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Human Molecular Genetics Advance Access originally published online on February 27, 2006
Human Molecular Genetics 2006 15(7):1237-1243; doi:10.1093/hmg/ddl039
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© The Author 2006. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oxfordjournals.org

Positive association between POU1F1 and mental retardation in young females in the Chinese Han population

Yun Sun1,2,{dagger}, Fuchang Zhang3,{dagger}, Jianjun Gao2, Xiaocai Gao3, Tingwei Guo1,2, Kejin Zhang3, Yongyong Shi2, Zijian Zheng3, Wei Tang2, Yonglan Zheng1,2, Sheng Li1, Xingwang Li2, Guoyin Feng4, Xiaoming Shen5,* and Lin He2,6,*

1Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 294 Taiyuan Road, Shanghai 200031, China, 2Bio-X Life Science Research Center, Shanghai Jiao Tong University, Hao Ran Building, 1954 Hua Shan Road, Shanghai 200030, China, 3Institute of Population and Health, Northwest University, Xi'an 710069, China, 4Shanghai Institute of Mental Health, 600 South Wan Ping Road, Shanghai 200030, China, 5Shanghai Key Lab of Children's Environmental Sciences, Xin Hua Hospital, Shanghai Jiao Tong University School of Medicine, 1665 Kong Jiang Road, Shanghai 200092, China and 6Institute for Nutritional Sciences, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, 319 Yue Yang Road, Shanghai 200031, China

* To whom correspondence should be addressed. Tel: +86 2162822491; Fax: +86 2162822491; Email: helin{at}nhgg.org (L. He) or Tel: +86 2163858528; Email: xmshen{at}shsmu.edu.cn (X. Shen)

Received December 12, 2005; Accepted February 21, 2006


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Genetic defects attributable to the genes involved in the hypothalamus–pituitary–thyroid (HPT) gland axis can cause abnormal thyroid hormone function and mental retardation (MR). Pit-1, encoded by the POU1F1 gene on human chromosome 3p11, is a pituitary-specific transcription factor responsible for the expression of several pituitary hormones. Thyrotropin is one of these hormones and is an important regulator in the HPT axis. One of the symptoms of patients with POU1F1 mutations is hypothyroidism and abnormalities of the nervous system early in the period after birth. We performed a case–control association study and a quantitative analysis of IQ to investigate the possible genetic contribution of POU1F1 in the Chinese Han population. Pairwise linkage disequilibrium (LD) analysis showed that rs300996, snp-7057 and rs300977 were in strong LD. There were significant differences of allele, genotype and haplotype frequencies of these three single nucleotide polymorphisms (SNPs) between cases and controls. When we conducted a breakdown comparison between cases and controls within different gender groups, no positive results in males were found. In females, however, we found significant differences between cases and controls in allele frequency distribution of rs300996 (P=0.0003), snp-7057 (P=0.0001) and rs300977 (P=0.0005) and in the distributions of common haplotypes combined by these SNPs (global P=0.0050). The P-value was 0.0301 for rs300996 and 0.0397 for the haplotype combination of rs300996–snp-7057–rs300977 in the analysis of the quantitative effects of the alleles and haplotypes on IQ in females. Our data suggest that POU1F1 may affect MR through a gender-specific mechanism.


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
Mental retardation (MR) is a disability characterized by significant limitations both in intellectual functioning and in adaptive behavior as expressed in conceptual, social and practical adaptive skills. This disability originates before age 18. MR affects 0.28–1.2% of children in different countries and regions (1Go).

The underlying causes of MR are established in less than half of all cases, but appear, to a significant extent, to be genetic in nature (2Go). Thyroid hormone is essential for the development of the brain and the nervous system both on the basic processes of neurogenesis and on the processes of terminal brain differentiation (3Go,4Go). Genetic defects affected by the genes involved in the hypothalamus–pituitary–thyroid gland (HPT) axis can cause abnormal thyroid hormone function along with impaired mental development and abnormal growth (5Go).

