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Genetic polymorphisms and multifactorial diseases: facts and fallacies revealed by the glucocorticoid receptor gene
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Genetic polymorphisms and multifactorial diseases: facts and fallacies revealed by the glucocorticoid receptor gene Elisabeth F.C. van Rossum, Henk Russcher and Steven W.J. Lamberts Department of Internal Medicine, Erasmus Medical Center, Dr Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
In recent years enormous progress in determining the sequence of the human genome has led to a rapid development of research into polymorphisms in genes involved in complex diseases. It is clear, however, that there are important limitations in many of these association studies. Problems with reliable and reproducable phenotyping, the number of individuals studied, racial heterogeneity, population stratification (founder effect), functionality and multiple testing often mean that studies are not reproducible. In this review we describe a number of the limitations related to this type of research; from both our own experience with studies on polymorphisms in the glucocorticoid receptor gene, and shortcomings and solutions from the literature.
or insertion polymorphisms (Table 1). Techniques to detect polymorphisms have developed rapidly in the past few years, especially with the introduction of high-throughput techniques [8] that allow researchers to screen candidate genes in many individuals in a simple, cheap and rapid manner. There is an exponential rise of association studies in recent literature. However, limitations must be recognized when conducting these studies (Box 1), and many association studies have been criticized with respect to these. In this review, we focus on the potential pitfalls when conducting genetic-association studies and offer recommendations for careful study design that will allow these type of studies to generate powerful data.
In the past few years rapid progress in determining the sequence of the human genome [1,2] has stimulated research into the role of polymorphisms in genes that might be involved in the pathogenesis of common diseases. Linkage analysis has been used widely to investigate the genetic basis of hereditary diseases [3–5]. These studies involve searching for genomic regions that contain several shared alleles more commonly than expected in affected individuals in a family. Using several genetic markers, a region can be identified that contains an allele that predisposes for a disease and which can be fine-mapped with additional markers. Linkage analysis is a powerful tool to detect rare, high-risk alleles. However, often it is difficult to narrow the region of interest adequately. Population-based association studies are a popular way to detect genes with a role in common, multifactorial diseases that have a strong environmental component [6,7]. Association studies test whether a genetic polymorphism occurs more frequently in affected cases than in healthy controls. In addition, some traits can be studied and compared between carriers and non-carriers of a polymorphism. Most polymorphisms studied are single nucleotide polymorphisms in which a nucleotide is substituted by another with a frequency of O1% in the normal population. Other types of polymorphisms include microsatellite repeat polymorphisms and either deletion
Limitations of association studies Phenotyping Reliable phenotyping, including careful recruitment of participants to rule out bias, is important in assuring the high quality of an association study. As discussed by Gambaro et al. [9], phenotypic differences between studies might occur because of variation in the definition of cases and controls in different studies, and the heterogeneous phenotype of some diseases. The sensitivity and specificity of the methods used to characterize the phenotype should also be taken into account. This applies to the researcher performing measurements and to the variance in the measurement of routine variables such as laboratory measurements. Errors (frequently undetected) are a problem in large-scale population studies that involve many data-collection steps and different researchers, and can occur at many levels (e.g. data-collection, genotyping and information processing). The influence of these errors can be reduced by increasing the sample size, minimizing inter-researcher variation (e.g. physical examination and evaluation of radiodiagnostics) and incorporating steps to double-check the parameters measured (Box 2).
Corresponding author: van Rossum, E.F.C. ([email protected]). Available online 4 November 2005
Multiple testing It is recognized that the rate of false-positive results (type I error) is relatively high when a large number of statistical tests are performed [10]. One way to diminish this problem is to statistically correct for multiple testing,
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Table 1. Genetic polymorphismsa
a
Polymorphism Single-base nucleotide substitutions (also called single-nucleotide polymorphism)
Change Change of one nucleotide
Examplea Gene encoding GR: N363S in exon 2; and BclI in intron 2
Refs [37]
Small-scale, multi-base deletions or insertions (also called deletion/insertion polymorphism)
Either insertion or deletion of 1–5 nucleotides
Gene encoding ACE: intronic 287-bp nonsense DNA domain
[38]
Microsatellite repeat variations (also called short tandem repeats)
Repeats of several nucleotides (2, 3 or 4)
Gene encoding IGF-1: CA repeat in promoter Gene encoding AR: CAG repeat in exon 1
[39,40]
Abbreviations: ACE, angiotensin-converting–enzyme; AR, androgen receptor; IGF-1, Insulin-like growth factor 1.
and other factors also help to reduce the number of falsepositive results. A good rationale for the association study, an a priori justification, increases the chances of finding true-positive results. For example, glucocorticoids (GCs) exert the majority of their effects by binding to the glucocorticoid receptor (GR), which makes the gene that encodes the GR a candidate when studying the genetic basis of differences in the response to GCs in the normal population. Initially dexamethasone-suppression tests in vivo were performed to investigate differences in sensitivity to GCs between carriers and noncarriers of several polymorphisms of the GR including N363S, ER22/23EK (two, linked singlenucleotide polymorphisms, the second of which results in an amino-acid change), and the intronic BclI polymorphism. The N363S and the BclI polymorphisms increase the response to dexamethasone, which indicates an increase in sensitivity to the effects of GCs [11,12]. By contrast, the ER22/23EK polymorphism decreases the response to dexamethasone, which indicates relative resistance to GCs (Box 3) [13]. These findings provide a rationale for our next hypotheses, which concern the association between GR polymorphisms and other parameters that are affected by GCs, such as body composition and metabolic parameters (insulin and lipids). As expected, we find associations between the ER22/23EK and several measures of decreased GC effects (lower insulin levels, lower cholesterol levels and beneficial changes in body composition) (Box 3) [13,14], whereas the N363S and the BclI polymorphisms are associated with measures of increased GC effects (more body fat, bigger insulin response to dexamethasone and less lean-body mass) [11,12]. Another way to reduce the rate of false-positive results is to increase statistical power by, for example, increasing the sample size [10]. Replication of study outcomes Another important aspect is confirming an association in a different study population, which diminishes the risk of findings occurring by chance. The phenotypic changes in carriers of the N363S, ER22/23EK and BclI polymorphisms in the subjects in whom the dexamethasone suppression test were performed matched the changes observed in GC sensitivity. In a study in Dutch, elderly, healthy individuals, the observation that carriers of the BclI polymorphism (G-allele) have a lower body-mass index (BMI) than non-carriers has www.sciencedirect.com
been confirmed in a separate population of elderly Dutch men [12]. However, one risk of trying to replicate an observed association in a different ethnic population is that, if the replication fails, the first association might be considered false-positive. It is important to realize that polymorphisms might have different effects in different ethnic backgrounds. First, the frequency of polymorphisms can differ between different ethnic groups. In this respect is it intriguing that, for example, this N363S genotype, which was found to be 3.1% (allele frequency) in the elderly healthy Dutch Caucasian population, is highly frequent in an Australian population (allele frequency 7.4%) [15], whereas in other reports no N363S-carriers have been detected in a Chinese population [16] nor in a Japanese population [17], and an allele frequency of 0.3% was found in a population of South Asian origin living in northeast England [18].
