Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2013 May 1.
Published in final edited form as: Int J Eat Disord. 2012 Jan 24;45(4):556–561. doi: 10.1002/eat.22001

Examining Associations between Disordered Eating and Serotonin Transporter Gene Polymorphisms

Melissa A Munn-Chernoff 1,2,5, Matthew B McQueen 2,3, Gary L Stetler 2, Brett C Haberstick 2, Soo Hyun Rhee 1,2, Laura E Sobik 4, Robin P Corley 2, Andrew Smolen 2, John K Hewitt 1,2, Michael C Stallings 1,2
PMCID: PMC3323686  NIHMSID: NIHMS348763  PMID: 22271047

Abstract

Objective

The serotonin system has been implicated in mood and appetite regulation, and the serotonin transporter gene (SLC6A4) is a commonly studied candidate gene for eating pathology. However, most studies have focused on a single polymorphism (5-HTTLPR) in SLC6A4; little research has utilized multiple single nucleotide polymorphisms (SNPs) to investigate associations between SLC6A4 and eating pathology more comprehensively.

Method

Family-based association tests were conducted for seven polymorphisms in or near SLC6A4, using families from the Colorado Center for Antisocial Drug Dependence. Data were available for 135 families, with phenotypic data available for female twins and female nontwin siblings. Seven items assessed two disordered eating characteristics: weight and shape concerns and behaviors (WSCB) and binge eating (BE).

Results

No significant associations were found between any genetic variant and the two disordered eating characteristics.

Discussion

This study suggests that utilizing polymorphisms in and near SLC6A4, including 5-HTTLPR, may not be useful in identifying genetic risk factors for disordered eating.

Keywords: eating disorders, disordered eating, serotonin transporter, family-based association, 5-HTTLPR, SNPs

Introduction

Twin studies have indicated moderate genetic influences on eating pathology, including clinical eating disorders1,2 and disordered eating characteristics (e.g., body dissatisfaction and binge eating)1,3, yet specific genetic variants contributing to these disorders and behaviors have not been clearly identified. Of interest in the eating disorder literature are genes in the serotonin system, as serotonin is known to be involved in mood and appetite regulation4. One putative gene in this system influencing eating disorders is the serotonin transporter gene (SLC6A4) since it regulates serotonin reuptake from the synaptic cleft. However, an important limitation of the literature investigating associations between SLC6A4 variants and eating disorders is that most studies have only investigated a single polymorphism within SLC6A4, the 43 base pair insertion/deletion polymorphism in the promoter region (5-HTTLPR) 5.

Variations in 5-HTTLPR have been shown to regulate basal transcription rates5 and are typically characterized as consisting of a short-allele, which leads to reduced transcriptional efficiency compared with the long-allele6. Although there have been inconsistent single study findings for both eating disorders, two recent meta-analyses7,8 showed that having at least one 5-HTTLPR short-allele increased the risk for anorexia nervosa but not bulimia nervosa. In addition, few studies have examined 5-HTTLPR with disordered eating9–11, despite evidence to suggest that it precedes the development of clinical eating disorders12. Thus, even though accumulating research suggests that 5-HTTLPR influences the risk for AN, it is not yet clear whether it increases the risk for BN or disordered eating.

Furthermore, although other genetic variants have been identified in this gene, few studies have explored their association with eating disorders. Earlier work investigated both a variable number tandem repeat polymorphism and 5-HTTLPR13,14, whereas more recent studies utilized single nucleotide polymorphisms (SNPs) to detect associations between SLC6A4 genetic variants and eating pathology. In the latter studies, no significant associations were found between SLC6A4 SNPs and anorexia nervosa or between these SNPs and anorexia nervosa subtypes15,16. Still, it is unknown if particular features commonly seen in women with anorexia and bulimia nervosa (e.g., weight concerns and binge eating) are associated with SLC6A4 variants.

We tested the feasibility of using a gene-based approach to investigate associations between multiple SLC6A4 polymorphisms and two disordered eating characteristics17. The use of multiple polymorphisms allows for a more comprehensive evaluation of the role of genetic variation in SLC6A4 and eating pathology. Moreover, the use of disordered eating characteristics rather than clinical eating disorders could provide valuable insight into risk factors for more general eating attitudes and behaviors.