Pit-1, encoded by the POU1F1 gene on human chromosome 3p11, is a POU homeodomain transcription factor important for the development of certain pituitary cells and the expression of pituitary hormones by these cells (6Go). Among these cells are thyrotrophs which synthesize thyrotropin (TSH). TSH is one of the most important regulators in the HPT axis, which via its receptor (TSHR) stimulates the growth and function of thyroid cells and regulates the synthesis and secretion of the thyroid hormone (7Go). In addition to its {alpha}-subunit which is common to all of the glycoprotein hormones, TSH is composed of a unique ß-subunit that dictates its biological function. The transcription of TSHß is activated by Pit-1 protein. Studies involving Snell and Jackson dwarf mice, which carry loss-of-function mutations in the Pit1 gene, are characterized by deficiencies of TSH and other hormones (8Go,9Go). These dwarf mice exhibit the retarded maturation of the neuronal network and abnormal behavior which should be ascribed to the deficient hormonal state caused by the low or undetectable levels of Pit-1 (10Go,11Go). Although, as reported by Lin et al. (12Go), TSHß expression occurs independently of Pit-1 in the rostral tip thyrotropes on e12.5 in mice, such thyrotropes phenotypically disappear by the time of birth. The presence of functional Pit-1 protein on e15.5 is necessary for subsequent activation of the caudomedial thyrotropes whose function will last throughout the life.

POU1F1 gene mutations in humans have been reported as causing combined pituitary hormone deficiency (CPHD) with low or zero levels of TSH, growth hormone and prolactin (13Go). These genetic lesions can be inherited either in an autosomal dominant or in an autosomal recessive mode. CPHD patients may exhibit the symptoms of hypothyroidism and abnormalities of the nervous system early in the period immediately after birth (14Go). In a reported case of Pit-1 deficiency (15Go), both the mother and child were affected by severe hypothyroidism linked to hereditary failure of thyrotroph development. Neonates also display impairments in neurological development, together with delay in cardiopulmonary function and bone maturation.

In a previous study, our colleagues concluded that polymorphisms in the thyroid-stimulating hormone receptor (TSHR) gene on chromosome 14q31 are not associated with MR in Chinese samples (16Go). Here, we suggest that the POU1F1 gene is another potential susceptibility candidate for association with MR. In this study, we performed a case–control study to investigate the genetic role of POU1F1 in the development of MR using subjects from Zhashui and Ankang counties, northwestern China, and using five single nucleotide polymorphisms (SNPs) spanning the entire POU1F1 gene.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 
All the samples from Zhashui and Ankang counties were grouped together for statistical analysis, because no significant differences were found in genotype frequency distribution of the five selected SNPs between these two counties (P>0.05). Genotype frequencies of all five markers studied showed no deviations from Hardy–Weinberg equilibrium (HWE) either in cases or in controls. The results analyzed on CLUMP are presented in Table 1. There were statistically significant differences of allele and genotype frequencies between cases and controls at rs300996, snp-7057 (a newly found SNP in our samples, details in Materials and Methods) and rs300977. The C allele frequency of rs300996 was higher in cases (56.9%) than in controls [48.6%, P=0.0094, odds ratio (OR)=1.395, 95% confidence interval (CI) 1.085–1.794]. The C allele frequency of snp-7057 was higher in cases (54.9%) than in controls (46.4%, P=0.0079, OR=1.405, 95% CI 1.093–1.805). The G allele frequency of rs300977 was higher in cases (56.4%) than in controls (47.9%, P=0.0074, OR=1.408, 95% CI 1.095–1.810).


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  		Table 1. Genotype and allele frequencies
 
Linkage disequilibrium (LD) between each pair of all the markers is presented in Table 2. The r2-value of each pair of the five SNPs showed three markers (rs300996, snp-7057 and rs300977) to be in strong LD (17Go) and a haplotype analysis was therefore performed. All the P-values corresponding to haplotypes are shown in Table 3. There were significant differences between cases and controls in the haplotypes A-T-A and C-C-G in rs300996 (C/A), snp-7057 (C/T) and rs300977 (G/A). The frequency of haplotype A-T-A was lower in cases (39.3%) than in controls (49.5%, P=0.0013, OR=0.661, 95% CI 0.513–0.852). The frequency of haplotype C-C-G was higher in cases (51.6%) than in controls (44.8%, P=0.0342, OR=1.311, 95% CI 1.020–1.684). The global haplotype frequency also showed significant differences between cases and controls (P=0.0110 from EHPLUS software).


