Search

Your search keyword '"Burt, Amber A."' showing total 334 results
Start Over Author "Burt, Amber A."
334 results on '"Burt, Amber A."'

3. Epigenetic associations with neonatal age in infants born very preterm, particularly among genes involved in neurodevelopment

Author

Hodge, Kenyaita M., Burt, Amber A., Camerota, Marie, Carter, Brian S., Check, Jennifer, Conneely, Karen N., Helderman, Jennifer, Hofheimer, Julie A., Hüls, Anke, McGowan, Elisabeth C., Neal, Charles R., Pastyrnak, Steven L., Smith, Lynne M., DellaGrotta, Sheri A., Dansereau, Lynne M., O’Shea, T. Michael, Marsit, Carmen J., Lester, Barry M., and Everson, Todd M.

Published
2024
Full Text
View/download PDF

7. Prenatal Pyrethroid Exposure, Placental Gene Network Modules, and Neonatal Neurobehavior

Author

Wang, Yewei, primary, Hermetz, Karen, additional, Burt, Amber, additional, Lesseur, Corina, additional, panuwet, Parinya, additional, Fiedler, Nancy, additional, Prapamontol, Tippawan, additional, suttiwan, panrapee, additional, Sittiwang, Supattra, additional, Naksen, Warangkana, additional, Barr, Dana, additional, Hao, Ke, additional, Chen, Jia, additional, and Marsit, Carmen, additional

Published
2024
Full Text
View/download PDF

8. Protein-coding variants implicate novel genes related to lipid homeostasis contributing to body-fat distribution

Author

Justice, Anne E, Karaderi, Tugce, Highland, Heather M, Young, Kristin L, Graff, Mariaelisa, Lu, Yingchang, Turcot, Valérie, Auer, Paul L, Fine, Rebecca S, Guo, Xiuqing, Schurmann, Claudia, Lempradl, Adelheid, Marouli, Eirini, Mahajan, Anubha, Winkler, Thomas W, Locke, Adam E, Medina-Gomez, Carolina, Esko, Tõnu, Vedantam, Sailaja, Giri, Ayush, Lo, Ken Sin, Alfred, Tamuno, Mudgal, Poorva, Ng, Maggie CY, Heard-Costa, Nancy L, Feitosa, Mary F, Manning, Alisa K, Willems, Sara M, Sivapalaratnam, Suthesh, Abecasis, Goncalo, Alam, Dewan S, Allison, Matthew, Amouyel, Philippe, Arzumanyan, Zorayr, Balkau, Beverley, Bastarache, Lisa, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bork-Jensen, Jette, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Broer, Linda, Burt, Amber A, Butterworth, Adam S, Caulfield, Mark J, Cesana, Giancarlo, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der Ida, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Collins, Francis S, Cook, James P, Cox, Amanda J, Crosslin, David S, Danesh, John, de Bakker, Paul IW, Denus, Simon de, Mutsert, Renée de, Dedoussis, George, Demerath, Ellen W, Dennis, Joe G, Denny, Josh C, Di Angelantonio, Emanuele, Dörr, Marcus, Drenos, Fotios, Dubé, Marie-Pierre, Dunning, Alison M, Easton, Douglas F, Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C, Fornage, Myriam, Fox, Caroline S, Franks, Paul W, Friedrich, Nele, Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Giedraitis, Vilmantas, Girotto, Giorgia, Gorski, Mathias, Grallert, Harald, Grarup, Niels, Grove, Megan L, Gustafsson, Stefan, Haessler, Jeff, Hansen, Torben, and Hattersley, Andrew T

Subjects
Clinical Research, Obesity, Genetics, Nutrition, Prevention, Biotechnology, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Metabolic and endocrine, Cardiovascular, Animals, Body Fat Distribution, Body Mass Index, Case-Control Studies, Drosophila, Exome, Female, Gene Frequency, Genetic Predisposition to Disease, Genetic Variation, Genome-Wide Association Study, Homeostasis, Humans, Lipids, Male, Proteins, Risk Factors, Waist-Hip Ratio, CHD Exome+ Consortium, Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, InterAct, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Body-fat distribution is a risk factor for adverse cardiovascular health consequences. We analyzed the association of body-fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, with 228,985 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries (discovery) and 132,177 European-ancestry individuals (validation). We identified 15 common (minor allele frequency, MAF ≥5%) and nine low-frequency or rare (MAF

Published
2019

11. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity.

Author

Turcot, Valérie, Lu, Yingchang, Highland, Heather M, Schurmann, Claudia, Justice, Anne E, Fine, Rebecca S, Bradfield, Jonathan P, Esko, Tõnu, Giri, Ayush, Graff, Mariaelisa, Guo, Xiuqing, Hendricks, Audrey E, Karaderi, Tugce, Lempradl, Adelheid, Locke, Adam E, Mahajan, Anubha, Marouli, Eirini, Sivapalaratnam, Suthesh, Young, Kristin L, Alfred, Tamuno, Feitosa, Mary F, Masca, Nicholas GD, Manning, Alisa K, Medina-Gomez, Carolina, Mudgal, Poorva, Ng, Maggie CY, Reiner, Alex P, Vedantam, Sailaja, Willems, Sara M, Winkler, Thomas W, Abecasis, Gonçalo, Aben, Katja K, Alam, Dewan S, Alharthi, Sameer E, Allison, Matthew, Amouyel, Philippe, Asselbergs, Folkert W, Auer, Paul L, Balkau, Beverley, Bang, Lia E, Barroso, Inês, Bastarache, Lisa, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bork-Jensen, Jette, Bots, Michiel L, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H, Broer, Linda, Brumat, Marco, Burt, Amber A, Butterworth, Adam S, Campbell, Peter T, Cappellani, Stefania, Carey, David J, Catamo, Eulalia, Caulfield, Mark J, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der I, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Cocca, Massimiliano, Collins, Francis S, Cook, James P, Corley, Janie, Corominas Galbany, Jordi, Cox, Amanda J, Crosslin, David S, Cuellar-Partida, Gabriel, D'Eustacchio, Angela, Danesh, John, Davies, Gail, Bakker, Paul IW, Groot, Mark CH, Mutsert, Renée, Deary, Ian J, Dedoussis, George, Demerath, Ellen W, Heijer, Martin, Hollander, Anneke I, Ruijter, Hester M, Dennis, Joe G, Denny, Josh C, Di Angelantonio, Emanuele, Drenos, Fotios, Du, Mengmeng, Dubé, Marie-Pierre, Dunning, Alison M, and Easton, Douglas F

Subjects
CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Understanding Society Scientific Group, Nutrition, Obesity, Developmental Biology, Medical and Health Sciences, Biological Sciences
Abstract

In the version of this article originally published, one of the two authors with the name Wei Zhao was omitted from the author list and the affiliations for both authors were assigned to the single Wei Zhao in the author list. In addition, the ORCID for Wei Zhao (Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA) was incorrectly assigned to author Wei Zhou. The errors have been corrected in the HTML and PDF versions of the article.

