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Liu J, Wei B, Zhang Y, You Y, Zhi Y. Association between PRKG1 gene and gene-environment interactions with pediatric asthma. J Asthma 2024; 61:754-761. [PMID: 38193459 DOI: 10.1080/02770903.2024.2303763] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/04/2023] [Accepted: 01/07/2024] [Indexed: 01/10/2024]
Abstract
OBJECTIVE To investigate the relationship between single nucleotide polymorphisms (SNPs) of cGMP-dependent protein kinase I (PRKG1) gene and gene-environment interactions with bronchial asthma in children. METHODS 109 asthma patients and 158 healthy controls from the General Hospital of Northern Theater Command were enrolled, based case-control study. The iMLDR® multiple SNP typing technique was applied to detect the genotypes of rs7903366, rs7081864, rs7070958 and rs7897633 in PRKG1 gene. The percentage of eosinophils (EOS%) in peripheral blood and serum immunoglobulin E (IgE) in the case group were also measured. Gene-environment interactions were examined using the generalized multi-factor dimensionality reduction (GMDR) method. RESULTS There were polymorphisms in four SNPs of PRKG1 gene in the case and control groups. The genotype and allele frequencies distribution of rs7897633 demonstrated statistical significance (p < 0.05). There were no statistically significant differences in EOS% and IgE among genotypes at the four SNPs of PRKG1 gene (p > 0.05). The haplotypes CAGA and TGAC presented significant association with asthma risk (p < 0.05). The four-factor model indicated a potential gene-environment interaction in rs7897633, allergen exposure, residence, and environmental tobacco smoke (ETS) exposure (p < 0.05). CONCLUSIONS The rs7897633 in PRKG1 gene was associated with susceptibility to childhood asthma, and C allele is a protective factor. The haplotype CAGA had a protective effect against asthma risk and TGAC was linked to the high risk of developing asthma. Moreover, the interaction of rs7897633, allergen exposure, residence, and ETS exposure conferred susceptibility to childhood asthma.
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Affiliation(s)
- Jun Liu
- Department of Neonatology, General Hospital of Northern Theater Command, Shenyang, P.R. China
- Post-graduate College, China Medical University, Shenyang, P.R. China
| | - Bing Wei
- Department of Neonatology, General Hospital of Northern Theater Command, Shenyang, P.R. China
| | - Yuxuan Zhang
- Department of Neonatology, General Hospital of Northern Theater Command, Shenyang, P.R. China
| | - Yuan You
- Department of Neonatology, General Hospital of Northern Theater Command, Shenyang, P.R. China
| | - Yanjie Zhi
- Department of Neonatology, General Hospital of Northern Theater Command, Shenyang, P.R. China
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Perez-Garcia J, Pino-Yanes M, Plender EG, Everman JL, Eng C, Jackson ND, Moore CM, Beckman KB, Medina V, Sharma S, Winnica DE, Holguin F, Rodríguez-Santana J, Villar J, Ziv E, Seibold MA, Burchard EG. Epigenomic response to albuterol treatment in asthma-relevant airway epithelial cells. Clin Epigenetics 2023; 15:156. [PMID: 37784136 PMCID: PMC10546710 DOI: 10.1186/s13148-023-01571-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2023] [Accepted: 09/25/2023] [Indexed: 10/04/2023] Open
Abstract
BACKGROUND Albuterol is the first-line asthma medication used in diverse populations. Although DNA methylation (DNAm) is an epigenetic mechanism involved in asthma and bronchodilator drug response (BDR), no study has assessed whether albuterol could induce changes in the airway epithelial methylome. We aimed to characterize albuterol-induced DNAm changes in airway epithelial cells, and assess potential functional consequences and the influence of genetic variation and asthma-related clinical variables. RESULTS We followed a discovery and validation study design to characterize albuterol-induced DNAm changes in paired airway epithelial cultures stimulated in vitro with albuterol. In the discovery phase, an epigenome-wide association study using paired nasal epithelial cultures from Puerto Rican children (n = 97) identified 22 CpGs genome-wide associated with repeated-use albuterol treatment (p < 9 × 10-8). Albuterol predominantly induced a hypomethylation effect on CpGs captured by the EPIC array across the genome (probability of hypomethylation: 76%, p value = 3.3 × 10-5). DNAm changes on the CpGs cg23032799 (CREB3L1), cg00483640 (MYLK4-LINC01600), and cg05673431 (KSR1) were validated in nasal epithelia from 10 independent donors (false discovery rate [FDR] < 0.05). The effect on the CpG cg23032799 (CREB3L1) was cross-tissue validated in bronchial epithelial cells at nominal level (p = 0.030). DNAm changes in these three CpGs were shown to be influenced by three independent genetic variants (FDR < 0.05). In silico analyses showed these polymorphisms regulated gene expression of nearby genes in lungs and/or fibroblasts including KSR1 and LINC01600 (6.30 × 10-14 ≤ p ≤ 6.60 × 10-5). Additionally, hypomethylation at the CpGs cg10290200 (FLNC) and cg05673431 (KSR1) was associated with increased gene expression of the genes where they are located (FDR < 0.05). Furthermore, while the epigenetic effect of albuterol was independent of the asthma status, severity, and use of medication, BDR was nominally associated with the effect on the CpG cg23032799 (CREB3L1) (p = 0.004). Gene-set enrichment analyses revealed that epigenomic modifications of albuterol could participate in asthma-relevant processes (e.g., IL-2, TNF-α, and NF-κB signaling pathways). Finally, nine differentially methylated regions were associated with albuterol treatment, including CREB3L1, MYLK4, and KSR1 (adjusted p value < 0.05). CONCLUSIONS This study revealed evidence of epigenetic modifications induced by albuterol in the mucociliary airway epithelium. The epigenomic response induced by albuterol might have potential clinical implications by affecting biological pathways relevant to asthma.
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Grants
- R01 ES015794 NIEHS NIH HHS
- R01 HL120393 NHLBI NIH HHS
- R01ES015794, R21ES24844 NIEHS NIH HHS
- UM1 HG008901 NHGRI NIH HHS
- R01MD010443, R56MD013312 NIMHD NIH HHS
- R01 HL135156 NHLBI NIH HHS
- R01 HL128439 NHLBI NIH HHS
- R01 HL117004 NHLBI NIH HHS
- R21 ES024844 NIEHS NIH HHS
- R01 HL117626 NHLBI NIH HHS
- R56 MD013312 NIMHD NIH HHS
- R01 MD010443 NIMHD NIH HHS
- R01 HL155024 NHLBI NIH HHS
- R01HL155024-01, HHSN268201600032I, 3R01HL-117626-02S1, HHSN268201800002I, 3R01HL117004-02S3, 3R01HL-120393-02S1, R01HL117004, R01HL128439, R01HL135156, X01HL134589 NHLBI NIH HHS
- HHSN268201600032C NHLBI NIH HHS
- U24 HG008956 NHGRI NIH HHS
- Ministerio de Universidades
- Ministerio de Ciencia e Innovación
- Instituto de Salud Carlos III
- National Heart, Lung, and Blood Institute
- National Human Genome Research Institute
- National Institute of Environmental Health Sciences
- National Institute on Minority Health and Health Disparities
- The Centers for Common Disease Genomics of the Genome Sequencing Program
- Tobacco-Related Disease Research Program
- Sandler Family Foundation
- American Asthma Foundation
- Amos Medical Faculty Development Program from the Robert Wood Johnson Foundation
- Harry Wm. and Diana V. Hind Distinguished Professor in Pharmaceutical Sciences II
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Affiliation(s)
- Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Canary Islands, Spain.
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology, and Genetics, Universidad de La Laguna (ULL), La Laguna, Tenerife, Canary Islands, Spain.
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain.
- Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna (ULL), La Laguna, Spain.
| | - Elizabeth G Plender
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Jamie L Everman
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA
| | - Nathan D Jackson
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
| | - Camille M Moore
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Department of Biomedical Research, National Jewish Health, Denver, CO, USA
- Department of Biostatistics and Informatics, University of Colorado, Denver, CO, USA
| | - Kenneth B Beckman
- University of Minnesota Genomics Center (UMNGC), Minneapolis, MN, USA
| | | | - Sunita Sharma
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Daniel Efrain Winnica
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | - Fernando Holguin
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
| | | | - Jesús Villar
- CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
- Multidisciplinary Organ Dysfunction Evaluation Research Network (MODERN), Research Unit, Hospital Universitario Dr. Negrín, Las Palmas de Gran Canaria, Spain
- Li Ka Shing Knowledge Institute at the St. Michael's Hospital, Toronto, ON, Canada
| | - Elad Ziv
- Institute for Human Genetics, University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Epidemiology and Biostatistics, University of California, San Francisco School of Medicine, San Francisco, CA, USA
| | - Max A Seibold
- Center for Genes, Environment, and Health, National Jewish Health, Denver, CO, USA
- Division of Pulmonary Sciences and Critical Care Medicine, University of Colorado School of Medicine, Aurora, CO, USA
- Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco (UCSF), San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco (UCSF), San Francisco, CA, USA
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Espuela-Ortiz A, Martin-Gonzalez E, Poza-Guedes P, González-Pérez R, Herrera-Luis E. Genomics of Treatable Traits in Asthma. Genes (Basel) 2023; 14:1824. [PMID: 37761964 PMCID: PMC10531302 DOI: 10.3390/genes14091824] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2023] [Revised: 09/12/2023] [Accepted: 09/16/2023] [Indexed: 09/29/2023] Open
Abstract
The astounding number of genetic variants revealed in the 15 years of genome-wide association studies of asthma has not kept pace with the goals of translational genomics. Moving asthma diagnosis from a nonspecific umbrella term to specific phenotypes/endotypes and related traits may provide insights into features that may be prevented or alleviated by therapeutical intervention. This review provides an overview of the different asthma endotypes and phenotypes and the genomic findings from asthma studies using patient stratification strategies and asthma-related traits. Asthma genomic research for treatable traits has uncovered novel and previously reported asthma loci, primarily through studies in Europeans. Novel genomic findings for asthma phenotypes and related traits may arise from multi-trait and specific phenotyping strategies in diverse populations.
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Affiliation(s)
- Antonio Espuela-Ortiz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Elena Martin-Gonzalez
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), 38200 San Cristóbal de La Laguna, Tenerife, Spain; (A.E.-O.); (E.M.-G.)
| | - Paloma Poza-Guedes
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Ruperto González-Pérez
- Allergy Department, Hospital Universitario de Canarias, 38320 Santa Cruz de Tenerife, Tenerife, Spain; (P.P.-G.); (R.G.-P.)
- Severe Asthma Unit, Hospital Universitario de Canarias, 38320 San Cristóbal de La Laguna, Tenerife, Spain
| | - Esther Herrera-Luis
- Department of Epidemiology, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD 21205, USA
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Sardon-Prado O, Diaz-Garcia C, Corcuera-Elosegui P, Korta-Murua J, Valverde-Molina J, Sanchez-Solis M. Severe Asthma and Biological Therapies: Now and the Future. J Clin Med 2023; 12:5846. [PMID: 37762787 PMCID: PMC10532431 DOI: 10.3390/jcm12185846] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2023] [Revised: 08/18/2023] [Accepted: 08/25/2023] [Indexed: 09/29/2023] Open
Abstract
Recognition of phenotypic variability in pediatric asthma allows for a more personalized therapeutic approach. Knowledge of the underlying pathophysiological and molecular mechanisms (endotypes) of corresponding biomarkers and new treatments enables this strategy to progress. Biologic therapies for children with severe asthma are becoming more relevant in this sense. The T2 phenotype is the most prevalent in childhood and adolescence, and non-T2 phenotypes are usually rare. This document aims to review the mechanism of action, efficacy, and potential predictive and monitoring biomarkers of biological drugs, focusing on the pediatric population. The drugs currently available are omalizumab, mepolizumab, benralizumab, dupilumab, and 1ezepelumab, with some differences in administrative approval prescription criteria between the U.S. Food and Drug Administration (FDA) and the European Medicines Agency (EMA). Previously, we described the characteristics of severe asthma in children and its diagnostic and therapeutic management.
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Affiliation(s)
- Olaia Sardon-Prado
- Division of Paediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain; (O.S.-P.); (P.C.-E.); (J.K.-M.)
