Search tips
Search criteria 


Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
Neurogenetics. Author manuscript; available in PMC 2010 July 1.
Published in final edited form as:
PMCID: PMC2753863

Examination of Association of Genes in the Serotonin System to Autism


Autism is characterized as one of the Pervasive Developmental Disorders (PDDs), a spectrum of often severe behavioral and cognitive disturbances of early development. The high heritability of autism has driven multiple efforts to identify genetic variation that increases autism susceptibility. Numerous studies have suggested that variation in peripheral and central metabolism of serotonin (5-HT) may play a role in the pathophysiology of autism. We screened 403 autism families for 45 SNPs in 10 serotonin pathway candidate genes. Although genome-wide linkage scans in autism have provided support for linkage to various loci located within the serotonin pathway, our study does not provide strong evidence for linkage to any specific gene within the pathway. The most significant association (p=0.0002; p=0.02 after correcting for multiple comparisons) was found at rs1150220 (HTR3A) located on Chromosome 11 (~113 Mb). To test specifically for multilocus effects, Multifactor Dimensionality Reduction (MDR) was employed, and a significant 2-way interaction (p-value = 0.01) was found between rs10830962, near MTNR1B (Chromosome11; 92,338,075 bp) and rs1007631, near SLC7A5 (Chromosome16; 86,413,596 bp). These data suggest that variation within genes on the serotonin pathway, particularly HTR3A, may have modest effects on autism risk.

Keywords: Autism, Serotonin, SNPs, linkage, association


Autism is a highly heritable but genetically complex neurodevelopmental disorder with an onset early in childhood. It is characterized by significant disturbances in language and reciprocal social interactions, combined with repetitive and stereotypic behaviors. Autism is not a distinct, categorical disorder but instead represents one extreme of a spectrum of social and communication impairment and behavioral problems, referred to as Autism Spectrum Disorders (ASD). Prevalence estimates for autism have substantially increased in the last decade. The incidence of severe autism is estimated as one in 1,000 individuals, with males affected at a rate four times that of females (1,2). The incidence increases to approximately two to three in 1,000 when the broad diagnosis is considered, including milder forms of ASD (3,2). Evidence from various studies indicates that ASD has a strong but genetically complex etiology, possibly involving epistasis and locus heterogeneity. While rare single mutations or chromosomal abnormalities are likely responsible for some cases, current models strongly suggest that inheritance of multiple interacting polymorphic loci contributes to a continuum of disease phenotypes in the majority of affected children (4,5). Twin and family studies support a multilocus etiology with as many as 5–20 loci being involved in its manifestation. Twin studies show a concordance of 60% among monozygotic (MZ) twins and 0% among dizygotic (DZ) pairs for classic autism, but increases to 92% for MZ and 10% for DZ pairs when the broader phenotype of related social and language abnormalities are included (6,7,8). Interestingly, the milder phenotypes are similarly elevated in other relatives of singleton probands, supporting the hypothesis that autism phenotypes are expressed across a spectrum of severity (9). The recurrence risk for siblings of autistic probands is approximately 3% for classic autism and up to 10% when all disorders within the spectrum are considered. While the observed sibling recurrence risk is low, the relative risk compared to the general population is 50–100 times that in the general population (10,7,8). Heritability is therefore estimated at 90%, which is among the highest for psychiatric disorders.

The high heritability of autism has driven the efforts of numerous groups to search for susceptibility loci using genome-wide linkage screens in multiplex families (11,12,13,14,15,16,17,18), and genome wide association studies (19). Although this genomic approach has yielded multiple suggestive regions, a specific risk locus has yet to be identified. Examination of families with only affected males has been suggested (20,21,22) as a method of looking at a more homogeneous autism subset. In addition to looking at the male-only subset, we have taken the alternative approach of selecting a set of functional candidate genes that enables us to examine each gene in more detail. This approach entails selecting genes based on knowledge of the specific phenotypes and our knowledge of the underlying neurobiology related to those behavioral abnormalities in individuals with autism. The extensive variation in phenotypes and severities within ASD suggests the involvement of multiple predisposing factors, interacting in a complex manner with normal neurodevelopment channels and pathways. The biological evidence supporting the involvement of neurobiological pathways, in particular the serotonin pathway (Figure 1) is compelling.