Published
2018

12. Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author

Turcot, Valérie, Lu, Yingchang, Highland, Heather M, Schurmann, Claudia, Justice, Anne E, Fine, Rebecca S, Bradfield, Jonathan P, Esko, Tõnu, Giri, Ayush, Graff, Mariaelisa, Guo, Xiuqing, Hendricks, Audrey E, Karaderi, Tugce, Lempradl, Adelheid, Locke, Adam E, Mahajan, Anubha, Marouli, Eirini, Sivapalaratnam, Suthesh, Young, Kristin L, Alfred, Tamuno, Feitosa, Mary F, Masca, Nicholas GD, Manning, Alisa K, Medina-Gomez, Carolina, Mudgal, Poorva, Ng, Maggie CY, Reiner, Alex P, Vedantam, Sailaja, Willems, Sara M, Winkler, Thomas W, Abecasis, Gonçalo, Aben, Katja K, Alam, Dewan S, Alharthi, Sameer E, Allison, Matthew, Amouyel, Philippe, Asselbergs, Folkert W, Auer, Paul L, Balkau, Beverley, Bang, Lia E, Barroso, Inês, Bastarache, Lisa, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bork-Jensen, Jette, Bots, Michiel L, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H, Broer, Linda, Brumat, Marco, Burt, Amber A, Butterworth, Adam S, Campbell, Peter T, Cappellani, Stefania, Carey, David J, Catamo, Eulalia, Caulfield, Mark J, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der I, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Cocca, Massimiliano, Collins, Francis S, Cook, James P, Corley, Janie, Corominas Galbany, Jordi, Cox, Amanda J, Crosslin, David S, Cuellar-Partida, Gabriel, D’Eustacchio, Angela, Danesh, John, Davies, Gail, Bakker, Paul IW, Groot, Mark CH, Mutsert, Renée, Deary, Ian J, Dedoussis, George, Demerath, Ellen W, Heijer, Martin, Hollander, Anneke I, Ruijter, Hester M, Dennis, Joe G, Denny, Josh C, Di Angelantonio, Emanuele, Drenos, Fotios, Du, Mengmeng, Dubé, Marie-Pierre, Dunning, Alison M, and Easton, Douglas F

Subjects
Genetics, Biotechnology, Nutrition, Obesity, Human Genome, Aetiology, 2.1 Biological and endogenous factors, Cancer, Stroke, Metabolic and endocrine, Cardiovascular, Oral and gastrointestinal, Adult, Animals, Body Mass Index, Drosophila, Energy Intake, Energy Metabolism, Female, Gene Frequency, Genetic Variation, Humans, Male, Proteins, Syndrome, CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, MAGIC Investigators, Understanding Society Scientific Group, Biological Sciences, Medical and Health Sciences, Developmental Biology
Abstract

Genome-wide association studies (GWAS) have identified >250 loci for body mass index (BMI), implicating pathways related to neuronal biology. Most GWAS loci represent clusters of common, noncoding variants from which pinpointing causal genes remains challenging. Here we combined data from 718,734 individuals to discover rare and low-frequency (minor allele frequency (MAF) < 5%) coding variants associated with BMI. We identified 14 coding variants in 13 genes, of which 8 variants were in genes (ZBTB7B, ACHE, RAPGEF3, RAB21, ZFHX3, ENTPD6, ZFR2 and ZNF169) newly implicated in human obesity, 2 variants were in genes (MC4R and KSR2) previously observed to be mutated in extreme obesity and 2 variants were in GIPR. The effect sizes of rare variants are ~10 times larger than those of common variants, with the largest effect observed in carriers of an MC4R mutation introducing a stop codon (p.Tyr35Ter, MAF = 0.01%), who weighed ~7 kg more than non-carriers. Pathway analyses based on the variants associated with BMI confirm enrichment of neuronal genes and provide new evidence for adipocyte and energy expenditure biology, widening the potential of genetically supported therapeutic targets in obesity.

Published
2018

13. Sequencing of sporadic Attention‐Deficit Hyperactivity Disorder (ADHD) identifies novel and potentially pathogenic de novo variants and excludes overlap with genes associated with autism spectrum disorder

Author

Kim, Daniel Seung, Burt, Amber A, Ranchalis, Jane E, Wilmot, Beth, Smith, Joshua D, Patterson, Karynne E, Coe, Bradley P, Li, Yatong K, Bamshad, Michael J, Nikolas, Molly, Eichler, Evan E, Swanson, James M, Nigg, Joel T, Nickerson, Deborah A, Jarvik, Gail P, and Genomics, on behalf of the University of Washington Center for Mendelian

Subjects
Biological Sciences, Bioinformatics and Computational Biology, Genetics, Prevention, Neurosciences, Attention Deficit Hyperactivity Disorder (ADHD), Intellectual and Developmental Disabilities (IDD), Brain Disorders, Pediatric, Human Genome, Mental Health, Autism, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Mental health, Adult, Attention Deficit Disorder with Hyperactivity, Autism Spectrum Disorder, Biomarkers, Child, Exome, Female, Genetic Predisposition to Disease, High-Throughput Nucleotide Sequencing, Humans, Male, Mutation, Missense, Phenotype, attention deficit hyperactivity disorder, exome sequencing, molecular inversion probe (MIP) sequencing, sporadic ADHD, autism spectrum disorder, intellectual disability, University of Washington Center for Mendelian Genomics, Clinical Sciences, Clinical sciences
Abstract

Attention-Deficit Hyperactivity Disorder (ADHD) has high heritability; however, studies of common variation account for

Published
2017

14. Rare and low-frequency coding variants alter human adult height

Author

Marouli, Eirini, Graff, Mariaelisa, Medina-Gomez, Carolina, Lo, Ken Sin, Wood, Andrew R, Kjaer, Troels R, Fine, Rebecca S, Lu, Yingchang, Schurmann, Claudia, Highland, Heather M, Rüeger, Sina, Thorleifsson, Gudmar, Justice, Anne E, Lamparter, David, Stirrups, Kathleen E, Turcot, Valérie, Young, Kristin L, Winkler, Thomas W, Esko, Tõnu, Karaderi, Tugce, Locke, Adam E, Masca, Nicholas GD, Ng, Maggie CY, Mudgal, Poorva, Rivas, Manuel A, Vedantam, Sailaja, Mahajan, Anubha, Guo, Xiuqing, Abecasis, Goncalo, Aben, Katja K, Adair, Linda S, Alam, Dewan S, Albrecht, Eva, Allin, Kristine H, Allison, Matthew, Amouyel, Philippe, Appel, Emil V, Arveiler, Dominique, Asselbergs, Folkert W, Auer, Paul L, Balkau, Beverley, Banas, Bernhard, Bang, Lia E, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F, Blüher, Matthias, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A, Bonnycastle, Lori L, Bork-Jensen, Jette, Bots, Michiel L, Bottinger, Erwin P, Bowden, Donald W, Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H, Broer, Linda, Burt, Amber A, Butterworth, Adam S, Carey, David J, Caulfield, Mark J, Chambers, John C, Chasman, Daniel I, Chen, Yii-Der Ida, Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y, Cocca, Massimiliano, Collins, Francis S, Cook, James P, Corley, Janie, Galbany, Jordi Corominas, Cox, Amanda J, Cuellar-Partida, Gabriel, Danesh, John, Davies, Gail, de Bakker, Paul IW, de Borst, Gert J, de Denus, Simon, de Groot, Mark CH, de Mutsert, Renée, Deary, Ian J, Dedoussis, George, Demerath, Ellen W, den Hollander, Anneke I, Dennis, Joe G, Di Angelantonio, Emanuele, Drenos, Fotios, Du, Mengmeng, Dunning, Alison M, Easton, Douglas F, Ebeling, Tapani, Edwards, Todd L, Ellinor, Patrick T, Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, and Faul, Jessica D

Subjects
Human Genome, Genetics, Aetiology, 2.1 Biological and endogenous factors, ADAMTS Proteins, Adult, Alleles, Body Height, Cell Adhesion Molecules, Female, Gene Frequency, Genetic Variation, Genome, Human, Glycoproteins, Glycosaminoglycans, Hedgehog Proteins, Humans, Intercellular Signaling Peptides and Proteins, Interferon Regulatory Factors, Interleukin-11 Receptor alpha Subunit, Male, Multifactorial Inheritance, NADPH Oxidase 4, NADPH Oxidases, Phenotype, Pregnancy-Associated Plasma Protein-A, Procollagen N-Endopeptidase, Proteoglycans, Proteolysis, Receptors, Androgen, Somatomedins, EPIC-InterAct Consortium, CHD Exome+ Consortium, ExomeBP Consortium, T2D-Genes Consortium, GoT2D Genes Consortium, Global Lipids Genetics Consortium, ReproGen Consortium, MAGIC Investigators, General Science & Technology
Abstract

Height is a highly heritable, classic polygenic trait with approximately 700 common associated variants identified through genome-wide association studies so far. Here, we report 83 height-associated coding variants with lower minor-allele frequencies (in the range of 0.1-4.8%) and effects of up to 2 centimetres per allele (such as those in IHH, STC2, AR and CRISPLD2), greater than ten times the average effect of common variants. In functional follow-up studies, rare height-increasing alleles of STC2 (giving an increase of 1-2 centimetres per allele) compromised proteolytic inhibition of PAPP-A and increased cleavage of IGFBP-4 in vitro, resulting in higher bioavailability of insulin-like growth factors. These 83 height-associated variants overlap genes that are mutated in monogenic growth disorders and highlight new biological candidates (such as ADAMTS3, IL11RA and NOX4) and pathways (such as proteoglycan and glycosaminoglycan synthesis) involved in growth. Our results demonstrate that sufficiently large sample sizes can uncover rare and low-frequency variants of moderate-to-large effect associated with polygenic human phenotypes, and that these variants implicate relevant genes and pathways.

