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1. Transcriptome-wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Author

Eric Jorgenson, Chani J. Hodonsky, Munan Xie, Amanda L. Tapia, Ruth J. F. Loos, Kristin L. Young, Jonathan D. Rosen, Tao Wang, Steve Buyske, Christy L. Avery, Kari E. North, Jennifer A. Smith, Charles Kooperberg, Jee-Young Moon, Yun Li, Stephanie A. Bien, Yongmei Liu, Laura M. Raffield, Stephen S. Rich, Jie Yin, Huijun Qian, Hélène Choquet, Maria Argos, Xiang Zhou, Jerome I. Rotter, Quan Sun, Lulu Shang, Yue Shan, Alexander P. Reiner, Madeline H. Kowalski, Myriam Fornage, Jia Wen, Marielisa Graff, Bryce Rowland, and Wei Zhao

Subjects
Blood cell, Transcriptome, Genetics, medicine.anatomical_structure, Hispanic latino, medicine, biochemistry, Biology, Association (psychology)
Abstract

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Also, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including N=229 African American and N=381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, N = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (N = 27,955) and Hispanic/Latino (N = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1×10^(-4)) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (N=802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Published
2021
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2. Social (Pragmatic) Communication Disorder: Another name for the Broad Autism Phenotype?

Author

Sherri Wilson, Yuli Fradkin, Steve Buyske, Judy F. Flax, Linda M. Brzustowicz, and Christine Gwin

Subjects
Adult, Male, Parents, Adolescent, Autism Spectrum Disorder, Interpersonal communication, Article, Developmental psychology, Diagnosis, Differential, Young Adult, 03 medical and health sciences, 0302 clinical medicine, Communication disorder, Developmental and Educational Psychology, medicine, Humans, 0501 psychology and cognitive sciences, Language disorder, Child, Social Communication Disorder, Social communication, Repetition (rhetorical device), Intelligence quotient, Siblings, 05 social sciences, medicine.disease, 030227 psychiatry, Diagnostic and Statistical Manual of Mental Disorders, Phenotype, Child, Preschool, Clinical diagnosis, Autism, Female, Stereotyped Behavior, Psychology, 050104 developmental & child psychology
Abstract

The Diagnostic and Statistical Manual of Mental Disorders’ (5th ed.) Social (Pragmatic) Communication Disorder is meant to capture the social elements of communication dysfunction in children who do not meet autism spectrum disorder criteria. It is unclear whether Social (Pragmatic) Communication Disorder captures these elements without overlapping with Autism Spectrum Disorder or the Diagnostic and Statistical Manual of Mental Disorders’ (5th ed.) Language Disorder. Standardized behavioral assessments administered during a family genetics study were used to evaluate the social communication impairment and the restricted interests and repetitive behaviors in persons with autism spectrum disorder, language impairment, or neither. Social communication impairment and restricted interests and repetitive behavior were significantly correlated in all family members regardless of affection status. Rates of social communication impairment and restricted interests and repetitive behavior were highest in individuals with autism spectrum disorder. One-third of family members with language impairment presented with at least mild/moderate levels of social communication impairment (36.6%) and restricted interests and repetitive behavior (43.3%). A subset of unaffected members also presented with mild/moderate levels of social communication impairment (parents = 10.1%, siblings 11.6%) and restricted interests and repetitive behavior (parents = 14.0%, siblings = 22.1%). The majority of child family members with mild/moderate levels of social communication impairment had similar restricted interest and repetitive behavior levels reflecting criteria representing the Broad Autism Phenotype. These data suggest that social pragmatic communication disorder does not capture the profiles of children who have both social communication impairment and restricted interests and repetitive behavior but are in need of clinical services.

Published
2019
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3. The gastrin-releasing peptide regulates stress-enhanced fear and dopamine signaling

Author

Premal Shah, Charles Hevi, Gleb P. Shumyatsky, John S. Favate, Stephanie E. Sillivan, Courtney A. Miller, Ileana Fuentes, Steve Buyske, Noriko K. Goldsmith, Eric R. Kandel, Akinori Nishi, Ko Zushida, Yoshikazu Morishita, and Shusaku Uchida

Subjects
Ventral tegmental area, medicine.anatomical_structure, Dopamine, Gastrin-releasing peptide, medicine, Premovement neuronal activity, Classical conditioning, Fear conditioning, Biology, Neuroscience, Amygdala, Basolateral amygdala, medicine.drug
Abstract

Fear extinction is an adaptive behavioral process critical for organism’s survival, but deficiency in extinction may lead to PTSD. While the amygdala and its neural circuits are critical for fear extinction, the molecular identity and organizational logic of cell types that lie at the core of these circuits remain unclear. Here we report that mice deficient for amygdala-enrichedgastrin-releasing peptidegene (Grp-/-) exhibit enhanced neuronal activity in the basolateral amygdala (BLA) and stronger fear conditioning, as well as deficient extinction in stress-enhanced fear learning (SEFL). rAAV2-retro-based tracing combined with visualization of the GFP knocked in theGrpgene showed that BLA receives GRPergic or conditioned stimulus projections from the indirect auditory thalamus-to-auditory cortex pathway, ventral hippocampus and ventral tegmental area. Transcription of dopamine-related genes was decreased in BLA ofGrp-/-mice following SEFL extinction recall, suggesting that the GRP may mediate fear extinction regulation by dopamine.Impact statementMice deficient for the amygdala-enrichedgastrin-releasing peptidegene are susceptible to stress-enhanced fear, a behavioral protocol with relevance to PTSD, and show a decrease in dopamine-related gene transcription.

Published
2021
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4. Alternative genomic diagnoses for individuals with a clinical diagnosis of Dubowitz syndrome

Author

Sixto Garcia Minaur, Pankaj B. Agrawal, A. Micheil Innes, Catherine A. Brownstein, David S. Wargowski, Brenda McInnes, Isaac Wong, Albert E. Chudley, Jennifer E. Posey, Francesc López-Giráldez, Ping-Yee B Au, Alper Gezdirici, Kyrieckos A. Aleck, Eric Boerwinkle, Paolo Prontera, Bilgen Bilge Geçkinli, Yeting Zhang, An Nguyen, David A. Dyment, Jukka S. Moilanen, Alan H. Beggs, Nara Sobreira, Hatip Aydin, Elizabeth E. Blue, Kathryn Dunn, Gerald F. Cox, Bernard N. Chodirker, Harrison Brand, Jinchuan Xing, Hind Al Sharhan, Bert B.A. de Vries, Maria Juliana Rodovalho Doriqui, Davut Pehlivan, Shalini N. Jhangiani, Centers for Mendelian Genomics, Katrin Õunap, Cheryl R. Greenberg, Kaya Bilguvar, Carol L. Clericuzio, Cynthia J. Curry, Taila Hartley, Julie Lauzon, Michael J. Bamshad, Timothy Poterba, R. Brian Lowry, Jill A. Fahrner, Cullen M. Dutmer, M. E. Suzanne Lewis, Steve Buyske, Ender Karaca, Aziz Mhanni, William T. Gibson, Valentina Stanley, April Hall, Elke de Boer, Kristin D. Kernohan, Joseph G. Gleeson, P. Dane Witmer, Jungmin Choi, Danny Antaki, Małgorzata J.M. Nowaczyk, Sander Pajusalu, Anne H. O’Donnell-Luria, Sarah L. Sawyer, Zeynep Coban Akdemir, Tara C. Matise, Jennifer McEvoy-Venneri, Casie A. Genetti, Kym M. Boycott, Lynette S. Penney, Ada Hamosh, Eleina M. England, Deniz Torun, Maha S. Zaki, Deborah A. Nickerson, Dyment, David A., O'Donnell-Luria, Anne, Agrawal, Pankaj B., Coban Akdemir, Zeynep, Aleck, Kyrieckos A., Antaki, Danny, Al Sharhan, Hind, Au, Ping-Yee B., Aydin, Hatip, Beggs, Alan H., Bilguvar, Kaya, Boerwinkle, Eric, Brand, Harrison, Brownstein, Catherine A., Buyske, Steve, Chodirker, Bernard, Choi, Jungmin, Chudley, Albert E., Clericuzio, Carol L., Cox, Gerald F., Curry, Cynthia, de Boer, Elke, de Vries, Bert B. A., Dunn, Kathryn, Dutmer, Cullen M., England, Eleina M., Fahrner, Jill A., Geckinli, Bilgen B., Genetti, Casie A., Gezdirici, Alper, Gibson, William T., Gleeson, Joseph G., Greenberg, Cheryl R., Hall, April, Hamosh, Ada, Hartley, Taila, Jhangiani, Shalini N., Karaca, Ender, Kernohan, Kristin, Lauzon, Julie L., Lewis, M. E. Suzanne, Lowry, R. Brian, Lopez-Giraldez, Francesc, Matise, Tara C., McEvoy-Venneri, Jennifer, McInnes, Brenda, Mhanni, Aziz, Garcia Minaur, Sixto, Moilanen, Jukka, Nguyen, An, Nowaczyk, Malgorzata J. M., Posey, Jennifer E., Ounap, Katrin, Pehlivan, Davut, Pajusalu, Sander, Penney, Lynette S., Poterba, Timothy, Prontera, Paolo, Doriqui, Maria Juliana Rodovalho, Sawyer, Sarah L., Sobreira, Nara, Stanley, Valentina, Torun, Deniz, Wargowski, David, Witmer, P. Dane, Wong, Isaac, Xing, Jinchuan, Zaki, Maha S., Zhang, Yeting, Boycott, Kym M., Bamshad, Michael J., Nickerson, Deborah A., Blue, Elizabeth E., and Innes, A. Micheil