Figure 1
Serotonin Pathway

The serotonin pathway was first implicated in 1961 when an elevation of whole blood serotonin (5-hydroxytryptamine, 5-HT) levels in patients with autism was reported (23). Since the initial report, a number of replication studies have shown hyperserotonemia in 25% to 50% of patients with autism (24,25). Other studies have shown that more than 99% of whole blood serotonin is contained in platelets (26,27) and that platelet serotonin accounts for the hyperserotonemia found in autism (27). Thus elevated serotonin levels are perhaps the most consistent pathophysiological finding in autism. Furthermore, deficits in the levels of tryptophan (a precursor in 5-HT synthesis) in adults with ASD increase the stereotypic behaviors associated with autism (28) and data from functional imaging studies indicate altered serotonin synthesis rates in children with autism versus non-autistic controls (29). Additional affirmation for the involvement of the serotonin system in autism is the positive response individuals display when treated with selective serotonin reuptake inhibitors (SSRIs) for disruptive and aggressive behavior (30,31,32). Several recent gene association studies have attempted to identify gene variants important for serotonin system function to show that the variant of interest is linked to autism susceptibility. The studies, mostly focused on the serotonin transporter, SLC6A4 (SERT), locus provide marginal evidence that genetic variation can impact the level of expression of the transporter (33), and that multiple and rare allelic variant might increase the risk of susceptibility to autism (34). However, even though variation in SLC6A4 was associated to autism in some studies (35,34) in other studies it showed no evidence for association (summarized in (36)). The results, when viewed collectively, provide solid but inconsistent evidence that dysfunctional serotonin signaling plays an integral role in the development of autistic behaviors.

Materials and Methods


Our analysis was conducted on a dataset consisting of 403 Caucasian American families collected in the Southeast United States by the Center for Human Genetics Research at Vanderbilt University and the Institute for Human Genomics at the University of Miami (Table 1). The dataset is a mixture of multiplex and parent-child trio families with additional unaffected sibs in some cases (Table 1). Probands for the study consisted of individuals between the ages of 3 and 21 years who were clinically diagnosed with autism using Diagnostic and Statistical Manual IV (DSM-IV) criteria. The clinical diagnosis of autism was confirmed based on clinical evaluation using DSM-IV diagnostic criteria supported by the Autism Diagnostic Interview-Revised (ADI-R) and medical records. Exclusion criteria included developmental level below 18 months, severe sensory problems (e.g., visual impairment or hearing loss), significant motor impairments (e.g., failure to sit by 12 months or walk by 24 months), or identified metabolic, genetic, or progressive neurological disorders. Parents/caregivers were informed of the purposes, risks, and benefits of participating in this project and provided informed consent.

Table 1
Dataset Distributions

Molecular Analysis

Genomic DNA was extracted from blood using standard protocols and a commercial system (Puregene; Gentra Systems, Minneapolis, MN). All single nucleotide polymorphisms (SNPs) were identified using the Ensembl (, dbSNP (, and AppliedBiosystems ( databases. Genes were selected based on their involvement in the serotonin pathway, including those that play a critical role in the synthesis and metabolism of serotonin, its transport within and across synapses and genes that affect serotonin receptor function. Multiple SNPs spanning each gene were chosen using a hierarchy of nonsynonymous coding change, minor allele frequency > 0.10, and location within the gene. We calculated the linkage disequilibrium between SNPs in this dataset to assess the coverage of the genes with the goal of capturing most of the common variations (supplementary material). A total of 45 SNPs were genotyped for the 10 genes (Table 2).

Table 2
Tested Genes and Single Nucleotide Polymorphisms (SNPs)

SNPs were genotyped using the ABI 7900 Taqman system (37). Laboratory personnel were blinded to pedigree structure, affection status, and location of quality control samples. Duplicate quality control samples were placed both within and across 384-well plates, and equivalent genotypes were required for all quality control samples to ensure accurate genotyping. Mendelian inconsistencies were identified using PedCheck (38). Suspect genotypes were re-read or retested.