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  		Table 2. Estimates of LD between the five markers
 

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  		Table 3. Estimated haplotype frequencies (rs300996–snp-7057–rs300977) and association significance
 
Additionally, to explore whether the role of POU1F1 with MR is gender related, we conducted a breakdown comparison between cases and controls within different gender groups. The results are presented in Tables 1 and 3. No differences of allele or genotype or haplotype frequencies were observed between cases and controls at these five markers in the male group. In the analysis of the female group, rs300996, snp-7057 and rs300977 showed more significant differences between cases and controls than in the comparison including both males and females. The C allele frequency of rs300996 was higher in cases (60.9%) than in controls (44.5%, P=0.0003, OR=1.941, 95% CI 1.353–2.783). The C allele frequency of snp-7057 was higher in cases (59.9%) than in controls (42.6%, P=0.0001, OR=2.014, 95% CI 1.405–2.888). The G allele frequency of rs300977 was higher in cases (58.4%) than in controls (42.6%, P=0.0005, OR=1.894, 95% CI 1.323–2.713). The frequency of haplotype C-C-G was higher in cases (54.7%) than in controls (39.9%, P=0.0011, OR=1.815, 95% CI 1.268–2.597). At the same time, the frequency of haplotype A-T-A was lower in cases (35.9%) than in controls (53.8%, P=0.00007, OR=0.481, 95% CI 0.334–0.692). The global haplotype frequency showed significant differences between cases and controls (P=0.0050 from EHPLUS software). The differences between cases and controls in females were still significant after Bonferroni correction.

We also performed a power calculation on the G*Power program, based on Cohen's method (18Go). When an effect size index of 0.23 (corresponding to ‘weak to moderate’ gene effect) was used, the present sample size revealed >90% power for detection of significant association ({alpha}<0.05).

We used UNPHASED/QTPHASE (2.403-w32) to assess the quantitative effects of the alleles and haplotypes on IQ. The results are presented in Table 4. In the total and the male group, the P-values for each marker and the haplotype combination of rs300996–snp-7057–rs300977 were all greater than 0.05. In the female group, the P-value was 0.0301 for rs300996 and 0.0397 for the haplotype combination of rs300996–snp-7057–rs300977.


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  		Table 4. The quantitative effects of the alleles and haplotypes on IQ
 

   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
MATERIALS AND METHODS
 REFERENCES
 
MR is a developmental disability that appears in children under the age of 18, and the possible causes of MR are diverse. Our samples came from the Qin-Ba mountain region, a relatively isolated and traditionally iodine-deficient area in northwestern China. For several years the province's health authorities have conducted iodination programs and popularized the use of iodine-enriched common salt. Now, the prevalence of endemic cretinism in this region has markedly declined, but the prevalence of total MR (2.78%) still remains higher than in most other areas of China (1.07%) (19Go). Genetic defects affected by the genes involved in the HPT axis can cause abnormal thyroid hormone function, which may cause severe and irreversible neurological and developmental abnormalities and is one of the leading causes of MR. In this study, we investigated the relationship between the POU1F1 gene and MR within our samples.

Initially, we conducted a total association study between cases and controls without consideration of gender. There were statistically significant differences of allele and genotype frequencies between cases and controls at rs300996, snp-7057 and rs300977. The frequency of haplotype C-C-G was higher in cases than in controls, whereas haplotype A-T-A was lower in cases than in controls. To explore whether a gender difference existed in the association between MR and POU1F1, we conducted a breakdown comparison between cases and controls within different gender groups. In the female group, both allele and genotype differences of rs300996, snp-7057 and rs300977 were more significant than in the combined groups. The frequency of haplotype C-C-G was higher in cases than in controls (P=0.0011, OR=1.815, 95% CI 1.268–2.597), suggesting that C-C-G was a risk haplotype for the mild and borderline forms of MR. Conversely, the frequency of haplotype A-T-A was lower in cases than in controls (P=0.00007, OR=0.481, 95% CI 0.334–0.692), and this haplotype might be protective against MR. No differences of allele, genotype or haplotype frequencies were observed in the male group between cases and controls at any of these five markers. Our findings would therefore suggest a gender-dependent genetic component in mild and borderline MR.

