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2. A methylation risk score for chronic kidney disease: a HyperGEN study

Author

Jones, Alana C, Patki, Amit, Srinivasasainagendra, Vinodh, Hidalgo, Bertha A, Tiwari, Hemant K, Limdi, Nita A, Armstrong, Nicole D, Chaudhary, Ninad S, Minniefield, Bré, Absher, Devin, Arnett, Donna K, Lange, Leslie A, Lange, Ethan M, Young, Bessie A, Diamantidis, Clarissa J, Rich, Stephen S, Mychaleckyj, Josyf C, Rotter, Jerome I, Taylor, Kent D, Kramer, Holly J, Tracy, Russell P, Durda, Peter, Kasela, Silva, Lappalinen, Tuuli, Liu, Yongmei, Johnson, W Craig, Van Den Berg, David J, Franceschini, Nora, Liu, Simin, Mouton, Charles P, Bhatti, Parveen, Horvath, Steve, Whitsel, Eric A, and Irvin, Marguerite R

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Prevention, Clinical Research, Human Genome, Health Disparities, Kidney Disease, Minority Health, Women's Health, 2.1 Biological and endogenous factors, 4.1 Discovery and preclinical testing of markers and technologies, Renal and urogenital, Humans, Renal Insufficiency, Chronic, DNA Methylation, Male, Female, Middle Aged, Glomerular Filtration Rate, CpG Islands, Risk Factors, Black or African American, Aged, Genome-Wide Association Study, Epigenesis, Genetic, Adult, Genetic Predisposition to Disease, Chronic kidney disease, eGFR, Methylation risk score, Epigenetics
Abstract

Chronic kidney disease (CKD) impacts about 1 in 7 adults in the United States, but African Americans (AAs) carry a disproportionately higher burden of disease. Epigenetic modifications, such as DNA methylation at cytosine-phosphate-guanine (CpG) sites, have been linked to kidney function and may have clinical utility in predicting the risk of CKD. Given the dynamic relationship between the epigenome, environment, and disease, AAs may be especially sensitive to environment-driven methylation alterations. Moreover, risk models incorporating CpG methylation have been shown to predict disease across multiple racial groups. In this study, we developed a methylation risk score (MRS) for CKD in cohorts of AAs. We selected nine CpG sites that were previously reported to be associated with estimated glomerular filtration rate (eGFR) in epigenome-wide association studies to construct a MRS in the Hypertension Genetic Epidemiology Network (HyperGEN). In logistic mixed models, the MRS was significantly associated with prevalent CKD and was robust to multiple sensitivity analyses, including CKD risk factors. There was modest replication in validation cohorts. In summary, we demonstrated that an eGFR-based CpG score is an independent predictor of prevalent CKD, suggesting that MRS should be further investigated for clinical utility in evaluating CKD risk and progression.

Published
2024

3. Validation of human telomere length multi-ancestry meta-analysis association signals identifies POP5 and KBTBD6 as human telomere length regulation genes

Author

Keener, Rebecca, Chhetri, Surya B, Connelly, Carla J, Taub, Margaret A, Conomos, Matthew P, Weinstock, Joshua, Ni, Bohan, Strober, Benjamin, Aslibekyan, Stella, Auer, Paul L, Barwick, Lucas, Becker, Lewis C, Blangero, John, Bleecker, Eugene R, Brody, Jennifer A, Cade, Brian E, Celedon, Juan C, Chang, Yi-Cheng, Cupples, L Adrienne, Custer, Brian, Freedman, Barry I, Gladwin, Mark T, Heckbert, Susan R, Hou, Lifang, Irvin, Marguerite R, Isasi, Carmen R, Johnsen, Jill M, Kenny, Eimear E, Kooperberg, Charles, Minster, Ryan L, Naseri, Take, Viali, Satupa’itea, Nekhai, Sergei, Pankratz, Nathan, Peyser, Patricia A, Taylor, Kent D, Telen, Marilyn J, Wu, Baojun, Yanek, Lisa R, Yang, Ivana V, Albert, Christine, Arnett, Donna K, Ashley-Koch, Allison E, Barnes, Kathleen C, Bis, Joshua C, Blackwell, Thomas W, Boerwinkle, Eric, Burchard, Esteban G, Carson, April P, Chen, Zhanghua, Chen, Yii-Der Ida, Darbar, Dawood, de Andrade, Mariza, Ellinor, Patrick T, Fornage, Myriam, Gelb, Bruce D, Gilliland, Frank D, He, Jiang, Islam, Talat, Kaab, Stefan, Kardia, Sharon LR, Kelly, Shannon, Konkle, Barbara A, Kumar, Rajesh, Loos, Ruth JF, Martinez, Fernando D, McGarvey, Stephen T, Meyers, Deborah A, Mitchell, Braxton D, Montgomery, Courtney G, North, Kari E, Palmer, Nicholette D, Peralta, Juan M, Raby, Benjamin A, Redline, Susan, Rich, Stephen S, Roden, Dan, Rotter, Jerome I, Ruczinski, Ingo, Schwartz, David, Sciurba, Frank, Shoemaker, M Benjamin, Silverman, Edwin K, Sinner, Moritz F, Smith, Nicholas L, Smith, Albert V, Tiwari, Hemant K, Vasan, Ramachandran S, Weiss, Scott T, Williams, L Keoki, Zhang, Yingze, Ziv, Elad, Raffield, Laura M, Reiner, Alexander P, Arvanitis, Marios, Greider, Carol W, Mathias, Rasika A, and Battle, Alexis

Subjects
Biological Sciences, Genetics, Human Genome, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Generic health relevance, Humans, Genome-Wide Association Study, Telomere, K562 Cells, Telomere Homeostasis, Polymorphism, Single Nucleotide, Gene Expression Regulation, CRISPR-Cas Systems, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract

Genome-wide association studies (GWAS) have become well-powered to detect loci associated with telomere length. However, no prior work has validated genes nominated by GWAS to examine their role in telomere length regulation. We conducted a multi-ancestry meta-analysis of 211,369 individuals and identified five novel association signals. Enrichment analyses of chromatin state and cell-type heritability suggested that blood/immune cells are the most relevant cell type to examine telomere length association signals. We validated specific GWAS associations by overexpressing KBTBD6 or POP5 and demonstrated that both lengthened telomeres. CRISPR/Cas9 deletion of the predicted causal regions in K562 blood cells reduced expression of these genes, demonstrating that these loci are related to transcriptional regulation of KBTBD6 and POP5. Our results demonstrate the utility of telomere length GWAS in the identification of telomere length regulation mechanisms and validate KBTBD6 and POP5 as genes affecting telomere length regulation.

Published
2024

4. Population-average mediation analysis for zero-inflated count outcomes

Author

Sims, Andrew, Long, D. Leann, Tiwari, Hemant K., Cui, Jinhong, Long, Dustin M., Brown, Todd M., Smith, Melissa J., and Levitan, Emily B.

Subjects
Statistics - Methodology
Abstract

Mediation analysis is an increasingly popular statistical method for explaining causal pathways to inform intervention. While methods have increased, there is still a dearth of robust mediation methods for count outcomes with excess zeroes. Current mediation methods addressing this issue are computationally intensive, biased, or challenging to interpret. To overcome these limitations, we propose a new mediation methodology for zero-inflated count outcomes using the marginalized zero-inflated Poisson (MZIP) model and the counterfactual approach to mediation. This novel work gives population-average mediation effects whose variance can be estimated rapidly via delta method. This methodology is extended to cases with exposure-mediator interactions. We apply this novel methodology to explore if diabetes diagnosis can explain BMI differences in healthcare utilization and test model performance via simulations comparing the proposed MZIP method to existing zero-inflated and Poisson methods. We find that our proposed method minimizes bias and computation time compared to alternative approaches while allowing for straight-forward interpretations., Comment: 34 pages, 2 figures, 4 tables, 49 pages of Supplemental material, 2 supplemental figures

Published
2023

7. Novel functional insights into ischemic stroke biology provided by the first genome-wide association study of stroke in indigenous Africans

Author

Akinyemi, Rufus O., Tiwari, Hemant K., Srinivasasainagendra, Vinodh, Akpa, Onoja, Sarfo, Fred S., Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Osaigbovo, Godwin O., Mamaeva, Olga A., Halloran, Brian A., Akinyemi, Joshua, Lackland, Daniel, Obiabo, Olugbo Y., Sunmonu, Taofik, Chukwuonye, Innocent I., Arulogun, Oyedunni, Jenkins, Carolyn, Adeoye, Abiodun, Agunloye, Atinuke, Ogah, Okechukwu S., Ogbole, Godwin, Fakunle, Adekunle, Uvere, Ezinne, Coker, Motunrayo M., Okekunle, Akinkunmi, Asowata, Osahon, Diala, Samuel, Ogunronbi, Mayowa, Adeleye, Osi, Laryea, Ruth, Tagge, Raelle, Adeniyi, Sunday, Adusei, Nathaniel, Oguike, Wisdom, Olowoyo, Paul, Adebajo, Olayinka, Olalere, Abimbola, Oladele, Olayinka, Yaria, Joseph, Fawale, Bimbo, Ibinaye, Philip, Oyinloye, Olalekan, Mensah, Yaw, Oladimeji, Omotola, Akpalu, Josephine, Calys-Tagoe, Benedict, Dambatta, Hamisu A., Ogunniyi, Adesola, Kalaria, Rajesh, Arnett, Donna, Rotimi, Charles, Ovbiagele, Bruce, and Owolabi, Mayowa O.

