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The Journal of Clinical Endocrinology & Metabolism Vol. 84, No. 6 2093-2097
Copyright © 1999 by The Endocrine Society

Original Studies

Linkage and Association of the Sodium Potassium-Adenosine Triphosphatase {alpha}2 and ß1 Genes with Respiratory Quotient and Resting Metabolic Rate in the Québec Family Study1

Peter T. Katzmarzyk, Tuomo Rankinen2, Louis Pérusse, Olivier Dériaz, Angelo Tremblay, Ingrid Borecki, D. C. Rao and Claude Bouchard

Physical Activity Sciences Laboratory (P.T.K., T.R., L.P., O.D., A.T., C.B.), Laval University, Ste-Foy, Quebec G1K 7P4, Canada; Department of Kinesiology and Health Science (P.T.K.), York University, North York, Ontario M3J 1P3, Canada; and Division of Biostatistics (I.B., D.C.R.) and Departments of Psychiatry and Genetics (D.C.R.), Washington University School of Medicine, St. Louis, Missouri 63110

Address all correspondence and requests for reprints to: Dr. Claude Bouchard, Physical Activity Sciences Laboratory, Division of Kinesiology, Department of Social and Preventive Medicine, PEPS, Laval University, Ste-Foy, Québec G1K 7P4, Canada. E-mail: claude.bouchard{at}kin.msp.ulaval.ca


   Abstract
Top
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 References
 
The purpose of this study was to examine the relationship between the {alpha}2 (exon 1 and exon 21–22 with BglII) and ß1 (MspI and PvuII) genes of the sodium potassium adenosine triphosphatase and resting metabolic rate (RMR) and respiratory quotient (RQ). The sample included 582 participants from 171 families of the Québec Family Study. RMR and RQ were adjusted for age, sex, fat mass, and fat free mass. Sib-pair analyses indicated a significant linkage between RQ and the {alpha}2 exon 1 marker (P = 0.03) and the {alpha}2 exon 21–22 marker (P = 0.02). No linkage was detected between the ß1 markers and either RMR or RQ, whereas RMR was not linked with the {alpha}2 makers. There was a significant interaction (P < 0.0003) between {alpha}2 exon 1 carrier status and age group [younger (<45 yr) vs. older (>=45 yr) adults] for RQ. The association between carrier status and RQ was significant in younger adults (RQ = 0.76 in carriers vs. 0.80 in noncarriers, P < 0.0001) but was not in older adults (RQ = 0.81 in carriers vs. 0.80 in noncarriers). The {alpha}2 exon 1 gene accounted for approximately 9.1% and 0.3% of the variance in RQ in younger and older adults, respectively. The results suggest that the sodium potassium adenosine triphosphatase {alpha}2 gene may play a role in fuel oxidation, particularly in younger individuals.


   Introduction
Top
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 References
 
OBESITY IS a chronic disease that results from long-term energy imbalance, where intake exceeds expenditure. Resting metabolic rate (RMR) and respiratory quotient (RQ) are associated with energy balance and substrate use and have thus been implicated as potentially playing a role in the development of obesity. For example, a low RMR was found to be associated with weight gain in the Pima Indians (1); however, these results could not be replicated in the Baltimore Longitudinal Study of Aging (2) and in nonobese Italian women (3). On the other hand, a low ratio of fat-to-carbohydrate oxidation rate (high RQ) has been associated with weight gain in the Pima (4), nonobese men (2), and nonobese women (3). Within this context, genes that could potentially influence RMR or RQ are candidate genes for obesity.

There is evidence for significant familial aggregation for RMR (5, 6) and RQ (4, 7), such that family members are more alike than unrelated individuals. Further, results from family and twin studies indicate that 30–40% of the variance in RMR (independent of age, sex, and body composition) can be explained by genetic factors (6, 8, 9), whereas a putative major gene accounting for 57% of the variance in RMR has also been reported (10).

The sodium potassium adenosine triphosphatase (Na,K-ATPase) is an essential and ubiquitous plasma membrane enzyme that is responsible for catalyzing the energy-dependent transport of Na+ and K+ across the cell membrane. The Na,K-ATPase is a heterodimer, composed of a catalytic ({alpha}) and a glycoprotein (ß) subunit. Although the ß-subunit does not have a catalytic function, it is necessary for the activation of the {alpha}-subunit and the transport of the heterodimer to the plasma membrane (11). Three isoforms have been identified for each of the {alpha}- and the ß-subunits, each encoded by separate genes and having unique characteristics and tissue distributions in humans.