The three markers, rs300996, snp-7057 and rs300977 show significant differences between female cases and female controls, which suggest that POU1F1 is involved in the etiology of MR, but they might not be direct nosogenetic polymorphisms because they are not in exons. However, rs300996 and snp-7057 are at –7 kb in 5' upstream region of the POU1F1 gene, where a proximal regulatory region locates, exhibiting an enhancer activity (20Go). Studies performed in transgenic mice have shown that a 15 kb of the 5' flanking region of the PIT1/GHF1gene is necessary to target gene expression to the anterior pituitary gland (21Go,22Go). An alternative splice acceptor site is in intron 1 of the human POU1F1 (GHF-1/PIT-I) gene. This splice site is responsible for a 78 bp in-frame insertion upstream from exon 2 and leads to the hGHF-2/PIT-2 cDNA detected in the human pituitary (23Go). rs300977 is near the splicing site in intron 1, and it might change the dimensional structure of DNA to impact transcription and splicing.

In general, a haplotype of closely located markers increases the power to detect association with the disease (24Go). In our study, the risk haplotype C-C-G and the protective haplotype A-T-A in rs300996 (C/A), snp-7057 (C/T) and rs300977 (G/A) show differences between female cases and female controls. These three SNPs span a region from the 5' flanking region to intron1 of POU1F1, which suggests that at least one susceptibility locus for MR lies within, or very close to, this region in our female cases. It has been reported that a 12 kb genomic DNA upstream of the human POU1F1 promoter contains the sites responsible for the activation and the tissue-specific expression of the POU1F1 gene (20Go). Our results allow us to hypothesize that females who carry the risk haplotype C-C-G may be regulated less efficiently and have a lower expression level of the pit-1 protein, compared with females who carry the protective haplotype A-T-A. Estrogen plays a key role not only in the control of reproductive behavior but also in the regulation of the neuroendocrine system (25Go). The pituitary gland is a heterogeneous tissue comprising several hormone-secreting and supporting cells, most of which are targeted by estrogens (26Go). In the anterior pituitary, estrogens increase activating protein-1 (AP-1) DNA-binding activity (27Go). AP-1 mediates estrogen-activated cell proliferation, differentiation and secretion. AP-1 can negatively regulate the human POU1F1 gene expression by binding to autoregulatory sites and competing with Pit-1, depending on their respective nuclear concentrations (28Go). Given the higher estrogen level in females (29Go), we suggest that those who carry the risk haplotype C-C-G will suffer more due to both a low quantity of Pit-1 and a high activity of AP-1, whereas those who carry the protective haplotype A-T-A are likely to have a balanceable level of Pit-1 despite the AP-1 action. The deficiency of Pit-1 can lead to hormone abnormality and result in dysfunction of thyroid hormone, thereby causing MR.

In the analysis of the quantitative effects of the alleles and haplotypes on IQ, the P-value was 0.0301 for rs300996 and 0.0397 for the haplotype combination of rs300996–snp-7057–rs300977 in the female group. Although the statistical power could be improved if the sample size is bigger, this result is consistent with the results from our case–control study that the genetic variants of POU1F1 act differently in the genders to lead to MR or low IQ.

In summary, this study provides supportive evidence for the potential association of the POU1F1 gene with mild and borderline MR. In particular, a gender differentiation was observed, which might help to explain the higher susceptibility of females than males in some hypothyroidism cases (30Go,31Go). MR is a complex disorder in children, and one or more factors may or may not interact with Pit-1 to cause MR. Further work is required to investigate the mechanism by which Pit-1 may affect brain development and MR in the context of estrogen action and to explore other candidate factors that result in MR in males and in both gender groups.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
REFERENCES
 
Subjects
All subjects were identified and recruited from Zha Shui and An Kang counties in the Qin-Ba mountain region of Shaanxi province, in northwest China. There is a high prevalence of MR in this relatively isolated and mountainous area. Familial clustering is found in the two counties with several families having multiple affected members in one or more generations. It is possible that genetic factors may interact with environmental factors to determine the overall risk of MR.