Published
2024
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11. Mendelian randomization supports bidirectional causality between telomere length and clonal hematopoiesis of indeterminate potential

Author

Nakao, Tetsushi, Bick, Alexander G, Taub, Margaret A, Zekavat, Seyedeh M, Uddin, Md M, Niroula, Abhishek, Carty, Cara L, Lane, John, Honigberg, Michael C, Weinstock, Joshua S, Pampana, Akhil, Gibson, Christopher J, Griffin, Gabriel K, Clarke, Shoa L, Bhattacharya, Romit, Assimes, Themistocles L, Emery, Leslie S, Stilp, Adrienne M, Wong, Quenna, Broome, Jai, Laurie, Cecelia A, Khan, Alyna T, Smith, Albert V, Blackwell, Thomas W, Codd, Veryan, Nelson, Christopher P, Yoneda, Zachary T, Peralta, Juan M, Bowden, Donald W, Irvin, Marguerite R, Boorgula, Meher, Zhao, Wei, Yanek, Lisa R, Wiggins, Kerri L, Hixson, James E, Gu, C Charles, Peloso, Gina M, Roden, Dan M, Reupena, Muagututi’a S, Hwu, Chii-Min, DeMeo, Dawn L, North, Kari E, Kelly, Shannon, Musani, Solomon K, Bis, Joshua C, Lloyd-Jones, Donald M, Johnsen, Jill M, Preuss, Michael, Tracy, Russell P, Peyser, Patricia A, Qiao, Dandi, Desai, Pinkal, Curran, Joanne E, Freedman, Barry I, Tiwari, Hemant K, Chavan, Sameer, Smith, Jennifer A, Smith, Nicholas L, Kelly, Tanika N, Hidalgo, Bertha, Cupples, L Adrienne, Weeks, Daniel E, Hawley, Nicola L, Minster, Ryan L, Deka, Ranjan, Naseri, Take T, de las Fuentes, Lisa, Raffield, Laura M, Morrison, Alanna C, Vries, Paul S, Ballantyne, Christie M, Kenny, Eimear E, Rich, Stephen S, Whitsel, Eric A, Cho, Michael H, Shoemaker, M Benjamin, Pace, Betty S, Blangero, John, Palmer, Nicholette D, Mitchell, Braxton D, Shuldiner, Alan R, Barnes, Kathleen C, Redline, Susan, Kardia, Sharon LR, Abecasis, Gonçalo R, Becker, Lewis C, Heckbert, Susan R, He, Jiang, Post, Wendy, Arnett, Donna K, Vasan, Ramachandran S, Darbar, Dawood, Weiss, Scott T, McGarvey, Stephen T, de Andrade, Mariza, Chen, Yii-Der Ida, Kaplan, Robert C, Meyers, Deborah A, Custer, Brian S, and Correa, Adolfo

Subjects
Cardiovascular, Genetics, Aging, Heart Disease, Heart Disease - Coronary Heart Disease, Human Genome, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Samoan Obesity, Lifestyle and Genetic Adaptations Study (OLaGA) Group, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium
Abstract

Human genetic studies support an inverse causal relationship between leukocyte telomere length (LTL) and coronary artery disease (CAD), but directionally mixed effects for LTL and diverse malignancies. Clonal hematopoiesis of indeterminate potential (CHIP), characterized by expansion of hematopoietic cells bearing leukemogenic mutations, predisposes both hematologic malignancy and CAD. TERT (which encodes telomerase reverse transcriptase) is the most significantly associated germline locus for CHIP in genome-wide association studies. Here, we investigated the relationship between CHIP, LTL, and CAD in the Trans-Omics for Precision Medicine (TOPMed) program (n = 63,302) and UK Biobank (n = 47,080). Bidirectional Mendelian randomization studies were consistent with longer genetically imputed LTL increasing propensity to develop CHIP, but CHIP then, in turn, hastens to shorten measured LTL (mLTL). We also demonstrated evidence of modest mediation between CHIP and CAD by mLTL. Our data promote an understanding of potential causal relationships across CHIP and LTL toward prevention of CAD.

Published
2022

13. Genetic determinants of telomere length from 109,122 ancestrally diverse whole-genome sequences in TOPMed

Author

Taub, Margaret A, Conomos, Matthew P, Keener, Rebecca, Iyer, Kruthika R, Weinstock, Joshua S, Yanek, Lisa R, Lane, John, Miller-Fleming, Tyne W, Brody, Jennifer A, Raffield, Laura M, McHugh, Caitlin P, Jain, Deepti, Gogarten, Stephanie M, Laurie, Cecelia A, Keramati, Ali, Arvanitis, Marios, Smith, Albert V, Heavner, Benjamin, Barwick, Lucas, Becker, Lewis C, Bis, Joshua C, Blangero, John, Bleecker, Eugene R, Burchard, Esteban G, Celedón, Juan C, Chang, Yen Pei C, Custer, Brian, Darbar, Dawood, de las Fuentes, Lisa, DeMeo, Dawn L, Freedman, Barry I, Garrett, Melanie E, Gladwin, Mark T, Heckbert, Susan R, Hidalgo, Bertha A, Irvin, Marguerite R, Islam, Talat, Johnson, W Craig, Kaab, Stefan, Launer, Lenore, Lee, Jiwon, Liu, Simin, Moscati, Arden, North, Kari E, Peyser, Patricia A, Rafaels, Nicholas, Seidman, Christine, Weeks, Daniel E, Wen, Fayun, Wheeler, Marsha M, Williams, L Keoki, Yang, Ivana V, Zhao, Wei, Aslibekyan, Stella, Auer, Paul L, Bowden, Donald W, Cade, Brian E, Chen, Zhanghua, Cho, Michael H, Cupples, L Adrienne, Curran, Joanne E, Daya, Michelle, Deka, Ranjan, Eng, Celeste, Fingerlin, Tasha E, Guo, Xiuqing, Hou, Lifang, Hwang, Shih-Jen, Johnsen, Jill M, Kenny, Eimear E, Levin, Albert M, Liu, Chunyu, Minster, Ryan L, Naseri, Take, Nouraie, Mehdi, Reupena, Muagututi A Sefuiva, Sabino, Ester C, Smith, Jennifer A, Smith, Nicholas L, Lasky-Su, Jessica, Taylor, James G, Telen, Marilyn J, Tiwari, Hemant K, Tracy, Russell P, White, Marquitta J, Zhang, Yingze, Wiggins, Kerri L, Weiss, Scott T, Vasan, Ramachandran S, Taylor, Kent D, Sinner, Moritz F, Silverman, Edwin K, Shoemaker, M Benjamin, Sheu, Wayne H-H, Sciurba, Frank, Schwartz, David A, Rotter, Jerome I, Roden, Daniel, Redline, Susan, and Raby, Benjamin A

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Human Genome, Biotechnology, Aetiology, 2.1 Biological and endogenous factors, Generic health relevance, Good Health and Well Being, NHLBI CARE Network, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology and Hemostasis Working Group, TOPMed Structural Variation Working Group
Abstract

Genetic studies on telomere length are important for understanding age-related diseases. Prior GWAS for leukocyte TL have been limited to European and Asian populations. Here, we report the first sequencing-based association study for TL across ancestrally-diverse individuals (European, African, Asian and Hispanic/Latino) from the NHLBI Trans-Omics for Precision Medicine (TOPMed) program. We used whole genome sequencing (WGS) of whole blood for variant genotype calling and the bioinformatic estimation of telomere length in n=109,122 individuals. We identified 59 sentinel variants (p-value

Published
2022

14. Genetic variation in genes regulating skeletal muscle regeneration and tissue remodelling associated with weight loss in chronic obstructive pulmonary disease

Author

Kumar, Preeti Lakshman, Wilson, Ava C, Rocco, Alison, Cho, Michael H, Wan, Emily, Hobbs, Brian D, Washko, George R, Ortega, Victor E, Christenson, Stephanie A, Li, Xingnan, Wells, J Michael, Bhatt, Surya P, DeMeo, Dawn L, Lutz, Sharon M, Rossiter, Harry, Casaburi, Richard, Rennard, Stephen I, Lomas, David A, Labaki, Wassim W, Tal‐Singer, Ruth, Bowler, Russel P, Hersh, Craig P, Tiwari, Hemant K, Dransfield, Mark, Thalacker‐Mercer, Anna, Meyers, Deborah A, Silverman, Edwin K, McDonald, Merry‐Lynn N, and COPDGene, ECLIPSE and SPIROMICS investigators

Subjects
Epidemiology, Health Sciences, Chronic Obstructive Pulmonary Disease, Genetics, Clinical Research, Lung, Prevention, Human Genome, Nutrition, Aetiology, Underpinning research, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Respiratory, Adult, Bayes Theorem, Genetic Variation, Genome-Wide Association Study, Humans, Muscle, Skeletal, Nerve Tissue Proteins, Pulmonary Disease, Chronic Obstructive, Regeneration, Weight Loss, GWAS, Cachexia, Weight loss, COPD, Biomarkers, Skeletal muscle regeneration, Tissue remodelling, COPDGene, ECLIPSE and SPIROMICS investigators, Physiology, Clinical Sciences, Human Movement and Sports Sciences, Clinical sciences, Allied health and rehabilitation science, Sports science and exercise
Abstract

BackgroundChronic obstructive pulmonary disease (COPD) is the third leading cause of death globally. COPD patients with cachexia or weight loss have increased risk of death independent of body mass index (BMI) and lung function. We tested the hypothesis genetic variation is associated with weight loss in COPD using a genome-wide association study approach.MethodsParticipants with COPD (N = 4308) from three studies (COPDGene, ECLIPSE, and SPIROMICS) were analysed. Discovery analyses were performed in COPDGene with replication in SPIROMICS and ECLIPSE. In COPDGene, weight loss was defined as self-reported unintentional weight loss > 5% in the past year or low BMI (BMI

Published
2021

15. Clinical and neuroimaging factors associated with 30-day fatality among indigenous West Africans with spontaneous intracerebral hemorrhage

Author

Komolafe, Morenikeji A., Sunmonu, Taofiki, Akinyemi, Joshua, Sarfo, Fred S., Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Owolabi, Lukman, Osaigbovo, Godwin O., Ogbole, Godwin, Tiwari, Hemant K., Jenkins, Carolyn, Lackland, Daniel T., Fakunle, Adekunle G., Uvere, Ezinne, Akpa, Onoja, Dambatta, Hamisu A., Akpalu, Josephine, Onasanya, Akinola, Olaleye, Adeniji, Ogah, Okechukwu S., Isah, Sulaiman Y., Fawale, Micheal B., Adebowale, Akintunde, Okekunle, Akinkunmi P., Arnett, Donna, Adeoye, Abiodun M., Agunloye, Atinuke M., Bello, Abiodun H., Aderibigbe, Adeniyi S., Idowu, Ahmed O., Sanusi, Ahmad A., Ogunmodede, Adebimpe, Balogun, Simon A., Egberongbe, Adedeji A., Rotimi, Folorunso T., Fredrick, Adeyemi, Akinnuoye, Andrew O., Adeniyi, Folu A., Calys-Tagoe, Benedict, Adebayo, Philip, Arulogun, Oyedunni, Agbogu-Ike, Obiageli U., Yaria, Joseph, Appiah, Lambert, Ibinaiye, Philip, Singh, Arti, Adeniyi, Sunday, Olalusi, Oladotun, Mande, Aliyu, Balogun, Olayemi, Akinyemi, Rufus, Ovbiagele, Bruce, and Owolabi, Mayowa

Published
2024
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16. Robust, flexible, and scalable tests for Hardy-Weinberg Equilibrium across diverse ancestries

