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Sghaireen MG, Ganji KK, Srivastava KC, Alam MK, Nashwan S, Migdadi FH, Al-Qerem A, Khader Y. Vitamin D, Cholesterol, and DXA Value Relationship with Bimaxillary Cone Beam CT Values. J Clin Med 2023; 12:jcm12072678. [PMID: 37048761 PMCID: PMC10094997 DOI: 10.3390/jcm12072678] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2023] [Revised: 03/18/2023] [Accepted: 03/31/2023] [Indexed: 04/07/2023] Open
Abstract
We evaluated the correlation that Vitamin D (Vit D), cholesterol levels, and T- and Z-scores of dual-energy X-ray absorptiometry (DXA) scans have with cone beam computed tomography values assessed in the anterior and posterior regions of maxillary and mandibular jaws. In total, 187 patients were recruited for this clinical study. Patients’ ages ranged between 45 and 65 years. Patients with valid DXA results, serum Vit D and cholesterol levels, and no evidence of bone disorders in the maxilla or mandibular region were included in the study and grouped in the control (non-osteoporosis) and case (osteoporosis) groups. Patients with a history of medical or dental disease that might complicate the dental implant therapy, chronic alcohol users, and patients who took calcium or Vit D supplements were excluded. The outcome variables assessed in the investigation were Vit D, cholesterol, Z-values, and cone beam computed tomography values. Regarding the case group, a significant (p < 0.05) inverse relationship was observed between Vit D and cholesterol. Although insignificant (p > 0.05), a positive relationship was found between Vit D and the cone beam computed tomography values in all regions of the jaws, except the mandibular posterior region (p < 0.05). Pearson correlation analysis was carried out. Vit D and cholesterol showed a statistically insignificant (p > 0.05) negative association with the cone beam computed tomography values in all regions of the jaws. However, the Z-values were highly correlated with the cone beam computed tomography values in all regions of the jaws (r > 7, p < 0.05). Vit D, cholesterol levels, and Z-values in women and men from young adulthood to middle age (45–65) were related with the cone beam computed tomography values of the jaws.
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Affiliation(s)
| | - Kiran Kumar Ganji
- Department of Preventive Dentistry, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia
| | - Kumar Chandan Srivastava
- Department of Oral & Maxillofacial Surgery & Diagnostic Sciences, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia
| | - Mohammad Khursheed Alam
- Department of Preventive Dentistry, College of Dentistry, Jouf University, Sakaka 72345, Saudi Arabia
| | - Shadi Nashwan
- Department of Computer Science, College of Computer and Information Sciences, Jouf University, Sakaka 72341, Saudi Arabia
| | | | - Ahmad Al-Qerem
- Department of Computer Science, Faculty of Information Technology, Zarqa University, Zarqa 13110, Jordan
| | - Yousef Khader
- Department of Public Health, Jordan University of Science & Technology, Ar-Ramtha 3030, Jordan
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Williams PT. Gene-environment interactions due to quantile-specific heritability of triglyceride and VLDL concentrations. Sci Rep 2020; 10:4486. [PMID: 32161301 PMCID: PMC7066156 DOI: 10.1038/s41598-020-60965-9] [Citation(s) in RCA: 23] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2019] [Accepted: 02/17/2020] [Indexed: 12/16/2022] Open
Abstract
"Quantile-dependent expressivity" is a dependence of genetic effects on whether the phenotype (e.g., triglycerides) is high or low relative to its distribution in the population. Quantile-specific offspring-parent regression slopes (βOP) were estimated by quantile regression for 6227 offspring-parent pairs. Quantile-specific heritability (h2), estimated by 2βOP/(1 + rspouse), decreased 0.0047 ± 0.0007 (P = 2.9 × 10-14) for each one-percent decrement in fasting triglyceride concentrations, i.e., h2 ± SE were: 0.428 ± 0.059, 0.230 ± 0.030, 0.111 ± 0.015, 0.050 ± 0.016, and 0.033 ± 0.010 at the 90th, 75th, 50th, 25th, and 10th percentiles of the triglyceride distribution, respectively. Consistent with quantile-dependent expressivity, 11 drug studies report smaller genotype differences at lower (post-treatment) than higher (pre-treatment) triglyceride concentrations. This meant genotype-specific triglyceride changes could not move in parallel when triglycerides were decreased pharmacologically, so that subtracting pre-treatment from post-treatment triglyceride levels necessarily created a greater triglyceride decrease for the genotype with a higher pre-treatment value (purported precision-medicine genetic markers). In addition, sixty-five purported gene-environment interactions were found to be potentially attributable to triglyceride's quantile-dependent expressivity, including gene-adiposity (APOA5, APOB, APOE, GCKR, IRS-1, LPL, MTHFR, PCSK9, PNPLA3, PPARγ2), gene-exercise (APOA1, APOA2, LPL), gene-diet (APOA5, APOE, INSIG2, LPL, MYB, NXPH1, PER2, TNFA), gene-alcohol (ALDH2, APOA5, APOC3, CETP, LPL), gene-smoking (APOC3, CYBA, LPL, USF1), gene-pregnancy (LPL), and gene-insulin resistance interactions (APOE, LPL).
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Affiliation(s)
- Paul T Williams
- Lawrence Berkeley National Laboratory, Molecular Biophysics & Integrated Bioimaging Division 1 Cyclotron Road, Berkeley, CA, 94720, USA.
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Ussher MH, Faulkner GEJ, Angus K, Hartmann‐Boyce J, Taylor AH. Exercise interventions for smoking cessation. Cochrane Database Syst Rev 2019; 2019:CD002295. [PMID: 31684691 PMCID: PMC6819982 DOI: 10.1002/14651858.cd002295.pub6] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
BACKGROUND Taking regular exercise, whether cardiovascular-type exercise or resistance exercise, may help people to give up smoking, particularly by reducing cigarette withdrawal symptoms and cravings, and by helping to manage weight gain. OBJECTIVES To determine the effectiveness of exercise-based interventions alone, or combined with a smoking cessation programme, for achieving long-term smoking cessation, compared with a smoking cessation intervention alone or other non-exercise intervention. SEARCH METHODS We searched the Cochrane Tobacco Addiction Group Specialised Register for studies, using the term 'exercise' or 'physical activity' in the title, abstract or keywords. The date of the most recent search was May 2019. SELECTION CRITERIA We included randomised controlled trials that compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme alone or another non-exercise control group. Trials were required to recruit smokers wishing to quit or recent quitters, to assess abstinence as an outcome and have follow-up of at least six months. DATA COLLECTION AND ANALYSIS We followed standard Cochrane methods. Smoking cessation was measured after at least six months, using the most rigorous definition available, on an intention-to-treat basis. We calculated risk ratios (RRs) and 95% confidence intervals (CIs) for smoking cessation for each study, where possible. We grouped eligible studies according to the type of comparison, as either smoking cessation or relapse prevention. We carried out meta-analyses where appropriate, using Mantel-Haenszel random-effects models. MAIN RESULTS We identified 24 eligible trials with a total of 7279 adult participants randomised. Two studies focused on relapse prevention among smokers who had recently stopped smoking, and the remaining 22 studies were concerned with smoking cessation for smokers who wished to quit. Eleven studies were with women only and one with men only. Most studies recruited fairly inactive people. Most of the trials employed supervised, group-based cardiovascular-type exercise supplemented by a home-based exercise programme and combined with a multi-session cognitive behavioural smoking cessation programme. The comparator in most cases was a multi-session cognitive behavioural smoking cessation programme alone. Overall, we judged two studies to be at low risk of bias, 11 at high risk of bias, and 11 at unclear risk of bias. Among the 21 studies analysed, we found low-certainty evidence, limited by potential publication bias and by imprecision, comparing the effect of exercise plus smoking cessation support with smoking cessation support alone on smoking cessation outcomes (RR 1.08, 95% CI 0.96 to 1.22; I2 = 0%; 6607 participants). We excluded one study from this analysis as smoking abstinence rates for the study groups were not reported. There was no evidence of subgroup differences according to the type of exercise promoted; the subgroups considered were: cardiovascular-type exercise alone (17 studies), resistance training alone (one study), combined cardiovascular-type and resistance exercise (one study) and type of exercise not specified (two studies). The results were not significantly altered when we excluded trials with high risk of bias, or those with special populations, or those where smoking cessation intervention support was not matched between the intervention and control arms. Among the two relapse prevention studies, we found very low-certainty evidence, limited by risk of bias and imprecision, that adding exercise to relapse prevention did not improve long-term abstinence compared with relapse prevention alone (RR 0.98, 95% CI 0.65 to 1.47; I2 = 0%; 453 participants). AUTHORS' CONCLUSIONS There is no evidence that adding exercise to smoking cessation support improves abstinence compared with support alone, but the evidence is insufficient to assess whether there is a modest benefit. Estimates of treatment effect were of low or very low certainty, because of concerns about bias in the trials, imprecision and publication bias. Consequently, future trials may change these conclusions.