- Department of Pediatrics, University of the Basque Country (UPV/EHU), 20014 Leioa, Spain
| | - Carolina Diaz-Garcia
- Paediatric Pulmonology and Allergy Unit, Santa Lucia General University Hospital, 30202 Cartagena, Spain;
| | - Paula Corcuera-Elosegui
- Division of Paediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain; (O.S.-P.); (P.C.-E.); (J.K.-M.)
| | - Javier Korta-Murua
- Division of Paediatric Respiratory Medicine, Donostia University Hospital, 20014 San Sebastián, Spain; (O.S.-P.); (P.C.-E.); (J.K.-M.)
| | - Jose Valverde-Molina
- Department of Paediatrics, Santa Lucía General University Hospital, 30202 Cartagena, Spain
- IMIB Biomedical Research Institute, 20120 Murcia, Spain;
| | - Manuel Sanchez-Solis
- IMIB Biomedical Research Institute, 20120 Murcia, Spain;
- Department of Pediatrics, University of Murcia, 20120 Murcia, Spain
- Paediatric Allergy and Pulmonology Units, Virgen de la Arrixaca University Children’s Hospital, 20120 Murcia, Spain
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5
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Shi Y, Miao BY, Ai XX, Cao P, Gao J, Xu Y, Yang Q, Fei J, Zhang Q, Mai QY, Wen YX, Qu YL, Zhou CQ, Xu YW. Identification of common genetic polymorphisms associated with down-regulated gonadotropin levels in an exome-wide association study. Fertil Steril 2023; 120:671-681. [PMID: 37001689 DOI: 10.1016/j.fertnstert.2023.03.031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Revised: 03/17/2023] [Accepted: 03/24/2023] [Indexed: 03/31/2023]
Abstract
OBJECTIVE To investigate whether common genetic polymorphisms are associated with gonadotropin levels after down-regulation with daily gonadotropin-releasing hormone agonist and whether the polymorphisms of candidate variants influence the ovarian response to exogenous gonadotropins. DESIGN Genetic association study. SETTING University-affiliated in vitro fertilization center. PATIENTS Subjects enrolled in an exploratory exome-wide association study (n = 862), a replication exome-wide association study (n = 86), and a classifier validation study (n = 148) were recruited from September 2016 to October 2018, September 2019 to September 2020, and January 2021 to December 2021, respectively. The included patients were aged ≤40 years and had a basal follicle-stimulating hormone (FSH) ≤12 IU/L. INTERVENTIONS All participants received a luteal phase down-regulation long protocol. Genome DNA was extracted from the peripheral blood leukocytes. For the exploratory and replication cohorts, exome sequencing was conducted on a HiSeq 2500 sequencing platform. The multiplex polymerase chain reaction amplification technique and next-generation sequencing also were performed in the exploratory and replication cohorts. For the samples of the validation cohort, Sanger sequencing was performed. MAIN OUTCOME MEASURES The primary endpoint was the gonadotropin levels after down-regulation, and the secondary endpoints were hormone levels and follicle diameters during stimulation, the total dose of FSH, duration of FSH stimulation, number of oocytes retrieved, and clinical pregnancy rate. RESULTS In the exploratory cohort, we identified that FSHB rs6169 (P=2.71 × 10-24) and its single-nucleotide polymorphisms in high linkage disequilibrium were associated with the down-regulated FSH level. The same locus was confirmed in the replication cohort. Women carrying the C allele of FSHB rs6169 exhibited higher average estradiol level during stimulation (P=6.82 × 10-5), shorter duration of stimulation, and less amount of exogenous FSH (Pduration=0.0002; Pdose=0.0024). In the independent validation set, adding rs6169 genotypes into the prediction model for FSH level after down-regulation enhanced the area under the curve from 0.560 to 0.712 in a logistic regression model, and increased prediction accuracy by 41.05% when a support vector machine classifier was applied. CONCLUSION The C allele of FSHB rs6169 is a susceptibility site for the relatively high level of FSH after down-regulation, which may be associated with increased ovarian FSH sensitivity.
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Affiliation(s)
- Yue Shi
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Ben-Yu Miao
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Xi-Xiong Ai
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China; Reproductive Medicine Center, The Affiliated Shenzhen Maternity and Child Healthcare Hospital of the South Medical University, Shenzhen, Guangdong, China
| | - Ping Cao
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China; Research School for Developmental Biology (GROW), Maastricht University, Maastricht, The Netherlands; Division of Obstetrics and Gynecology, Department of Clinical Science, Intervention and Technology (CLINTEC), Karolinska Institute, Stockholm, Sweden
| | - Jun Gao
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Yan Xu
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Qun Yang
- Peking Medriv Academy of Genetics and Reproduction, Peking, China
| | - Jia Fei
- Peking Medriv Academy of Genetics and Reproduction, Peking, China
| | - Qian Zhang
- Peking Medriv Academy of Genetics and Reproduction, Peking, China
| | - Qing-Yun Mai
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Yang-Xing Wen
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Yan-Lin Qu
- Department of Management Science and Engineering, Stanford University, Stanford, California
| | - Can-Quan Zhou
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China
| | - Yan-Wen Xu
- Reproductive Medicine Center, the First Affiliated Hospital of Sun Yat-sen University, Guangzhou, Guangdong, People's Republic of China; Guangdong Provincial Key Laboratory of Reproductive Medicine, Guangzhou, Guangdong, China.
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6
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Tan T, Atkinson EG. Strategies for the Genomic Analysis of Admixed Populations. Annu Rev Biomed Data Sci 2023; 6:105-127. [PMID: 37127050 PMCID: PMC10871708 DOI: 10.1146/annurev-biodatasci-020722-014310] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 05/03/2023]
Abstract
Admixed populations constitute a large portion of global human genetic diversity, yet they are often left out of genomics analyses. This exclusion is problematic, as it leads to disparities in the understanding of the genetic structure and history of diverse cohorts and the performance of genomic medicine across populations. Admixed populations have particular statistical challenges, as they inherit genomic segments from multiple source populations-the primary reason they have historically been excluded from genetic studies. In recent years, however, an increasing number of statistical methods and software tools have been developed to account for and leverage admixture in the context of genomics analyses. Here, we provide a survey of such computational strategies for the informed consideration of admixture to allow for the well-calibrated inclusion of mixed ancestry populations in large-scale genomics studies, and we detail persisting gaps in existing tools.
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Affiliation(s)
- Taotao Tan
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
| | - Elizabeth G Atkinson
- Department of Molecular and Human Genetics, Baylor College of Medicine, Houston, Texas, USA;
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7
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Ding YC, Song H, Adamson AW, Schmolze D, Hu D, Huntsman S, Steele L, Patrick CS, Tao S, Hernandez N, Adams CD, Fejerman L, Gardner K, Nápoles AM, Pérez-Stable EJ, Weitzel JN, Bengtsson H, Huang FW, Neuhausen SL, Ziv E. Profiling the Somatic Mutational Landscape of Breast Tumors from Hispanic/Latina Women Reveals Conserved and Unique Characteristics. Cancer Res 2023; 83:2600-2613. [PMID: 37145128 PMCID: PMC10390863 DOI: 10.1158/0008-5472.can-22-2510] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Revised: 02/16/2023] [Accepted: 05/02/2023] [Indexed: 05/06/2023]
Abstract
Somatic mutational profiling is increasingly being used to identify potential targets for breast cancer. However, limited tumor-sequencing data from Hispanic/Latinas (H/L) are available to guide treatment. To address this gap, we performed whole-exome sequencing (WES) and RNA sequencing on 146 tumors and WES of matched germline DNA from 140 H/L women in California. Tumor intrinsic subtype, somatic mutations, copy-number alterations, and expression profiles of the tumors were characterized and compared with data from tumors of non-Hispanic White (White) women in The Cancer Genome Atlas (TCGA). Eight genes were significantly mutated in the H/L tumors including PIK3CA, TP53, GATA3, MAP3K1, CDH1, CBFB, PTEN, and RUNX1; the prevalence of mutations in these genes was similar to that observed in White women in TCGA. Four previously reported Catalogue of Somatic Mutations in Cancer (COSMIC) mutation signatures (1, 2, 3, 13) were found in the H/L dataset, along with signature 16 that has not been previously reported in other breast cancer datasets. Recurrent amplifications were observed in breast cancer drivers including MYC, FGFR1, CCND1, and ERBB2, as well as a recurrent amplification in 17q11.2 associated with high KIAA0100 gene expression that has been implicated in breast cancer aggressiveness. In conclusion, this study identified a higher prevalence of COSMIC signature 16 and a recurrent copy-number amplification affecting expression of KIAA0100 in breast tumors from H/L compared with White women. These results highlight the necessity of studying underrepresented populations. SIGNIFICANCE Comprehensive characterization of genomic and transcriptomic alterations in breast tumors from Hispanic/Latina patients reveals distinct genetic alterations and signatures, demonstrating the importance of inclusive studies to ensure equitable care for patients. See related commentary by Schmit et al., p. 2443.
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Affiliation(s)
- Yuan Chun Ding
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Hanbing Song
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California
| | - Aaron W. Adamson
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Daniel Schmolze
- Department of Pathology, City of Hope Medical Center, Duarte, California
| | - Donglei Hu
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
| | - Scott Huntsman
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
| | - Linda Steele
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Carmina S. Patrick
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Shu Tao
- Integrative Genomics Shared Resource, Beckman Research Institute of City of Hope, Duarte, California
| | - Natalie Hernandez
- Western University of Health Sciences College of Graduate Nursing, Pomona, California
| | | | - Laura Fejerman
- Department of Public Health Sciences and Comprehensive Cancer Center, University of California Davis, Davis, California
| | - Kevin Gardner
- Department of Pathology and Cell Biology, Columbia University Irvine Medical Center, New York, New York
| | - Anna María Nápoles
- Division of Intramural Research, National Institute on Minority and Health Disparities, National Institutes of Health, Bethesda, Maryland
| | | | | | - Henrik Bengtsson
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California
| | - Franklin W. Huang
- Division of Hematology/Oncology, Department of Medicine, University of California, San Francisco, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California
- Bakar Computational Health Sciences Institute, University of California, San Francisco, San Francisco, California
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California
- Chan Zuckerberg Biohub, San Francisco, California
- Department of Medicine, San Francisco Veterans Affairs Medical Center, San Francisco, California
| | - Susan L. Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, California
| | - Elad Ziv
- Division of General Internal Medicine, Department of Medicine, University of California, San Francisco, San Francisco, California
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California
- Institute for Human Genetics, University of California, San Francisco, San Francisco, California
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8
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Sharma R, Tiwari A, Kho AT, Wang AL, Srivastava U, Piparia S, Desai B, Wong R, Celedón JC, Peters SP, Smith LJ, Irvin CG, Castro M, Weiss ST, Tantisira KG, McGeachie MJ. Circulating MicroRNAs associated with Bronchodilator Response in Childhood Asthma. RESEARCH SQUARE 2023:rs.3.rs-3101724. [PMID: 37461659 PMCID: PMC10350209 DOI: 10.21203/rs.3.rs-3101724/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
Rationale Bronchodilator response (BDR) is a measure of improvement in airway smooth muscle tone, inhibition of liquid accumulation and mucus section into the lumen in response to short-acting beta-2 agonists that varies among asthmatic patients. MicroRNAs (miRNAs) are well-known post-translational regulators. Identifying miRNAs associated with BDR could lead to a better understanding of the underlying complex pathophysiology. Objective The purpose of this study is to identify circulating miRNAs associated with bronchodilator response in asthma and decipher possible mechanism of bronchodilator response variation. Methods We used available small RNA sequencing on blood serum from 1,134 asthmatic children aged 6 to 14 years who participated in the Genetics of Asthma in Costa Rica Study (GACRS). We filtered the participants into high and low bronchodilator response (BDR) quartiles and used DeSeq2 to identify miRNAs with differential expression (DE) in high (N= 277) vs low (N= 278) BDR group. Replication was carried out in the Leukotriene modifier Or Corticosteroids or Corticosteroid-Salmeterol trial (LOCCS), an adult asthma cohort. The putative target genes of DE miRNAs were identified, and pathway enrichment analysis was performed. Results We identified 10 down-regulated miRNAs having odds ratios (OR) between 0.37 and 0.76 for a doubling of miRNA counts and one up-regulated miRNA (OR=2.26) between high and low BDR group. These were assessed for replication in the LOCCS cohort, where two miRNAs (miR-200b-3p and miR-1246) were associated. Further, functional annotation of 11 DE miRNAs were performed as well as of two replicated miRs. Target genes of these miRs were enriched in regulation of cholesterol biosynthesis by SREBPs, ESR-mediated signaling, G1/S transition, RHO GTPase cycle, and signaling by TGFB family pathways. Conclusion MiRNAs miR-1246 and miR-200b-3p are associated with both childhood and adult asthma BDR. Our findings add to the growing body of evidence that miRNAs play a significant role in the difference of asthma treatment response among patients as it points to genomic regulatory machinery underlying difference in bronchodilator response among patients. Trial registration LOCCS cohort [ClinicalTrials.gov number: NCT00156819], GACRS cohort [ClinicalTrials.gov number: NCT00021840].