Author

Kwong, Alan M, Blackwell, Thomas W, LeFaive, Jonathon, de Andrade, Mariza, Barnard, John, Barnes, Kathleen C, Blangero, John, Boerwinkle, Eric, Burchard, Esteban G, Cade, Brian E, Chasman, Daniel I, Chen, Han, Conomos, Matthew P, Cupples, L Adrienne, Ellinor, Patrick T, Eng, Celeste, Gao, Yan, Guo, Xiuqing, Irvin, Marguerite Ryan, Kelly, Tanika N, Kim, Wonji, Kooperberg, Charles, Lubitz, Steven A, Mak, Angel CY, Manichaikul, Ani W, Mathias, Rasika A, Montasser, May E, Montgomery, Courtney G, Musani, Solomon, Palmer, Nicholette D, Peloso, Gina M, Qiao, Dandi, Reiner, Alexander P, Roden, Dan M, Shoemaker, M Benjamin, Smith, Jennifer A, Smith, Nicholas L, Su, Jessica Lasky, Tiwari, Hemant K, Weeks, Daniel E, Weiss, Scott T, Consortium, TOPMed Analysis Working Group NHLBI Trans-Omics for Precision Medicine, Scott, Laura J, Smith, Albert V, Abecasis, Gonçalo R, Boehnke, Michael, and Kang, Hyun Min

Subjects
Genetics, Alleles, Gene Frequency, Genetics, Population, Genotype, Humans, Linkage Disequilibrium, Models, Genetic, Models, Statistical, Phenotype, Software, population structure, principal components analysis, next-generation sequencing, genotype likelihoods, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Analysis Working Group, Developmental Biology
Abstract

Traditional Hardy-Weinberg equilibrium (HWE) tests (the χ2 test and the exact test) have long been used as a metric for evaluating genotype quality, as technical artifacts leading to incorrect genotype calls often can be identified as deviations from HWE. However, in data sets composed of individuals from diverse ancestries, HWE can be violated even without genotyping error, complicating the use of HWE testing to assess genotype data quality. In this manuscript, we present the Robust Unified Test for HWE (RUTH) to test for HWE while accounting for population structure and genotype uncertainty, and to evaluate the impact of population heterogeneity and genotype uncertainty on the standard HWE tests and alternative methods using simulated and real sequence data sets. Our results demonstrate that ignoring population structure or genotype uncertainty in HWE tests can inflate false-positive rates by many orders of magnitude. Our evaluations demonstrate different tradeoffs between false positives and statistical power across the methods, with RUTH consistently among the best across all evaluations. RUTH is implemented as a practical and scalable software tool to rapidly perform HWE tests across millions of markers and hundreds of thousands of individuals while supporting standard VCF/BCF formats. RUTH is publicly available at https://www.github.com/statgen/ruth.

Published
2021

18. A lipidome-wide association study of the lipoprotein insulin resistance index

Author

Bagheri, Minoo, Tiwari, Hemant K, Murillo, Anarina L, Al-Tobasei, Rafet, Arnett, Donna K, Kind, Tobias, Barupal, Dinesh Kumar, Fan, Sili, Fiehn, Oliver, O’connell, Jeff, Montasser, May, Aslibekyan, Stella, and Irvin, Marguerite R

Subjects
Diabetes, Obesity, Heart Disease, Cardiovascular, Prevention, Metabolic and endocrine, Adult, Aged, Body Mass Index, Diabetes Mellitus, Type 2, Female, Humans, Insulin Resistance, Lipidomics, Lipids, Lipoproteins, Male, Middle Aged, Triglycerides, Waist Circumference, Insulin resistance, Lipoprotein, GOLDN, Triglyceride, Diglyceride, Phospholipid, Other Information and Computing Sciences, Medical Biochemistry and Metabolomics, Nutrition and Dietetics, Nutrition & Dietetics
Abstract

BackgroundThe lipoprotein insulin resistance (LPIR) score was shown to predict insulin resistance (IR) and type 2 diabetes (T2D) in healthy adults. However, the molecular basis underlying the LPIR utility for classification remains unclear.ObjectiveTo identify small molecule lipids associated with variation in the LPIR score, a weighted index of lipoproteins measured by nuclear magnetic resonance, in the Genetics of Lipid Lowering Drugs and Diet Network (GOLDN) study (n = 980).MethodsLinear mixed effects models were used to test the association between the LPIR score and 413 lipid species and their principal component analysis-derived groups. Significant associations were tested for replication with homeostatic model assessment-IR (HOMA-IR), a phenotype correlated with the LPIR score (r = 0.48, p

Published
2020

19. Heme metabolism genes Downregulated in COPD Cachexia

Author

Wilson, Ava C, Kumar, Preeti L, Lee, Sool, Parker, Margaret M, Arora, Itika, Morrow, Jarrett D, Wouters, Emiel FM, Casaburi, Richard, Rennard, Stephen I, Lomas, David A, Agusti, Alvar, Tal-Singer, Ruth, Dransfield, Mark T, Wells, J Michael, Bhatt, Surya P, Washko, George, Thannickal, Victor J, Tiwari, Hemant K, Hersh, Craig P, Castaldi, Peter J, Silverman, Edwin K, and McDonald, Merry-Lynn N

Subjects
Hematology, Lung, Chronic Obstructive Pulmonary Disease, Clinical Research, Genetics, Nutrition, Respiratory, Aged, Aged, 80 and over, Cachexia, Cohort Studies, Down-Regulation, Female, Follow-Up Studies, Genome-Wide Association Study, Heme, Humans, Longitudinal Studies, Male, Middle Aged, Pulmonary Disease, Chronic Obstructive, Chronic obstructive pulmonary disease, Cardiorespiratory Medicine and Haematology, Clinical Sciences, Respiratory System
Abstract

IntroductionCachexia contributes to increased mortality and reduced quality of life in Chronic Obstructive Pulmonary Disease (COPD) and may be associated with underlying gene expression changes. Our goal was to identify differential gene expression signatures associated with COPD cachexia in current and former smokers.MethodsWe analyzed whole-blood gene expression data from participants with COPD in a discovery cohort (COPDGene, N = 400) and assessed replication (ECLIPSE, N = 114). To approximate the consensus definition using available criteria, cachexia was defined as weight-loss > 5% in the past 12 months or low body mass index (BMI) ( 5% in the past 12 months or low BMI and 3/5 criteria: decreased muscle strength, anorexia, abnormal biochemistry (anemia or high c-reactive protein (> 5 mg/l)), fatigue, and low FFMI. Differential gene expression was assessed between cachectic and non-cachectic subjects, adjusting for age, sex, white blood cell counts, and technical covariates. Gene set enrichment analysis was performed using MSigDB.ResultsThe prevalence of COPD cachexia was 13.7% in COPDGene and 7.9% in ECLIPSE. Fourteen genes were differentially downregulated in cachectic versus non-cachectic COPD patients in COPDGene (FDR

Published
2020

21. Inherited causes of clonal haematopoiesis in 97,691 whole genomes

Author

Bick, Alexander G, Weinstock, Joshua S, Nandakumar, Satish K, Fulco, Charles P, Bao, Erik L, Zekavat, Seyedeh M, Szeto, Mindy D, Liao, Xiaotian, Leventhal, Matthew J, Nasser, Joseph, Chang, Kyle, Laurie, Cecelia, Burugula, Bala Bharathi, Gibson, Christopher J, Niroula, Abhishek, Lin, Amy E, Taub, Margaret A, Aguet, Francois, Ardlie, Kristin, Mitchell, Braxton D, Barnes, Kathleen C, Moscati, Arden, Fornage, Myriam, Redline, Susan, Psaty, Bruce M, Silverman, Edwin K, Weiss, Scott T, Palmer, Nicholette D, Vasan, Ramachandran S, Burchard, Esteban G, Kardia, Sharon LR, He, Jiang, Kaplan, Robert C, Smith, Nicholas L, Arnett, Donna K, Schwartz, David A, Correa, Adolfo, de Andrade, Mariza, Guo, Xiuqing, Konkle, Barbara A, Custer, Brian, Peralta, Juan M, Gui, Hongsheng, Meyers, Deborah A, McGarvey, Stephen T, Chen, Ida Yii-Der, Shoemaker, M Benjamin, Peyser, Patricia A, Broome, Jai G, Gogarten, Stephanie M, Wang, Fei Fei, Wong, Quenna, Montasser, May E, Daya, Michelle, Kenny, Eimear E, North, Kari E, Launer, Lenore J, Cade, Brian E, Bis, Joshua C, Cho, Michael H, Lasky-Su, Jessica, Bowden, Donald W, Cupples, L Adrienne, Mak, Angel CY, Becker, Lewis C, Smith, Jennifer A, Kelly, Tanika N, Aslibekyan, Stella, Heckbert, Susan R, Tiwari, Hemant K, Yang, Ivana V, Heit, John A, Lubitz, Steven A, Johnsen, Jill M, Curran, Joanne E, Wenzel, Sally E, Weeks, Daniel E, Rao, Dabeeru C, Darbar, Dawood, Moon, Jee-Young, Tracy, Russell P, Buth, Erin J, Rafaels, Nicholas, Loos, Ruth JF, Durda, Peter, Liu, Yongmei, Hou, Lifang, Lee, Jiwon, Kachroo, Priyadarshini, Freedman, Barry I, Levy, Daniel, Bielak, Lawrence F, Hixson, James E, Floyd, James S, Whitsel, Eric A, Ellinor, Patrick T, Irvin, Marguerite R, Fingerlin, Tasha E, Raffield, Laura M, and Armasu, Sebastian M

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Biotechnology, Regenerative Medicine, Stem Cell Research, Human Genome, Underpinning research, Aetiology, 1.1 Normal biological development and functioning, 2.1 Biological and endogenous factors, Cardiovascular, Generic health relevance, Inflammatory and immune system, Good Health and Well Being, Adult, Africa, Aged, Aged, 80 and over, Black People, Cell Self Renewal, Clonal Hematopoiesis, DNA-Binding Proteins, Dioxygenases, Female, Genetic Predisposition to Disease, Genome, Human, Germ-Line Mutation, Hematopoietic Stem Cells, Humans, Intracellular Signaling Peptides and Proteins, Male, Middle Aged, National Heart, Lung, and Blood Institute (U.S.), Phenotype, Precision Medicine, Proto-Oncogene Proteins, Tripartite Motif Proteins, United States, Whole Genome Sequencing, alpha Karyopherins, NHLBI Trans-Omics for Precision Medicine Consortium, General Science & Technology
Abstract

Age is the dominant risk factor for most chronic human diseases, but the mechanisms through which ageing confers this risk are largely unknown1. The age-related acquisition of somatic mutations that lead to clonal expansion in regenerating haematopoietic stem cell populations has recently been associated with both haematological cancer2-4 and coronary heart disease5-this phenomenon is termed clonal haematopoiesis of indeterminate potential (CHIP)6. Simultaneous analyses of germline and somatic whole-genome sequences provide the opportunity to identify root causes of CHIP. Here we analyse high-coverage whole-genome sequences from 97,691 participants of diverse ancestries in the National Heart, Lung, and Blood Institute Trans-omics for Precision Medicine (TOPMed) programme, and identify 4,229 individuals with CHIP. We identify associations with blood cell, lipid and inflammatory traits that are specific to different CHIP driver genes. Association of a genome-wide set of germline genetic variants enabled the identification of three genetic loci associated with CHIP status, including one locus at TET2 that was specific to individuals of African ancestry. In silico-informed in vitro evaluation of the TET2 germline locus enabled the identification of a causal variant that disrupts a TET2 distal enhancer, resulting in increased self-renewal of haematopoietic stem cells. Overall, we observe that germline genetic variation shapes haematopoietic stem cell function, leading to CHIP through mechanisms that are specific to clonal haematopoiesis as well as shared mechanisms that lead to somatic mutations across tissues.