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Affiliation(s)
- Michael H Ussher
- St George's, University of LondonPopulation Health Research InstituteCranmer TerraceLondonUKSW17 0RE
- University of StirlingInstitute for Social MarketingStirlingUK
| | - Guy E J Faulkner
- University of British ColumbiaSchool of Kinesiology2146 Health Sciences MallVancouverCanadaV6T 1Z3
| | - Kathryn Angus
- University of StirlingInstitute for Social MarketingStirlingUK
| | - Jamie Hartmann‐Boyce
- University of OxfordNuffield Department of Primary Care Health SciencesRadcliffe Observatory QuarterWoodstock RoadOxfordUKOX2 6GG
| | - Adrian H Taylor
- University of PlymouthFaculty of Health: Medicine, Dentistry and Human SciencesRoom N32, ITTC Building, Tamar Science ParkDerrifordPlymouthUKPL6 8BX
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Negative correlation of high-density lipoprotein-cholesterol and bone mineral density in postmenopausal Iranian women with vitamin D deficiency. Menopause 2019; 25:458-464. [PMID: 29557847 DOI: 10.1097/gme.0000000000001082] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
OBJECTIVE The aim of the study was to investigate the association between high-density lipoprotein (HDL) and bone status taking into account serum vitamin D levels in postmenopausal Iranian women. METHODS During January 2015 and February 2016, a total of 488 postmenopausal Iranian women participated in this cross-sectional study, all of whom were not taking osteoporosis medication and were not suffering from any chronic disorder. Dual X-ray absorptiometry was used to assess bone mineral density (BMD) of the total hip, femoral neck, and lumbar vertebrae (L2-L4). Each person was categorized based on the World Health Organization osteoporosis criteria in at least one skeletal region. At the end of the data collection, lipid profiles and vitamin D levels were measured for all participants. Vitamin D serum levels less than 30 ng/mL were defined as vitamin D deficiency or insufficiency. RESULTS 27.9% of all participants displayed osteoporosis. Osteoporotic participants tended to be older with higher HDL serum levels (P < 0.001). No significant difference was seen in low-density of lipoprotein, total triglyceride, and total cholesterol levels among participants (P > 0.05). In a univariate model, after adjusting for age, menopausal age, obesity, physical activity, and use of antihyperlipidemic drugs (statins), there were significant negative associations among HDL levels and BMD values and T-score in the three regions (P < 0.004). Interestingly, after classification of participants based on vitamin D levels and adjustment for confounding factors, these significant negative associations between HDL levels and BMD values as well as T-score were observed only in participants with vitamin D deficiency or insufficiency, in the three regions (P < 0.008). CONCLUSIONS Our data show that in postmenopausal women with vitamin D deficiency, serum levels of HDL have negative correlation with bone status.
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Mehramiz M, Ghasemi F, Esmaily H, Tayefi M, Hassanian SM, Sadeghzade M, Sadabadi F, Moohebati M, Azarpazhooh MR, Parizadeh SMR, Heidari-Bakavoli A, Safarian M, Nematy M, Ebrahimi M, Ryzhikov M, Ferns GA, Ghayour-Mobarhan M, Avan A. Interaction between a variant of CDKN2A/B-gene with lifestyle factors in determining dyslipidemia and estimated cardiovascular risk: A step toward personalized nutrition. Clin Nutr 2018; 37:254-261. [DOI: 10.1016/j.clnu.2016.12.018] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2016] [Revised: 12/12/2016] [Accepted: 12/22/2016] [Indexed: 01/12/2023]
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Tao F, Weinstock J, Venners SA, Cheng J, Hsu YH, Zou Y, Pan F, Jiang S, Zha X, Xu X. Associations of the ABCA1 and LPL Gene Polymorphisms With Lipid Levels in a Hyperlipidemic Population. Clin Appl Thromb Hemost 2017; 24:771-779. [PMID: 28891316 DOI: 10.1177/1076029617725601] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022] Open
Abstract
We conducted a cross-sectional study to investigate the effects of the adenosine triphosphate-binding cassette transporter 1 (ABCA1) I883M and lipoprotein lipase (LPL) HindIII polymorphisms on lipid levels in patients with hyperlipidemia. A total of 533 patients were enrolled. Serum lipid parameters were determined by an automatic biochemistry analyzer. Genotyping of the ABCA1 I883M and LPL HindIII was carried out using the polymerase chain reaction-restriction fragment length polymorphism technique. Multiple linear regression analysis was used to estimate the associations between serum lipid levels and the genetic polymorphisms. The frequency distribution of the ABCA1 I883M and LPL HindIII polymorphisms did not deviate from Hardy-Weinberg equilibrium. The major finding of our regression analysis showed that neither the ABCA1 I883M nor the LPL HindIII polymorphism was associated with baseline serum lipid levels in the total population. However, among patients with elevated alanine aminotransferase (ALT) levels (ALT ≥ 40 U/L), carriers of the M allele of the ABCA1 gene had lower levels of high-density lipoprotein cholesterol (HDL-C) and higher levels of low-density lipoprotein cholesterol (LDL-C) after adjusting for age, sex, smoking status, alcohol consumption, education level, occupation, and work intensity ( P < .05 for both). A test on interaction terms between the ABCA1 I833M polymorphism and ALT on HDL-C and LDL-C levels also remained significant ( P = .001 and P = .014, respectively). Our data suggest that there are significant interactive effects between ABCA1 I883M and ALT levels on HDL-C and LDL-C levels. However, the LPL HindIII polymorphism did not influence lipid levels.
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Affiliation(s)
- Fang Tao
- 1 School of Life Sciences, Anhui University, Hefei, China
| | - Justin Weinstock
- 2 Department of Statistics, University of Virginia, Charlottesville, VA, USA
| | - Scott A Venners
- 3 Faculty of Health Sciences, Simon Fraser University, Burnaby, British Columbia, Canada
| | - Jun Cheng
- 1 School of Life Sciences, Anhui University, Hefei, China
| | - Yi-Hsiang Hsu
- 4 Institute for Aging Research, HSL and Harvard Medical School, Boston, MA, USA.,5 Molecular and Integrative Physiological Sciences Program, Harvard School of Public Health, Boston, MA, USA
| | - Yanfeng Zou
- 6 Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Faming Pan
- 6 Department of Epidemiology and Biostatistics, School of Public Health, Anhui Medical University, Hefei, China
| | - Shanqun Jiang
- 1 School of Life Sciences, Anhui University, Hefei, China.,7 Institute of Biomedicine, Anhui Medical University, Hefei, China
| | - Xiangdong Zha
- 1 School of Life Sciences, Anhui University, Hefei, China
| | - Xiping Xu
- 8 Division of Epidemiology and Biostatistics, University of Illinois at Chicago School of Public Health, Chicago, IL, USA
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7
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Abstract
BACKGROUND Taking regular exercise may help people give up smoking by moderating nicotine withdrawal and cravings, and by helping to manage weight gain. OBJECTIVES To determine whether exercise-based interventions alone, or combined with a smoking cessation programme, are more effective than a smoking cessation intervention alone. SEARCH METHODS We searched the Cochrane Tobacco Addiction Group Specialized Register in April 2014, and searched MEDLINE, EMBASE, PsycINFO, and CINAHL Plus in May 2014. SELECTION CRITERIA We included randomized trials which compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme (which we considered the control in this review). Studies were required to recruit smokers or recent quitters and have a follow-up of six months or more. Studies that did not meet the full inclusion criteria because they only assessed the acute effects of exercise on smoking behaviour, or because the outcome was smoking reduction, are summarised but not formally included. DATA COLLECTION AND ANALYSIS We extracted data on study characteristics and smoking outcomes. Because of differences between studies in the characteristics of the interventions used we summarized the results narratively, making no attempt at meta-analysis. We assessed risk of selection and attrition bias using standard methodological procedures expected by The Cochrane Collaboration. MAIN RESULTS We identified 20 trials with a total of 5,870 participants. The largest study was an internet trial with 2,318 participants, and eight trials had fewer than 30 people in each treatment arm. Studies varied in the timing and intensity of the smoking cessation and exercise programmes offered. Only one included study was judged to be at low risk of bias across all domains assessed. Four studies showed significantly higher abstinence rates in a physically active group versus a control group at end of treatment. One of these studies also showed a significant benefit for exercise versus control on abstinence at the three-month follow-up and a benefit for exercise of borderline significance (p = 0.05) at the 12-month follow-up. Another study reported significantly higher abstinence rates at six month follow-up for a combined exercise and smoking cessation programme compared with brief smoking cessation advice. One study showed significantly higher abstinence rates for the exercise group versus a control group at the three-month follow-up but not at the end of treatment or 12-month follow-up. The other studies showed no significant effect for exercise on abstinence. AUTHORS' CONCLUSIONS Only two of the 20 trials offered evidence for exercise aiding smoking cessation in the long term. All the other trials were too small to reliably exclude an effect of intervention, or included an exercise intervention which may not have been sufficiently intense to achieve the desired level of exercise. Trials are needed with larger sample sizes, sufficiently intense interventions in terms of both exercise intensity and intensity of support being provided, equal contact control conditions, and measures of exercise adherence and change in physical activity in both exercise and comparison groups.