Box 1. Fallacies of polymorphism studies † † † † † † † † †
Unreliable phenotyping Few individuals studied Racial heterogeneity Population stratification (founder effect) Gender differences Age differences Function of the genetic variation not studied Statistical analysis (false positive results by multiple testing) Publication bias
Box 2. Requirements to assure high quality of association studies † Good phenotyping (careful recruitment of subjects and datacollection, high sensitivity and specificity of tests, minimizing inter-researcher variation, and double-checking measured parameters) † Large number of individuals studied (depending on the frequency of the studied gene variant) † Homogeneity of the study population with respect to ethnicity, gender, age and environmental factors or the use of statistical corrections for these confounders † Replication in different study population(s) † A good rationale for the association under investigation to increase the a priori justification † Statistical analysis using multiple testing corrections † Confirming results in vivo with experiments in vitro † Unraveling the molecular basis of the mechanism of the gene variation studied
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Box 3. Simplified scheme of a relationship between a genetic polymorphism and a phenotype Table I shows data on the ER22/23EK polymorphism in the gene that encodes the GR. This polymorphism consists of two, singlenucleotide polymorphisms in codons 22 and 23, the latter of which results in an amino acid change from arginine (R) to lysine (K). It is likely that this alters the secondary structure of GR mRNA, forcing a shift towards the use of the AUG1 rather than the AUG27 codon as the start codon. The preferred use of AUG1 start codon in the ER22/23EK variant alters the ratio between GR-A (transcriptionally less active) and GR-B (transcriptionally more active) [26,27]. Indeed, experiments in vitro show a reduced trans-activating capacity of the ER22/23EK variant, whereas trans-inhibition is unchanged because the different translational isoforms are equally potent at inhibiting NF-kB. In addition, the ability of GR to upregulate expression of GILZ is reduced in ER22/23EK
homozygotes, whereas trans-repression of IL-2 does not differ from the controls [23]. In dexamethasone-suppression tests, carriers of the ER22/23EK polymorphism have significantly higher cortisol levels than noncarriers, which indicates that carriers of ER22/23EK are relatively resistant to the effects of GCs with respect to the sensitivity of the negative-feedback mechanism [13]. The ER22/23EK polymorphism is associated with several phenotypic changes, including increased insulin sensitivity, lower total and lowdensity lipoprotein cholesterol levels, lower C-reactive protein levels, beneficial sex-specific body composition (greater height, lean mass and muscle strength in males, and smaller waist and hip circumferences in females), lower risk of developing dementia and cerebral white matter lesions, and longevity [13,14,41,42]. All these phenotypic changes can be explained by subtle decreases in the sensitivity to GCs.
Table I Polymorphism ER22/23EK (GAGAGG/ GAAAAG)
GR protein GR-A:GR-B increases
In vitro Decreased transactivation
In vivo Decreased response to 1 mg dexamethasone
Phenotype Healthier metabolic profile (insulin, total and lowdensity lipoprotein-cholesterol and C-reactive protein levels decrease)
No change in trans-repression Beneficial effects on body composition Decreased risk of dementia and cerebral white matter lesions Longevity
Second, some combinations of a polymorphism and other polymorphic genes, which vary between ethnic groups, might also lead to a different phenotype. For GCs, combinations of either variations or mutations in other genes that are involved in GC action are also related to some phenotypes. In this context, Draper et al. [19] have shown that mutations in the genes that encode 11 b-hydroxysteroid dehydrogenase type 1 (11b-HSD1), which catalyzes the reduction of inactive cortisone to active cortisol and, thereby, regulates tissue-specific bioavailabilty of GCs, and hexose-6phosphate dehydrogenase lead to a phenotype in which there is cortisone reductase deficiency (which resembles polycystic ovary syndrome with adrenocorticotropin-mediated androgen excess). Individuals with only the 11b-HSD1 mutation do not have this pathological phenotype. A third cause of different outcomes in replication studies is that environmental factors might contribute to the effects of a polymorphism on phenotype. In the example of the N363S polymorphism in the GR gene, hypersensitivity to GCs in carriers of this polymorphism seems to result in easier fat storage caused by hypersensitive insulin secretion in response to GCs [11,20]. In a highfat diet environment, these carriers are more likely to become obese than in a setting in which a low-fat diet is more common and, thus, this variant might result in different phenotypes. In addition, population stratification (also referred to as the ‘founder effect’) is a major problem in association studies [6]. The founder effect is the tendency for high frequencies of both some genes and particular diseases within a population to lead to falsepositive associations. Lohmueller et al. [21] have suggested that larger sample sizes and studies with www.sciencedirect.com