Published
2017

15. Epigenome-wide analysis identifies genes and pathways linked to acoustic cry variation in preterm infants

Author

Aghagoli, Ghazal, Sheinkopf, Stephen J., Everson, Todd M., Marsit, Carmen J., Lee, Hannah, Burt, Amber A., Carter, Brian S., Helderman, Jennifer B., Hofheimer, Julie A., McGowan, Elisabeth C., Neal, Charles R., O’Shea, T. Michael, Pastyrnak, Steven L., Smith, Lynne M., Soliman, Antoine, Dansereau, Lynne M., DellaGrotta, Sheri A., Padbury, James F., and Lester, Barry M.

Published
2021
Full Text
View/download PDF

16. Association Between Absolute Neutrophil Count and Variation at TCIRG1: The NHLBI Exome Sequencing Project

Author

Rosenthal, Elisabeth A, Makaryan, Vahagn, Burt, Amber A, Crosslin, David R, Kim, Daniel Seung, Smith, Joshua D, Nickerson, Deborah A, Reiner, Alex P, Rich, Stephen S, Jackson, Rebecca D, Ganesh, Santhi K, Polfus, Linda M, Qi, Lihong, Dale, David C, University of Washington, Center for Mendelian Genomics, and Jarvik, Gail P

Subjects
Biological Sciences, Genetics, Atherosclerosis, Heart Disease, Human Genome, Cardiovascular, Prevention, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Good Health and Well Being, Adult, Aged, Aged, 80 and over, Alleles, Cohort Studies, Female, Gene Frequency, Genotype, High-Throughput Nucleotide Sequencing, Humans, Leukocyte Count, Male, Middle Aged, Mutation, Missense, National Heart, Lung, and Blood Institute (U.S.), Neutropenia, Neutrophils, Sequence Analysis, DNA, United States, Vacuolar Proton-Translocating ATPases, neutropenia, absolute neutrophil count, rare variant replication, next-generation sequence data, University of Washington, Center for Mendelian Genomics, Public Health and Health Services, Epidemiology
Abstract

Neutrophils are a key component of innate immunity. Individuals with low neutrophil count are susceptible to frequent infections. Linkage and association between congenital neutropenia and a single rare missense variant in TCIRG1 have been reported in a single family. Here, we report on nine rare missense variants at evolutionarily conserved sites in TCIRG1 that are associated with lower absolute neutrophil count (ANC; p = 0.005) in 1,058 participants from three cohorts: Atherosclerosis Risk in Communities (ARIC), Coronary Artery Risk Development in Young Adults (CARDIA), and Jackson Heart Study (JHS) of the NHLBI Grand Opportunity Exome Sequencing Project (GO ESP). These results validate the effects of TCIRG1 coding variation on ANC and suggest that this gene may be associated with a spectrum of mild to severe effects on ANC.

Published
2016

17. Large-Scale Exome-wide Association Analysis Identifies Loci for White Blood Cell Traits and Pleiotropy with Immune-Mediated Diseases

Author

Tajuddin, Salman M, Schick, Ursula M, Eicher, John D, Chami, Nathalie, Giri, Ayush, Brody, Jennifer A, Hill, W David, Kacprowski, Tim, Li, Jin, Lyytikäinen, Leo-Pekka, Manichaikul, Ani, Mihailov, Evelin, O’Donoghue, Michelle L, Pankratz, Nathan, Pazoki, Raha, Polfus, Linda M, Smith, Albert Vernon, Schurmann, Claudia, Vacchi-Suzzi, Caterina, Waterworth, Dawn M, Evangelou, Evangelos, Yanek, Lisa R, Burt, Amber, Chen, Ming-Huei, van Rooij, Frank JA, Floyd, James S, Greinacher, Andreas, Harris, Tamara B, Highland, Heather M, Lange, Leslie A, Liu, Yongmei, Mägi, Reedik, Nalls, Mike A, Mathias, Rasika A, Nickerson, Deborah A, Nikus, Kjell, Starr, John M, Tardif, Jean-Claude, Tzoulaki, Ioanna, Edwards, Digna R Velez, Wallentin, Lars, Bartz, Traci M, Becker, Lewis C, Denny, Joshua C, Raffield, Laura M, Rioux, John D, Friedrich, Nele, Fornage, Myriam, Gao, He, Hirschhorn, Joel N, Liewald, David CM, Rich, Stephen S, Uitterlinden, Andre, Bastarache, Lisa, Becker, Diane M, Boerwinkle, Eric, de Denus, Simon, Bottinger, Erwin P, Hayward, Caroline, Hofman, Albert, Homuth, Georg, Lange, Ethan, Launer, Lenore J, Lehtimäki, Terho, Lu, Yingchang, Metspalu, Andres, O’Donnell, Chris J, Quarells, Rakale C, Richard, Melissa, Torstenson, Eric S, Taylor, Kent D, Vergnaud, Anne-Claire, Zonderman, Alan B, Crosslin, David R, Deary, Ian J, Dörr, Marcus, Elliott, Paul, Evans, Michele K, Gudnason, Vilmundur, Kähönen, Mika, Psaty, Bruce M, Rotter, Jerome I, Slater, Andrew J, Dehghan, Abbas, White, Harvey D, Ganesh, Santhi K, Loos, Ruth JF, Esko, Tõnu, Faraday, Nauder, Wilson, James G, Cushman, Mary, Johnson, Andrew D, Edwards, Todd L, Zakai, Neil A, Lettre, Guillaume, Reiner, Alex P, and Auer, Paul L

Subjects
Biological Sciences, Biomedical and Clinical Sciences, Genetics, Immunology, Stem Cell Research, Human Genome, Stem Cell Research - Nonembryonic - Non-Human, Autoimmune Disease, Hematology, 2.1 Biological and endogenous factors, 1.1 Normal biological development and functioning, Underpinning research, Aetiology, Inflammatory and immune system, Blood Cell Count, Exome, Genetic Loci, Genetic Pleiotropy, Genome-Wide Association Study, Humans, Immune System Diseases, Leukocytes, Quality Control, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

White blood cells play diverse roles in innate and adaptive immunity. Genetic association analyses of phenotypic variation in circulating white blood cell (WBC) counts from large samples of otherwise healthy individuals can provide insights into genes and biologic pathways involved in production, differentiation, or clearance of particular WBC lineages (myeloid, lymphoid) and also potentially inform the genetic basis of autoimmune, allergic, and blood diseases. We performed an exome array-based meta-analysis of total WBC and subtype counts (neutrophils, monocytes, lymphocytes, basophils, and eosinophils) in a multi-ancestry discovery and replication sample of ∼157,622 individuals from 25 studies. We identified 16 common variants (8 of which were coding variants) associated with one or more WBC traits, the majority of which are pleiotropically associated with autoimmune diseases. Based on functional annotation, these loci included genes encoding surface markers of myeloid, lymphoid, or hematopoietic stem cell differentiation (CD69, CD33, CD87), transcription factors regulating lineage specification during hematopoiesis (ASXL1, IRF8, IKZF1, JMJD1C, ETS2-PSMG1), and molecules involved in neutrophil clearance/apoptosis (C10orf54, LTA), adhesion (TNXB), or centrosome and microtubule structure/function (KIF9, TUBD1). Together with recent reports of somatic ASXL1 mutations among individuals with idiopathic cytopenias or clonal hematopoiesis of undetermined significance, the identification of a common regulatory 3' UTR variant of ASXL1 suggests that both germline and somatic ASXL1 mutations contribute to lower blood counts in otherwise asymptomatic individuals. These association results shed light on genetic mechanisms that regulate circulating WBC counts and suggest a prominent shared genetic architecture with inflammatory and autoimmune diseases.