Animal studies suggest that Na,K-ATPase activity contributes from 20–40% of whole-body RMR (12, 13, 14), whereas a human study indicates that at least 20% of whole-body RMR can be attributed to Na,K-ATPase activity (15). Further, inhibition of Na,K-ATPase with digoxin or ouabain in humans results in a decrease in both RMR (16, 17) and fat oxidation rate (17). Thus, Na,K-ATPase seems to be intimately linked with whole-body resting energy expenditure and fuel use, suggesting a role in the maintenance of body weight and perhaps in the development of obesity.

An earlier report from the Québec Family Study (QFS) reported suggestive linkage between the ß1 gene of the Na,K-ATPase and RQ, based on 94 pairs of sibs, as well as an association between the {alpha}2 gene (exon 1) and RQ in 102 unrelated adults (18). These results suggested that variation in the genes encoding the Na,K-ATPase may be important in explaining variation in RQ but not RMR in humans. The purpose of the present study is to reexamine the relationships between RMR, RQ, and variation in the genes encoding Na,K-ATPase, using the entire Phase II sample of the QFS (n = 582, 291 sib pairs).


   Materials and Methods
Top
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 References
 
Sample

The aims and design of the QFS have been previously described (19). A total of 582 individuals (253 parents and 329 offspring) from 171 families were available for the present study (Table 1Go). These were recruited from a larger pool of families of French descent, living in the greater Québec City area. The age of individuals in the sample ranged from 18–74 yr. The study was approved by the Medical Ethics Committee at Laval University, and informed consent was obtained from all participants.


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  		Table 1. Descriptive characteristics of participants

 
Phenotypes

RMR and RQ were measured using a ventilated hood and an open-circuit indirect calorimeter, as previously described (18). Measurements were made early in the morning, after an overnight fast, while participants sat quietly in a semireclined position. Respiratory exchange data from the final 10 min of the 30-min data collection period were used to calculate RMR and RQ. Gas samples were assayed with a zirconia cell O2 analyzer (Amatek CD-3A, Thermox Instruments Division, Pittsburgh, PA) and an infrared CO2 analyzer (Amatek S-3A). Analyzers were calibrated before each test using gases of known percentages of O2 and CO2. RMR is expressed kilojoules per minute-1 of energy expenditure, whereas the RQ is simply the ratio of CO2 produced to O2 consumed.

Measurements of fat mass (FM) and fat-free mass (FFM) were obtained from underwater weighing using the conversion factor of Siri (20), as previously described (21). Body density measurements were made according to the procedures of Behnke and Wilmore (22), whereas residual lung volume was determined using the helium dilution technique (23).

Data adjustments

Given that age, sex, and body composition are known to be major determinants of energy expenditure (6, 24), RMR and RQ were adjusted for the effects of age, age2, age3, FM, and FFM using regression procedures. Data adjustments were made separately in males and females 18–29 yr, 30–49 yr, and 50–74 yr old (six groups). Outliers (>3 SD from the mean) were temporarily set aside so that the regression models would not be unduly influenced by extreme observations. Covariates were added in a forward stepwise manner, and significant terms were retained at the 5% level of significance. Heteroscedasticity was examined by regressing the squared residuals on age, age2, age3, FM, and FFM. The final phenotype was computed for all individuals (including outliers) by using the best regression models and was standardized to zero mean and unit variance.

Table 2Go presents the results of the data adjustment procedures. Briefly, the five covariates (or a subset) explained between 45% and 75% of the variance in RMR and between 3.6% and 12.8% of the variance in RQ in the age and sex groups defined above. There was no heteroscedasticity detected for any of the regressions. Thus, the final phenotype was simply the residual of the mean regression, standardized to zero mean and unit variance.