family-based controls will help to avoid this problem and to make results more replicable. Sex-specific and age-specific associations Sex-specific and age-dependent association of polymorphisms is also described, and the ER22/23EK variant is an example of a sex-specific polymorphic association. Young, adult, male carriers of ER22/23EK are, on average, taller, have more lean mass and are stronger (Box 3), whereas female carriers have a tendency towards lower fat mass, and smaller waist and hip circumferences [14]. Both associations can be explained by a relative resistance to the effects of GCs, as shown previously in a population including both men and women [13]. Why this polymorphism is associated with different changes in body composition in men and women is unclear, but hormonal factors might be involved. An example of an age-dependent association of a GR polymorphism is the relationship between the BclI and BMI. In middle-aged subjects this variant is associated with an increase in the BMI and the waist-to-hip ratio (WHR) [22]. By contrast, in two elderly populations this variant is associated with lower BMI [12]. However, because BMI does not differentiate between fat mass and lean mass we have also studied body composition using dual energy X-ray absorptiometry (DEXA) scans. We observed that carriers of the BclI variant allele (G-allele) have a tendency towards lower lean mass but there are no differences in fat mass, which indicates that carriers of this variant suffer more from sarcopenia during the normal aging process than non-carriers [12]. Both the increased BMI and WHR in middle-aged individuals (more abdominal fat mass) and the decreased BMI in older individuals (more loss of lean mass during aging) can
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be explained by an increased sensitivity to GCs, as shown previously [12]. Thus, polymorphisms can be associated with particular hormonal and metabolic conditions, which, because of numerous other processes, result in different phenotypes at different ages. Therefore, in replication studies it is important to take into account factors such as gender and age as well as ethnicity. Biological plausibility Another important feature of association studies is that there should be a biological plausibility for a candidate gene. Usually, candidate genes encode a factor that is important in a particular pathway and, thus, might be involved in the pathophysiology of a disease. Also, linkage analysis can lead to the identification of candidate genes. However, an association between a polymorphism and a phenotype does not necessarily indicate a causal relationship: a polymorphism can be in linkage disequilibrium with another polymorphism in the same gene or even in an adjacent gene. Testing of the effects of a polymorphism in vitro can help to distinguish between functional and non-functional polymorphisms. For the GR gene, the ER22/23EK polymorphism influences the trans-activating capacity of the GR, but trans-repression of NF-kB is unaltered [23]. In addition, Russcher et al. have studied both upregulatory and downregulatory effects of GR polymorphisms by investigating the effects of the ER22/23EK variant on GC-induced leucine zipper (GILZ) protein and interleukin-2 (IL-2), respectively. Although upregulation of GILZ is reduced in homozygous carriers of ER22/23EK, transrepression of IL-2 is unaltered compared with the control group (Box 3). This is consistent with our findings in vivo that there is reduced sensitivity to GCs in carriers of ER22/23EK. Russcher et al. have also studied the effects of the N363S variant, and found that this polymorphism
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increases the trans-activating capacity, both in vitro and ex vivo [23]. This is consistent with the association between the N363S variant and increased sensitivity to GCs in vivo [11]. Furthermore, the location of the polymorphism in a gene is important with respect to function. For example, the N363S polymorphism changes asparagine to serine, which creates a potential phosphorylation site that might be relevant for DNA binding by the GR [24,25]. However, the exact effect of the N363S polymorphism is not elucidated. By contrast, the molecular mechanism through which the ER22/23EK polymorphism reduces sensitivity to GCs has been clarified recently [26]. Yudt et al. [27] report that at least two methionine initiation codons in the GR mRNA, AUG1 and AUG27, result in two translation variants, GR-A (94 kDa) and GR-B (91 kDa). The shorter GR-B protein has a stronger trans-activating effect in transient transfection experiments [27], and the sensitivity to GCs in carriers of ER22/23EK is lower because more of the longer, less transcriptionally active GR-A isoform is formed (Box 3) [26]. Indeed, Russcher et al. show that the reduction in trans-activating capacity of the GR in carriers of ER22/23EK is explained by the change in GR-A:GR-B. Trans-inhibition seems to be unchanged because the isoforms are equally potent at inhibiting the trans-activating activity of NF-kB [23]. It is likely that this polymorphism alters the secondary structure of GR mRNA, which forces more translation to be initiated from AUG1. The functional effects of intronic polymorphisms is a difficult issue. Often, intronic polymorphisms are considered to be non-functional because they do not change the coding sequence. However, they might still be involved in the splicing process by, for example, changing the sequence of so-called intronic splicing silencers and enhancers, and through other mechanisms that are important for gene expression [28].
Linkage
TthIII1
1.00 (high)
N363S
BclI
0.22 (low) ER22/23EK ER22/23EK
BclI
N363S
TthIII1
Figure 1. Haplotype reconstruction calculations according to Stephens et al. (Phase Reconstruction Method) [32]. The polymorphisms in the GR (ER22/23EK, BclI, N363S and TthIII1) are indicated on both axes. The colors indicate the calculated degree of linkage (red indicates high linkage, assigned a value of 1.00; blue indicates low linkage, assigned a value of 0.22). The TthIII1 polymorphism is linked to the ER22/23EK variant (red), whereas TthIII1 does not show linkage with the BclI polymorphism (blue). In addition, the ER22/23EK and BclI polymorphisms (red) are also linked because the presence of one excludes the other on the same allele. www.sciencedirect.com
