Skip to main content
Key Specialties
Cardiology Diabetology Endocrinology Gastroenterology Geriatrics and Gerontology Gynecology and Obstetrics Hematology Infectious Disease Internal Medicine Nephrology Neurology Oncology Pediatrics Respiratory Medicine Rheumatology Surgery
Congress Coverage
2024 ACC Congress 2023 ESMO Congress 2023 EASD Congress 2023 ERS Congress 2023 ESC Congress
Clinical Collections
Advances in Alzheimer’s

Keynote webinar | Spotlight on medication adherence

LIVE: Thursday 27th June 2024, 18:00-19:30 (CEST)
Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.
ADVANCED SEARCH
Log in
Top
BMC Geriatrics
Published in: BMC Geriatrics 1/2013

Open Access 01-12-2013 | Research article

Interactions between Social/ behavioral factors and ADRB2 genotypes may be associated with health at advanced ages in China

Authors: Yi Zeng, Lingguo Cheng, Ling Zhao, Qihua Tan, Qiushi Feng, Huashuai Chen, Ke Shen, Jianxin Li, Fengyu Zhang, Huiqing Cao, Simon G Gregory, Ze Yang, Jun Gu, Wei Tao, Xiao-Li Tian, Elizabeth R Hauser

Published in: BMC Geriatrics | Issue 1/2013

Login to get access

Abstract

Background

Existing literature indicates that ADRB2 gene is associated with health and longevity, but none of previous studies investigated associations of carrying the ADRB2 minor alleles and interactions between ADRB2 genotypes and social/behavioral factors(GxE) with health outcomes at advanced ages. This study intends to fill in this research gap.

Method

We conducted an exploratory analysis, using longitudinal survey phenotype/genotype data from 877 oldest-old aged 90+. To estimate association of GxE interactions with health outcome, adjusted for the potential correlation between genotypes and social/behavioral factors and various other potentially confounding factors, we develop and test an innovative three-step procedure which combines logistic regression and structural equation methods.

Results

Interaction between regular exercise and carrying rs1042718 minor allele is significantly and positively associated with good cognitive function; interaction between regular exercise and carrying rs1042718 or rs1042719 minor allele is significantly and positively associated with self-reported good health; and interaction between social-leisure activities and carrying rs1042719 minor allele is significantly and positively associated with self-reported good health. Carrying rs1042718 or rs1042719 minor alleles is significantly and negatively associated with negative emotion, but the ADRB2 SNPs are not significantly associated with cognitive function and self-reported health. Our structural equation analysis found that, adjusted for the confounding effects of correlation of the ADRB2 SNPs with negative emotion, interaction between negative emotion and carrying rs1042718 or rs1042719 minor allele is significantly and negatively associated with cognitive function. The positive association of regular exercise and social-leisure activities with cognitive function and self-reported health, and negative association of negative emotion with cognitive function, were much stronger among carriers of rs1042718 or rs1042719 alleles, compared to the non-carriers.