Subjects
0301 basic medicine, Male, ANOMALIES, INTELLECTUAL DISABILITY, Eczema, 030105 genetics & heredity, PHENOTYPE, genetic heterogeneity, Locus heterogeneity, Dubowitz syndrome, Exome, Child, Genetics (clinical), Exome sequencing, Growth Disorders, Genetics, FRAMESHIFT, Genomics, 3. Good health, VPS13B, genome sequencing, LOSS-OF-FUNCTION, Child, Preschool, symbols, Microcephaly, Female, microarray, Adolescent, DNA Copy Number Variations, Biology, NSUN2, PATIENT, DNA sequencing, Histone Deacetylases, Article, 03 medical and health sciences, symbols.namesake, medicine, Humans, Genetic Predisposition to Disease, ANEMIA, Genetic heterogeneity, Genome, Human, MUTATIONS, Facies, Infant, PLATFORM, medicine.disease, Repressor Proteins, 030104 developmental biology, Mendelian inheritance, exome sequencing
Abstract

Dubowitz syndrome (DubS) is considered a recognizable syndrome characterized by a distinctive facial appearance and deficits in growth and development. There have been over 200 individuals reported with Dubowitz or a "Dubowitz-like" condition, although no single gene has been implicated as responsible for its cause. We have performed exome (ES) or genome sequencing (GS) for 31 individuals clinically diagnosed with DubS. After genome-wide sequencing, rare variant filtering and computational and Mendelian genomic analyses, a presumptive molecular diagnosis was made in 13/27 (48%) families. The molecular diagnoses included biallelic variants in SKIV2L, SLC35C1, BRCA1, NSUN2; de novo variants in ARID1B, ARID1A, CREBBP, POGZ, TAF1, HDAC8, and copy-number variation at1p36.11(ARID1A), 8q22.2(VPS13B), Xp22, and Xq13(HDAC8). Variants of unknown significance in known disease genes, and also in genes of uncertain significance, were observed in 7/27 (26%) additional families. Only one gene, HDAC8, could explain the phenotype in more than one family (N = 2). All but two of the genomic diagnoses were for genes discovered, or for conditions recognized, since the introduction of next-generation sequencing. Overall, the DubS-like clinical phenotype is associated with extensive locus heterogeneity and the molecular diagnoses made are for emerging clinical conditions sharing characteristic features that overlap the DubS phenotype.

Published
2021

5. Transcriptome-Wide Association Study of Blood Cell Traits in African Ancestry and Hispanic/Latino Populations

Author

Kari E. North, Jie Yin, Maria Argos, Tao Wang, Jiawen Chen, Jee-Young Moon, Myriam Fornage, Yongmei Liu, Xiang Zhou, Steve Buyske, Kristin L. Young, Bryce Rowland, Jonathan D. Rosen, Laura M. Raffield, Alexander P. Reiner, Lulu Shang, Stephanie A. Bien, Christy L. Avery, Eric Jorgenson, Quan Sun, Marielisa Graff, Amanda L. Tapia, Madeline H. Kowalski, Jia Wen, Hélène Choquet, Yue Shan, Chani J. Hodonsky, Munan Xie, Jerome I. Rotter, Yun Li, Ruth J. F. Loos, Wei Zhao, Stephen S. Rich, Jennifer A. Smith, Huijun Qian, and Charles Kooperberg

Subjects
Quantitative Trait Loci, TWAS, Genome-wide association study, QH426-470, Hematocrit, Biology, Polymorphism, Single Nucleotide, Article, White People, TWAS (transcriptome-wide association study), non-European populations, ancestry, expression analysis, Cohort Studies, Correlation, 03 medical and health sciences, 0302 clinical medicine, Clinical Research, White blood cell, Genetics, medicine, Humans, Genetic Predisposition to Disease, Polymorphism, Gene, Genetics (clinical), 030304 developmental biology, 0303 health sciences, Blood Cells, medicine.diagnostic_test, Human Genome, Single Nucleotide, Hispanic or Latino, Hematology, Atherosclerosis, Black or African American, Phenotype, Good Health and Well Being, medicine.anatomical_structure, Genetic epidemiology, Cohort, Trait, Transcriptome, 030217 neurology & neurosurgery, Genome-Wide Association Study, Biotechnology
Abstract

Background: Thousands of genetic variants have been associated with hematological traits, though target genes remain unknown at most loci. Moreover, limited analyses have been conducted in African ancestry and Hispanic/Latino populations; hematological trait associated variants more common in these populations have likely been missed. Methods: To derive gene expression prediction models, we used ancestry-stratified datasets from the Multi-Ethnic Study of Atherosclerosis (MESA, including n = 229 African American and n = 381 Hispanic/Latino participants, monocytes) and the Depression Genes and Networks study (DGN, n = 922 European ancestry participants, whole blood). We then performed a transcriptome-wide association study (TWAS) for platelet count, hemoglobin, hematocrit, and white blood cell count in African (n = 27,955) and Hispanic/Latino (n = 28,324) ancestry participants. Results: Our results revealed 24 suggestive signals (p < 1 × 10−4) that were conditionally distinct from known GWAS identified variants and successfully replicated these signals in European ancestry subjects from UK Biobank. We found modestly improved correlation of predicted and measured gene expression in an independent African American cohort (the Genetic Epidemiology Network of Arteriopathy (GENOA) study (n = 802), lymphoblastoid cell lines) using the larger DGN reference panel; however, some genes were well predicted using MESA but not DGN. Conclusions: These analyses demonstrate the importance of performing TWAS and other genetic analyses across diverse populations and of balancing sample size and ancestry background matching when selecting a TWAS reference panel.