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The molecular mechanisms that account for the effects of majority of polymorphisms have not been identified. Recently, methods other than the association between a single polymorphism and phenotypic data (e.g. haplotype analysis) have become popular to study the effects of polymorphisms. Haplotypes have been constructed that consist of alleles that contain several polymorphisms in one gene to identify the association between phenotypic changes and particular risk alleles. In the GR gene, Stevens et al. [29] have constructed a haplotype that is associated with an increased sensitivity to GCs. Interestingly, the three polymorphisms described in this review are mutually exclusive (i.e. they never occur on the same allele) [30]. Although this is probably a result of chance during evolution, this naturally occurring phenomenon can simplify the analysis of association studies that use these polymorphisms. A fourth restriction-fragmentlength polymorphism in the promoter region of the GR gene (TthIII1) [31] is linked to the ER22/23EK allele [30]. The combined allele (TthIII1 T and ER22/23EK) is associated with relative resistance to GCs, whereas there is no difference in sensitivity of the TthIII1 T allele itself (TthIII1 T and 22/23ER) compared with non-carriers of both variant alleles (TthIII1 C and 22/23ER) [30]. Figure 1 shows a graphical reproduction of haplotype reconstruction calculations according to Stephens et al. (Phase Reconstruction Method) [32]. Animal models can also be used to show the in vivo effects of a specific mutation. For example, Oitzl et al. [33] report a mutant mouse (GRdim/dim) in which homozygous A458T mutation of the GR makes it unable to dimerize. GR-knockout mice (GRK/K) do not survive after birth because of respiratory insufficiency as a consequence of impaired fetal lung development [34]. Studying the in vivo function of polymorphisms in this way contributes to the understanding of the associations observed in humans. Publication bias A perceived problem with association studies is that of publication bias, whereby it is thought that journals tend to publish positive rather than negative results [35]. However, a large meta-analysis of 301 publications on 25 associations shows that publication bias is unlikely to account for the lack of reproducibility of association-study results [21]. In 11 of the 25 associations examined, the results were replicable (this is, however, !50%). From this study, Lohmueller et al. state that underpowered, non-significant studies of real associations with modest genetic effects can reasonably account for much of the variability in replication. This meta-analysis reinforces the need for well-designed, sufficiently powered replication studies of every positive association between a common polymorphism and a common complex disease. Conclusions Worldwide, many genetic data became available with the Human Genome Project, and technical and informatic methods have improved rapidly. In the future, there is likely to be a shift towards whole-genome-association studies [36], and careful study design is a number one priority for these future studies. The set-up of these www.sciencedirect.com
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studies should focus on a good rationale for the association under study, careful phenotyping, large numbers of individuals in the study, homogeneity of the study population, correction for multiple testing, and unraveling the underlying mechanisms of the observed associations by in vitro experiments, animal models and molecular methods. In addition, replication of the association in a comparable study population reduces the risk of the findings occurring by chance. Taking these factors into account, association studies on polymorphisms can be a powerful tool to detect relationships between genetic variations and complex diseases or traits. Acknowledgements These studies were supported financially by grant 903–43–093 from the Netherlands Organization for Scientific Research (NWO) and the NWORIDE (Research Institute for Diseases of the Elderly), The Netherlands.
References 1 Lander, E.S. et al. (2001) Initial sequencing and analysis of the human genome. Nature 409, 860–921 2 Venter, J.C. et al. (2001) The sequence of the human genome. Science 291, 1304–1351 3 Hastbacka, J. et al. (1992) Linkage disequilibrium mapping in isolated founder populations: diastrophic dysplasia in Finland. Nat. Genet. 2, 204–211 4 Kaplan, N.L. et al. (1995) Likelihood methods for locating disease genes in nonequilibrium populations. Am. J. Hum. Genet. 56, 18–32 5 Jorde, L.B. (2000) Linkage disequilibrium and the search for complex disease genes. Genome Res. 10, 1435–1444 6 Lander, E.S. and Schork, N.J. (1994) Genetic dissection of complex traits. Science 265, 2037–2048 7 Risch, N.J. (2000) Searching for genetic determinants in the new millennium. Nature 405, 847–856 8 Collins, F.S. et al. (1997) Variations on a theme: cataloging human DNA sequence variation. Science 278, 1580–1581 9 Gambaro, G. et al. (2000) Association studies of genetic polymorphisms and complex disease. Lancet 355, 308–311 10 Salanti, G. et al. (2005) Obstacles and opportunities in meta-analysis of genetic association studies. Genet. Med. 7, 13–20 11 Huizenga, N.A. et al. (1998) A polymorphism in the glucocorticoid receptor gene may be associated with an increased sensitivity to glucocorticoids in vivo. J. Clin. Endocrinol. Metab. 83, 144–151 12 van Rossum, E.F.C. et al. (2003) Identification of the Bcl I Polymorphism in the Glucocorticoid Receptor Gene: association with sensitivity to glucocorticoids in vivo, and body mass index. Clin. Endocrinol. (Oxf.) 59, 585–592 13 van Rossum, E.F.C. et al. (2002) A polymorphism in the glucocorticoid receptor gene, which decreases sensitivity to glucocorticoids in vivo, is associated with low insulin and cholesterol levels. Diabetes 51, 3128–3134 14 van Rossum, E.F.C. et al. (2004) The ER22/23EK Polymorphism in the Glucocorticoid Receptor Gene is Associated with a Beneficial Body Composition and Muscle Strength in Young Adults. J of Clin Endocrin Metab 89, 4004–4009 15 Lin, R.C. et al. (1999) High penetrance, overweight, and glucocorticoid receptor variant: case-control study. BMJ 319, 1337–1338 16 Lei, S.F. et al. (2003) Polymorphisms of four bone mineral density candidate genes in Chinese populations and comparison with other populations of different ethnicity. J. Bone Miner. Metab. 21, 34–42 17 Ikeda, Y. et al. (2001) A polymorphism in the promoter region of the glucocorticoid receptor gene is associated with its transcriptional activity. Endocr. J. 48, 723–726 18 Syed, A.A. et al. (2004) Low prevalence of the N363S polymorphism of the glucocorticoid receptor in South Asians living in the United Kingdom. J. Clin. Endocrinol. Metab. 89, 232–235 19 Draper, N. et al. (2003) Mutations in the genes encoding 11betahydroxysteroid dehydrogenase type 1 and hexose-6-phosphate