Materials and Methods

Participants

Participants were adolescent and young adult female twins and female nontwin siblings (mean age: 17.30 ± 1.25 years; range: 16.00–21.00), as well as their male siblings and parents from the Colorado Center for Antisocial Drug Dependence (CADD)18. This is a population-based community sample that assesses substance use, personality traits, and psychopathology from families whose twins were born in the state of Colorado18. The CADD twin sample was drawn from two studies- the Colorado Community Twin Study (CTS) and the Longitudinal Twin Study (LTS)18. For CTS families, twins were recruited by birth records obtained from the Colorado Department of Heath, Division of Vital Statistics or through primary and secondary schools beginning in 1983. Twins born from 1986 onwards were invited to participate in the CTS and willing participants born between 1980 and 1990 were included in the CADD study. Families from the LTS were recruited only from the Colorado Department of Health, Division of Vital Statistics, only from the greater Denver metropolitan area, and only from families whose twins had healthy birth weights and gestational ages born between 1984 and 1990. The CADD sample was comparable with the larger sample of twin families from which it was drawn18.

Overall, 135 families (465 individuals) from our previous biometrical twin analyses17 were included in the current study. The number of families included in the analyses was smaller than the 838 families from our previous study because we wanted to include only those families that could potentially be informative for the within-family association test between disordered eating characteristics and genetic variants. Thus, families were excluded if: 1) no genotyping was completed for an entire family; 2) only one member of the family had genotypic information (since there must be at least two family members for a within-family association test); 3) genotypic information was only available for 5-HTTLPR (since we were particularly interested in SLC6A4 SNPs, we wanted to make sure the families also had SNP information); and 4) monozygotic (MZ) twins had to have a nontwin sibling with genotype information (because MZ twin pairs alone are not informative for within-family testing). The final sample consisted of 43 MZ, 61 dizygotic, and 31 opposite-sex twin pairs.

The number of family members ranged from two to five and could include one or both twins, a full nontwin sibling (male or female), and the biological parents. Notably, phenotypic data were only available for female offspring, whereas genotypic data were available for male and female offspring and biological parents. The self-reported ethnicity composition of the sample was as follows: 88.6% White, 5.1% more than one race, 1.2% American Indian, 0.8% Asian, 0.8% Native Hawaiian, 0.8% Black, and 2.7% unknown. Study protocol was approved by the University of Colorado's Institutional Review Board. Participants 18 years old or older gave informed consent to participate; participants under age 18 gave assent. Parents also provided informed consent for participants under age 18.

Assessment

A seven-item eating pathology screening tool19,20 assessed eating attitudes and behaviors. Phenotypic exploratory and confirmatory factor analyses revealed two disordered eating characteristics: weight and shape concerns and behaviors (WSCB; which assessed feeling fat, thinking about staying thin, eating less than usual when upset, and self-induced vomiting) and binge eating (BE; which assessed eating in secret, finding it hard to stop eating, and eating more than usual when upset)17. The two disordered eating characteristics were scored from 0 to 3+, reflecting the number of items endorsed on each factor (note: WSCB had a possible range from 0 – 4 but was truncated at 3+ to create a four-category ordinal scale for both WSCB and BE)17. Biometrical model-fitting showed that these characteristics were moderately heritable (h2 = 0.43 [95% confidence interval: 0.33–0.52] for WSCB and 0.49 [0.36–0.58] for BE)17. In the current study, 52.0% of the participants with available phenotypic data (i.e., female offspring) endorsed at least one WSCB item and 30.6% endorsed at least one BE item; the nonparametric phenotypic correlation between WSCB and BE was significant (r = 0.26, p < 0.001).

In addition, we conducted an independent study to assess the validity of the seven-item eating pathology screening tool by comparing it to a widely used disordered eating measure- the Eating Disorder Examination Questionnaire (EDE-Q21). Results from 133 female undergraduate students (mean age: 18.91 ± 1.26; range: 18.00 – 26.00) suggested that the correlation between a total score of the seven-item assessment and the EDE-Q Global Score was 0.63 (p < 0.05). Furthermore, using an EDE-Q clinical cut-off score of four21, the mean total score of the seven-item assessment was higher in individuals who met the clinical cut-off score (n = 17; mean = 5.06 ± 1.20) compared with females who did not meet the clinical cut-off score (n = 116; mean = 3.18 ± 1.60). Thus, this seven-item eating pathology screening tool provides useful information to detect disordered eating in young adult females.