Participants were screened to obtain social disability (SD) scores using the Adaptive Scale for Infants and Children revised by Zuo et al. (32Go), Medical school of Peking University. Children 3–5 years old were tested using the Chinese-Wechsler Young Children Scale of Intelligence (C-WYCSI) (33Go). Those 6–16 years old were tested using the Chinese-Wechsler Intelligence Scale for Children (C-WISC) (34Go). A neurological examination, conducted by physicians, included tests of hearing, vision, voice and speech, reflexes, posture and gait, and partial results of this examination had been published elsewhere (35Go,36Go). We defined IQs of less than 70 accompanied by SD scores of 8 or less as MR and IQs 70–79 and SD scores of 9 as a borderline form of MR (Borderline). Among the patients with IQ<70, we classified them into four subtypes: mild MR, IQ scores from 69 to 50; moderate MR, IQ scores from 49 to 35; severe MR, IQ scores from 34 to 20 and profound MR, IQ scores below 20, based on Chinese Classification of Mental Disorders 2nd revision (CCMD-2-R) and the classification of mental and behavioral disorders from the World Health Organization (37Go,38Go). The causes of profound, severe and moderate MR were mostly clear and non-genetic, so only subjects with mild and borderline MR not affected by trachoma, infection, trauma, toxicosis, cerebral palsy or birth complications were included as cases. The subjects who had an IQ within normal range with no disability on those scales and from families with no history of MR were classified as normal controls. There are 195 cases (94 males and 101 females, mean age 10.7±2.8 years, average IQ 67±9.10) including 75 mild (average IQ 60±7.27) and 120 borderline (average IQ 72±6.60) MR subjects and 333 controls (178 males and 155 females, mean age 10.0±2.9 years, average IQ 95±13.96) involved in our case–control study.

All subjects were Han Chinese in origin. Written informed consent was obtained from either the participants or the participants' relatives, after the procedure had been fully explained. The protocol was reviewed and approved by the Ethical Committee of the National Human Genome Center.

Variants identification and genotyping
POU1F1 spans ~17 kb in the human genome and consists of six exons. Initially, we selected seven SNPs within POU1F1 from the dbSNP (http://www.ncbi.nlm.nih.gov/SNP/) and tested their allele frequencies in 32 healthy Chinese individuals using DNA sequencing. The SNPs with minor allele frequencies <5% (rs394939, rs4988460 and rs1051612) were then excluded from the study. Finally, five SNPs with minor allele frequency over 5% (rs300996, snp-7057, rs300977, rs4988463 and rs4988464) were selected. The SNPs rs4988463 (T/A) and rs4988464 (A/T) are in the 3'-UTR, whereas rs300977 (G/A) is in intron 1. When we genotyped rs300996 (C/A) in the 5' upstream region, a new polymorphism was detected downstream of rs300996 separated by 44 bases. This new SNP is named snp-7057 (C/T). The flanking sequence of snp-7057 is caagtaagattcagccacatctact (C/T) tccttagtgattcagaataacaatg.

Genomic DNA was extracted from peripheral blood using a modified phenol/chloroform method. Polymerase chain reactions (PCRs) were carried out in 96-well microtiter plates with a final 25 µl reaction volume containing 50 mM KCl, 10 mM Tris–HCl (pH 8.0), 1.5 mM MgCl2, 200 mM dNTPs, 5 µl Q solution (Qiagen, Valencia, CA, USA), 10 pM each primer, 20 ng DNA and 2.5 U Taq polymerase (Life Technologies, Karlsuhe, Germany). PCR conditions consisted of an initial 5 min at 95°C, 35 cycles at 94°C for 30 s, annealing temperature for 40 s (the annealing temperature needed for each pair of primers are listed in Table 1), 72°C for 50 s and a final extension period of 10 min at 72°C using the GeneAmp PCR System 9700 (Applied BioSystems, Foster City, CA). All the SNPs were genotyped using DNA sequencing on an ABI 3100 genetic analyzer using the ABI Prism BigDye Terminator Cycle Sequencing Kit Version 3.1 (Applied BioSystems). The primers used for PCR and DNA sequencing are listed in Table 5.


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  		Table 5. The primers sequences and annealing temperature for PCR
 