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dehydrogenase interact to cause cortisone reductase deficiency. Nat. Genet. 34, 434–439 Di Blasio, A.M. et al. (2003) The relation between two polymorphisms in the glucocorticoid receptor gene and body mass index, blood pressure and cholesterol in obese patients. Clin. Endocrinol. (Oxf.) 59, 68–74 Lohmueller, K.E. et al. (2003) Meta-analysis of genetic association studies supports a contribution of common variants to susceptibility to common disease. Nat. Genet. 33, 177–182 Weaver, J.U. et al. (1992) An association between a Bcl1 restriction fragment length polymorphism of the glucocorticoid receptor locus and hyperinsulinaemia in obese women. J. Mol. Endocrinol. 9, 295–300 Russcher, H. et al. (2005) Two polymorphisms in the glucocorticoid receptor gene directly affect glucocorticoid-regulated gene expression. J. Clin. Endocrinol. Metab. 90, 5804–5810 Feng, J. et al. (2000) Five missense variants in the amino-terminal domain of the glucocorticoid receptor: no association with puerperal psychosis or schizophrenia. Am. J. Med. Genet. 96, 412–417 Moalli, P.A. and Rosen, S.T. (1994) Glucocorticoid receptors and resistance to glucocorticoids in hematologic malignancies. Leuk. Lymphoma 15, 363–374 Russcher, H. et al. (2005) Increased Expression of the Glucocorticoid Receptor-A Translational Isoform as a Result of the ER22/23EK Polymorphism. Mol. Endocrinol. 19, 1687–1696 Yudt, M.R. and Cidlowski, J.A. (2001) Molecular identification and characterization of a and b forms of the glucocorticoid receptor. Mol. Endocrinol. 15, 1093–1103 Nissim-Rafinia, M. and Kerem, B. (2002) Splicing regulation as a potential genetic modifier. Trends Genet. 18, 123–127 Stevens, A. et al. (2004) Glucocorticoid sensitivity is determined by a specific glucocorticoid receptor haplotype. J. Clin. Endocrinol. Metab. 89, 892–897 van Rossum, E.F.C. et al. (2004) Characterization of a promoter polymorphism in the glucocorticoid receptor gene and its relationship to three other polymorphisms. Clin. Endocrinol. (Oxf.) 61, 573–581
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31 Rosmond, R. et al. (2000) A polymorphism of the 5 0 -flanking region of the glucocorticoid receptor gene locus is associated with basal cortisol secretion in men. Metabolism 49, 1197–1199 32 Stephens, M. et al. (2001) A new statistical method for haplotype reconstruction from population data. Am. J. Hum. Genet. 68, 978–989 33 Oitzl, M.S. et al. (2001) Point mutation in the mouse glucocorticoid receptor preventing DNA binding impairs spatial memory. Proc. Natl. Acad. Sci. U. S. A. 98, 12790–12795 34 Cole, T.J. et al. (1995) Targeted disruption of the glucocorticoid receptor gene blocks adrenergic chromaffin cell development and severely retards lung maturation. Genes Dev. 9, 1608–1621 35 Chowdhury, T.A. (2000) Association studies of genetic polymorphisms and complex disease. Lancet 355, 1277–1278 36 Neale, B.M. and Sham, P.C. (2004) The future of association studies: gene-based analysis and replication. Am. J. Hum. Genet. 75, 353–362 37 van Rossum, E.F.C. and Lamberts, S.W.J. (2004) Polymorphisms in the glucocorticoid receptor gene and their associations with metabolic parameters and body composition. Recent Prog. Horm. Res. 59, 333–357 38 Lindpaintner, K. et al. (1995) A prospective evaluation of an angiotensin-converting-enzyme gene polymorphism and the risk of ischemic heart disease. N. Engl. J. Med. 332, 706–711 39 Rosen, C.J. et al. (1998) Association between serum insulin growth factor-I (IGF-I) and a simple sequence repeat in IGF-I gene: implications for genetic studies of bone mineral density. J. Clin. Endocrinol. Metab. 83, 2286–2290 40 Chamberlain, N.L. et al. (1994) The length and location of CAG trinucleotide repeats in the androgen receptor N-terminal domain affect transactivation function. Nucleic Acids Res. 22, 3181–3186 41 van Rossum, E.F.C. et al. (2004) Association of the ER22/23EK polymorphism in the glucocorticoid receptor gene with survival and C-reactive protein levels in elderly men. Am. J. Med. 117, 158–162 42 van Rossum, E.F.C. et al. (2003) The ER22/23EK polymorphism in the glucocorticoid receptor gene protects against white matter lesions and dementia. In 85th Annual Meeting of the Endocrine Society (Vol. abstract)
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Genetic polymorphisms and multifactorial diseases: facts and fallacies revealed by the glucocorticoid receptor gene Elisabeth F.C. van Rossum, Henk Russcher and Steven W.J. Lamberts Department of Internal Medicine, Erasmus Medical Center, Dr Molewaterplein 40, 3015 GD Rotterdam, The Netherlands
In recent years enormous progress in determining the sequence of the human genome has led to a rapid development of research into polymorphisms in genes involved in complex diseases. It is clear, however, that there are important limitations in many of these association studies. Problems with reliable and reproducable phenotyping, the number of individuals studied, racial heterogeneity, population stratification (founder effect), functionality and multiple testing often mean that studies are not reproducible. In this review we describe a number of the limitations related to this type of research; from both our own experience with studies on polymorphisms in the glucocorticoid receptor gene, and shortcomings and solutions from the literature.
or insertion polymorphisms (Table 1). Techniques to detect polymorphisms have developed rapidly in the past few years, especially with the introduction of high-throughput techniques [8] that allow researchers to screen candidate genes in many individuals in a simple, cheap and rapid manner. There is an exponential rise of association studies in recent literature. However, limitations must be recognized when conducting these studies (Box 1), and many association studies have been criticized with respect to these. In this review, we focus on the potential pitfalls when conducting genetic-association studies and offer recommendations for careful study design that will allow these type of studies to generate powerful data.
