Hardy-Weinberg analysis of a large set of published association studies reveals genotyping error and a deficit of heterozygotes across multiple loci

  • Srijan Sen1Email author and

    Affiliated with

    • Margit Burmeister1, 2

      Affiliated with

      Human Genomics20083:36

      DOI: 10.1186/1479-7364-3-1-36

      Received: 7 April 2008

      Accepted: 7 April 2008

      Published: 1 September 2008

      Abstract

      In genetic association studies, deviation from Hardy-Weinberg equilibrium (HWD) can be due to recent admixture or selection at a locus, but is most commonly due to genotyping errors. In addition to its utility for identifying potential genotyping errors in individual studies, here we report that HWD can be useful in detecting the presence, magnitude and direction of genotyping error across multiple studies. If there is a consistent genotyping error at a given locus, larger studies, in general, will show more evidence for HWD than small studies. As a result, for loci prone to genotyping errors, there will be a correlation between HWD and the study sample size. By contrast, in the absence of consistent genotyping errors, there will be a chance distribution of p-values among studies without correlation with sample size. We calculated the evidence for HWD at 17 separate polymorphic loci investigated in 325 published genetic association studies. In the full set of studies, there was a significant correlation between HWD and locus-standardised sample size (p = 0.001). For 14/17 of the individual loci, there was a positive correlation between extent of HWD and sample size, with the evidence for two loci (5-HTTLPR and CTSD) rising to the level of statistical significance. Among single nucleotide polymorphisms (SNPs), 15/23 studies that deviated significantly from Hardy-Weinberg equilibrium (HWE) did so because of a deficit of hetero-zygotes. The inbreeding coefficient (F(is)) is a measure of the degree and direction of deviation from HWE. Among studies investigating SNPs, there was a significant correlation between F(is) and HWD (R = 0.191; p = 0.002), indicating that the greater the deviation from HWE, the greater the deficit of heterozygotes. By contrast, for repeat variants, only one in five studies that deviated significantly from HWE showed a deficit of heterozygotes and there was no significant correlation between F(is) and HWD. These results indicate the presence of HWD across multiple loci, with the magnitude of the deviation varying substantially from locus to locus. For SNPs, HWD tends to be due to a deficit of heterozygotes, indicating that allelic dropout may be the most prevalent genotyping error.

      Keywords

      meta-analysis polymorphism variant deviation

      Introduction

      Genotyping errors are an important and increasingly recognised problem in modern genetics [1]. Traditional family-based genetic studies allow for straightforward identification of genotyping errors through a familial Mendelian inheritance check. Over the past decade, however, there has been increasing interest in case-control association studies, a type of study in which investigators generally compare a group of subjects having a particular disease with another group not having the disease, to identify a genotypic difference between the groups. Unfortunately, these association studies do not allow for simple inheritance checks to identify errors and, as a result, we have limited insight into the prevalence and nature of genotyping errors in published association studies.

      Hardy-Weinberg law states that if conditions of population equilibrium are met (random mating and negligible mutation, migration, stratification, genetic drift and selection), then genotype frequencies should fit a predictable binomial distribution calculable from the allele frequencies. Significant deviation from the predicted distribution has been used as a marker for genotyping error.[2] Previous work has estimated that the control sample genotype distribution violates Hardy-Weinberg equilibrium (HWE) in approximately 10 per cent of published association studies [35]. Furthermore, exclusion of studies that violate HWE alters the results of a substantial fraction of gene association meta-analyses [6].

      The inbreeding coefficient (F(is)) can be used as a measure of the degree and direction of deviation from HWE (HWD). Positive F(is) values indicate an excess of homozygotes and negative F(is) values indicate a deficit of homozygotes. Salanti and colleagues [4] found that with a moderate level of HWD (F(is) = 0.10), only 7 per cent of association studies had at least 80 per cent power to find significant evidence for violation of HWE. Because of this low level of power, focusing on statistically significant violation of HWE in individual association studies substantially limits the insight that we can gain into potential genotyping errors from HWE analysis [7]. A complementary approach that bypasses the problem of limited power in individual studies is the analysis of HWD patterns across a set of studies. As originally demonstrated by Weir,[8] if a locus is prone to genotyping error, the evidence for HWD will increase with increasing sample size. By contrast, if there is no substantial genotyping error, or if the error is random, there will be no relationship between HWD and sample size. By examining a set of studies at a given locus, we can learn about the level of genotyping error present at that locus. Furthermore, by looking at the evidence across multiple loci, we can gain insight into the level and nature of genotyping error in association studies in general.

      Here, we investigate: (1) the relationship between sample size and HWD across well-studied loci, and (2) the direction of deviation in a set of association studies compiled from previous meta-analyses.