Statistical analysis
HWE tests were performed for each polymorphism on an online calculator (http://www.kursus.kvl.dk/shares/vetgen/_Popgen/genetik/applets/kitest.htm). The mean age of each group, allele frequencies and genotype frequencies of each polymorphism were calculated using SPSS (version 13.0). The CLUMP program (version 2.3) implementing a Monte Carlo simulation strategy (39Go) was used to compare the discrepancies of allele and genotype frequencies between cases and controls. Pairwise LD of all possible pairs of the five polymorphisms was estimated using 2LD software where the extent of LD was measured by standardized D' (40Go) and using EMLD software where the extent of LD was measured by r2 (https://epi.mdanderson.org/~qhuang/Software/pub.htm). The haplotype frequencies were estimated using EHPLUS software, which is designed for model-free analysis and permutation tests of allelic association based on an EH algorithm (41Go,42Go). The individual and global haplotype frequency differences between cases and controls were compared using SHEsis, a robust and user-friendly software platform with a series of tools for analysis in association study with high efficiency (43Go), and those haplotypes with a frequency under 5% were excluded from the analysis. The global haplotype frequency differences between cases and controls were also compared using EHPLUS software after 1000 permutations. In this study, the P-values were two-tailed and significance was accepted when P<0.05. ORs with 95% CIs were estimated for the effects of high-risk haplotypes and calculated using an internet-based facility (http://www.pedro.fhs.usyd.edu.au/Utilities/CIcalculator.xls). The statistical power of our sample size were estimated using the G*Power program (44Go). The quantitative effects of the alleles and haplotypes on IQ were assessed using UNPHASED/QTPHASE(2.403-w32) (45Go).


   ACKNOWLEDGEMENTS
 
We sincerely thank all participants in this study. This work was supported by grants from the national 973 and 863 programs, the National Natural Science Foundation of China, the Shanghai Municipal Commission for Science and Technology and ‘the Tenth Five-Year Plan’ National Tackle Problem Item (2001BA901A49).

Conflict of Interest statement: None declared.


   FOOTNOTES
 
{dagger} The authors wish it to be known that, in their opinion, the first two authors should be regarded as joint First Authors. Back


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 RESULTS
 DISCUSSION
 MATERIALS AND METHODS
 REFERENCES
 

  1. Leonard, H. and Wen, X. (2002) The epidemiology of mental retardation: challenges and opportunities in the new millennium. Ment. Retard. Dev. Disabil. Res. Rev., 8, 117–134.[CrossRef][ISI][Medline]

  2. Inlow, J.K. and Restifo, L.L. (2004) Molecular and comparative genetics of mental retardation. Genetics, 166, 835–881.[Abstract/Free Full Text]

  3. Oppenheimer, J.H. and Schwartz, H.L. (1997) Molecular basis of thyroid hormone-dependent brain development. Endocr. Rev., 18, 462–475.[Abstract/Free Full Text]

  4. Anderson, G.W. (2001) Thyroid hormones and the brain. Front. Neuroendocrinol., 22, 1–17.[CrossRef][ISI][Medline]

  5. Winter, W.E. and Signorino, M.R. (2001) Review: molecular thyroidology. Ann. Clin. Lab. Sci., 31, 221–244.[Abstract/Free Full Text]

  6. Cushman, L.J., Showalter, A.D. and Rhodes, S.J. (2002) Genetic defects in the development and function of the anterior pituitary gland. Ann. Med., 34, 179–191.[ISI][Medline]

  7. De Felice, M., Postiglione, M.P. and Di Lauro, R. (2004) Minireview: thyrotropin receptor signaling in development and differentiation of the thyroid gland: insights from mouse models and human diseases. Endocrinology, 145, 4062–4067.[Free Full Text]

  8. Li, S., Crenshaw, E.B., III, Rawson, E.J., Simmons, D.M., Swanson, L.W. and Rosenfeld, M.G. (1990) Dwarf locus mutants lacking three pituitary cell types result from mutations in the POU-domain gene pit-1. Nature, 347, 528–533.[CrossRef][Medline]

  9. Rhodes, S.J., DiMattia, G.E. and Rosenfeld, M.G. (1994) Transcriptional mechanisms in anterior pituitary cell differentiation. Curr. Opin. Genet. Dev., 4, 709–717.[CrossRef][Medline]

  10. Noguchi, T., Sugisaki, T. and Tsukada, Y. (1982) Postnatal action of growth and thyroid hormones on the retarded cerebral myelinogenesis of Snell dwarf mice (dw). J. Neurochem., 38, 257–263.[ISI][Medline]

  11. Sekiguchi, M., Abe, H., Moriya, M., Tanaka, O. and Nowakowski, R.S. (1998) Cerebellar microfolia and other abnormalities of neuronal growth, migration, and lamination in the Pit1dw-J homozygote mutant mouse. J. Comp. Neurol., 400, 363–374.[CrossRef][ISI][Medline]

