1
|
Zhang K, Wang C, Wu Y, Xu Z. Identification of novel biomarkers in obstructive sleep apnea via integrated bioinformatics analysis and experimental validation. PeerJ 2023; 11:e16608. [PMID: 38077447 PMCID: PMC10702330 DOI: 10.7717/peerj.16608] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Accepted: 11/15/2023] [Indexed: 12/18/2023] Open
Abstract
Background Obstructive sleep apnea (OSA) is a complex and multi-gene inherited disease caused by both genetic and environmental factors. However, due to the high cost of diagnosis and complex operation, its clinical application is limited. This study aims to explore potential target genes associated with OSA and establish a corresponding diagnostic model. Methods This study used microarray datasets from the Gene Expression Omnibus (GEO) database to identify differentially expressed genes (DEGs) related to OSA and perform functional annotation and pathway analysis. The study employed multi-scale embedded gene co-expression network analysis (MEGENA) combined with least absolute shrinkage and selection operator (LASSO) regression analysis to select hub genes and construct a diagnostic model for OSA. In addition, the study conducted correlation analysis between hub genes and OSA-related genes, immunoinfiltration, gene set enrichment analysis (GSEA), miRNA network analysis, and identified potential transcription factors (TFs) and targeted drugs for hub genes. Finally, the study used chronic intermittent hypoxia (CIH) mouse model to simulate OSA hypoxic conditions and verify the expression of hub genes in CIH mice. Results In this study, a total of 401 upregulated genes and 275 downregulated genes were identified, and enrichment analysis revealed that these differentially expressed genes may be associated with pathways such as vasculature development, cellular response to cytokine stimulus, and negative regulation of cell population proliferation. Through MEGENA combined with LASSO regression, seven OSA hub genes were identified, including C12orf54, FOS, GPR1, OR9A4, MYO5B, RAB39B, and KLHL4. The diagnostic model constructed based on these genes showed strong stability. The expression levels of hub genes were significantly correlated with the expression levels of OSA-related genes and mainly acted on pathways such as the JAK/STAT signaling pathway and the cytosolic DNA-sensing pathway. Drug-target predictions for hub genes were made using the Connectivity Map (CMap) database and the Drug-Gene Interaction database (Dgidb), which identified targeted therapeutic drugs for the hub genes. In vivo experiments showed that the hub genes were all decreasing in the OSA mouse model. Conclusions This study identified novel biomarkers for OSA and established a reliable diagnostic model. The transcriptional changes identified may help to reveal the pathogenesis, mechanisms, and sequelae of OSA.
Collapse
Affiliation(s)
- Kai Zhang
- Beijing Children’s Hospital, Department of Respiratory Medicine, Beijing, People’s Republic of China
| | - Caizhen Wang
- The Second Hospital of Hebei Medical University, Pediatric Intensive Care Unit, Shijiazhuang, Hebei, People’s Republic of China
| | - Yunxiao Wu
- Beijing Children’s Hospital, Department of Respiratory Medicine, Beijing, People’s Republic of China
| | - Zhifei Xu
- Beijing Children’s Hospital, Department of Respiratory Medicine, Beijing, People’s Republic of China
| |
Collapse
|
2
|
Sofer T, Kurniansyah N, Murray M, Ho YL, Abner E, Esko T, Huffman JE, Cho K, Wilson PWF, Gottlieb DJ. Genome-wide association study of obstructive sleep apnoea in the Million Veteran Program uncovers genetic heterogeneity by sex. EBioMedicine 2023; 90:104536. [PMID: 36989840 PMCID: PMC10065974 DOI: 10.1016/j.ebiom.2023.104536] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/09/2023] [Revised: 03/07/2023] [Accepted: 03/08/2023] [Indexed: 03/30/2023] Open
Abstract