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Affiliation(s)
- Rinku Sharma
- Brigham and Women's Hospital and Harvard Medical School
| | | | - Alvin T Kho
- Brigham and Women's Hospital and Harvard Medical School
| | | | | | | | - Brinda Desai
- University of California San Diego and Rady Children's Hospital
| | - Richard Wong
- University of California San Diego and Rady Children's Hospital
| | - Juan C Celedón
- University of Pittsburgh, UPMC Children's Hospital of Pittsburgh
| | | | | | | | | | - Scott T Weiss
- Brigham and Women's Hospital and Harvard Medical School
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9
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Matera MG, Rogliani P, Novelli G, Cazzola M. The impact of genomic variants on patient response to inhaled bronchodilators: a comprehensive update. Expert Opin Drug Metab Toxicol 2023. [PMID: 37269324 DOI: 10.1080/17425255.2023.2221848] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Accepted: 06/01/2023] [Indexed: 06/05/2023]
Abstract
INTRODUCTION The bronchodilator response (BDR) depends on many factors, including genetic ones. Numerous single nucleotide polymorphisms (SNPs) influencing BDR have been identified. However, despite several studies in this field, genetic variations are not currently being utilized to support the use of bronchodilators. AREAS COVERED In this narrative review, the possible impact of genetic variants on BDR is discussed. EXPERT OPINION Pharmacogenetic studies of β2-agonists have mainly focused on ADRB2 gene. Three SNPs, A46G, C79G, and C491T, have functional significance. However, other uncommon variants may contribute to individual variability in salbutamol response. SNPs haplotypes in ADRB2 may have a role. Many variants in genes coding for muscarinic ACh receptor (mAChR) have been reported, particularly in the M2 and, to a lesser degree, M3 mAChRs, but no consistent evidence for a pharmacological relevance of these SNPs has been reported. Moreover, there is a link between SNPs and ethnic and/or age profiles regarding BDR. Nevertheless, replication of pharmacogenetic results is limited and often, BDR is dissociated from what is expected based on SNP identification. Pharmacogenetic studies on bronchodilators must continue. However, they must integrate data derived from a multi-omics approach with epigenetic factors that may modify BDR.
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Affiliation(s)
- Maria Gabriella Matera
- Department of Experimental Medicine, University of Campania 'Luigi Vanvitelli', Naples, Italy
| | - Paola Rogliani
- Department of Experimental Medicine, University of Rome 'Tor Vergata', Rome, Italy
| | - Giuseppe Novelli
- Department of Biomedicine and Prevention, University of Rome 'Tor Vergata', Rome, Italy
| | - Mario Cazzola
- Department of Experimental Medicine, University of Rome 'Tor Vergata', Rome, Italy
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10
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Perez-Garcia J, Herrera-Luis E, Li A, Mak ACY, Huntsman S, Oh SS, Elhawary JR, Eng C, Beckman KB, Hu D, Lorenzo-Diaz F, Lenoir MA, Rodriguez-Santana J, Zaitlen N, Villar J, Borrell LN, Burchard EG, Pino-Yanes M. Multi-omic approach associates blood methylome with bronchodilator drug response in pediatric asthma. J Allergy Clin Immunol 2023; 151:1503-1512. [PMID: 36796456 DOI: 10.1016/j.jaci.2023.01.026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2022] [Revised: 01/13/2023] [Accepted: 01/31/2023] [Indexed: 02/16/2023]
Abstract
BACKGROUND Albuterol is the drug most widely used as asthma treatment among African Americans despite having a lower bronchodilator drug response (BDR) than other populations. Although BDR is affected by gene and environmental factors, the influence of DNA methylation is unknown. OBJECTIVE This study aimed to identify epigenetic markers in whole blood associated with BDR, study their functional consequences by multi-omic integration, and assess their clinical applicability in admixed populations with a high asthma burden. METHODS We studied 414 children and young adults (8-21 years old) with asthma in a discovery and replication design. We performed an epigenome-wide association study on 221 African Americans and replicated the results on 193 Latinos. Functional consequences were assessed by integrating epigenomics with genomics, transcriptomics, and environmental exposure data. Machine learning was used to develop a panel of epigenetic markers to classify treatment response. RESULTS We identified 5 differentially methylated regions and 2 CpGs genome-wide significantly associated with BDR in African Americans located in FGL2 (cg08241295, P = 6.8 × 10-9) and DNASE2 (cg15341340, P = 7.8 × 10-8), which were regulated by genetic variation and/or associated with gene expression of nearby genes (false discovery rate < 0.05). The CpG cg15341340 was replicated in Latinos (P = 3.5 × 10-3). Moreover, a panel of 70 CpGs showed good classification for those with response and nonresponse to albuterol therapy in African American and Latino children (area under the receiver operating characteristic curve for training, 0.99; for validation, 0.70-0.71). The DNA methylation model showed similar discrimination as clinical predictors (P > .05). CONCLUSIONS We report novel associations of epigenetic markers with BDR in pediatric asthma and demonstrate for the first time the applicability of pharmacoepigenetics in precision medicine of respiratory diseases.
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Affiliation(s)
- Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
| | - Esther Herrera-Luis
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain
| | - Annie Li
- Department of Medicine, University of California, San Francisco, Calif
| | - Angel C Y Mak
- Department of Medicine, University of California, San Francisco, Calif
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, Calif
| | - Sam S Oh
- Department of Medicine, University of California, San Francisco, Calif
| | | | - Celeste Eng
- Department of Medicine, University of California, San Francisco, Calif
| | | | - Donglei Hu
- Department of Medicine, University of California, San Francisco, Calif
| | - Fabian Lorenzo-Diaz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain; Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias (IUETSPC), ULL, Santa Cruz de Tenerife, Spain
| | | | | | - Noah Zaitlen
- Department of Neurology, University of California, Los Angeles, Calif; Department of Computational Medicine, University of California, Los Angeles, Calif
| | - Jesús Villar
- Multidisciplinary Organ Dysfunction Evaluation Research Network (MODERN), Research Unit, Hospital Universitario Dr Negrín, Las Palmas de Gran Canaria, Spain; CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Luisa N Borrell
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY
| | - Esteban G Burchard
- Department of Medicine, University of California, San Francisco, Calif; Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, Calif
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna (ULL), La Laguna, Spain; CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain; Instituto de Tecnologías Biomédicas, ULL, La Laguna, Spain.
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11
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Kachuri L, Mak ACY, Hu D, Eng C, Huntsman S, Elhawary JR, Gupta N, Gabriel S, Xiao S, Keys KL, Oni-Orisan A, Rodríguez-Santana JR, LeNoir MA, Borrell LN, Zaitlen NA, Williams LK, Gignoux CR, Burchard EG, Ziv E. Gene expression in African Americans, Puerto Ricans and Mexican Americans reveals ancestry-specific patterns of genetic architecture. Nat Genet 2023; 55:952-963. [PMID: 37231098 PMCID: PMC10260401 DOI: 10.1038/s41588-023-01377-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2021] [Accepted: 03/21/2023] [Indexed: 05/27/2023]
Abstract
We explored ancestry-related differences in the genetic architecture of whole-blood gene expression using whole-genome and RNA sequencing data from 2,733 African Americans, Puerto Ricans and Mexican Americans. We found that heritability of gene expression significantly increased with greater proportions of African genetic ancestry and decreased with higher proportions of Indigenous American ancestry, reflecting the relationship between heterozygosity and genetic variance. Among heritable protein-coding genes, the prevalence of ancestry-specific expression quantitative trait loci (anc-eQTLs) was 30% in African ancestry and 8% for Indigenous American ancestry segments. Most anc-eQTLs (89%) were driven by population differences in allele frequency. Transcriptome-wide association analyses of multi-ancestry summary statistics for 28 traits identified 79% more gene-trait associations using transcriptome prediction models trained in our admixed population than models trained using data from the Genotype-Tissue Expression project. Our study highlights the importance of measuring gene expression across large and ancestrally diverse populations for enabling new discoveries and reducing disparities.
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Affiliation(s)
- Linda Kachuri
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Epidemiology and Population Health, Stanford University, Stanford, CA, USA
| | - Angel C Y Mak
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Jennifer R Elhawary
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Namrata Gupta
- Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | | | - Shujie Xiao
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, MI, USA
| | - Kevin L Keys
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
- Berkeley Institute for Data Science, University of California, Berkeley, Berkeley, CA, USA
| | - Akinyemi Oni-Orisan
- Department of Clinical Pharmacy, University of California, San Francisco, San Francisco, CA, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA
| | | | | | - Luisa N Borrell
- Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY, USA
| | - Noah A Zaitlen
- Department of Neurology, University of California, Los Angeles, Los Angeles, CA, USA
- Department of Computational Medicine, University of California, Los Angeles, Los Angeles, CA, USA
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research, Henry Ford Health System, Detroit, MI, USA
- Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Christopher R Gignoux
- Colorado Center for Personalized Medicine, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
- Department of Biomedical Informatics, University of Colorado Anschutz Medical Campus, Aurora, CO, USA.
| | - Esteban González Burchard
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, San Francisco, CA, USA.
| | - Elad Ziv
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA.
- Institute for Human Genetics, University of California, San Francisco, San Francisco, CA, USA.
- Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, CA, USA.
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12
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Mabelane T, Masekela R, Dandara C, Hadebe S. Immunogenetics and pharmacogenetics of allergic asthma in Africa. FRONTIERS IN ALLERGY 2023; 4:1165311. [PMID: 37228580 PMCID: PMC10203899 DOI: 10.3389/falgy.2023.1165311] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2023] [Accepted: 04/20/2023] [Indexed: 05/27/2023] Open
Abstract
Asthma is a common chronic condition in children and in an African setting is often highly prevalent in urban areas as compared to rural areas. Asthma is a heritable disease and the genetic risk is often exacerbated by unique localised environmental factors. The Global Initiative for Asthma (GINA) recommendation for the control of asthma includes inhaled corticosteroids (ICS) alone or together with short-acting β2-agonists (SABA) or long-acting β2-agonists (LABA). While these drugs can relieve asthma symptoms, there is evidence of reduced efficacy in people of African ancestry. Whether this is due to immunogenetics, genomic variability in drug metabolising genes (pharmacogenetics) or genetics of asthma-related traits is not well defined. Pharmacogenetic evidence of first-line asthma drugs in people of African ancestry is lacking and is further compounded by the lack of representative genetic association studies in the continent. In this review, we will discuss the paucity of data related to the pharmacogenetics of asthma drugs in people of African ancestry, mainly drawing from African American data. We will further discuss how this gap can be bridged to improve asthma health outcomes in Africa.