Statistical Analysis

Genotyping efficiency, Hardy-Weinberg Equilibrium and linkage disequilibrium (LD) were checked using Haploview (39) and the genotypes generated in our study. Linkage analysis was conducted using two-point heterogeneity LOD scores (HLOD) calculated using FASTLINK and HOMOG (40). Both recessive and dominant models with disease allele frequencies of 0.01 and 0.001, respectively, were analyzed. This approach is robust for detecting linkage signals when the underlying model is unknown or complex (41). The Pedigree Disequilibrium Test (PDT) assessed family based allelic association and the Genotype-PDT (GenoPDT) tested genotypic association to the risk of autism (42). Taking into account the 4:1 ratio of males to females affected with autism, the HLOD, PDT, and Geno-PDT were also run in a subset of families containing only affected males (male-only, N=303). All statistical results are reported as nominal p-values, except where specified. In the latter case we performed a correction according to the method of Nyholt (43), which corrects for the effective number of independent tests taking the LD between SNPs into account.

Multifactor Dimensionality Reduction (MDR) analysis was used to detect multilocus interactions (44). Since MDR is designed for case-control data, we extracted from any family with a complete parent-child trio (one per family for multiplex families) the genotype of the affected child. We constructed the genotype of the “pseudo” controls using the non-transmitted alleles of the parents (45). We tested for all two-way and three-way interactions. MDR is a model free method of analysis that generates empiric p-values based on randomly permuting the data for all possible combinations, thus correcting for multiple comparisons. MDR has >80% power to detect both main and interactive effects in a dataset of this size, even in the presence of locus or genetic heterogeneity (46).


No lod scores >1.0 were observed in the overall dataset. In the male-only subset, we observed only a single LOD score >1.0 (1.36) for rs34532313 in MTNR1A (chromosome 4) in a dominant model (supplementary material).

We initially tested 75 SNPs in a subset of 241 families. Of these, 26 SNPs generated no lod scores >1.0 or association p-values <0.05 and 4 were later found not to be relevant to the pathway. Thus a total of 30 SNPs were dropped from further consideration. We tested 45 SNPs in 10 different genes in the full dataset of 403 families for association with autism risk. Nominally significant results were obtained for SNPs in five different genes (YWHAZ, MTNR1B, HTR3A, SLC7A5, AANAT) (Table 3). Our most significant p-value was 0.0002 at rs1150220 in HTR3A, a serotonin receptor located on chromosome 11, the only result that survives a Nyholt correction (p=0.022). The odds ratios for the heterozygote and homozygote are 1.46 (1.044, 2.042) and 1.251 (0.539, 2.090) respectively. Examination of the male-only dataset identified additional nominally significant results in MTNR1B (p=0.006), a melatonin receptor on chromosome 11, SLC7A5 (p=0.003) on chromosome 16, and a marginal association for AANAT (p=0.01) on chromosome 17.

Table 3
Pedigree Disequilibrium Test (PDT)

MDR analysis for gene-gene interactions was performed across all 45 SNPs. A modestly significant interaction (p=0.01) between rs10830962, near MTNR1B and rs1007631, near SLC7A5 (Chromosome 16) was observed (Prediction Accuracy = 59.6%) (Table 4).

Table 4
Overall dataset MDR analysis results


Abnormalities in serotonin metabolism are one of the few consistent biological findings observed in autistic individuals. Although genome wide linkage scans and candidate gene studies have implicated various loci in the serotonin pathway, the results have been inconsistent. Our study was designed to test two underlying hypotheses. First, does any prominent candidate gene in the serotonin system display a major locus effect in a previously unexamined dataset? Our data suggests that a single locus effect resides within HTR3A, which provided strong association results with a p-value of 0.0002 (p=0.022 corrected) at rs1150220. This result was not restricted to the male subset. This particular SNP is intronic, and there is no current data to suggest a functional consequence of this variation.

Second, do the serotonin system genes provide interesting multilocus interaction effects? This question is driven, in part, by the possibility of genetic buffering, where the moderate dysfunction of one or more genes (perhaps due to common variation) is compensated by other genes. Should more than one gene have moderately altered function, the entire system may then be perturbed. Our MDR analysis identified a moderate interactive effect between rs10830962 and rs1007631 (p-value of 0.01) in a two-way interaction model in the overall dataset. Neither of these SNPs resides within the coding sequence of a gene, with rs10830962 near MTNR1B and rs1007631 near SLC7A5. There is no obvious biological explanation for this interaction, since the genes are not adjacent in the pathway and there is no evidence of direct biological interaction. However, it is possible that these SNPs, or others in LD with them, may have as yet unknown regulatory functions.