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Affiliation(s)
- Michael H Ussher
- Population Health Research Institute, St George's, University of London, Cranmer Terrace, London, UK, SW17 0RE
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Lyu S, Su J, Xiang Q, Wu M. Association of dietary pattern and physical activity level with triglyceride to high-density lipoprotein cholesterol ratio among adults in Jiangsu, China: a cross-sectional study with sex-specific differences. Nutr Res 2014; 34:674-81. [PMID: 25176039 DOI: 10.1016/j.nutres.2014.07.007] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/27/2013] [Revised: 06/30/2014] [Accepted: 07/07/2014] [Indexed: 11/16/2022]
Abstract
Our study aims to explore the association between dietary patterns and physical activity levels (PAL) with a triglyceride-to-high-density lipoprotein cholesterol (TG/HDL-C) ratio, and to examine whether the association is sex dependent among Chinese adults. In this cross-sectional study, data were collected through questionnaires, anthropometric measurement, and biochemical tests. Four food patterns ("meat," "healthy," "high-energy," and "traditional Chinese") were established through factor analysis. Physical activity level was categorized as "active," "moderate," and "inactive." Logistic regression models were used to determine the associations between food patterns and PAL with TG/HDL-C ratio. Compared with quartile 1, quartiles 2 and 3 of meat pattern among men were found to be associated with lower risk of high TG/HDL-C ratio (the highest quartile of TG/HDL-C ratio). Similar decreased risk of high TG/HDL-C ratio was also observed in the highest quartile 4 of healthy pattern among women. Active PAL was protective against high TG/HDL-C ratio among both men (odds ratio [OR], 0.69; 95% confidence interval [CI], 0.55-0.86) and women (OR, 0.77; 95% CI, 0.62-0.96). Although no statistically significant interaction was observed, we found that individuals with active PAL and low healthy diet had a similar OR with those with inactive PAL and high healthy diet (0.62 vs 0.68). In conclusion, dietary patterns were associated with TG/HDL-C ratio in a sex-specific way, and active PAL was consistently related to decreased risk of high TG/HDL-C ratio across genders.
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Affiliation(s)
- Shurong Lyu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Jian Su
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Quanyong Xiang
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China
| | - Ming Wu
- Jiangsu Provincial Center for Disease Control and Prevention, Nanjing, Jiangsu, China.
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Tanisawa K, Ito T, Sun X, Cao ZB, Sakamoto S, Tanaka M, Higuchi M. Polygenic risk for hypertriglyceridemia is attenuated in Japanese men with high fitness levels. Physiol Genomics 2014; 46:207-15. [DOI: 10.1152/physiolgenomics.00182.2013] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
High cardiorespiratory fitness (CRF) is associated with a reduced risk for dyslipidemia; however, blood lipid levels are also affected by individual genetic variations. We performed a cross-sectional study to determine whether CRF modifies polygenic risk for dyslipidemia. Serum levels of triglycerides (TG), LDL cholesterol (LDL-C), and HDL cholesterol (HDL-C) were measured in 170 Japanese men (age 20–79 yr). CRF was assessed by measuring maximal oxygen uptake (V̇o2max), and subjects were divided into low-fitness and high-fitness groups according to the reference V̇o2max value for health promotion in Japan. We analyzed 19 single nucleotide polymorphisms (SNPs) associated with TG, LDL-C, or HDL-C levels. Based on these SNPs, we calculated three genetic risk scores (GRSs: TG-GRS, LDL-GRS, and HDL-GRS), and subjects were divided into low, middle, and high groups according to the tertile for each GRS. Serum TG levels of low-fitness individuals were higher in the high and middle TG-GRS groups than in the low TG-GRS group ( P < 0.01 and P < 0.05, respectively), whereas no differences were detected in the TG levels of high-fitness individuals among the TG-GRS groups. In contrast, the high LDL-GRS group had higher LDL-C levels than did the low LDL-GRS group, and HDL-C levels were lower in the high HDL-GRS group than in the low HDL-GRS group regardless of the fitness level ( P < 0.05). These results suggest that high CRF attenuates polygenic risk for hypertriglyceridemia; however, high CRF may not modify the polygenic risk associated with high LDL-C and low HDL-C levels in Japanese men.
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Affiliation(s)
- Kumpei Tanisawa
- Graduate School of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
- Department of Genomics for Longevity and Health, Tokyo Metropolitan Institute of Gerontology, Itabashi, Tokyo, Japan
| | - Tomoko Ito
- Graduate School of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
| | - Xiaomin Sun
- Graduate School of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan
| | - Zhen-Bo Cao
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan; and
| | - Shizuo Sakamoto
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan; and
- Institute of Advanced Active Aging Research, Tokorozawa, Saitama, Japan
| | - Masashi Tanaka
- Department of Genomics for Longevity and Health, Tokyo Metropolitan Institute of Gerontology, Itabashi, Tokyo, Japan
| | - Mitsuru Higuchi
- Faculty of Sport Sciences, Waseda University, Tokorozawa, Saitama, Japan; and
- Institute of Advanced Active Aging Research, Tokorozawa, Saitama, Japan
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Pirim D, Wang X, Radwan ZH, Niemsiri V, Hokanson JE, Hamman RF, Barmada MM, Demirci FY, Kamboh MI. Lipoprotein lipase gene sequencing and plasma lipid profile. J Lipid Res 2013; 55:85-93. [PMID: 24212298 DOI: 10.1194/jlr.m043265] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Lipoprotein lipase (LPL) plays a crucial role in lipid metabolism by hydrolyzing triglyceride (TG)-rich particles and affecting HDL cholesterol (HDL-C) levels. In this study, the entire LPL gene plus flanking regions were resequenced in individuals with extreme HDL-C/TG levels (n = 95), selected from a population-based sample of 623 US non-Hispanic White (NHW) individuals. A total of 176 sequencing variants were identified, including 28 novel variants. A subset of 64 variants [common tag single nucleotide polymorphisms (tagSNP) and selected rare variants] were genotyped in the total sample, followed by association analyses with major lipid traits. A gene-based association test including all genotyped variants revealed significant association with HDL-C (P = 0.024) and TG (P = 0.006). Our single-site analysis revealed seven independent signals (P < 0.05; r² < 0.40) with either HDL-C or TG. The most significant association was for the SNP rs295 exerting opposite effects on TG and HDL-C levels with P values of 7.5.10⁻⁴ and 0.002, respectively. Our work highlights some common variants and haplotypes in LPL with significant associations with lipid traits; however, the analysis of rare variants using burden tests and SKAT-O method revealed negligible effects on lipid traits. Comprehensive resequencing of LPL in larger samples is warranted to further test the role of rare variants in affecting plasma lipid levels.
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Affiliation(s)
- Dilek Pirim
- Department of Human Genetics, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA; and
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Baik I, Lee S, Kim SH, Shin C. A lipoprotein lipase gene polymorphism interacts with consumption of alcohol and unsaturated fat to modulate serum HDL-cholesterol concentrations. J Nutr 2013; 143:1618-25. [PMID: 23902956 DOI: 10.3945/jn.113.175315] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022] Open
Abstract
There are limited data from prospective studies regarding interactions between lipoprotein lipase gene (LPL) and lifestyle factors in association with HDL-cholesterol (HDL-C) concentrations, a biomarker of coronary heart disease risk. Our prospective cohort study investigated the interactive effects of a common LPL polymorphism and lifestyle factors, including obesity, smoking, alcohol consumption, physical activity, and dietary intake, on follow-up measurements of HDL-C and triglyceride (TG) concentrations. A total of 5314 Korean men and women aged 40-69 y participated in the study. Serum HDL-C and TG concentrations were measured in all participants at baseline and 6-y follow-up examinations. On the basis of genome-wide association data for HDL-C and TG concentrations, we selected the most significant polymorphism (rs10503669), which was in high linkage disequilibrium with the serine 447 stop (S447×) mutation (D' = 0.99) of LPL. We found that carrying the T allele reflecting the LPL ×447 allele was positively associated with follow-up measurement of HDL-C concentrations (P < 0.001). In the linear regression model adjusted for baseline HDL-C concentration and potential risk factors, we observed interactive effects of the polymorphism and consumption of alcohol (P-interaction < 0.01) and unsaturated fat (P-interaction < 0.05) on follow-up measurement of HDL-C concentrations. We also observed interactive effects of the polymorphism and body mass index (P-interaction < 0.01) on follow-up measurement of TG concentrations after adjusting for the baseline level and potential risk factors. Our findings suggest that carriers of the LPL ×447 allele benefit from moderate alcohol consumption and a diet high in unsaturated fat to minimize reduction of blood HDL-C concentrations and that obese persons who do not carry the LPL ×447 allele need to control body weight to prevent hypertriglyceridemia.