In the past few years rapid progress in determining the sequence of the human genome [1,2] has stimulated research into the role of polymorphisms in genes that might be involved in the pathogenesis of common diseases. Linkage analysis has been used widely to investigate the genetic basis of hereditary diseases [3–5]. These studies involve searching for genomic regions that contain several shared alleles more commonly than expected in affected individuals in a family. Using several genetic markers, a region can be identified that contains an allele that predisposes for a disease and which can be fine-mapped with additional markers. Linkage analysis is a powerful tool to detect rare, high-risk alleles. However, often it is difficult to narrow the region of interest adequately. Population-based association studies are a popular way to detect genes with a role in common, multifactorial diseases that have a strong environmental component [6,7]. Association studies test whether a genetic polymorphism occurs more frequently in affected cases than in healthy controls. In addition, some traits can be studied and compared between carriers and non-carriers of a polymorphism. Most polymorphisms studied are single nucleotide polymorphisms in which a nucleotide is substituted by another with a frequency of O1% in the normal population. Other types of polymorphisms include microsatellite repeat polymorphisms and either deletion
Limitations of association studies Phenotyping Reliable phenotyping, including careful recruitment of participants to rule out bias, is important in assuring the high quality of an association study. As discussed by Gambaro et al. [9], phenotypic differences between studies might occur because of variation in the definition of cases and controls in different studies, and the heterogeneous phenotype of some diseases. The sensitivity and specificity of the methods used to characterize the phenotype should also be taken into account. This applies to the researcher performing measurements and to the variance in the measurement of routine variables such as laboratory measurements. Errors (frequently undetected) are a problem in large-scale population studies that involve many data-collection steps and different researchers, and can occur at many levels (e.g. data-collection, genotyping and information processing). The influence of these errors can be reduced by increasing the sample size, minimizing inter-researcher variation (e.g. physical examination and evaluation of radiodiagnostics) and incorporating steps to double-check the parameters measured (Box 2).
Corresponding author: van Rossum, E.F.C. ([email protected]). Available online 4 November 2005
Multiple testing It is recognized that the rate of false-positive results (type I error) is relatively high when a large number of statistical tests are performed [10]. One way to diminish this problem is to statistically correct for multiple testing,
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Table 1. Genetic polymorphismsa
a
Polymorphism Single-base nucleotide substitutions (also called single-nucleotide polymorphism)
Change Change of one nucleotide
Examplea Gene encoding GR: N363S in exon 2; and BclI in intron 2
Refs [37]
Small-scale, multi-base deletions or insertions (also called deletion/insertion polymorphism)
Either insertion or deletion of 1–5 nucleotides
Gene encoding ACE: intronic 287-bp nonsense DNA domain
[38]
Microsatellite repeat variations (also called short tandem repeats)
Repeats of several nucleotides (2, 3 or 4)
Gene encoding IGF-1: CA repeat in promoter Gene encoding AR: CAG repeat in exon 1
[39,40]
Abbreviations: ACE, angiotensin-converting–enzyme; AR, androgen receptor; IGF-1, Insulin-like growth factor 1.
and other factors also help to reduce the number of falsepositive results. A good rationale for the association study, an a priori justification, increases the chances of finding true-positive results. For example, glucocorticoids (GCs) exert the majority of their effects by binding to the glucocorticoid receptor (GR), which makes the gene that encodes the GR a candidate when studying the genetic basis of differences in the response to GCs in the normal population. Initially dexamethasone-suppression tests in vivo were performed to investigate differences in sensitivity to GCs between carriers and noncarriers of several polymorphisms of the GR including N363S, ER22/23EK (two, linked singlenucleotide polymorphisms, the second of which results in an amino-acid change), and the intronic BclI polymorphism. The N363S and the BclI polymorphisms increase the response to dexamethasone, which indicates an increase in sensitivity to the effects of GCs [11,12]. By contrast, the ER22/23EK polymorphism decreases the response to dexamethasone, which indicates relative resistance to GCs (Box 3) [13]. These findings provide a rationale for our next hypotheses, which concern the association between GR polymorphisms and other parameters that are affected by GCs, such as body composition and metabolic parameters (insulin and lipids). As expected, we find associations between the ER22/23EK and several measures of decreased GC effects (lower insulin levels, lower cholesterol levels and beneficial changes in body composition) (Box 3) [13,14], whereas the N363S and the BclI polymorphisms are associated with measures of increased GC effects (more body fat, bigger insulin response to dexamethasone and less lean-body mass) [11,12]. Another way to reduce the rate of false-positive results is to increase statistical power by, for example, increasing the sample size [10]. Replication of study outcomes Another important aspect is confirming an association in a different study population, which diminishes the risk of findings occurring by chance. The phenotypic changes in carriers of the N363S, ER22/23EK and BclI polymorphisms in the subjects in whom the dexamethasone suppression test were performed matched the changes observed in GC sensitivity. In a study in Dutch, elderly, healthy individuals, the observation that carriers of the BclI polymorphism (G-allele) have a lower body-mass index (BMI) than non-carriers has www.sciencedirect.com
been confirmed in a separate population of elderly Dutch men [12]. However, one risk of trying to replicate an observed association in a different ethnic population is that, if the replication fails, the first association might be considered false-positive. It is important to realize that polymorphisms might have different effects in different ethnic backgrounds. First, the frequency of polymorphisms can differ between different ethnic groups. In this respect is it intriguing that, for example, this N363S genotype, which was found to be 3.1% (allele frequency) in the elderly healthy Dutch Caucasian population, is highly frequent in an Australian population (allele frequency 7.4%) [15], whereas in other reports no N363S-carriers have been detected in a Chinese population [16] nor in a Japanese population [17], and an allele frequency of 0.3% was found in a population of South Asian origin living in northeast England [18].
