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American Journal of Clinical Nutrition, Vol. 80, No. 5, 1410-1414, November 2004
© 2004 American Society for Clinical Nutrition

ORIGINAL RESEARCH COMMUNICATION

Quantitative trait locus determining dietary macronutrient intakes is located on human chromosome 2p221,2,3

Guowen Cai, Shelley A Cole, Raul A Bastarrachea-Sosa, Jean W MacCluer, John Blangero and Anthony G Comuzzie

1 From the Department of Genetics, Southwest Foundation for Biomedical Research, San Antonio, TX

2 Supported by National Heart, Lung, and Blood Institute grant P01 HL45522.

3 Address reprint requests to G Cai, Department of Genetics, Southwest Foundation for Biomedical Research, 7620 NW Loop 410, San Antonio, TX 78227-5301. E-mail: gcai{at}darwin.sfbr.org.


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Obesity is generally accompanied by increased food intake.

Objective: We sought to identify the genes influencing variation in dietary macronutrient intakes in Mexican Americans.

Design: We conducted a genome-wide scan by using data derived from food-frequency questionnaires in 816 participants from the San Antonio Family Heart Study. Household effect was simultaneously estimated in a variance component model with the use of SOLAR.

Results: All dietary intake measures (total calories, proteins, fat, saturated fat, monounsaturated fat, polyunsaturated fat, carbohydrates, and sucrose) were moderately heritable. Household effect was insignificant except on total calories and sucrose. Suggestive evidence of linkage with saturated fat intake was found on chromosome 2p22 near marker D2S1346 [logarithm of odds (LOD) = 2.62]. Intakes of total calories, fat, protein, and monounsaturated fat were also suggestively linked to the same marker. A significant linkage signal on chromosome 2p22 for leptin concentrations and fat mass was localized in this population, so we used leptin or fat mass as a covariate. Multipoint LOD scores for saturated fat dropped to 1.27 and 1.90, respectively, which suggested that this region on chromosome 2p contributes to both saturated fat intake and body adiposity. This chromosomal region contains the proopiomelanocortin gene (POMC). However, 2 polymorphisms in exon 3 of the POMC gene showed no association with saturated fat intake.

Conclusions: The results strengthen the hypothesis that chromosome 2p22 harbors genes that influence a variety of obesity-related phenotypes, including macronutrient intakes.

Key Words: Genome scan • dietary intake • obesity • POMC gene • multipoint linkage • polymorphism


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Obesity has become a global epidemic and is believed to be associated with elevated incidences of type 2 diabetes, hypertension, stroke, and coronary heart disease (1). Increased food intake relative to energy expenditure is the principal contributor to the development of this chronic disorder. The regulation of dietary behavior is complex and includes environmental, biological, psychological, and genetic factors (2). Family and twin studies show a genetic determination for food preference (3) and eating behavior (4). Locations for genes underlying eating disorders such as anorexia nervosa and bulimia nervosa were proposed (5, 6). Rare mutations in genes controlling food intake such as melanocortin-4 receptor (7) were related to severe obesity in a small portion of the human population. However, the genes influencing the variation in the amounts of macronutrient intake (fats, carbohydrates, and proteins), which can predispose a general population to a risk of obesity and obesity-related diseases, were not identified.

Although understanding the genetic components of food intake is essential for the study of obesity, accurate dietary data are difficult to obtain. In this study we analyzed nutrient intake of Mexican Americans participating in the San Antonio Family Heart Study (SAFHS). Because food selection is largely influenced by income and ethnic background, we estimated nutrient intake by using standardized questionnaires adjusted for low-income Mexican Americans in San Antonio, TX. The large, extended families of this population allowed us to assess the heritability after accounting for the shared household effect and to localize chromosomal regions that influence nutrient consumption.


   SUBJECTS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
A total of 1431 subjects of 42 extended Mexican American families were recruited in the SAFHS (8). Data analyzed in this study were collected between 1992 and 1995. Families were ascertained through a randomly chosen proband (without regard to any existing disease) from a listing of residences in a low-income area of San Antonio, TX. Those aged 40–60 y who also had a spouse and at least 6 offspring or siblings or both who were aged ≥16 y were included in the proband. All relatives except pregnant women were invited to participate. All procedures were approved by the Institutional Review Board at the University of Texas Health Science Center, San Antonio.