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Affiliation(s)
- Tshegofatso Mabelane
- Department of Medicine, Sefako Makgatho Health Science University, Ga-Rankuwa, South Africa
| | - Refiloe Masekela
- Department of Paediatrics, Nelson Mandela School of Medicine, Inkosi Albert Luthuli Hospital, University of KwaZulu-Natal, Durban, South Africa
| | - Collet Dandara
- Division of Human Genetics, Department of Pathology, Faculty of Health Sciences and Institute of Infectious Diseases Molecular Medicine, University of Cape Town, Cape Town, South Africa
- Platform for Pharmacogenomics Research and Translation, South African Medical Research Council, Cape Town, South Africa
| | - Sabelo Hadebe
- Division of Immunology, Department of Pathology, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa
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13
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Nierenberg JL, Adamson AW, Hu D, Huntsman S, Patrick C, Li M, Steele L, Tong B, Shieh Y, Fejerman L, Gruber SB, Haiman CA, John EM, Kushi LH, Torres-Mejía G, Ricker C, Weitzel JN, Ziv E, Neuhausen SL. Whole exome sequencing and replication for breast cancer among Hispanic/Latino women identifies FANCM as a susceptibility gene for estrogen-receptor-negative breast cancer. MEDRXIV : THE PREPRINT SERVER FOR HEALTH SCIENCES 2023:2023.01.25.23284924. [PMID: 36747679 PMCID: PMC9901069 DOI: 10.1101/2023.01.25.23284924] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/30/2023]
Abstract
Introduction Breast cancer (BC) is one of the most common cancers globally. Genetic testing can facilitate screening and risk-reducing recommendations, and inform use of targeted treatments. However, genes included in testing panels are from studies of European-ancestry participants. We sequenced Hispanic/Latina (H/L) women to identify BC susceptibility genes. Methods We conducted a pooled BC case-control analysis in H/L women from the San Francisco Bay area, Los Angeles County, and Mexico (4,178 cases and 4,344 controls). Whole exome sequencing was conducted on 1,043 cases and 1,188 controls and a targeted 857-gene panel on the remaining samples. Using ancestry-adjusted SKAT-O analyses, we tested the association of loss of function (LoF) variants with overall, estrogen receptor (ER)-positive, and ER-negative BC risk. We calculated odds ratios (OR) for BC using ancestry-adjusted logistic regression models. We also tested the association of single variants with BC risk. Results We saw a strong association of LoF variants in FANCM with ER-negative BC (p=4.1×10-7, OR [CI]: 6.7 [2.9-15.6]) and a nominal association with overall BC risk. Among known susceptibility genes, BRCA1 (p=2.3×10-10, OR [CI]: 24.9 [6.1-102.5]), BRCA2 (p=8.4×10-10, OR [CI]: 7.0 [3.5-14.0]), and PALB2 (p=1.8×10-8, OR [CI]: 6.5 [3.2-13.1]) were strongly associated with BC. There were nominally significant associations with CHEK2, RAD51D, and TP53. Conclusion In H/L women, LoF variants in FANCM were strongly associated with ER-negative breast cancer risk. It previously was proposed as a possible susceptibility gene for ER-negative BC, but is not routinely tested in clinical practice. Our results demonstrate that FANCM should be added to BC gene panels.
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Affiliation(s)
- Jovia L Nierenberg
- Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, CA, USA
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Aaron W Adamson
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Carmina Patrick
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Min Li
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Linda Steele
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
| | - Barry Tong
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Yiwey Shieh
- Department of Population Health Sciences, Weill Cornell Medicine, New York, NY, USA
| | - Laura Fejerman
- Department of Public Health Service, University of California, Davis, Davis, CA, USA
- UC Davis Comprehensive Cancer Center, University of California, Davis, Davis, CA, USA
| | - Stephen B Gruber
- Department of Medical Oncology and Center for Precision Medicine, City of Hope National Medical Center, Duarte, CA, USA
| | - Christopher A Haiman
- Department of Preventive Medicine, Norris Comprehensive Cancer Center, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | - Esther M John
- Department of Epidemiology & Population Health, Stanford University School of Medicine, Stanford, CA, USA
- Department of Medicine, Stanford University School of Medicine, Stanford, CA, USA
- Stanford Cancer Institute, Stanford University School of Medicine, Stanford, CA, USA
| | - Lawrence H Kushi
- Division of Research, Kaiser Permanente Northern California, Oakland, CA, USA
| | | | - Charité Ricker
- Department of Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
| | | | - Elad Ziv
- Department of Medicine, University of California, San Francisco, San Francisco, CA, USA
| | - Susan L Neuhausen
- Department of Population Sciences, Beckman Research Institute of City of Hope, Duarte, CA, USA
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14
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Principe S, Vijverberg SJH, Abdel-Aziz MI, Scichilone N, Maitland-van der Zee AH. Precision Medicine in Asthma Therapy. Handb Exp Pharmacol 2023; 280:85-106. [PMID: 35852633 DOI: 10.1007/164_2022_598] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Asthma is a complex, heterogeneous disease that necessitates a proper patient evaluation to decide the correct treatment and optimize disease control. The recent introduction of new target therapies for the most severe form of the disease has heralded a new era of treatment options, intending to treat and control specific molecular pathways in asthma pathophysiology. Precision medicine, using omics sciences, investigates biological and molecular mechanisms to find novel biomarkers that can be used to guide treatment selection and predict response. The identification of reliable biomarkers indicative of the pathological mechanisms in asthma is essential to unravel new potential treatment targets. In this chapter, we provide a general description of the currently available -omics techniques, focusing on their implications in asthma therapy.
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Affiliation(s)
- Stefania Principe
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands.
- Dipartimento Universitario di Promozione della Salute, Materno Infantile, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro" (PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", University of Palermo, Palermo, Italy.
| | - Susanne J H Vijverberg
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
| | - Mahmoud I Abdel-Aziz
- Department of Respiratory Medicine, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands
- Department of Clinical Pharmacy, Faculty of Pharmacy, Assiut University, Assiut, Egypt
| | - Nicola Scichilone
- Dipartimento Universitario di Promozione della Salute, Materno Infantile, Medicina Interna e Specialistica di Eccellenza "G. D'Alessandro" (PROMISE) c/o Pneumologia, AOUP "Policlinico Paolo Giaccone", University of Palermo, Palermo, Italy
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15
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The Genetic Factors of the Airway Epithelium Associated with the Pathology of Asthma. Genes (Basel) 2022; 13:genes13101870. [PMID: 36292755 PMCID: PMC9601469 DOI: 10.3390/genes13101870] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 10/12/2022] [Accepted: 10/14/2022] [Indexed: 11/04/2022] Open
Abstract
Asthma is a chronic disease of the airways characterized by inflammation, tightened muscles, and thickened airway walls leading to symptoms such as shortness of breath, chest tightness, and cough in patients. The increased risk of asthma in children of asthmatics parents supports the existence of genetic factors involved in the pathogenesis of this disease. Genome-wide association studies have discovered several single nucleotide polymorphisms associated with asthma. These polymorphisms occur within several genes and can contribute to different asthma phenotypes, affect disease severity, and clinical response to different therapies. The complexity in the etiology of asthma also results from interactions between environmental and genetic factors. Environmental exposures have been shown to increase the prevalence of asthma in individuals who are genetically susceptible. This review summarizes what is currently known about the genetics of asthma in relation to risk, response to common treatments, and gene-environmental interactions.
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16
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Gereige JD, Xu H, Ortega VE, Cho MH, Liu M, Sakornsakolpat P, Silverman EK, Beaty TH, Miller BE, Bakke P, Gulsvik A, Hersh CP, Morrow JD, Ampleford EJ, Hawkins GA, Bleecker ER, Meyers DA, Peters SP, Celedón JC, Tantisira K, Li J, Dupuis J, O'Connor GT. A genome-wide association study of bronchodilator response in participants of European and African ancestry from six independent cohorts. ERJ Open Res 2022; 8:00484-2021. [PMID: 35769418 PMCID: PMC9234425 DOI: 10.1183/23120541.00484-2021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/30/2021] [Accepted: 05/08/2022] [Indexed: 11/30/2022] Open
Abstract
Introduction Bronchodilator response (BDR) is a measurement of acute bronchodilation in response to short-acting β2-agonists, with a heritability between 10 and 40%. Identifying genetic variants associated with BDR may lead to a better understanding of its complex pathophysiology. Methods We performed a genome-wide association study (GWAS) of BDR in six adult cohorts with participants of European ancestry (EA) and African ancestry (AA) including community cohorts and cohorts ascertained on the basis of obstructive pulmonary disease. Validation analysis was carried out in two paediatric asthma cohorts. Results A total of 10 623 EA and 3597 AA participants were included in the analyses. No single nucleotide polymorphism (SNP) was associated with BDR at the conventional genome-wide significance threshold (p<5×10-8). Performing fine mapping and using a threshold of p<5×10-6 to identify suggestive variants of interest, we identified three SNPs with possible biological relevance: rs35870000 (within FREM1), which may be involved in IgE- and IL5-induced changes in airway smooth muscle cell responsiveness; rs10426116 (within ZNF284), a zinc finger protein, which has been implicated in asthma and BDR previously; and rs4782614 (near ATP2C2), involved in calcium transmembrane transport. Validation in paediatric cohorts yielded no significant SNPs, possibly due to age-genotype interaction effects. Conclusion Ancestry-stratified and ancestry-combined GWAS meta-analyses of over 14 000 participants did not identify genetic variants associated with BDR at the genome-wide significance threshold, although a less stringent threshold identified three variants showing suggestive evidence of association. A common definition and protocol for measuring BDR in research may improve future efforts to identify variants associated with BDR.
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Affiliation(s)
- Jessica D. Gereige
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, MA, USA
- Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
| | - Hanfei Xu
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - Victor E. Ortega
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Michael H. Cho
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Ming Liu
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Bioinformatics and Computational Biology Program, Worcester Polytechnic Institute, Worcester, MA, USA
| | - Phuwanat Sakornsakolpat
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Edwin K. Silverman
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Terri H. Beaty
- Dept of Epidemiology, Johns Hopkins University Bloomberg School of Public Health, Baltimore, MD, USA
| | | | - Per Bakke
- Dept of Clinical Science, University of Bergen, Bergen, Norway
| | - Amund Gulsvik
- Dept of Clinical Science, University of Bergen, Bergen, Norway
| | - Craig P. Hersh
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | - Jarrett D. Morrow
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
| | | | - Elizabeth J. Ampleford
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Gregory A. Hawkins
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Eugene R. Bleecker
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Deborah A. Meyers
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Stephen P. Peters
- Division of Genetics, Genomics and Precision Medicine, Department of Medicine, University of Arizona, Tucson, AZ, USA
| | - Juan C. Celedón
- Division of Pediatric Pulmonary Medicine, UPMC Children's Hospital of Pittsburgh, University of Pittsburgh, Pittsburgh, PA, USA
| | - Kelan Tantisira
- Division of Pediatric Respiratory Medicine, University of California and Rady Children's Hospital, San Diego, CA, USA
| | - Jiang Li
- Channing Division of Network Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA
- Research Center, The Seventh Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong, China
| | - Josée Dupuis
- Dept of Biostatistics, Boston University School of Public Health, Boston, MA, USA
| | - George T. O'Connor
- Division of Pulmonary, Allergy, Sleep, and Critical Care Medicine, Boston Medical Center, Boston, MA, USA
- Pulmonary Center, Boston University School of Medicine, Boston, MA, USA
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17
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Pharmacogenomics and Pediatric Asthmatic Medications. JOURNAL OF RESPIRATION 2022. [DOI: 10.3390/jor2010003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/16/2022] Open
Abstract
Asthma is a respiratory condition often stemming from childhood, characterized by difficulty breathing and/or chest tightness. Current treatment options for both adults and children include beta-2 agonists, inhaled corticosteroids (ICS), and leukotriene modifiers (LTM). Despite recommendations by the Global Initiative for Asthma, a substantial number of patients are unresponsive to treatment and unable to control symptoms. Pharmacogenomics have increasingly become the front line of precision medicine, especially with the recent use of candidate gene and genome- wide association studies (GWAS). Screening patients preemptively could likely decrease adverse events and therapeutic failure. However, research in asthma, specifically in pediatrics, has been low. Although numerous adult trials have evaluated the impact of pharmacogenomics and treatment response, the lack of evidence in children has hindered progress towards clinical application. This review aims to discuss the impact of genetic variability and response to asthmatic medications in the pediatric population.