Published
2020

22. Dynamic incorporation of multiple in silico functional annotations empowers rare variant association analysis of large whole-genome sequencing studies at scale.

Author

Li, Xihao, Li, Zilin, Zhou, Hufeng, Gaynor, Sheila M, Liu, Yaowu, Chen, Han, Sun, Ryan, Dey, Rounak, Arnett, Donna K, Aslibekyan, Stella, Ballantyne, Christie M, Bielak, Lawrence F, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Broome, Jai G, Conomos, Matthew P, Correa, Adolfo, Cupples, L Adrienne, Curran, Joanne E, Freedman, Barry I, Guo, Xiuqing, Hindy, George, Irvin, Marguerite R, Kardia, Sharon LR, Kathiresan, Sekar, Khan, Alyna T, Kooperberg, Charles L, Laurie, Cathy C, Liu, X Shirley, Mahaney, Michael C, Manichaikul, Ani W, Martin, Lisa W, Mathias, Rasika A, McGarvey, Stephen T, Mitchell, Braxton D, Montasser, May E, Moore, Jill E, Morrison, Alanna C, O'Connell, Jeffrey R, Palmer, Nicholette D, Pampana, Akhil, Peralta, Juan M, Peyser, Patricia A, Psaty, Bruce M, Redline, Susan, Rice, Kenneth M, Rich, Stephen S, Smith, Jennifer A, Tiwari, Hemant K, Tsai, Michael Y, Vasan, Ramachandran S, Wang, Fei Fei, Weeks, Daniel E, Weng, Zhiping, Wilson, James G, Yanek, Lisa R, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Neale, Benjamin M, Sunyaev, Shamil R, Abecasis, Gonçalo R, Rotter, Jerome I, Willer, Cristen J, Peloso, Gina M, Natarajan, Pradeep, and Lin, Xihong

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Lipids Working Group, Humans, Genetic Predisposition to Disease, Phenotype, Genome, Models, Genetic, Computer Simulation, Cholesterol, LDL, Genetic Variation, Genome-Wide Association Study, Molecular Sequence Annotation, Whole Genome Sequencing, Models, Genetic, Cholesterol, LDL, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Large-scale whole-genome sequencing studies have enabled the analysis of rare variants (RVs) associated with complex phenotypes. Commonly used RV association tests have limited scope to leverage variant functions. We propose STAAR (variant-set test for association using annotation information), a scalable and powerful RV association test method that effectively incorporates both variant categories and multiple complementary annotations using a dynamic weighting scheme. For the latter, we introduce 'annotation principal components', multidimensional summaries of in silico variant annotations. STAAR accounts for population structure and relatedness and is scalable for analyzing very large cohort and biobank whole-genome sequencing studies of continuous and dichotomous traits. We applied STAAR to identify RVs associated with four lipid traits in 12,316 discovery and 17,822 replication samples from the Trans-Omics for Precision Medicine Program. We discovered and replicated new RV associations, including disruptive missense RVs of NPC1L1 and an intergenic region near APOC1P1 associated with low-density lipoprotein cholesterol.

Published
2020

23. Genetic Admixture and Survival in Diverse Populations with Pulmonary Arterial Hypertension

Author

Karnes, Jason H, Wiener, Howard W, Schwantes-An, Tae-Hwi, Natarajan, Balaji, Sweatt, Andrew J, Chaturvedi, Abhishek, Arora, Amit, Batai, Ken, Nair, Vineet, Steiner, Heidi E, Giles, Jason B, Yu, Jeffrey, Hosseini, Maryam, Pauciulo, Michael W, Lutz, Katie A, Coleman, Anna W, Feldman, Jeremy, Vanderpool, Rebecca, Tang, Haiyang, Garcia, Joe GN, Yuan, Jason X-J, Kittles, Rick, de Jesus Perez, Vinicio, Zamanian, Roham T, Rischard, Franz, Tiwari, Hemant K, Nichols, William C, Benza, Raymond L, and Desai, Ankit A

Subjects
Lung, Good Health and Well Being, Adult, Black or African American, Aged, Female, Hispanic or Latino, Humans, Male, Middle Aged, Pulmonary Arterial Hypertension, Survival Rate, United States, White People, pulmonary arterial hypertension, Hispanic American, Native American, survival, health disparities, Medical and Health Sciences, Respiratory System
Abstract

Rationale: Limited information is available on racial/ethnic differences in pulmonary arterial hypertension (PAH).Objectives: Determine effects of race/ethnicity and ancestry on mortality and disease outcomes in diverse patients with PAH.Methods: Patients with Group 1 PAH were included from two national registries with genome-wide data and two local cohorts, and further incorporated in a global meta-analysis. Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for transplant-free, all-cause mortality in Hispanic patients with non-Hispanic white (NHW) patients as the reference group. Odds ratios (ORs) for inpatient-specific mortality in patients with PAH were also calculated for race/ethnic groups from an additional National Inpatient Sample dataset not included in the meta-analysis.Measurements and Main Results: After covariate adjustment, self-reported Hispanic patients (n = 290) exhibited significantly reduced mortality versus NHW patients (n = 1,970) after global meta-analysis (HR, 0.60 [95% CI, 0.41-0.87]; P = 0.008). Although not significant, increasing Native American genetic ancestry appeared to account for part of the observed mortality benefit (HR, 0.48 [95% CI, 0.23-1.01]; P = 0.053) in the two national registries. Finally, in the National Inpatient Sample, an inpatient mortality benefit was also observed for Hispanic patients (n = 1,524) versus NHW patients (n = 8,829; OR, 0.65 [95% CI, 0.50-0.84]; P = 0.001). An inpatient mortality benefit was observed for Native American patients (n = 185; OR, 0.38 [95% CI, 0.15-0.93]; P = 0.034).Conclusions: This study demonstrates a reproducible survival benefit for Hispanic patients with Group 1 PAH in multiple clinical settings. Our results implicate contributions of genetic ancestry to differential survival in PAH.

Published
2020

24. Use of >100,000 NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium whole genome sequences improves imputation quality and detection of rare variant associations in admixed African and Hispanic/Latino populations.

Author

Kowalski, Madeline H, Qian, Huijun, Hou, Ziyi, Rosen, Jonathan D, Tapia, Amanda L, Shan, Yue, Jain, Deepti, Argos, Maria, Arnett, Donna K, Avery, Christy, Barnes, Kathleen C, Becker, Lewis C, Bien, Stephanie A, Bis, Joshua C, Blangero, John, Boerwinkle, Eric, Bowden, Donald W, Buyske, Steve, Cai, Jianwen, Cho, Michael H, Choi, Seung Hoan, Choquet, Hélène, Cupples, L Adrienne, Cushman, Mary, Daya, Michelle, de Vries, Paul S, Ellinor, Patrick T, Faraday, Nauder, Fornage, Myriam, Gabriel, Stacey, Ganesh, Santhi K, Graff, Misa, Gupta, Namrata, He, Jiang, Heckbert, Susan R, Hidalgo, Bertha, Hodonsky, Chani J, Irvin, Marguerite R, Johnson, Andrew D, Jorgenson, Eric, Kaplan, Robert, Kardia, Sharon LR, Kelly, Tanika N, Kooperberg, Charles, Lasky-Su, Jessica A, Loos, Ruth JF, Lubitz, Steven A, Mathias, Rasika A, McHugh, Caitlin P, Montgomery, Courtney, Moon, Jee-Young, Morrison, Alanna C, Palmer, Nicholette D, Pankratz, Nathan, Papanicolaou, George J, Peralta, Juan M, Peyser, Patricia A, Rich, Stephen S, Rotter, Jerome I, Silverman, Edwin K, Smith, Jennifer A, Smith, Nicholas L, Taylor, Kent D, Thornton, Timothy A, Tiwari, Hemant K, Tracy, Russell P, Wang, Tao, Weiss, Scott T, Weng, Lu-Chen, Wiggins, Kerri L, Wilson, James G, Yanek, Lisa R, Zöllner, Sebastian, North, Kari E, Auer, Paul L, NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Raffield, Laura M, Reiner, Alexander P, and Li, Yun

Subjects
NHLBI Trans-Omics for Precision Medicine (TOPMed) Consortium, TOPMed Hematology & Hemostasis Working Group, Humans, Genetic Predisposition to Disease, Computational Biology, Genetics, Population, Gene Frequency, Linkage Disequilibrium, Databases, Genetic, Adult, Aged, Aged, 80 and over, Middle Aged, African Americans, Hispanic Americans, United States, Female, Male, Genome-Wide Association Study, beta-Globins, Genotyping Techniques, Precision Medicine, Whole Genome Sequencing, Genetics, Population, Databases, Genetic, and over, Developmental Biology
Abstract

Most genome-wide association and fine-mapping studies to date have been conducted in individuals of European descent, and genetic studies of populations of Hispanic/Latino and African ancestry are limited. In addition, these populations have more complex linkage disequilibrium structure. In order to better define the genetic architecture of these understudied populations, we leveraged >100,000 phased sequences available from deep-coverage whole genome sequencing through the multi-ethnic NHLBI Trans-Omics for Precision Medicine (TOPMed) program to impute genotypes into admixed African and Hispanic/Latino samples with genome-wide genotyping array data. We demonstrated that using TOPMed sequencing data as the imputation reference panel improves genotype imputation quality in these populations, which subsequently enhanced gene-mapping power for complex traits. For rare variants with minor allele frequency (MAF) < 0.5%, we observed a 2.3- to 6.1-fold increase in the number of well-imputed variants, with 11-34% improvement in average imputation quality, compared to the state-of-the-art 1000 Genomes Project Phase 3 and Haplotype Reference Consortium reference panels. Impressively, even for extremely rare variants with minor allele count 86%. Subsequent association analyses of TOPMed reference panel-imputed genotype data with hematological traits (hemoglobin (HGB), hematocrit (HCT), and white blood cell count (WBC)) in ~21,600 African-ancestry and ~21,700 Hispanic/Latino individuals identified associations with two rare variants in the HBB gene (rs33930165 with higher WBC [p = 8.8x10-15] in African populations, rs11549407 with lower HGB [p = 1.5x10-12] and HCT [p = 8.8x10-10] in Hispanics/Latinos). By comparison, neither variant would have been genome-wide significant if either 1000 Genomes Project Phase 3 or Haplotype Reference Consortium reference panels had been used for imputation. Our findings highlight the utility of the TOPMed imputation reference panel for identification of novel rare variant associations not previously detected in similarly sized genome-wide studies of under-represented African and Hispanic/Latino populations.