Published
2016

18. Platelet-Related Variants Identified by Exomechip Meta-analysis in 157,293 Individuals

Author

Eicher, John D, Chami, Nathalie, Kacprowski, Tim, Nomura, Akihiro, Chen, Ming-Huei, Yanek, Lisa R, Tajuddin, Salman M, Schick, Ursula M, Slater, Andrew J, Pankratz, Nathan, Polfus, Linda, Schurmann, Claudia, Giri, Ayush, Brody, Jennifer A, Lange, Leslie A, Manichaikul, Ani, Hill, W David, Pazoki, Raha, Elliot, Paul, Evangelou, Evangelos, Tzoulaki, Ioanna, Gao, He, Vergnaud, Anne-Claire, Mathias, Rasika A, Becker, Diane M, Becker, Lewis C, Burt, Amber, Crosslin, David R, Lyytikäinen, Leo-Pekka, Nikus, Kjell, Hernesniemi, Jussi, Kähönen, Mika, Raitoharju, Emma, Mononen, Nina, Raitakari, Olli T, Lehtimäki, Terho, Cushman, Mary, Zakai, Neil A, Nickerson, Deborah A, Raffield, Laura M, Quarells, Rakale, Willer, Cristen J, Peloso, Gina M, Abecasis, Goncalo R, Liu, Dajiang J, Consortium, Global Lipids Genetics, Deloukas, Panos, Samani, Nilesh J, Schunkert, Heribert, Erdmann, Jeanette, Consortium, CARDIoGRAM Exome, Consortium, Myocardial Infarction Genetics, Fornage, Myriam, Richard, Melissa, Tardif, Jean-Claude, Rioux, John D, Dube, Marie-Pierre, de Denus, Simon, Lu, Yingchang, Bottinger, Erwin P, Loos, Ruth JF, Smith, Albert Vernon, Harris, Tamara B, Launer, Lenore J, Gudnason, Vilmundur, Edwards, Digna R Velez, Torstenson, Eric S, Liu, Yongmei, Tracy, Russell P, Rotter, Jerome I, Rich, Stephen S, Highland, Heather M, Boerwinkle, Eric, Li, Jin, Lange, Ethan, Wilson, James G, Mihailov, Evelin, Mägi, Reedik, Hirschhorn, Joel, Metspalu, Andres, Esko, Tõnu, Vacchi-Suzzi, Caterina, Nalls, Mike A, Zonderman, Alan B, Evans, Michele K, Engström, Gunnar, Orho-Melander, Marju, Melander, Olle, O’Donoghue, Michelle L, Waterworth, Dawn M, Wallentin, Lars, White, Harvey D, Floyd, James S, Bartz, Traci M, Rice, Kenneth M, Psaty, Bruce M, Starr, JM, Liewald, David CM, Hayward, Caroline, and Deary, Ian J

Subjects
Genetics, Cardiovascular, Hematology, 1.1 Normal biological development and functioning, Underpinning research, Blood, Blood Platelets, Exome, Female, Genetic Variation, Genome-Wide Association Study, Humans, Male, Mean Platelet Volume, Platelet Count, Global Lipids Genetics Consortium, CARDIoGRAM Exome Consortium, Myocardial Infarction Genetics Consortium, Biological Sciences, Medical and Health Sciences, Genetics & Heredity
Abstract

Platelet production, maintenance, and clearance are tightly controlled processes indicative of platelets' important roles in hemostasis and thrombosis. Platelets are common targets for primary and secondary prevention of several conditions. They are monitored clinically by complete blood counts, specifically with measurements of platelet count (PLT) and mean platelet volume (MPV). Identifying genetic effects on PLT and MPV can provide mechanistic insights into platelet biology and their role in disease. Therefore, we formed the Blood Cell Consortium (BCX) to perform a large-scale meta-analysis of Exomechip association results for PLT and MPV in 157,293 and 57,617 individuals, respectively. Using the low-frequency/rare coding variant-enriched Exomechip genotyping array, we sought to identify genetic variants associated with PLT and MPV. In addition to confirming 47 known PLT and 20 known MPV associations, we identified 32 PLT and 18 MPV associations not previously observed in the literature across the allele frequency spectrum, including rare large effect (FCER1A), low-frequency (IQGAP2, MAP1A, LY75), and common (ZMIZ2, SMG6, PEAR1, ARFGAP3/PACSIN2) variants. Several variants associated with PLT/MPV (PEAR1, MRVI1, PTGES3) were also associated with platelet reactivity. In concurrent BCX analyses, there was overlap of platelet-associated variants with red (MAP1A, TMPRSS6, ZMIZ2) and white (PEAR1, ZMIZ2, LY75) blood cell traits, suggesting common regulatory pathways with shared genetic architecture among these hematopoietic lineages. Our large-scale Exomechip analyses identified previously undocumented associations with platelet traits and further indicate that several complex quantitative hematological, lipid, and cardiovascular traits share genetic factors.

Published
2016

19. Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits

Author

Chami, Nathalie, Chen, Ming-Huei, Slater, Andrew J, Eicher, John D, Evangelou, Evangelos, Tajuddin, Salman M, Love-Gregory, Latisha, Kacprowski, Tim, Schick, Ursula M, Nomura, Akihiro, Giri, Ayush, Lessard, Samuel, Brody, Jennifer A, Schurmann, Claudia, Pankratz, Nathan, Yanek, Lisa R, Manichaikul, Ani, Pazoki, Raha, Mihailov, Evelin, Hill, W David, Raffield, Laura M, Burt, Amber, Bartz, Traci M, Becker, Diane M, Becker, Lewis C, Boerwinkle, Eric, Bork-Jensen, Jette, Bottinger, Erwin P, O’Donoghue, Michelle L, Crosslin, David R, de Denus, Simon, Dubé, Marie-Pierre, Elliott, Paul, Engström, Gunnar, Evans, Michele K, Floyd, James S, Fornage, Myriam, Gao, He, Greinacher, Andreas, Gudnason, Vilmundur, Hansen, Torben, Harris, Tamara B, Hayward, Caroline, Hernesniemi, Jussi, Highland, Heather M, Hirschhorn, Joel N, Hofman, Albert, Irvin, Marguerite R, Kähönen, Mika, Lange, Ethan, Launer, Lenore J, Lehtimäki, Terho, Li, Jin, Liewald, David CM, Linneberg, Allan, Liu, Yongmei, Lu, Yingchang, Lyytikäinen, Leo-Pekka, Mägi, Reedik, Mathias, Rasika A, Melander, Olle, Metspalu, Andres, Mononen, Nina, Nalls, Mike A, Nickerson, Deborah A, Nikus, Kjell, O’Donnell, Chris J, Orho-Melander, Marju, Pedersen, Oluf, Petersmann, Astrid, Polfus, Linda, Psaty, Bruce M, Raitakari, Olli T, Raitoharju, Emma, Richard, Melissa, Rice, Kenneth M, Rivadeneira, Fernando, Rotter, Jerome I, Schmidt, Frank, Smith, Albert Vernon, Starr, John M, Taylor, Kent D, Teumer, Alexander, Thuesen, Betina H, Torstenson, Eric S, Tracy, Russell P, Tzoulaki, Ioanna, Zakai, Neil A, Vacchi-Suzzi, Caterina, van Duijn, Cornelia M, van Rooij, Frank JA, Cushman, Mary, Deary, Ian J, Edwards, Digna R Velez, Vergnaud, Anne-Claire, Wallentin, Lars, Waterworth, Dawn M, White, Harvey D, Wilson, James G, and Zonderman, Alan B

Subjects
Epidemiology, Biological Sciences, Health Sciences, Genetics, Rare Diseases, Hematology, Human Genome, Clinical Research, 2.1 Biological and endogenous factors, Aetiology, Black or African American, Allelic Imbalance, Erythrocyte Indices, Erythrocytes, Erythropoiesis, Exome, Gene Frequency, Genetic Pleiotropy, Genetic Variation, Genotype, Hematocrit, Hemoglobins, Humans, Quantitative Trait Loci, Medical and Health Sciences, Genetics & Heredity, Biological sciences, Biomedical and clinical sciences, Health sciences
Abstract