BACKGROUND Genome-wide association studies (GWAS) for obstructive sleep apnoea (OSA) are limited due to the underdiagnosis of OSA, leading to misclassification of OSA, which consequently reduces statistical power. We performed a GWAS of OSA in the Million Veteran Program (MVP) of the U.S. Department of Veterans Affairs (VA) healthcare system, where OSA prevalence is close to its true population prevalence. METHODS We performed GWAS of 568,576 MVP participants, stratified by biological sex and by harmonized race/ethnicity and genetic ancestry (HARE) groups of White, Black, Hispanic, and Asian individuals. We considered both BMI adjusted (BMI-adj) and unadjusted (BMI-unadj) models. We replicated associations in independent datasets, and analysed the heterogeneity of OSA genetic associations across HARE and sex groups. We finally performed a larger meta-analysis GWAS of MVP, FinnGen, and the MGB Biobank, totalling 916,696 individuals. FINDINGS MVP participants are 91% male. OSA prevalence is 21%. In MVP there were 18 and 6 genome-wide significant loci in BMI-unadj and BMI-adj analyses, respectively, corresponding to 21 association regions. Of these, 17 were not previously reported in association with OSA, and 13 replicated in FinnGen (False Discovery Rate p-value < 0.05). There were widespread significant differences in genetic effects between men and women, but less so across HARE groups. Meta-analysis of MVP, FinnGen, and MGB biobank revealed 17 additional, previously unreported, genome-wide significant regions. INTERPRETATION Sex differences in genetic associations with OSA are widespread, likely associated with multiple OSA risk factors. OSA shares genetic underpinnings with several sleep phenotypes, suggesting shared aetiology and causal pathways. FUNDING Described in acknowledgements.
Collapse
Affiliation(s)
- Tamar Sofer
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
| | - Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA
| | - Michael Murray
- Massachusetts Veterans Epidemiology Research and Information Center, VA Healthcare System, Boston, MA, USA
| | - Yuk-Lam Ho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Healthcare System, Boston, MA, USA
| | - Erik Abner
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Tõnu Esko
- Estonian Genome Center, Institute of Genomics, University of Tartu, Tartu, Estonia
| | - Jennifer E Huffman
- Massachusetts Veterans Epidemiology Research and Information Center, VA Healthcare System, Boston, MA, USA; VA Palo Alto Health Care System, Palo Alto, CA, USA; Palo Alto Veterans Institute for Research, Palo Alto, CA, USA
| | - Kelly Cho
- Massachusetts Veterans Epidemiology Research and Information Center, VA Healthcare System, Boston, MA, USA; Division of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA
| | | | - Daniel J Gottlieb
- Division of Sleep and Circadian Disorders, Department of Medicine, Brigham and Women's Hospital, Boston, MA, USA; Massachusetts Veterans Epidemiology Research and Information Center, VA Healthcare System, Boston, MA, USA
| |
Collapse
|
3
|
Madrid-Valero JJ, Gregory AM. Behaviour genetics and sleep: A narrative review of the last decade of quantitative and molecular genetic research in humans. Sleep Med Rev 2023; 69:101769. [PMID: 36933344 DOI: 10.1016/j.smrv.2023.101769] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/04/2022] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/05/2023]
Abstract
During the last decade quantitative and molecular genetic research on sleep has increased considerably. New behavioural genetics techniques have marked a new era for sleep research. This paper provides a summary of the most important findings from the last ten years, on the genetic and environmental influences on sleep and sleep disorders and their associations with health-related variables (including anxiety and depression) in humans. In this review we present a brief summary of the main methods in behaviour genetic research (such as twin and genome-wide association studies). We then discuss key research findings on: genetic and environmental influences on normal sleep and sleep disorders, as well as on the association between sleep and health variables (highlighting a substantial role for genes in individual differences in sleep and their associations with other variables). We end by discussing future lines of enquiry and drawing conclusions, including those focused on problems and misconceptions associated with research of this type. In this last decade our knowledge about genetic and environmental influences on sleep and its disorders has expanded. Both, twin and genome-wide association studies show that sleep and sleep disorders are substantially influenced by genetic factors and for the very first time multiple specific genetic variants have been associated with sleep traits and disorders.