Published
2021
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6. Pilot Study for Implementing an Osteoporosis Education and Exercise Program in an Assisted Living Facility and Senior Community

Author

Sally Fullman, Mary L. Wagner, Steve Buyske, Lori Morell, and Aparna P. Nanduri

Subjects
Male, Gerontology, Health Knowledge, Attitudes, Practice, medicine.medical_specialty, Osteoporosis, Poison control, Pilot Projects, 030209 endocrinology & metabolism, Suicide prevention, Peer Group, Occupational safety and health, 03 medical and health sciences, 0302 clinical medicine, Assisted Living Facilities, Prohibitins, Injury prevention, medicine, Humans, Muscle Strength, 030212 general & internal medicine, Range of Motion, Articular, Exercise, Geriatric Assessment, Health Education, Postural Balance, Aged, Aged, 80 and over, business.industry, Public health, medicine.disease, Health promotion, Exercise Test, Physical therapy, Accidental Falls, Female, Diet, Healthy, Geriatrics and Gerontology, business, Program Evaluation, Fall prevention
Abstract

Background: Project Healthy Bones (PHB) is a 24-week, peer-led exercise and education program for older adults at risk of osteoporosis. Method: Residents from an assisted living and senior community program were enrolled after medical clearance. Participant demographics, geriatric fitness assessments, exercise logs, quizzes, and surveys were collected at baseline and 24 weeks. Data were analyzed using paired t tests and ANOVA of change scores for the pooled data within the R statistical environment. Results: Forty of the 53 enrolled participants completed the program. Participants improved their strength, balance, posture, and flexibility, resulting in a reduced risk of falls and fractures. In addition, their knowledge of bone health, nutrition, and fall prevention increased. Conclusion: Offering low-cost disease-specific programs such as PHB helps minimize the complications of osteoporosis and improve the overall health of participants. Implementing disease-specific public health programs in assisted living centers can increase access to programs.

Published
2016
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7. Abstract 053: Genome-wide Tcea3 -SNP Interaction Study Identifies Novel QT Interval Loci

Author

Stella Trompet, Martina Müller-Nurasyid, Elsayed Z. Soliman, Steve Buyske, Kari E. North, Dan E. Arking, Henry Lin, Katharina Schramm, Nona Sotoodehnia, Maria P Concas, Raymond Noordam, Christy L. Avery, Charles Kooperberg, Ching-Ti Lin, Antoine R Baldassari, and Christopher Newton-Cheh

Subjects
Genetics, Transcription elongation, business.industry, Physiology (medical), Medicine, SNP, Single-nucleotide polymorphism, Genome-wide association study, Cardiology and Cardiovascular Medicine, business, Genome, QT interval, Genetic association
Abstract

Background: QT interval (QT) genome-wide association studies (GWAS) have identified upwards of 35 common variant loci, including SNPs adjacent to putative transcription elongation factor TCEA3. Transcription elongation control has broad effects on gene expression, the misregulation of which is known to influence cardiac conduction system morphogenesis as well as activation or repression of key regulatory genes. Thus, we hypothesized that a genome-wide gene-gene interaction study of TCEA3 lead SNP rs2298632 would identify novel loci that influence QT. Methods: Using 1000 Genomes imputed data (>20 million SNPs) in n=67,445 participants (69% Caucasian; 18% Hispanic/Latino; 11% African American) from 10 studies, we conducted genome-wide meta-analyses to test for the presence of: interaction effect loci by examining rs2298632xSNP interactions on QT; and joint effect loci by simultaneously examining SNP main effects and rs2298632xSNP interactions on QT. Inverse-variance weighted meta-analysis of genomically controlled ancestry- and study-specific summary effects estimated using multivariable adjusted linear models or generalized estimating equations that incorporated robust standard errors was performed using METAL. SNPs demonstrating evidence of heterogeneity (Cochran’s Q P < 0.05) and SNPs that were infrequent or rare (minor allele frequency [MAF] Results: We identified one genome-wide significant interaction effect locus ( P INT -8 ) at PVT1 (lead SNP: rs4733591; mean MAF = 32%), a long non-coding RNA gene for which previous GWAS identified suggestive associations with left ventricular systolic dysfunction. We also identified four genome-wide significant joint effect loci ( P JOINT -8 ) that mapped within or nearby NUCKS1 (lead SNP: rs823094; MAF = 0.33) , CASR (lead SNP = rs17251221; MAF = 0.13) , ACTBL2 (lead SNP = rs7737409; MAF = 0.22) , and KDM1B (lead SNP = rs34969716; MAF = 0.26) , loci with roles in calcium sensing, regulation of gene expression through histone modification, and tumor suppression. Conclusion: Extension of traditional main effects GWAS to interrogate gene-gene interactions for biologically motivated loci like TCEA3 may help inform the structure and function of genetic pathways underlying complex traits like QT.

Published
2018
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8. The PAGE Study: How Genetic Diversity Improves Our Understanding of the Architecture of Complex Traits

Author

Steve Buyske, Claudia Schurmann, Andrés Moreno-Estrada, Cathy C. Laurie, Ulrike Peters, Yesha Patel, Eimear E. Kenny, Michael Preuss, Hannah Poisner, Kari E. North, Carlos Bustamante, Christopher A. Haiman, Stephanie A. Bien, Anne E. Justice, Katherine K. Nishimura, Yuqing Li, Loic Le Marchand, Unhee Lim, E Stahl, Christopher R. Gignoux, Alexandra Sockell, Paul Norman, Ewa Deelman, Yingchang Lu, Rebecca D. Jackson, Huckins Lm, Gerardo Heiss, Kimberly F. Doheny, Chani J. Hodonsky, Brenna M. Henn, Benyam Hailu, Genevieve L. Wojcik, Jane Romm, Misa Graff, Loos R, Christy L. Avery, Danyu Lin, José Luis Ambite, Kris Young, Eric Boerwinkle, Kathleen C. Barnes, Gillian M. Belbin, Bridget M Lin, Lindsay Fernández-Rhodes, Cecilia A. Laurie, Christian Caberto, Sung-Hyuk Park, Tara C. Matise, Abhishek Vishnu, Loreall Pooler, Ran Tao, Elena P. Sorokin, Ron Do, Lucia A. Hindorff, Sarah C. Nelson, Heather M. Highland, L R Wilkens, Cheryl A. Winkler, Iona Cheng, Acuna-Alonso, Matthew P. Conomos, Myriam Fornage, Xin Sheng, Girish N. Nadkarni, Christopher S. Carlson, Ruth H. Walker, Janina M. Jeff, Jeffrey Haessler, Daniel O. Stram, Sabati C, Sachiko Yoneyama, Jonathan M. Kocarnik, Christina L. Wassel, Timothy A. Thornton, Charles Kooperberg, Veronica Wendy Setiawan, Yao Hu, Sinead Cullina, Canizales-Quinteroes S, Niha Zubair, Melissa A. Richard, Karan Vahi, Karla Sandoval, Marie Verbanck, Erwin P. Bottinger, and Alexander P. Reiner

Subjects
0303 health sciences, medicine.medical_specialty, education.field_of_study, Genetic diversity, Public health, Population, Genomics, Genome-wide association study, Disease, Biology, Health equity, 3. Good health, 03 medical and health sciences, 0302 clinical medicine, Evolutionary biology, 030220 oncology & carcinogenesis, medicine, education, 030304 developmental biology, Genetic association
Abstract

Summary/AbstractGenome-wide association studies (GWAS) have laid the foundation for investigations into the biology of complex traits, drug development, and clinical guidelines. However, the dominance of European-ancestry populations in GWAS creates a biased view of the role of human variation in disease, and hinders the equitable translation of genetic associations into clinical and public health applications. The Population Architecture using Genomics and Epidemiology (PAGE) study conducted a GWAS of 26 clinical and behavioral phenotypes in 49,839 non-European individuals. Using strategies designed for analysis of multi-ethnic and admixed populations, we confirm 574 GWAS catalog variants across these traits, and find 38 secondary signals in known loci and 27 novel loci. Our data shows strong evidence of effect-size heterogeneity across ancestries for published GWAS associations, substantial benefits for fine-mapping using diverse cohorts, and insights into clinical implications. We strongly advocate for continued, large genome-wide efforts in diverse populations to reduce health disparities.