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18
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Fishe J, Zheng Y, Lyu T, Bian J, Hu H. Environmental effects on acute exacerbations of respiratory diseases: A real-world big data study. THE SCIENCE OF THE TOTAL ENVIRONMENT 2022; 806:150352. [PMID: 34555607 PMCID: PMC8627495 DOI: 10.1016/j.scitotenv.2021.150352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/05/2021] [Revised: 09/11/2021] [Accepted: 09/11/2021] [Indexed: 05/06/2023]
Abstract
BACKGROUND The effects of weather periods, race/ethnicity, and sex on environmental triggers for respiratory exacerbations are not well understood. This study linked the OneFlorida network (~15 million patients) with an external exposome database to analyze environmental triggers for asthma, bronchitis, and COPD exacerbations while accounting for seasonality, sex, and race/ethnicity. METHODS This is a case-crossover study of OneFlorida database from 2012 to 2017 examining associations of asthma, bronchitis, and COPD exacerbations with exposures to heat index, PM 2.5 and O 3. We spatiotemporally linked exposures using patients' residential addresses to generate average exposures during hazard and control periods, with each case serving as its own control. We considered age, sex, race/ethnicity, and neighborhood deprivation index as potential effect modifiers in conditional logistic regression models. RESULTS A total of 1,148,506 exacerbations among 533,446 patients were included. Across all three conditions, hotter heat indices conferred increasing exacerbation odds, except during November to March, where the opposite was seen. There were significant differences when stratified by race/ethnicity (e.g., for asthma in April, May, and October, heat index quartile 4, odds were 1.49 (95% confidence interval (CI) 1.42-1.57) for Non-Hispanic Blacks and 2.04 (95% CI 1.92-2.17) for Hispanics compared to 1.27 (95% CI 1.19-1.36) for Non-Hispanic Whites). Pediatric patients' odds of asthma and bronchitis exacerbations were significantly lower than adults in certain circumstances (e.g., for asthma during June - September, pediatric odds 0.71 (95% CI 0.68-0.74) and adult odds 0.82 (95% CI 0.79-0.85) for the highest quartile of PM 2.5). CONCLUSION This study of acute exacerbations of asthma, bronchitis, and COPD found exacerbation risk after exposure to heat index, PM 2.5 and O 3 varies by weather period, age, and race/ethnicity. Future work can build upon these results to alert vulnerable populations to exacerbation triggers.
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Affiliation(s)
- Jennifer Fishe
- Department of Emergency Medicine, University of Florida College of Medicine - Jacksonville, United States of America; Center for Data Solutions, University of Florida College of Medicine - Jacksonville, United States of America.
| | - Yi Zheng
- Department of Epidemiology, University of Florida College of Medicine & College of Public Health and Health Professions, United States of America
| | - Tianchen Lyu
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Jiang Bian
- Department of Health Outcomes and Biomedical Informatics, College of Medicine, University of Florida, Gainesville, FL, United States of America
| | - Hui Hu
- Department of Epidemiology, University of Florida College of Medicine & College of Public Health and Health Professions, United States of America
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19
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Ortega VE, Daya M, Szefler SJ, Bleecker ER, Chinchilli VM, Phipatanakul W, Mauger D, Martinez FD, Herrera-Luis E, Pino-Yanes M, Hawkins GA, Ampleford EJ, Kunselman SJ, Cox C, Bacharier LB, Cabana MD, Cardet JC, Castro M, Denlinger LC, Eng C, Fitzpatrick AM, Holguin F, Hu D, Jackson DJ, Jarjour N, Kraft M, Krishnan JA, Lazarus SC, Lemanske RF, Lima JJ, Lugogo N, Mak A, Moore WC, Naureckas ET, Peters SP, Pongracic JA, Sajuthi SP, Seibold MA, Smith LJ, Solway J, Sorkness CA, Wenzel S, White SR, Burchard EG, Barnes K, Meyers DA, Israel E, Wechsler ME. Pharmacogenetic studies of long-acting beta agonist and inhaled corticosteroid responsiveness in randomised controlled trials of individuals of African descent with asthma. THE LANCET. CHILD & ADOLESCENT HEALTH 2021; 5:862-872. [PMID: 34762840 PMCID: PMC8787857 DOI: 10.1016/s2352-4642(21)00268-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Revised: 08/13/2021] [Accepted: 08/17/2021] [Indexed: 12/25/2022]
Abstract
BACKGROUND Pharmacogenetic studies in asthma cohorts, primarily made up of White people of European descent, have identified loci associated with response to inhaled beta agonists and corticosteroids (ICSs). Differences exist in how individuals from different ancestral backgrounds respond to long-acting beta agonist (LABA) and ICSs. Therefore, we sought to understand the pharmacogenetic mechanisms regulating therapeutic responsiveness in individuals of African descent. METHODS We did ancestry-based pharmacogenetic studies of children (aged 5-11 years) and adolescents and adults (aged 12-69 years) from the Best African Response to Drug (BARD) trials, in which participants with asthma uncontrolled with low-dose ICS (fluticasone propionate 50 μg in children, 100 μg in adolescents and adults) received different step-up combination therapies. The hierarchal composite outcome of pairwise superior responsiveness in BARD was based on asthma exacerbations, a 31-day difference in annualised asthma-control days, or a 5% difference in percentage predicted FEV1. We did whole-genome admixture mapping of 15 159 ancestral segments within 312 independent regions, stratified by the two age groups. The two co-primary outcome comparisons were the step up from low-dose ICS to the quintuple dose of ICS (5 × ICS: 250 μg twice daily in children and 500 μg twice daily in adolescents and adults) versus double dose (2-2·5 × ICS: 100 μg twice daily in children, 250 μg twice daily in adolescents and adults), and 5 × ICS versus 100 μg fluticasone plus a LABA (salmeterol 50 μg twice daily). We used a genome-wide significance threshold of p<1·6 × 10-4, and tested for replication using independent cohorts of individuals of African descent with asthma. FINDINGS We included 249 unrelated children and 267 unrelated adolescents and adults in the BARD pharmacogenetic analysis. In children, we identified a significant admixture mapping peak for superior responsiveness to 5 × ICS versus 100 μg fluticasone plus salmeterol on chromosome 12 (odds ratio [ORlocal African] 3·95, 95% CI 2·02-7·72, p=6·1 × 10-5) fine mapped to a locus adjacent to RNFT2 and NOS1 (rs73399224, ORallele dose 0·17, 95% CI 0·07-0·42, p=8·4 × 10-5). In adolescents and adults, we identified a peak for superior responsiveness to 5 × ICS versus 2·5 × ICS on chromosome 22 (ORlocal African 3·35, 1·98-5·67, p=6·8 × 10-6) containing a locus adjacent to TPST2 (rs5752429, ORallele dose 0·21, 0·09-0·52, p=5·7 × 10-4). We replicated rs5752429 and nominally replicated rs73399224 in independent African American cohorts. INTERPRETATION BARD is the first genome-wide pharmacogenetic study of LABA and ICS response in clinical trials of individuals of African descent to detect and replicate genome-wide significant loci. Admixture mapping of the composite BARD trial outcome enabled the identification of novel pharmacogenetic variation accounting for differential therapeutic responses in people of African descent with asthma. FUNDING National Institutes of Health, National Heart, Lung, and Blood Institute.
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Affiliation(s)
- Victor E Ortega
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA.
| | - Michelle Daya
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Stanley J Szefler
- Department of Pediatrics, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Eugene R Bleecker
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Vernon M Chinchilli
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Wanda Phipatanakul
- Division of Pediatric Allergy and Immunology, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA
| | - Dave Mauger
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Fernando D Martinez
- Asthma and Airway Disease Research Center, University of Arizona Health Sciences, Tucson, AZ, USA
| | - Esther Herrera-Luis
- Department of Biochemistry, La Laguna, Tenerife, Spain; Microbiology, Cell Biology, and Genetics, La Laguna, Tenerife, Spain; Genomics and Health Group, La Laguna, Tenerife, Spain; Universidad de La Laguna, La Laguna, Tenerife, Spain
| | - Maria Pino-Yanes
- Department of Biochemistry, La Laguna, Tenerife, Spain; Microbiology, Cell Biology, and Genetics, La Laguna, Tenerife, Spain; Genomics and Health Group, La Laguna, Tenerife, Spain; Universidad de La Laguna, La Laguna, Tenerife, Spain; CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Gregory A Hawkins
- Department of Biochemistry, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Elizabeth J Ampleford
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Susan J Kunselman
- Department of Public Health Sciences, Pennsylvania State University College of Medicine, Hershey, PA, USA
| | - Corey Cox
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Leonard B Bacharier
- Department of Pediatrics, Washington University School of Medicine, St Louis, MO, USA
| | - Michael D Cabana
- Department of Pediatrics, University of California San Francisco, San Francisco, CA, USA
| | - Juan Carlos Cardet
- Department of Internal Medicine, Division of Allergy and Immunology, Morsani College of Medicine, University of South Florida, Tampa, FL, USA
| | - Mario Castro
- Department of Internal Medicine, Division of Pulmonary, Critical Care, and Sleep Medicine, University of Kansas Medical Center, Kansas City, KS, USA
| | - Loren C Denlinger
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | | | - Fernando Holguin
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Daniel J Jackson
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - Nizar Jarjour
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Monica Kraft
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Jerry A Krishnan
- Breathe Chicago Center, Division of Pulmonary, Critical Care, Sleep, and Allergy, University of Illinois, Chicago, IL, USA
| | - Stephen C Lazarus
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Robert F Lemanske
- Department of Pediatrics, University of Wisconsin-Madison, Madison, WI, USA
| | - John J Lima
- Center for Pharmacogenomics and Translational Research, Nemours Children's Health System, Jacksonville, FL, USA
| | - Njira Lugogo
- Department of Medicine, Division of Pulmonary and Critical Care, University of Michigan, Ann Arbor, MI, USA
| | - Angel Mak
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Wendy C Moore
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | | | - Stephen P Peters
- Department of Internal Medicine, Section for Pulmonary, Critical Care, Allergy, and Immunologic Diseases, Wake Forest School of Medicine, Winston-Salem, NC, USA
| | - Jacqueline A Pongracic
- Department of Pediatrics, Ann & Robert H Lurie Children's Hospital of Chicago, Chicago, IL, USA
| | - Satria P Sajuthi
- Center for Genes, Environment, and Health, Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Max A Seibold
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA; Center for Genes, Environment, and Health, Department of Pediatrics, National Jewish Health, Denver, CO, USA
| | - Lewis J Smith
- Department of Medicine, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Julian Solway
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Christine A Sorkness
- Department of Medicine, Division of Allergy, Pulmonary and Critical Care Medicine, University of Wisconsin-Madison, Madison, WI, USA
| | - Sally Wenzel
- Department of Environmental and Occupational Health, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA
| | - Steven R White
- Department of Medicine, University of Chicago, Chicago, IL, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA, USA
| | - Kathleen Barnes
- Department of Medicine, University of Colorado Anschutz Medical Campus, Denver, CO, USA
| | - Deborah A Meyers
- Department of Internal Medicine, Division of Genetics, Genomics, and Precision Medicine, University of Arizona College of Medicine, Tucson, AZ, USA
| | - Elliot Israel
- Department of Pulmonary and Critical Care Medicine and Allergy and Immunology, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
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20
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Fishe JN, Labilloy G, Higley R, Casey D, Ginn A, Baskovich B, Blake KV. Single Nucleotide Polymorphisms (SNPs) in PRKG1 & SPATA13-AS1 are associated with bronchodilator response: a pilot study during acute asthma exacerbations in African American children. Pharmacogenet Genomics 2021; 31:146-154. [PMID: 33851947 PMCID: PMC8373649 DOI: 10.1097/fpc.0000000000000434] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
OBJECTIVE Inhaled bronchodilators are the first-line treatment for asthma exacerbations, but individual bronchodilator response (BDR) varies by race and ethnicity. Studies have examined BDR's genetic underpinnings, but many did not include children or were not conducted during an asthma exacerbation. This pilot study tested single-nucleotide polymorphisms' (SNPs') association with pediatric African American BDR during an acute asthma exacerbation. METHODS This was a study of pediatric asthma patients in the age group 2-18 years treated in the emergency department for an asthma exacerbation. We measured BDR before and after inhaled bronchodilator treatments using both the Pediatric Asthma Severity Score (PASS) and asthma severity score. We collected genomic DNA and examined whether 21 candidate SNPs from a review of the literature were associated with BDR using crude odds ratios (OR) and adjusted analysis. RESULTS The final sample population was 53 children, with an average age of 7.2 years. The average initial PASS score (scale of ascending severity from 0 to 6) was 2.5. After adjusting for BMI, age category, gender and smoke exposure, rs912142 was associated with decreased odds of having low BDR (OR, 0.20; 95% confidence interval (CI), 0.02-0.92), and rs7081864 and rs7903366 were associated with decreased odds of having high BDR (OR, 0.097; 95% CI, 0.009-0.62). CONCLUSIONS We found three SNPs significantly associated with pediatric African American BDR that provide information regarding a child's potential response to emergency asthma exacerbation treatment. Once validated in larger studies, such information could guide pharmacogenomic evidence-based emergency asthma treatment to improve patient outcomes.