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  		Table 2. Results of data adjustment procedures for RMR and RQ

 
Genotypes

The method has been described in detail previously (18). Briefly, genomic DNA was prepared from permanent lymphoblastoid cells by the proteinase K and phenol/chloroform technique (25), and the samples were digested with restriction enzymes BglII ({alpha}2 gene) and MspI (ß1 gene) and PvuII (ß1 gene). All of these restriction enzymes have been shown to identify polymorphisms with codominant Mendelian inheritance (26, 27). The resulting DNA fragments were separated by agarose gel electrophoresis and were transferred to nylon filters, hybridized with phosphorus 32-labeled genomic probes, and visualized with autoradiograms after 1–7 days of exposure at -70 C. Phage {lambda} DNA, digested with HindIII and EcoRI, was used as a size standard. The genomic probes used were as follows: {alpha}2 exon 1 probe is a 2.5-kb DNA fragment at the 5' end of the {alpha}2 gene that includes exon 1; {alpha}2 exon 21–22 probe is a 1.0-kb DNA fragment of the 3' portion of the {alpha}2 gene that includes exons 21 and 22; and the ß1 probe is a 1.2 kb-DNA fragment from the 3' portion of the ß1 gene. All probes were generously given by Dr. J. B. Lingrel from the University of Cincinnati.

Statistical analyses

A {chi}-square test was used to determine whether genotype frequencies were in Hardy-Weinberg equilibrium. Sib-pair linkage analyses of the adjusted phenotypes were performed using SIBPAL 3.0 software from the Statistical Analysis for Genetic Epidemiology (S.A.G.E.) package (28). Briefly, the purpose of sib-pair analysis is to test for linkage between a marker locus and a putative gene influencing the phenotype. Sibs sharing a greater proportion of alleles identical by descent at the marker locus should have more similar phenotypes under a linkage hypothesis. Thus, the squared sib-pair phenotypic difference is regressed on the proportion of alleles shared as identical by descent at the locus. A resulting significant negative slope is taken as evidence for linkage.

Associations among genotypes were examined using general linear models, implemented in SAS software (29). Given the small number of homozygous participants for the rare {alpha}2 alleles at exon 1 (3.3 kb) and exon 21–22 (10.5 kb), participants were categorized into carriers and noncarriers of each rare allele, for the purpose of the association studies. The association analyses were conducted using the original (unadjusted) phenotypes, while including the effects of age, age2, age3, FM, FFM, and sex in the model, using parents and one offspring randomly chosen from each family. Males and females were combined into the same sample. Further, sex-dependent and age-dependent gene effects were examined by including genotype-by-sex and genotype X age-group interaction terms in the model. The age groups were defined as younger (age < 45 yr) and older (age >= 45 yr) adults. Finally, genotype X genotype interactions were examined by modeling all possible marker interactions.


   Results
Top
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 References
 
The physical characteristics of the participants are presented in Table 1Go. Mean ages in the parental generation are 54.9 yr in males and 52.3 yr in females, whereas the mean ages in the offspring are 28.0 yr and 28.9 yr in males and females, respectively. The allele frequencies were 0.88 (8.0 Kb) and 0.12 (3.3 kb) at the {alpha}2 exon 1 locus, 0.82 (4.3 kb) and 0.18 (10.5 kb) at the {alpha}2 exon 21–22 locus, 0.54 (5.3 kb) and 0.46 (6.7 kb) at the ß1 MspI locus, and 0.59 (5.1 kb) and 0.41 (4.7 kb) at the ß1 MspI locus. All genotype frequencies were in Hardy-Weinberg equilibrium. Both the {alpha}2 and ß1 markers were in linkage disequilibrium; however, the disequilibrium was much stronger for the ß1 ({chi}2 = 229.98, P < 0.0001) than the {alpha}2 ({chi}2 = 4.09, P < 0.05) markers.

The results of the sib-pair linkage analyses are provided in Table 3Go. There were significant, though not strong, linkages between RQ and the {alpha}2 exon 1 marker (P = 0.03) and the {alpha}2 exon 21–22 marker (P = 0.02). No linkage was detected between the {alpha}2 markers and RMR, or between the ß1 markers and either RMR or RQ.