Published
2017
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9. Genome-wide meta-analysis of 241,258 adults accounting for smoking behaviour identifies novel loci for obesity traits

Author

P. Eline Slagboom, Massimo Mangino, David J. Porteous, Karin Leander, Nancy L. Heard-Costa, Sharon L.R. Kardia, Jennifer Bragg, Ken K. Ong, Igor Rudan, Blair H. Smith, Mark A. Sarzynski, Torben Hansen, James F. Wilson, Weihua Zhang, Zoltán Kutalik, Karl Gertow, Yii-Der Ida Chen, Daniele Cusi, Lu Qi, Nicholas G. Martin, Peter Vollenweider, Thomas W. Winkler, Graciela E. Delgado, Thorkild I. A. Sørensen, André G. Uitterlinden, J. Wouter Jukema, Rajesh Rawal, Dena G. Hernandez, Amy J. Swift, Naveed Sattar, Ruth J. F. Loos, George Dedoussis, Ani Manichaikul, Henrik Vestergaard, Jian'an Luan, Luting Xue, Charles Kooperberg, Rona J. Strawbridge, John-Olov Jansson, Jian Gong, Martina Müller-Nurasyid, L. Adrienne Cupples, Frida Renström, Stephan J. L. Bakker, Ivana Kolcic, Mathias Gorski, Tamara B. Harris, Sandosh Padmanabhan, Stephanie A. Bien, Arthur W. Musk, Cristina Menni, Steve Buyske, Anubha Mahajan, Claudia Schurmann, John Blangero, Natalia Pervjakova, Inês Barroso, Kristin L. Young, Momoko Horikoshi, Robert A. Scott, Ozren Polasek, Shafqat Ahmad, Jeremiah Perez, Stella Trompet, Claude Bouchard, Claudia Langenberg, Paul M. Ridker, Tuomas O. Kilpeläinen, Oddgeir L. Holmen, Tarunveer S. Ahluwalia, Alan F. Wright, Ulf de Faire, Cecilia M. Lindgren, Misa Graff, Jie Huang, Liesbeth Vandenput, Marcel Bruinenberg, Luigi Ferrucci, Johanne Marie Justesen, Audrey Y. Chu, Melanie Waldenberger, Karen L. Mohlke, Ching-Ti Liu, Barbara Thorand, Joseph Hung, Pim van der Harst, Colin A. McKenzie, Sailaja Vedantam, Gitta H. Lubke, Bruna Gigante, Göran Hallmans, Sara Lupoli, Anja Ludolph-Donislawski, Michael Boehnke, Treva Rice, Lori L. Bonnycastle, Daniele Braga, Mika Kähönen, Joel Eriksson, Gonçalo R. Abecasis, Joseph M. Wu, Niels Grarup, Ilja M. Nolte, Jonathan Marchini, Georg Homuth, Pamela A. F. Madden, John Beilby, Andrew D. Johnson, Nanette R. Lee, Caroline Hayward, Unhee Lim, Bamidele O. Tayo, Peter S. Chines, Lynda M. Rose, Amélie Bonnefond, Elena Tremoli, Serena Sanna, David P. Strachan, Barbara McKnight, Narisu Narisu, Anton J. M. de Craen, David R. Weir, Albertine J. Oldehinkel, Jessica Tyrrell, Beverley Balkau, Kirsti Kvaløy, Marie-Claude Vohl, Jennifer A. Smith, Rainer Rauramaa, Andrew C. Heath, Erwin P. Bottinger, Andrew Wong, Günther Silbernagel, Mattias Lorentzon, Philippe Froguel, Uzma Afzal, Tanja B. Grammer, Dabeeru C. Rao, Charlotta Pisinger, Nicola Glorioso, Najaf Amin, Andrew P. Morris, Tanguy Corre, Alan James, Julius S. Ngwa, Jennifer E. Huffman, Gudny Eiriksdottir, Maija Hassinen, Lenore J. Launer, Marit E. Jørgensen, Dorret I. Boomsma, Harry Campbell, Scott Coggeshall, Timothy M. Frayling, Konstantin Strauch, Johanna Kuusisto, David Hadley, Penny Gordon-Larsen, Xuan Deng, Dorothée Thuillier, Albert V. Smith, Jaakko Tuomilehto, Harald Grallert, Lynne J. Hocking, Dan Mellström, M. Carola Zillikens, Lars Lind, Hester M. den Ruijter, Gemma Cadby, Joanne E. Curran, Richard N. Bergman, David J. Stott, Matthias Olden, Veronique Vitart, Robert Luben, Cinzia Sarti, Gert J. de Borst, Lyle J. Palmer, Sven Bergmann, Alexander Teumer, John D. Eicher, Marcus E. Kleber, Marie Loh, Genovefa Kolovou, Iris M. Heid, Gonneke Willemsen, Marie Neergaard Harder, David J. Hunter, Stefania Bandinelli, Francis S. Collins, Hans J. Grabe, Virginia Fisher, John Whitfield, Leo-Pekka Lyytikäinen, Salome Scholtens, Tamuno Alfred, Richard S. Cooper, Jouke-Jan Hottenga, Martina Chittani, Jan A. Staessen, Bernhard K. Krämer, Markku Laakso, Min A. Jhun, Marjo-Riitta Järvelin, Saima Afaq, Rita P. S. Middelberg, Jing Hua Zhao, Toshiko Tanaka, Kent D. Taylor, Rudi G. J. Westendorp, Panagiotis Deloukas, Nina Hutri-Kähönen, Reiner Biffar, Krista Fischer, Leena Kinnunen, Diana Kuh, Jaspal S. Kooner, Caroline S. Fox, Harold Snieder, Pau Navarro, Stéphane Lobbens, Tao Huang, Vilmundur Gudnason, Jacqueline M. Vink, Terrence Forrester, Kari E. North, Annette Peters, Mika Kivimäki, David Schlessinger, Ian Ford, Kristian Hveem, Christopher A. Haiman, Lucia A. Hindorff, Oluf Pedersen, Ingrid B. Borecki, Bruce H. R. Wolffenbuttel, Nicholas J. Wareham, Cornelia M. van Duijn, Lawrence F. Bielak, Loic Le Marchand, Linda S. Adair, Tõnu Esko, Anne U. Jackson, Ying Wu, Eco J. C. de Geus, Jana V. van Vliet-Ostaptchouk, Louis Pérusse, Peter J. van der Most, Ulrike Peters, Magnus Karlsson, Anders Hamsten, Anne E. Justice, Alena Stančáková, Henning Tiemeier, Eric Boerwinkle, Catharina A. Hartman, Claes Ohlsson, Grant W. Montgomery, Elise Lim, Traci M. Bartz, Erik Ingelsson, Martina E. Zimmermann, Laura J. Rasmussen-Torvik, Terho Lehtimäki, Heikki A. Koistinen, Pirjo Komulainen, Damiano Baldassarre, Marten A. Siemelink, Niek Verweij, Gerard Pasterkamp, Markus Juonala, Wei Zhao, Andres Metspalu, Sander W. van der Laan, Tuomo Rankinen, Timo A. Lakka, Yun Ju Sung, Heather M. Stringham, Bruce M. Psaty, Niha Zubair, Stavroula Kanoni, Saskia Haitjema, Bengt Sennblad, Llilda Barata, Morris A. Swertz, Mary F. Feitosa, Tim D. Spector, Paul W. Franks, Qibin Qi, Francesco Cucca, Allan Linneberg, Reija Männikkö, Jonathan Marten, Olli T. Raitakari, Mark I. McCarthy, Joel N. Hirschhorn, Winfried März, Sarah H. Wild, Meena Kumari, Nese Direk, Patricia A. Peyser, Jessica D. Faul, John C. Chambers, Nicholas D. Hastie, Mette Hollensted, Jacek Czajkowski, Daniel I. Chasman, Matthias Nauck, Gérard Waeber, Brendan M. Buckley, Kai Savonen, Judith M. Vonk, Carsten A. Böger, Loic Yengo, Anna Eriksson, Henry Völzke, Pedro Marques-Vidal, Center for Liver, Digestive and Metabolic Diseases (CLDM), Groningen Institute for Organ Transplantation (GIOT), Lifestyle Medicine (LM), Groningen Kidney Center (GKC), Interdisciplinary Centre Psychopathology and Emotion regulation (ICPE), Life Course Epidemiology (LCE), Groningen Institute for Gastro Intestinal Genetics and Immunology (3GI), Groningen Research Institute for Asthma and COPD (GRIAC), Cardiovascular Centre (CVC), Clinicum, Department of Medicine, University of Helsinki, Endokrinologian yksikkö, HUS Internal Medicine and Rehabilitation, Luan, Jian'an [0000-0003-3137-6337], Marten, Jonathan [0000-0001-6916-2014], Langenberg, Claudia [0000-0002-5017-7344], Luben, Robert [0000-0002-5088-6343], Ong, Kenneth [0000-0003-4689-7530], Wareham, Nicholas [0000-0003-1422-2993], Barroso, Ines [0000-0001-5800-4520], Apollo - University of Cambridge Repository, Læknadeild (HÍ), Faculty of Medicine (UI), Heilbrigðisvísindasvið (HÍ), School of Health Sciences (UI), Háskóli Íslands, University of Iceland, Biological Psychology, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, APH - Mental Health, APH - Health Behaviors & Chronic Diseases, APH - Methodology, APH - Personalized Medicine, Epidemiology, Erasmus MC other, Medical Microbiology & Infectious Diseases, Internal Medicine, Child and Adolescent Psychiatry / Psychology, and Psychiatry