Zygosity and Genotyping

Zygosity information was obtained using a combination of physical similarity ratings and genotyping. Zygosity was initially assigned using a modified version of the Nichols and Bilbro questionnaire22. For most participants, zygosity was subsequently confirmed using a minimum of 11 highly informative short tandem repeat polymorphisms. Any discrepancies between similarity ratings and genotyping were resolved18.

DNA samples were obtained via cheek swab buccal cell collection. For both CTS and LTS families, 5-HTTLPR was genotyped according to modified protocols23,24. The recently identified SNP (rs25531) in the 5-HTTLPR long-allele was not examined in this sample because genotypic information was not available. All SNPs in CTS families were genotyped using a 32-SNP, ABI Taqman® OpenArray® (Carlsbad, CA). All SNPs in LTS families were genotyped with the Illumina® (San Diego, CA) GoldenGate 96-SNP assay25 using their BeadXpress™ system. SLC6A4 SNP selection was based on the following criteria: 1) coverage of the gene from the region upstream of 5-HTTLPR to the 3' UTR (47 kilobases); 2) an acceptable Golden Gate assay25 design score; 3) a minor allele frequency of at least 0.10; 4) HapMap26 validation; and 5) if possible, a reported association with a behavioral phenotype. Genotype frequencies for the seven polymorphisms in parents and offspring are presented in Table 1.

TABLE 1.

Genotype frequencies

Genotype Frequency
Polymorphism Genotype Parents* (n = 137) Offspring* (n = 285) Total* (n = 422)
rs12945042 AA 20 31 51
AG 53 107 160
GG 55 117 172
5-HTTLPR LL 27 64 91
SL 48 92 140
SS 15 32 47
rs6354 AA 66 159 225
AC 27 67 94
CC 0 4 4
rs2020942 AA 26 40 66
AG 50 112 162
GG 43 101 144
rs140700 AA 2 3 5
AG 21 45 66
GG 102 204 306
rs2054847 AA 24 48 72
AG 50 129 179
GG 51 82 133
rs1042173 AA 45 62 107
AC 47 130 177
CC 31 54 85
Open in a new tab

Note:

*

The maximum number of individuals for whom genotypic data could be available. Only one member of a MZ twin pair was included in the genotype frequencies.

Although our 32-SNP assay (for CTS) and 96-SNP assay (for LTS) included variants in other loci, we examined only SLC6A4 variants for three reasons. First, the SNP panel was not designed for eating pathology research, so we focused on polymorphisms related to SLC6A4 given prior interest in 5-HTTLPR. We wanted to expand on this body of literature by examining other polymorphisms in SLC6A4. Second, our inclusion of 5-HTTLPR and other genetic variants using a family-based design provides additional within-family information to the SLC6A4 and eating pathology literature. Finally, the number of families included in this study is small. Examining associations between the disordered eating characteristics and genetic variants in other loci would have reduced our statistical power.

Statistical Analyses

Haploview27 was utilized to determine linkage disequilibrium (LD) patterns among the genetic variants. Hardy-Weinberg Equilibrium (HWE) was calculated using Merlin28. Because our sample population was a relatively small subset of the total CADD sample, HWE calculations were based on the founders of the full sample, who were also genotyped for these SNPs (n = 222) and for 5-HTTLPR (n = 499)1. Family-based association tests operationalized in FBAT29 were then used to conduct all association analyses. FBAT is an extension of the Transmission Disequilibrium Test that utilizes both within- and between-family information29. Because MZ twin pairs share 100% of their genetic make-up and are not informative for within-family testing (although they are informative for between-family testing), one MZ twin was randomly selected from each MZ twin pair to be included in the analyses. FBAT accommodates ordinal data that are not normally distributed29.