Collapse
Affiliation(s)
- Juan J Madrid-Valero
- Department of Health Psychology, Faculty of Health Sciences, University of Alicante, Spain.
| | - Alice M Gregory
- Department of Psychology, Goldsmiths, University of London, London, United Kingdom
| |
Collapse
|
4
|
Kurniansyah N, Wallace DA, Zhang Y, Yu B, Cade B, Wang H, Ochs-Balcom HM, Reiner AP, Ramos AR, Smith JD, Cai J, Daviglus M, Zee PC, Kaplan R, Kooperberg C, Rich SS, Rotter JI, Gharib SA, Redline S, Sofer T. An integrated multi-omics analysis of sleep-disordered breathing traits implicates P2XR4 purinergic signaling. Commun Biol 2023; 6:125. [PMID: 36721044 PMCID: PMC9889381 DOI: 10.1038/s42003-023-04520-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2022] [Accepted: 01/23/2023] [Indexed: 02/01/2023] Open
Abstract
Sleep Disordered Breathing (SDB) is a common disease associated with increased risk for cardiometabolic, cardiovascular, and cognitive diseases. How SDB affects the molecular environment is still poorly understood. We study the association of three SDB measures with gene expression measured using RNA-seq in multiple blood tissues from the Multi-Ethnic Study of Atherosclerosis. We develop genetic instrumental variables for the associated transcripts as polygenic risk scores (tPRS), then generalize and validate the tPRS in the Women's Health Initiative. We measure the associations of the validated tPRS with SDB and serum metabolites in Hispanic Community Health Study/Study of Latinos. Here we find differential gene expression by blood cell type in relation to SDB traits and link P2XR4 expression to average oxyhemoglobin saturation during sleep and butyrylcarnitine (C4) levels. These findings can be used to develop interventions to alleviate the effect of SDB on the human molecular environment.
Collapse
Affiliation(s)
- Nuzulul Kurniansyah
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Danielle A Wallace
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Ying Zhang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
| | - Bing Yu
- Department of Epidemiology, Human Genetics, and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX, 77030, USA
| | - Brian Cade
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Heming Wang
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- The Broad Institute of MIT and Harvard, Cambridge, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Heather M Ochs-Balcom
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
| | - Alexander P Reiner
- Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, The State University of New York, Buffalo, NY, USA
- Department of Epidemiology, University of Washington, Seattle, WA, USA
| | - Alberto R Ramos
- Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA
| | - Joshua D Smith
- Northwest Genomic Center, University of Washington, Seattle, WA, USA
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina, at Chapel Hill, NC, USA
| | - Martha Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, USA
| | - Phyllis C Zee
- Division of Sleep Medicine, Department of Neurology, Northwestern University, Chicago, IL, USA
| | - Robert Kaplan
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
- Department of Epidemiology & Population Health, Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY, USA
| | - Charles Kooperberg
- Division of Public Health Sciences, Fred Hutchinson Cancer Center, Seattle, WA, USA
| | - Stephen S Rich
- Center for Public Health Genomics, University of Virginia School of Medicine, Charlottesville, VA, USA
| | - Jerome I Rotter
- The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA, USA
| | - Sina A Gharib
- Computational Medicine Core, Center for Lung Biology, UW Medicine Sleep Center, Department of Medicine, University of Washington, Seattle, WA, USA
| | - Susan Redline
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA
| | - Tamar Sofer
- Division of Sleep and Circadian Disorders, Brigham and Women's Hospital, Boston, MA, USA.
- Division of Sleep Medicine, Harvard Medical School, Boston, MA, USA.