  12. Lin, S., Li, S., Drolet, D. and Rosenfeld, M. (1994) Pituitary ontogeny of the Snell dwarf mouse reveals Pit-1-independent and Pit-1-dependent origins of the thyrotrope. Development, 120, 515–522.[Abstract]

  13. Cohen, L.E. and Radovick, S. (2002) Molecular basis of combined pituitary hormone deficiencies. Endocr. Rev., 23, 431–442.[Abstract/Free Full Text]

  14. Blankenstein, O., Muhlenberg, R., Kim, C., Wuller, S., Pfaffle, R. and Heimann, G. (2001) A new C-terminal located mutation (V272ter) in the PIT-1 gene manifesting with severe congenital hypothyroidism. Possible functionality of the PIT-1 C-terminus. Horm. Res., 56, 81–86.[CrossRef][ISI][Medline]

  15. de Zegher, F., Pernasetti, F., Vanhole, C., Devlieger, H., Van den Berghe, G. and Martial, J.A. (1995) The prenatal role of thyroid hormone evidenced by fetomaternal Pit-1 deficiency. J. Clin. Endocrinol. Metab., 80, 3127–3130.[Abstract]

  16. Guo, T.W., Zhang, F.C., Gao, J.J., Bian, L., Gao, X.C., Ma, J., Yang, M., Ji, Q., Duan, S.W., Zheng, Z.J. et al. (2005) Polymorphisms in the TSHR (thyrotropin receptor) gene on chromosome 14q31 are not associated with mental retardation in the iodine-deficient areas of China. Neurosci. Lett., 382, 179–184.[CrossRef][ISI][Medline]

  17. Ardlie, K.G., Kruglyak, L. and Seielstad, M. (2002) Patterns of linkage disequilibrium in the human genome. Nat. Rev. Genet., 3, 299–309.[CrossRef][ISI][Medline]

  18. Cohen, J. (1988) Statistical Power Analysis for the Behavioral Sciences, 2nd edn. Hillsdale, NJ, Erlbaum.

  19. Zhang, Z., Wang, Z., Zhang, R., Gong, F. and Wang, Z. (2001) The iodine nutritive status of the pregnant women and wet nurses in Qin-Ba mountain areas. Chin. J. Endemiol., 20, 201–203.

  20. Rajas, F., Delhase, M., De La Hoya, M., Verdood, P., Castrillo, J.L. and Hooghe-Peters, E.L. (1998) Nuclear factor 1 regulates the distal silencer of the human PIT1/GHF1 gene. Biochem. J., 333, 77–84.

  21. Lew, D., Brady, H., Klausing, K., Yaginuma, K., Theill, L.E., Stauber, C., Karin, M. and Mellon, P.L. (1993) GHF-1-promoter-targeted immortalization of a somatotropic progenitor cell results in dwarfism in transgenic mice. Genes. Dev., 7, 683–693.[Abstract/Free Full Text]

  22. Rhodes, S.J., Chen, R., DiMattia, G.E., Scully, K.M., Kalla, K.A., Lin, S.C., Yu, V.C. and Rosenfeld, M.G. (1993) A tissue-specific enhancer confers Pit-1-dependent morphogen inducibility and autoregulation on the pit-1 gene. Genes. Dev., 7, 913–932.[Abstract/Free Full Text]

  23. Delhase, M., Vila, V., Hooghe-Peters, E.L. and Castrillo, J. (1995) A novel pituitary transcription factor is produced by alternative splicing of the human GHF-1/PIT-1 gene. Gene, 155, 273–275.[CrossRef][ISI][Medline]

  24. Collins, A. and Morton, N.E. (1998) Mapping a disease locus by allelic association. Proc. Natl Acad. Sci. USA, 95, 1741–1745.[Abstract/Free Full Text]

  25. Kuiper, G.G., Shughrue, P.J., Merchenthaler, I. and Gustafsson, J.A. (1998) The estrogen receptor beta subtype: a novel mediator of estrogen action in neuroendocrine systems. Front. Neuroendocrinol., 19, 253–286.[CrossRef][ISI][Medline]

  26. Mitchner, N.A., Garlick, C. and Ben-Jonathan, N. (1998) Cellular distribution and gene regulation of estrogen receptors alpha and beta in the rat pituitary gland. Endocrinology, 139, 3976–3983.[Abstract/Free Full Text]