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Affiliation(s)
- Jennifer N Fishe
- Department of Emergency Medicine, Division of Research, University of Florida College of Medicine - Jacksonville
- Center for Data Solutions, University of Florida College of Medicine - Jacksonville
| | - Guillaume Labilloy
- Center for Data Solutions, University of Florida College of Medicine - Jacksonville
| | - Rebecca Higley
- Department of Emergency Medicine, Division of Research, University of Florida College of Medicine - Jacksonville
| | - Deirdre Casey
- University of Florida Health Jacksonville, Jacksonville
| | - Amber Ginn
- Department of Pathology, University of Florida College of Medicine - Jacksonville
| | - Brett Baskovich
- Department of Pathology, University of Florida College of Medicine - Jacksonville
| | - Kathryn V Blake
- Nemours Center for Pharmacogenomics and Translational Research, Jacksonville, Florida, USA
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21
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Methods and implementation of a pediatric asthma pharmacogenomic study in the emergency department setting. Pharmacogenet Genomics 2021; 30:201-207. [PMID: 33017130 DOI: 10.1097/fpc.0000000000000414] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
OBJECTIVES The emergency department (ED) is a challenging setting to conduct pharmacogenomic studies and integrate that data into fast-paced and potentially life-saving treatment decisions. Therefore, our objective is to present the methods and feasibility of a pilot pharmacogenomic study set in the ED that measured pediatric bronchodilator response (BDR) during acute asthma exacerbations. METHODS This is an exploratory pilot study that collected buccal swabs for DNA and measured BDR during ED encounters for pediatric asthma exacerbations. We evaluated the study's feasibility with a qualitative analysis of ED provider surveys and quantitatively by the proportion of eligible patients enrolled. RESULTS We enrolled 59 out of 90 patients (65%) that were identified and considered eligible during a 5-month period (target enrollment 60 patients over 12 months). The median patient age was 7 years (interquartile range 4-9 years), 61% (N = 36) were male, and 92% (N = 54) were African American. Quality DNA collection was successful for all 59 patients. The ED provider survey response rate was 100%. Most ED providers reported that the study did not impact their workflow (98% of physicians, 88% of nurses, and 90% of respiratory therapists). ED providers did report difficulties with spirometry in the younger age group. CONCLUSIONS Pharmacogenomic studies can be conducted in the ED setting, and enroll a younger patient population with a high proportion of minority participants. By disseminating this study's methods and feasibility analysis, we aim to increase interest in pharmacogenomic studies set in the ED and aimed toward future ED-based pharmacogenomic decision-making.
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22
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Genetic Ancestry Inference and Its Application for the Genetic Mapping of Human Diseases. Int J Mol Sci 2021; 22:ijms22136962. [PMID: 34203440 PMCID: PMC8269095 DOI: 10.3390/ijms22136962] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Revised: 06/24/2021] [Accepted: 06/25/2021] [Indexed: 12/21/2022] Open
Abstract
Admixed populations arise when two or more ancestral populations interbreed. As a result of this admixture, the genome of admixed populations is defined by tracts of variable size inherited from these parental groups and has particular genetic features that provide valuable information about their demographic history. Diverse methods can be used to derive the ancestry apportionment of admixed individuals, and such inferences can be leveraged for the discovery of genetic loci associated with diseases and traits, therefore having important biomedical implications. In this review article, we summarize the most common methods of global and local genetic ancestry estimation and discuss the use of admixture mapping studies in human diseases.
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23
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Genetic Determinants of Poor Response to Treatment in Severe Asthma. Int J Mol Sci 2021; 22:ijms22084251. [PMID: 33923891 PMCID: PMC8073667 DOI: 10.3390/ijms22084251] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2021] [Revised: 04/16/2021] [Accepted: 04/17/2021] [Indexed: 01/02/2023] Open
Abstract
Severe asthma is a multifactorial disorder with marked phenotypic heterogeneity and complex interactions between genetics and environmental risk factors, which could, at least in part, explain why during standard pharmacologic treatment, many patients remain poorly controlled and at an increased risk of airway remodeling and disease progression. The concept of “precision medicine” to better suit individual unique needs is an emerging trend in the management of chronic respiratory diseases. Over the past few years, Genome-Wide Association Studies (GWAS) have revealed novel pharmacogenetic variants related to responses to inhaled corticosteroids and the clinical efficacy of bronchodilators. Optimal clinical response to treatment may vary between racial/ethnic groups or individuals due to genetic differences. It is also plausible to assume that epigenetic factors play a key role in the modulation of gene expression patterns and inflammatory cytokines. Remarkably, specific genetic variants related to treatment effectiveness may indicate promising pathways for novel therapies in severe asthma. In this review, we provide a concise update of genetic determinants of poor response to treatment in severe asthma and future directions in the field.
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24
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Goddard PC, Keys KL, Mak ACY, Lee EY, Liu AK, Samedy-Bates LA, Risse-Adams O, Contreras MG, Elhawary JR, Hu D, Huntsman S, Oh SS, Salazar S, Eng C, Himes BE, White MJ, Burchard EG. Integrative genomic analysis in African American children with asthma finds three novel loci associated with lung function. Genet Epidemiol 2021; 45:190-208. [PMID: 32989782 PMCID: PMC7902343 DOI: 10.1002/gepi.22365] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2020] [Revised: 08/21/2020] [Accepted: 09/14/2020] [Indexed: 11/06/2022]
Abstract
Bronchodilator (BD) drugs are commonly prescribed for treatment and management of obstructive lung function present with diseases such as asthma. Administration of BD medication can partially or fully restore lung function as measured by pulmonary function tests. The genetics of baseline lung function measures taken before BD medication have been extensively studied, and the genetics of the BD response itself have received some attention. However, few studies have focused on the genetics of post-BD lung function. To address this gap, we analyzed lung function phenotypes in 1103 subjects from the Study of African Americans, Asthma, Genes, and Environment, a pediatric asthma case-control cohort, using an integrative genomic analysis approach that combined genotype, locus-specific genetic ancestry, and functional annotation information. We integrated genome-wide association study (GWAS) results with an admixture mapping scan of three pulmonary function tests (forced expiratory volume in 1 s [FEV1 ], forced vital capacity [FVC], and FEV1 /FVC) taken before and after albuterol BD administration on the same subjects, yielding six traits. We identified 18 GWAS loci, and five additional loci from admixture mapping, spanning several known and novel lung function candidate genes. Most loci identified via admixture mapping exhibited wide variation in minor allele frequency across genotyped global populations. Functional fine-mapping revealed an enrichment of epigenetic annotations from peripheral blood mononuclear cells, fetal lung tissue, and lung fibroblasts. Our results point to three novel potential genetic drivers of pre- and post-BD lung function: ADAMTS1, RAD54B, and EGLN3.
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Affiliation(s)
- Pagé C. Goddard
- Department of Genetics, Stanford University, Stanford, California, USA
- Department of Medicine, University of California, San Francisco, California, USA
| | - Kevin L. Keys
- Department of Medicine, University of California, San Francisco, California, USA
- Berkeley Institute for Data Science, University of California, Berkeley, California, USA
| | - Angel C. Y. Mak
- Department of Medicine, University of California, San Francisco, California, USA
| | - Eunice Y. Lee
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
| | - Amy K. Liu
- Department of Neurology, University of California, San Francisco, California, USA
| | - Lesly-Anne Samedy-Bates
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
| | - Oona Risse-Adams
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Biology, University of California, Santa Cruz, California, USA
| | - María G. Contreras
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Biology, San Francisco State University, San Francisco, California, USA
| | - Jennifer R. Elhawary
- Department of Medicine, University of California, San Francisco, California, USA
| | - Donglei Hu
- Department of Medicine, University of California, San Francisco, California, USA
| | - Scott Huntsman
- Department of Medicine, University of California, San Francisco, California, USA
| | - Sam S. Oh
- Department of Medicine, University of California, San Francisco, California, USA
| | - Sandra Salazar
- Department of Medicine, University of California, San Francisco, California, USA
| | - Celeste Eng
- Department of Medicine, University of California, San Francisco, California, USA
| | - Blanca E. Himes
- Department of Biostatistics, Epidemiology and Informatics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Marquitta J. White
- Department of Medicine, University of California, San Francisco, California, USA
| | - Esteban G. Burchard
- Department of Medicine, University of California, San Francisco, California, USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, California, USA
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25
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Walsh R, Voorhies K, McDonald ML, McGeachie M, Sordillo JE, Lange C, Wu AC, Lutz SM. The Role of SNP Interactions when Determining Independence of Novel Signals in Genetic Association Studies-An Application to ARG1 and Bronchodilator Response. J Pers Med 2021; 11:jpm11020145. [PMID: 33669563 PMCID: PMC7922125 DOI: 10.3390/jpm11020145] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/21/2020] [Revised: 02/12/2021] [Accepted: 02/15/2021] [Indexed: 11/16/2022] Open
Abstract
Genome-wide association studies (GWAS) play a critical role in identifying many loci for common diseases and traits. There has been a rapid increase in the number of GWAS over the past decade. As additional GWAS are being conducted, it is unclear whether a novel signal associated with the trait of interest is independent of single nucleotide polymorphisms (SNPs) in the same region that has been previously associated with the trait of interest. The general approach to determining whether the novel association is independent of previous signals is to examine the association of the novel SNP with the trait of interest conditional on the previously identified SNP and/or calculate linkage disequilibrium (LD) between the two SNPs. However, the role of epistasis and SNP by SNP interactions are rarely considered. Through simulation studies, we examined the role of SNP by SNP interactions when determining the independence of two genetic association signals. We have created an R package on Github called gxgRC to generate these simulation studies based on user input. In genetic association studies of asthma, we considered the role of SNP by SNP interactions when determining independence of signals for SNPs in the ARG1 gene and bronchodilator response.
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Affiliation(s)
- Ryan Walsh
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA; (R.W.); (K.V.); (J.E.S.); (A.C.W.)
| | - Kirsten Voorhies
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA; (R.W.); (K.V.); (J.E.S.); (A.C.W.)
| | - Merry-Lynn McDonald
- Division of Pulmonary, Allergy and Critical Care Medicine, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL 35294, USA;
| | - Michael McGeachie
- Channing Division of Network Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA 02115, USA;
| | - Joanne E. Sordillo
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA; (R.W.); (K.V.); (J.E.S.); (A.C.W.)
| | - Christoph Lange
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
| | - Ann Chen Wu
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA; (R.W.); (K.V.); (J.E.S.); (A.C.W.)
| | - Sharon M. Lutz
- Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA 02215, USA; (R.W.); (K.V.); (J.E.S.); (A.C.W.)
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA;
- Correspondence: ; Tel.: +1-617-867-4823; Fax: +1-617-867-4853
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Atkinson EG, Maihofer AX, Kanai M, Martin AR, Karczewski KJ, Santoro ML, Ulirsch JC, Kamatani Y, Okada Y, Finucane HK, Koenen KC, Nievergelt CM, Daly MJ, Neale BM. Tractor uses local ancestry to enable the inclusion of admixed individuals in GWAS and to boost power. Nat Genet 2021; 53:195-204. [PMID: 33462486 PMCID: PMC7867648 DOI: 10.1038/s41588-020-00766-y] [Citation(s) in RCA: 104] [Impact Index Per Article: 34.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/15/2020] [Accepted: 12/15/2020] [Indexed: 12/26/2022]
Abstract
Admixed populations are routinely excluded from genomic studies due to concerns over population structure. Here, we present a statistical framework and software package, Tractor, to facilitate the inclusion of admixed individuals in association studies by leveraging local ancestry. We test Tractor with simulated and empirical two-way admixed African-European cohorts. Tractor generates accurate ancestry-specific effect-size estimates and P values, can boost genome-wide association study (GWAS) power and improves the resolution of association signals. Using a local ancestry-aware regression model, we replicate known hits for blood lipids, discover novel hits missed by standard GWAS and localize signals closer to putative causal variants.
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Affiliation(s)
- Elizabeth G Atkinson
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA.