Conclusions

The results indicate significant positive associations of interactions between social/behavioral factors and the ADRB2 genotypes with health outcomes of cognitive function and self-reported health, and negative associations of carrying rs1042718 or rs1042719 minor alleles with negative emotion, at advanced ages in China. Our findings are exploratory rather than causal conclusions. This study implies that near-future health promotion programs considering individuals’ genetic profiles, with appropriate protection of privacy/confidentiality, would yield increased benefits and reduced costs to the programs and their participants.
Appendix
Available only for authorised users
Literature
1.
Chang L, Villacorta L, Zhang J, Garcia-Barrio MT, Yang K, Hamblin M, Whitesall SE, D’Alecy LG, Chen YE: Vascular smooth muscle cell–selective peroxisome proliferator–activated receptor-γ deletion leads to hypotension. Circulation. 2009, 119 (16): 2161-2169. 10.1161/CIRCULATIONAHA.108.815803.CrossRefPubMedPubMedCentral
2.
Singh M, Roginskaya M, Dalal S, Menon B, Kaverina E, Boluyt MO, Singh K: Extracellular ubiquitin inhibits beta-AR-stimulated apoptosis in cardiac myocytes: role of GSK-3beta and mitochondrial pathways. Cardiovasc Res. 2010, 86 (1): 20-28. 10.1093/cvr/cvp402.CrossRefPubMed
3.
Zee RY, Cook NR, Cheng S, Erlich HA, Lindpaintner K, Ridker PM: Polymorphism in the beta2-adrenergic receptor and lipoprotein lipase genes as risk determinants for idiopathic venous thromboembolism: a multilocus, population-based, prospective genetic analysis. Circulation. 2006, 113 (18): 2193-2200. 10.1161/CIRCULATIONAHA.106.615401.CrossRefPubMed
4.
Woszczek G, Borowiec M, Ptasinska A, Kosinski S, Pawliczak R, Kowalski M: β2‒ADR haplotypes/polymorphisms associate with bronchodilator response and total IgE in grass allergy. Allergy. 2005, 60 (11): 1412-1417. 10.1111/j.1398-9995.2005.00869.x.CrossRefPubMed
5.
Yan L, Vatner DE, O’Connor JP, Ivessa A, Ge H, Chen W, Hirotani S, Ishikawa Y, Sadoshima J, Vatner SF: Type 5 adenylyl cyclase disruption increases longevity and protects against stress. Cell. 2007, 130 (2): 247-258. 10.1016/j.cell.2007.05.038.CrossRefPubMed
6.
Kulminski AM, Culminskaya I, Ukraintseva SV, Arbeev KG, Land KC, Yashin AI: Beta2-adrenergic receptor gene polymorphisms as systemic determinants of healthy aging in an evolutionary context. Mech Ageing Dev. 2010, 131 (5): 338-345. 10.1016/j.mad.2010.04.001.CrossRefPubMedPubMedCentral
7.
Kulminski AM, Culminskaya IV, Ukraintseva SV, Arbeev KG, Akushevich I, Land KC, Yashin AI: Polymorphisms in the ACE and ADRB2 genes and risks of aging-associated phenotypes: the case of myocardial infarction. Rejuvenation Res. 2010, 13 (1): 13-21. 10.1089/rej.2009.0905.CrossRefPubMedPubMedCentral
8.
Zhao L, Yang F, Xu K, Cao H, Zheng GY, Zhang Y, Li J, Cui H, Chen X, Zhu Z, et al: Common genetic variants of the beta2-adrenergic receptor affect its translational efficiency and are associated with human longevity. Aging Cell. 2012, 11 (6): 1094-1101. 10.1111/acel.12011.CrossRefPubMedPubMedCentral
9.
Maddock RJ, Carter CS, Magliozzi JR, Gietzen D: Evidence that decreased function of lymphocyte beta adrenoreceptors reflects regulatory and adaptive processes in panic disorder with agoraphobia. Am J Psychiatry. 1993, 150 (8): 1219-CrossRefPubMed
10.
Suarez EC, Shiller AD, Kuhn CM, Schanberg S, Williams R, Zimmermann EA: The relationship between hostility and beta-adrenergic receptor physiology in health young males. Psychosom Med. 1997, 59 (5): 481-487.CrossRefPubMed
11.
Mann JJ, Brown RP, Halper JP, Sweeney JA, Kocsis JH, Stokes PE, Bilezikian JP: Reduced sensitivity of lymphocyte beta-adrenergic receptors in patients with endogenous depression and psychomotor agitation. New Engl J Med. 1985, 313 (12): 715-720. 10.1056/NEJM198509193131202.CrossRefPubMed