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Affiliation(s)
- Inkyung Baik
- Department of Foods and Nutrition, College of Natural Sciences, Kookmin University, Seoul, Korea
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12
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Genetic variation in Tanis was associated with elevating plasma triglyceride level in Chinese nondiabetic subjects. Lipids Health Dis 2013; 12:97. [PMID: 23829426 PMCID: PMC3706366 DOI: 10.1186/1476-511x-12-97] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2013] [Accepted: 06/29/2013] [Indexed: 01/31/2023] Open
Abstract
BACKGROUND The association of genetic polymorphisms of Tanis with triglyceride concentration in human has not been thoroughly examined. We aimed to investigate the relationship between triglyceride concentrations and Tanis genetic polymorphisms. METHODS All participants (n=1497) selected from subjects participating in the Cardiovascular Risk Survey (CRS) study were divided into two groups according to ethnicity (Han: n=1059; Uygur: n= 438). Four tagging SNPs (rs12910524, rs1384565, rs2101171, rs4965814) of Tanis gene were genotyped using TaqMan® assays from Applied Biosystems following the manufacturer's suggestions and analyzed in an ABI 7900HT Fast Real-Time PCR System. RESULTS We found that the SNP rs12910524 was associated with triglyceride levels by analyses of a dominant model (P<0.001), recessive model (P <0.001) and additive model (P < 0.001) not only in Han ethnic but also in Uygur ethnic group, and the difference remained significant after the adjustment of sex, age, alcohol intake, smoking, BMI and plasma glucose (GLU) level (All P < 0.001). However, this relationship was not observed in rs1384565, rs2101171, and rs4965814 before and after multivariate adjustment (All P > 0.05). Furthermore, there were significant interactions between rs12910524 and GLU on TG both in Han (P=0.001) and Uygur population (P=2.60×10(-4)). CONCLUSION Our results indicated that the rs12910524 in the Tanis gene was associated with triglyceride concentrations in subjects without diabetes in China.
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Mo X, Liu X, Wang L, Lu X, Chen S, Li H, Huang J, Chen J, Cao J, Li J, Tang Y, Gu D. Association of lipoprotein lipase polymorphism rs2197089 with serum lipid concentrations and LPL gene expression. J Hum Genet 2013; 58:160-4. [DOI: 10.1038/jhg.2012.151] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
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Pyun JA, Kim S, Park K, Baik I, Cho NH, Koh I, Lee JY, Cho YS, Kim YJ, Go MJ, Shim E, Kwack K, Shin C. Interaction Effects of Lipoprotein Lipase Polymorphisms with Lifestyle on Lipid Levels in a Korean Population: A Cross-sectional Study. Genomics Inform 2012; 10:88-98. [PMID: 23105935 PMCID: PMC3480683 DOI: 10.5808/gi.2012.10.2.88] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/15/2012] [Revised: 05/13/2012] [Accepted: 05/23/2012] [Indexed: 12/28/2022] Open
Abstract
Lipoprotein lipase (LPL) plays an essential role in the regulation of high-density lipoprotein cholesterol (HDLC) and triglyceride levels, which have been closely associated with cardiovascular diseases. Genetic studies in European have shown that LPL single-nucleotide polymorphisms (SNPs) are strongly associated with lipid levels. However, studies about the influence of interactions between LPL SNPs and lifestyle factors have not been sufficiently performed. Here, we examine if LPL polymorphisms, as well as their interaction with lifestyle factors, influence lipid concentrations in a Korean population. A two-stage association study was performed using genotype data for SNPs on the LPL gene, including the 3' flanking region from 7,536 (stage 1) and 3,703 (stage 2) individuals. The association study showed that 15 SNPs and 4 haplotypes were strongly associated with HDLC (lowest p = 2.86 × 10-22) and triglyceride levels (lowest p = 3.0 × 10-15). Interactions between LPL polymorphisms and lifestyle factors (lowest p = 9.6 × 10-4) were also observed on lipid concentrations. These findings suggest that there are interaction effects of LPL polymorphisms with lifestyle variables, including energy intake, fat intake, smoking, and alcohol consumption, as well as effects of LPL polymorphisms themselves, on lipid concentrations in a Korean population.
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Affiliation(s)
- Jung-A Pyun
- Department of Biomedical Science, College of Life Science, CHA University, Seongnam 463-836, Korea
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Ackert-Bicknell CL. HDL cholesterol and bone mineral density: is there a genetic link? Bone 2012; 50:525-33. [PMID: 21810493 PMCID: PMC3236254 DOI: 10.1016/j.bone.2011.07.002] [Citation(s) in RCA: 62] [Impact Index Per Article: 5.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/28/2011] [Revised: 06/27/2011] [Accepted: 07/04/2011] [Indexed: 12/16/2022]
Abstract
Overwhelming evidence has linked cardiovascular disease and osteoporosis, but the shared root cause of these two diseases of the elderly remains unknown. Low levels of high density lipoprotein cholesterol (HDL) and bone mineral density (BMD) are risk factors for cardiovascular disease and osteoporosis respectively. A number of correlation studies have attempted to determine if there is a relationship between serum HDL and BMD but these studies are confounded by a number of variables including age, diet, genetic background, gender and hormonal status. Collectively, these data suggest that there is a relationship between these two phenotypes, but that the nature of this relationship is context specific. Studies in mice plainly demonstrate that genetic loci for BMD and HDL co-map and transgenic mouse models have been used to show that a single gene can affect both serum HDL and BMD. Work completed to date has demonstrated that HDL can interact directly with both osteoblasts and osteoclasts, but no direct evidence links bone back to the regulation of HDL levels. Understanding the genetic relationship between BMD and HDL has huge implications for understanding the clinical relationship between CVD and osteoporosis and for the development of safe treatment options for both diseases.
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Abstract
BACKGROUND Taking regular exercise may help people give up smoking by moderating nicotine withdrawal and cravings, and by helping to manage weight gain. OBJECTIVES To determine whether exercise-based interventions alone, or combined with a smoking cessation programme, are more effective than a smoking cessation intervention alone. SEARCH METHODS In July 2011, we searched the Cochrane Tobacco Addiction Group Specialized Register for studies including the terms 'exercise' or 'physical activity'. We also searched MEDLINE, EMBASE, PsycINFO, Dissertation Abstracts and CINAHL using the terms 'exercise' or 'physical activity' and 'smoking cessation'. SELECTION CRITERIA We included randomized trials which compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme, recruiting smokers or recent quitters, and with a follow up of six months or more. DATA COLLECTION AND ANALYSIS We extracted data on study characteristics and smoking outcomes. Because of differences in studies we summarized the results narratively, making no attempt at meta-analysis. MAIN RESULTS We identified 15 trials, seven of which had fewer than 25 people in each treatment arm. They varied in the timing and intensity of the smoking cessation and exercise programmes. Three studies showed significantly higher abstinence rates in a physically active group versus a control group at end of treatment. One of these studies also showed a significant benefit for exercise versus control on abstinence at the three-month follow up and a benefit for exercise of borderline significance (p = 0.05) at the 12-month follow up. One study showed significantly higher abstinence rates for the exercise group versus a control group at the three-month follow up but not at the end of treatment or 12-month follow up. The other studies showed no significant effect for exercise on abstinence. AUTHORS' CONCLUSIONS Only one of the 15 trials offered evidence for exercise aiding smoking cessation at a 12-month follow up. All the other trials were too small to reliably exclude an effect of intervention, or included an exercise intervention which was insufficiently intense to achieve the desired level of exercise. Trials are needed with larger sample sizes, sufficiently intense interventions, equal contact control conditions, and measures of exercise adherence and change in physical activity in both exercise and comparison groups.
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Affiliation(s)
- Michael H Ussher
- Division of PopulationHealth Sciences and Education, StGeorge’s,University of London,CranmerTerrace, London, SW17 0RE, UK.