Each family member was interviewed and received a physical examination. Pedigree relations, socioeconomic status, and medical and environmental risk factors, including diet and drug use, were recorded. Blood was drawn for determination of genotypes and phenotypes. A food-frequency questionnaire (FFQ) developed specifically for San Antonio Mexican Americans, based on the approach of Willett et al (9), was administered to assess nutrient intakes, and 816 participants completed the FFQ. The modifications and validation of the semiquantitative questionnaire were described by Stern et al (10). A total of 102 food items were included in the questionnaire, accounting for 80–85% of the macronutrient consumption of this population: total calories, total protein, total fat, and total carbohydrate. The daily intake of these food components were derived with the use of the nutrient table from the US Department of Agriculture (11-13). Each subject was interviewed individually in a private room to avoid influence from other family members.

DNA was extracted from lymphocytes and amplified by polymerase chain reaction with fluorescently labeled primers from MapPairs 6 and 8 Linkage Screening Sets (Research Genetics Inc, Huntsville, AL). The genotyping method was described previously (14, 15). Briefly, the polymerase chain reactions with each primer were performed independently and pooled into panels and analyzed on an automated DNA sequencer (Applied Biosystems model 377 with Genescan and Genotyper programs; Applied Biosystems, Foster City, CA). Two polymorphisms in POMC (proopiomelanocortin gene) exon 3 [C->T at position 7284, C->T at position 7566; numbered according to Takahashi et al (16)] were typed by using direct nucleotide sequencing as described by Hixson et al (17).

The macronutrient intakes were modeled as household effects, and heritability was estimated by using a variance decomposition approach (18). The phenotypic variances of a trait were partitioned into household effect, additive genetic effect, and random environmental effect. A household matrix was generated by assigning a unique identifier to each address such that persons living in the same house received the same identifier. The household effect was estimated as the proportion of the total phenotypic variance attributable to shared residence. The heritability was determined by modeling the phenotypic covariance between relative pairs as a function of their kinships, conditioned on household effect and covariates such as age, age-squared, sex, and their interactions. Maximum likelihood techniques were used to estimate the model limits. The significance of the household effect and the heritability was tested by using a likelihood ratio statistic.

Multipoint linkage analysis was used to identify the chromosomal regions linked to the traits under study. This method assumes that the genetic covariances between relative pairs in a pedigree are expected to be a function of the identity-by-descent relation at a marker (19). The variance component linkage model included additive genetic effects as a result of quantitative trait loci (QTLs), nonadditive genetic effects, and environmental effects. The hypothesis that there was no linkage between the QTL and the trait was tested by comparing the likelihood of the restricted model to that of a model in which the QTL effect was estimated by the maximum likelihood technique. The logarithm of the ratio between the 2 likelihoods yielded a logarithm of odds (LOD) score equivalent to the classic LOD score of linkage analysis. Age, age-squared, sex, and their interactions were entered into the analyses as covariates. Although we obtained locus-specific heritability estimates from the multipoint linkage analysis at the peak of the signal, the estimates tended to be inflated so they were not reported in this paper. According to Göring et al (20), the effect size of the identified locus cannot be reliably calculated with the use of a single data set of the currently available sample size. Therefore, the solution is to conduct a pointwise estimation in an independent data set by not conditioning on the significant findings. The quantitative genetic and linkage analyses were conducted in SOLAR 2.1 (Southwest Foundation for Biomedical Research, San Antonio, TX) (21).

We conducted a measured genotype analysis (18, 22) in SOLAR (21) to investigate the association between dietary saturated fat intake and polymorphisms in POMC. A model in which the main effects of a polymorphism were estimated separately by using a maximum likelihood method was compared with a null model in which the main effects were constrained to zero. Age, sex, age-squared, and their interactions were incorporated into the analyses as covariates. A likelihood ratio statistic asymptotically distributes as a chi-square with the df equal to the number of parameters estimated.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
The means and SDs of macronutrient intakes, fat mass, and leptin in male and female Mexican Americans are shown in Table 1Go. The average age of men was similar to that of women. Men consumed more food than women in total calories, total carbohydrate, total protein, total fat, saturated fat, monounsaturated fat, polyunsaturated fat, and total sucrose. However, the percentages of total calories contributed by protein, carbohydrate, and fat were similar in both sexes. As was demonstrated in other studies of leptin, women had higher leptin concentrations and more fat mass than men.


