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Baker S, Biroli P, van Kippersluis H, von Hinke S. Advantageous early-life environments cushion the genetic risk for ischemic heart disease. Proc Natl Acad Sci U S A 2024; 121:e2314056121. [PMID: 38917008 PMCID: PMC11228495 DOI: 10.1073/pnas.2314056121] [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: 08/15/2023] [Accepted: 04/18/2024] [Indexed: 06/27/2024] Open
Abstract
In one of the first papers on the impact of early-life conditions on individuals' health in older age, Barker and Osmond [Lancet, 327, 1077-1081 (1986)] show a strong positive relationship between infant mortality rates in the 1920s and ischemic heart disease in the 1970s. We merge historical data on infant mortality rates to 370,000 individual records in the UK Biobank using information on local area and year of birth. We replicate the association between the early-life infant mortality rate and later-life ischemic heart disease in our sample. We then go "beyond Barker," by showing considerable genetic heterogeneity in this association that is robust to within-area as well as within-family analyses. We find no association between the polygenic index and heart disease in areas with the lowest infant mortality rates, but a strong positive relationship in areas characterized by high infant mortality. These findings suggest that advantageous environments can cushion one's genetic disease risk.
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Affiliation(s)
- Samuel Baker
- School of Economics, University of Bristol, Bristol BS8 1TU, United Kingdom
| | - Pietro Biroli
- Department of Economic Sciences, University of Bologna, Bologna, Italy
| | - Hans van Kippersluis
- Erasmus School of Economics, Erasmus University Rotterdam, 3062 PA Rotterdam, The Netherlands
| | - Stephanie von Hinke
- School of Economics, University of Bristol, Bristol BS8 1TU, United Kingdom
- Institute for Fiscal Studies, London WC1E 7AE, United Kingdom
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2
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Fernández-Rhodes L, McArdle CE, Rao H, Wang Y, Martinez-Miller EE, Ward JB, Cai J, Sofer T, Isasi CR, North KE. A Gene-Acculturation Study of Obesity Among US Hispanic/Latinos: The Hispanic Community Health Study/Study of Latinos. Psychosom Med 2023; 85:358-365. [PMID: 36917487 PMCID: PMC10159946 DOI: 10.1097/psy.0000000000001193] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/16/2023]
Abstract
OBJECTIVE In the United States, Hispanic/Latino adults face a high burden of obesity; yet, not all individuals are equally affected, partly due in part to this ethnic group's marked sociocultural diversity. We sought to analyze the modification of body mass index (BMI) genetic effects in Hispanic/Latino adults by their level of acculturation, a complex biosocial phenomenon that remains understudied. METHODS Among 11,747 Hispanic/Latinos adults in the Hispanic Community Health Study/Study of Latinos aged 18 to 76 years from four urban communities (2008-2011), we a) tested our hypothesis that the effect of a genetic risk score (GRS) for increased BMI may be exacerbated by higher levels of acculturation and b) examined if GRS acculturation interactions varied by gender or Hispanic/Latino background group. All genetic modeling controlled for relatedness, age, gender, principal components of ancestry, center, and complex study design within a generalized estimated equation framework. RESULTS We observed a GRS increase of 0.34 kg/m 2 per risk allele in weighted mean BMI. The estimated main effect of GRS on BMI varied both across acculturation level and across gender. The difference between high and low acculturation ranged from 0.03 to 0.23 kg/m 2 per risk allele, but varied across acculturation measure and gender. CONCLUSIONS These results suggest the presence of effect modification by acculturation, with stronger effects on BMI among highly acculturated individuals and female immigrants. Future studies of obesity in the Hispanic/Latino community should account for sociocultural environments and consider their intersection with gender to better target obesity interventions.
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Affiliation(s)
- Lindsay Fernández-Rhodes
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Cristin E. McArdle
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
| | - Hridya Rao
- Department of Biobehavioral Health, Pennsylvania State University, University Park, PA
| | - Yujie Wang
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Erline E. Martinez-Miller
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Clinical Sciences, University of Texas Southwestern Medical Center, Dallas, TX
| | - Julia B. Ward
- Carolina Population Center, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Social & Scientific Systems, a DLH Holdings Company, Durham, NC
| | - Jianwen Cai
- Department of Biostatistics, University of North Carolina at Chapel Hill, Chapel Hill, NC
| | - Tamar Sofer
- Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA
| | - Carmen R. Isasi
- Departments of Epidemiology & Population Health and Pediatrics, Albert Einstein College of Medicine, Bronx, NY
| | - Kari E North
- Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC
- Carolina Center for Genome Sciences, University of North Carolina at Chapel Hill, Chapel Hill, NC
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3
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Olmastroni E, Gazzotti M, Arca M, Averna M, Pirillo A, Catapano AL, Casula M. Twelve Variants Polygenic Score for Low-Density Lipoprotein Cholesterol Distribution in a Large Cohort of Patients With Clinically Diagnosed Familial Hypercholesterolemia With or Without Causative Mutations. J Am Heart Assoc 2022; 11:e023668. [PMID: 35322671 PMCID: PMC9075429 DOI: 10.1161/jaha.121.023668] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/08/2023]
Abstract
Background A significant proportion of individuals clinically diagnosed with familial hypercholesterolemia (FH), but without any disease‐causing mutation, are likely to have polygenic hypercholesterolemia. We evaluated the distribution of a polygenic risk score, consisting of 12 low‐density lipoprotein cholesterol (LDL‐C)‐raising variants (polygenic LDL‐C risk score), in subjects with a clinical diagnosis of FH. Methods and Results Within the Lipid Transport Disorders Italian Genetic Network (LIPIGEN) study, 875 patients who were FH‐mutation positive (women, 54.75%; mean age, 42.47±15.00 years) and 644 patients who were FH‐mutation negative (women, 54.21%; mean age, 49.73±13.54 years) were evaluated. Patients who were FH‐mutation negative had lower mean levels of pretreatment LDL‐C than patients who were FH‐mutation positive (217.14±55.49 versus 270.52±68.59 mg/dL, P<0.0001). The mean value (±SD) of the polygenic LDL‐C risk score was 1.00 (±0.18) in patients who were FH‐mutation negative and 0.94 (±0.20) in patients who were FH‐mutation positive (P<0.0001). In the receiver operating characteristic analysis, the area under the curve for recognizing subjects characterized by polygenic hypercholesterolemia was 0.59 (95% CI, 0.56–0.62), with sensitivity and specificity being 78% and 36%, respectively, at 0.905 as a cutoff value. Higher mean polygenic LDL‐C risk score levels were observed among patients who were FH‐mutation negative having pretreatment LDL‐C levels in the range of 150 to 350 mg/dL (150–249 mg/dL: 1.01 versus 0.91, P<0.0001; 250–349 mg/dL: 1.02 versus 0.95, P=0.0001). A positive correlation between polygenic LDL‐C risk score and pretreatment LDL‐C levels was observed among patients with FH independently of the presence of causative mutations. Conclusions This analysis confirms the role of polymorphisms in modulating LDL‐C levels, even in patients with genetically confirmed FH. More data are needed to support the use of the polygenic score in routine clinical practice.
