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(Circulation. 2002;105:1904.)
© 2002 American Heart Association, Inc.
Clinical Investigation and Reports |
From the Division of Biostatistics (T.R., Y.H., M.A.P., D.C.R.) and Departments of Genetics and Psychiatry (D.C.R.), Washington University School of Medicine, St Louis, Mo; Physical Activity Sciences Laboratory (J.-P.D., L.P.), Lipid Research Center (J.-P.D., J.B.), and Molecular Endocrinology Laboratory (J.G.), Laval University, Québec, Canada; School of Kinesiology and Leisure Studies (A.S.L.), University of Minnesota, Minneapolis; Department of Kinesiology (J.S.S.), Indiana University, Bloomington, Ind; Department of Health and Kinesiology (J.H.W.), Texas A&M University, College Station, Tex; and Pennington Biomedical Research Center (C.B.), Baton Rouge, La.
Correspondence to Treva Rice, PhD, Division of Biostatistics, Washington University School of Medicine, Box 8067, 660 S Euclid Ave, St. Louis, MO 63110. E-mail treva{at}wubios.wustl.edu
| Abstract |
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Methods and Results The lipid profile was assessed in 115 black (224 individuals) and 99 white families (469 individuals), who participated in the HERITAGE Family Study, while in a sedentary state (baseline visit) and after exercise training for 20 weeks (post visit). Variables included total cholesterol, triglyceride, low-density lipoprotein cholesterol (LDL-C), apolipoprotein B (ApoB), high-density lipoprotein cholesterol (HDL-C), apolipoprotein A-I, and HDL-C subfractions 2 (HDL2-C) and 3 (HDL3-C). Familial correlations for the training responses (
=post-baseline) were significant for most variables, and the percent variance accounted for by familial factors (ie, maximal heritabilities) ranged from 25% to 38%. Exceptions were for higher heritabilities near 60% for
ApoB in blacks and
HDL2-C in whites and a lower estimate of zero for
LDL-C in blacks.
Conclusions Heritable factors in part determine lipid profile responses to regular exercise. Maximal heritabilities were similar across ethnic groups and variables, except for
LDL-C,
ApoB, and
HDL2-C. Molecular studies to identify the markers and genes associated with these influences are currently underway.
Key Words: genetics heritability lipids exercise
| Introduction |
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Although it is well documented that baseline lipids and lipoproteins are influenced by heritable factors,14 less is known of familial components for lipid responses to exercise. That is, are some individuals, because of their genetic make-up, more likely to have an improved lipid profile with exercise training? The HERITAGE Family Study is unique with regard to investigating this question because sedentary families were assessed at baseline and then again after 20 weeks of endurance exercise training. Although there were mean changes only for high-density lipoprotein cholesterol (HDL-C), ApoA-I, and triglyceride (TG),15 there was a great deal of variability for all lipids. This variability, when contrasted between and within families, constitutes the basis for estimates of heritability. In the current investigation of these HERITAGE families, we address whether the responses to exercise training cluster in families.
| Methods |
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7 METs [1 MET=3.5 mL O2 uptake/kg/min] for subjects 50 years or older and
8 METs for subjects younger than 50 years). With a few exceptions approved by a physician, body mass index was
40 kg/m2. Systolic blood pressure was
150 mm Hg, and diastolic blood pressure was
99 mm Hg. Analysis of dietary questionnaires17 ensured that the subjects maintained the same diet composition throughout the protocol.15 Each individual was trained on a cycle ergometer 3 times per week for 20 weeks. The training intensity and/or duration was adjusted every 2 weeks to ensure that the participant was working at a heart rate associated with 75% of baseline VO2max for 50 minutes during the last 6 weeks. The power output was adjusted automatically to the heart rate response by a computer program that controlled the cycle ergometer during all training sessions. Sessions were supervised on site, and adherence to the protocol was strictly monitored.18
Measures
Blood samples were obtained from an antecubital vein into Vacutainer tubes that contained EDTA and were taken in the morning after a 12-hour fast with participants in a semirecumbent position, twice at baseline, and again at 24- and 72-hours after the last training session. For eumenorrheic women, all samples were obtained in the early follicular phase of the menstrual cycle when blood plasma cholesterol alterations are minimal.19 Plasma samples for lipid assays were packed with ice for shipping to the Core Laboratory at the Lipid Research Center of Laval University.