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  		Table 3. Sib-pair linkage results between the Na, K-ATPase {alpha}2 and ß1 gene markers and resting metabolic rate and respiratory quotient

 
There were no significant associations between the Na,K-ATPase genes and either RMR or RQ, with the exception of the {alpha}2 exon 1 marker and RQ. There was a significant interaction (P < 0.0001) between {alpha}2 exon 1 carrier status and age group [younger (<45 yr) vs. older (>=45 yr) adults] for RQ (Fig. 1Go). The significant age group X genotype interaction persisted within males (F = 3.77, P = 0.05) and females (F = 9.79, P = 0.002), as well. The association between carrier status of the 3.3-kb allele and RQ was highly significant in younger adults (P < 0.0001) but not in older adults (Table 4Go). Further, the {alpha}2 exon 1 gene accounted for approximately 9.1% and 0.3% of the variation in RQ in younger and older adults, respectively. Again, the association remained when the data were split into male (F = 5.13, P = 0.03) and female (F = 11.21, P = 0.001) groups. However, there was no association between {alpha}2 exon 21–22 carrier status and RQ.



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  		Figure 1. RQ in carriers and noncarriers of the 3.3-kb allele of the Na,K-ATPase {alpha}2 exon 1 marker, according to age group [younger (< 45 yr) vs. older (>=45 yr)]. Error bars indicate 1 SE. Means are adjusted for the effects of age, age2, age3, FM, FFM, and sex.

 

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  		Table 4. Respiratory quotient according to the presence or absence of the 3.3-kb allele at the {alpha}2 exon 1 and the 10.5-kb allele at the {alpha}2 exon 21–22 Na, K-ATPase marker loci

 
The pattern of RQ, in relation to {alpha}2 exon 1 carrier status, for the 3.3-kb allele indicated that carriers had significantly lower values for RQ than noncarriers, particularly in young adults (Table 4Go). Although the numbers of 3.3-kb/3.3-kb homozygotes is small, the RQ trend observed with carrier status was further examined using the genotype status. Briefly, 3.3-kb/3.3-kb homozygotes (n = 6) had a mean RQ of 0.76 ± 0.020 vs. 0.79 ± 0.005 in 3.3-kb/8.0-kb heterozygotes (n = 84) and 0.80 ± 0.003 in 8.0-kb/8.0-kb homozygotes (n = 311) (P = 0.07). Thus, the same trend is observed using the 3.3-kb carrier status and the genotype status, suggesting that variation in the {alpha}2 exon 1 polymorphism is influencing relative rates of fuel oxidated. Finally, gene-gene interactions were examined by modeling all possible gene marker interactions. Results (not presented) indicated that there were no significant sex-by-gene or gene-by-gene interactions.


   Discussion
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
References
 
The results support the hypothesis that variation in the Na,K-ATPase {alpha}2 genes is associated with resting relative fuel oxidation rates in humans. The {alpha}-subunit is the catalytic part of the Na,K-ATPase, whereas the function of the ß-subunit is poorly understood. Although the Na,K-ATPase cannot function without its ß-subunit (11), the functional aspects of ion transport seem to rest with the {alpha}-subunit. Thus, genetic variation in genes encoding the {alpha}-subunit may have more functional consequences than those encoding the ß-subunit. The {alpha}-subunit isoforms have distinct activity and tissue distributions. The expression of the {alpha}1 isoform is ubiquitous; the {alpha}2 isoform is expressed in excitable tissues, such as brain, skeletal muscle, and the heart; whereas {alpha}3 is expressed almost exclusively in neural tissue (30, 31). Given the wide distribution of {alpha}2 within the body, particularly in skeletal muscle, it has the potential to modify the whole-body RQ.

The lower RQ observed in carriers of the 3.3-kb allele of the {alpha}2 exon 1 marker could be the result of either enhanced fat oxidation, slightly blunted carbohydrate oxidation, or a combination of the two. Inhibition of Na,K-ATPase by digoxin resulted in a significant decrease in fat oxidation rate, but not carbohydrate oxidation rate, in a sample of young males (17). Further, there were significant correlations between changes in serum levels of digoxin and changes in both RQ (r = 0.66) and plasma K+ (r = 0.82). Thus, it is plausible that carriers of the 3.3 kb-allele of the the {alpha}2 exon 1 gene have enhanced Na,K-ATPase activity, which could lead to an increase in fat oxidation rate, relative to carbohydrate oxidation rate, and thus to a decrease in RQ.