Red blood cell (RBC) traits are important heritable clinical biomarkers and modifiers of disease severity. To identify coding genetic variants associated with these traits, we conducted meta-analyses of seven RBC phenotypes in 130,273 multi-ethnic individuals from studies genotyped on an exome array. After conditional analyses and replication in 27,480 independent individuals, we identified 16 new RBC variants. We found low-frequency missense variants in MAP1A (rs55707100, minor allele frequency [MAF] = 3.3%, p = 2 × 10(-10) for hemoglobin [HGB]) and HNF4A (rs1800961, MAF = 2.4%, p < 3 × 10(-8) for hematocrit [HCT] and HGB). In African Americans, we identified a nonsense variant in CD36 associated with higher RBC distribution width (rs3211938, MAF = 8.7%, p = 7 × 10(-11)) and showed that it is associated with lower CD36 expression and strong allelic imbalance in ex vivo differentiated human erythroblasts. We also identified a rare missense variant in ALAS2 (rs201062903, MAF = 0.2%) associated with lower mean corpuscular volume and mean corpuscular hemoglobin (p < 8 × 10(-9)). Mendelian mutations in ALAS2 are a cause of sideroblastic anemia and erythropoietic protoporphyria. Gene-based testing highlighted three rare missense variants in PKLR, a gene mutated in Mendelian non-spherocytic hemolytic anemia, associated with HGB and HCT (SKAT p < 8 × 10(-7)). These rare, low-frequency, and common RBC variants showed pleiotropy, being also associated with platelet, white blood cell, and lipid traits. Our association results and functional annotation suggest the involvement of new genes in human erythropoiesis. We also confirm that rare and low-frequency variants play a role in the architecture of complex human traits, although their phenotypic effect is generally smaller than originally anticipated.

Published
2016

21. Actionable exomic incidental findings in 6503 participants: challenges of variant classification

Author

Amendola, Laura M, Dorschner, Michael O, Robertson, Peggy D, Salama, Joseph S, Hart, Ragan, Shirts, Brian H, Murray, Mitzi L, Tokita, Mari J, Gallego, Carlos J, Kim, Daniel Seung, Bennett, James T, Crosslin, David R, Ranchalis, Jane, Jones, Kelly L, Rosenthal, Elisabeth A, Jarvik, Ella R, Itsara, Andy, Turner, Emily H, Herman, Daniel S, Schleit, Jennifer, Burt, Amber, Jamal, Seema M, Abrudan, Jenica L, Johnson, Andrew D, Conlin, Laura K, Dulik, Matthew C, Santani, Avni, Metterville, Danielle R, Kelly, Melissa, Foreman, Ann Katherine M, Lee, Kristy, Taylor, Kent D, Guo, Xiuqing, Crooks, Kristy, Kiedrowski, Lesli A, Raffel, Leslie J, Gordon, Ora, Machini, Kalotina, Desnick, Robert J, Biesecker, Leslie G, Lubitz, Steven A, Mulchandani, Surabhi, Cooper, Greg M, Joffe, Steven, Richards, C Sue, Yang, Yaoping, Rotter, Jerome I, Rich, Stephen S, O’Donnell, Christopher J, Berg, Jonathan S, Spinner, Nancy B, Evans, James P, Fullerton, Stephanie M, Leppig, Kathleen A, Bennett, Robin L, Bird, Thomas, Sybert, Virginia P, Grady, William M, Tabor, Holly K, Kim, Jerry H, Bamshad, Michael J, Wilfond, Benjamin, Motulsky, Arno G, Scott, C Ronald, Pritchard, Colin C, Walsh, Tom D, Burke, Wylie, Raskind, Wendy H, Byers, Peter, Hisama, Fuki M, Rehm, Heidi, Nickerson, Debbie A, and Jarvik, Gail P

Subjects
Biological Sciences, Genetics, Biotechnology, Human Genome, Clinical Research, Good Health and Well Being, Adult, Black People, Exome, Female, Gene Frequency, Genes, Dominant, Genetic Association Studies, Genetic Testing, Genome, Human, Genomics, High-Throughput Nucleotide Sequencing, Humans, Incidental Findings, Male, Phenotype, Polymorphism, Single Nucleotide, White People, Medical and Health Sciences, Bioinformatics
Abstract

Recommendations for laboratories to report incidental findings from genomic tests have stimulated interest in such results. In order to investigate the criteria and processes for assigning the pathogenicity of specific variants and to estimate the frequency of such incidental findings in patients of European and African ancestry, we classified potentially actionable pathogenic single-nucleotide variants (SNVs) in all 4300 European- and 2203 African-ancestry participants sequenced by the NHLBI Exome Sequencing Project (ESP). We considered 112 gene-disease pairs selected by an expert panel as associated with medically actionable genetic disorders that may be undiagnosed in adults. The resulting classifications were compared to classifications from other clinical and research genetic testing laboratories, as well as with in silico pathogenicity scores. Among European-ancestry participants, 30 of 4300 (0.7%) had a pathogenic SNV and six (0.1%) had a disruptive variant that was expected to be pathogenic, whereas 52 (1.2%) had likely pathogenic SNVs. For African-ancestry participants, six of 2203 (0.3%) had a pathogenic SNV and six (0.3%) had an expected pathogenic disruptive variant, whereas 13 (0.6%) had likely pathogenic SNVs. Genomic Evolutionary Rate Profiling mammalian conservation score and the Combined Annotation Dependent Depletion summary score of conservation, substitution, regulation, and other evidence were compared across pathogenicity assignments and appear to have utility in variant classification. This work provides a refined estimate of the burden of adult onset, medically actionable incidental findings expected from exome sequencing, highlights challenges in variant classification, and demonstrates the need for a better curated variant interpretation knowledge base.

Published
2015

22. 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

23. 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, Cardiovascular, Atherosclerosis, Aetiology, 2.1 Biological and endogenous factors, 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

25. A multi‐omic approach identifies an autism spectrum disorder ( ASD ) regulatory complex of functional epimutations in placentas from children born preterm

Author

Freedman, Anastasia N., primary, Clark, Jeliyah, additional, Eaves, Lauren A., additional, Roell, Kyle, additional, Oran, Ali, additional, Koval, Lauren, additional, Rager, Julia, additional, Santos, Hudson P., additional, Kuban, Karl, additional, Joseph, Robert M., additional, Frazier, Jean, additional, Marsit, Carmen J., additional, Burt, Amber A., additional, O'Shea, T. Michael, additional, and Fry, Rebecca C., additional

Published
2023
Full Text
View/download PDF

26. Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Author

Cilleros-Portet, Ariadna, primary, Lesseur, Corina, additional, Mari, Sergi, additional, Cosin-Tomas, Marta, additional, Lozano, Manuel, additional, Irizar, Amaia, additional, Burt, Amber, additional, Garcia-Santisteban, Iraia, additional, Garrido Martin, Diego, additional, Escaramis, Georgia, additional, Hernangomez-Laderas, Alba, additional, Soler-Blasco, Raquel, additional, Breeze, Charles E., additional, Gonzalez-Garcia, Barbara P., additional, Santa-Marina, Loreto, additional, Chen, Jia, additional, Llop, Sabrina, additional, Fernandez, Mariana F., additional, Vrijhed, Martine, additional, Ibarluzea, Jesus, additional, Guxens, Monica, additional, Marsit, Carmen, additional, Bustamante, Mariona, additional, Bilbao, Jose Ramon, additional, and Fernandez-Jimenez, Nora, additional

Published
2023
Full Text
View/download PDF

27. Sex-based differences in placental DNA methylation profiles related to gestational age: an NIH ECHO meta-analysis

Author

Bulka, Catherine M., primary, Everson, Todd M., additional, Burt, Amber A., additional, Marsit, Carmen J., additional, Karagas, Margaret R., additional, Boyle, Kristen E., additional, Niemiec, Sierra, additional, Kechris, Katerina, additional, Davidson, Elizabeth J., additional, Yang, Ivana V., additional, Feinberg, Jason I., additional, Volk, Heather E., additional, Ladd-Acosta, Christine, additional, Breton, Carrie V., additional, O’Shea, T. Michael, additional, and Fry, Rebecca C., additional