Published
2019

25. Patient-level and system-level determinants of stroke fatality across 16 large hospitals in Ghana and Nigeria: a prospective cohort study

Author

Sarfo, Fred S, Akpa, Onoja M, Ovbiagele, Bruce, Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Ogbole, Godwin, Fakunle, Adekunle, Okekunle, Akinkunmi Paul, Asowata, Osahon J, Calys-Tagoe, Benedict, Uvere, Ezinne O, Sanni, Taofeek, Olowookere, Samuel, Ibinaiye, Philip, Akinyemi, Joshua O, Arulogun, Oyedunni, Jenkins, Carolyn, Lackland, Daniel T, Tiwari, Hemant K, Isah, Suleiman Y, Abubakar, Sani A, Oladimeji, Adebayo, Adebayo, Philip, Akpalu, Josephine, Onyeonoro, Ugochukwu, Ogunmodede, James A, Akisanya, Cynthia, Mensah, Yaw, Oyinloye, Olalekan I, Appiah, Lambert, Agunloye, Atinuke M, Osaigbovo, Godwin O, Adeoye, Abiodun M, Adeleye, Osimhiarherhuo Ohifemen, Laryea, Ruth Y, Olunuga, Taiwo, Ogah, Okechukwu S, Oguike, Wisdom, Ogunronbi, Mayowa, Adeniyi, Wasiu, Olugbo, Obiabo Y, Bello, Abiodun H, Ogunjimi, Luqman, Diala, Samuel, Dambatta, Hamisu A, Singh, Arti, Adamu, Sheila, Obese, Vida, Adusei, Nathaniel, Owusu, Dorcas, Ampofo, Michael, Tagge, Raelle, Fawale, Bimbo, Yaria, Joseph, Akinyemi, Rufus O, and Owolabi, Mayowa O

Published
2023
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26. Are there differences in perceptions, preferences and attitudes towards disclosure of genetic testing for Stroke? A qualitative study among stroke-free SIREN-SIBS genomics study participants

Author

Arulogun, Oyedunni, Nichols, Michelle, Jenkins, Carolyn, Fakunle, Adekunle Gregory, Akpa, Onoja, Sarfo, Fred S., Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Osaigbovo, Godwin O., Okekunle, Akinkunmi Paul, Akinyemi, Joshua, Ogbole, Godwin, Calys-Tagoe, Benedict, Adeleye, Adeniji, Mensah, Yaw, Asowata, Osahon Jeffery, Adeoye, Abiodun M., Appiah, Lambert, Singh, Arti, Adebayo, Philip, Arnett, Donna, Tiwari, Hemant K., Lackland, Daniel, Ibinaiye, Philip, Oguike, Wisdom, Melikam, Chimdinma, Sunday, Adeniyi, Bello, Abiodun, Ogah, Okechukwu, Akinyemi, Rufus, Ovbiagele, Bruce, and Owolabi, Mayowa

Published
2023
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27. Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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28. Returning integrated genomic risk and clinical recommendations: The eMERGE study

Author

Gordon, Adam, Sobowale, Agboade, Allworth, Aimee, Patel, Akshar, DiVietro, Alanna, Strong, Alanna, Sherafati, Alborz, Sherfati, Alborz, Bick, Alex, Miller, Alexandra, Chandel, Alka, Rosenthal, Alyssa, Khera, Amit, Kontorovich, Amy, Beck, Andrew, Beck, Andy, Espinoza, Angelica, Lewis, Anna, Prince, Anya, Khan, Atlas, Iverson, Ayuko, Khales, Bahram Namjou, Benoit, Barbara, Hernan, Becca, Kallman, Ben, Kerman, Ben, Shoemaker, Ben, Satterfield, Benjamin, Devine, Beth, Etheridge, Bethany, Goff, Blake, Freimuth, Bob, Grundmeier, Bob, Collier, Brenae, Mutai, Brenda, Harnett, Brett, Chang, Brian, Piening, Brian, Davis, Brittney, Korf, Bruce, Patterson, Candace, Demetriou, Carmen, Ta, Casey, Hammack, Catherine, Nelson, Catrina, Gascoigne, Caytie, Dorn, Chad, Moretz, Chad, Kachulis, Chris, Hoell, Christie, Cowles, Christine, Lange, Christoph, Weng, Chunhua, Prows, Cindy, Brokamp, Cole, Liu, Cong, Scherr, Courtney, Gonzalez, Crystal, Ramirez, Cynthia, Shimbo, Daichi, Roden, Dan, Schaid, Daniel, Kaufman, Dave, Crosslin, David, Kochan, David, Veenstra, David, Singh, Davinder, Karavite, Dean, Abrams, Debbie, Absher, Devin, Edwards, Digna Velez, Haverfield, Eden, Morales, Eduardo, Esplin, Edward, Malolepsza, Edyta, Alipour, Ehsan, Kenny, Eimear, Rosenthal, Elisabeth, Duvall, Eliza, McNally, Elizabeth, Bhoj, Elizabeth, Cohn, Elizabeth, Hibler, Elizabeth, Karlson, Elizabeth, Clayton, Ellen, Chesnut, Emily, DeFranco, Emily, Gallagher, Emily, Soper, Emily, Perez, Emma, Cash, Erin, Berner, Eta, Wang, Fei, Wehbe, Firas, Ricci, Francisco, Mentch, Frank, Shaibi, Gabriel, Jarvik, Gail, Hahn, George, Hripcsak, George, Wiesner, Georgia, Belbin, Gillian, Davogustto, Gio, Nadkarni, Girish, Qiu, Haijun, Hakonarson, Hakon, Bangash, Hana, Beasley, Hannah, Liu, Hao, Aungst, Heide, Tiwari, Hemant, Duckham, Hillary, Thomas, Hope, Kullo, Iftikhar, Holm, Ingrid, Allen, Isabelle, Ionita-Laza, Iuliana, Hellwege, Jacklyn, Petrzelka, Jacob, Odgis, Jacqueline, Narula, Jahnavi, Petrzelka, Jake, Patel, Jalpa, Cimino, James, Meigs, James, Snyder, James, Olson, Janet, Zahner, Janet, Pennington, Jeff, Pacheco, Jen, Pacheco, Jennifer Allen, Morse, Jennifer, Corsmo, Jeremy, Thayer, Jeritt, Cimino, Jim, Chen, Jingheng, Fournier, Jocelyn, Jackson, Jodell, Glessner, Joe, Pacyna, Joel, Smith, Johanna, Connolly, John, Lynch, John, Shelley, John, Mosley, Jonathan, Nestor, Jordan, Smoller, Jordan, Alsip, Jorge, Kannry, Joseph, Sutton, Joseph, Peterson, Josh, Smith, Joshua, Galasso, Julia, Smith, Julia, Wynn, Julia, Gundelach, Justin, Starren, Justin, Choi, Karmel, Mittendorf, Kate, Anderson, Katherine, Bonini, Katherine, Leppig, Kathleen, Muenzen, Kathleen, Larkin, Katie, Stuttgen, Kelsey, Wiley, Ken, Nguyen, Kenny, Dufendach, Kevin, Atkins, Kiley, Sawicki, Konrad, Norland, Kristjan, Kiryluk, Krzysztof, Beskow, Laura, Rasmussen-Torvik, Laura, Kottyan, Leah, Hsu, Li, Tian, Lifeng, Mahanta, Lisa, Martin, Lisa, Wang, Lisa, Gomez, Lizbeth, Thompson, Lorenzo, Orlando, Lori, Richter, Lucas, Rasmussen, Luke, Petukhova, Lynn, Seabolt, Lynn, O’Brien, Madison, Harden, Maegan, Fullerton, Malia, Harr, Margaret, Beasley, Mark, Guindo, Marta, Horike, Martha, Horike-Pyne, Martha, Abdalla, Marwah, Hamed, Marwan, Terry, Mary Beth, Maradik, Mary, Wyatt, Matt, Davis, Matthew, Lebo, Matthew, Smith, Maureen, Rosario, Maya del, Sabatello, Maya, Behr, Meckenzie, Roy-Puckelwartz, Meg, Habrat, Mel, Myers, Melanie, Yetisgen, Meliha, Iris, Merve, DaSilva, Michael, Preuss, Michael, McGowan, Michelle, Shi, Mingjian, Perera, Minoli, Thomas, Minta, Elkind, Mitch, Abbass, Mohammad, Saadatagah, Mohammad, Hess, Molly, Maradik, Molly, Vaitinadin, Nataraja “RJ”, Vaitinadin, Nataraja, Muthu, Naveen, Netherly, Neil, Lennon, Niall, Shang, Ning, Limdi, Nita, Forrest, Noah, Romero, Noheli, Robinson, Nora, Abul-Husn, Noura, Elsekaily, Omar, Dikilitas, Ozan, Kovatch, Patricia, Davis, Patrick, Appelbaum, Paul, Francaviglia, Paul, O’Reilly, Paul, Chandler, Paulette, Caraballo, Pedro, Tarczy-Hornoch, Peter, Shum, Pierre, Marathe, Priya, Murali, Priyanka, Feng, Qiping, Wells, Quinn, Atchley, Rachel, Narla, Radhika, Barton, Rene, Sterling, Rene, Chisholm, Rex, Green, Richard, Sharp, Richard, Peters, Riki, Kukafka, Rita, Rowley, Robb, Freimuth, Robert, Green, Robert, Winter, Robert, Mueller, Roger, Loos, Ruth, Irvin, Ryan, Suckiel, Sabrina, Hussain, Sajjad, Sharba, Samer, Aronson, Sandy, Jones, Sarah, Knerr, Sarah, Nigbur, Scott, Weiss, Scott, Mooney, Sean, Terek, Shannon, Aufox, Sharon, Nirenberg, Sharon, Murphy, Shawn, O’Byrne, Sheila, Wang (Sam) Choi, Shing, Aguilar, Sienna, Bland, S.T., Rodrigues, Stefanie, Ledbetter, Stephanie, Rutledge, Stephanie, Booth, Stuart James, Xian, Su, Trinidad, Susan Brown, Bakken, Suzanne, Schmidlen, Tara, Rakhra-Burris, Tejinder, Manolio, Teri, Mersha, Tesfaye, Walunas, Theresa, Chandereng, Thevaa, May, Thomas, Ge, Tian, Edwards, Todd, Kaszemacher, Tom, Hernandez, Valentina, Willis, Valerie, Desai, Vemi, Desai, Vimi, Lorenzi, Virginia, Gainer, Vivian, Wei, Wei-Qi, Chung, Wendy, Su, Wu-Chen, Chang, Xiao, Zhao, Yiqing, Luo, Yuan, Shen, Yufeng, Linder, Jodell E., Bland, Sarah T., Caraballo, Pedro J., Chisholm, Rex L., Clayton, Ellen Wright, Crosslin, David R., Esplin, Edward D., Forman, Sophie, Freimuth, Robert R., Gordon, Adam S., Harden, Maegan V., Holm, Ingrid A., Jarvik, Gail P., Karlson, Elizabeth W., Labrecque, Sofia, Lennon, Niall J., Limdi, Nita A., Mittendorf, Kathleen F., Murphy, Shawn N., Prows, Cynthia A., Rasmussen, Luke V., Sawicki, Konrad Teodor, Velez Edwards, Digna R., Abul-Husn, Noura S., Below, Jennifer E., Berner, Eta S., Booth, James, Chung, Wendy K., Cimino, James J., Fullerton, Stephanie M., Guiducci, Candace, Habrat, Melissa L., Hain, Heather, Hoell, Christin, Irvin, Marguerite R., Kachulis, Christopher, Kenny, Eimear E., Kullo, Iftikhar J., Manolio, Teri A., McNally, Elizabeth M., Mooney, Sean D., Namjou, Bahram, Perez, Emma F., Puckelwartz, Megan J., Roden, Dan M., Rosenthal, Elisabeth A., Saadatagah, Seyedmohammad, Schaid, Dan J., Schultz, Baergen, Shaibi, Gabriel Q., Sharp, Richard R., Shirts, Brian, Smith, Maureen E., Smoller, Jordan W., Suckiel, Sabrina A., Tiwari, Hemant K., Trinidad, Susan B., Wells, Quinn S., Wiesner, Georgia L., and Peterson, Josh F.