We examined associations between each polymorphism and the two phenotypes (i.e., WSCB and BE) independently. An additive mode of inheritance was assumed throughout all models, and the offset value was allowed to be freely estimated in order to minimize the variance of the test statistic30. As specified by FBAT29, the default number of informative families (at least 10 for a given analysis) was utilized. An initial p-value of 0.05 was used to determine statistical significance. However, in order to correct for multiple testing (seven polymorphisms times two phenotypes equals 14 tests; see Results section), we used the Bonferroni correction31, where the corrected critical p-value was 0.004.

Results

Figure 1 shows the location of the six SNPs in and near SLC6A4 included in this study, as well as 5-HTTLPR (and rs25531 that lies within 5-HTTLPR). None of the seven polymorphisms showed Mendelian errors or were in Hardy Weinberg Disequilibrium. Minor allele frequencies for the genetic variants ranged from 0.09 (rs140700) to 0.48 (rs1042173) (Table 2).

FIGURE 1.

FIGURE 1

Open in a new tab

Serotonin transporter gene (SLC6A4) polymorphism information. The serotonin transporter gene is typically read from the 3-prime to 5-prime end. However, the expanded portion of the figure has been inverted for ease of interpretation. The marker position is located under the polymorphism and was obtained from HapMap.

TABLE 2.

Descriptive SLC6A4 polymorphism information and results for association analyses

WSCB BE
SNP Allele MA (Freq) #Fam p RA #Fam p RA
rs12945042 A/G A (0.34) 63 0.14 A 60 0.18 A
5-HTTLPR S/L S (0.46) 40 0.64 S 38 0.66 L
rs6354 A/C C (0.14) 42 0.31 C 39 0.45 C
rs2020942 A/G A (0.39) 57 0.80 A 58 0.40 A
rs140700 A/G A (0.09) 32 1.00 A 30 0.58 A
rs2054847 A/G A (0.44) 63 0.94 A 62 0.86 G
rs1042173 A/C C (0.48) 57 0.93 C 58 0.32 A
Open in a new tab

Note: WSCB = weight and shape concerns and behaviors; BE = binge eating; SNP = single nucleotide polymorphism; MA = minor allele; Freq = frequency; #Fam = number of informative families; RA = risk allele. The p-values presented in the table are before applying Bonferroni correction (p = 0.004).

The r2 values were generally low (i.e., ≤ 0.48), suggesting that the information these SNPs provided were relatively independent. One exception was the r2 value of 0.82 between rs1042173 and rs2054847, indicating that these two SNPs were associated with each other. Figures of the LD patterns are provided in Figure 2.

FIGURE 2.

FIGURE 2

Open in a new tab

D' (left) and R2 (right) values for polymorphisms in and near SLC6A4.

Association results for WSCB and BE are presented in Table 2. When testing for an association between each of the seven polymorphisms and WSCB, no genetic variants were significant even before correcting for multiple testing (all p-values > 0.05). Similarly, no associations between SNPs in or near SLC6A4 and BE were detected (all p-values > 0.05). These data suggest that genetic variants in and near SLC6A4 are not associated with weight and shape concerns/behaviors or binge eating.

Discussion

This study sought to determine the feasibility of utilizing a gene-based approach to examine the association between multiple polymorphisms in and near SLC6A4 and disordered eating. We did not find significant associations between SLC6A4 polymorphisms and weight and shape concerns and behaviors (WSCB) or between these same variants and binge eating (BE). Despite recent meta-analyses7,8 suggesting that the 5-HTTLPR short-allele is significantly associated with anorexia nervosa, we found no allele to be associated with eating disorder symptoms. This finding is similar to prior research9,10 that reported no main effects for binge eating or drive for thinness with 5-HTTLPR alleles. It is possible that including polymorphisms from other loci and exploring epistasis would yield significant findings, as has been shown between 5-HTTLPR and MAO genotypes with eating disorders and their symptoms10,32. However, our sample size was too small to perform these analyses. Even though our findings were not significant, it is interesting that the 5-HTTLPR risk allele for WSCB was the short-allele and for BE it was the long-allele. Prior studies reported that the long-allele was associated with abnormal eating behaviors in a Japanese sample of women11 and in Caucasian women with binge eating disorder33. More studies are clearly needed to determine if there is a differential risk allele for specific disordered eating characteristics.