      Materials and methods

      Studies

      Genetic loci for analysis were identified through published meta-analyses. Meta-analyses were identified through PubMed at the National Library of Medicine, limiting the search to meta-analyses published between 2001 and 2005 and using the search terms: (1) association genetic; (2) association polymorphism; (3) association variant. These results were supplemented by a database of meta-analyses compiled by Ioannidis and colleagues [9, 10]. Loci were subsequently chosen using the criteria: (1) biallelic markers; (2) at least ten independent studies; and (3) sample size data for all three genotype groups included in the publication. For each included study, we recorded the control group sample size for the three genotype groups (Supplementary Table 1).
      Table 1

      Relationship between sample size and Hardy-Weinberg exact test p-values for individual loci

      Variant

      Variant

      No. of studies

      Correlation (p-value)

      PON192

      SNP

      39

      -0.120 (0.467)

      GPIIIa

      SNP

      33

      -0.050 (0.783)

      5-HTTLPR

      Repeat

      31

      -0.444(0.014)

      L-myc-ECORI

      Repeat

      28

      -0.296(0.126)

      MTHFR677

      SNP

      23

      -0.201(0.358)

      VDR

      SNP

      17

      -0.140(0.593)

      CTSD

      SNP

      16

      -0.582(0.018)

      DRD2

      SNP

      21

      -0.191(0.407)

      Neurod1

      SNP

      14

      -0.433(0.122)

      TPH

      SNP

      13

      0.297(0.324)

      COLIAI

      SNP

      13

      0.188(0.538)

      ADDI

      SNP

      12

      -0.275(0.387)

      SRD5A2

      SNP

      12

      -0.326(0.301)

      BSMI

      SNP

      11

      -0.188(0.503)

      IL-I

      SNP

      11

      -0.520(0.101)

      CYPI7

      SNP

      10

      -0.175(0.628)

      Analyses

      The most straightforward way to assess HWD in a set of studies investigating a given locus is to pool the genotype cell counts from each of the relevant studies and assess HWD among the three pooled genotype groups. All of these studies investigated population samples with different ethnicities, however, and consequently different allele frequencies. As a result, simply combining data from different studies would find substantial HWD due to lack of heterozygotes, even in the absence of geno-typing error.

      We took an alternative approach to assessing HWD among a set of studies investigating a given locus. For each locus, we determined the correlation between the HWD exact test p-value of each study and study sample size. The stronger the correlation, the stronger the evidence for HWD at that locus. Given that many included studies had small homozygote minor allele cell counts (fewer than five subjects), and that the chi square test is an unreliable test of HWD in the presence of small cell counts, an exact test was used to determine the strength of evidence for HWD [11].

      In addition to investigating the correlation between HWD and sample size among studies investigating each individual locus, we also wanted to explore the strength and significance of this correlation across all studies, regardless of locus. A straightforward assessment of correlation between sample size and HWD, however, would be confounded by statistical artefact. Specifically, the mean sample size varies substantially across loci. Because the level of HWD varies substantially across loci (as demonstrated by our initial analyses), a correlation between sample size and HWD p-value among the set of all studies could merely represent that loci with larger mean sample sizes have greater HWD. In order to control for this potential confound, we calculated a standardised sample size for each study, such that each locus had a mean sample size = 50 and sample size standard deviation = 10. Subsequently, we calculated the strength and significance of the correlation between this locus-standardised sample size and HWD p-value for the set of all studies. The raw sample size for each study was converted to a T-score so that each locus had an overall mean standardised sample size of 50 ± 10. Subsequently, the correlation between standardised sample size and exact test p-value was calculated for the set of all studies.

      Inbreeding coefficient was calculated using the following formula:
      F ( is ) = P ( AA ) / P ( A ) + P ( aa ) / P ( a ) 1 http://static-content.springer.com/image/art%3A10.1186%2F1479-7364-3-1-36/MediaObjects/40246_2008_Article_217_Equa_HTML.gif

      where p = frequency; A = major allele; a = minor allele; AA = homozygous major allele; aa = homozygous minor allele. All analyses were carried out in SPSS 12.0 (SPSS Inc., Chicago, IL, USA).

      Results

      In total, 325 studies, investigating 17 loci, fit the criteria for analysis. Twenty-eight studies (9 per cent) showed significant HWD. This proportion is in line with the results of previous studies [35]. The number of studies per locus ranged from ten (CYP1) to 39 (PON1 Q192R). The average sample size per locus ranged from 71 (DRD2) to 1,020 (ADD1) (Figure 1).
      http://static-content.springer.com/image/art%3A10.1186%2F1479-7364-3-1-36/MediaObjects/40246_2008_Article_217_Fig1_HTML.jpg
      Figure 1

      Hardy-Weinberg disequilibrium (HWD) p -value vs sample size across 325 studies.