Subjects
0301 basic medicine, Netherlands Twin Register (NTR), Medicin och hälsovetenskap, Offita, Chemistry(all), Epidemiology, General Physics and Astronomy, Genome-wide association study, methods [Genome-Wide Association Study], Biochemistry, Genome-wide association studies, Medical and Health Sciences, Body Mass Index, genetics [Obesity], Genetics research, IMPUTATION, Body Fat Distribution, genetics [Genetic Predisposition to Disease], OXIDATIVE STRESS, POPULATION, Adiposity, METABOLIC SYNDROME, Genetics, education.field_of_study, Multidisciplinary, Smoking, Public Health, Global Health, Social Medicine and Epidemiology, genetics [Smoking], ASSOCIATION, 3142 Public health care science, environmental and occupational health, 3. Good health, Multidisciplinary Sciences, DEFICIENCY, Phenotype, ADDICTION, Science & Technology - Other Topics, Medical genetics, ddc:500, Waist Circumference, Reykingar, genetics [Adiposity], Adult, medicine.medical_specialty, Science, Quantitative Trait Loci, Population, genetics [Waist Circumference], Accounting, Biology, Quantitative trait locus, Physics and Astronomy(all), Polymorphism, Single Nucleotide, Article, General Biochemistry, Genetics and Molecular Biology, 03 medical and health sciences, SDG 3 - Good Health and Well-being, GWAS, obesity, smoking, MD Multidisciplinary, Genetic predisposition, medicine, Journal Article, Erfðafræði, Humans, Genetic Predisposition to Disease, Obesity, education, Genetic association, Science & Technology, VITAMIN-C, genetics [Quantitative Trait Loci], Waist-Hip Ratio, business.industry, Biochemistry, Genetics and Molecular Biology(all), Epistasis, Genetic, Rannsóknir, General Chemistry, ta3121, R1, GENE, Folkhälsovetenskap, global hälsa, socialmedicin och epidemiologi, MICE, 030104 developmental biology, 3121 General medicine, internal medicine and other clinical medicine, business, Body mass index, Developmental Psychopathology, Imputation (genetics), Genetics and Molecular Biology(all), Genome-Wide Association Study
Abstract