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Surakka I, Isaacs A, Karssen LC, Laurila PPP, Middelberg RPS, Tikkanen E, Ried JS, Lamina C, Mangino M, Igl W, Hottenga JJ, Lagou V, van der Harst P, Mateo Leach I, Esko T, Kutalik Z, Wainwright NW, Struchalin MV, Sarin AP, Kangas AJ, Viikari JS, Perola M, Rantanen T, Petersen AK, Soininen P, Johansson Å, Soranzo N, Heath AC, Papamarkou T, Prokopenko I, Tönjes A, Kronenberg F, Döring A, Rivadeneira F, Montgomery GW, Whitfield JB, Kähönen M, Lehtimäki T, Freimer NB, Willemsen G, de Geus EJC, Palotie A, Sandhu MS, Waterworth DM, Metspalu A, Stumvoll M, Uitterlinden AG, Jula A, Navis G, Wijmenga C, Wolffenbuttel BHR, Taskinen MR, Ala-Korpela M, Kaprio J, Kyvik KO, Boomsma DI, Pedersen NL, Gyllensten U, Wilson JF, Rudan I, Campbell H, Pramstaller PP, Spector TD, Witteman JCM, Eriksson JG, Salomaa V, Oostra BA, Raitakari OT, Wichmann HE, Gieger C, Järvelin MR, Martin NG, Hofman A, McCarthy MI, Peltonen L, van Duijn CM, Aulchenko YS, Ripatti S. A genome-wide screen for interactions reveals a new locus on 4p15 modifying the effect of waist-to-hip ratio on total cholesterol. PLoS Genet 2011; 7:e1002333. [PMID: 22028671 PMCID: PMC3197672 DOI: 10.1371/journal.pgen.1002333] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2011] [Accepted: 08/23/2011] [Indexed: 11/19/2022] Open
Abstract
Recent genome-wide association (GWA) studies described 95 loci controlling serum lipid levels. These common variants explain ∼25% of the heritability of the phenotypes. To date, no unbiased screen for gene-environment interactions for circulating lipids has been reported. We screened for variants that modify the relationship between known epidemiological risk factors and circulating lipid levels in a meta-analysis of genome-wide association (GWA) data from 18 population-based cohorts with European ancestry (maximum N = 32,225). We collected 8 further cohorts (N = 17,102) for replication, and rs6448771 on 4p15 demonstrated genome-wide significant interaction with waist-to-hip-ratio (WHR) on total cholesterol (TC) with a combined P-value of 4.79×10(-9). There were two potential candidate genes in the region, PCDH7 and CCKAR, with differential expression levels for rs6448771 genotypes in adipose tissue. The effect of WHR on TC was strongest for individuals carrying two copies of G allele, for whom a one standard deviation (sd) difference in WHR corresponds to 0.19 sd difference in TC concentration, while for A allele homozygous the difference was 0.12 sd. Our findings may open up possibilities for targeted intervention strategies for people characterized by specific genomic profiles. However, more refined measures of both body-fat distribution and metabolic measures are needed to understand how their joint dynamics are modified by the newly found locus.
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Affiliation(s)
- Ida Surakka
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Aaron Isaacs
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Netherlands Genomics Initiative, Leiden, The Netherlands
| | - Lennart C. Karssen
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Pirkka-Pekka P. Laurila
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
- Department of Medical Genetics, Haartman Institute, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
| | - Rita P. S. Middelberg
- Queensland Institute of Medical Research, Brisbane, Australia
- Department of Medicine, Prince Charles Hospital, Chermside, Australia
| | - Emmi Tikkanen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Janina S. Ried
- Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Claudia Lamina
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Massimo Mangino
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Wilmar Igl
- Department of Immunology, Genetics, and Pathology, University of Uppsala, Uppsala, Sweden
| | - Jouke-Jan Hottenga
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Vasiliki Lagou
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Pim van der Harst
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Irene Mateo Leach
- Department of Cardiology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Tõnu Esko
- The Estonian Genome Center and the Center of Translational Genomics of the University of Tartu, Tartu, Estonia
- The Institute of Molecular and Cellular Biology of the University of Tartu, Tartu, Estonia
| | - Zoltán Kutalik
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- Swiss Institute of Bioinformatics, Lausanne, Switzerland
| | - Nicholas W. Wainwright
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Non-Communicable Disease Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Maksim V. Struchalin
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Antti-Pekka Sarin
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
| | - Antti J. Kangas
- Computational Medicine Research Group, Institute of Clinical Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
| | - Jorma S. Viikari
- Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland
| | - Markus Perola
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
- The Estonian Genome Center and the Center of Translational Genomics of the University of Tartu, Tartu, Estonia
| | - Taina Rantanen
- Department of Health Sciences, Gerontology Research Centre, University of Jyväskylä, Jyväskylä, Finland
| | - Ann-Kristin Petersen
- Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Pasi Soininen
- NMR Metabonomics Laboratory, Department of Biosciences, University of Eastern Finland, Kuopio, Finland
| | - Åsa Johansson
- Department of Immunology, Genetics, and Pathology, University of Uppsala, Uppsala, Sweden
| | - Nicole Soranzo
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
| | - Andrew C. Heath
- Department of Psychiatry, Washington University School of Medicine, St. Louis, Missouri, United States of America
| | - Theodore Papamarkou
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Non-Communicable Disease Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Inga Prokopenko
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
| | - Anke Tönjes
- Medical Department, University of Leipzig, Leipzig, Germany
- IFB AdiposityDiseases, University of Leipzig, Leipzig, Germany
| | - Florian Kronenberg
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
| | - Angela Döring
- Institute of Epidemiology I, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Epidemiology II, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Fernando Rivadeneira
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)–sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | | | | | - Mika Kähönen
- Department of Clinical Physiology, Tampere University Hospital, Tampere, Finland
- Medical School, University of Tampere, Tampere, Finland
| | - Terho Lehtimäki
- Medical School, University of Tampere, Tampere, Finland
- Department of Clinical Chemistry, Tampere University Hospital, Tampere, Finland
| | - Nelson B. Freimer
- Department of Psychiatry, University of California Los Angeles, Los Angeles, United States of America
- Center for Neurobehavioral Genetics, Semel Institute for Neuroscience and Human Behavior, University of California Los Angeles, Los Angeles, United States of America
| | - Gonneke Willemsen
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Eco J. C. de Geus
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Aarno Palotie
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Medical Genetics, Haartman Institute, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
| | - Manj S. Sandhu
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
- Non-Communicable Disease Research Group, Department of Public Health and Primary Care, University of Cambridge, Cambridge, United Kingdom
| | - Dawn M. Waterworth
- Genetics, Medicines Discovery, and Development, GlaxoSmithKline, Philadelphia, Pennsylvania, United States of America
| | - Andres Metspalu
- The Estonian Genome Center and the Center of Translational Genomics of the University of Tartu, Tartu, Estonia
- The Institute of Molecular and Cellular Biology of the University of Tartu, Tartu, Estonia
- The Estonian Biocentre, Tartu, Estonia
| | | | - André G. Uitterlinden
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)–sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Antti Jula
- Department of Chronic Disease Prevention, National Institute for Health and Welfare, Turku, Finland
| | - Gerjan Navis
- Division of Nephrology, Department of Internal Medicine, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Cisca Wijmenga
- Department of Genetics, University Medical Centre Groningen and University of Groningen, Groningen, The Netherlands
| | - Bruce H. R. Wolffenbuttel
- Department of Endocrinology, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | | | - Mika Ala-Korpela
- Computational Medicine Research Group, Institute of Clinical Medicine, University of Oulu and Biocenter Oulu, Oulu, Finland
- NMR Metabonomics Laboratory, Department of Biosciences, University of Eastern Finland, Kuopio, Finland
- Department of Internal Medicine and Biocenter Oulu, Clinical Research Center, University of Oulu, Oulu, Finland
| | - Jaakko Kaprio
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Department of Public Health, University of Helsinki, Helsinki, Finland
- Unit for Child and Adolescent Mental Health, National Institute for Health and Welfare, Helsinki, Finland
| | - Kirsten O. Kyvik
- Institute of Regional Health Services Research, University of Southern Denmark, Odense, Denmark
- Odense Patient data Explorative Network (OPEN), Odense University Hospital, Odense, Denmark
| | - Dorret I. Boomsma
- Department of Biological Psychology, VU University Amsterdam, Amsterdam, The Netherlands
| | - Nancy L. Pedersen
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Stockholm, Sweden
| | - Ulf Gyllensten
- Department of Immunology, Genetics, and Pathology, University of Uppsala, Uppsala, Sweden
| | - James F. Wilson
- Centre for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, United Kingdom
| | - Igor Rudan
- Centre for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, United Kingdom
- Croatian Centre for Global Health, University of Split Medical School, Split, Croatia
| | - Harry Campbell
- Centre for Population Health Sciences, University of Edinburgh Medical School, Edinburgh, United Kingdom
| | - Peter P. Pramstaller