HTR3A is an interesting candidate gene. The product of HTR3A belongs to the ligand-gated ion channel receptor superfamily, it is permeable to Na+, K+ and C2+ ions. HTR3A is composed of four hydrophobic transmembrane segments, a large extracellular domain containing a Cys-Cys loop, a long intracellular segment between the third and the fourth transmembrane regions and an extracellular C-terminus (47). HTR3A is located on chromosome 11q23.1–23.2 and encodes subunit A of the type 3 receptor for serotonin, and functions as a neurotransmitter, a hormone, and a mitogen. This receptor causes fast, depolarizing responses in neurons after activation. It functions to mediate rapid synaptic transmission in the brain (48). At the presynaptic location of the receptor it mediates neurotransmitter release (49). The gene consists of nine exons and spans approximately 15 kb (50). HTR3A contains 9 known coding variations (3 non-synonymous). HTR3A is highly expressed in the central nervous system as well as in the colon, intestine and stomach (51). For HTR3A to have the highest activity it forms heteromeric combinations with HTR3B. However, HTR3A is unusual in that it can form homomeric assemblies with reduced channel activity (52). Alternatively spliced transcript variants encoding different isoforms have also been identified.

The serotonin system has been widely investigated in neuropsychiatric disorders and has been implicated as having a role in learning, mood, thermoregulation, sleep, sexuality, and appetite (53,54,55,56). Variations in HTR3A has specifically been linked to several mental disorders such as bipolar disorder (57,58), harm avoidance in women (59) and schizophrenia (60). Furthermore, HTR3B was associated to depression in a sample of Japanese women with major depression (61). Krzywkowski et al. demonstrated that naturally occurring variation in the receptor created a drastic change in their function and expression (62). Thus, dysfunction of HTR3A resulting in altered neurotransmission within the pathway is a possible source of insight in elucidating the etiology of the disorder.

Even though we captured a significant number of the common variation for these genes, our study is not fully comprehensive. There could be variation in regulatory elements for these genes outside of the coding regions, within the intronic regions not completely covered by our analysis, and even outside the flanking regions selected in our study. There could be an extreme level of locus heterogeneity, which has a significant negative impact on power both for PDT and MDR analyses. Since we only examined common variation, the underlying effects could arise from multiple rare variants in one or more of these genes.

Supplementary Material


We wish to thank both the patients with autism and their family members who agreed to participate in this study, as well as the personnel of the Center for Human Genetics Research at Vanderbilt University and the Miami Institute for Human Genomics at the University of Miami. We would like to thank M.J. Allen for her excellent technical support. This research was supported in part by National Institutes of Health (NIH) program project grant NS026630 (MPV, JLH) and NIH R01 grant MH080647.