12.
Yu BH, Dimsdale JE, Mills PJ: Psychological states and lymphocyte β-adrenergic receptor responsiveness. Neuropsychopharmacology. 1999, 21 (1): 147-152. 10.1016/S0893-133X(98)00133-X.CrossRefPubMed
13.
Magliozzi JR, Gietzen D, Maddock RJ, Haack D, Doran AR, Goodman T, Weiler PG: Lymphocyte beta-adrenoreceptor density in patients with unipolar depression and normal controls. Biol Psychiat. 1989, 26 (1): 15-25. 10.1016/0006-3223(89)90004-8.CrossRefPubMed
14.
Connors SL, Crowell DE, Eberhart CG, Copeland J, Newschaffer CJ, Spence SJ, Zimmerman AW: β 2-Adrenergic receptor activation and genetic polymorphisms in autism: data from dizygotic twins. J Child Neurol. 2005, 20 (11): 876-884. 10.1177/08830738050200110401.CrossRefPubMed
15.
Cheslack-Postava K, Fallin M, Avramopoulos D, Connors S, Zimmerman A, Eberhart C, Newschaffer C: β2-Adrenergic receptor gene variants and risk for autism in the AGRE cohort. Mol Psychiatr. 2007, 12 (3): 283-291.
16.
Wang D, Govindaiah G, Liu R, De Arcangelis V, Cox CL, Xiang YK: Binding of amyloid β peptide to β2 adrenergic receptor induces PKA-dependent AMPA receptor hyperactivity. FASEB J. 2010, 24 (9): 3511-3521. 10.1096/fj.10-156661.CrossRefPubMedPubMedCentral
17.
Yu JT, Tan L, Ou JR, Zhu JX, Liu K, Song JH, Sun YP: Polymorphisms at the β2-adrenergic receptor gene influence Alzheimer’s disease susceptibility. Brain Res. 2008, 1210: 216-222.CrossRefPubMed
18.
Dimsdale JE, Mills P, Patterson T, Ziegler M, Dillon E: Effects of chronic stress on beta-adrenergic receptors in the homeless. Psychosom Med. 1994, 56 (4): 290-295.CrossRefPubMed
19.
Diatchenko L, Anderson AD, Slade GD, Fillingim RB, Shabalina SA, Higgins TJ, Sama S, Belfer I, Goldman D, Max MB: Three major haplotypes of the β2 adrenergic receptor define psychological profile, blood pressure, and the risk for development of a common musculoskeletal pain disorder. Am J Med Genet B Neuropsychiatr Genet. 2006, 141 (5): 449-462.CrossRef
20.
Graafsma SJ, van Tits LJ, van Heijst P, Reyenga J, Lenders JWM, de Miranda JFR, Thien T: Adrenoceptors on blood cells in patients with essential hypertension before and after mental stress. J Hypertens. 1989, 7 (7): 519-524. 10.1097/00004872-198907000-00002.CrossRefPubMed
21.
Lanfear DE, Jones PG, Marsh S, Cresci S, McLeod HL, Spertus JA: β2-adrenergic receptor genotype and survival among patients receiving β-blocker therapy after an acute coronary syndrome. JAMA. 2005, 294 (12): 1526-1533. 10.1001/jama.294.12.1526.CrossRefPubMed
22.
Lanfear DE, Spertus JA, McLeod HL: [beta] 2-adrenergic receptor genotype predicts survival: implications and future directions. J Cardiovasc Nursing. 2006, 21 (6): 474-477. 10.1097/00005082-200611000-00011.CrossRef
23.
Ferdinands JM, Mannino DM, Gwinn ML, Bray MS: ADRB2 Arg16Gly polymorphism, lung function, and mortality: results from the atherosclerosis risk in communities study. PloS one. 2007, 2 (3): e289-10.1371/journal.pone.0000289.CrossRefPubMedPubMedCentral
24.
Landi MT, Dracheva T, Rotunno M, Figueroa JD, Liu H, Dasgupta A, Mann FE, Fukuoka J, Hames M, Bergen AW: Gene expression signature of cigarette smoking and its role in lung adenocarcinoma development and survival. PLoS One. 2008, 3 (2): e1651-10.1371/journal.pone.0001651.CrossRefPubMedPubMedCentral
25.
Sehnert AJ, Daniels SE, Elashoff M, Wingrove JA, Burrow CR, Horne B, Muhlestein JB, Donahue M, Liggett SB, Anderson JL, et al: Lack of association between adrenergic receptor genotypes and survival in heart failure patients treated with carvedilol or metoprolol. J Am Coll Cardiol. 2008, 52 (8): 644-651. 10.1016/j.jacc.2008.05.022.CrossRefPubMed