The mechanisms of the hypothesized effects remain unknown; however, one possibility rests with changes in fatty acid uptake, as a result of changes in plasma membrane potential difference, which is regulated largely by Na,K-ATPase activity. Increased Na,K-ATPase activity has been shown to increase the uptake of oleate in rat hepatocytes (32) and myocytes (33). Further, a recent study has shown that, at low fatty acid concentrations, hepatocellular fatty acid uptake is driven, in part, by an intracellular negative electric membrane potential (34). Similarly, carrier-mediated uptake of fatty acids in rat hepatocytes was shown to follow an inwardly directed transmembrane proton gradient (35). Through this phenomenon, intracellular free-fatty acid concentration would be increased, leading to an alteration of carbohydrate metabolism (36), and thus influence the RQ. Further, it is possible that the variation in RQ associated with the {alpha}2 gene is caused by altered hormone/Na+ pump activity relationships, because Na,K-ATPase activity is influenced, in part, by several hormones (insulin, thyroid hormones, catecholamines, and others) (37). More work is required to better understand the metabolic pathways that link Na,K-ATPase activity and relative fuel use.

An earlier report, based on a subsample of the current dataset (QFS), indicated marginal evidence for linkage between the ß1 MspI marker and RQ (P = 0.04) in a sample of 94 pairs of siblings (18). However, with the incorporation of the entire cohort of QFS siblings (291 pairs), the linkage is no longer evident (P = 0.69). The original publication of Dériaz et al. (18) also reported a significant association between 3.3-kb carrier status at the {alpha}2 exon 1 marker and RQ, in a sample of 102 unrelated adults (P = 0.02), in which the carriers had significantly greater RQ (0.84 ± 0.009) than noncarriers (0.82 ± 0.005). At that time, the sample included only one 3.3-kb/3.3-kb homozygote, whereas the current sample contains six homozygotes. In addition, the previous analysis was based on the parental generation only, whereas the present investigation also includes members of the offspring generation. It should be noted that the significant association between carrier status and RQ was found only in the younger adult (age < 45 yr) age group.

The finding of a significant age X genotype interaction effect on RQ is intriguing. The results suggest that the association between carrier status at the exon 1 locus of the {alpha}2 gene is stronger in younger than in older adults. There are some potential explanations for this finding. Animal studies have shown that the energy costs associated with Na,K-ATPase activity are higher in younger than in older animals, and this has been attributed to higher growth rates in young animals (12). Further, a lower RMR observed in older men (67 ± 6 yr) vs. younger men (28 ± 7 yr) was shown to be partially attributable to lower Na,K-ATPase activity in the older men, after adjusting for differences in FFM (16). It is also possible that the link between Na,K-ATPase and fuel use is stronger in younger than in older individuals, and this is why the genetic effect is greater in younger individuals. In addition to the growth hypothesis, younger individuals have likely not developed progressive metabolic abnormalities to the same extent as older individuals, which may cloud the hypothesized relationships.

Despite the fact that it is an attractive biological hypothesis, the results do not provide support for linkage or association between the Na,K-ATPase genes and RMR. However, this does not preclude the involvement of these genes in the regulation of RMR. Other polymorphisms within the genes may be more informative. In addition, the interaction between genes at two or more loci may contribute to the expression of RMR; thus, studies that incorporate variation at these and other candidate genes may be required to detect the contribution of the NA,K-ATPase genes on RMR. The results do suggest, however, a role for the {alpha}2 genes of the Na,K-ATPase in substrate use, and this gene should be further investigated, with respect to its true effects on lipid and carbohydrate oxidation rates.


   Acknowledgments
 
We thank Dr. J. B. Lingrel for providing all of the Na,K-ATPase probes, and Monique Chagnon for her expert technical help in the laboratory. Thanks are also expressed to Guy Fournier, Lucie Allard, Anne-Marie Bricault, Claude Leblanc, and Dr. Germain Thériault for their contribution to the data collection in the QFS.