- Institute of Genetic Medicine, European Academy Bozen/Bolzano (EURAC), Bolzano, Italy
- Affiliated Institute of the University of Lübeck, Lübeck, Germany
- Department of Neurology, University of Lübeck, Lübeck, Germany
- Department of Neurology, Central Hospital of Bolzano, Bolzano, Italy
| | - Tim D. Spector
- Department of Twin Research and Genetic Epidemiology, King's College London, London, United Kingdom
| | - Jacqueline C. M. Witteman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)–sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Johan G. Eriksson
- Department of General Practice and Primary Health Care, University of Helsinki, Helsinki, Finland
- Unit of General Practice, Helsinki University Central Hospital, Helsinki, Finland
- Folkhälsan Research Centre, Helsinki, Finland
- Vasa Central Hospital, Vasa, Finland
- Department of Health Promotion and Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Veikko Salomaa
- Unit of Chronic Disease Epidemiology and Prevention, National Institute for Health and Welfare, Helsinki, Finland
| | - Ben A. Oostra
- Department of Clinical Genetics, Erasmus MC, Rotterdam, The Netherlands
| | - Olli T. Raitakari
- Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland
- Clinical Physiology, University of Turku and Turku University Hospital, Turku, Finland
| | - H.-Erich Wichmann
- Institute of Epidemiology I, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
- Institute of Medical Informatics, Biometry and Epidemiology, Chair of Epidemiology, Ludwig-Maximilians-Universität, Munich, Germany
- Klinikum Grosshadern, Munich, Germany
| | - Christian Gieger
- Institute of Genetic Epidemiology, Helmholtz Zentrum München – German Research Center for Environmental Health, Neuherberg, Germany
| | - Marjo-Riitta Järvelin
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom
| | | | - Albert Hofman
- Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands
- Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands
- Netherlands Genomics Initiative (NGI)–sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Mark I. McCarthy
- Oxford Centre for Diabetes, Endocrinology, and Metabolism, University of Oxford, Oxford, United Kingdom
- Wellcome Trust Centre for Human Genetics, University of Oxford, Oxford, United Kingdom
- Oxford NIHR Biomedical Research Centre, Churchill Hospital, Oxford, United Kingdom
| | - Leena Peltonen
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
- Department of Medical Genetics, Haartman Institute, University of Helsinki and Helsinki University Central Hospital, Helsinki, Finland
- Department of Medical Genetics, University of Lausanne, Lausanne, Switzerland
- The Broad Institute of Massachusetts Institute of Technology and Harvard University, Cambridge, Massachusetts, United States of America
| | - Cornelia M. van Duijn
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
- Centre for Medical Systems Biology, Netherlands Genomics Initiative, Leiden, The Netherlands
- Netherlands Genomics Initiative (NGI)–sponsored Netherlands Consortium for Healthy Aging (NCHA), Leiden, The Netherlands
| | - Yurii S. Aulchenko
- Genetic Epidemiology Unit, Department of Epidemiology, Erasmus University Medical Center, Rotterdam, The Netherlands
| | - Samuli Ripatti
- Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland
- Public Health Genomics Unit, National Institute for Health and Welfare, Helsinki, Finland
- Genetic Epidemiology Group, Wellcome Trust Sanger Institute, Hinxton, United Kingdom
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Patel MJ, Slentz CA, Kraus WE. Metabolic deterioration of the sedentary control group in clinical trials. J Appl Physiol (1985) 2011; 111:1211-7. [PMID: 21778417 DOI: 10.1152/japplphysiol.00421.2011] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Randomized clinical trials of exercise training regimens in sedentary individuals have provided a mechanistic understanding of the long-term health benefits and consequences of physical activity and inactivity. The sedentary control periods from these trials have provided evidence of the progressive metabolic deterioration that results from as little as 4-6 mo of continuing a physically inactive lifestyle. These clinical trials have also demonstrated that only a modest amount of physical activity is required to prevent this metabolic deterioration, and this amount of physical activity is consistent with current physical activity recommendations (150 min/wk of moderate intensity physical activity). These recommendations have been issued to the general population for a vast array of health benefits. While greater adherence to these recommendations should result in substantial improvements in the health of the population, these recommendations still remain inadequate for many individuals. An individual's physical activity requirements are influenced by such factors as an individual's diet, nonexercise physical activity patterns, genetic profile, and medications. Improving the understanding of how these factors influence an individual's physical activity requirements will help advance the field and help move the field toward the development of more personalized physical activity recommendations.
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Affiliation(s)
- Mahesh J Patel
- Division of Cardiovascular Medicine, Duke Univ. Medical Center, Durham, NC 27710, USA.
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19
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Ahmad T, Chasman DI, Buring JE, Lee IM, Ridker PM, Everett BM. Physical activity modifies the effect of LPL, LIPC, and CETP polymorphisms on HDL-C levels and the risk of myocardial infarction in women of European ancestry. ACTA ACUST UNITED AC 2011; 4:74-80. [PMID: 21252145 DOI: 10.1161/circgenetics.110.957290] [Citation(s) in RCA: 32] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
BACKGROUND Recent genome-wide association studies have identified common variants associated with high-density lipoprotein cholesterol (HDL-C). Whether these associations are modified by physical activity, which increases HDL-C levels and reduces the risk of cardiovascular disease, is uncertain. METHODS AND RESULTS In a prospective cohort study of 22 939 apparently healthy US women of European ancestry, we selected 58 single nucleotide polymorphisms (SNPs) in 9 genes that demonstrated genome-wide association (P<5×10(-8)) with HDL-C levels and sought evidence of effect modification according to levels of physical activity. Physical activity modified the effects on HDL-C of 7 SNPs at 3 loci, and the strongest evidence of effect was observed for rs10096633 at lipoprotein lipase (LPL), rs1800588 at hepatic lipase (LIPC), and rs1532624 at cholesteryl ester transfer protein (CETP) (each P-interaction<0.05). The per-minor-allele increase in HDL-C for rs1800588 at LIPC and rs1532624 at CETP was greater in active than inactive women, whereas the reverse was observed for rs10096633 at LPL. Minor-allele carrier status at the LPL SNP was associated with a reduced risk of myocardial infarction in active (hazard ratio, 0.51; 95% confidence interval 0.30-0.86) but not among inactive women (hazard ratio 1.13; 95% confidence interval 0.79 to 1.61; P-interaction=0.007). By contrast, carrier status at the CETP SNP was associated with a reduced risk of myocardial infarction regardless of activity level (hazard ratio, 0.72; 95% confidence interval, 0.57 to 0.92; P-interaction=0.71). No association between LIPC SNP carrier status and myocardial infarction risk was noted. CONCLUSIONS The effects of common variants in the LPL, LIPC, and CETP genes on HDL-C levels are modified by physical activity. For a common variant in LPL, the impact on myocardial infarction varied by activity level, whereas the effects of a common variant in CETP on myocardial infarction risk did not.
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Affiliation(s)
- Tariq Ahmad
- Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA
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Boes E, Coassin S, Kollerits B, Heid IM, Kronenberg F. Genetic-epidemiological evidence on genes associated with HDL cholesterol levels: a systematic in-depth review. Exp Gerontol 2008; 44:136-60. [PMID: 19041386 DOI: 10.1016/j.exger.2008.11.003] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2008] [Revised: 10/09/2008] [Accepted: 11/04/2008] [Indexed: 12/12/2022]
Abstract
High-density lipoprotein (HDL) particles exhibit multiple antiatherogenic effects. They are key players in the reverse cholesterol transport which shuttles cholesterol from peripheral cells (e.g. macrophages) to the liver or other tissues. This complex process is thought to represent the basis for the antiatherogenic properties of HDL particles. The amount of cholesterol transported in HDL particles is measured as HDL cholesterol (HDLC) and is inversely correlated with the risk for coronary artery disease: an increase of 1mg/dL of HDLC levels is associated with a 2% and 3% decrease of the risk for coronary artery disease in men and women, respectively. Genetically determined conditions with high HDLC levels (e.g. familial hyperalphalipoproteinemia) often coexist with longevity, and higher HDLC levels were found among healthy elderly individuals. HDLC levels are under considerable genetic control with heritability estimates of up to 80%. The identification and characterization of genetic variants associated with HDLC concentrations can provide new insights into the background of longevity. This review provides an extended overview on the current genetic-epidemiological evidence from association studies on genes involved in HDLC metabolism. It provides a path through the jungle of association studies which are sometimes confusing due to the varying and sometimes erroneous names of genetic variants, positions and directions of associations. Furthermore, it reviews the recent findings from genome-wide association studies which have identified new genes influencing HDLC levels. The yet identified genes together explain only a small amount of less than 10% of the HDLC variance, which leaves an enormous room for further yet to be identified genetic variants. This might be accomplished by large population-based genome-wide meta-analyses and by deep-sequencing approaches on the identified genes. The resulting findings will probably result in a re-drawing and extension of the involved metabolic pathways of HDLC metabolism.