With respect to SLC6A4 SNPs, our findings corroborate prior studies that did not find significant associations with anorexia nervosa and anorexia nervosa subtypes15,16. Of particular interest is the fact that three of our SNPs- rs6354, rs140700, and rs1042173-overlapped with genetic variants included in the study by Pinheiro et al16 (C. M. Bulik and L. M. Thornton, personal communication, March 25, 2011). Furthermore, two genome-wide association studies did not detect significant associations between anorexia nervosa and SLC6A4 SNPs34,35. Thus, SLC6A4 SNPs may not represent genetic risk factors for eating pathology.

In conclusion, we did not find significant associations between disordered eating and polymorphisms in and near SLC6A4. The lack of significant findings could be due to the small sample size, the age of our sample (given that individuals may not be past the risk period for eating disorder symptoms), or the use of disordered eating symptoms rather than clinical diagnoses (we do not have clinical diagnoses of eating disorders in our twin samples). It will be important for future research to include multiple polymorphisms in many loci, including other neurotransmitter systems, in order to fully understand the role of genes on eating related behaviors.

Acknowledgements

This work was supported by grants from the National Institute of Drug Abuse (DA011015, DA012485) and the National Institute of Child Health and Human Development (HD010333). This research and a portion of the manuscript preparation were also supported on training grant T32 MH016880, and a portion of the manuscript preparation was supported by training grants T32 HD007289 and F31 MH084466, all to M.A. Munn. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

The authors would like to thank Ms. Sally Ann Rhea and Dr. Kelly L. Klump for their careful review of the manuscript, Drs. Carol A. Beresford and Thomas P. Beresford for their thoughts on the disordered eating measurement, Dr. R. Jay Schulz-Heik for his help with the validity of the disordered eating measurement, and the families and staff members for their continued support of this project.

Footnotes

Biomedical and Commercial Financial Support and Conflicts of Interest The authors do not declare any biomedical and commercial financial support or potential conflicts of interest.

1

Parental genotypes for CTS families were not available. Thus, HWE was calculated only on LTS founders. However, we also examined HWE in Haploview using both offspring and parents from the 135 families. These results were not different from HWE in founders only (which are reported in the text).