   Footnotes
 
1 The QFS is currently supported by the Medical Research Council of Canada (PG-11811, GR-15187, and MT-13960) and funding (to C.B.) from the Donald B. Brown Research Chair on Obesity, which is supported by the Medical Research Council of Canada and Hoffman-La Roche Canada. Some of the results of this paper were obtained by using the program software S.A.G.E., which is supported by a USPHS Resource Grant (1-P41-RR03655) from the National Center for Research Resources. Back

2 Fellow from the Academy of Finland. Back

Received December 10, 1998.

Revised February 26, 1999.

Accepted March 8, 1999.


   References
Top
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 References
 

  1. Ravussin E, Lillioja S, Knowler WC, et al. 1988 Reduced rate of energy expenditure as a risk factor for body-weight gain. N Engl J Med. 318:467–472.[Abstract]
  2. Seidell JC, Muller DC, Sorkin JD, Andres R. 1992 Fasting respiratory exchange ratio and resting metabolic rate as predictors of weight gain: the Baltimore Longitudinal Study on Aging. Int J Obes. 16:667–674.[Medline]
  3. Marra M, Scalfi L, Covino A, Esposito-Del Puente A, Contaldo F. 1988 Fasting respiratory quotient as a predictor of weight changes in non-obese women. Int J Obes. 22:601–603.
  4. Zurlo F, Lillioja S, Esposito-Del Puente A, et al. 1990 Low ratio of fat to carbohydrate oxidation as predictor of weight gain: study of 24-h RQ. Am J Physiol. 259:E650–E657.
  5. Bogardus C, Lillioja S, Ravussin E, et al. 1986 Familial dependence of the resting metabolic rate. N Engl J Med. 315:96–100.[Abstract]
  6. Bouchard C, Tremblay A, Nadeau A, et al. 1989 Genetic effect in resting and exercise metabolic rates. Metabolism. 38:364–370.[CrossRef][Medline]
  7. Toubro S, Sorenson TI, Hindsberger C, Christensen NJ, Astrup A. 1998 Twenty-four-hour respiratory quotient: the role of diet and familial resemblance. J Clin Endocrinol Metab. 83:2758–2764.[Abstract/Free Full Text]
  8. Fontaine E, Savard R, Tremblay A, Després J-P, Poehlman E, Bouchard C. 1985 Resting metabolic rate in monozygotic and dizygotic twins. Acta Genet Med Gemellol (Roma). 34:41–47.[Medline]
  9. Bouchard C, Pérusse L, Dériaz O, Després J-P, Tremblay A. 1993 Genetic influences on energy expenditure in humans. Crit Rev Food Sci Nutr. 33:345–350.[Medline]
  10. Rice T, Tremblay A, Dériaz O, Pérusse L, Rao DC, Bouchard C. 1996 A major gene for resting metabolic rate unassociated with body composition: results from the Québec Family Study. Obes Res. 4:441–449.[Medline]
  11. McDonough AA, Geering K, Farley RA. 1990 The sodium pump needs its B subunit. FASEB J. 4:1598–1605.[Abstract]
  12. Milligan LP, McBride BW. 1985 Shifts in animal energy requirements across physiological and alimentational states. Energy costs of ion pumping by animal tissues. J Nutr. 115:1374–1382.
  13. Kelly JM, McBride BW. 1990 The sodium pump and other mechanisms of thermogenesis in selected tissues. Proc Nutr Soc. 49:185–202.[CrossRef][Medline]
  14. Clausen T, Van Hardeveld CV, Everts ME. 1991 Significance of cation transport in control of energy metabolism and thermogenesis. Physiol Rev. 71:733–774.[Free Full Text]
  15. Swaminathan R, Burrows G, McMurray J. 1982 Energy cost of sodium pump activity in man: an in vivo study of metabolic rate in human subjects given digoxin. IRCS Med Sci. 10:949.
  16. Poehlman ET, Toth MJ, Webb GD. 1993 Sodium-potassium pump activity contributes to the age-related decline in resting metabolic rate. J Clin Endocrinol Metab. 76:1054–1057.[Abstract]
  17. Lyon X, Schutz Y, Buclin T, Jequier E, Dériaz O. 1995 Inhibition of Na(+)-K(+)-ATPase by digoxin and its relation with energy expenditure and nutrient oxidation rate. Am J Physiol. 268:E1051–E1056.