Published
2023
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29. Genome-wide polygenic score to predict chronic kidney disease across ancestries

Author

Khan, Atlas, Turchin, Michael C., Patki, Amit, Srinivasasainagendra, Vinodh, Shang, Ning, Nadukuru, Rajiv, Jones, Alana C., Malolepsza, Edyta, Dikilitas, Ozan, Kullo, Iftikhar J., Schaid, Daniel J., Karlson, Elizabeth, Ge, Tian, Meigs, James B., Smoller, Jordan W., Lange, Christoph, Crosslin, David R., Jarvik, Gail P., Bhatraju, Pavan K., Hellwege, Jacklyn N., Chandler, Paulette, Torvik, Laura Rasmussen, Fedotov, Alex, Liu, Cong, Kachulis, Christopher, Lennon, Niall, Abul-Husn, Noura S., Cho, Judy H., Ionita-Laza, Iuliana, Gharavi, Ali G., Chung, Wendy K., Hripcsak, George, Weng, Chunhua, Nadkarni, Girish, Irvin, Marguerite R., Tiwari, Hemant K., Kenny, Eimear E., Limdi, Nita A., and Kiryluk, Krzysztof

Published
2022
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30. Differential associations between pre-diabetes, diabetes and stroke occurrence among West Africans

Author

Sarfo, Fred Stephen, Ovbiagele, Bruce, Akinyemi, Joshua, Akpa, Onoja, Akpalu, Albert, Wahab, Kolawole, Ogbole, Godwin, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Osaigbovo, Godwin, Jenkins, Carolyn, Fakunle, Adekunle, Adeoye, Abiodun, Lackland, Dan, Arnett, Donna, Tiwari, Hemant K., Olunuga, Taiwo, Uvere, Ezinne, Fawale, Bimbo, Ogah, Okechukwu, Agunloye, Atinuke, Faniyan, Moyinoluwalogo, Diala, Samuel, Yinka, Oladele, Laryea, Ruth, Osimhiarherhuo, Adeleye, Akinsanya, Cynthia, Abdulwasiu, Adeniyi, Akpalu, Josephine, Arulogun, Oyedunni, Appiah, Lambert, Dambatta, Hamisu, Olayemi, Balogun, Onasanya, Akinola, Isah, Sulaiman, Akinyemi, Rufus, and Owolabi, Mayowa

Published
2022
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31. Determinants of metabolic syndrome and its prognostic implications among stroke patients in Africa: Findings from the Stroke Investigative Research and Educational Network (SIREN) study

Author

Adeoye, Abiodun M., Akintunde, Adeseye A., Akinyemi, Joshua, Fakunle, Adekunle G., Sarfo, Fred S., Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Osaigbovo, Godwin O., Akpa, Onoja, Arulogun, Oyedunni, Okekunle, Akinkunmi P., Ogah, Okechukwu S., Jenkins, Carolyn, Ogbole, Godwin, Tiwari, Hemant K., Asowata, Osahon J., Ibinaiye, Philip, Appiah, Lambert, Agunloye, Atinuke M., Yaria, Joseph, Calys-Tagoe, Benedict, Agbogu-Ike, Obiageli U., Adeniyi, Sunday, Adebayo, Philip, Balogun, Olayemi, Aderonmu, Olajumoke, Adeegbe, Oluwayemisi T., Adebayo, Oladimeji, Akinyemi, Rufus, Ovbiagele, Bruce, and Owolabi, Mayowa

Published
2022
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32. Development and validation of a trans-ancestry polygenic risk score for type 2 diabetes in diverse populations

Author

Ge, Tian, Irvin, Marguerite R., Patki, Amit, Srinivasasainagendra, Vinodh, Lin, Yen-Feng, Tiwari, Hemant K., Armstrong, Nicole D., Benoit, Barbara, Chen, Chia-Yen, Choi, Karmel W., Cimino, James J., Davis, Brittney H., Dikilitas, Ozan, Etheridge, Bethany, Feng, Yen-Chen Anne, Gainer, Vivian, Huang, Hailiang, Jarvik, Gail P., Kachulis, Christopher, Kenny, Eimear E., Khan, Atlas, Kiryluk, Krzysztof, Kottyan, Leah, Kullo, Iftikhar J., Lange, Christoph, Lennon, Niall, Leong, Aaron, Malolepsza, Edyta, Miles, Ayme D., Murphy, Shawn, Namjou, Bahram, Narayan, Renuka, O’Connor, Mark J., Pacheco, Jennifer A., Perez, Emma, Rasmussen-Torvik, Laura J., Rosenthal, Elisabeth A., Schaid, Daniel, Stamou, Maria, Udler, Miriam S., Wei, Wei-Qi, Weiss, Scott T., Ng, Maggie C. Y., Smoller, Jordan W., Lebo, Matthew S., Meigs, James B., Limdi, Nita A., and Karlson, Elizabeth W.

Published
2022
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34. Polygenic liability for anxiety in association with comorbid anxiety in multiple sclerosis

Author

Kowalec, Kaarina, primary, Harder, Arvid, additional, Dolovich, Casandra, additional, Fitzgerald, Kathryn C., additional, Salter, Amber, additional, Lu, Yi, additional, Bernstein, Charles N., additional, Bolton, James M., additional, Cutter, Gary, additional, Fisk, John D., additional, Gelernter, Joel, additional, Graff, Lesley A., additional, Hägg, Sara, additional, Hitchon, Carol A., additional, Levey, Daniel F., additional, Lublin, Fred D., additional, McKay, Kyla A., additional, Patten, Scott, additional, Patki, Amit, additional, Stein, Murray B., additional, Tiwari, Hemant K., additional, Wolinsky, Jerry S., additional, and Marrie, Ruth A., additional

Published
2024
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35. Predicting oncology Drug-Induced cardiotoxicity with Donor-Specific iPSC-CMs—a proof-of-Concept study with doxorubicin

Author

Pang, Li, primary, Cai, Chengzhong, additional, Aggarwal, Praful, additional, Wang, Dong, additional, Vijay, Vikrant, additional, Bagam, Prathyusha, additional, Blamer, Jacob, additional, Matter, Andrea, additional, Turner, Amy, additional, Ren, Lijun, additional, Papineau, Katy, additional, Srinivasasainagendra, Vinodh, additional, Tiwari, Hemant K, additional, Yang, Xi, additional, Schnackenberg, Laura, additional, Mattes, William, additional, and Broeckel, Ulrich, additional

Published
2024
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36. Polygenic Risk for Type 2 Diabetes in African Americans

Author

Irvin, Marguerite R., primary, Ge, Tian, additional, Patki, Amit, additional, Srinivasasainagendra, Vinodh, additional, Armstrong, Nicole D., additional, Davis, Brittney, additional, Jones, Alana C, additional, Perez, Emma, additional, Stalbow, Lauren, additional, Lebo, Matthew, additional, Kenny, Eimear, additional, Loos, Ruth J.F., additional, Ng, Maggie C. Y., additional, Smoller, Jordan W., additional, Meigs, James B., additional, Lange, Leslie A., additional, Karlson, Elizabeth W., additional, Limdi, Nita A., additional, and Tiwari, Hemant K., additional

Published
2024
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37. A Novel Afrocentric Stroke Risk Assessment Score: Models from the Siren Study

Author

Akpa, Onoja, Sarfo, Fred S., Owolabi, Mayowa, Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Osaigbovo, Godwin O., Ogbole, Godwin, Tiwari, Hemant K., Jenkins, Carolyn, Fakunle, Adekunle G., Olowookere, Samuel, Uvere, Ezinne O., Akinyemi, Joshua, Arulogun, Oyedunni, Akpalu, Josephine, Tito-Ilori, Moyinoluwalogo M., Asowata, Osahon J., Ibinaiye, Philip, Akisanya, Cynthia, Oyinloye, Olalekan I., Appiah, Lambert, Sunmonu, Taofik, Olowoyo, Paul, Agunloye, Atinuke M., Adeoye, Abiodun M., Yaria, Joseph, Lackland, Daniel T., Arnett, Donna, Laryea, Ruth Y., Adigun, Taiwo O., Okekunle, Akinkunmi P., Calys-Tagoe, Benedict, Ogah, Okechukwu S., Ogunronbi, Mayowa, Obiabo, Olugbo Y., Isah, Suleiman Y., Dambatta, Hamisu A., Tagge, Raelle, Ogenyi, Obande, Fawale, Bimbo, Melikam, Chimdinma L., Onasanya, Akinola, Adeniyi, Sunday, Akinyemi, Rufus, and Ovbiagele, Bruce

Published
2021
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38. Influence of age on links between major modifiable risk factors and stroke occurrence in West Africa

Author

Sarfo, Fred S., Akpa, Onoja, Ovbiagele, Bruce, Akpalu, Albert, Wahab, Kolawole, Komolafe, Morenikeji, Obiako, Reginald, Owolabi, Lukman, Osaigbovo, Godwin O., Jenkins, Carolyn, Ogbole, Godwin, Fakunle, Adekunle, Tiwari, Hemant K., Arulogun, Oyedunni, Arnett, Donna K., Asowata, Osahon, Ogah, Okechukwu, Akinyemi, Rufus O., and Owolabi, Mayowa O.