References

  • 1.Bulik CM, Sullivan PF, Kendler KS. Heritability of binge-eating and broadly defined bulimia nervosa. Biol Psychiatry. 1998;44:1210–1218. doi: 10.1016/s0006-3223(98)00280-7. [DOI] [PubMed] [Google Scholar]
  • 2.Bulik CM, Sullivan PF, Tozzi F, Furberg H, Lichtenstein P, Pedersen NL. Prevalence, heritability, and prospective risk factors for anorexia nervosa. Arch Gen Psychiatry. 2006;63:305–312. doi: 10.1001/archpsyc.63.3.305. [DOI] [PubMed] [Google Scholar]
  • 3.Klump KL, Burt SA, McGue M, Iacono WG. Changes in genetic and environmental influences on disordered eating across adolescence: A longitudinal twin study. Arch Gen Psychiatry. 2007;64:1409–1415. doi: 10.1001/archpsyc.64.12.1409. [DOI] [PubMed] [Google Scholar]
  • 4.Lucki I. The spectrum of behaviors influenced by serotonin. Biol Psychiatry. 1998;44:151–162. doi: 10.1016/s0006-3223(98)00139-5. [DOI] [PubMed] [Google Scholar]
  • 5.Heils A, Teufel A, Petri S, Stöber G, Riederer P, Bengel D, et al. Allelic variation of human serotonin transporter gene expression. J Neurochem. 1996;66:2621–2624. doi: 10.1046/j.1471-4159.1996.66062621.x. [DOI] [PubMed] [Google Scholar]
  • 6.Lesch KP, Bengel D, Heils A, Sabol SZ, Greenberg BD, Petri S, et al. Association of anxiety-related traits with a polymorphism in the serotonin transporter gene regulatory region. Science. 1996;274:1527–1531. doi: 10.1126/science.274.5292.1527. [DOI] [PubMed] [Google Scholar]
  • 7.Calati R, De Ronchi D, Bellini M, Serretti A. The 5-HTTLPR polymorphism and eating disorders: A meta-analysis. Int J Eat Disord. 2011;44:191–199. doi: 10.1002/eat.20811. [DOI] [PubMed] [Google Scholar]
  • 8.Lee Y, Lin PY. Association between serotonin transporter gene polymorphism and eating disorders: A meta-analytic study. Int J Eat Disord. 2010;43:498–504. doi: 10.1002/eat.20732. [DOI] [PubMed] [Google Scholar]
  • 9.Akkermann K, Nordquist N, Oreland L, Harro J. Serotonin transporter gene promoter polymorphism affects the severity of binge eating in general population. Prog Neuropsychopharmacol Biol Psychiatry. 2010;34:111–114. doi: 10.1016/j.pnpbp.2009.10.008. [DOI] [PubMed] [Google Scholar]
  • 10.Akkermann K, Paaver M, Nordquist N, Oreland L, Harro J. Association of 5-HTT gene polymorphism, platelet MAO activity, and drive for thinness in a population-based sample of adolescent girls. Int J Eat Disord. 2008;41:399–404. doi: 10.1002/eat.20516. [DOI] [PubMed] [Google Scholar]
  • 11.Matsushita S, Nakamura T, Nishiguchi N, Higuchi S. Association of serotonin transporter regulatory region polymorphism and abnormal eating behaviors. Mol Psychiatry. 2002;7:538–540. doi: 10.1038/sj.mp.4001028. [DOI] [PubMed] [Google Scholar]
  • 12.Striegel-Moore RH, Siberstein LR, Rodin J. Toward an understanding of risk factors for bulimia. Am Psychol. 1986;41:246–263. doi: 10.1037//0003-066x.41.3.246. [DOI] [PubMed] [Google Scholar]
  • 13.Lauzurica N, Hurtado A, Escartí A, Delgado M, Barios V, Morandé, et al. Polymorphisms within the promoter and the intron 2 of the serotonin transporter gene in a population of bulimic patients. Neurosci Lett. 2003;352:226–230. doi: 10.1016/j.neulet.2003.08.058. [DOI] [PubMed] [Google Scholar]
  • 14.Martásková D, Šlachtová L, Kemlink D, Záhoráková D, Papežová H. Polymorphisms in serotonin-related genes in anorexia nervosa. The first study in Czech population and meta-analyses with previously performed studies. Folia Biologica (Praha) 2009;55:192–197. doi: 10.14712/fb2009055050192. [DOI] [PubMed] [Google Scholar]
  • 15.Kiezebrink K, Mann ET, Bujac SR, Stubbins MJ, Campbell DA, Blundell JE. Evidence of complex involvement of serotonergic genes with restrictive and binge purge subtypes of anorexia nervosa. World J Biol Psychiatry. 2010;11:824–833. doi: 10.3109/15622975.2010.484550. [DOI] [PubMed] [Google Scholar]