26.
Nakada T, Russell JA, Boyd JH, Aguirre-Hernandez R, Thain KR, Thair SA, Nakada E, McConechy M, Walley KR: β2-adrenergic receptor gene polymorphism is associated with mortality in septic shock. Am J Resp Crit Care. 2010, 181 (2): 143-149. 10.1164/rccm.200903-0332OC.CrossRef
27.
Hjelmborg JB, Iachine I, Skytthe A, Vaupel JW, McGue M, Koskenvuo M, Kaprio J, Pedersen NL, Christensen K: Genetic influence on human lifespan and longevity. Human Genetics. 2006, 119 (3): 312-321. 10.1007/s00439-006-0144-y.CrossRef
28.
Ewbank DC: Mortality Differences by APOE Genotype Estimated From Demographic Synthesis. Genet Epidemiol. 2002, 22: 146-155. 10.1002/gepi.0164.CrossRefPubMed
29.
Zeng Y, Poston DL, Vlosky DA, Gu D: Healthy longevity in China: demographic, socioeconomic, and psychological dimensions, Volume 20. 2008, Dordrecht, the Netherlands: Springer Publisher
30.
Zeng Y, Vaupel JW: Functional capacity and self–evaluation of health and life of oldest old in China. J Social Issues. 2002, 58 (4): 733-748. 10.1111/1540-4560.00287.CrossRef
31.
Coale AJ, Li S: The effect of age misreporting in China on the calculation of mortality rates at very high ages. Demography. 1991, 28 (2): 293-301. 10.2307/2061281.CrossRefPubMed
32.
Wang Z, Zeng Y, Jeune B, Vaupel JW: Age validation of Han Chinese centenarians. Genus. 1998, 54 (1/2): 123-141.PubMed
33.
Poston DL, Luo H: Zhongguo 2000 nian shaoshu minzu de nian ling dui ji he shu zi pian hao (Age structure and composition of the Chinese minorities in 2000). Zhongguo Shaoshu Minzu Renkou (Chinese Minority Populations). 2004, 19 (3): 9-15.
34.
Folstein MF, Folstein SE, McHugh PR: “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975, 12 (3): 189-198. 10.1016/0022-3956(75)90026-6.CrossRefPubMed
35.
Deb S, Braganza J: Comparison of rating scales for the diagnosis of dementia in adults with Down’s syndrome. J Intellect Disabil Res. 1999, 43 (5): 400-407.CrossRefPubMed
36.
Osterweil D, Mulford P, Syndulko K, Martin M: Cognitive function in old and very old residents of a residential facility: Relationship to age, education, and dementia. J Am Geriatr Soc. 1994, 42 (7): 766-773.CrossRefPubMed
37.
Power C, Matthews S, Manor O: Inequalities in self-rated health: explanations from different stages of life. Lancet. 1998, 351 (9108): 1009-1013. 10.1016/S0140-6736(97)11082-0.CrossRefPubMed
38.
Mackenbach JP, Kunst AE, Cavelaars AEJM, Groenhof F, Geurts JJM, Studygroup A, Gunning-Schepers L: Socioeconomic inequalities in morbidity and mortality in western Europe. Lancet. 1997, 349: 1655-1659. 10.1016/S0140-6736(96)07226-1.CrossRefPubMed
39.
Shetterly SM, Baxter J, Mason LD, Hamman RF: Self-rated health among Hispanic vs non-Hispanic white adults: the San Luis Valley Health and Aging Study. Am J Public Health. 1996, 86 (12): 1798-1801. 10.2105/AJPH.86.12.1798.CrossRefPubMedPubMedCentral
40.
Singh-Manoux A, Guéguen A, Martikainen P, Ferrie J, Marmot M, Shipley M: Self-rated health and mortality: short-and long-term associations in the Whitehall II study. Psychosom Med. 2007, 69 (2): 138-143. 10.1097/PSY.0b013e318030483a.CrossRefPubMed
41.
Goldman N, Lin IF, Weinstein M, Lin YH: Evaluating the quality of self-reports of hypertension and diabetes. J Clin Epidemiol. 2003, 56 (2): 148-154. 10.1016/S0895-4356(02)00580-2.CrossRefPubMed
42.
Østbye T, Krause KM, Norton MC, Tschanz JA, Sanders L, Hayden K, Pieper C, Welsh‒Bohmer KA: Ten dimensions of health and their relationships with overall self‒reported health and survival in a predominately religiously active elderly population: the cache county memory study. J Am Geriatr Soc. 2005, 54 (2): 199-209.CrossRef
43.