Box 1. Fallacies of polymorphism studies † † † † † † † † †
Unreliable phenotyping Few individuals studied Racial heterogeneity Population stratification (founder effect) Gender differences Age differences Function of the genetic variation not studied Statistical analysis (false positive results by multiple testing) Publication bias
Box 2. Requirements to assure high quality of association studies † Good phenotyping (careful recruitment of subjects and datacollection, high sensitivity and specificity of tests, minimizing inter-researcher variation, and double-checking measured parameters) † Large number of individuals studied (depending on the frequency of the studied gene variant) † Homogeneity of the study population with respect to ethnicity, gender, age and environmental factors or the use of statistical corrections for these confounders † Replication in different study population(s) † A good rationale for the association under investigation to increase the a priori justification † Statistical analysis using multiple testing corrections † Confirming results in vivo with experiments in vitro † Unraveling the molecular basis of the mechanism of the gene variation studied
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Box 3. Simplified scheme of a relationship between a genetic polymorphism and a phenotype Table I shows data on the ER22/23EK polymorphism in the gene that encodes the GR. This polymorphism consists of two, singlenucleotide polymorphisms in codons 22 and 23, the latter of which results in an amino acid change from arginine (R) to lysine (K). It is likely that this alters the secondary structure of GR mRNA, forcing a shift towards the use of the AUG1 rather than the AUG27 codon as the start codon. The preferred use of AUG1 start codon in the ER22/23EK variant alters the ratio between GR-A (transcriptionally less active) and GR-B (transcriptionally more active) [26,27]. Indeed, experiments in vitro show a reduced trans-activating capacity of the ER22/23EK variant, whereas trans-inhibition is unchanged because the different translational isoforms are equally potent at inhibiting NF-kB. In addition, the ability of GR to upregulate expression of GILZ is reduced in ER22/23EK
homozygotes, whereas trans-repression of IL-2 does not differ from the controls [23]. In dexamethasone-suppression tests, carriers of the ER22/23EK polymorphism have significantly higher cortisol levels than noncarriers, which indicates that carriers of ER22/23EK are relatively resistant to the effects of GCs with respect to the sensitivity of the negative-feedback mechanism [13]. The ER22/23EK polymorphism is associated with several phenotypic changes, including increased insulin sensitivity, lower total and lowdensity lipoprotein cholesterol levels, lower C-reactive protein levels, beneficial sex-specific body composition (greater height, lean mass and muscle strength in males, and smaller waist and hip circumferences in females), lower risk of developing dementia and cerebral white matter lesions, and longevity [13,14,41,42]. All these phenotypic changes can be explained by subtle decreases in the sensitivity to GCs.
Table I Polymorphism ER22/23EK (GAGAGG/ GAAAAG)
GR protein GR-A:GR-B increases
In vitro Decreased transactivation
In vivo Decreased response to 1 mg dexamethasone
Phenotype Healthier metabolic profile (insulin, total and lowdensity lipoprotein-cholesterol and C-reactive protein levels decrease)
No change in trans-repression Beneficial effects on body composition Decreased risk of dementia and cerebral white matter lesions Longevity
Second, some combinations of a polymorphism and other polymorphic genes, which vary between ethnic groups, might also lead to a different phenotype. For GCs, combinations of either variations or mutations in other genes that are involved in GC action are also related to some phenotypes. In this context, Draper et al. [19] have shown that mutations in the genes that encode 11 b-hydroxysteroid dehydrogenase type 1 (11b-HSD1), which catalyzes the reduction of inactive cortisone to active cortisol and, thereby, regulates tissue-specific bioavailabilty of GCs, and hexose-6phosphate dehydrogenase lead to a phenotype in which there is cortisone reductase deficiency (which resembles polycystic ovary syndrome with adrenocorticotropin-mediated androgen excess). Individuals with only the 11b-HSD1 mutation do not have this pathological phenotype. A third cause of different outcomes in replication studies is that environmental factors might contribute to the effects of a polymorphism on phenotype. In the example of the N363S polymorphism in the GR gene, hypersensitivity to GCs in carriers of this polymorphism seems to result in easier fat storage caused by hypersensitive insulin secretion in response to GCs [11,20]. In a highfat diet environment, these carriers are more likely to become obese than in a setting in which a low-fat diet is more common and, thus, this variant might result in different phenotypes. In addition, population stratification (also referred to as the ‘founder effect’) is a major problem in association studies [6]. The founder effect is the tendency for high frequencies of both some genes and particular diseases within a population to lead to falsepositive associations. Lohmueller et al. [21] have suggested that larger sample sizes and studies with www.sciencedirect.com
family-based controls will help to avoid this problem and to make results more replicable. Sex-specific and age-specific associations Sex-specific and age-dependent association of polymorphisms is also described, and the ER22/23EK variant is an example of a sex-specific polymorphic association. Young, adult, male carriers of ER22/23EK are, on average, taller, have more lean mass and are stronger (Box 3), whereas female carriers have a tendency towards lower fat mass, and smaller waist and hip circumferences [14]. Both associations can be explained by a relative resistance to the effects of GCs, as shown previously in a population including both men and women [13]. Why this polymorphism is associated with different changes in body composition in men and women is unclear, but hormonal factors might be involved. An example of an age-dependent association of a GR polymorphism is the relationship between the BclI and BMI. In middle-aged subjects this variant is associated with an increase in the BMI and the waist-to-hip ratio (WHR) [22]. By contrast, in two elderly populations this variant is associated with lower BMI [12]. However, because BMI does not differentiate between fat mass and lean mass we have also studied body composition using dual energy X-ray absorptiometry (DEXA) scans. We observed that carriers of the BclI variant allele (G-allele) have a tendency towards lower lean mass but there are no differences in fat mass, which indicates that carriers of this variant suffer more from sarcopenia during the normal aging process than non-carriers [12]. Both the increased BMI and WHR in middle-aged individuals (more abdominal fat mass) and the decreased BMI in older individuals (more loss of lean mass during aging) can