  • 16.Pinheiro AP, Bulik CM, Thornton LM, Sullivan PF, Root TL, Bloss CS, et al. Association study of 182 candidate genes in anorexia nervosa. Am J Med Genet B Neuropsychiatr Genet. 2010;153B:1070–1080. doi: 10.1002/ajmg.b.31082. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17.Munn MA, Stallings MC, Rhee SH, Sobik LE, Corley RP, Rhea SA, et al. Bivariate analysis of disordered eating characteristics in adolescence and young adulthood. Int J Eat Disord. 2010;43:751–761. doi: 10.1002/eat.20854. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18.Rhea SA, Gross AA, Haberstick BC, Corley RP. Colorado twin registry. Twin Res Hum Genet. 2006;9:941–949. doi: 10.1375/183242706779462895. [DOI] [PubMed] [Google Scholar]
  • 19.Freund KM, Graham SM, Lesky LG, Moskowitz MA. Detection of bulimia in a primary care setting. J Gen Intern Med. 1993;8:236–242. doi: 10.1007/BF02600088. [DOI] [PubMed] [Google Scholar]
  • 20.Vandereycken W. Validity and reliability of the Anorectic Behavior Observation Scale for parents. Acta Psychiatr Scand. 1992;85:163–166. doi: 10.1111/j.1600-0447.1992.tb01462.x. [DOI] [PubMed] [Google Scholar]
  • 21.Fairburn CG, Beglin SJ. Assessment of eating disorders: Interview or self-report questionnaire? Int J Eat Disord. 1994;16:363–370. [PubMed] [Google Scholar]
  • 22.Nichols RC, Bilbro WC., Jr The diagnosis of twin zygosity. Acta Genet Stat Med. 1996;16:265–275. doi: 10.1159/000151973. [DOI] [PubMed] [Google Scholar]
  • 23.Gelernter J, Cubells JF, Kidd JR, Pakstis AJ, Kidd KK. Population studies of polymorphisms of the serotonin transporter protein gene. Am J Med Genet. 1999;88:61–66. [PubMed] [Google Scholar]
  • 24.Anchordoquy HC, McGeary C, Liu L, Krauter KS, Smolen A. Genotyping of three candidate genes after whole-genome preamplification of DNA collected from buccal cells. Behav Genet. 2003;33:73–78. doi: 10.1023/a:1021007701808. [DOI] [PubMed] [Google Scholar]
  • 25.Fann JB, Oliphant A, Shen R, Kermani BG, Garcia F, Gunderson KL, et al. Highly parallel SNP genotyping. Cold Spring Harb Symp Quant Biol. 2003;68:69–78. doi: 10.1101/sqb.2003.68.69. [DOI] [PubMed] [Google Scholar]
  • 26.International HapMap Consortium A haplotype map of the human genome. Nature. 2005;437:1299–1320. doi: 10.1038/nature04226. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Barrett JC, Fry B, Maller J, Daly MJ. Haploview: Analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265. doi: 10.1093/bioinformatics/bth457. [DOI] [PubMed] [Google Scholar]
  • 28.Abecasis GR, Cherny SS, Cookson WO, Cardon LR. Merlin-rapid analysis of dense genetic maps using sparse gene flow trees. Nat Genet. 2002;30:97–101. doi: 10.1038/ng786. [DOI] [PubMed] [Google Scholar]
  • 29.Rabinowitz D, Laird N. A unified approach to adjusting association tests for population admixture with arbitrary pedigree structure and arbitrary missing marker information. Hum Hered. 2000;504:227–233. doi: 10.1159/000022918. [DOI] [PubMed] [Google Scholar]
  • 30.Lunetta KL, Farone SV, Biederman J, Laird NM. Family based tests of association and linkage using unaffected sibs, covariates and interactions. Am J Hum Gen. 2000;66:605–614. doi: 10.1086/302782. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 31.Bonferroni CE. Teoria statistica delle classi e calcolo delle probabilitá. Pubblicazioni del R Istituto Superiore di Scienze Economiche e Commerciali di Firenze. 1936;8:3–62. [Google Scholar]
  • 32.Urwin RE, Nunn KP. Epistatic interaction between the monoamine oxidase A and serotonin transporter genes in anorexia nervosa. Eur J Hum Genet. 2005;13:370–375. doi: 10.1038/sj.ejhg.5201328. [DOI] [PubMed] [Google Scholar]
  • 33.Monteleone P, Tortorella A, Castaldo E, Maj M. Association of a functional serotonin transporter gene polymorphism with binge eating disorder. Am J Med Genet B Neuropsychiatr Genet. 2006;141B:7–9. doi: 10.1002/ajmg.b.30232. [DOI] [PubMed] [Google Scholar]
  • 34.Nakabayashi K, Komaki G, Tajima A, Ando T, Ishikawa M, Nomoto J, et al. Identification of novel candidate loci for anorexia nervosa at 1q41 and 11q22 in Japanese by a genome-wide association analysis with microsatellite markers. J Hum Genet. 2009;54:531–537. doi: 10.1038/jhg.2009.74. [DOI] [PubMed] [Google Scholar]
  • 35.Wang K, Zhang H, Bloss CS, Duvvuri V, Kaye W, Schork NJ, et al. A genome-wide association study on common SNPs and rare CNVs in anorexia nervosa. Mol Psychiatry. doi: 10.1038/mp.2010.107. in press. [DOI] [PubMed] [Google Scholar]

RESOURCES