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA.
| | - Adam X Maihofer
- Department of Psychiatry, University of California, San Diego, La Jolla, CA, USA
| | - Masahiro Kanai
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Bioinformatics and Integrative Genomics, Harvard Medical School, Boston, MA, USA
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
| | - Alicia R Martin
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Konrad J Karczewski
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Marcos L Santoro
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Departamento de Psiquiatria, Universidade Federal de São Paulo, São Paulo, Brazil
- Departamento de Morfologia e Genética, Universidade Federal de São Paulo, São Paulo, Brazil
| | - Jacob C Ulirsch
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Biological and Biomedical Sciences, Harvard Medical School, Boston, MA, USA
| | - Yoichiro Kamatani
- Laboratory of Complex Trait Genomics, Department of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, Tokyo, Japan
| | - Yukinori Okada
- Department of Statistical Genetics, Graduate School of Medicine, Osaka University, Suita, Japan
- Laboratory of Statistical Immunology, Immunology Frontier Research Center (WPI-IFReC), Osaka University, Suita, Japan
- Integrated Frontier Research for Medical Science Division, Institute for Open and Transdisciplinary Research Initiatives, Osaka University, Suita, Japan
| | - Hilary K Finucane
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
| | - Karestan C Koenen
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA
| | | | - Mark J Daly
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Program in Medical and Population Genetics, Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Institute for Molecular Medicine Finland, University of Helsinki, Helsinki, Finland
| | - Benjamin M Neale
- Analytic and Translational Genetics Unit, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA
- Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA
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Hassan R, Allali I, Agamah FE, Elsheikh SSM, Thomford NE, Dandara C, Chimusa ER. Drug response in association with pharmacogenomics and pharmacomicrobiomics: towards a better personalized medicine. Brief Bioinform 2020; 22:6012864. [PMID: 33253350 DOI: 10.1093/bib/bbaa292] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2020] [Revised: 09/19/2020] [Accepted: 10/03/2020] [Indexed: 12/15/2022] Open
Abstract
Researchers have long been presented with the challenge imposed by the role of genetic heterogeneity in drug response. For many years, Pharmacogenomics and pharmacomicrobiomics has been investigating the influence of an individual's genetic background to drug response and disposition. More recently, the human gut microbiome has proven to play a crucial role in the way patients respond to different therapeutic drugs and it has been shown that by understanding the composition of the human microbiome, we can improve the drug efficacy and effectively identify drug targets. However, our knowledge on the effect of host genetics on specific gut microbes related to variation in drug metabolizing enzymes, the drug remains limited and therefore limits the application of joint host-microbiome genome-wide association studies. In this paper, we provide a historical overview of the complex interactions between the host, human microbiome and drugs. While discussing applications, challenges and opportunities of these studies, we draw attention to the critical need for inclusion of diverse populations and the development of an innovative and combined pharmacogenomics and pharmacomicrobiomics approach, that may provide an important basis in personalized medicine.
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Affiliation(s)
- Radia Hassan
- Division of Human Genetics, Department of Pathology, University of Cape Town
| | - Imane Allali
- Department of Biology, Faculty of Sciences, Mohammed V University in Rabat, Morocco
| | - Francis E Agamah
- Division of Human Genetics, Department of Pathology, University of Cape Town
| | | | - Nicholas E Thomford
- Lecturers at the Department of Medical Biochemistry School of Medical Sciences, University of Cape Coast, Ghana
| | - Collet Dandara
- Division of Human Genetics, Department of Pathology, University of Cape Town
| | - Emile R Chimusa
- Division of Human Genetics, Department of Pathology, University of Cape Town
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28
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Asthma genomics and pharmacogenomics. Curr Opin Immunol 2020; 66:136-142. [PMID: 33171417 DOI: 10.1016/j.coi.2020.10.001] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2020] [Accepted: 10/04/2020] [Indexed: 12/16/2022]
Abstract
In this review, we summarize recent published work interrogating the relationship between genetic variation or gene expression regulation across the genome and asthma or asthma treatment outcomes. This includes 11 genome-wide association studies of asthma phenotypes that collectively identified 64 novel loci; transcriptome-wide asthma association studies which identified genes involved in virus recognition, bacterial infection, lung tissue remodeling, eosinophilic and neutrophilic inflammation and genes in the chromosome 17q12 asthma susceptibility locus; and three epigenome-wide studies of asthma that had robust sample sizes and replicated findings. We also highlight pharmacogenomic studies of corticosteroids, bronchodilator response to albuterol and zileuton, although finding from these studies may still be preliminary due to their relatively small sample sizes and limited availability of replication cohorts.
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Magaña J, Contreras MG, Keys KL, Risse-Adams O, Goddard PC, Zeiger AM, Mak ACY, Elhawary JR, Samedy-Bates LA, Lee E, Thakur N, Hu D, Eng C, Salazar S, Huntsman S, Hu T, Burchard EG, White MJ. An epistatic interaction between pre-natal smoke exposure and socioeconomic status has a significant impact on bronchodilator drug response in African American youth with asthma. BioData Min 2020; 13:7. [PMID: 32636926 PMCID: PMC7333373 DOI: 10.1186/s13040-020-00218-7] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2020] [Accepted: 06/23/2020] [Indexed: 11/30/2022] Open
Abstract
BACKGROUND Asthma is one of the leading chronic illnesses among children in the United States. Asthma prevalence is higher among African Americans (11.2%) compared to European Americans (7.7%). Bronchodilator medications are part of the first-line therapy, and the rescue medication, for acute asthma symptoms. Bronchodilator drug response (BDR) varies substantially among different racial/ethnic groups. Asthma prevalence in African Americans is only 3.5% higher than that of European Americans, however, asthma mortality among African Americans is four times that of European Americans; variation in BDR may play an important role in explaining this health disparity. To improve our understanding of disparate health outcomes in complex phenotypes such as BDR, it is important to consider interactions between environmental and biological variables. RESULTS We evaluated the impact of pairwise and three-variable interactions between environmental, social, and biological variables on BDR in 233 African American youth with asthma using Visualization of Statistical Epistasis Networks (ViSEN). ViSEN is a non-parametric entropy-based approach able to quantify interaction effects using an information-theory metric known as Information Gain (IG). We performed analyses in the full dataset and in sex-stratified subsets. Our analyses identified several interaction models significantly, and suggestively, associated with BDR. The strongest interaction significantly associated with BDR was a pairwise interaction between pre-natal smoke exposure and socioeconomic status (full dataset IG: 2.78%, p = 0.001; female IG: 7.27%, p = 0.004)). Sex-stratified analyses yielded divergent results for females and males, indicating the presence of sex-specific effects. CONCLUSIONS Our study identified novel interaction effects significantly, and suggestively, associated with BDR in African American children with asthma. Notably, we found that all of the interactions identified by ViSEN were "pure" interaction effects, in that they were not the result of strong main effects on BDR, highlighting the complexity of the network of biological and environmental factors impacting this phenotype. Several associations uncovered by ViSEN would not have been detected using regression-based methods, thus emphasizing the importance of employing statistical methods optimized to detect both additive and non-additive interaction effects when studying complex phenotypes such as BDR. The information gained in this study increases our understanding and appreciation of the complex nature of the interactions between environmental and health-related factors that influence BDR and will be invaluable to biomedical researchers designing future studies.
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Affiliation(s)
- J. Magaña
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - M. G. Contreras
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Department of Biology, San Francisco State University, San Francisco, CA USA
| | - K. L. Keys
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Berkeley Institute for Data Science, University of California, Berkeley, CA USA
| | - O. Risse-Adams
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Lowell Science Research Program, Lowell High School, San Francisco, CA USA
- Department of Biology, University of California, Santa Cruz, CA USA
| | - P. C. Goddard
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Department of Genetics, Stanford University, Stanford, CA USA
| | - A. M. Zeiger
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Sidney Kimmel Medical College, Thomas Jefferson University, Philadelphia, PA USA
| | - A. C. Y. Mak
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - J. R. Elhawary
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - L. A. Samedy-Bates
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - E. Lee
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - N. Thakur
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - D. Hu
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - C. Eng
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - S. Salazar
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - S. Huntsman
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
| | - T. Hu
- School of Computing, Queen’s University, Kingston, ON Canada
| | - E. G. Burchard
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA USA
| | - M. J. White
- Department of Medicine, University of California, 1550 4th Street, UCSF Rock Hall, Box 2911, San Francisco, CA 94158 USA
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Precision Medicine in Childhood Asthma: Omic Studies of Treatment Response. Int J Mol Sci 2020; 21:ijms21082908. [PMID: 32326339 PMCID: PMC7215369 DOI: 10.3390/ijms21082908] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/28/2020] [Revised: 04/11/2020] [Accepted: 04/17/2020] [Indexed: 12/12/2022] Open
Abstract
Asthma is a heterogeneous and multifactorial respiratory disease with an important impact on childhood. Difficult-to-treat asthma is not uncommon among children, and it causes a high burden to the patient, caregivers, and society. This review aims to summarize the recent findings on pediatric asthma treatment response revealed by different omic approaches conducted in 2018–2019. A total of 13 studies were performed during this period to assess the role of genomics, epigenomics, transcriptomics, metabolomics, and the microbiome in the response to short-acting beta agonists, inhaled corticosteroids, and leukotriene receptor antagonists. These studies have identified novel associations of genetic markers, epigenetic modifications, metabolites, bacteria, and molecular mechanisms involved in asthma treatment response. This knowledge will allow us establishing molecular biomarkers that could be integrated with clinical information to improve the management of children with asthma.
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31
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Zhang H, De T, Zhong Y, Perera MA. The Advantages and Challenges of Diversity in Pharmacogenomics: Can Minority Populations Bring Us Closer to Implementation? Clin Pharmacol Ther 2020; 106:338-349. [PMID: 31038731 DOI: 10.1002/cpt.1491] [Citation(s) in RCA: 26] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2019] [Accepted: 04/18/2019] [Indexed: 01/01/2023]
Abstract
Health disparities exist among minorities in the United States, with differences seen in disease prevalence, mortality, and responses to medications. These differences are multifactorial with genetic variation explaining a portion of this variability. Pharmacogenomics aims to find the effect of genetic variations on drug response, with the goal of optimizing drug therapy and development. Although genome-wide association studies have been useful in unbiasedly surveying the genome for genetic drivers of clinically relevant phenotypes, most of these studies have been conducted in mainly participants of European and Asian descent, contributing to a growing health disparity in precision medicine. Diversity is important to pharmacogenomic studies, and there may be real advantages to the use of these complex genomes in pharmacogenomics. In this review we will outline some of the advantages and confounders of pharmacogenomics in minorities, describe the role of genetic variation in pharmacologic pathways, and highlight a number of population-specific findings.
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Affiliation(s)
- Honghong Zhang
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Tanima De
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Yizhen Zhong
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
| | - Minoli A Perera
- Department of Pharmacology, Feinberg School of Medicine, Northwestern University, Chicago, Illinois, USA
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32
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Perez-Garcia J, Espuela-Ortiz A, Lorenzo-Diaz F, Pino-Yanes M. Pharmacogenetics of Pediatric Asthma: Current Perspectives. PHARMACOGENOMICS & PERSONALIZED MEDICINE 2020; 13:89-103. [PMID: 32256100 PMCID: PMC7090194 DOI: 10.2147/pgpm.s201276] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/20/2019] [Accepted: 03/03/2020] [Indexed: 12/11/2022]
Abstract
Asthma is a chronic respiratory disease that affects 339 million people worldwide and has a considerable impact on the pediatric population. Asthma symptoms can be controlled by pharmacological treatment. However, some patients do not respond to therapy and continue suffering from symptoms, which impair the quality of life of patients and limit their daily activity. Genetic variation has been shown to have a role in treatment response. The aim of this review is to update the main findings described in pharmacogenetic studies of pediatric asthma published from January 1, 2018 to December 31, 2019. During this period, the response to short-acting beta-agonists and inhaled corticosteroids in childhood asthma has been evaluated by eleven candidate-gene studies, one meta-analysis of a candidate gene, and six pharmacogenomic studies. The findings have allowed validating the association of genes previously related to asthma treatment response (ADRB2, GSDMB, FCER2, VEGFA, SPAT2SL, ASB3, and COL2A1), and identifying novel associations (PRKG1, DNAH5, IL1RL1, CRISPLD2, MMP9, APOBEC3B-APOBEC3C, EDDM3B, and BBS9). However, some results are not consistent across studies, highlighting the need to conduct larger studies in diverse populations with more homogeneous definitions of treatment response. Once stronger evidence was established, genetic variants will have the potential to be applied in clinical practice as biomarkers of treatment response enhancing asthma management and improving the quality of life of asthma patients.