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Affiliation(s)
- Elena Olmastroni
- Epidemiology and Preventive Pharmacology Service (SEFAP) Department of Pharmacological and Biomolecular Sciences University of Milan Italy
| | - Marta Gazzotti
- Epidemiology and Preventive Pharmacology Service (SEFAP) Department of Pharmacological and Biomolecular Sciences University of Milan Italy
| | - Marcello Arca
- Department of Translational and Precision Medicine Sapienza University of Rome Rome Italy
| | - Maurizio Averna
- Department of Health Promotion Sciences Maternal and Infantile Care Internal Medicine and Medical Specialties (PROMISE) School of Medicine University of Palermo Palermo Italy
| | - Angela Pirillo
- IRCCS MultiMedica Sesto S. Giovanni (MI), Milan Italy.,Centre for the Study of Atherosclerosis E. Bassini Hospital, Cinisello Balsamo Milan Italy
| | - Alberico Luigi Catapano
- Epidemiology and Preventive Pharmacology Service (SEFAP) Department of Pharmacological and Biomolecular Sciences University of Milan Italy.,IRCCS MultiMedica Sesto S. Giovanni (MI), Milan Italy
| | - Manuela Casula
- Epidemiology and Preventive Pharmacology Service (SEFAP) Department of Pharmacological and Biomolecular Sciences University of Milan Italy.,IRCCS MultiMedica Sesto S. Giovanni (MI), Milan Italy
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Powell-Wiley TM, Baumer Y, Baah FO, Baez AS, Farmer N, Mahlobo CT, Pita MA, Potharaju KA, Tamura K, Wallen GR. Social Determinants of Cardiovascular Disease. Circ Res 2022; 130:782-799. [PMID: 35239404 PMCID: PMC8893132 DOI: 10.1161/circresaha.121.319811] [Citation(s) in RCA: 239] [Impact Index Per Article: 119.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Social determinants of health (SDoH), which encompass the economic, social, environmental, and psychosocial factors that influence health, play a significant role in the development of cardiovascular disease (CVD) risk factors as well as CVD morbidity and mortality. The COVID-19 pandemic and the current social justice movement sparked by the death of George Floyd have laid bare long-existing health inequities in our society driven by SDoH. Despite a recent focus on these structural drivers of health disparities, the impact of SDoH on cardiovascular health and CVD outcomes remains understudied and incompletely understood. To further investigate the mechanisms connecting SDoH and CVD, and ultimately design targeted and effective interventions, it is important to foster interdisciplinary efforts that incorporate translational, epidemiological, and clinical research in examining SDoH-CVD relationships. This review aims to facilitate research coordination and intervention development by providing an evidence-based framework for SDoH rooted in the lived experiences of marginalized populations. Our framework highlights critical structural/socioeconomic, environmental, and psychosocial factors most strongly associated with CVD and explores several of the underlying biologic mechanisms connecting SDoH to CVD pathogenesis, including excess stress hormones, inflammation, immune cell function, and cellular aging. We present landmark studies and recent findings about SDoH in our framework, with careful consideration of the constructs and measures utilized. Finally, we provide a roadmap for future SDoH research focused on individual, clinical, and policy approaches directed towards developing multilevel community-engaged interventions to promote cardiovascular health.
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Affiliation(s)
- Tiffany M Powell-Wiley
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD.,Intramural Research Program, National Institute on Minority Health and Health Disparities (T.M.P.-W.), National Institutes of Health, Bethesda, MD
| | - Yvonne Baumer
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Foster Osei Baah
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Andrew S Baez
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Nicole Farmer
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD (N.F., G.R.W.)
| | - Christa T Mahlobo
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD.,The Pennsylvania State University (C.T.M.)
| | - Mario A Pita
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Kameswari A Potharaju
- Social Determinants of Obesity and Cardiovascular Risk Laboratory, National Heart, Lung, and Blood Institute (T.M.P.-W., Y.B., F.O.B., A.S.B., C.T.M., M.A.P., K.A.P.), National Institutes of Health, Bethesda, MD
| | - Kosuke Tamura
- Neighborhood Social and Geospatial Determinants of Health Disparities Laboratory, Population and Community Sciences Branch, Intramural Research Program, National Institute on Minority Health and Health Disparities (K.T.), National Institutes of Health, Bethesda, MD
| | - Gwenyth R Wallen
- Translational Biobehavioral and Health Disparities Branch, National Institutes of Health, Clinical Center, Bethesda, MD (N.F., G.R.W.)