Few genome-wide association studies (GWAS) account for environmental exposures, like smoking, potentially impacting the overall trait variance when investigating the genetic contribution to obesity-related traits. Here, we use GWAS data from 51,080 current smokers and 190,178 nonsmokers (87% European descent) to identify loci influencing BMI and central adiposity, measured as waist circumference and waist-to-hip ratio both adjusted for BMI. We identify 23 novel genetic loci, and 9 loci with convincing evidence of gene-smoking interaction (GxSMK) on obesity-related traits. We show consistent direction of effect for all identified loci and significance for 18 novel and for 5 interaction loci in an independent study sample. These loci highlight novel biological functions, including response to oxidative stress, addictive behaviour, and regulatory functions emphasizing the importance of accounting for environment in genetic analyses. Our results suggest that tobacco smoking may alter the genetic susceptibility to overall adiposity and body fat distribution., A full list of acknowledgments appears in the Supplementary Note 4. Co-author A.J.M.d.C. recently passed away while this work was in process. This work was performed under the auspices of the Genetic Investigation of ANthropometric Traits (GIANT) consortium. We acknowledge the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) Consortium for encouraging CHARGE studies to participate in this effort and for the contributions of CHARGE members to the analyses conducted for this research. Funding for this study was provided by the Aase and Ejner Danielsens Foundation; Academy of Finland (41071, 77299, 102318, 110413, 117787, 121584, 123885, 124243, 124282, 126925, 129378, 134309, 286284); Accare Center for Child and Adolescent Psychiatry; Action on Hearing Loss (G51); Agence Nationale de la 359 Recherche; Agency for Health Care Policy Research (HS06516); ALF/LUA research grant in Gothenburg; ALFEDIAM; ALK-Abelló A/S; Althingi; American Heart Association (13POST16500011); Amgen; Andrea and Charles Bronfman Philanthropies; Ardix Medical; Arthritis Research UK; Association Diabète Risque Vasculaire; Australian National Health and Medical Research Council (241944, 339462, 389875, 389891, 389892, 389927, 389938, 442915, 442981, 496739, 552485, 552498); Avera Institute; Bayer Diagnostics; Becton Dickinson; BHF (RG/14/5/30893); Boston Obesity Nutrition Research Center (DK46200), Bristol-Myers Squibb; British Heart Foundation (RG/10/12/28456, RG2008/08, RG2008/014, SP/04/002); Medical Research Council of Canada; Canadian Institutes for Health Research (FRCN-CCT-83028); Cancer Research UK; Cardionics; Cavadis B.V., Center for Medical Systems Biology; Center of Excellence in Genomics; CFI; CIHR; City of Kuopio; CNAMTS; Cohortes Santé TGIR; Contrat de Projets État-Région; Croatian Science Foundation (8875); Danish Agency for Science, Technology and Innovation; Danish Council for Independent Research (DFF-1333-00124, DFF-1331-00730B); County Council of Dalarna; Dalarna University; Danish Council for Strategic Research; Danish Diabetes Academy; Danish Medical Research Council; Department of Health, UK; Development Fund from the University of Tartu (SP1GVARENG); Diabetes Hilfs- und Forschungsfonds Deutschland; Diabetes UK; Diabetes Research and Wellness Foundation Fellowship; Donald W. Reynolds Foundation; Dr Robert Pfleger-Stiftung; Dutch Brain Foundation; Dutch Diabetes Research Foundation; Dutch Inter University Cardiology Institute; Dutch Kidney Foundation (E033); Dutch Ministry of Justice; the DynaHEALTH action No. 633595, Economic Structure Enhancing Fund of the Dutch Government; Else Kröner-Fresenius-Stiftung (2012_A147, P48/08//A11/08); Emil Aaltonen Foundation; Erasmus University Medical Center Rotterdam; Erasmus MC and Erasmus University Rotterdam; the Municipality of Rotterdam; Estonian Government (IUT20-60, IUT24-6); Estonian Research Roadmap through the Estonian Ministry of Education and Research (3.2.0304.11-0312); European Research Council (ERC Starting Grant and 323195:SZ-245 50371-GLUCOSEGENES-FP7-IDEAS-ERC); European Regional Development Fund; European Science Foundation (EU/QLRT-2001-01254); European Commission (018947, 018996, 201668, 223004, 230374, 279143, 284167, 305739, BBMRI-LPC-313010, HEALTH-2011.2.4.2-2-EU-MASCARA, HEALTH-2011-278913, HEALTH-2011-294713-EPLORE, HEALTH-F2-2008-201865-GEFOS, HEALTH-F2-2013-601456, HEALTH-F4-2007-201413, HEALTH-F4-2007-201550-HYPERGENES, HEALTH-F7-305507 HOMAGE, IMI/115006, LSHG-CT-2006-018947, LSHG-CT-2006-01947, LSHM-CT-2004-005272, LSHM-CT-2006-037697, LSHM-CT-2007-037273, QLG1-CT-2002-00896, QLG2-CT-2002-01254); Faculty of Biology and Medicine of Lausanne; Federal Ministry of Education and Research (01ZZ0103, 01ZZ0403, 01ZZ9603, 03IS2061A, 03ZIK012); Federal State of Mecklenburg-West Pomerania; Fédération Française de Cardiologie; Finnish Cultural Foundation; Finnish Diabetes Association; Finnish Foundation of Cardiovascular Research; Finnish Heart Association; Fondation Leducq; Food Standards Agency; Foundation for Strategic Research; French Ministry of Research; FRSQ; Genetic Association Information Network (GAIN) of the Foundation for the NIH; German Federal Ministry of Education and Research (BMBF, 01ER1206, 01ER1507); GlaxoSmithKline; Greek General Secretary of Research and Technology; Göteborg Medical Society; Health and Safety Executive; Healthcare NHS Trust; Healthway; Western Australia; Heart Foundation of Northern Sweden; Helmholtz Zentrum München—German Research Center for Environmental Health; Hjartavernd; Ingrid Thurings Foundation; INSERM; InterOmics (PB05 MIUR-CNR); INTERREG IV Oberrhein Program (A28); Interuniversity Cardiology Institute of the Netherlands (ICIN, 09.001); Italian Ministry of Health (ICS110.1/RF97.71); Italian Ministry of Economy and Finance (FaReBio di Qualità); Marianne and Marcus Wallenberg Foundation; the Ministry of Health, Welfare and Sports, the Netherlands; J.D.E. and Catherine T, MacArthur Foundation Research Networks on Successful Midlife Development and Socioeconomic Status and Health; Juho Vainio Foundation; Juvenile Diabetes Research Foundation International; KfH Stiftung Präventivmedizin e.V.; King's College London; Knut and Alice Wallenberg Foundation; Kuopio University Hospital; Kuopio, Tampere and Turku University Hospital Medical Funds (X51001); La Fondation de France; Leenaards Foundation; Lilly; LMUinnovativ; Lundberg Foundation; Magnus Bergvall Foundation; MDEIE; Medical Research Council UK (G0000934, G0601966, G0700931, MC_U106179471, MC_UU_12019/1); MEKOS Laboratories; Merck Santé; Ministry for Health, Welfare and Sports, The Netherlands; Ministry of Cultural Affairs of Mecklenburg-West Pomerania; Ministry of Economic Affairs, The Netherlands; Ministry of Education and Culture of Finland (627;2004-2011); Ministry of Education, Culture and Science, The Netherlands; Ministry of Science, Education and Sport in the Republic of Croatia (108-1080315-0302); MRC centre for Causal Analyses in Translational Epidemiology; MRC Human Genetics Unit; MRC-GlaxoSmithKline pilot programme (G0701863); MSD Stipend Diabetes; National Institute for Health Research; Netherlands Brain Foundation (F2013(1)-28); Netherlands CardioVascular Research Initiative (CVON2011-19); Netherlands Genomics Initiative (050-060-810); Netherlands Heart Foundation (2001 D 032, NHS2010B280); Netherlands Organization for Scientific Research (NWO) and Netherlands Organisation for Health Research and Development (ZonMW) (56-464-14192, 60-60600-97-118, 100-001-004, 261-98-710, 400-05-717, 480-04-004, 480-05-003, 481-08-013, 904-61-090, 904-61-193, 911-11-025, 985-10-002, Addiction-31160008, BBMRI–NL 184.021.007, GB-MaGW 452-04-314, GB-MaGW 452-06-004, GB-MaGW 480-01-006, GB-MaGW 480-07-001, GB-MW 940-38-011, Middelgroot-911-09-032, NBIC/BioAssist/RK 2008.024, Spinozapremie 175.010.2003.005, 175.010.2007.006); Neuroscience Campus Amsterdam; NHS Foundation Trust; National Institutes of Health (1RC2MH089951, 1Z01HG000024, 24152, 263MD9164, 263MD821336, 2R01LM010098, 32100-2, 32122, 32108, 5K99HL130580-02, AA07535, AA10248, AA11998, AA13320, AA13321, AA13326, AA14041, AA17688, AG13196, CA047988, DA12854, DK56350, DK063491, DK078150, DK091718, DK100383, DK078616, ES10126, HG004790, HHSN268200625226C, HHSN268200800007C, HHSN268201200036C, HHSN268201500001I, HHSN268201100046C, HHSN268201100001C, HHSN268201100002C, HHSN268201100003C, HHSN268201100004C, HHSN271201100004C, HL043851, HL45670, HL080467, HL085144, HL087660, HL054457, HL119443, HL118305, HL071981, HL034594, HL126024, HL130114, KL2TR001109, MH66206, MH081802, N01AG12100, N01HC55015, N01HC55016, N01C55018, N01HC55019, N01HC55020, N01HC55021, N01HC55022, N01HC85079, N01HC85080, N01HC85081, N01HC85082, N01HC85083, N01HC85086, N01HC95159, N01HC95160, N01HC95161, N01HC95162, N01HC95163, N01HC95164, N01HC95165, N01HC95166, N01HC95167, N01HC95168, N01HC95169, N01HG65403, N01WH22110, N02HL6‐4278, N01-HC-25195, P01CA33619, R01HD057194, R01HD057194, R01AG023629, R01CA63, R01D004215701A, R01DK075787, R01DK062370, R01DK072193, R01DK075787, R01DK089256, R01HL53353, R01HL59367, R01HL086694, R01HL087641, R01HL087652, R01HL103612, R01HL105756, R01HL117078, R01HL120393, R03 AG046389, R37CA54281, RC2AG036495, RC4AG039029, RPPG040710371, RR20649, TW008288, TW05596, U01AG009740, U01CA98758, U01CA136792, U01DK062418, U01HG004402, U01HG004802, U01HG007376, U01HL080295, UL1RR025005, UL1TR000040, UL1TR000124, UL1TR001079, 2T32HL007055-36, T32GM074905, HG002651, HL084729, N01-HC-25195, UM1CA182913); NIH, National Institute on Aging (Intramural funding, NO1-AG-1-2109); Northern Netherlands Collaboration of Provinces; Novartis Pharma; Novo Nordisk; Novo Nordisk Foundation; Nutricia Research Foundation (2016-T1); ONIVINS; Parnassia Bavo group; Pierre Fabre; Province of Groningen; Päivikki and Sakari Sohlberg Foundation; Påhlssons Foundation; Paavo Nurmi Foundation; Radboud Medical Center Nijmegen; Research Centre for Prevention and Health, the Capital Region of Denmark; the Research Institute for Diseases in the Elderly; Research into Ageing; Robert Dawson Evans Endowment of the Department of Medicine at Boston University School of Medicine and Boston Medical Center; Roche; Royal Society; Russian Foundation for Basic Research (NWO-RFBR 047.017.043); Rutgers University Cell and DNA Repository (NIMH U24 MH068457-06); Sanofi-Aventis; Scottish Government Health Directorates, Chief Scientist Office (CZD/16/6); Siemens Healthcare; Social Insurance Institution of Finland (4/26/2010); Social Ministry of the Federal State of Mecklenburg-West Pomerania; Société Francophone du 358 Diabète; State of Bavaria; Stiftelsen för Gamla Tjänarinnor; Stockholm County Council (560183, 592229); Strategic Cardiovascular and Diabetes Programmes of Karolinska Institutet and Stockholm County Council; Stroke Association; Swedish Diabetes Association; Swedish Diabetes Foundation (2013-024); Swedish Foundation for Strategic Research; Swedish Heart-Lung Foundation (20120197, 20150711); Swedish Research Council (0593, 8691, 2012-1397, 2012-1727, and 2012-2215); Swedish Society for Medical Research; Swiss Institute of Bioinformatics; Swiss National Science Foundation (3100AO-116323/1, 31003A-143914, 33CSCO-122661, 33CS30-139468, 33CS30-148401, 51RTP0_151019); Tampere Tuberculosis Foundation; Technology Foundation STW (11679); The Fonds voor Wetenschappelijk Onderzoek Vlaanderen, Ministry of the Flemish Community (G.0880.13, G.0881.13); The Great Wine Estates of the Margaret River Region of Western Australia; Timber Merchant Vilhelm Bangs Foundation; Topcon; Tore Nilsson Foundation; Torsten and Ragnar Söderberg's Foundation; United States – Israel Binational Science Foundation (Grant 2011036), Umeå University; University Hospital of Regensburg; University of Groningen; University Medical Center Groningen; University of Michigan; University of Utrecht; Uppsala Multidisciplinary Center for Advanced Computational Science (UPPMAX) (b2011036); Velux Foundation; VU University’s Institute for Health and Care Research; Västra Götaland Foundation; Wellcome Trust (068545, 076113, 079895, 084723, 088869, WT064890, WT086596, WT098017, WT090532, WT098051, 098381); Wissenschaftsoffensive TMO; Yrjö Jahnsson Foundation; and Åke Wiberg Foundation. The views expressed in this manuscript are those of the authors and do not necessarily represent the views of the National Heart, Lung, and Blood Institute (NHLBI); the National Institutes of Health (NIH); or the U.S. Department of Health and Human Services.