1. Fombonne E. The epidemiology of autism: a review. Psychol. Med. 1999;29:769–786. [PubMed]
2. Williams JG, Higgins JP, Brayne CE. Systematic review of prevalence studies of autism spectrum disorders. Arch. Dis. Child. 2006;91:8–15. [PMC free article] [PubMed]
3. Fombonne E. Epidemiological surveys of autism and other pervasive developmental disorders: an update. J. Autism Dev. Disord. 2003;33:365–382. [PubMed]
4. Veenstra-Vanderweele J, Christian SL, Cook EH., Jr Autism as a paradigmatic complex genetic disorder. Annu. Rev. Genomics Hum. Genet. 2004;5:379–405. [PubMed]
5. Veenstra-Vanderweele J, Cook EH., Jr Molecular genetics of autism spectrum disorder. Mol. Psychiatry. 2004;9:819–832. [PubMed]
6. Folstein S, Rutter M. Genetic influences and infantile autism. Nature. 1977;265:726–728. [PubMed]
7. Rutter M, Macdonald H, Le CA, Harrington R, Bolton P, Bailey A. Genetic factors in child psychiatric disorders--II. Empirical findings. J. Child Psychol. Psychiatry. 1990;31:39–83. [PubMed]
8. Rutter M, Bolton P, Harrington R, Le CA, Macdonald H, Simonoff E. Genetic factors in child psychiatric disorders--I. A review of research strategies. J. Child Psychol. Psychiatry. 1990;31:3–37. [PubMed]
9. Piven J. The broad autism phenotype: a complementary strategy for molecular genetic studies of autism. Am. J. Med. Genet. 2001;105:34–35. [PubMed]
10. Pickles A, Bolton P, Macdonald H, Bailey A, Le CA, Sim CH, Rutter M. Latent-class analysis of recurrence risks for complex phenotypes with selection and measurement error: a twin and family history study of autism. Am. J. Hum. Genet. 1995;57:717–726. [PubMed]
11. Barrett S, Beck JC, Bernier R, Bisson E, Braun TA, Casavant TL, Childress D, Folstein SE, Garcia M, Gardiner MB, Gilman S, Haines JL, Hopkins K, Landa R, Meyer NH, Mullane JA, Nishimura DY, Palmer P, Piven J, Purdy J, Santangelo SL, Searby C, Sheffield V, Singleton J, Slager S. An autosomal genomic screen for autism. Collaborative linkage study of autism. Am. J. Med. Genet. 1999;88:609–615. [PubMed]
12. Buxbaum JD, Silverman JM, Smith CJ, Kilifarski M, Reichert J, Hollander E, Lawlor BA, Fitzgerald M, Greenberg DA, Davis KL. Evidence for a susceptibility gene for autism on chromosome 2 and for genetic heterogeneity. Am. J. Hum. Genet. 2001;68:1514–1520. [PubMed]
13. International Molecular Genetic Study Autism Consortium (IMGSAC) A genomewide screen for autism: strong evidence for linkage to chromosomes 2q, 7q, and 16p. Am. J. Hum. Genet. 2001;69:570–581. [PubMed]
14. Liu J, Nyholt DR, Magnussen P, Parano E, Pavone P, Geschwind D, Lord C, Iversen P, Hoh J, Ott J, Gilliam TC. A genomewide screen for autism susceptibility loci. Am. J. Hum. Genet. 2001;69:327–340. [PubMed]
15. Philippe A, Martinez M, Guilloud-Bataille M, Gillberg C, Rastam M, Sponheim E, Coleman M, Zappella M, Aschauer H, Van ML PenetC, Feingold J, Brice A, Leboyer M. Genome-wide scan for autism susceptibility genes. Paris Autism Research International Sibpair Study. Hum. Mol. Genet. 1999;8:805–812. [PubMed]
16. Risch N, Spiker D, Lotspeich L, Nouri N, Hinds D, Hallmayer J, Kalaydjieva L, McCague P, Dimiceli S, Pitts T, Nguyen L, Yang J, Harper C, Thorpe D, Vermeer S, Young H, Hebert J, Lin A, Ferguson J, Chiotti C, Wiese-Slater S, Rogers T, Salmon B, Nicholas P, Petersen PB, Pingree C, McMahon W, Wong DL, Cavalli-Sforza LL, Kraemer HC, Myers RM. A genomic screen of autism: evidence for a multilocus etiology. Am. J. Hum. Genet. 1999;65:493–507. [PubMed]