  27. Zhu, Y.S. and Pfaff, D.W. (1998) Differential regulation of AP-1 DNA binding activity in rat hypothalamus and pituitary by estrogen. Brain Res. Mol. Brain Res., 55, 115–125.[Medline]

  28. Delhase, M., Castrillo, J.L., de la Hoya, M., Rajas, F. and Hooghe-Peters, E.L. (1996) AP-1 and Oct-1 transcription factors down-regulate the expression of the human PIT1/GHF1 gene. J. Biol. Chem., 271, 32349–32358.[Abstract/Free Full Text]

  29. Klein, K.O., Baron, J., Colli, M.J., McDonnell, D.P. and Cutler, G.B., Jr. (1994) Estrogen levels in childhood determined by an ultrasensitive recombinant cell bioassay. J. Clin. Invest., 94, 2475–2480.[ISI][Medline]

  30. Lorey, F.W. and Cunningham, G.C. (1992) Birth prevalence of primary congenital hypothyroidism by sex and ethnicity. Hum. Biol., 64, 531–538.[ISI][Medline]

  31. Devos, H., Rodd, C., Gagne, N., Laframboise, R. and Van Vliet, G. (1999) A search for the possible molecular mechanisms of thyroid dysgenesis: sex ratios and associated malformations. J. Clin. Endocrinol. Metab., 84, 2502–2506.[Abstract/Free Full Text]

  32. Zuo, Q., Zhang, Z. and Lei, Z. (1988) Adaptive Scale of Infant and Children. Medical University of China, Beijing, China.

  33. Gong, Y. and Dai, X. (1992) Chinese-Wechsler Young Children Scale of Intelligence (C-WYCSI). Map Press, Hunan, China.

  34. Gong, Y. and Cai, T. (1993) Wechsler Intelligence Scale for Children, Chinese Revision (C-WISC). Map Press, Hunan, China.

  35. Gao, X.C., Zhang, F.C., Zheng, Z.J., Li, R.L. and Dai, H.X. (2005) Change of suspicious sub-cretin children's psychomotor function in different periods of iodine supplementation. Chin. J. Endemiol., 24, 186–188.

  36. Gao, X.C., Zhang, F.C., Li, X., Liu, Z. and Zheng, Z.J. (1999) Experimental studies on cognitive ability of color and figure of mental retarded children and marginal children in Qinba mountain. J. Northwest Univ., 29, 449–452.

  37. Chinese Association of Psychiatry. (1995) Chinese Classification of Mental Disorders, 2nd revision. Southeast University Press, Nanking, China.

  38. The World Health Organization. (1992) The ICD-10 Classification of Mental and Behavioral Disorders: Clinical Descriptions and Diagnostic Guidelines. WHO, Geneva, Switzerland.

  39. Sham, P.C. and Curtis, D. (1995) Monte-Carlo tests for associations between disease and alleles at highly polymorphic loci. Ann. Hum. Genet., 59, 97–105.[ISI][Medline]

  40. Zapata, C., Carollo, C. and Rodriguez, S. (2001) Sampling variance and distribution of the D' measure of overall gametic disequilibrium between multiallelic loci. Ann. Hum. Genet., 65, 395–406.[CrossRef][ISI][Medline]

  41. Xie, X. and Ott, J. (1993) Testing linkage disequilibrium between a disease gene and marker loci. Am. J. Hum. Genet., 53, 1107–1107.[ISI][Medline]

  42. Zhao, J.H., Curtis, D. and Sham, P.C. (2000) Model-free analysis and permutation tests for allelic associations. Hum. Hered., 50, 133–139.[ISI][Medline]

  43. Shi, Y.Y. and He, L. (2005) SHEsis, a powerful software platform for analyses of linkage disequilibrium, haplotype construction, and genetic association at polymorphism loci. Cell Res., 15, 97–98.[CrossRef][ISI][Medline]

  44. Erdfelder, E., Faul, F. and Buchner, A. (1996) G*Power: a general power analysis program. Behav. Res. Methods. Instrum. Comput., 28, 1–11.[ISI]

  45. Dudbridge, F. (2003) Pedigree disequilibrium tests for multilocus haplotypes. Genet. Epidemiol., 25, 115–121.[CrossRef][ISI][Medline]


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