Published
2023
Full Text
View/download PDF

28. Placental Transcriptome Variation Associated with Season, Location, and Prenatal Pyrethroid Exposures in the Offspring of Thai Farm-Working Women

Author

Wang, Yewei, primary, Hermetz, Karen, additional, Burt, Amber, additional, Kennedy, Elizabeth, additional, Lesseur, Corina, additional, Panuwet, Parinya, additional, Fiedler, Nancy, additional, Prapamontol, Tippawan, additional, Suttiwan, Panrapee, additional, Naksen, Warangkana, additional, Boyd Barr, Dana, additional, Hao, Ke, additional, Chen, Jia, additional, and Marsit, Carmen J., additional

Published
2023
Full Text
View/download PDF

29. Burden of potentially pathologic copy number variants is higher in children with isolated congenital heart disease and significantly impairs covariate-adjusted transplant-free survival

Author

Kim, Daniel Seung, Kim, Jerry H., Burt, Amber A., Crosslin, David R., Burnham, Nancy, Kim, Cecilia E., McDonald-McGinn, Donna M., Zackai, Elaine H., Nicolson, Susan C., Spray, Thomas L., Stanaway, Ian B., Nickerson, Deborah A., Heagerty, Patrick J., Hakonarson, Hakon, Gaynor, J. William, and Jarvik, Gail P.

Published
2016
Full Text
View/download PDF

30. Potentially causal associations between placental DNA methylation and schizophrenia and other neuropsychiatric disorders

Author

Cilleros-Portet, Ariadna, Lesseur, Corina, Marí, Sergi, Cosin-Tomas, Marta, Lozano, Manuel, Irizar, Amaia, Burt, Amber, García-Santisteban, Iraia, Martín, Diego Garrido, Escaramís, Geòrgia, Hernangomez-Laderas, Alba, Soler-Blasco, Raquel, Breeze, Charles E., Gonzalez-Garcia, Bárbara P., Santa-Marina, Loreto, Chen, Jia, Llop, Sabrina, Fernández, Mariana F., Vrijhed, Martine, Ibarluzea, Jesús, Guxens, Mònica, Marsit, Carmen, Bustamante, Mariona, Bilbao, Jose Ramon, and Fernandez-Jimenez, Nora

Subjects
Article
Abstract

Increasing evidence supports the role of placenta in neurodevelopment and potentially, in the later onset of neuropsychiatric disorders. Recently, methylation quantitative trait loci (mQTL) and interaction QTL (iQTL) maps have proven useful to understand SNP-genome wide association study (GWAS) relationships, otherwise missed by conventional expression QTLs. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation (DNAm). We constructed the first public placentalcis-mQTL database including nearly eight million mQTLs calculated in 368 fetal placenta DNA samples from the INMA project, ran cell type- and gestational age-imQTL models and combined those data with the summary statistics of the largest GWAS on 10 neuropsychiatric disorders using Summary-based Mendelian Randomization (SMR) and colocalization. Finally, we evaluated the influence of the DNAm sites identified on placental gene expression in the RICHS cohort. We found that placentalcis-mQTLs are highly enriched in placenta-specific active chromatin regions, and useful to map the etiology of neuropsychiatric disorders at prenatal stages. Specifically, part of the genetic burden for schizophrenia, bipolar disorder and major depressive disorder confers risk through placental DNAm. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, regional pleiotropic methylation signals associated to the same disorder, and cell type- imQTLs, additionally associated to the expression levels of relevant immune genes in placenta. In conclusion, the genetic risk of several neuropsychiatric disorders could operate, at least in part, through DNAm and associated gene expression in placenta.

Published
2023

32. Placental microRNAs relate to early childhood growth trajectories

Author

Kennedy, Elizabeth M., primary, Hermetz, Karen, additional, Burt, Amber, additional, Pei, Dong, additional, Koestler, Devin C., additional, Hao, Ke, additional, Chen, Jia, additional, Gilbert-Diamond, Diane, additional, Ramakrishnan, Usha, additional, Karagas, Margaret R., additional, and Marsit, Carmen J., additional

Published
2022
Full Text
View/download PDF

33. Identifying gene–gene interactions that are highly associated with four quantitative lipid traits across multiple cohorts

Author

De, Rishika, Verma, Shefali S., Holzinger, Emily, Hall, Molly, Burt, Amber, Carrell, David S., Crosslin, David R., Jarvik, Gail P., Kuivaniemi, Helena, Kullo, Iftikhar J., Lange, Leslie A., Lanktree, Matthew B., Larson, Eric B., North, Kari E., Reiner, Alex P., Tragante, Vinicius, Tromp, Gerard, Wilson, James G., Asselbergs, Folkert W., Drenos, Fotios, Moore, Jason H., Ritchie, Marylyn D., Keating, Brendan, and Gilbert-Diamond, Diane

Published
2017
Full Text
View/download PDF

35. Human placental microRNAs dysregulated by cadmium exposure predict neurobehavioral outcomes at birth

Author

Tehrani, Jesse M., primary, Kennedy, Elizabeth, additional, Tung, Pei Wen, additional, Burt, Amber, additional, Hermetz, Karen, additional, Punshon, Tracy, additional, Jackson, Brian P., additional, Hao, Ke, additional, Chen, Jia, additional, Karagas, Margaret R., additional, Koestler, Devin C., additional, Lester, Barry, additional, and Marsit, Carmen J., additional

Published
2022
Full Text
View/download PDF

37. Publisher Correction: Protein-altering variants associated with body mass index implicate pathways that control energy intake and expenditure in obesity