17. Shao Y, Wolpert CM, Raiford KL, Menold MM, Donnelly SL, Ravan SA, Bass MP, McClain C, von WL, Vance JM, Abramson RH, Wright HH, shley-Koch A, Gilbert JR, DeLong RG, Cuccaro ML, Pericak-Vance MA. Genomic screen and follow-up analysis for autistic disorder. Am. J. Med. Genet. 2002;114:99–105. [PubMed]
18. Szatmari P, Paterson AD, Zwaigenbaum L, Roberts W, Brian J, Liu XQ, Vincent JB, Skaug JL, Thompson AP, Senman L, Feuk L, Qian C, Bryson SE, Jones MB, Marshall CR, Scherer SW, Vieland VJ, Bartlett C, Mangin LV, Goedken R, Segre A, Pericak-Vance MA, Cuccaro ML, Gilbert JR, Wright HH, Abramson RK, Betancur C, Bourgeron T, Gillberg C, Leboyer M, Buxbaum JD, Davis KL, Hollander E, Silverman JM, Hallmayer J, Lotspeich L, Sutcliffe JS, Haines JL, Folstein SE, Piven J, Wassink TH, Sheffield V, Geschwind DH, Bucan M, Brown WT, Cantor RM, Constantino JN, Gilliam TC, Herbert M, Lajonchere C, Ledbetter DH, Lese-Martin C, Miller J, Nelson S, Samango-Sprouse CA, Spence S, State M, Tanzi RE, Coon H, Dawson G, Devlin B, Estes A, Flodman P, Klei L, McMahon WM, Minshew N, Munson J, Korvatska E, Rodier PM, Schellenberg GD, Smith M, Spence MA, Stodgell C, Tepper PG, Wijsman EM, Yu CE, Roge B, Mantoulan C, Wittemeyer K, Poustka A, Felder B, Klauck SM, Schuster C, Poustka F, Bolte S, Feineis-Matthews S, Herbrecht E, Schmotzer G, Tsiantis J, Papanikolaou K, Maestrini E, Bacchelli E, Blasi F, Carone S, Toma C, Van EH, de JM, Kemner C, Koop F, Langemeijer M, Hijimans C, Staal WG, Baird G, Bolton PF, Rutter ML, Weisblatt E, Green J, Aldred C, Wilkinson JA, Pickles A, Le CA, Berney T, McConachie H, Bailey AJ, Francis K, Honeyman G, Hutchinson A, Parr JR, Wallace S, Monaco AP, Barnby G, Kobayashi K, Lamb JA, Sousa I, Sykes N, Cook EH, Guter SJ, Leventhal BL, Salt J, Lord C, Corsello C, Hus V, Weeks DE, Volkmar F, Tauber M, Fombonne E, Shih A. Mapping autism risk loci using genetic linkage and chromosomal rearrangements. Nat. Genet. 2007;39:319–328. [PubMed]
19. Arking DE, Cutler DJ, Brune CW, Teslovich TM, West K, Ikeda M, Rea A, Guy M, Lin S, Cook EH, Chakravarti A. A common genetic variant in the neurexin superfamily member CNTNAP2 increases familial risk of autism. Am. J. Hum. Genet. 2008;82:160–164. [PubMed]
20. Nyholt DR. Genetic case-control association studies--correcting for multiple testing. Hum. Genet. 2001;109:564–567. [PubMed]
21. Stone JL, Merriman B, Cantor RM, Yonan AL, Gilliam TC, Geschwind DH, Nelson SF. Evidence for sex-specific risk alleles in autism spectrum disorder. Am. J. Hum. Genet. 2004;75:1117–1123. [PubMed]
22. Cantor RM, Kono N, Duvall JA, varez-Retuerto A, Stone JL, Alarcon M, Nelson SF, Geschwind DH. Replication of autism linkage: fine-mapping peak at 17q21. Am. J. Hum. Genet. 2005;76:1050–1056. [PubMed]
23. Schain RJ, Freedman DX. Studies on 5-hydroxyindole metabolism in autistic and other mentally retarded children. J. Pediatr. 1961;58:315–320. [PubMed]
24. Anderson GM, Gutknecht L, Cohen DJ, Brailly-Tabard S, Cohen JH, Ferrari P, Roubertoux PL, Tordjman S. Serotonin transporter promoter variants in autism: functional effects and relationship to platelet hyperserotonemia. Mol. Psychiatry. 2002;7:831–836. [PubMed]
25. Cook EH, Leventhal BL. The serotonin system in autism. Curr. Opin. Pediatr. 1996;8:348–354. [PubMed]
26. Anderson GM, Freedman DX, Cohen DJ, Volkmar FR, Hoder EL, McPhedran P, Minderaa RB, Hansen CR, Young JG. Whole blood serotonin in autistic and normal subjects. J. Child Psychol. Psychiatry. 1987;28:885–900. [PubMed]
27. Cook EH, Jr, Leventhal BL, Freedman DX. Free serotonin in plasma: autistic children and their first-degree relatives. Biol. Psychiatry. 1988;24:488–491. [PubMed]