Kaslow NJ, Rehm LP, Siegel AW: Social-cognitive and cognitive correlates of depression in children. J Abnorm Child Psych. 1984, 12 (4): 605-620. 10.1007/BF00916853.CrossRef
44.
Zeng Y, Chen H, Shi X, Yin Z, Yang Z, Gu J, Blazer D: Health Consequences of Familial Longevity Influence Among the Chinese Elderly. J Gerontol A Biol Sci Med Sci. 2012, doi:10.1093/gerona/gls203.
45.
IOM (Institute of Medicine NAoSC): Genes, behavior, and the social environment: Moving beyond the nature/nurture debate. 2006, Washington, D.C: National Academia of Sciences
46.
Rothman KJ: Epidemiology: An Introduction. 2002, New York: Oxford University Press, USA
47.
Zeng Y, Hughes CL, Lewis MA, Li J, Zhang F: Interactions between life stress factors and carrying the APOE4 allele adversely impact self-reported health in old adults. J Gerontol A Biol Sci Med Sci. 2011, 66 (10): 1054-1061.CrossRefPubMed
48.
Muthén LK, Muthén BO: Mplus: Statistical Analysis with Latent Variables; User’s Guide; [Version 6]. 2010, Los Angeles, CA: Muthén & Muthén
49.
Aiken LS, West SG, Reno RR: Multiple regression: testing and interpreting interactions. 1991, Newbury Park, CA: Sage Publications, Inc
50.
Helm R, Mark A: Analysis and evaluation of moderator effects in regression models: state of art, alternatives and empirical example. Rev Manag Sci. 2012, 6 (4): 307-332. 10.1007/s11846-010-0057-y.CrossRef
51.
Mi X, Eskridge KM, George V, Wang D: Structural equation modeling of gene–environment interactions in coronary heart disease. Ann Hum Genet. 2011, 75 (2): 255-265.PubMed
52.
Byrne B: Structural equation modeling with LISREL, PRELIS, and SIMPLIS: Basic concepts, applications, and programming. 1998, Mahwah, NJ: Lawrence Erlbaum
53.
Sobel ME: Asymptotic confidence intervals for indirect effects in structural equation models. Sociol Methodology. 1982, 13: 290-312.CrossRef
54.
Bollen KA: Total, direct, and indirect effects in structural equation models. Sociol Methodology. 1987, 17 (1): 37-69.CrossRef
55.
Hosmer DW, Lemeshow S: Confidence interval estimation of interaction. Epidemiology. 1992, 3 (5): 452-456. 10.1097/00001648-199209000-00012.CrossRefPubMed
56.
Carstens ME, Engelbrecht AH, Russell VA, Aalbers C, Gagiano CA, Chalton DO, Talijaard JJF: Beta-adrenoceptors on lymphocytes of patients with major depressive disorder. Psychiatr Res. 1987, 20 (3): 239-248. 10.1016/0165-1781(87)90084-9.CrossRef
57.
Pandey GN, Janicak PG, Davis JM: Decreased beta-adrenergic receptors in the leukocytes of depressed patients. Psychiatr Res. 1987, 22 (4): 265-273. 10.1016/0165-1781(87)90105-3.CrossRef
58.
Kahn AJ: Epigenetic and mitochondrial mechanisms in aging and longevity: a report of a meeting of the longevity consortium, Napa, California, October 25–27, 2006. J Gerontol A Biol Sci Med Sci. 2007, 62 (6): 577-582. 10.1093/gerona/62.6.577.CrossRefPubMed
59.
McDonald JH: Handbook of biological statistics, Volume 2. 2009, Baltimore, MD: Sparky House Publishing
60.
Motulsky H: Intuitive biostatistics: a nonmathematical guide to statistical thinking. 2010, Oxford: Oxford University Press
61.
Bender R, Lange S: Adjusting for multiple testing—when and how?. J Clin Epidemiol. 2001, 54 (4): 343-349. 10.1016/S0895-4356(00)00314-0.CrossRefPubMed
Metadata
Title
Interactions between Social/ behavioral factors and ADRB2 genotypes may be associated with health at advanced ages in China
Authors
Yi Zeng
Lingguo Cheng
Ling Zhao
Qihua Tan
Qiushi Feng
Huashuai Chen
Ke Shen
Jianxin Li
Fengyu Zhang
Huiqing Cao
Simon G Gregory
Ze Yang
Jun Gu
Wei Tao
Xiao-Li Tian
Elizabeth R Hauser
Publication date
01-12-2013
Publisher
BioMed Central
Published in
BMC Geriatrics / Issue 1/2013
Electronic ISSN: 1471-2318
DOI
https://doi.org/10.1186/1471-2318-13-91