Total cholesterol (TC) and TG levels were determined in plasma and in lipoproteins by enzymatic methods using a Technicon RA-500 Analyzer (Bayer Corporation Inc, Tarrytown, NY). Plasma VLDLs were isolated by ultracentrifugation.20 The HDL-C fraction was obtained after precipitation of LDL in the infranatant by the heparin manganese chloride method.21 Selective precipitation was used to isolate the HDL2-C and HDL3-C subfractions using dextran sulfate.22 ApoA-I was measured in the infranatant and ApoB was measured in the plasma and infranatant fraction by the rocket immunoelectrophoretic method.23 The Apo measurements were calibrated with reference standards from the Centers for Disease Control and Prevention (Atlanta, Ga). Extensive quality control procedures24 verified the reproducibility of the plasma measurements.25 Daily variation was characterized by high intraclass correlations (from 0.79 for HDL3-C to 0.95 for ApoB and TC), and the coefficient of variation was between 4.2% (ApoA-I) and 21.8% (TG). The laboratory measurement error was low, with repeated-measure and split-sample intraclass correlations that range from 0.93 (HDL3-C) to 0.99 (TC, TG, HDL-C, LDL-C, ApoB) and coefficient of variations that range from 0.7% to 10%.
To adjust for plasma volume changes associated with exercise, plasma total proteins were assayed by the biuret method at baseline and after training. The lipid levels after training were then corrected on the basis of the correlation of baseline to post-training protein levels. The 2 baseline lipid values were averaged to obtain the baseline variable, and the average of the 2 protein-corrected post-training lipid values constituted the post-training variable. TG was nonnormally distributed, and a log transformation reduced the skewness. Training responses were computed (
=post-training- baseline).
Covariates
The effects of variables suspected to influence the lipid profile, especially in response to exercise training, were explored with a regression procedure. Dietary habits (2 scales that indexed a high- and a low-fat diet) were derived from the Minnesota Eating Pattern Assessment Tool (EPAT).26,17 Habitual activity levels (work, sports, and leisure indexes) were derived from the Atherosclerosis Risk in Communities study (ARIC)/Baecke Physical Activity Questionnaire.27,28 A menstrual history assessed hormone usage (scored as Yes/No), and a health screening questionnaire assessed use of antineoplastic drugs or cardioprotective agents such as beta-blockers or diuretics. Diabetics and people on beta-blockers, other antihypertensive drugs, and lipid-lowering agents were excluded from the study. Fitness was assessed with the baseline VO2max exercise test.29 In addition, baseline fasting insulin level was used as a general index of glucose homeostasis. Blood samples were collected under EDTA, and the tubes were centrifuged at 1000g at a temperature of 4°C for 10 minutes. Plasma was kept frozen at -20°C until the time of assay. Plasma insulin was measured by radioimmunoassay with polyethylene glycol separation.30
Each
(response) was adjusted for the effects of baseline level and of covariates using a stepwise multiple regression procedure separately for each sex by generation by race group. Only terms that were significant at the 5% level were retained.
Familial Aggregation
A sex-specific family correlation model was used to assess heritability. Four types of individuals (fathers=F, mothers=M, sons=S, and daughters=D), lead to 8 correlations within 3 groups: 1 spouse (FM), 4 parent-offspring (FS, FD, MS, and MD), and 3 sibling (SS, DD, and SD). Correlations were estimated using maximum likelihood methods, as outlined in more detail elsewhere (see Data Supplement). Maximal heritability (h2), defined as the percent of variance due to additive familial effects, was adjusted for degree of spouse resemblance and indexed both genetic and familial environmental sources of variance.
| Results |
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A summary of the most parsimonious familial correlations is in Table 2. A detailed description of all of the tests that lead to these models is found elsewhere (see Data Supplement). There was significant familial resemblance for most variables, with
30% of the phenotypic variance accounted for by familial factors (maximal heritabilities). The exceptions were for no heritability for
LDL-C in blacks (0%) and higher estimates of
60% for
ApoB in blacks and
HDL2-C in whites. These traditional heritabilities are expressed as a percentage of the residual variance (ie, after removing effects caused by covariates). Heritability may be expressed alternatively as a percent of total variance (Data Supplement), ie, h2*=h2x(1-R2), in which h2 is the heritability in Table 2 and R2 is the variance due to covariates.