28. McDougle CJ, Naylor ST, Cohen DJ, Aghajanian GK, Heninger GR, Price LH. Effects of tryptophan depletion in drug-free adults with autistic disorder. Arch. Gen. Psychiatry. 1996;53:993–1000. [PubMed]
29. Chugani DC, Muzik O, Behen M, Rothermel R, Janisse JJ, Lee J, Chugani HT. Developmental changes in brain serotonin synthesis capacity in autistic and nonautistic children. Ann. Neurol. 1999;45:287–295. [PubMed]
30. Cook EH, Jr, Leventhal BL, Freedman DX. Serotonin and measured intelligence. J. Autism Dev. Disord. 1988;18:553–559. [PubMed]
31. Hollander E, Phillips A, Chaplin W, Zagursky K, Novotny S, Wasserman S, Iyengar R. A placebo controlled crossover trial of liquid fluoxetine on repetitive behaviors in childhood and adolescent autism. Neuropsychopharmacology. 2005;30:582–589. [PubMed]
32. Hollander E, Soorya L, Wasserman S, Esposito K, Chaplin W, Anagnostou E. Divalproex sodium vs. placebo in the treatment of repetitive behaviours in autism spectrum disorder. Int. J. Neuropsychopharmacol. 2006;9:209–213. [PubMed]
33. Prasad HC, Zhu CB, McCauley JL, Samuvel DJ, Ramamoorthy S, Shelton RC, Hewlett WA, Sutcliffe JS, Blakely RD. Human serotonin transporter variants display altered sensitivity to protein kinase G and p38 mitogen-activated protein kinase. Proc. Natl. Acad. Sci. U. S. A. 2005;102:11545–11550. [PubMed]
34. Sutcliffe JS, Delahanty RJ, Prasad HC, McCauley JL, Han Q, Jiang L, Li C, Folstein SE, Blakely RD. Allelic heterogeneity at the serotonin transporter locus (SLC6A4) confers susceptibility to autism and rigid-compulsive behaviors. Am. J. Hum. Genet. 2005;77:265–279. [PubMed]
35. McCauley JL, Olson LM, Dowd M, Amin T, Steele A, Blakely RD, Folstein SE, Haines JL, Sutcliffe JS. Linkage and association analysis at the serotonin transporter (SLC6A4) locus in a rigid-compulsive subset of autism. Am. J. Med. Genet. B Neuropsychiatr. Genet. 2004;127:104–112. [PubMed]
36. Ramoz N, Reichert JG, Corwin TE, Smith CJ, Silverman JM, Hollander E, Buxbaum JD. Lack of evidence for association of the serotonin transporter gene SLC6A4 with autism. Biol. Psychiatry. 2006;60:186–191. [PubMed]
37. Oliveira SA, Scott WK, Nance MA, Watts RL, Hubble JP, Koller WC, Lyons KE, Pahwa R, Stern MB, Hiner BC, Jankovic J, Ondo WG, Allen FH, Jr, Scott BL, Goetz CG, Small GW, Mastaglia FL, Stajich JM, Zhang F, Booze MW, Reaves JA, Middleton LT, Haines JL, Pericak-Vance MA, Vance JM, Martin ER. Association study of Parkin gene polymorphisms with idiopathic Parkinson disease. Arch. Neurol. 2003;60:975–980. [PubMed]
38. O'Connell JR, Weeks DE. PedCheck: a program for identification of genotype incompatibilities in linkage analysis. Am. J. Hum. Genet. 1998;63:259–266. [PubMed]
39. Barrett JC, Fry B, Maller J, Daly MJ. Haploview: analysis and visualization of LD and haplotype maps. Bioinformatics. 2005;21:263–265. [PubMed]
40. Ott J. Analysis of human Genetic Linkage. 3rd ed. Baltimore: Johns Hopkins University Press;
41. Hodge SE. What association analysis can and cannot tell us about the genetics of complex disease. Am. J. Med. Genet. 1994;54:318–323. [PubMed]
42. Martin ER, Bass MP, Gilbert JR, Pericak-Vance MA, Hauser ER. Genotype-based association test for general pedigrees: the genotype-PDT. Genet. Epidemiol. 2003;25:203–213. [PubMed]
43. Nyholt DR. A simple correction for multiple testing for single-nucleotide polymorphisms in linkage disequilibrium with each other. Am. J. Hum. Genet. 2004;74:765–769. [PubMed]
44. Ritchie MD, Hahn LW, Roodi N, Bailey LR, Dupont WD, Parl FF, Moore JH. Multifactor-dimensionality reduction reveals high-order interactions among estrogen-metabolism genes in sporadic breast cancer. Am. J. Hum. Genet. 2001;69:138–147. [PubMed]