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Carter AR, Harrison S, Gill D, Davey Smith G, Taylor AE, Howe LD, Davies NM. Educational attainment as a modifier for the effect of polygenic scores for cardiovascular risk factors: cross-sectional and prospective analysis of UK Biobank. Int J Epidemiol 2022; 51:885-897. [PMID: 35134953 PMCID: PMC9189971 DOI: 10.1093/ije/dyac002] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/25/2021] [Accepted: 01/06/2022] [Indexed: 01/22/2023] Open
Abstract
Background Understanding the interplay between educational attainment and genetic predictors of cardiovascular risk may improve our understanding of the aetiology of educational inequalities in cardiovascular disease. Methods In up to 320 120 UK Biobank participants of White British ancestry (mean age = 57 years, female 54%), we created polygenic scores for nine cardiovascular risk factors or diseases: alcohol consumption, body mass index, low-density lipoprotein cholesterol, lifetime smoking behaviour, systolic blood pressure, atrial fibrillation, coronary heart disease, type 2 diabetes and stroke. We estimated whether educational attainment modified genetic susceptibility to these risk factors and diseases. Results On the additive scale, higher educational attainment reduced genetic susceptibility to higher body mass index, smoking, atrial fibrillation and type 2 diabetes, but increased genetic susceptibility to higher LDL-C and higher systolic blood pressure. On the multiplicative scale, there was evidence that higher educational attainment increased genetic susceptibility to atrial fibrillation and coronary heart disease, but little evidence of effect modification was found for all other traits considered. Conclusions Educational attainment modifies the genetic susceptibility to some cardiovascular risk factors and diseases. The direction of this effect was mixed across traits considered and differences in associations between the effect of the polygenic score across strata of educational attainment was uniformly small. Therefore, any effect modification by education of genetic susceptibility to cardiovascular risk factors or diseases is unlikely to substantially explain the development of inequalities in cardiovascular risk.
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Affiliation(s)
- Alice R Carter
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Sean Harrison
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Dipender Gill
- Clinical Pharmacology and Therapeutics Section, Institute of Medical and Biomedical Education and Institute for Infection and Immunity, St George’s, University of London, London, UK
- Clinical Pharmacology Group, Pharmacy and Medicines Directorate, St George’s University Hospitals NHS Foundation Trust, London, UK
- Novo Nordisk Research Centre Oxford, Old Road Campus, Oxford, UK
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, UK
| | - George Davey Smith
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Amy E Taylor
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- NIHR Bristol Biomedical Research Centre, University of Bristol, Bristol, UK
| | - Laura D Howe
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
| | - Neil M Davies
- MRC Integrative Epidemiology Unit, University of Bristol Bristol, UK
- Population Health Sciences, Bristol Medical School, University of Bristol, Bristol, UK
- K.G. Jebsen Center for Genetic Epidemiology, Department of Public Health and Nursing, NTNU, Norwegian University of Science and Technology, Trondheim, Norway
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6
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Khouly I, Pardiñas López S, Díaz Prado SM, Ferrantino L, Kalm J, Larsson L, Asa’ad F. Global DNA Methylation in Dental Implant Failure Due to Peri-Implantitis: An Exploratory Clinical Pilot Study. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH 2022; 19:ijerph19021020. [PMID: 35055840 PMCID: PMC8775395 DOI: 10.3390/ijerph19021020] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Subscribe] [Scholar Register] [Received: 12/08/2021] [Revised: 01/14/2022] [Accepted: 01/15/2022] [Indexed: 12/14/2022]
Abstract
Background: Peri-implantitis (PIT) is highly prevalent in patients with dental implants and is a challenging condition to treat due to the limited outcomes reported for non-surgical and surgical therapies. Therefore, epigenetic therapeutics might be of key importance to treat PIT. However, developing epigenetic therapeutics is based on understanding the relationship between epigenetics and disease. To date, there is still scarce knowledge about the relationship between epigenetic modifications and PIT, which warrants further investigations. Aim: The purpose of this study was to evaluate the level of global DNA methylation associated with implant failure (IF) due to PIT compared to periodontally healthy (PH) patients. Material and Methods: A total of 20 participants were initially enrolled in this pilot, exploratory, single-blinded, cross-sectional clinical human study in two groups: 10 in the PH group and 10 in the IF group. In the participants who have completed the study, gingival tissue and bone samples were harvested from each participant and were used to perform global DNA methylation analysis. The percentage of global DNA methylation (5-mC%) was compared (1) between groups (PH and IF); (2) between the subgroups of gingival tissue and bone separately; (3) in the whole sample, comparing gingival tissue and bone; (4) within groups, comparing gingival tissue and bone. Demographic, periodontal, and peri-implant measurements as well as periodontal staging, were also recorded. All statistical comparisons were made at the 0.05 significance level. Results: Out of the initially enrolled 20 patients, only 19 completed the study and, thus, were included in the final analysis; 10 patients in the PH group and 9 patients in the IF group, contributing to a total of 38 samples. One patient from the IF group was excluded from the study due to systemic disease. The mean implant survival time was 10.8 years (2.17–15.25 years). Intergroup comparison, stratified by group, indicated a similar 5-mC% between the PH and IF groups in both gingival tissue and bone (p = 0.599), only in bone (p = 0.414), and only in gingival tissue (p = 0.744). Intragroup comparison, stratified by the type of sample, indicated a significantly higher 5-mC% in gingival tissue samples compared to bone in both the PH and IF groups (p = 0.001), in the PH group (p = 0.019), and in the IF group (p = 0.009). Conclusions: Within the limitations of this study, higher global DNA methylation levels were found in gingival tissue samples compared to bone, regardless of the study groups. However, similar global DNA methylation levels were observed overall between the IF and PH groups. Yet, differences in the global DNA methylation levels between gingival tissues and bone, regardless of the study group, could reflect a different epigenetic response between various tissues within the same microenvironment. Further studies are necessary to elucidate the present findings and to evaluate the role of epigenetic modifications in IF due to PIT.