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be explained by an increased sensitivity to GCs, as shown previously [12]. Thus, polymorphisms can be associated with particular hormonal and metabolic conditions, which, because of numerous other processes, result in different phenotypes at different ages. Therefore, in replication studies it is important to take into account factors such as gender and age as well as ethnicity. Biological plausibility Another important feature of association studies is that there should be a biological plausibility for a candidate gene. Usually, candidate genes encode a factor that is important in a particular pathway and, thus, might be involved in the pathophysiology of a disease. Also, linkage analysis can lead to the identification of candidate genes. However, an association between a polymorphism and a phenotype does not necessarily indicate a causal relationship: a polymorphism can be in linkage disequilibrium with another polymorphism in the same gene or even in an adjacent gene. Testing of the effects of a polymorphism in vitro can help to distinguish between functional and non-functional polymorphisms. For the GR gene, the ER22/23EK polymorphism influences the trans-activating capacity of the GR, but trans-repression of NF-kB is unaltered [23]. In addition, Russcher et al. have studied both upregulatory and downregulatory effects of GR polymorphisms by investigating the effects of the ER22/23EK variant on GC-induced leucine zipper (GILZ) protein and interleukin-2 (IL-2), respectively. Although upregulation of GILZ is reduced in homozygous carriers of ER22/23EK, transrepression of IL-2 is unaltered compared with the control group (Box 3). This is consistent with our findings in vivo that there is reduced sensitivity to GCs in carriers of ER22/23EK. Russcher et al. have also studied the effects of the N363S variant, and found that this polymorphism
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increases the trans-activating capacity, both in vitro and ex vivo [23]. This is consistent with the association between the N363S variant and increased sensitivity to GCs in vivo [11]. Furthermore, the location of the polymorphism in a gene is important with respect to function. For example, the N363S polymorphism changes asparagine to serine, which creates a potential phosphorylation site that might be relevant for DNA binding by the GR [24,25]. However, the exact effect of the N363S polymorphism is not elucidated. By contrast, the molecular mechanism through which the ER22/23EK polymorphism reduces sensitivity to GCs has been clarified recently [26]. Yudt et al. [27] report that at least two methionine initiation codons in the GR mRNA, AUG1 and AUG27, result in two translation variants, GR-A (94 kDa) and GR-B (91 kDa). The shorter GR-B protein has a stronger trans-activating effect in transient transfection experiments [27], and the sensitivity to GCs in carriers of ER22/23EK is lower because more of the longer, less transcriptionally active GR-A isoform is formed (Box 3) [26]. Indeed, Russcher et al. show that the reduction in trans-activating capacity of the GR in carriers of ER22/23EK is explained by the change in GR-A:GR-B. Trans-inhibition seems to be unchanged because the isoforms are equally potent at inhibiting the trans-activating activity of NF-kB [23]. It is likely that this polymorphism alters the secondary structure of GR mRNA, which forces more translation to be initiated from AUG1. The functional effects of intronic polymorphisms is a difficult issue. Often, intronic polymorphisms are considered to be non-functional because they do not change the coding sequence. However, they might still be involved in the splicing process by, for example, changing the sequence of so-called intronic splicing silencers and enhancers, and through other mechanisms that are important for gene expression [28].
Linkage
TthIII1
1.00 (high)
N363S
BclI
0.22 (low) ER22/23EK ER22/23EK
BclI
N363S
TthIII1
Figure 1. Haplotype reconstruction calculations according to Stephens et al. (Phase Reconstruction Method) [32]. The polymorphisms in the GR (ER22/23EK, BclI, N363S and TthIII1) are indicated on both axes. The colors indicate the calculated degree of linkage (red indicates high linkage, assigned a value of 1.00; blue indicates low linkage, assigned a value of 0.22). The TthIII1 polymorphism is linked to the ER22/23EK variant (red), whereas TthIII1 does not show linkage with the BclI polymorphism (blue). In addition, the ER22/23EK and BclI polymorphisms (red) are also linked because the presence of one excludes the other on the same allele. www.sciencedirect.com
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The molecular mechanisms that account for the effects of majority of polymorphisms have not been identified. Recently, methods other than the association between a single polymorphism and phenotypic data (e.g. haplotype analysis) have become popular to study the effects of polymorphisms. Haplotypes have been constructed that consist of alleles that contain several polymorphisms in one gene to identify the association between phenotypic changes and particular risk alleles. In the GR gene, Stevens et al. [29] have constructed a haplotype that is associated with an increased sensitivity to GCs. Interestingly, the three polymorphisms described in this review are mutually exclusive (i.e. they never occur on the same allele) [30]. Although this is probably a result of chance during evolution, this naturally occurring phenomenon can simplify the analysis of association studies that use these polymorphisms. A fourth restriction-fragmentlength polymorphism in the promoter region of the GR gene (TthIII1) [31] is linked to the ER22/23EK allele [30]. The combined allele (TthIII1 T and ER22/23EK) is associated with relative resistance to GCs, whereas there is no difference in sensitivity of the TthIII1 T allele itself (TthIII1 T and 22/23ER) compared with non-carriers of both variant alleles (TthIII1 C and 22/23ER) [30]. Figure 1 shows a graphical reproduction of haplotype reconstruction calculations according to Stephens et al. (Phase Reconstruction Method) [32]. Animal models can also be used to show the in vivo effects of a specific mutation. For example, Oitzl et al. [33] report a mutant mouse (GRdim/dim) in which homozygous A458T mutation of the GR makes it unable to dimerize. GR-knockout mice (GRK/K) do not survive after birth because of respiratory insufficiency as a consequence of impaired fetal lung development [34]. Studying the in vivo function of polymorphisms in this way contributes to the understanding of the associations observed in humans. Publication bias A perceived problem with association studies is that of publication bias, whereby it is thought that journals tend to publish positive rather than negative results [35]. However, a large meta-analysis of 301 publications on 25 associations shows that publication bias is unlikely to account for the lack of reproducibility of association-study results [21]. In 11 of the 25 associations examined, the results were replicable (this is, however, !50%). From this study, Lohmueller et al. state that underpowered, non-significant studies of real associations with modest genetic effects can reasonably account for much of the variability in replication. This meta-analysis reinforces the need for well-designed, sufficiently powered replication studies of every positive association between a common polymorphism and a common complex disease. Conclusions Worldwide, many genetic data became available with the Human Genome Project, and technical and informatic methods have improved rapidly. In the future, there is likely to be a shift towards whole-genome-association studies [36], and careful study design is a number one priority for these future studies. The set-up of these www.sciencedirect.com
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studies should focus on a good rationale for the association under study, careful phenotyping, large numbers of individuals in the study, homogeneity of the study population, correction for multiple testing, and unraveling the underlying mechanisms of the observed associations by in vitro experiments, animal models and molecular methods. In addition, replication of the association in a comparable study population reduces the risk of the findings occurring by chance. Taking these factors into account, association studies on polymorphisms can be a powerful tool to detect relationships between genetic variations and complex diseases or traits. Acknowledgements These studies were supported financially by grant 903–43–093 from the Netherlands Organization for Scientific Research (NWO) and the NWORIDE (Research Institute for Diseases of the Elderly), The Netherlands.
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