45. Ma DQ, Whitehead PL, Menold MM, Martin ER, shley-Koch AE, Mei H, Ritchie MD, DeLong GR, Abramson RK, Wright HH, Cuccaro ML, Hussman JP, Gilbert JR, Pericak-Vance MA. Identification of significant association and gene-gene interaction of GABA receptor subunit genes in autism. Am. J. Hum. Genet. 2005;77:377–388. [PubMed]
46. Ritchie MD, Edwards TL, Fanelli TJ, Motsinger AA. Genetic heterogeneity is not as threatening as you might think. Genet. Epidemiol. 2007;31:797–800. [PubMed]
47. Reeves DC, Lummis SC. The molecular basis of the structure and function of the 5-HT3 receptor: a model ligand-gated ion channel (review) Mol. Membr. Biol. 2002;19:11–26. [PubMed]
48. Jackson MB, Yakel JL. The 5-HT3 receptor channel. Annu. Rev. Physiol. 1995;57:447–468. [PubMed]
49. Krzywkowski K. Do polymorphisms in the human 5-HT3 genes contribute to pathological phenotypes? Biochem. Soc. Trans. 2006;34:872–876. [PubMed]
50. Bruss M, Eucker T, Gothert M, Bonisch H. Exon-intron organization of the human 5-HT3A receptor gene. Neuropharmacology. 2000;39:308–315. [PubMed]
51. Niesler B, Frank B, Kapeller J, Rappold GA. Cloning, physical mapping and expression analysis of the human 5-HT3 serotonin receptor-like genes HTR3C, HTR3D and HTR3E. Gene. 2003;310:101–111. [PubMed]
52. Morales M, Wang SD. Differential composition of 5-hydroxytryptamine3 receptors synthesized in the rat CNS and peripheral nervous system. J. Neurosci. 2002;22:6732–6741. [PubMed]
53. Alessandro S, Kato M. The serotonin transporter gene and effectiveness of SSRIs. Expert. Rev. Neurother. 2008;8:111–120. [PubMed]
54. Merens W, Willem Van der Does AJ, Spinhoven P. The effects of serotonin manipulations on emotional information processing and mood. J. Affect. Disord. 2007;103:43–62. [PubMed]
55. Sanger DJ, Soubrane C, Scatton B. New perspectives for the treatment of disorders of sleep and arousal. Ann. Pharm. Fr. 2007;65:268–274. [PubMed]
56. Steffen KJ, Roerig JL, Mitchell JE, Uppala S. Emerging drugs for eating disorder treatment. Expert. Opin. Emerg. Drugs. 2006;11:315–336. [PubMed]
57. Niesler B, Weiss B, Fischer C, Nothen MM, Propping P, Bondy B, Rietschel M, Maier W, Albus M, Franzek E, Rappold GA. Serotonin receptor gene HTR3A variants in schizophrenic and bipolar affective patients. Pharmacogenetics. 2001;11:21–27. [PubMed]
58. Niesler B, Kapeller J, Hammer C, Rappold G. Serotonin type 3 receptor genes: HTR3A, B, C, D, E. Pharmacogenomics. 2008;9:501–504. [PubMed]
59. Melke J, Westberg L, Nilsson S, Landen M, Soderstrom H, Baghaei F, Rosmond R, Holm G, Bjorntorp P, Nilsson LG, Adolfsson R, Eriksson E. A polymorphism in the serotonin receptor 3A (HTR3A) gene and its association with harm avoidance in women. Arch. Gen. Psychiatry. 2003;60:1017–1023. [PubMed]
60. Ji X, Takahashi N, Saito S, Ishihara R, Maeno N, Inada T, Ozaki N. Relationship between three serotonin receptor subtypes (HTR3A, HTR2A and HTR4) and treatment-resistant schizophrenia in the Japanese population. Neurosci. Lett. 2008;435:95–98. [PubMed]
61. Yamada K, Hattori E, Iwayama Y, Ohnishi T, Ohba H, Toyota T, Takao H, Minabe Y, Nakatani N, Higuchi T, tera-Wadleigh SD, Yoshikawa T. Distinguishable haplotype blocks in the HTR3A and HTR3B region in the Japanese reveal evidence of association of HTR3B with female major depression. Biol. Psychiatry. 2006;60:192–201. [PubMed]
62. Krzywkowski K, Jensen AA, Connolly CN, Brauner-Osborne H. Naturally occurring variations in the human 5-HT3A gene profoundly impact 5-HT3 receptor function and expression. Pharmacogenet. Genomics. 2007;17:255–266. [PubMed]