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Affiliation(s)
- Ismael Khouly
- Department of Oral and Maxillofacial Surgery, College of Dentistry, New York University, New York, NY 10010, USA
- Correspondence:
| | - Simon Pardiñas López
- Periodontology and Oral Surgery, Clínica Médico Dental Pardiñas, Real 66, 3°, 15003 A Coruña, Spain;
- Institute of Biomedical Research of A Coruña (INIBIC), Galician Health Service (SERGAS), University Hospital Complex A Coruña (CHUAC), 15006 A Coruña, Spain;
- Centro de Investigaciones Científicas Avanzadas (CICA), University of A Coruña, Rúa As Casballeiras, 15071 A Coruña, Spain
- Cell Therapy and Regenerative Medicine Group, Department of Physiotherapy, Medicine and Biomedical Sciences, Faculty of Health Sciences, University of A Coruña (UDC), 15006 A Coruña, Spain
| | - Silvia María Díaz Prado
- Institute of Biomedical Research of A Coruña (INIBIC), Galician Health Service (SERGAS), University Hospital Complex A Coruña (CHUAC), 15006 A Coruña, Spain;
- Centro de Investigaciones Científicas Avanzadas (CICA), University of A Coruña, Rúa As Casballeiras, 15071 A Coruña, Spain
- Cell Therapy and Regenerative Medicine Group, Department of Physiotherapy, Medicine and Biomedical Sciences, Faculty of Health Sciences, University of A Coruña (UDC), 15006 A Coruña, Spain
- Centro de Investigación Biomédica en Red (CIBER) de Bioingeniería, Biomateriales y Nanomedicina (CIBER-BBN), 28029 Madrid, Spain
| | - Luca Ferrantino
- Department of Biomedical, Surgical, and Dental Sciences, University of Milan, 20122 Milan, Italy;
- Department of Aesthetic Dentistry, Istituto Stomatologico Italiano, 20122 Milan, Italy
| | - Josephine Kalm
- Department of Periodontology, Institute of Odontology, The Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden; (J.K.); (L.L.)
| | - Lena Larsson
- Department of Periodontology, Institute of Odontology, The Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden; (J.K.); (L.L.)
| | - Farah Asa’ad
- Department of Biomaterials, Institute of Clinical Sciences, The Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden;
- Department of Oral Biochemistry, Institute of Odontology, The Sahlgrenska Academy at University of Gothenburg, SE-405 30 Göteborg, Sweden
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7
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McArdle CE, Bokhari H, Rodell CC, Buchanan V, Preudhomme LK, Isasi CR, Graff M, North K, Gallo LC, Pirzada A, Daviglus ML, Wojcik G, Cai J, Perreira K, Fernandez-Rhodes L. Findings from the Hispanic Community Health Study/Study of Latinos on the Importance of Sociocultural Environmental Interactors: Polygenic Risk Score-by-Immigration and Dietary Interactions. Front Genet 2021; 12:720750. [PMID: 34938310 PMCID: PMC8685455 DOI: 10.3389/fgene.2021.720750] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2021] [Accepted: 09/08/2021] [Indexed: 01/05/2023] Open
Abstract
Introduction: Hispanic/Latinos experience a disproportionate burden of obesity. Acculturation to US obesogenic diet and practices may lead to an exacerbation of innate genetic susceptibility. We examined the role of gene-environment interactions to better characterize the sociocultural environmental determinants and their genome-scale interactions, which may contribute to missing heritability of obesity. We utilized polygenic risk scores (PRSs) for body mass index (BMI) to perform analyses of PRS-by-acculturation and other environmental interactors among self-identified Hispanic/Latino adults from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL). Methods: PRSs were derived using genome-wide association study (GWAS) weights from a publicly available, large meta-analysis of European ancestry samples. Generalized linear models were run using a set of a priori acculturation-related and environmental factors measured at visit 1 (2008-2011) and visit 2 (2014-2016) in an analytic subsample of 8,109 unrelated individuals with genotypic, phenotypic, and complete case data at both visits. We evaluated continuous measures of BMI and waist-to-hip ratio. All models were weighted for complex sampling design, combined, and sex-stratified. Results: Overall, we observed a consistent increase of BMI with greater PRS across both visits. We found the best-fitting model adjusted for top five principal components of ancestry, sex, age, study site, Hispanic/Latino background genetic ancestry group, sociocultural factors and PRS interactions with age at immigration, years since first arrival to the United States (p < 0.0104), and healthy diet (p < 0.0036) and explained 16% of the variation in BMI. For every 1-SD increase in PRS, there was a corresponding 1.10 kg/m2 increase in BMI (p < 0.001). When these results were stratified by sex, we observed that this 1-SD effect of PRS on BMI was greater for women than men (1.45 vs. 0.79 kg/m2, p < 0.001). Discussion: We observe that age at immigration and the adoption of certain dietary patterns may play a significant role in modifying the effect of genetic risk on obesity. Careful consideration of sociocultural and immigration-related factors should be evaluated. The role of nongenetic factors, including the social environment, should not be overlooked when describing the performance of PRS or for promoting population health in understudied populations in genomics.