Author

Turcot, Valérie, Lu, Yingchang, Highland, Heather M., Schurmann, Claudia, Justice, Anne E., Fine, Rebecca S., Bradfield, Jonathan P., Esko, Tõnu, Giri, Ayush, Graff, Mariaelisa, Guo, Xiuqing, Hendricks, Audrey E., Karaderi, Tugce, Lempradl, Adelheid, Locke, Adam E., Mahajan, Anubha, Marouli, Eirini, Sivapalaratnam, Suthesh, Young, Kristin L., Alfred, Tamuno, Feitosa, Mary F., Masca, Nicholas G. D., Manning, Alisa K., Medina-Gomez, Carolina, Mudgal, Poorva, Ng, Maggie C. Y., Reiner, Alex P., Vedantam, Sailaja, Willems, Sara M., Winkler, Thomas W., Abecasis, Gonçalo, Aben, Katja K., Alam, Dewan S., Alharthi, Sameer E., Allison, Matthew, Amouyel, Philippe, Asselbergs, Folkert W., Auer, Paul L., Balkau, Beverley, Bang, Lia E., Barroso, Inês, Bastarache, Lisa, Benn, Marianne, Bergmann, Sven, Bielak, Lawrence F., Blüher, Matthias, Boehnke, Michael, Boeing, Heiner, Boerwinkle, Eric, Böger, Carsten A., Bork-Jensen, Jette, Bots, Michiel L., Bottinger, Erwin P., Bowden, Donald W., Brandslund, Ivan, Breen, Gerome, Brilliant, Murray H., Broer, Linda, Brumat, Marco, Burt, Amber A., Butterworth, Adam S., Campbell, Peter T., Cappellani, Stefania, Carey, David J., Catamo, Eulalia, Caulfield, Mark J., Chambers, John C., Chasman, Daniel I., Chen, Yii-Der I., Chowdhury, Rajiv, Christensen, Cramer, Chu, Audrey Y., Cocca, Massimiliano, Collins, Francis S., Cook, James P., Corley, Janie, Galbany, Jordi Corominas, Cox, Amanda J., Crosslin, David S., Cuellar-Partida, Gabriel, D’Eustacchio, Angela, Danesh, John, Davies, Gail, Bakker, Paul I. W., Groot, Mark C. H., Mutsert, Renée, Deary, Ian J., Dedoussis, George, Demerath, Ellen W., Heijer, Martin, Hollander, Anneke I., Ruijter, Hester M., Dennis, Joe G., Denny, Josh C., Di Angelantonio, Emanuele, Drenos, Fotios, Du, Mengmeng, Dubé, Marie-Pierre, Dunning, Alison M., Easton, Douglas F., Edwards, Todd L., Ellinghaus, David, Ellinor, Patrick T., Elliott, Paul, Evangelou, Evangelos, Farmaki, Aliki-Eleni, Farooqi, I. Sadaf, Faul, Jessica D., Fauser, Sascha, Feng, Shuang, Ferrannini, Ele, Ferrieres, Jean, Florez, Jose C., Ford, Ian, Fornage, Myriam, Franco, Oscar H., Franke, Andre, Franks, Paul W., Friedrich, Nele, Frikke-Schmidt, Ruth, Galesloot, Tessel E., Gan, Wei, Gandin, Ilaria, Gasparini, Paolo, Gibson, Jane, Giedraitis, Vilmantas, Gjesing, Anette P., Gordon-Larsen, Penny, Gorski, Mathias, Grabe, Hans-Jörgen, Grant, Struan F. A., Grarup, Niels, Griffiths, Helen L., Grove, Megan L., Gudnason, Vilmundur, Gustafsson, Stefan, Haessler, Jeff, Hakonarson, Hakon, Hammerschlag, Anke R., Hansen, Torben, Harris, Kathleen Mullan, Harris, Tamara B., Hattersley, Andrew T., Have, Christian T., Hayward, Caroline, He, Liang, Heard-Costa, Nancy L., Heath, Andrew C., Heid, Iris M., Helgeland, Øyvind, Hernesniemi, Jussi, Hewitt, Alex W., Holmen, Oddgeir L., Hovingh, G. Kees, Howson, Joanna M. M., Hu, Yao, Huang, Paul L., Huffman, Jennifer E., Ikram, M. Arfan, Ingelsson, Erik, Jackson, Anne U., Jansson, Jan-Håkan, Jarvik, Gail P., Jensen, Gorm B., Jia, Yucheng, Johansson, Stefan, Jørgensen, Marit E., Jørgensen, Torben, Jukema, J. Wouter, Kahali, Bratati, Kahn, René S., Kähönen, Mika, Kamstrup, Pia R., Kanoni, Stavroula, Kaprio, Jaakko, Karaleftheri, Maria, Kardia, Sharon L. R., Karpe, Fredrik, Kathiresan, Sekar, Kee, Frank, Kiemeney, Lambertus A., Kim, Eric, Kitajima, Hidetoshi, Komulainen, Pirjo, Kooner, Jaspal S., Kooperberg, Charles, Korhonen, Tellervo, Kovacs, Peter, Kuivaniemi, Helena, Kutalik, Zoltán, Kuulasmaa, Kari, Kuusisto, Johanna, Laakso, Markku, Lakka, Timo A., Lamparter, David, Lange, Ethan M., Lange, Leslie A., Langenberg, Claudia, Larson, Eric B., Lee, Nanette R., Lehtimäki, Terho, Lewis, Cora E., Li, Huaixing, Li, Jin, Li-Gao, Ruifang, Lin, Honghuang, Lin, Keng-Hung, Lin, Li-An, Lin, Xu, Lind, Lars, Lindström, Jaana, Linneberg, Allan, Liu, Ching-Ti, Liu, Dajiang J., Liu, Yongmei, Lo, Ken S., Lophatananon, Artitaya, Lotery, Andrew J., Loukola, Anu, Luan, Jian’an, Lubitz, Steven A., Lyytikäinen, Leo-Pekka, Männistö, Satu, Marenne, Gaëlle, Mazul, Angela L., McCarthy, Mark I., McKean-Cowdin, Roberta, Medland, Sarah E., Meidtner, Karina, Milani, Lili, Mistry, Vanisha, Mitchell, Paul, Mohlke, Karen L., Moilanen, Leena, Moitry, Marie, Montgomery, Grant W., Mook-Kanamori, Dennis O., Moore, Carmel, Mori, Trevor A., Morris, Andrew D., Morris, Andrew P., Müller-Nurasyid, Martina, Munroe, Patricia B., Nalls, Mike A., Narisu, Narisu, Nelson, Christopher P., Neville, Matt, Nielsen, Sune F., Nikus, Kjell, Njølstad, Pål R., Nordestgaard, Børge G., Nyholt, Dale R., O’Connel, Jeffrey R., O’Donoghue, Michelle L., Loohuis, Loes M. Olde, Ophoff, Roel A., Owen, Katharine R., Packard, Chris J., Padmanabhan, Sandosh, Palmer, Colin N. A., Palmer, Nicholette D., Pasterkamp, Gerard, Patel, Aniruddh P., Pattie, Alison, Pedersen, Oluf, Peissig, Peggy L., Peloso, Gina M., Pennell, Craig E., Perola, Markus, Perry, James A., Perry, John R. B., Pers, Tune H., Person, Thomas N., Peters, Annette, Petersen, Eva R. B., Peyser, Patricia A., Pirie, Ailith, Polasek, Ozren, Polderman, Tinca J., Puolijoki, Hannu, Raitakari, Olli T., Rasheed, Asif, Rauramaa, Rainer, Reilly, Dermot F., Renström, Frida, Rheinberger, Myriam, Ridker, Paul M., Rioux, John D., Rivas, Manuel A., Roberts, David J., Robertson, Neil R., Robino, Antonietta, Rolandsson, Olov, Rudan, Igor, Ruth, Katherine S., Saleheen, Danish, Salomaa, Veikko, Samani, Nilesh J., Sapkota, Yadav, Sattar, Naveed, Schoen, Robert E., Schreiner, Pamela J., Schulze, Matthias B., Scott, Robert A., Segura-Lepe, Marcelo P., Shah, Svati H., Sheu, Wayne H.-H., Sim, Xueling, Slater, Andrew J., Small, Kerrin S., Smith, Albert V., Southam, Lorraine, Spector, Timothy D., Speliotes, Elizabeth K., Starr, John M., Stefansson, Kari, Steinthorsdottir, Valgerdur, Stirrups, Kathleen E., Strauch, Konstantin, Stringham, Heather M., Stumvoll, Michael, Sun, Liang, Surendran, Praveen, Swift, Amy J., Tada, Hayato, Tansey, Katherine E., Tardif, Jean-Claude, Taylor, Kent D., Teumer, Alexander, Thompson, Deborah J., Thorleifsson, Gudmar, Thorsteinsdottir, Unnur, Thuesen, Betina H., Tönjes, Anke, Tromp, Gerard, Trompet, Stella, Tsafantakis, Emmanouil, Tuomilehto, Jaakko, Tybjaerg-Hansen, Anne, Tyrer, Jonathan P., Uher, Rudolf, Uitterlinden, André G., Uusitupa, Matti, Laan, Sander W., Duijn, Cornelia M., Leeuwen, Nienke, van Setten, Jessica, Vanhala, Mauno, Varbo, Anette, Varga, Tibor V., Varma, Rohit, Edwards, Digna R. Velez, Vermeulen, Sita H., Veronesi, Giovanni, Vestergaard, Henrik, Vitart, Veronique, Vogt, Thomas F., Völker, Uwe, Vuckovic, Dragana, Wagenknecht, Lynne E., Walker, Mark, Wallentin, Lars, Wang, Feijie, Wang, Carol A., Wang, Shuai, Wang, Yiqin, Ware, Erin B., Wareham, Nicholas J., Warren, Helen R., Waterworth, Dawn M., Wessel, Jennifer, White, Harvey D., Willer, Cristen J., Wilson, James G., Witte, Daniel R., Wood, Andrew R., Wu, Ying, Yaghootkar, Hanieh, Yao, Jie, Yao, Pang, Yerges-Armstrong, Laura M., Young, Robin, Zeggini, Eleftheria, Zhan, Xiaowei, Zhang, Weihua, Zhao, Jing Hua, Zhao, Wei, Zhao, Wei, Zhou, Wei, Zondervan, Krina T, CHD Exome+ Consortium, EPIC-CVD Consortium, ExomeBP Consortium, Global Lipids Genetic Consortium, GoT2D Genes Consortium, EPIC InterAct Consortium, INTERVAL Study, ReproGen Consortium, T2D-Genes Consortium, The MAGIC Investigators, Understanding Society Scientific Group, Rotter, Jerome I., Pospisilik, John A., Rivadeneira, Fernando, Borecki, Ingrid B., Deloukas, Panos, Frayling, Timothy M., Lettre, Guillaume, North, Kari E., Lindgren, Cecilia M., Hirschhorn, Joel N., and Loos, Ruth J. F.