Other articles of this Issue 1/2013

BMC Geriatrics 1/2013 Go to the issue

Correspondence

When it is time to hang up the keys: the driving and dementia toolkit – for persons with dementia (PWD) and caregivers – a practical resource

Study protocol

The brain-in-motion study: effect of a 6-month aerobic exercise intervention on cerebrovascular regulation and cognitive function in older adults

Research article

Laxative use and incident falls, fractures and change in bone mineral density in postmenopausal women: results from the Women’s Health Initiative

Study protocol

A best practice fall prevention exercise program to improve balance, strength / power, and psychosocial health in older adults: study protocol for a randomized controlled trial

Research article

Teaching and learning about dementia in UK medical schools: a national survey

Research article

How much do elders with chronic conditions know about their medications?
Live Webinar | 27-06-2024 | 18:00 (CEST)

Keynote webinar | Spotlight on medication adherence

Reserve your place

Live: Thursday 27th June 2024, 18:00-19:30 (CEST)

WHO estimates that half of all patients worldwide are non-adherent to their prescribed medication. The consequences of poor adherence can be catastrophic, on both the individual and population level.

Join our expert panel to discover why you need to understand the drivers of non-adherence in your patients, and how you can optimize medication adherence in your clinics to drastically improve patient outcomes.

Prof. Kevin Dolgin
Prof. Florian Limbourg
Prof. Anoop Chauhan
Developed by: Springer Medicine
Obesity Clinical Trial Summary

At a glance: The STEP trials

Read more

A round-up of the STEP phase 3 clinical trials evaluating semaglutide for weight loss in people with overweight or obesity.

Developed by: Springer Medicine

Highlights from the ACC 2024 Congress

Year in Review: Pediatric cardiology

Pediatric Cardiology Video

Watch Dr. Anne Marie Valente present the last year's highlights in pediatric and congenital heart disease in the official ACC.24 Year in Review session.

Year in Review: Pulmonary vascular disease

Cardiopulmonary Comorbidity Video

The last year's highlights in pulmonary vascular disease are presented by Dr. Jane Leopold in this official video from ACC.24.

Year in Review: Valvular heart disease

Valvular Heart Disease Video

Watch Prof. William Zoghbi present the last year's highlights in valvular heart disease from the official ACC.24 Year in Review session.

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

ACC 2024 Congress Coverage

Year in Review: Heart failure and cardiomyopathies

Heart Failure Video

Watch this official video from ACC.24. Dr. Biykem Bozkurt discusses last year's major advances in heart failure and cardiomyopathies.

Watch now

Semaglutide benefits people with type 2 diabetes and obesity-related heart failure

16-04-2024 Type 2 Diabetes News

Incentivised to exercise

11-04-2024 Lifestyle Modifications News

New intervention for STEMI-related cardiogenic shock

10-04-2024 Myocardial Infarction News

» View more highlights on the ACC 2024 congress hub page

Image Credits