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Affiliation(s)
- Cristin E. McArdle
- Department of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, United States,*Correspondence: Cristin E. McArdle,
| | - Hassan Bokhari
- Department of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, United States
| | - Clinton C. Rodell
- Carey Business School, Johns Hopkins University, Baltimore, MD, United States
| | - Victoria Buchanan
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Liana K. Preudhomme
- Department of Psychology, University of Miami, Coral Gables, FL, United States
| | - Carmen R. Isasi
- Department of Epidemiology and Population Health, Albert Einstein College of Medicine, Bronx, NY, United States
| | - Mariaelisa Graff
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Kari North
- Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States,Carolina Center for Genome Sciences, School of Medicine, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Linda C. Gallo
- Department of Psychology, San Diego State University, San Diego, CA, United States
| | - Amber Pirzada
- Institute for Minority Health Research, Carle Illinois College of Medicine, University of Illinois at Urbana–Champaign, Champaign, IL, United States
| | - Martha L. Daviglus
- Institute for Minority Health Research, University of Illinois at Chicago, Chicago, IL, United States
| | - Genevieve Wojcik
- Department of Epidemiology, Johns Hopkins University, Baltimore, MD, United States
| | - Jianwen Cai
- Department of Biostatistics, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
| | - Krista Perreira
- Department of Social Medicine, University of North Carolina School of Medicine, Chapel Hill, NC, United States
| | - Lindsay Fernandez-Rhodes
- Department of Biobehavioral Health, College of Health and Human Development, The Pennsylvania State University, University Park, PA, United States,Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States
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8
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McGraw KE, Riggs DW, Rai S, Navas-Acien A, Xie Z, Lorkiewicz P, Lynch J, Zafar N, Krishnasamy S, Taylor KC, Conklin DJ, DeFilippis AP, Srivastava S, Bhatnagar A. Exposure to volatile organic compounds - acrolein, 1,3-butadiene, and crotonaldehyde - is associated with vascular dysfunction. ENVIRONMENTAL RESEARCH 2021; 196:110903. [PMID: 33636185 PMCID: PMC8119348 DOI: 10.1016/j.envres.2021.110903] [Citation(s) in RCA: 41] [Impact Index Per Article: 13.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2020] [Revised: 02/03/2021] [Accepted: 02/16/2021] [Indexed: 05/03/2023]
Abstract
BACKGROUND Cardiovascular disease (CVD) is the leading cause of mortality worldwide. Exposure to air pollution, specifically particulate matter of diameter ≤2.5 μm (PM2.5), is a well-established risk factor for CVD. However, the contribution of gaseous pollutant exposure to CVD risk is less clear. OBJECTIVE To examine the vascular effects of exposure to individual volatile organic compounds (VOCs) and mixtures of VOCs. METHODS We measured urinary metabolites of acrolein (CEMA and 3HPMA), 1,3-butadiene (DHBMA and MHBMA3), and crotonaldehyde (HPMMA) in 346 nonsmokers with varying levels of CVD risk. On the day of enrollment, we measured blood pressure (BP), reactive hyperemia index (RHI - a measure of endothelial function), and urinary levels of catecholamines and their metabolites. We used generalized linear models for evaluating the association between individual VOC metabolites and BP, RHI, and catecholamines, and we used Bayesian Kernel Machine Regression (BKMR) to assess exposure to VOC metabolite mixtures and BP. RESULTS We found that the levels of 3HPMA were positively associated with systolic BP (0.98 mmHg per interquartile range (IQR) of 3HPMA; CI: 0.06, 1.91; P = 0.04). Stratified analysis revealed an increased association with systolic BP in Black participants despite lower levels of urinary 3HPMA. This association was independent of PM2.5 exposure and BP medications. BKMR analysis confirmed that 3HPMA was the major metabolite associated with higher BP in the presence of other metabolites. We also found that 3HPMA and DHBMA were associated with decreased endothelial function. For each IQR of 3HPMA or DHBMA, there was a -4.4% (CI: -7.2, -0.0; P = 0.03) and a -3.9% (CI: -9.4, -0.0; P = 0.04) difference in RHI, respectively. Although in the entire cohort the levels of several urinary VOC metabolites were weakly associated with urinary catecholamines and their metabolites, in Black participants, DHBMA levels showed strong associations with urinary norepinephrine and normetanephrine levels. DISCUSSION Exposure to acrolein and 1,3-butadiene is associated with endothelial dysfunction and may contribute to elevated risk of hypertension in participants with increased sympathetic tone, particularly in Black individuals.
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Affiliation(s)
- Katlyn E McGraw
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA; University of Louisville School of Public Health and Information Sciences, USA; Department of Environmental and Occupational Health Sciences, USA
| | - Daniel W Riggs
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA; University of Louisville School of Public Health and Information Sciences, USA; Department of Epidemiology and Population Health, USA
| | - Shesh Rai
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA; University of Louisville School of Public Health and Information Sciences, USA; Department of Bioinformatics and Biostatistics, 485 E Gray Street, Louisville, KY, 40202, USA
| | - Ana Navas-Acien
- Columbia University Mailman School of Public Health, USA; Department of Environmental Health Science, 722 W 168th St, New York, NY, 10032, USA
| | - Zhengzhi Xie
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA
| | - Pawel Lorkiewicz
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA
| | - Jordan Lynch
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA
| | - Nagma Zafar
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA
| | - Sathya Krishnasamy
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA
| | - Kira C Taylor
- University of Louisville School of Public Health and Information Sciences, USA; Department of Epidemiology and Population Health, USA
| | - Daniel J Conklin
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA
| | - Andrew P DeFilippis
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA
| | - Sanjay Srivastava
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA; University of Louisville School of Public Health and Information Sciences, USA
| | - Aruni Bhatnagar
- Christina Lee Brown Envirome Institute, 302 E Muhammad Ali Blvd, Louisville, KY, 40202, USA; Superfund Research Center, 302 E Muhammad Ali Blvd, Louisville, KY 40202, USA.
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9
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Allan S, Olaiya R, Burhan R. Reviewing the use and quality of machine learning in developing clinical prediction models for cardiovascular disease. Postgrad Med J 2021; 98:551-558. [PMID: 33692158 DOI: 10.1136/postgradmedj-2020-139352] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2020] [Revised: 02/10/2021] [Accepted: 02/12/2021] [Indexed: 12/23/2022]
Abstract
Cardiovascular disease (CVD) is one of the leading causes of death across the world. CVD can lead to angina, heart attacks, heart failure, strokes, and eventually, death; among many other serious conditions. The early intervention with those at a higher risk of developing CVD, typically with statin treatment, leads to better health outcomes. For this reason, clinical prediction models (CPMs) have been developed to identify those at a high risk of developing CVD so that treatment can begin at an earlier stage. Currently, CPMs are built around statistical analysis of factors linked to developing CVD, such as body mass index and family history. The emerging field of machine learning (ML) in healthcare, using computer algorithms that learn from a dataset without explicit programming, has the potential to outperform the CPMs available today. ML has already shown exciting progress in the detection of skin malignancies, bone fractures and many other medical conditions. In this review, we will analyse and explain the CPMs currently in use with comparisons to their developing ML counterparts. We have found that although the newest non-ML CPMs are effective, ML-based approaches consistently outperform them. However, improvements to the literature need to be made before ML should be implemented over current CPMs.