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Affiliation(s)
- Javier Perez-Garcia
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
| | - Antonio Espuela-Ortiz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
| | - Fabian Lorenzo-Diaz
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain.,Instituto Universitario de Enfermedades Tropicales y Salud Pública de Canarias (IUETSPC), Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
| | - Maria Pino-Yanes
- Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Comunidad de Madrid, Spain.,Instituto de Tecnologías Biomédicas (ITB), Universidad de La Laguna, San Cristóbal de La Laguna, Santa Cruz de Tenerife, Spain
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Tong DMH, Hernandez RD. Population genetic simulation study of power in association testing across genetic architectures and study designs. Genet Epidemiol 2020; 44:90-103. [PMID: 31587362 PMCID: PMC6980249 DOI: 10.1002/gepi.22264] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Revised: 08/26/2019] [Accepted: 09/16/2019] [Indexed: 12/22/2022]
Abstract
While it is well established that genetics can be a major contributor to population variation of complex traits, the relative contributions of rare and common variants to phenotypic variation remains a matter of considerable debate. Here, we simulate genetic and phenotypic data across different case/control panel sampling strategies, sequencing methods, and genetic architecture models based on evolutionary forces to determine the statistical performance of rare variant association tests (RVATs) widely in use. We find that the highest statistical power of RVATs is achieved by sampling case/control individuals from the extremes of an underlying quantitative trait distribution. We also demonstrate that the use of genotyping arrays, in conjunction with imputation from a whole-genome sequenced (WGS) reference panel, recovers the vast majority (90%) of the power that could be achieved by sequencing the case/control panel using current tools. Finally, we show that for dichotomous traits, the statistical performance of RVATs decreases as rare variants become more important in the trait architecture. Our results extend previous work to show that RVATs are insufficiently powered to make generalizable conclusions about the role of rare variants in dichotomous complex traits.
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Affiliation(s)
- Dominic M. H. Tong
- University of California, Berkeley ‐ University of California, San Francisco Graduate Program in BioengineeringSan FranciscoCalifornia
| | - Ryan D. Hernandez
- Department of Bioengineering and Therapeutic SciencesUniversity of CaliforniaSan FranciscoCalifornia
- Department of Human GeneticsMcGill UniversityMontrealCanada
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34
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Zhang E, Levin AM, Williams LK. How does race and ethnicity effect the precision treatment of asthma? EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2019; 4:337-356. [PMID: 33015363 DOI: 10.1080/23808993.2019.1690396] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
Abstract
Introduction Asthma is a common condition that affects large numbers of children and adults, yet the burden of disease is not equally distributed amongst groups. In the United States, African Americans and Puerto Ricans have higher rates of asthma and its complications when compared with European Americans. However, clinical trials and genetic studies have largely focused on the latter group. Areas covered Here we examine what is known regarding differences in asthma treatment response by race-ethnicity. We also review existing genetic studies related to the use of asthma medications, paying special attention to studies that included substantial numbers of non-white population groups. Publicly accessible search engines of the medical literature were queried using combinations of the terms asthma, race, ethnicity, pharmacogenomics, and pharmacogenetics, as well as the names of individual asthma medication classes. The list of articles reviewed was supplemented by bibliographies and expert knowledge. Expert opinion A substantial and coordinated effort is still needed to both identify and validate genetic biomarkers of asthma medication response, as currently there are no clinically actionable genetic markers available for this purpose. The path to identifying such markers in non-white populations is even more formidable, since these groups are underrepresented in existing data.
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Affiliation(s)
- Ellen Zhang
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
| | - Albert M Levin
- Department of Public Health Sciences, Henry Ford Health System, Detroit, MI, USA
| | - L Keoki Williams
- Center for Individualized and Genomic Medicine Research (CIGMA), Department of Internal Medicine, Henry Ford Health System, Detroit, MI, USA
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Schoettler N, Rodríguez E, Weidinger S, Ober C. Advances in asthma and allergic disease genetics: Is bigger always better? J Allergy Clin Immunol 2019; 144:1495-1506. [PMID: 31677964 DOI: 10.1016/j.jaci.2019.10.023] [Citation(s) in RCA: 37] [Impact Index Per Article: 7.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2019] [Revised: 10/22/2019] [Accepted: 10/23/2019] [Indexed: 12/13/2022]
Abstract
This review focuses on genome-wide association studies (GWASs) of asthma and allergic diseases published between January 1, 2018, and June 30, 2019. During this time period, there were 38 GWASs reported in 19 articles, including the largest performed to date for many of these conditions. Overall, we learned that childhood-onset asthma is associated with the most independent loci compared with other defined groups of asthma and allergic disease cases; adult-onset asthma and moderate-to-severe asthma are associated with fewer genes, which are largely a subset of those associated with childhood-onset asthma. There is significant genetic overlap between asthma and allergic diseases, particularly with respect to childhood-onset asthma, which involves genes that reflect the importance of barrier function biology, and to HLA region genes, which are the most frequently associated genes overall in both groups of diseases. Although the largest GWASs in African American and Latino/Hispanic populations were reported during this period, they are still significantly underpowered compared with studies reported in populations of European ancestry, highlighting the need for larger studies, particularly in patients with childhood-onset asthma and allergic diseases, in these important populations that carry the greatest burden of disease.
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Affiliation(s)
- Nathan Schoettler
- Section of Pulmonary and Critical Care Medicine, Department of Medicine, University of Chicago, Chicago, Ill; Department of Human Genetics, University of Chicago, Chicago, Ill.
| | - Elke Rodríguez
- Department of Dermatology, Allergology and Venereology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Stephan Weidinger
- Department of Dermatology, Allergology and Venereology, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany
| | - Carole Ober
- Department of Human Genetics, University of Chicago, Chicago, Ill
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36
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Szpiech ZA, Mak ACY, White MJ, Hu D, Eng C, Burchard EG, Hernandez RD. Ancestry-Dependent Enrichment of Deleterious Homozygotes in Runs of Homozygosity. Am J Hum Genet 2019; 105:747-762. [PMID: 31543216 PMCID: PMC6817522 DOI: 10.1016/j.ajhg.2019.08.011] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2019] [Accepted: 08/27/2019] [Indexed: 12/20/2022] Open
Abstract
Runs of homozygosity (ROH) are important genomic features that manifest when an individual inherits two haplotypes that are identical by descent. Their length distributions are informative about population history, and their genomic locations are useful for mapping recessive loci contributing to both Mendelian and complex disease risk. We have previously shown that ROH, and especially long ROH that are likely the result of recent parental relatedness, are enriched for homozygous deleterious coding variation in a worldwide sample of outbred individuals. However, the distribution of ROH in admixed populations and their relationship to deleterious homozygous genotypes is understudied. Here we analyze whole-genome sequencing data from 1,441 unrelated individuals from self-identified African American, Puerto Rican, and Mexican American populations. These populations are three-way admixed between European, African, and Native American ancestries and provide an opportunity to study the distribution of deleterious alleles partitioned by local ancestry and ROH. We re-capitulate previous findings that long ROH are enriched for deleterious variation genome-wide. We then partition by local ancestry and show that deleterious homozygotes arise at a higher rate when ROH overlap African ancestry segments than when they overlap European or Native American ancestry segments of the genome. These results suggest that, while ROH on any haplotype background are associated with an inflation of deleterious homozygous variation, African haplotype backgrounds may play a particularly important role in the genetic architecture of complex diseases for admixed individuals, highlighting the need for further study of these populations.
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Affiliation(s)
- Zachary A Szpiech
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA; Department of Biological Sciences, Auburn University, Auburn, AL 36842, USA.
| | - Angel C Y Mak
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Marquitta J White
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Donglei Hu
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Celeste Eng
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Esteban G Burchard
- Department of Medicine, University of California San Francisco, San Francisco, CA 94158, USA
| | - Ryan D Hernandez
- Department of Bioengineering and Therapeutic Sciences, University of California San Francisco, San Francisco, CA 94158, USA; Institute for Human Genetics, University of California San Francisco, San Francisco, CA 94158, USA; Quantitative Biosciences Institute, University of California San Francisco, San Francisco, CA 94158, USA; Department of Human Genetics, McGill University, Montreal, QC H3A 0G1, Canada; Genome Quebec Innovation Center, McGill University, Montreal, QC H3A 0G1, Canada.
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37
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Grinde KE, Brown LA, Reiner AP, Thornton TA, Browning SR. Genome-wide Significance Thresholds for Admixture Mapping Studies. Am J Hum Genet 2019; 104:454-465. [PMID: 30773276 PMCID: PMC6407497 DOI: 10.1016/j.ajhg.2019.01.008] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/05/2018] [Accepted: 01/17/2019] [Indexed: 01/25/2023] Open
Abstract
Admixture mapping studies have become more common in recent years, due in part to technological advances and growing international efforts to increase the diversity of genetic studies. However, many open questions remain about appropriate implementation of admixture mapping studies, including how best to control for multiple testing, particularly in the presence of population structure. In this study, we develop a theoretical framework to characterize the correlation of local ancestry and admixture mapping test statistics in admixed populations with contributions from any number of ancestral populations and arbitrary population structure. Based on this framework, we develop an analytical approach for obtaining genome-wide significance thresholds for admixture mapping studies. We validate our approach via analysis of simulated traits with real genotype data for 8,064 unrelated African American and 3,425 Hispanic/Latina women from the Women's Health Initiative SNP Health Association Resource (WHI SHARe). In an application to these WHI SHARe data, our approach yields genome-wide significant p value thresholds of 2.1 × 10-5 and 4.5 × 10-6 for admixture mapping studies in the African American and Hispanic/Latina cohorts, respectively. Compared to other commonly used multiple testing correction procedures, our method is fast, easy to implement (using our publicly available R package), and controls the family-wise error rate even in structured populations. Importantly, we note that the appropriate admixture mapping significance threshold depends on the number of ancestral populations, generations since admixture, and population structure of the sample; as a result, significance thresholds are not, in general, transferable across studies.
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Affiliation(s)
- Kelsey E Grinde
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA.
| | - Lisa A Brown
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA; Seattle Genetics, Bothell, WA 98021, USA
| | - Alexander P Reiner
- Department of Epidemiology, University of Washington, Seattle, WA 98195, USA; Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA
| | - Timothy A Thornton
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
| | - Sharon R Browning
- Department of Biostatistics, University of Washington, Seattle, WA 98195, USA
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Hernandez-Pacheco N, Pino-Yanes M, Flores C. Genomic Predictors of Asthma Phenotypes and Treatment Response. Front Pediatr 2019; 7:6. [PMID: 30805318 PMCID: PMC6370703 DOI: 10.3389/fped.2019.00006] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/09/2018] [Accepted: 01/10/2019] [Indexed: 12/11/2022] Open
Abstract
Asthma is a complex respiratory disease considered as the most common chronic condition in children. A large genetic contribution to asthma susceptibility is predicted by the clustering of asthma and allergy symptoms among relatives and the large disease heritability estimated from twin studies, ranging from 55 to 90%. Genetic basis of asthma has been extensively investigated in the past 40 years using linkage analysis and candidate-gene association studies. However, the development of dense arrays for polymorphism genotyping has enabled the transition toward genome-wide association studies (GWAS), which have led the discovery of several unanticipated asthma genes in the last 11 years. Despite this, currently known risk variants identified using many thousand samples from distinct ethnicities only explain a small proportion of asthma heritability. This review examines the main findings of the last 2 years in genomic studies of asthma using GWAS and admixture mapping studies, as well as the direction of studies fostering integrative perspectives involving omics data. Additionally, we discuss the need for assessing the whole spectrum of genetic variation in association studies of asthma susceptibility, severity, and treatment response in order to further improve our knowledge of asthma genes and predictive biomarkers. Leveraging the individual's genetic information will allow a better understanding of asthma pathogenesis and will facilitate the transition toward a more precise diagnosis and treatment.
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Affiliation(s)
- Natalia Hernandez-Pacheco
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain
| | - Maria Pino-Yanes
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,Genomics and Health Group, Department of Biochemistry, Microbiology, Cell Biology and Genetics, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain
| | - Carlos Flores
- Research Unit, Hospital Universitario N.S. de Candelaria, Universidad de La Laguna, Santa Cruz de Tenerife, Spain.,CIBER de Enfermedades Respiratorias, Instituto de Salud Carlos III, Madrid, Spain.,Genomics Division, Instituto Tecnológico y de Energías Renovables, Santa Cruz de Tenerife, Spain
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