- Departments of Medicine and of Biostatistics, Harvard University, Boston, MA, USA.
| |
Collapse
|
5
|
Madrid-Valero JJ, Barclay NL, Rowe R, Perach R, Buysse DJ, Ordoñana JR, Eley TC, Gregory AM. Association between symptoms of sleep apnea and problem behaviors in young adult twins and siblings. Psychol Med 2021; 51:1175-1182. [PMID: 32026794 DOI: 10.1017/s0033291719004070] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
BACKGROUND Sleep apnea is one of the most common sleep disorders and it is related to multiple negative health consequences. Previous studies have shown that sleep apnea is influenced by genetic factors. However, studies have not investigated the genetic and environmental influences of symptoms of sleep apnea in young adults. Furthermore, the underpinnings of the relationship between apnea symptoms and internalizing/externalizing problems are unknown. The objectives of this study were to estimate the magnitude of: (1) genetic and environmental influences on self-reported apnea symptoms; (2) the relationship between self-reported apnea symptoms and internalizing/externalizing traits; (3) genetic and environmental influences on the associations between self-reported apnea symptoms, internalizing behaviors and externalizing behaviors. METHODS In a twin/sibling study, univariate and multivariate models were fitted to estimate both individual variance and sources of covariance between symptoms of sleep apnea and internalizing/externalizing behaviors. RESULTS Our results show that genetic influences account for 40% of the variance in sleep apnea symptoms. Moreover, there are modest associations between depression, anxiety and externalizing behaviors with apnea symptoms (ranging from r = 0.22-0.29). However, the origins of these associations differ. For example, whereas most of the covariation between symptoms of depression and sleep apnea can be explained by genes (95%), there was a larger role for the environment (53%) in the association between symptoms of anxiety and sleep apnea. CONCLUSIONS Genetic factors explain a significant proportion of variance in symptoms of apnea and most of the covariance with depression.
Collapse
Affiliation(s)
- Juan J Madrid-Valero
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- Murcia Institute of Biomedical Research, IMIB-Arrixaca, Murcia, Spain
| | - Nicola L Barclay
- Nuffield Department of Clinical Neurosciences, Sleep and Circadian Neuroscience Institute, University of Oxford, Oxford, UK
| | - Richard Rowe
- Department of Psychology, University of Sheffield, Sheffield, UK
| | - Rotem Perach
- Department of Psychology, Goldsmiths, University of London, London, UK
| | - Daniel J Buysse
- University of Pittsburgh School of Medicine, Pittsburgh, Pennsylvania, USA
| | - Juan R Ordoñana
- Department of Human Anatomy and Psychobiology, University of Murcia, Murcia, Spain
- Murcia Institute of Biomedical Research, IMIB-Arrixaca, Murcia, Spain
| | - Thalia C Eley
- King's College London, MRC Social, Genetic, and Developmental Psychiatry Centre, Institute of Psychiatry, Psychology, and Neuroscience, London, UK
| | - Alice M Gregory
- Department of Psychology, Goldsmiths, University of London, London, UK
| |
Collapse
|
6
|
Au CT, Chan KCC, Zhang J, Liu KH, Chu WCW, Wing YK, Li AM. Intermediate phenotypes of childhood obstructive sleep apnea. J Sleep Res 2020; 30:e13191. [PMID: 32926500 DOI: 10.1111/jsr.13191] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2020] [Revised: 08/17/2020] [Accepted: 08/19/2020] [Indexed: 12/01/2022]
Abstract
An intermediate phenotype of a disease is a trait in the path of pathogenesis from genetic predisposition to disease manifestation. Identifying intermediate phenotypes with high heritability is helpful in delineating the genetics of a disorder. In this study, we aimed to examine various traits with regards to obesity, cardiovascular risk and upper airway structure to identify potential intermediate phenotypes of childhood obstructive sleep apnea (OSA). Children aged between 6 and 18 years and their parents and siblings were recruited. All subjects underwent anthropometric measurements, cardiovascular risk assessment, sonographic measurement of lateral parapharyngeal wall (LPW) thickness, X-ray cephalometry and overnight polysomnography. A total of 34 phenotypes were examined. One hundred and one families consisting of 127 children (46 overweight) and 198 adults (84 overweight) were recruited. Heritability of obstructive apnea-hypopnea index (OAHI) was significant in overweight (h2 = 0.54) but not normal-weight individuals (h2 = 0.12). LPW thickness (h2 = 0.68) and resting blood pressure (h2 = 0.36 and 0.43 for systolic blood pressure [SBP] and diastolic blood pressure [DBP], respectively) were significantly heritable and associated with OAHI. Moreover, these traits were found to have shared genetic variance with OAHI in the overweight subgroup. Hyoid bone position also had significant heritability (h2 = 0.55) and association with OAHI but genetic correlation with OSA severity was not demonstrated. These findings suggest that LPW thickness and resting blood pressure are possible intermediate phenotypes of OSA independent of body mass index, especially in overweight patients. Identifying genes relevant to these phenotypes may help to elucidate the genetic susceptibility of OSA.