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Affiliation(s)
- Simon Allan
- Manchester Medical School, The University of Manchester, Manchester, UK
| | - Raphael Olaiya
- UCL Centre for Artificial Intelligence, University College London, London, UK
| | - Rasan Burhan
- St George's Healthcare NHS Trust, St George's Healthcare NHS Trust, London, UK
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10
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Zhou F, Ren J, Lu X, Ma S, Wu C. Gene-Environment Interaction: A Variable Selection Perspective. Methods Mol Biol 2021; 2212:191-223. [PMID: 33733358 DOI: 10.1007/978-1-0716-0947-7_13] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
Gene-environment interactions have important implications for elucidating the genetic basis of complex diseases beyond the joint function of multiple genetic factors and their interactions (or epistasis). In the past, G × E interactions have been mainly conducted within the framework of genetic association studies. The high dimensionality of G × E interactions, due to the complicated form of environmental effects and the presence of a large number of genetic factors including gene expressions and SNPs, has motivated the recent development of penalized variable selection methods for dissecting G × E interactions, which has been ignored in the majority of published reviews on genetic interaction studies. In this article, we first survey existing studies on both gene-environment and gene-gene interactions. Then, after a brief introduction to the variable selection methods, we review penalization and relevant variable selection methods in marginal and joint paradigms, respectively, under a variety of conceptual models. Discussions on strengths and limitations, as well as computational aspects of the variable selection methods tailored for G × E studies, have also been provided.
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Affiliation(s)
- Fei Zhou
- Department of Statistics, Kansas State University, Manhattan, KS, USA
| | - Jie Ren
- Department of Biostatistics, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Xi Lu
- Department of Statistics, Kansas State University, Manhattan, KS, USA
| | - Shuangge Ma
- Department of Biostatistics, School of Public Health, Yale University, New Haven, CT, USA
| | - Cen Wu
- Department of Statistics, Kansas State University, Manhattan, KS, USA.
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11
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Lenart P, Scheringer M, Bienertova‐Vasku J. The Pathosome: A Dynamic Three‐Dimensional View of Disease–Environment Interaction. Bioessays 2019; 41:e1900014. [DOI: 10.1002/bies.201900014] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2019] [Revised: 04/02/2019] [Indexed: 12/20/2022]
Affiliation(s)
- Peter Lenart
- Department of Pathological PhysiologyFaculty of MedicineMasaryk UniversityKamenice 5, Building A18 625 00 Brno Czech Republic
- Research Centre for Toxic Compounds in the Environment, Faculty of ScienceMasaryk UniversityKamenice 5, Building A29 625 00 Brno Czech Republic
| | - Martin Scheringer
- Research Centre for Toxic Compounds in the Environment, Faculty of ScienceMasaryk UniversityKamenice 5, Building A29 625 00 Brno Czech Republic
- Institute of Biogeochemistry and Pollutant DynamicsETH ZurichUniversitätstrasse 16 CH‐8092 Zürich Switzerland
| | - Julie Bienertova‐Vasku
- Department of Pathological PhysiologyFaculty of MedicineMasaryk UniversityKamenice 5, Building A18 625 00 Brno Czech Republic
- Research Centre for Toxic Compounds in the Environment, Faculty of ScienceMasaryk UniversityKamenice 5, Building A29 625 00 Brno Czech Republic
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12
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Vural H, Kaya M. Prediction of new potential associations between LncRNAs and environmental factors based on KATZ measure. Comput Biol Med 2018; 102:120-125. [PMID: 30268976 DOI: 10.1016/j.compbiomed.2018.09.019] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/14/2018] [Revised: 09/24/2018] [Accepted: 09/24/2018] [Indexed: 12/19/2022]
Abstract
The associations between genetic and environmental factors (EFs) are significant to understand the development and progression of many complex human diseases. There have been many research studies concerning genetic factors (protein-coding genes, microRNAs) and EFs but limited research addressing the associations between long noncoding RNAs (lncRNAs) and EFs. LncRNAs of more than 200 nucleotides are an important class of non-coding transcripts and are effective in the organization of gene expressions and, therefore, on the formation of diseases. Environmental factors can alter the expression patterns of some lncRNAs, so a thorough understanding of the associations between lncRNAs and environmental factors will contribute to the understanding of the mechanisms of many complex diseases at the molecular level. In this study, we have developed a model based on the KATZ measure to find potential new associations between lncRNAs and EFs by using the DLREFD database, which contains proven associations between lncRNAs and EFs. The KATZ measure and Gaussian interaction profile kernel similarity were used to predict new potential associations between lncRNAs and EFs. The AUC results obtained by global leave-one-out cross-validation and 2-fold and 5-fold cross-validations were 0.855, 0.827, 0.838, respectively. These results show that our model can predict new potential associations between lncRNAs and EFs with high reliability. Also, the results obtained in case studies demonstrate the effectiveness of our model.
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Affiliation(s)
- Hüseyin Vural
- Department of Computer Technologies, Adıyaman University, Adıyaman, Turkey.
| | - Mehmet Kaya
- Department of Computer Engineering, Fırat University, Elazığ, Turkey.