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| Discussion |
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HDL-C was attributed to these sources, leaving
85% still unaccounted for, which could be due in part to familial/genetic factors.
No previous studies were found reporting heritability estimates for these training responses. In the current study, familial factors accounted for
30% of the variation of the adjusted training responses with little evidence for ethnic differences. The exceptions were for no familial influence on
LDL-C (h2=0%) in blacks and higher estimates approaching 60% for
ApoB in blacks and
HDL2-C in whites. These estimates also can be expressed as a percent of the total variation. For example, the total percentage of variance accounted for in
LDL-C in blacks is 37%, stratified into that due to the covariates (37%) and heritability (0%). Similarly, in whites, the total variance accounted for is 39%. However, it is stratified differently due to covariates (7%) and familial factors (32%). Thus, for
LDL-C, the total accounted for is approximately the same across ethnic groups, although the source is partitioned differently. This discrepancy between blacks and whites may indicate genetic heterogeneity in possible underlying pleiotropic genes (ie, a gene or genes that affect multiple traits) for the LDL-training responses and the covariates. For example, baseline values of LDL-C and VO2max account for a significant percentage of the variance in blacks but not in whites. If the "genes" for initial LDL-C or fitness levels29 also affect the LDL response (ie, pleiotropic effect), then the adjustment would remove their effects and the heritability would decrease. These results are consistent with Crouse et al32 who reported that changes in LDL-C vary depending on training level. Our results suggest this dependency, in part, may have a genetic basis, at least in the black sample.
A related discrepancy specific to the black sample involves LDL-C and ApoB. The heritability for
LDL-C is lower (h2=0%) than that for
ApoB (h2=59%±26%). Although ApoB is the primary surface component of LDL, it is not the only carrier of ApoB; thus, we should not expect the circulating plasma levels and, therefore, the heritabilities for the 2 responses to be the same. The genetic pleiotropic hypothesis outlined above with respect to
LDL-C and baseline LDL-C and VO2max is still applicable with respect to the low
LDL-C finding. However, we note that the within-individual correlation between the covariate-adjusted
LDL-C and
ApoB responses is significant in the blacks (r=0.55), which suggests that some common factors, either genetic or nongenetic, underlie their covariation. If genetic, then presumably they are pleiotropic with respect to baseline LDL-C and fitness measures. These various hypotheses for LDL-C and ApoB responses and baseline LDL-C and VO2max warrant further investigation with multivariate methods to disentangle the possible common genetic causes.
A few studies investigated whether genetic markers are associated with lipid responses to exercise training. For example, a greater training-induced improvement was found in individuals with the E2 or E3 alleles of the apolipoprotein E genotypes.34 Similarly, the PvuII polymorphism of the lipoprotein lipase and the ID polymorphism of the angiotensin-converting enzyme gene were both associated with training-induced improvements. Other genes that directly or indirectly affect lipid metabolism should also be considered in this context.35 For example, genes that affect baseline levels of LDL include the LDL receptor, the LDL-receptor binding region of ApoB, cholesterol 7
-hydroxylase, and others mapped to chromosomes 1p (autosomal dominant hypercholesterolemia), 13q (LDL-Clowering gene), and 15q (precocious hypercholesterolemia). Whether these genes also affect the lipid and lipoprotein responses to exercise training warrant investigation.
In summary, these HERITAGE data represent the first report that indicates chronic responses to exercise training are in part determined by heritable factors. The possible exception is for changes in LDL-C. However, pleiotropic hypotheses among LDL-C, ApoB, and initial fitness measures are needed to thoroughly investigate this issue. It is important to note that the training responses in the current study were adjusted for baseline levels, so that these estimates are specific to the response and are independent of initial levels. In fact, the responses were adjusted for other known confounding factors, including adiposity, physical fitness and activity levels, and hormonal and behavioral characteristics. Although these factors accounted for a significant proportion of the variance in the blood lipid training responses, even more variance was accounted for by familial factors. Thus, some individuals, because of their genetic makeup, will be more likely to have an improved lipid profile with training. Given these results, molecular studies are needed to identify the markers that are linked with these responses.
| Acknowledgments |
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| Footnotes |
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Received October 19, 2001; revision received February 13, 2002; accepted February 14, 2002.
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