Published
2021
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39. Linkage and association analysis of circulating vitamin D and parathyroid hormone identifies novel loci in Alaska Native Yup’ik people

Author

Aslibekyan, Stella, Vaughan, Laura K, Wiener, Howard W, Hidalgo, Bertha A, Lemas, Dominick J, O’Brien, Diane M, Hopkins, Scarlett E, Stanhope, Kimber L, Havel, Peter J, Thummel, Kenneth E, Boyer, Bert B, and Tiwari, Hemant K

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, American Indian or Alaska Native, Complementary and Integrative Health, Arctic, Nutrition, Human Genome, Clinical Research, Metabolic and endocrine, Alaska Native, Vitamin D, Linkage, n-3 fatty acids, Parathyroid hormone, Nutrition & Dietetics, Nutrition and dietetics
Abstract

BackgroundVitamin D deficiency is a well-documented public health issue with both genetic and environmental determinants. Populations living at far northern latitudes are vulnerable to vitamin D deficiency and its health sequelae, although consumption of traditional native dietary pattern rich in fish and marine mammals may buffer the effects of reduced sunlight exposure. To date, few studies have investigated the genetics of vitamin D metabolism in circumpolar populations or considered genediet interactions with fish and n-3 fatty acid intake.MethodsWe searched for genomic regions exhibiting linkage and association with circulating levels of vitamin D and parathyroid hormone (PTH) in 982 Yup'ik individuals from the Center for Alaska Native Health Research Study. We also investigated potential interactions between genetic variants and a biomarker of traditional dietary intake, the δ15N value.ResultsWe identified several novel regions linked with circulating vitamin D and PTH as well as replicated a previous linkage finding on 2p16.2 for vitamin D. Bioinformatic analysis revealed multiple candidate genes for both PTH and vitamin D, including CUBN, MGAT3, and NFKBIA. Targeted association analysis identified NEBL as a candidate gene for vitamin D and FNDC3B for PTH. We observed significant associations between a variant in MXD1 and vitamin D only when an interaction with the δ15N value was included. Finally, we integrated pathway level information to illustrate the biological validity of the proposed candidate genes.ConclusionWe provide evidence of linkage between several biologically plausible genomic regions and vitamin D metabolism in a circumpolar population. Additionally, these findings suggest that a traditional dietary pattern may modulate genetic effects on circulating vitamin D.

Published
2016

40. Polymorphisms in stearoyl coa desaturase and sterol regulatory element binding protein interact with N‐3 polyunsaturated fatty acid intake to modify associations with anthropometric variables and metabolic phenotypes in Yup'ik people

Author

Lemas, Dominick J, Klimentidis, Yann C, Aslibekyan, Stella, Wiener, Howard W, O'Brien, Diane M, Hopkins, Scarlett E, Stanhope, Kimber L, Havel, Peter J, Allison, David B, Fernandez, Jose R, Tiwari, Hemant K, and Boyer, Bert B

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Nutrition, Genetics, Obesity, Prevention, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Adult, Alaska, Anthropometry, Apolipoprotein A-I, Cholesterol, Cross-Sectional Studies, Diabetes Mellitus, Type 2, Diet, Fatty Acids, Omega-3, Female, Glucose Transporter Type 4, Glycated Hemoglobin, Humans, Male, Polymorphism, Single Nucleotide, Stearoyl-CoA Desaturase, Sterol Regulatory Element Binding Protein 1, Alaska Native, BMI, Gene-by-environment interactions, n-3 PUFA, Food Sciences, Public Health and Health Services, Food Science, Nutrition & Dietetics, Food sciences, Nutrition and dietetics
Abstract

Scopen-3 polyunsaturated fatty acid (n-3 PUFA) intake is associated with protection from obesity; however, the mechanisms of protection remain poorly characterized. The stearoyl CoA desaturase (SCD), insulin-sensitive glucose transporter (SLC2A4), and sterol regulatory element binding protein (SREBF1) genes are transcriptionally regulated by n-3 PUFA intake and harbor polymorphisms associated with obesity. The present study investigated how consumption of n-3 PUFA modifies associations between SCD, SLC2A4, and SREBF1 polymorphisms and anthropometric variables and metabolic phenotypes.Materials and methodsAnthropometric variables and metabolic phenotypes were measured in a cross-sectional sample of Yup'ik individuals (n = 1135) and 33 polymorphisms were tested for main effects and interactions using linear models that account for familial correlations. n-3 PUFA intake was estimated using red blood cell nitrogen stable isotope ratios. SCD polymorphisms were associated with ApoA1 concentration and n-3 PUFA interactions with SCD polymorphisms were associated with reduced fasting cholesterol levels and waist-to-hip ratio. SLC2A4 polymorphisms were associated with hip circumference, high-density lipoprotein and ApoA1 concentrations. SREBF1 polymorphisms were associated with low-density lipoprotein and HOMA-IR and n-3 PUFA interactions were associated with reduced fasting insulin and HOMA-IR levels.ConclusionThe results suggest that an individual's genotype may interact with dietary n-3 PUFAs in ways that are associated with protection from obesity-related diseases in Yup'ik people.

Published
2016

42. The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) Diet and Metabolites in Chronic Kidney Disease.

Author

Couch, Catharine A., Ament, Zsuzsanna, Patki, Amit, Kijpaisalratana, Naruchorn, Bhave, Varun, Jones, Alana C., Armstrong, Nicole D., Cheung, Katharine L., Kimberly, W. Taylor, Tiwari, Hemant K., and Irvin, Marguerite Ryan

Abstract

The Mediterranean-DASH Intervention for Neurodegenerative Delay (MIND) is a hybrid of the Mediterranean and DASH (Dietary Approaches to Stop Hypertension) diets, and its association with renal outcomes remains unclear. In the REasons for Geographic and Racial Disparities in Stroke (REGARDS) cohort, diet data were collected at baseline using food frequency questionnaires. Modified Poisson regression was used to examine the association of MIND diet with incident chronic kidney disease (CKD). In the REGARDS stroke case-cohort, 357 metabolites were measured in baseline plasma. Weighted linear regression was used to test associations between MIND diet and metabolites. Weighted logistic regression was used to test associations between MIND-associated metabolites and incident CKD. Mediation analyses were conducted to determine whether metabolites mediated the relationship between MIND diet and CKD. A higher MIND diet score was associated with a decreased risk of incident CKD (risk ratio 0.90, 95% CI (0.86–0.94); p = 2.03 × 10−7). Fifty-seven metabolites were associated with MIND diet (p < 3 × 10−4). Guanosine was found to mediate the relationship between MIND diet and incident CKD (odds ratio for indirect effects 0.93, 95% CI (0.88–0.97); p < 0.05). These findings suggest a role of the MIND diet in renal outcomes. [ABSTRACT FROM AUTHOR]

Published
2024
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43. Population‐average mediation analysis for zero‐inflated count outcomes.

Author

Sims, Andrew, Long, D. Leann, Tiwari, Hemant K., Cui, Jinhong, Long, Dustin M., Brown, Todd M., Smith, Melissa J., and Levitan, Emily B.

Subjects
DIAGNOSIS of diabetes, COUNTERFACTUALS (Logic)
Abstract

Mediation analysis is an increasingly popular statistical method for explaining causal pathways to inform intervention. While methods have increased, there is still a dearth of robust mediation methods for count outcomes with excess zeroes. Current mediation methods addressing this issue are computationally intensive, biased, or challenging to interpret. To overcome these limitations, we propose a new mediation methodology for zero‐inflated count outcomes using the marginalized zero‐inflated Poisson (MZIP) model and the counterfactual approach to mediation. This novel work gives population‐average mediation effects whose variance can be estimated rapidly via delta method. This methodology is extended to cases with exposure‐mediator interactions. We apply this novel methodology to explore if diabetes diagnosis can explain BMI differences in healthcare utilization and test model performance via simulations comparing the proposed MZIP method to existing zero‐inflated and Poisson methods. We find that our proposed method minimizes bias and computation time compared to alternative approaches while allowing for straight‐forward interpretations. [ABSTRACT FROM AUTHOR]

Published
2024
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44. Publisher Correction: Stroke genetics informs drug discovery and risk prediction across ancestries

Author

Mishra, Aniket, Malik, Rainer, Hachiya, Tsuyoshi, Jürgenson, Tuuli, Namba, Shinichi, Posner, Daniel C., Kamanu, Frederick K., Koido, Masaru, Le Grand, Quentin, Shi, Mingyang, He, Yunye, Georgakis, Marios K., Caro, Ilana, Krebs, Kristi, Liaw, Yi-Ching, Vaura, Felix C., Lin, Kuang, Winsvold, Bendik Slagsvold, Srinivasasainagendra, Vinodh, Parodi, Livia, Bae, Hee-Joon, Chauhan, Ganesh, Chong, Michael R., Tomppo, Liisa, Akinyemi, Rufus, Roshchupkin, Gennady V., Habib, Naomi, Jee, Yon Ho, Thomassen, Jesper Qvist, Abedi, Vida, Cárcel-Márquez, Jara, Nygaard, Marianne, Leonard, Hampton L., Yang, Chaojie, Yonova-Doing, Ekaterina, Knol, Maria J., Lewis, Adam J., Judy, Renae L., Ago, Tetsuro, Amouyel, Philippe, Armstrong, Nicole D., Bakker, Mark K., Bartz, Traci M., Bennett, David A., Bis, Joshua C., Bordes, Constance, Børte, Sigrid, Cain, Anael, Ridker, Paul M., Cho, Kelly, Chen, Zhengming, Cruchaga, Carlos, Cole, John W., de Jager, Phil L., de Cid, Rafael, Endres, Matthias, Ferreira, Leslie E., Geerlings, Mirjam I., Gasca, Natalie C., Gudnason, Vilmundur, Hata, Jun, He, Jing, Heath, Alicia K., Ho, Yuk-Lam, Havulinna, Aki S., Hopewell, Jemma C., Hyacinth, Hyacinth I., Inouye, Michael, Jacob, Mina A., Jeon, Christina E., Jern, Christina, Kamouchi, Masahiro, Keene, Keith L., Kitazono, Takanari, Kittner, Steven J., Konuma, Takahiro, Kumar, Amit, Lacaze, Paul, Launer, Lenore J., Lee, Keon-Joo, Lepik, Kaido, Li, Jiang, Li, Liming, Manichaikul, Ani, Markus, Hugh S., Marston, Nicholas A., Meitinger, Thomas, Mitchell, Braxton D., Montellano, Felipe A., Morisaki, Takayuki, Mosley, Thomas H., Nalls, Mike A., Nordestgaard, Børge G., O’Donnell, Martin J., Okada, Yukinori, Onland-Moret, N. Charlotte, Ovbiagele, Bruce, Peters, Annette, Psaty, Bruce M., Rich, Stephen S., Rosand, Jonathan, Sabatine, Marc S., Sacco, Ralph L., Saleheen, Danish, Sandset, Else Charlotte, Salomaa, Veikko, Sargurupremraj, Muralidharan, Sasaki, Makoto, Satizabal, Claudia L., Schmidt, Carsten O., Shimizu, Atsushi, Smith, Nicholas L., Sloane, Kelly L., Sutoh, Yoichi, Sun, Yan V., Tanno, Kozo, Tiedt, Steffen, Tatlisumak, Turgut, Torres-Aguila, Nuria P., Tiwari, Hemant K., Trégouët, David-Alexandre, Trompet, Stella, Tuladhar, Anil Man, Tybjærg-Hansen, Anne, van Vugt, Marion, Vibo, Riina, Verma, Shefali S., Wiggins, Kerri L., Wennberg, Patrik, Woo, Daniel, Wilson, Peter W. F., Xu, Huichun, Yang, Qiong, Yoon, Kyungheon, Millwood, Iona Y., Gieger, Christian, Ninomiya, Toshiharu, Grabe, Hans J., Jukema, J. Wouter, Rissanen, Ina L., Strbian, Daniel, Kim, Young Jin, Chen, Pei-Hsin, Mayerhofer, Ernst, Howson, Joanna M. M., Irvin, Marguerite R., Adams, Hieab, Wassertheil-Smoller, Sylvia, Christensen, Kaare, Ikram, Mohammad A., Rundek, Tatjana, Worrall, Bradford B., Lathrop, G. Mark, Riaz, Moeen, Simonsick, Eleanor M., Kõrv, Janika, França, Paulo H. C., Zand, Ramin, Prasad, Kameshwar, Frikke-Schmidt, Ruth, de Leeuw, Frank-Erik, Liman, Thomas, Haeusler, Karl Georg, Ruigrok, Ynte M., Heuschmann, Peter Ulrich, Longstreth, W. T., Jung, Keum Ji, Bastarache, Lisa, Paré, Guillaume, Damrauer, Scott M., Chasman, Daniel I., Rotter, Jerome I., Anderson, Christopher D., Zwart, John-Anker, Niiranen, Teemu J., Fornage, Myriam, Liaw, Yung-Po, Seshadri, Sudha, Fernández-Cadenas, Israel, Walters, Robin G., Ruff, Christian T., Owolabi, Mayowa O., Huffman, Jennifer E., Milani, Lili, Kamatani, Yoichiro, Dichgans, Martin, and Debette, Stephanie