Published
2019
Full Text
View/download PDF

39. Profiling placental DNA methylation associated with maternal SSRI treatment during pregnancy

Author

Inkster, Amy M., primary, Konwar, Chaini, additional, Peñaherrera, Maria S., additional, Brain, Ursula, additional, Khan, Almas, additional, Price, E. Magda, additional, Schuetz, Johanna M., additional, Portales-Casamar, Élodie, additional, Burt, Amber, additional, Marsit, Carmen J., additional, Vaillancourt, Cathy, additional, Oberlander, Tim F., additional, and Robinson, Wendy P., additional

Published
2022
Full Text
View/download PDF

41. 247-OR: Maternal Prepregnancy Obesity and Gestational Diabetes Are Associated with Epigenetic Gestational Aging in the Placenta

Author

HUFF, KATELYN, primary, ROELL, KYLE, additional, BULKA, CATHERINE, additional, BOYLE, KRISTEN E., additional, BRETON, CARRIE, additional, BURT, AMBER, additional, DABELEA, DANA, additional, KAHN, LINDA, additional, KARAGAS, MARGARET R., additional, MARSIT, CARMEN, additional, NIEMIEC, SIERRA, additional, VOLK, HEATHER, additional, O'SHEA, THOMAS M., additional, and FRY, REBECCA, additional

Published
2022
Full Text
View/download PDF

42. Variation in placental microRNA expression associates with maternal family history of cardiovascular disease.

Author

Tehrani, Jesse M., Kennedy, Elizabeth M., Tian, Fu-Ying, Everson, Todd M., Deyssenroth, Maya, Burt, Amber, Hermetz, Karen, Hao, Ke, Chen, Jia, Koestler, Devin C., and Marsit, Carmen J.

Subjects
GENE expression, FAMILY history (Medicine), MICRORNA, NON-coding RNA, PLACENTA
Abstract

In the United States, cardiovascular disease is the leading cause of death and the rate of maternal mortality remains among the highest of any industrialized nation. Maternal cardiometabolic health throughout gestation and postpartum is representative of placental health and physiology. Both proper placental functionality and placental microRNA expression are essential to successful pregnancy outcomes, and both are highly sensitive to genetic and environmental sources of variation. Placental pathologies, such as preeclampsia, are associated with maternal cardiovascular health but may also contribute to the developmental programming of chronic disease in offspring. However, the role of more subtle alterations to placental function and microRNA expression in this developmental programming remains poorly understood. We performed small RNA sequencing to investigate microRNA in placentae from the Rhode Island Child Health Study (n = 230). MicroRNA counts were modeled on maternal family history of cardiovascular disease using negative binomial generalized linear models. MicroRNAs were considered to be differentially expressed at a false discovery rate (FDR) less than 0.10. Parallel mRNA sequencing data and bioinformatic target prediction software were then used to identify potential mRNA targets of differentially expressed microRNAs. Nine differentially expressed microRNAs were identified (FDR < 0.1). Bioinformatic target prediction revealed 66 potential mRNA targets of these microRNAs, many of which are implicated in TGFβ signaling pathway but also in pathways involving cellular metabolism and immunomodulation. A robust association exists between familial cardiovascular disease and placental microRNA expression which may be implicated in both placental insufficiencies and the developmental programming of chronic disease. [ABSTRACT FROM AUTHOR]

Published
2023
Full Text
View/download PDF

44. Selenium-associated differentially expressed microRNAs and their targeted mRNAs across the placental genome in two U.S. birth cohorts

Author

Tian, Fu-Ying, primary, Kennedy, Elizabeth M., additional, Hermetz, Karen, additional, Burt, Amber, additional, Everson, Todd M., additional, Punshon, Tracy, additional, Jackson, Brian P., additional, Hao, Ke, additional, Chen, Jia, additional, Karagas, Margaret R., additional, Koestler, Devin C., additional, and Marsit, Carmen, additional

Published
2021
Full Text
View/download PDF

45. Prenatal lead (Pb) exposure is associated with differential placental DNA methylation and hydroxymethylation in a human population.

Author

Pei Wen Tung, Kennedy, Elizabeth M., Burt, Amber, Hermetz, Karen, Karagas, Margaret, and Marsit, Carmen J.

Subjects
DNA methylation, LEAD, LEAD exposure, METHYLATION, PLACENTA, MORPHOGENESIS
Abstract

Prenatal lead (Pb) exposure is associated with adverse developmental outcomes and to epigenetic alterations such as DNA methylation and hydroxymethylation in animal models and in newborn blood. Given the importance of the placenta in foetal development, we sought to examine how prenatal Pb exposure was associated with differential placental DNA methylation and hydroxymethylation and to identify affected biological pathways linked to developmental outcomes. Maternal (n = 167) and infant (n = 172) toenail and placenta (n = 115) samples for prenatal Pb exposure were obtained from participants in a US birth cohort, and methylation and hydroxymethylation data were quantified using the Illumina Infinium MethylationEPIC BeadChip. An epigenome-wide association study was applied to identify differential methylation and hydroxymethylation associated with Pb exposure. Biological functions of the Pb-associated genes were determined by overrepresentation analysis through ConsensusPathDB. Prenatal Pb quantified from maternal toenail, infant toenail, and placenta was associated with 480, 27, and 2 differentially methylated sites (q < 0.05), respectively, with both increases and decreases associated with exposure. Alternatively, we identified 2, 1, and 14 differentially hydroxymethylated site(s) associated with maternal toenail, infant toenail, and placental Pb, respectively, with most showing increases in hydroxymethylation with exposure. Significantly overrepresented pathways amongst genes associated with differential methylation and hydroxymethylation (q < 0.10) included mechanisms pertaining to nervous system and organ development, calcium transport and regulation, and signalling activities. Our results suggest that both methylation and hydroxymethylation in the placenta can be variable based on Pb exposure and that the pathways impacted could affect placental function. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

46. Selenium-associated differentially expressed microRNAs and their targeted mRNAs across the placental genome in two U.S. birth cohorts.

Author

Tian, Fu-Ying, Kennedy, Elizabeth M., Hermetz, Karen, Burt, Amber, Everson, Todd M., Punshon, Tracy, Jackson, Brian P., Hao, Ke, Chen, Jia, Karagas, Margaret R., Koestler, Devin C., and Marsit, Carmen

Subjects
INDUCTIVELY coupled plasma mass spectrometry, ABRUPTIO placentae, COHORT analysis, MICRORNA
Abstract

Selenium is an important micronutrient for foetal development. MicroRNAs play an important role in the function of the placenta, in communication between the placenta and maternal systems, and their expression can be altered through environmental and nutritional cues. To investigate the associations between placental selenium concentration and microRNA expression in the placenta, our observational study included 393 mother-child pairs from the New Hampshire Birth Cohort Study (NHBCS) and the Rhode Island Child Health Study (RICHS). Placental selenium concentrations were quantified using inductively coupled plasma mass spectrometry, and microRNA transcripts were measured using RNA-seq. We fit negative binomial additive models for assessing the association between selenium and microRNAs. We used the microRNA Data Integration Portal (mirDIP) to predict the target mRNAs of the differentially expressed microRNAs and verified the relationships between miRNA and mRNA targets in a subset of samples using existing whole transcriptome data (N = 199). We identified a non-monotonic association between selenium concentration and the expression of miR-216a-5p/miR-217-5p cluster (effective degrees of freedom, EDF = 2.44 and 2.08; FDR = 3.08 × 10−5) in placenta. Thirty putative target mRNAs of miR-216a-5p and/or miR-217-5p were identified computationally and empirically and were enriched in selenium metabolic pathways (driven by selenoprotein coding genes, TXNRD2 and SELENON). Our findings suggest that selenium influences placental microRNA expression. Further, miR-216a-5p and its putative target mRNAs could be the potential mechanistic targets of the health effect of selenium. [ABSTRACT FROM AUTHOR]

Published
2022
Full Text
View/download PDF

Catalog

Books, media, physical & digital resources
See catalog results