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  		TABLE 1. Characteristics of dietary intake, leptin, and fat mass in Mexican Americans1

 
Quantitative genetic analysis, estimates of household effect, and distribution of limits of macronutrient intakes revealed modest heritabilities for all categories of nutrient intakes, ranging from 0.09 to 0.21, when the household effects were simultaneously estimated (Table 2Go). The effects of household were significant for total calories and sucrose only. However, all nonzero household effects were incorporated into heritability analyses even though they were not significant. The phenotypes were normally distributed with kurtosis from –0.07 to 0.75 and skewness from –0.14 to 0.17, after log transformation.


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  		TABLE 2. Heritability analyses and genome scan results for dietary intake in Mexican Americans1

 
A summary of the LOD scores from the genome-wide scans is also presented in Table 2Go. The consumption of total calories, total protein, total fat, saturated fat, monounsaturated fat, and polyunsaturated fat linked to the same marker D2S1346 on chromosome 2, with saturated fat giving the largest LOD of 2.62. Adding diabetes status as a covariate, this LOD score did not change (2.59). With the use of leptin or fat mass as a covariate, the maximum LOD for saturated fat consumption dropped to 1.27 and 1.9, respectively. The LOD scores of the same genetic location for total carbohydrate and sucrose consumption were 0.73 and 0, respectively. Another location on chromosome 2 near marker D2S1394 was found to be linked to total carbohydrate (LOD = 0.95) and sucrose intake (LOD = 1.60). The consumption of total fat, total saturated fat, and total protein were genetically correlated with each other with pairwise genetic correlation coefficients from 0.78 to 0.90 (data not shown). The results of genome scans of saturated fat intake, total calories, total fat, and total protein on chromosome 2 are given in Figure 1Go. The association between polymorphisms in POMC exon 3 (C->T at position 7284 and C->T at position 7566) and saturated fat intake was not significant (P > 0.05).



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  		FIGURE 1.. The multipoint linkage analysis of dietary macronutrient intakes on chromosome 2.

 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The key finding in this study was that the chromosome 2p22 region near marker D2S1346 might contain genes that influence macronutrient consumption (total calories, total protein, total fat, and saturated and unsaturated fats) in Mexican Americans. To our knowledge, this is one of the 2 genome-wide scans by using dietary intake derived from FFQs. Previously, familial aggregation of nutrient intake was reported in this population (23). However, genome-wide screening was not conducted for the traits. Interestingly, the same genetic marker was identified in multipoint linkage analysis by using serum leptin concentrations and fat mass in this Mexican American population (14). We performed genome-wide scans that incorporated leptin concentrations or fat mass as covariates, and the LOD scores decreased from 2.62 to 1.7 and 1.9, respectively. These results suggested that this chromosomal region might contribute to dietary macronutrient intakes and adiposity phenotypes in Mexican Americans.

Our result on 2p22 replicated those from other studies on obesity-related traits. Suggestive evidence of linkage to 2p22 was previously reported by using traits of a principal component factor of the metabolic syndrome in the HERITAGE Family Study (24), serum triacylglycerol concentrations in Pima Indians (25), diastolic exercise blood pressure (26), and systolic blood pressure in the Genetic Epidemiology Network of Atherosclerosis (27). The same region was found to be linked to physical inactivity in the Quebec Family Study (28), body mass index (29), and leptin concentrations in African Americans (30). A meta-analysis of 4 European genome-wide scans, including Botnia I and II (31), the Warren 2 scan in the United Kingdom, and 143 families from France, suggested 2p22 was significantly associated with type 2 diabetes. Collectively, our study and those previous studies implied that 2p22 might harbor genes influencing macronutrient intake, and the cumulative effects of dietary habits over time predispose an individual to the metabolic syndrome.