Published
2022
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45. Pharmacogenomics of Coronary Artery Response to Intravenous Gamma Globulin in Kawasaki Disease

Author

Shrestha, Sadeep, primary, Wiener, Howard W, additional, Chowdhury, Sabrina, additional, Kajimoto, Hidemi, additional, Srinivasasainagendra, Vinodh, additional, Mamaeva, Olga A, additional, Brahmbhatt, Ujval N, additional, Ledee, Dolena, additional, Lau, Yung, additional, Padilla, Luz A, additional, Chen, Jake, additional, Dahdah, Nagib, additional, Tiwari, Hemant K, additional, and Portman, Michael A, additional

Published
2024
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46. Pharmacogenomics of intravenous immunoglobulin response in Kawasaki disease

Author

Shrestha, Sadeep, primary, Wiener, Howard W., additional, Kajimoto, Hidemi, additional, Srinivasasainagendra, Vinodh, additional, Ledee, Dolena, additional, Chowdhury, Sabrina, additional, Cui, Jinhong, additional, Chen, Jake Y., additional, Beckley, Mikayla A, additional, Padilla, Luz A., additional, Dahdah, Nagib, additional, Tiwari, Hemant K., additional, and Portman, Michael A., additional

Published
2024
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47. Clinical and neuroimaging factors associated with 30-day fatality among indigenous West Africans with spontaneous intracerebral hemorrhage

Author

Komolafe, Morenikeji A., primary, Sunmonu, Taofiki, additional, Akinyemi, Joshua, additional, Sarfo, Fred S., additional, Akpalu, Albert, additional, Wahab, Kolawole, additional, Obiako, Reginald, additional, Owolabi, Lukman, additional, Osaigbovo, Godwin O., additional, Ogbole, Godwin, additional, Tiwari, Hemant K., additional, Jenkins, Carolyn, additional, Lackland, Daniel T., additional, Fakunle, Adekunle G., additional, Uvere, Ezinne, additional, Akpa, Onoja, additional, Dambatta, Hamisu A., additional, Akpalu, Josephine, additional, Onasanya, Akinola, additional, Olaleye, Adeniji, additional, Ogah, Okechukwu S., additional, Isah, Sulaiman Y., additional, Fawale, Micheal B., additional, Adebowale, Akintunde, additional, Okekunle, Akinkunmi P., additional, Arnett, Donna, additional, Adeoye, Abiodun M., additional, Agunloye, Atinuke M., additional, Bello, Abiodun H., additional, Aderibigbe, Adeniyi S., additional, Idowu, Ahmed O., additional, Sanusi, Ahmad A., additional, Ogunmodede, Adebimpe, additional, Balogun, Simon A., additional, Egberongbe, Adedeji A., additional, Rotimi, Folorunso T., additional, Fredrick, Adeyemi, additional, Akinnuoye, Andrew O., additional, Adeniyi, Folu A., additional, Calys-Tagoe, Benedict, additional, Adebayo, Philip, additional, Arulogun, Oyedunni, additional, Agbogu-Ike, Obiageli U., additional, Yaria, Joseph, additional, Appiah, Lambert, additional, Ibinaiye, Philip, additional, Singh, Arti, additional, Adeniyi, Sunday, additional, Olalusi, Oladotun, additional, Mande, Aliyu, additional, Balogun, Olayemi, additional, Akinyemi, Rufus, additional, Ovbiagele, Bruce, additional, and Owolabi, Mayowa, additional

Published
2023
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49. Risk Factor Characterization of Ischemic Stroke Subtypes Among West Africans

Author

Sarfo, Fred S., Ovbiagele, Bruce, Akpa, Onoja, Akpalu, Albert, Wahab, Kolawole, Obiako, Reginald, Komolafe, Morenikeji, Owolabi, Lukman, Ogbole, Godwin, Calys-Tagoe, Benedict, Fakunle, Adekunle, Sanni, Taofeek, Mulugeta, Gebregziabher, Abdul, Salaam, Akintunde, Adeseye A., Olowookere, Samuel, Uvere, Ezinne O., Ibinaiye, Philip, Akinyemi, Joshua, Uwanuruochi, Kelechukwu, Olayemi, Balogun, Odunlami, Olufemi A., Abunimye, Esther, Arulogun, Oyedunni, Isah, Suleiman Y., Abubakar, Sani A., Oladimeji, Adebayo, Adebayo, Philip, Shidali, Vincent, Chukwuonye, Innocent I., Akpalu, Josephine, Tito-Ilori, Moyinoluwalogo M., Asowata, Osahon J., Sanya, Emmanuel O., Amusa, Ganiyu, Onyeonoro, Ugochukwu, Ogunmodede, James A., Sule, Abdullateef G., Akisanya, Cynthia, Mensah, Yaw, Oyinloye, Olalekan I., Appiah, Lambert, Agunloye, Atinuke M., Osaigbovo, Godwin O., Olabinri, Eunice, Kolo, Philip M., Okeke, Obiora, Adeoye, Abiodun M., Ajose, Olabamiji, Jenkins, Carolyn, Lackland, Daniel T., Egberongbe, Adedeji A., Adeniji, Olaleye, Ohifemen Adeleye, Osimhiarherhuo, Tiwari, Hemant K., Arnett, Donna, Laryea, Ruth Y., Olunuga, Taiwo, Akinwande, Kazeem S., Imoh, Lucius, Ogah, Okechukwu S., Melikam, Ezinne S., Adebolaji, Adeyemo, Oguike, Wisdom, Ogunronbi, Olumayowa, Adeniyi, Wasiu, Olugbo, Obiabo Y., Bello, Abiodun H., Ohagwu, Kenneth A., Ogunjimi, Luqman, Agyekum, Francis, Iheonye, Henry, Adesina, Julius, Diala, Samuel, Dambatta, Hamisu A., Ikubor, Joyce, Singh, Arti, Adamu, Sheila, Obese, Vida, Adusei, Nathaniel, Owusu, Dorcas, Ampofo, Michael, Tagge, Raelle, Efidi, Richard, Fawale, Bimbo, Yaria, Joseph, Akinyemi, Rufus, and Owolabi, Mayowa

Published
2021
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50. Linkage and association analysis of obesity traits reveals novel loci and interactions with dietary n-3 fatty acids in an Alaska Native (Yup’ik) population

Author

Vaughan, Laura Kelly, Wiener, Howard W, Aslibekyan, Stella, Allison, David B, Havel, Peter J, Stanhope, Kimber L, O’Brien, Diane M, Hopkins, Scarlett E, Lemas, Dominick J, Boyer, Bert B, and Tiwari, Hemant K

Subjects
Biomedical and Clinical Sciences, Nutrition and Dietetics, Clinical Research, Human Genome, Obesity, American Indian or Alaska Native, Prevention, Genetics, Nutrition, 2.1 Biological and endogenous factors, Aetiology, Stroke, Cancer, Cardiovascular, Oral and gastrointestinal, Metabolic and endocrine, Adult, Alaska, Anthropometry, Body Composition, Computational Biology, Cross-Sectional Studies, Diet, Fatty Acids, Omega-3, Female, Genetic Linkage, Genome, Human, Humans, Inuit, Male, Polymorphism, Single Nucleotide, Waist Circumference, Alaska Native, Linkage, n-3 fatty acids, Clinical Sciences, Endocrinology & Metabolism, Clinical sciences
Abstract

ObjectiveTo identify novel genetic markers of obesity-related traits and to identify gene-diet interactions with n-3 polyunsaturated fatty acid (n-3 PUFA) intake in Yup'ik people.Material and methodsWe measured body composition, plasma adipokines and ghrelin in 982 participants enrolled in the Center for Alaska Native Health Research (CANHR) Study. We conducted a genome-wide SNP linkage scan and targeted association analysis, fitting additional models to investigate putative gene-diet interactions. Finally, we performed bioinformatic analysis to uncover likely candidate genes within the identified linkage peaks.ResultsWe observed evidence of linkage for all obesity-related traits, replicating previous results and identifying novel regions of interest for adiponectin (10q26.13-2) and thigh circumference (8q21.11-13). Bioinformatic analysis revealed DOCK1, PTPRE (10q26.13-2) and FABP4 (8q21.11-13) as putative candidate genes in the newly identified regions. Targeted SNP analysis under the linkage peaks identified associations between three SNPs and obesity-related traits: rs1007750 on chromosome 8 and thigh circumference (P=0.0005), rs878953 on chromosome 5 and thigh skinfold (P=0.0004), and rs1596854 on chromosome 11 for waist circumference (P=0.0003). Finally, we showed that n-3 PUFA modified the association between obesity related traits and two additional variants (rs2048417 on chromosome 3 for adiponectin, P for interaction=0.0006 and rs730414 on chromosome 11 for percentage body fat, P for interaction=0.0004).ConclusionsThis study presents evidence of novel genomic regions and gene-diet interactions that may contribute to the pathophysiology of obesity-related traits among Yup'ik people.

Published
2015

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