Published
2017
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10. Interleukin-1β/Interleukin10 Ratio Produced by Monocytes as a Biomarker of Neuroinflammation in Autism

Author

Harumi Jyonouchi, Lee Geng, and Steve Buyske

Subjects
0301 basic medicine, Innate immune system, business.industry, medicine.medical_treatment, Irritability, medicine.disease, behavioral disciplines and activities, 03 medical and health sciences, Lethargy, 030104 developmental biology, 0302 clinical medicine, Cytokine, Stereotypy, mental disorders, Immunology, medicine, Autism, Biomarker (medicine), medicine.symptom, business, 030217 neurology & neurosurgery, Neuroinflammation
Abstract

Objective: Innate immune abnormalities have been frequently reported in children with autism spectrum disorders (ASD), but a role of innate immunity in ASD is not well understood. This study explored a possible role of innate immunity in ASD clinical features and co-morbidities.Methods: Purified peripheral blood monocytes (PBMo) from ASD (N=125) and non-ASD (N=36) subjects were cultured overnight with or without stimulants of innate immunity, and production of pro-inflammatory and counter-regulator cytokines were assessed. Behavioral symptoms were assessed by aberrant behavioral checklist (ABC) at the time of PBMo sampling.Results: ASD PBMo revealed highly variable IL-1β/IL-10 ratios, in contrast to a tight range of IL-1β/IL-10 ratios in non-ASD control cells. There was no association between cytokine levels or IL-1β/IL-10 ratios and ABC subscale scores when ASD data was analyzed, as a whole. However, when ASD data was separated into high, low, or normal (equivalent to controls) IL-1β/IL-1 ratio groups, IL-1β levels were positively associated with stereotypy in the high ratio group. In contrast, IL-1β and IL-10 levels were negatively associated with irritability, lethargy, and hyperactivity in the normal ratio group. The low ratio group revealed a negative association between IL-1β levels and lethargy. When longitudinal changes in cytokine production from PBMo were studied in selected ASD subjects, fluctuating ratios were found in ASD subjects with deviated (high or low) IL-1β/IL-10 ratios, but ratios remained stable in ASD subjects with normal ratios. ASD subjects with deviated ratios were found to have higher frequencies of non-IgE mediated food allergy (NFA) (p

Published
2017
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11. Abstract P252: Generalization and Fine Mapping of PR Interval Loci in Hispanics: The Population Architecture Using Genomics and Epidemiology (PAGE) Study

Author

Suzette J. Bielinski, Nona Sotoodehnia, Elsayed Z. Soliman, Mercedes R. Carnethon, Charles Kooperberg, Donald M. Lloyd-Jones, Janina M. Jeff, Cara L. Carty, Amanda A. Seyerle, Susan R. Heckbert, Jerome I. Rotter, Bruce M. Psaty, Jian Gong, Christina L. Wassel, Christy L. Avery, David Duggan, Chunyuan Wu, Peter M. Okin, Dana C. Crawford, Marco V Perez, Lucia A. Hindorff, Sanjiv J. Shah, Myriam Fornage, Ralph V. Shohet, and Steve Buyske

Subjects
Genetics, Linkage disequilibrium, education.field_of_study, business.industry, Population, Locus (genetics), Single-nucleotide polymorphism, Physiology (medical), Genetic model, Medicine, SNP, PR interval, Cardiology and Cardiovascular Medicine, business, education, Genetic association
Abstract

PR interval (PR) prolongation is a predictor of atrial fibrillation, a common cardiac arrhythmia, and is an established risk factor for pacemaker implantation, heart failure, stroke, and all-cause mortality. Previous genome-wide association studies in European (EU) and African (AA) descent populations have identified multiple loci associated with PR. However, it is unclear whether these loci are relevant in other racial groups, including Hispanic/Latinos (HL). Extending studies to include admixed populations such as HL also provides the potential to narrow regions associated with PR and identify population specific variants. Therefore, we evaluated 1,135 SNPs from four previously identified PR loci ( SCN5A, SCN10A, CAV1-CAV2, and TBX5-TBX3 ), fine-mapped on the Illumina Metabochip for association with PR. Associations were examined using linear regression assuming an additive genetic model and adjusting for global ancestry and clinical covariates (age, sex, RR interval, body mass index, height, systolic blood pressure) in 11,800 HL participants from participating studies of the Population Architecture using Genomics and Epidemiology (PAGE) consortia. Three of the four loci ( SCN5A, SCN10A, and CAV1-CAV2 ) generalized to HL populations ( P 2 >0.2 with EU-identified index SNPs). At each of these loci, we identified SNPs with stronger evidence of association with PR than the EU-identified index SNP when examined in the HL population ( SCN5A : rs7374540; SCN10A : rs6801957; CAV-CAV2 : rs717957). Conditional analyses also identified two additional independent SNPs at each of the three generalized loci ( SCN5A : rs3796387, rs9861242; SCN10A : rs10428132, rs7433723; CAV1-CAV2 : rs3801995, rs3807994), representing potential secondary signals. Furthermore, linkage disequilibrium (LD) patterns in Hispanics enabled the narrowing of the regions flanking the EU-identified index SNPs. For example, at the CAV1-CAV2 locus, HL LD patterns indicated that seven SNPs were in LD with rs3807989, the EU-identified index SNP, compared to 17 SNPs that were in LD with rs3807989 when applying EU LD patterns, reducing the size of the region by 71 kilobases. Finally, we examined evidence for population specific signals outside of the specific regions identified in EU populations which were associated with PR in Hispanics by focusing on SNPs uncorrelated with the EU index signals. At all four loci, multiple SNPs had evidence of association independent of the signals examined based on EU results. In conclusion, the same genetic loci that influence PR in European descent populations are also important in Hispanic populations, although we detected evidence for population specific SNPs. These results emphasize the importance of examining genetic associations in diverse populations in order to narrow the genomic interval for future functional interrogation.

Published
2014
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12. Abstract MP60: Fine Mapping of Body Fat Distribution Loci in African American Populations: The Population Architecture Using Genomics and Epidemiology (PAGE) Study

Author

Ulrike Peters, Richard S. Cooper, Charles Kooperberg, Carmen R. Isasi, Lynne R. Wilkens, JoAnn E. Manson, Jian Gong, Lewis H. Kuller, Mark Leppert, Steve Buyske, Marguerite R. Irvin, Kari E. North, Rachel H. Mackey, Praveen Sethupathy, Petra Buzkova, Lucia A. Hindorff, Misa Graff, Sachiko Yoneyama, Martha L. Daviglus, Cora E. Lewis, Denise K. Houston, Unhee Lim, C. Charles Gu, Rongling Li, and Myriam Fornage

Subjects
Genetics, education.field_of_study, business.industry, Population, Genomics, Single-nucleotide polymorphism, Locus (genetics), Genome-wide association study, symbols.namesake, Bonferroni correction, Physiology (medical), symbols, Medicine, SNP, Cardiology and Cardiovascular Medicine, business, education, Genetic association
Abstract