Our result is not consistent with that of the other genome scan on dietary intake (32). Collaku et al (32) reported that dietary energy and nutrient intake mapped to chromosome 1p21 and 20q and a QTL on chromosome 12q14 was found to influence fat intake in the whites. In the blacks, chromosome 12q23, 1q32, and 7q11 might affect the variations in macronutrient intakes. However, 2p22 was identified to be liable for dietary energy and macronutrient intake in Mexican Americans in our study. This discordance might be due to differences in ethnic groups, sample size, and analytic methods. The principal genes influencing food intakes in different populations could be different. Also, environment accounted for more than one-half of the variations in dietary intakes in our study. Similar environmental effect was shown in eating patterns of twins (33).

Our study did not replicate the findings of a mouse study on dietary intake by Smith Richards et al (34) by searching the human and mouse homology database (Internet: http://www.nchi.nlm.nih.gov/HomoloGene/). We duplicated neither the QTLs controlling body weight (35) nor percent of body fat, plasma hepatic lipase activity, and cholesterol on mouse chromosome 7 (36). The peak in our linkage signal region corresponds to mouse chromosome 12.

A strong candidate gene contained in the signal region is POMC, which is mainly produced in neuronal cells of the arcuate nucleus in the hypothalamus (37). The posttranslational processing of POMC yields several peptide hormones, including {alpha}-melanocortin stimulating hormone, adrenocorticotropic hormone, and ß-endorphin, all of which are regulators for appetite, obesity, and energy metabolism (37). An early association study in Mexican Americans of the SAFHS indicated that POMC polymorphisms were significantly associated with normal variations in leptin concentrations (17). However, 2 polymorphisms in POMC exon 3 did not show association with dietary saturated fat intakes in this study. In animal studies, homozygous POMC-null mice showed significantly higher body weight than wild-type mice (38). The POMC transgenic mice had reduced levels of hyperphagia induced by fasting, and the POMC transgene in leptin-deficient mice attenuated the severities of obesity and hyperphagia (39). However, in our study no significant association was detected between saturated fat intake and 2 polymorphisms of POMC. Therefore, although there is some evidence to support POMC being a candidate for further study, it is plausible that other novel genes in this region cause the observed peak in the linkage signal region.

This study might be limited by the inaccuracy arising from calculating nutrient consumption from a FFQ. No better way currently exists to estimate food intake in a large population study. Obese patients tend to underreport the amount of food they have consumed. Also, any FFQ, even after modification for the specific study population, does not cover all food items, so participants document consuming only the food listed. In addition, a FFQ administered at one point in time is not able to provide life-long information about the eating pattern for a person who has lived several decades. Therefore, the FFQ is a coarse estimation of food intake, and genome-wide screening by using data derived from a FFQ has a reduced power to detect QTLs that influence nutrient intakes. However, the combination of a large sample size, experienced interviewers, and a FFQ tailored to a population living in one area minimize the effect of these limitations.

In summary, the present study detected significant heritabilities in macronutrient consumption after accounting for shared household environment. Subsequent genome-wide scans showed suggestive linkage of total calories, total fat, total protein, saturated fat, monounsaturated fat, and polyunsaturated fat intakes to chromosome 2p near marker D2S1346. Two polymorphisms of the candidate gene POMC were not found to be associated with saturated fat intake. Combined with previous findings in this region, our study suggested that chromosome 2p22 might contain QTLs related to dietary intake and obesity-related phenotypes.


   ACKNOWLEDGMENTS
 
We thank the participants in the San Antonio Family Heart Study. GC was responsible for the data cleaning, analysis design, data analysis, interpretation of the results, and writing of the manuscript.

SAC provided significant advice and revised the manuscript. RAB-S provided advice and consultation. JWM was the principal investigator in the San Antonio Family Heart Study and provided advice. JB provided significant advice and consulted on the data analysis. AGC was the coleader of this project and provided advice. None of the authors had a financial or personal interest in the sponsorship of this research study.


   REFERENCES
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 ABSTRACT
 INTRODUCTION
 SUBJECTS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication April 8, 2004. Accepted for publication June 25, 2004.




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