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Affiliation(s)
- Eva Boes
- Division of Genetic Epidemiology, Department of Medical Genetics, Molecular and Clinical Pharmacology, Innsbruck Medical University, Innsbruck, Austria
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21
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Abstract
BACKGROUND Taking regular exercise may help people give up smoking by moderating nicotine withdrawal and cravings, and by helping to manage weight gain. OBJECTIVES To determine whether exercise-based interventions alone or combined with a smoking cessation programme are more effective than a smoking cessation intervention alone. SEARCH STRATEGY In July 2008, we searched the Cochrane Tobacco Addiction Group Specialized Register for studies including the terms 'exercise' or 'physical activity'. We also searched MEDLINE, EMBASE, PsycINFO, Dissertation Abstracts and CINAHL. SELECTION CRITERIA We included randomized trials which compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme, recruiting smokers or recent quitters, and with a follow up of six months or more. DATA COLLECTION AND ANALYSIS We extracted data on study characteristics and smoking outcomes. Because of differences in studies we summarized the results narratively, making no attempt at meta-analysis. MAIN RESULTS We identified 13 trials, six of which had fewer than 25 people in each treatment arm. They varied in the timing and intensity of the smoking cessation and exercise programmes. Three studies showed significantly higher abstinence rates in a physically active group versus a control group at end of treatment. One of these studies also showed a significant benefit for exercise versus control on abstinence at the three-month follow up and a benefit for exercise of borderline significance (P = 0.05) at the 12-month follow up. One study showed significantly higher abstinence rates for the exercise group versus a control group at the three-month follow up but not at the end of treatment or 12-month follow up. The other studies showed no significant effect for exercise on abstinence. AUTHORS' CONCLUSIONS Only one of the 13 trials offered evidence for exercise aiding smoking cessation at a 12-month follow up. All the other trials were too small to exclude reliably an effect of intervention, or included an exercise intervention which was insufficiently intense to achieve the desired level of exercise. Trials are needed with larger sample sizes, sufficiently intense interventions, equal contact control conditions, measures of exercise adherence and change in physical activity in both exercise and comparison groups.
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Affiliation(s)
- Michael H Ussher
- Division of Community Health Sciences, St George's, University of London, Cranmer Terrace, London, UK, SW17 0RE.
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22
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Franks PW, Mesa JL, Harding AH, Wareham NJ. Gene-lifestyle interaction on risk of type 2 diabetes. Nutr Metab Cardiovasc Dis 2007; 17:104-124. [PMID: 17011759 DOI: 10.1016/j.numecd.2006.04.001] [Citation(s) in RCA: 29] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/24/2006] [Revised: 04/04/2006] [Accepted: 04/09/2006] [Indexed: 01/04/2023]
Abstract
The descriptive epidemiology of type 2 diabetes suggests that gene-lifestyle interactions are critical to the development of the condition. However, unravelling the molecular detail of these interactions is a complex task. The existing literature is based on small intervention studies or cross-sectional observational quantitative trait studies. Our systematic review of the literature identified some evidence of interactions, most notably for a common variant in the PPAR-gamma gene which appears to interact with the nature of dietary fat intake. Other interactions have been reported for adrenoceptors, uncoupling proteins, fatty acid binding proteins, apolipoproteins and lipoprotein lipase. There are, to date, no reports based on the ideal study design which is a case-control study nested within a cohort. To limit the likelihood of false discovery, such studies would need to be large and the search for interaction should be restricted to a priori biologically driven hypotheses. Additional study designs that examine differential response to lifestyle change or test interaction in the context of quantitative trait studies would complement the nested case-control approach, but the emphasis here should be on precision of measurement of both phenotype and lifestyle behaviour.
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Affiliation(s)
- Paul W Franks
- Medical Research Council Epidemiology Unit, Elsie Widdowson Laboratories, 120 Fulbourn Road, Cambridge, CB1 9NL, UK
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23
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Abstract
Since the effects of tobacco smoke are so detrimental to health, growing consideration has been given to the development of harm reduction strategies for those smokers who are unable or unwilling to stop using tobacco. The term harm reduction refers to a policy, strategy, or particular intervention that assumes continued use of an undesired behavior and aspires to lower the risk of adverse consequences associated with the continuation of this addictive behavior. Up to this point, tobacco harm reduction interventions have focused on reducing tobacco-related harm through the utilization of innovative tobacco products, reduced tobacco consumption, and pharmaceutical medications. With the possible exception of medicinal nicotine products, these strategies remain unproven and thus far no scientific or medical literature exists to suggest these harm reduction strategies reduce tobacco-related exposure, morbidity, or mortality. Consequently, a need exists for broadening the range of potentially effective harm reduction strategies. This preliminary review suggests that physical activity has the potential to become one such strategy. Of the eight principles that characterize a harm reduction strategy, all are at least partially satisfied by physical activity. Further, emerging evidence indicates that physical activity may delay the occurrence of disease and premature death initiated by tobacco consumption. Significant concerns remain regarding the practicality of physical activity as a harm reduction strategy and the extent to which participation in physical activity may be used to justify continued smoking.
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24
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Mutch DM, Wahli W, Williamson G. Nutrigenomics and nutrigenetics: the emerging faces of nutrition. FASEB J 2006; 19:1602-16. [PMID: 16195369 DOI: 10.1096/fj.05-3911rev] [Citation(s) in RCA: 162] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Abstract
The recognition that nutrients have the ability to interact and modulate molecular mechanisms underlying an organism's physiological functions has prompted a revolution in the field of nutrition. Performing population-scaled epidemiological studies in the absence of genetic knowledge may result in erroneous scientific conclusions and misinformed nutritional recommendations. To circumvent such issues and more comprehensively probe the relationship between genes and diet, the field of nutrition has begun to capitalize on both the technologies and supporting analytical software brought forth in the post-genomic era. The creation of nutrigenomics and nutrigenetics, two fields with distinct approaches to elucidate the interaction between diet and genes but with a common ultimate goal to optimize health through the personalization of diet, provide powerful approaches to unravel the complex relationship between nutritional molecules, genetic polymorphisms, and the biological system as a whole. Reluctance to embrace these new fields exists primarily due to the fear that producing overwhelming quantities of biological data within the confines of a single study will submerge the original query; however, the current review aims to position nutrigenomics and nutrigenetics as the emerging faces of nutrition that, when considered with more classical approaches, will provide the necessary stepping stones to achieve the ambitious goal of optimizing an individual's health via nutritional intervention.
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Affiliation(s)
- David M Mutch
- Nestlé Research Center, Vers-chez-les-Blanc, Lausanne, Switzerland.
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25
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Turk JR, Laughlin MH. Physical activity and atherosclerosis: which animal model? ACTA ACUST UNITED AC 2005; 29:657-83. [PMID: 15536667 DOI: 10.1139/h04-042] [Citation(s) in RCA: 51] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/29/2023]
Abstract
Atherosclerosis is a progressive disease that is the most important single contributor to human cardiovascular morbidity and mortality. Epidemiologic studies show that physical activity, or routine exercise, reduces the risk of developing cardiovascular disease. The mechanisms through which exercise may function in primary or secondary prevention of atherosclerosis remain largely to be established. Most studies in humans are performed after the onset of clinical signs when disease is well advanced and the prescription of exercise is based on empirical evidence of benefit in secondary prevention. Animal models per-mit the study of the initiation and progression of preclinical stages of atherosclerosis. In order to provide information relevant to treatment and prevention, these models should mimic human disease and interactions of physical activity with disease processes as closely as possible. The purpose of this review is to compare animal models of atherosclerosis and to summarize the available data in those models in regard to the effects of exercise.
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Affiliation(s)
- James R Turk
- Dept. of Biomedical Sciences, College of Veterinary Medicine, University of Missouri, Columbia 65211, USA
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26
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Abstract
BACKGROUND Taking regular exercise may help people give up smoking by moderating nicotine withdrawal and cravings. OBJECTIVES To determine whether exercise-based interventions alone or combined with a smoking cessation programme are more effective than a smoking cessation intervention alone. SEARCH STRATEGY We searched the Cochrane Tobacco Addiction Group specialized register for studies including the terms 'exercise' or 'physical activity' in July 2004. In August 2004 we searched MEDLINE, EMBASE, PsycINFO, CINAHL, Dissertation Abstracts and SPORTDiscus. SELECTION CRITERIA We included randomized trials which compared an exercise programme alone, or an exercise programme as an adjunct to a cessation programme, with a cessation programme, recruiting smokers or recent quitters, and with a follow up of six months or more. DATA COLLECTION AND ANALYSIS We extracted data on study characteristics and smoking outcomes. Because of differences in studies we summarized the results narratively, making no attempt at meta-analysis. MAIN RESULTS We identified 11 trials, six of which had fewer than 25 people in each treatment arm. They varied in the timing and intensity of the smoking cessation and exercise programmes. Three studies showed significantly higher abstinence rates in a physically active group versus a control group at end of treatment. One of these studies also showed a benefit for exercise versus control on abstinence at both the three month and 12 month follow-up points. One study showed significantly higher abstinence rates for the exercise group versus a control group at the three month follow up but not at the end of treatment or at 12 month follow up. The other studies showed no significant effect for exercise on abstinence. AUTHORS' CONCLUSIONS Only one of the 11 trials offered evidence for exercise aiding smoking cessation. All but one of the other trials were too small to conclude that the intervention was ineffective, or included an exercise intervention which was insufficiently intense to achieve the desired level of exercise. Trials are needed with larger sample sizes, sufficiently intense exercise interventions, equal contact control conditions and measures of exercise adherence.