  18. Dériaz O, Dionne F, Pérusse L, et al. 1994 DNA variation in the genes of the Na,K-adenosine triphosphatase and its relation with resting metabolic rate, respiratory quotient, and body fat. J Clin Invest. 93:838–843.
  19. Bouchard C. 1996 Genetic epidemiology, association, and sib-pair linkage: results from the Québec Family Study. In: Bray GA, Ryan DH, eds. Molecular and Genetic Aspects of Obesity, Pennington Center Nutrition Series. Vol. 5. Baton Rouge: Louisiana State University Press; 470–481.
  20. Siri WE. 1976 The gross composition of the body. Adv Biol Med Phys. 4:239–280.
  21. Himes J, Bouchard C. 1985 Do the new Metropolitan Life Insurance weight-height tables correctly assess body frame and body fat relationships? Am J Public Health. 75:1076–1079.[Abstract/Free Full Text]
  22. Behnke AR, Wilmore JH. 1974 Evaluation and regulation of body build and composition. Englewood Cliffs, NJ: Prentice-Hall.
  23. Meneely GR, Kaltreider NL. 1949 The volume of the lung determined by helium dilution: description of the method and comparison with other procedures. J Clin Invest. 28:129–139.
  24. Ravussin E, Bogardus C. 1989 Relationship of genetics, age and physical fitness to daily energy expenditure and fuel utilization. Am J Clin Nutr. 49:968–975.
  25. Neitzel H. 1986 A routine method for the establishment of permanent growing lymphoblastoid cell lines. Hum Genet. 73:320–326.[CrossRef][Medline]
  26. Schull MM, Pugh DG, Lingrel JB. 1989 Characterization of the human Na,K-ATPase a2 gene and identification of intragenic restriction fragment length polymorphisms. J Biol Chem. 264:17532–17543.[Abstract/Free Full Text]
  27. Schull MM, Pugh DG, Lane LK, Lingrel JB. 1990 MspI and PvuII polymorphisms in the Na,K-ATPase B subunit gene ATP1B1. Nucleic Acids Res. 18:1087.[Free Full Text]
  28. S.A.G.E. 1997 Statistical Analysis for Genetic Epidemiology. Release 3.0. Computer program package available from the Department of Epidemiology and Biostatistics, Rammelkamp Center for Education and Research, MetroHealth Campus, Case Western Reserve University, Cleveland.
  29. SAS Institute. 1988 SAS/STAT Users Guide. Cary, NC: SAS Institute.
  30. Sweadner KJ. 1989 Isozymes of the Na+/K+-ATPase. Biochim Biophys Acta. 988:185–220.[Medline]
  31. Lingrel JB, Orlowski J, Shull MM, Price EM. 1990 Molecular genetic of Na,K-ATPase. Prog Nucleic Acid Res Mol Biol. 38:37–89.[Medline]
  32. Weisiger RA, Fitz JG, Scharschmidt BF. 1989 Hepatic oleate uptake: electrochemical driving forces in intact rat liver. J Clin Invest. 83:411–420.
  33. Stremmel W. 1988 Fatty acid uptake by isolated rat heart myocytes represents a carrier-mediated effect transport process. J Clin Invest. 81:844–852.
  34. Elsing C, Kassner A, Gajdzik L, Graf J, Stremmel W. 1998 Electrogenicity of hepatocellular fatty acid uptake. Eur J Med Res. 18:393–396.
  35. Elsing C, Kassner A, Stremmel W. 1996 Effect of surface and intracellular pH on hepatocellular fatty acid uptake. Am J Physiol. 271:G1067–1073.
  36. Randle PJ, Garland PB, Hales CN, Newsholme EA. 1963 The fatty-acid cycle, its role in insulin sensitivity and the metabolic disturbances of diabetes mellitus. Lancet. 1:785–789.[Medline]
  37. Ewart HS, Klip A. 1995 Hormonal regulation of the Na+-K+-ATPase: mechanisms underlying rapid and sustained changes in pump activity. Am J Physiol 269:C295–C311.



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T. Rice, Y. C. Chagnon, L. Perusse, I. B. Borecki, O. Ukkola, T. Rankinen, J. Gagnon, A. S. Leon, J. S. Skinner, J. H. Wilmore, et al.
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