Collapse
Affiliation(s)
- Chun Ting Au
- Department of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Kate Ching-Ching Chan
- Department of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Jihui Zhang
- Sleep Assessment Unit, Department of Psychiatry, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Kin Hung Liu
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Winnie Chiu Wing Chu
- Department of Imaging and Interventional Radiology, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Yun Kwok Wing
- Sleep Assessment Unit, Department of Psychiatry, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| | - Albert Martin Li
- Department of Paediatrics, Prince of Wales Hospital, The Chinese University of Hong Kong, Shatin, Hong Kong
| |
Collapse
|
7
|
Lindberg E, Janson C, Johannessen A, Svanes C, Real FG, Malinovschi A, Franklin KA, Holm M, Schlünssen V, Jogi NO, Gislason T, Benediktsdóttir B. Sleep time and sleep-related symptoms across two generations – results of the community-based RHINE and RHINESSA studies. Sleep Med 2020; 69:8-13. [DOI: 10.1016/j.sleep.2019.12.017] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/02/2018] [Revised: 09/03/2019] [Accepted: 12/23/2019] [Indexed: 12/15/2022]
|
8
|
Poor sleep quality and lipid profile in a rural cohort (The Baependi Heart Study). Sleep Med 2019; 57:30-35. [DOI: 10.1016/j.sleep.2018.12.028] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/19/2018] [Revised: 08/15/2018] [Accepted: 12/20/2018] [Indexed: 12/11/2022]
|
9
|
Tanizawa K, Chin K. Genetic factors in sleep-disordered breathing. Respir Investig 2017; 56:111-119. [PMID: 29548648 DOI: 10.1016/j.resinv.2017.11.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2017] [Revised: 11/22/2017] [Accepted: 11/27/2017] [Indexed: 01/03/2023]
Abstract
Sleep-disordered breathing (SDB) is characterized by repetitive episodes of decreased or arrested respiratory airflow during sleep. SDB is common and affects approximately 20% of the Japanese general population. Most traits of normal sleep and SDB show familial aggregation, suggesting significant effects of genetic factors. Obstructive sleep apnea (OSA) is the most common type of SDB and has a high heritability. Regardless of high heritability, no risk locus for OSA has reached a genome-wide level of significance (P < 5×10-8) in linkage or candidate gene analysis. However, a recent genome-wide association study identified some genetic risks for OSA with P < 5×10-8 for the first time. The identified genes are associated with inflammation, hypoxia signaling, and sleep pathways. The effects of genetic factors on the consequences of OSA has not been determined, although a correlation between OSA and cardiovascular disease may differ across races. Congenital central hypoventilation syndrome (CCHS) is a genetically inherited disorder caused by mutations in the paired-like homeobox 2B (PHOX2B) gene of polyalanine repeat mutations in the 20-alanine repeat or non-polyalanine repeat mutations. PHOX2B genotypes are also associated with clinical phenotypes of CCHS, including severity of hypoventilation. SDB, including obesity hypoventilation syndrome, is often seen in genetic obesity-associated disorders such as Prader-Willi syndrome. Although advances in genetics have resulted in identification of some genetic causes of SDB, further studies are required to elucidate the cellular and molecular mechanisms between genetic risks and clinical manifestations.