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Affiliation(s)
- M Ussher
- Department of Community Health Sciences (Psychology), St George's Hospital Medical School, Cranmer Terrace, London, UK, SW17 0RE.
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27
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Lee J, Tan CS, Chia KS, Tan CE, Chew SK, Ordovas JM, Tai ES. The lipoprotein lipase S447X polymorphism and plasma lipids. J Lipid Res 2004; 45:1132-9. [PMID: 15060087 DOI: 10.1194/jlr.m400016-jlr200] [Citation(s) in RCA: 42] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
We studied 4,058 subjects from a representative sample of the Singapore population 1) to determine the association between the S447X polymorphism at the LPL locus and serum lipid concentration in Chinese, Malays, and Asian Indians living in Singapore and 2) to explore any interactions with apolipoprotein E (APOE) genotype, exercise, obesity, cigarette smoking, and alcohol intake. Information on obesity, lifestyle factors (including smoking, alcohol consumption, and exercise frequency), glucose tolerance, and fasting lipids was obtained. Male and female carriers of the X447 allele had lower serum triglyceride concentrations and higher HDL cholesterol (HDL-C) concentrations. The association between the X447 allele and serum HDL-C concentration was modulated by APOE genotype in males and cigarette smoking and alcohol intake in females. The effect of the X447 allele was greatest in men who carried the E4 allele and women who smoked or consumed alcohol. The X447 allele at the LPL locus is common and associated with a less atherogenic lipid profile in Asian populations. Interactions with APOE genotype, cigarette smoking, and alcohol intake reinforce the importance of examining genetic associations, such as this one, in the context of the population of interest.
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Affiliation(s)
- J Lee
- National University of Singapore-Genome Institute of Singapore Center for Molecular Epidemiology, Community, Occupational and Family Medicine, Singapore
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28
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Devroey D, De Swaef N, Coigniez P, Vandevoorde J, Kartounian J, Betz W. Correlations between lipid levels and age, gender, glycemia, obesity, diabetes, and smoking. Endocr Res 2004; 30:83-93. [PMID: 15098922 DOI: 10.1081/erc-120029887] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/03/2022]
Abstract
A low level of high-density lipoprotein cholesterol (HDL-C) is an important cardiovascular risk factor. Dietary measures and pharmacological agents are often not sufficient to reach the HDL-C target level of 40 mg/dl in patients with low baseline HDL-C. This study assesses the association between lipid levels and age, gender, body mass index (BMI), glycemia, diabetes and smoking and focuses on the parameters influencing HDL-C. In the town of Lede (Belgium) all patients aged between 45 and 64 years were invited during 1999 for a free of charge health check-up and blood test. Blood pressure, weight, length and smoking habits were recorded. Serum levels for glycemia and lipoproteins were determined. In total, 629 subjects attended for the check-up. In a logistic regression analysis age above 50 years was correlated with low HDL-C (OR = 2.27 CI = 1.10-4.68). Male gender was correlated with low HDL-C (OR = 3.85 CI = 1.77-8.43) and with high triglycerides (TG) (OR = 1.94 CI = 1.14-3.30). From the level of 90 mg/dl glycemia was correlated with low HDL-C (OR = 2.56 CI = 1.02-6.39) and high TG (OR = 2.12 CI = 1.16-4.06). Obesity was correlated with low HDL-C (OR = 2.36 CI = 1.18-4.71) and high TG (OR = 2.17 CI = 1.88-5.23). This study provides some evidence to sharpen the target levels for glycemia and BMI among patients with low HDL-C and high TG. For these patients, the target glycemia should be around 90 mg/dl and BMI around 25 kg/m2. Physical activity and diet are also important in the achievement of these target levels.
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Affiliation(s)
- Dirk Devroey
- Department of General Practice, University of Brussels (VUB), Brussels, Belgium.
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29
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Rios DLS, Vargas AF, Ewald GM, Torres MR, Zago AJ, Callegari-Jacques SM, Hutz MH. Common Variants in the Lipoprotein Lipase Gene in Brazil: Association with Lipids and Angiographically Assessed Coronary Atherosclerosis. Clin Chem Lab Med 2003; 41:1351-6. [PMID: 14580165 DOI: 10.1515/cclm.2003.207] [Citation(s) in RCA: 12] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
Lipoprotein lipase is the rate-limiting enzyme in the lipolysis of plasma triglyceride-rich lipoproteins. We studied six variants (T-93G, D9N, N291S, PvuII, HindIII and S447X) in the lipoprotein lipase (LPL) gene in 309 non-diabetic patients with angiographically assessed coronary artery disease and in 197 controls in a southern Brazilian population of European descent. The HindIII H-allele was associated with lower triglycerides (p < 0.01) and higher high-density lipoprotein cholesterol (p = 0.03) levels, and the S447X mutation was associated with lower triglyceride levels (p < 0.01) in males, but not females. No other significant lipid associations were observed. Haplotypes were derived from these two sites (HindIII/S447X), and carriers of H-S and H-X haplotypes showed lower triglycerides (p < 0.01) and increased high-density lipoprotein cholesterol (p = 0.01) levels when compared to the H+S haplotype in males. In this gender, the H-X haplotype was associated with a protective effect (OR = 0.36, 95%CI = 0.13-0.97) for significant disease (> or = 60% of luminal coronary stenosis), even controlling for other classical risk factors.
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Affiliation(s)
- Domingos L S Rios
- Departamento de Genética, Instituto de Biociências, Universidade Federal do Rio Grande do Sul, Porto Alegre, RS, Brazil
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30
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Abstract
Plasma lipid levels have been identified as major risk factors for cardiovascular disease. Multiple behavioral and environmental factors are known to modulate their concentrations in the general population; however, there is dramatic individual variability in the association between risk factors and disease, as well as in the individual response to therapeutic intervention. These differences may be due to the interaction between genetic and nongenetic factors that are ultimately responsible for the individual disease risk and response to intervention. Great strides have been made to characterize the genes involved in the homeostasis of plasma lipoprotein levels and to identify polymorphisms that could contribute to an earlier and more precise individual risk assessment. Especially relevant has been the recent interest and progress on examining the interaction between a number of candidate genes and nongenetic factors, namely smoking, alcohol drinking, physical activity, and sex. The APOE locus continues to be the most thoroughly studied gene in this regard; however, other genes (ie, LPL, APOC3, ADH3) are showing promising results.
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Affiliation(s)
- Jose M Ordovas
- Nutrition and Genomics Laboratory, JM-USDA-Human Nutrition Research Center on Aging at Tufts University, 711 Washington Street, Boston, MA 02111, USA.
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31
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Rankinen T, Pérusse L, Rauramaa R, Rivera MA, Wolfarth B, Bouchard C. The human gene map for performance and health-related fitness phenotypes: the 2001 update. Med Sci Sports Exerc 2002; 34:1219-33. [PMID: 12165675 DOI: 10.1097/00005768-200208000-00001] [Citation(s) in RCA: 45] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
This review presents the 2001 update of the human gene map for physical performance and health-related phenotypes. It is based on scientific papers published by the end of 2001. Association studies with candidate genes, genome-wide scans with polymorphic markers, and single gene defects causing exercise intolerance to variable degrees are included. The genes and markers with evidence of association or linkage with a performance or fitness phenotype in sedentary or active people, in adaptation to acute exercise or for training-induced changes are positioned on the genetic map of all autosomes and the X chromosome. Negative studies are reviewed, but a gene or locus must be supported by at least one positive study before being inserted on the map. By the end of 2000, there were 29 loci depicted on the map. The 2001 map includes 71 loci on the autosomes and two on the X chromosome. Among these genes or markers, 24 are from prior publications on exercise intolerance and four relate to other pathologies. Finally, 13 sequence variants in mitochondrial DNA have been shown to influence relevant fitness and performance phenotypes.
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Affiliation(s)
- Tuomo Rankinen
- Human Genomics Laboratory, Pennington Biomedical Research Center, 6400 Perkins Road, Baton Rouge, LA 70808-4124, USA
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