Introduction: Waist-to-hip ratio (WHR) is associated with cardiometabolic disease and its risk factors independent of body-mass-index (BMI). Previous GWAS on WHR adjusting for BMI (WHR’) have identified several SNPs but mainly among European descent populations (EA SNPs). While these SNPs point to general loci of interest, they are not likely the causal variants. Expanding analyses of these loci to other race and ethnic populations can dually assess whether these loci apply to more diverse populations and utilize differences in genetic linkage disequilibrium (LD) patterns to narrow the region containing the causal variant. Objective: To better capture genetic variants of WHR’ in self-identified African Americans (AA) within 14 loci containing previously reported WHR’ EA SNPs. Methods: Up to 14,322 AA participants (aged 20-93 years, 61% female) were included from seven studies. Individuals were genotyped using the Illumina iSelect Metabochip array consisting of nearly 200,000 SNPs enriched to fine map GWAS signals of cardiometabolic traits, including the 14 WHR’ loci. We modeled WHR’ adjusting for age, sex, study site, and the first three ancestry principle components for each study and conducted an inverse variance weighted meta-analysis. Variants reaching a Bonferroni adjusted threshold of P Results: Within the 14 regions, seven loci (in or near TBX15-WARS2, DNM3-PIGC, GRB14, NISCH-STAB1, ADAMTS9, VEGFA, and RSPO3 ) contained a significant AA SNP. In the GRB14 locus, the AA SNP (rs10195252, P =1.93x10 -06 ) was the same as the EA SNP. Among four of the seven loci, the AA SNPs (rs12096179 near TBX15-WARS2, rs2371767 in ADAMTS9 , rs1358990 near VEGFA, and rs9385487 in RSPO3 ) were not independent of the EA SNPs (LD r 2 ≥0.3), but were more significant in AA, possibly narrowing the region containing the functional variant. Two AA SNPs (rs11715796 in NISCH-STAB1 and rs4916251 near DNM3-PIGC ) suggesting independence from the EA SNP (r 2 NISCH-STAB1 had a stronger association after conditioning on the EA SNP, signifying independence. The AA SNP near DNM3-PIGC was less significant after conditioning, indicating it points to the same signal as the EA SNP. We have identified participants from additional cohorts for inclusion in future analyses and will conduct a sex-stratified analysis to further explore WHR’ loci among AA. Conclusions: Examination of 14 previously identified loci for WHR’ in AA individuals revealed one novel signal in NISCH-STAB1 . Five additional non-independent AA SNPs suggested a narrower region containing the WHR’ altering variant based on the LD structure differences between EA and AA. These findings highlight the value in expanding genetic association studies to other race and ethnic populations.

Published
2014
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13. HLA DR and DQ alleles and haplotypes associated with clinical response to glatiramer acetate in multiple sclerosis

Author

Michael Kaufman, Steve Buyske, Kouichi Ito, Reuben M. Valenzuela, Mary Ann Picone, and Suhayl Dhib-Jalbut

Subjects
Expanded Disability Status Scale, business.industry, Multiple sclerosis, Haplotype, General Medicine, medicine.disease, Neurology, Immunology, HLA-DQ, HLA-DR, medicine, Neurology (clinical), Typing, Glatiramer acetate, business, Prospective cohort study, medicine.drug
Abstract

Clinical response to immunomodulatory therapies in multiple sclerosis (MS) is variable among patients. Currently, there are no validated biomarkers of clinical response to any of the approved treatments for MS. The objective of this study was to determine if HLA-class II alleles predict the clinical response to glatiramer acetate (GA).This was a prospective study of 64 MS patients with relapsing-remitting disease. Patients were HLA-typed and classified as GA-responders or non-responders after 2 years of treatment based on a clinical criterion. Statistical models were used to determine whether HLA-DR and DQ alleles and haplotypes predict the clinical response to GA.Tests of association of response singled out four alleles and two haplotypes with nominal p0.01. The presence of alleles DR15 or DQ6 or the absence of DR17 and DQ2 alleles was associated with favorable clinical response. The presence of the DR15-DQ6 haplotype and the absence of the DR17-DQ2 haplotype were also associated with favorable treatment response. A best fitting two-haplotype model resulted in the identification of three prognostic categories (good, neutral, and poor). A DR15-DQ6 positive but DR17-DQ2 negative combination was strongly predictive of a favorable clinical response (71%). Conversely, a DR15-DQ6 negative but DR17-DQ2 positive combination was strongly predictive of poor clinical response to GA (17%).HLA-DR and DQ typing may prove to be useful biomarkers of predicting response to GA in MS and may help select patients appropriate for this treatment.

Published
2012

15. Abstract 5064: Pleiotropy analysis identifies a novel prostate cancer variant at 6p21.33: The PAGE, PRACTICAL, and BPC3 Consortia

Author

José Luis Ambite, Daniele Campa, Christopher A. Haiman, S. Lani Park, Shelly-Ann Love, Fredrick R. Schumacher, Loic Le Marchand, Steve Buyske, Ying Han, Lucia A. Hindorff, Iona Cheng, Jay H. Fowke, Anne M. Butler, Konstantinos K. Tsilidis, Lynne R. Wilkens, Federico Canzian, William S. Bush, and Logan Dumitrescu

Subjects
Cancer Research, education.field_of_study, Framingham Risk Score, business.industry, Population, Follicular lymphoma, Cancer, medicine.disease, Bioinformatics, medicine.disease_cause, Prostate cancer, Oncology, Pleiotropy, Medicine, business, education, Carcinogenesis, Genetic association
Abstract

Background: Genome-wide association studies have identified hundreds of susceptibility loci for various cancer sites including prostate cancer. Several of the risk loci have demonstrated pleiotropic effects with multiple cancers, suggesting shared biological pathways in carcinogenesis. In the present study, we systematically investigated the effects of other cancer-associated variants on prostate cancer risk. Methods: We examined 196 genetic risk variants identified for 18 cancer and cancer-related traits in a total of 28,135 prostate cancer cases and 37,218 controls. This large meta-analysis of multiethnic samples was assembled from three consortia: Population Architecture using Genetics and Epidemiology (PAGE), Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) and Breast and Prostate Cancer Cohort Consortium (BPC3). Study- and ethnic-specific logistic regressions results were combined through fixed-effect meta-analysis to evaluate the association between each variant and prostate cancer risk, applying a Bonferroni-corrected significance threshold of 2.6×10-4. We also assessed the cumulative effect of other cancer risk variants on prostate cancer susceptibility via risk score analysis. Results: Three variants, RTEL rs6010620, TERT rs2853676 and HLA rs6457327, demonstrated statistically significant associations with prostate cancer risk after correcting for multiple comparisons. Originally reported as a follicular lymphoma risk variant, rs6457327 was associated with prostate cancer at the genome-wide significant level (meta-analysis OR=0.93, 95% CI: 0.91-0.96; p=4.5×10-8). The cumulative genetic risk score for risk variants of other cancers demonstrated a significant effect on prostate cancer risk (p=0.021). Conclusions: This systematic pleiotropy analysis identified HLA as a novel susceptibility locus for prostate cancer in a large multiethnic population. The genetic variant with pleiotropic effects on both follicular lymphoma and prostate cancer provides evidence for shared etiologic mechanisms between prostate cancer and other cancer sites. Citation Format: Ying Han, Shelly-Ann Love, William S. Bush, Daniele Campa, Anne M. Butler, Logan Dumitrescu, Konstantinos Tsilidis, Iona Cheng, Lynne R. Wilkens, Jay H. Fowke, Jose Luis Ambite, Steve Buyske, S. Lani Park, The PRACTICAL Consortium, The BPC3 Consortium, Christopher A. Haiman, Loic Le Marchand, Lucia A. Hindorff, Federico Canzian, Fredrick R. Schumacher. Pleiotropy analysis identifies a novel prostate cancer variant at 6p21.33: The PAGE, PRACTICAL, and BPC3 Consortia. [abstract]. In: Proceedings of the 105th Annual Meeting of the American Association for Cancer Research; 2014 Apr 5-9; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2014;74(19 Suppl):Abstract nr 5064. doi:10.1158/1538-7445.AM2014-5064

Published
2014
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