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13
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Ramos-Lopez O, Riezu-Boj JI, Milagro FI, Goni L, Cuervo M, Martinez JA. Differential lipid metabolism outcomes associated with ADRB2 gene polymorphisms in response to two dietary interventions in overweight/obese subjects. Nutr Metab Cardiovasc Dis 2018; 28:165-172. [PMID: 29331538 DOI: 10.1016/j.numecd.2017.11.006] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/25/2017] [Revised: 10/26/2017] [Accepted: 11/27/2017] [Indexed: 01/27/2023]
Abstract
BACKGROUND AND AIMS A precise nutrigenetic management of hypercholesterolemia involves the understanding of the interactions between the individual's genotype and dietary intake. The aim of this study was to analyze the response to two dietary energy-restricted interventions on cholesterol changes in carriers of two ADRB2 polymorphisms. METHODS AND RESULTS A 4-month nutritional intervention was conducted involving two different hypo-energetic diets based on low-fat (LF) and moderately high-protein (MHP) dietary patterns. A total of 107 unrelated overweight/obese individuals were genotyped for two ADRB2 non-synonymous polymorphisms: Arg16Gly (rs1042713) and Gln27Glu (rs1042714). Genotyping was performed by next-generation sequencing and haplotypes were phenotypically screened. Anthropometric measurements and the biochemical profile were assessed by conventional methods. Both diets induced cholesterol decreases at the end of both nutritional interventions. Interestingly, phenotypical differences were observed according to the Arg16Gly polymorphism. Within the MHP group, Gly16Gly homozygotes had lower reductions in total cholesterol (-6.5 mg/dL vs. -24.2 mg/dL, p = 0.009), LDL-c levels (-1.4 mg/dL vs. -16.5 mg/dL, p = 0.005), and non-HDL-c (-4.5 mg/dL vs. -21.5 mg/dL, p = 0.008) than Arg16 allele carriers. Conversely, within the LF group, Gly16Gly homozygotes underwent similar falls in total cholesterol (-18.5 mg/dL vs. -18.7 mg/dL, ns), LDL-c levels (-9.7 mg/dL vs. -13.1 mg/dL, ns), and non-HDL-c (-15.3 mg/dL vs. -15.7 mg/dL, ns) than Arg16 allele carriers. The Gln27Glu polymorphism and the Gly16/Glu27 haplotype showed similar, but not greater effects. CONCLUSIONS An energy-restricted LF diet could be more beneficial than a MHP diet to reduce serum cholesterol, LDL-c, and non-HDL-c among Gly16Gly genotype carriers. CLINICALTRIALS.GOV: Identifier: NCT02737267.
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Affiliation(s)
- O Ramos-Lopez
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain
| | - J I Riezu-Boj
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - F I Milagro
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain; Biomedical Research Centre Network in Physiopathology of Obesity and Nutrition (CIBERobn), Carlos III Institute, Madrid, Spain
| | - L Goni
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain
| | - M Cuervo
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; Biomedical Research Centre Network in Physiopathology of Obesity and Nutrition (CIBERobn), Carlos III Institute, Madrid, Spain
| | - J A Martinez
- Department of Nutrition, Food Science and Physiology, University of Navarra, Pamplona, Spain; Center for Nutrition Research, University of Navarra, Pamplona, Spain; Navarra Institute for Health Research (IdiSNA), Pamplona, Spain; Biomedical Research Centre Network in Physiopathology of Obesity and Nutrition (CIBERobn), Carlos III Institute, Madrid, Spain; Madrid Institute of Advanced Studies (IMDEA Food), Madrid, Spain.
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14
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Affiliation(s)
- Marina Paz De Jesus
- Marina Paz De Jesus and Magen Mitchel are BSN students at the University of Texas Health Science Center in Houston, Tex
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15
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Smith JA, Ware EB, Middha P, Beacher L, Kardia SLR. Current Applications of Genetic Risk Scores to Cardiovascular Outcomes and Subclinical Phenotypes. CURR EPIDEMIOL REP 2015; 2:180-190. [PMID: 26269782 PMCID: PMC4527979 DOI: 10.1007/s40471-015-0046-4] [Citation(s) in RCA: 56] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/27/2022]
Abstract
Genetic risk scores are a useful tool for examining the cumulative predictive ability of genetic variation on cardiovascular disease. Important considerations for creating genetic risk scores include the choice of genetic variants, weighting, and comparability across ethnicities. Genetic risk scores that use information from genome-wide meta-analyses can successfully predict cardiovascular outcomes and subclinical phenotypes, yet there is limited clinical utility of these scores beyond traditional cardiovascular risk factors in many populations. Novel uses of genetic risk scores include evaluating the genetic contribution of specific intermediate traits or risk factors to cardiovascular disease, risk prediction in high-risk populations, gene-by-environment interaction studies, and Mendelian randomization studies. Though questions remain about the ultimate clinical utility of the genetic risk score, further investigation in high-risk populations and new ways to combine genetic risk scores with traditional risk factors may prove to be fruitful.
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Affiliation(s)
- Jennifer A. Smith
- />Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA
| | - Erin B. Ware
- />Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA
- />Research Center for Group Dynamics, Institute for Social Research, University of Michigan, Ann Arbor, MI 48104 USA
| | - Pooja Middha
- />Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA
| | - Lisa Beacher
- />Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA
| | - Sharon L. R. Kardia
- />Department of Epidemiology, School of Public Health, University of Michigan, 1415 Washington Heights, Ann Arbor, MI 48109 USA
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16
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Zhao LP, Fan W, Goodman G, Radich J, Martin P. Deciphering Genome Environment Wide Interactions Using Exposed Subjects Only. Genet Epidemiol 2015; 39:334-46. [PMID: 25694100 DOI: 10.1002/gepi.21890] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/28/2014] [Revised: 12/29/2014] [Accepted: 01/06/2015] [Indexed: 01/17/2023]
Abstract
The recent successes of genome-wide association studies (GWAS) have renewed interest in genome environment wide interaction studies (GEWIS) to discover genetic factors that modulate penetrance of environmental exposures to human diseases. Indeed, gene-environment interactions (G × E), which have not been emphasized in the GWAS era, could be a source contributing to the missing heritability, a major bottleneck limiting continuing GWAS successes. In this manuscript, we describe a design and analytic strategy to focus on G × E using only exposed subjects, dubbed as e-GEWIS. Operationally, an e-GEWIS analysis is equivalent to a GWAS analysis on exposed subjects only, and it has actually been used in some earlier GWAS without being explicitly identified as such. Through both analytics and simulations, e-GEWIS has been shown better efficiency than the usual cross-product-based analysis of G × E interaction with both cases and controls (cc-GEWIS), and they have comparable efficiency to case-only analysis of G × E (c-GEWIS), with potentially smaller sample sizes. The formalization of e-GEWIS here provides a theoretical basis to legitimize this framework for routine investigation of G × E, for more efficient G × E study designs, and for improvement of reproducibility in replicating GEWIS findings. As an illustration, we apply e-GEWIS to a lung cancer GWAS data set to perform a GEWIS, focusing on gene and smoking interaction. The e-GEWIS analysis successfully uncovered positive genetic associations on chromosome 15 among current smokers, suggesting a gene-smoking interaction. Although this signal was detected earlier, the current finding here serves as a positive control in support of this e-GEWIS strategy.