Collapse
Affiliation(s)
- Kiminobu Tanizawa
- Department of Respiratory Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan.
| | - Kazuo Chin
- Department of Respiratory Care and Sleep Control Medicine, Graduate School of Medicine, Kyoto University, 54 Shogoin Kawaharacho, Sakyo-ku, Kyoto 606-8507, Japan
| |
Collapse
|
10
|
Egan KJ, von Schantz M, Negrão AB, Santos HC, Horimoto ARVR, Duarte NE, Gonçalves GC, Soler JMP, de Andrade M, Lorenzi-Filho G, Vallada H, Taporoski TP, Pedrazzoli M, Azambuja AP, de Oliveira CM, Alvim RO, Krieger JE, Pereira AC. Cohort profile: the Baependi Heart Study-a family-based, highly admixed cohort study in a rural Brazilian town. BMJ Open 2016; 6:e011598. [PMID: 27797990 PMCID: PMC5093390 DOI: 10.1136/bmjopen-2016-011598] [Citation(s) in RCA: 25] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/22/2016] [Revised: 06/08/2016] [Accepted: 08/25/2016] [Indexed: 01/01/2023] Open
Abstract
PURPOSE Cardiovascular disease (CVD) is a major challenge to global health. The same epidemiological transition scenario is replayed as countries develop, but with variations based on environment, culture and ethnic mixture. The Baependi Heart Study was set up in 2005 to develop a longitudinal family-based cohort study that reflects on some of the genetic and lifestyle-related peculiarities of the Brazilian populations, in order to evaluate genetic and environmental influences on CVD risk factor traits. PARTICIPANTS Probands were recruited in Baependi, a small rural town in the state of Minas Gerais, Brazil, following by first-degree and then increasingly more distant relatives. The first follow-up wave took place in 2010, and the second in 2016. At baseline, the study evaluated 1691 individuals across 95 families. Cross-sectional data have been collected for 2239 participants. FINDINGS TO DATE Environmental and lifestyle factors and measures relevant to cardiovascular health have been reported. Having expanded beyond cardiovascular health outcomes, the phenotype datasets now include genetics, biochemistry, anthropometry, mental health, sleep and circadian rhythms. Many of these have yielded heritability estimates, and a shared genetic background of anxiety and depression has recently been published. In spite of universal access to electricity, the population has been found to be strongly shifted towards morningness compared with metropolitan areas. FUTURE PLANS A new follow-up, marking 10 years of the study, is ongoing in 2016, in which data are collected as in 2010 (with the exception of the neuropsychiatric protocol). In addition to this, a novel questionnaire package collecting information about intelligence, personality and spirituality is being planned. The data set on circadian rhythms and sleep will be amended through additional questionnaires, actimetry, home sleep EEG recording and dim light melatonin onset (DLMO) analysis. Finally, the anthropometric measures will be expanded by adding three-dimensional facial photography, voice recording and anatomical brain MRI.
Collapse
Affiliation(s)
- Kieren J Egan
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
| | - Malcolm von Schantz
- Faculty of Health and Medical Sciences, University of Surrey, Guildford, UK
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
- Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - André B Negrão
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Hadassa C Santos
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Andréa R V R Horimoto
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Nubia E Duarte
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Guilherme C Gonçalves
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Júlia M P Soler
- Department of Statistics, University of São Paulo, São Paulo, Brazil
| | - Mariza de Andrade
- Department of Health Sciences Research, Mayo Clinic, Rochester, Minnesota, USA
| | - Geraldo Lorenzi-Filho
- Sleep Laboratory, Pulmonary Division, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Homero Vallada
- Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Tâmara P Taporoski
- Institute of Psychiatry, University of São Paulo Medical School, São Paulo, Brazil
| | - Mario Pedrazzoli
- School of Arts, Science, and Humanities, University of São Paulo, São Paulo, Brazil
| | - Ana P Azambuja
- Natura Innovation and Product Technology Ltd., Cajamar, SP, Brazil
| | - Camila M de Oliveira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
- Department of Physiology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - Rafael O Alvim
- Department of Physiology, Federal University of Juiz de Fora, Juiz de Fora, Brazil
| | - José E Krieger
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| | - Alexandre C Pereira
- Laboratory of Genetics and Molecular Cardiology, Heart Institute (Incor), University of São Paulo Medical School, São Paulo, Brazil
| |
Collapse
|