sampled intravenous glucose tolerance tests were conducted to assess the impact of exenatide on insulin secretion and insulin action. This pilot study was a crossover design in which participants received exenatide and saline in random order. Results: Exenatide increased first phase insulin secretion 1.9‐fold (p = 1.9 × 10−9) and accelerated the rate of glucose disappearance 2.4‐fold (p = 2 × 10−10). Minimal model analysis showed that exenatide increased glucose effectiveness (Sg) by 32% (p =.0008) but did not significantly affect insulin sensitivity (Si). The exenatide‐induced increase in insulin secretion made the largest contribution to interindividual variation in exenatide‐induced acceleration of glucose disappearance while interindividual variation in the drug effect on Sg contributed to a lesser extent (β = 0.58 or 0.27, respectively). Conclusions: This pilot study provides validation for the value of a frequently sampled intravenous glucose tolerance test (including minimal model analysis) to provide primary data for our ongoing pharmacogenomic study of pharmacodynamic effects of semaglutide (NCT05071898). Three endpoints provide quantitative assessments of the effects of glucagon‐like peptide‐1 receptor agonists on glucose metabolism: first phase insulin secretion, glucose disappearance rates and glucose effectiveness. [ABSTRACT FROM AUTHOR]
Published: 2023
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47. Excessive platelet inhibition following Pipeline embolization of intracranial aneurysms.

Author: Miller, Timothy R., Khunte, Mihir, Caffes, Nicholas, Anders, Megan, Rock, Peter, Beitelshees, Amber L., Malhotra, Ajay, Cannarsa, Gregory, Cherian, Jacob, Simard, J. Marc, Jindal, Gaurav, and Gandhi, Dheeraj
Subjects: INTRACRANIAL aneurysm surgery, CONFIDENCE intervals, MULTIPLE regression analysis, THERAPEUTIC embolization, CLOPIDOGREL, PLATELET aggregation inhibitors, ODDS ratio, MIDAZOLAM
Abstract: Background High levels of platelet inhibition have been associated with hemorrhagic complications following Pipeline embolization of intracranial aneurysms. We therefore titrate clopidogrel dosing to maintain a moderate level of platelet inhibition using the VerifyNow P2Y12 assay. However, many patients demonstrate dramatic increases in platelet inhibition following treatment despite being on a consistent antiplatelet regimen. We therefore elected to explore the incidence of this phenomenon and possible predisposing factors. Methods All successful Pipeline aneurysm treatments performed at our institution from 2011 to 2019 with moderate procedure-day platelet inhibition levels as indicated by a VerifyNow PRU of 60-235 were included. Patients who received glycoprotein IIb/IIIa inhibitors and those treated for ruptured/symptomatic lesions were excluded. The incidence of excessive platelet inhibition defined by a PRU<60 within 8 weeks of treatment was noted. Multivariable logistic regression was performed to determined independent predictors of the phenomenon. Results Some 190 treatments were performed in 178 qualifying patients. A post-procedure PRU <60 occurred following 79% of treatments, documented on average after 8.5 (range 1-47) days. A higher procedure day hematocrit level (P=0.003, OR 1.09, 95% CI 1.029 to 1.152) was an independent predictor of reaching a PRU <60, while intra-procedural midazolam exposure (P=0.044, OR 0.44, 95% CI 0.201 to 0.980) and a higher procedure-day PRU (P=0.047, OR 0.99, 95% CI 0.982 to 1.000) were associated with a reduced odds. Time-since-procedure and hematocrit levels were associated with excessive platelet inhibition when excluding patients who initially demonstrated hyperresponse. Conclusion Elevations in platelet inhibition were frequently observed following flow diversion with Pipeline. [ABSTRACT FROM AUTHOR]
Published: 2023
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48. Pharmacodynamic Effects of Low-Dose Pioglitazone in Patients with the Metabolic Syndrome without Diabetes Mellitus

Author: Vu, Anh, Kosmiski, Lisa A., Beitelshees, Amber L., Prigeon, Ronald, Sidhom, Maha S., Bredbeck, Brooke, Predhomme, Julie, Deininger, Kimberly M., and Aquilante, Christina L.
Published: 2016
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49. Evaluation of Potential Racial Disparities in CYP2C19‐Guided P2Y12 Inhibitor Prescribing After Percutaneous Coronary Intervention.

Author: Cavallari, Larisa H., Limdi, Nita A., Beitelshees, Amber L., Lee, James C., Duarte, Julio D., Franchi, Francesco, Tuteja, Sony, Giri, Jay, Empey, Philip E., Kreutz, Rolf P., Skaar, Todd C., Allen, John M., Coons, James C., Gong, Yan, McDonough, Caitrin W., Stevenson, James M., Thomas, Cameron D., Johnson, Julie A., Stouffer, George A., and Angiolillo, Dominick J.
Subjects: PERCUTANEOUS coronary intervention, RACIAL inequality, BLACK people, CYTOCHROME P-450 CYP2C19, HOSPITAL admission & discharge
Abstract: Black patients suffer worse outcomes after percutaneous coronary intervention (PCI) than White patients. Inequities in antiplatelet prescribing may contribute to this health disparity. We compared P2Y12 inhibitor prescribing by race following CYP2C19 genotyping to guide antiplatelet therapy selection after PCI. Patients from 9 sites that performed clinical CYP2C19 genotyping after PCI were included. Alternative therapy (e.g., prasugrel or ticagrelor) was recommended for CYP2C19 no‐function allele carriers, in whom clopidogrel is predicted to be less effective. The primary outcome was choice of P2Y12 inhibitor (clopidogrel vs. alternative therapy) based on genotype. Of 3,342 patients included, 2,448 (73%) were White, and 659 (20%) were Black. More Black than White patients had a no‐function allele (34.3% vs. 29.7%, P = 0.024). At hospital discharge following PCI, 44.2% of Black and 44.0% of White no‐function allele carriers were prescribed alternative therapy. At the time of the last follow‐up within 12 months, numerically fewer Black (51.8%) than White (56.7%) no‐function allele carriers were prescribed alternative therapy (P = 0.190). However, the difference was not significant after accounting for other factors associated with P2Y12 inhibitor selection (odds ratio 0.79, 95% confidence interval 0.58–1.08). Alternative therapy use did not differ between Black (14.3%) and White (16.7%) patients without a no‐function allele (P = 0.232). Among real‐world patients who received CYP2C19 testing after PCI, P2Y12 inhibitor prescribing rates did not differ between Black and White patients. Our data suggest an absence of racial disparity in genotype‐guided antiplatelet prescribing among patients receiving CYP2C19 testing. [ABSTRACT FROM AUTHOR]
Published: 2023
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50. α-Adducin polymorphism associated with increased risk of adverse cardiovascular outcomes: Results from GENEtic Substudy of the INternational VErapamil SR-trandolapril STudy (INVEST-GENES)

Author: Gerhard, Tobias, Gong, Yan, Beitelshees, Amber L., Mao, Xianyun, Lobmeyer, Maximilian T., Cooper-DeHoff, Rhonda M., Langaee, Taimour Y., Schork, Nicholas J., Shriver, Mark D., Pepine, Carl J., and Johnson, Julie A.
Published: 2008
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