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Affiliation(s)
- Lue Ping Zhao
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.,School of Public Health Sciences, University of Washington, Seattle, WA, United States of America
| | - Wenhong Fan
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Gary Goodman
- Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America.,Swedish Medical Center Cancer Institute, Seattle, WA, United States of America
| | - Jerry Radich
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
| | - Paul Martin
- Division of Clinical Research, Fred Hutchinson Cancer Research Center, Seattle, WA, United States of America
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17
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Flowers E, Won GY, Fukuoka Y. MicroRNAs associated with exercise and diet: a systematic review. Physiol Genomics 2015; 47:1-11. [PMID: 25465031 PMCID: PMC7199230 DOI: 10.1152/physiolgenomics.00095.2014] [Citation(s) in RCA: 54] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2014] [Accepted: 11/26/2014] [Indexed: 11/22/2022] Open
Abstract
MicroRNAs are posttranscriptional regulators of gene expression. MicroRNAs reflect individual biologic adaptation to exposures in the environment. As such, measurement of circulating microRNAs presents an opportunity to evaluate biologic changes associated with behavioral interventions (i.e., exercise, diet) for weight loss. The aim of this study was to perform a systematic review of the literature to summarize what is known about circulating microRNAs associated with exercise, diet, and weight loss. We performed a systematic review of three scientific databases. We included studies reporting on circulating microRNAs associated with exercise, diet, and weight loss in humans. Of 1,219 studies identified in our comprehensive database search, 14 were selected for inclusion. Twelve reported on microRNAs associated with exercise, and two reported on microRNAs associated with diet and weight loss. The majority of studies used a quasiexperimental, cross-sectional design. There were numerous differences in the type and intensity of exercise and dietary interventions, the biologic source of microRNAs, and the methodological approaches used quantitate microRNAs. Data from several studies support an association between circulating microRNAs and exercise. The evidence for an association between circulating microRNAs and diet is weaker because of a small number of studies. Additional research is needed to validate previous observations using methodologically rigorous approaches to microRNA quantitation to determine the specific circulating microRNA signatures associated with behavioral approaches to weight loss. Future directions include longitudinal studies to determine if circulating microRNAs are predictive of response to behavioral interventions.
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Affiliation(s)
- Elena Flowers
- Department of Physiological Nursing, School of Nursing, University of California, San Francisco, California;
| | - Gloria Y Won
- Fishbon Library, University of California, San Francisco, California; and
| | - Yoshimi Fukuoka
- Institute for Health and Aging/Department of Social & Behavioral Sciences, University of California, San Francisco, California
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Kelishadi R, Poursafa P. A review on the genetic, environmental, and lifestyle aspects of the early-life origins of cardiovascular disease. Curr Probl Pediatr Adolesc Health Care 2014; 44:54-72. [PMID: 24607261 DOI: 10.1016/j.cppeds.2013.12.005] [Citation(s) in RCA: 103] [Impact Index Per Article: 10.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/21/2013] [Accepted: 12/04/2013] [Indexed: 12/29/2022]
Abstract
This article is a comprehensive review on developmental origins of health and disease regarding various factors related to the origins of cardiovascular diseases from early life. It presents a summary of the impacts of various factors such as epigenetics; gene-environment interaction; ethnic predisposition to cardiovascular diseases and their underlying risk factors; prenatal factors; fetal programming; maternal weight status and weight gain during pregnancy; type of feeding during infancy; growth pattern during childhood; obesity; stunting; socioeconomic status; dietary and physical activity habits; active, secondhand, and thirdhand smoking, as well as environmental factors including air pollution and global climate change on the development and progress of cardiovascular diseases and their risk factors. The importance of early identification of predisposing factors for cardiovascular diseases for primordial and primary prevention of cardiovascular diseases from early life is highlighted.
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Affiliation(s)
- Roya Kelishadi
- Faculty of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran; Child Growth and Development Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
| | - Parinaz Poursafa
- Environment Research Center, Isfahan University of Medical Sciences, Isfahan, Iran
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Portilla EC, Muñoz W, Sierra CH. Mecanismos celulares y moleculares de la aterotrombosis. REVISTA COLOMBIANA DE CARDIOLOGÍA 2014. [DOI: 10.1016/s0120-5633(14)70009-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022] Open
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20
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Flowers E, Aouizerat BE. MicroRNA associated with dyslipidemia and coronary disease in humans. Physiol Genomics 2013; 45:1199-205. [PMID: 24170031 DOI: 10.1152/physiolgenomics.00106.2013] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023] Open
Abstract
MicroRNAs are structural components of an epigenetic mechanism of posttranscriptional regulation of messenger RNA translation. Recently, there has been significant interest in the application of microRNA as a blood-based biomarker of underlying physiological conditions. Dyslipidemia is a complex, heterogeneous condition conferring substantially increased risk for cardiovascular disease. The purpose of this review is to describe the current body of knowledge on the role of microRNA regulation of lipoprotein metabolism in humans and to discuss relevant methodological and study design considerations. We highlight the potential roles for microRNA in gene-environment interactions.
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Affiliation(s)
- Elena Flowers
- Department of Physiological Nursing, School of Nursing, University of California, San Francisco, California; and
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