      Among individual loci, 14/17 variants showed a negative correlation between sample size and HWD p- value, indicating that the majority of studied variants show evidence of consistent genotyping error. Overall, the correlations ranged from R = 0.29 (TPH) to R = -0.59 (CTSD) and was significant for two loci (CTSD and 5-HTTLPR) (Table 1). Among the set of all 325 studies, 23 studies had a homozygote minor allele cell count = 0. The strength and significance of correlations were not substantially changed with the exclusion of these studies (data not shown).

      The 325 studies investigated 15 single nucleotide polymorphism (SNP) loci (267 studies) and two repeat polymorphism loci (58 studies). The percentage of individual studies that significantly deviated from HWE was the same (9 per cent) for both the SNP and repeat polymorphism categories. Similarly, the standardised sample size-HWD correlation was statistically significant for both SNP (p = 0.018) and repeat polymorphism (p = 0.004) groups. Of the 28 studies that showed significant deviation from HWE, 23 studies were SNP studies and five were repeat polymorphism studies. Fifteen out of 23 HWE-violating SNP studies showed a deficit of heterozygotes, while only one in five HWE-violating repeat polymorphism studies showed a deficit of heterozygotes. In addition, for SNP studies, there was a significant correlation between F(is) and HWD p-value (R = 0.190; p = 0.002), while repeat polymorphisms showed no evidence of correlation (R = 0.03). In the set of all 325 studies, there was a significant correlation between standardised sample size and HWD (R = 0.18; p = 0.001) (Figure 2).
      http://static-content.springer.com/image/art%3A10.1186%2F1479-7364-3-1-36/MediaObjects/40246_2008_Article_217_Fig2_HTML.jpg
      Figure 2

      Mean F(is) statistic stratified by variant type.

      To gain insight into the reliability of the results found among controls, and to help to differentiate between selection and genotyping error as the primary cause of HWD, we investigated the correlation between F(is) among cases (F(cases)) and controls (F(controls)) for each individual study. If the HWD among control subjects is due to selection, then we would expect the genotype that is deficient among controls to be overrepresented among cases, and thus F(is) among control and case studies would show a negative correlation. By contrast, if the HWD among control subjects is due to genotyping error, then we would expect the genotype that is deficient among controls also to be deficient among cases, and thus the inbreeding coefficients would show a positive correlation. Lastly, if the HWD among controls were due purely to chance, then we would expect no correlation whatsoever between F(is) statistics.

      Looking across 12 loci and 221 studies for which we had data for both cases and controls, we found a significant positive correlation between F (controls) and F (cases) (r = 0.174; p = 0.01). Further, the correlation was in the positive direction for 11/12 loci. These findings indicate that for any given study, the direction and magnitude of HWD among cases is similar to the direction of magnitude of HWD among controls. This result is consistent with genotyping error rather than selection as the primary source of HWD, and provides further evidence that these findings are not due purely to chance.

      Discussion

      The primary finding of this analysis was the identification of HWD across a large subset of published association studies investigating both SNP and repeat variants. Although deviation was present at most loci, the degree of deviation varied substantially across loci. At least among SNP studies, the predominant cause of this deviation was a deficit of heterozygotes.

      In addition to genotyping error, other factors can contribute to HWD. For example, strong selection against a specific genotype can skew the genotypic distribution of a population. In fact, HWD among cases has been used as a test for genotype phenotype association,[12, 13] and Wittke-Thompson and colleagues [14] have demonstrated a pattern of expected deviation among cases and, under some conditions, controls for various disease models. Our finding that the HWD among cases has a strong tendency to be in the same direction as the deviation found among controls is contrary to the expected result under the selection model, however.

      Population stratification is another factor that can contribute to HWD. To eliminate the possibility of ethnic differences between studies causing stratification and HWD in our study, we did not pool the three genotype counts for all studies investigating a given locus and calculate a HWD p-value from this pooled sample. Instead, for each locus, we determined the correlation between the HWD exact test p-value and study sample size. Thus, any effect of stratification in our study is not due to allele frequency differences between studies investigating the same locus. Although population stratification within individual studies may contribute to HWD in our study, there are multiple considerations that are likely to mitigate its effect. First, most studies included in our analysis utilise samples that are ethnically homogeneous. Secondly, a significant proportion of the studies formally tested and rejected the presence of population stratification in their sample. Thirdly, the consistent direction of deviation across studies and the different patterns of deviation found between SNP and repeat variants are more consistent with genotyping error than stratification as a primary cause of HWD. We cannot however, definitively exclude stratification as a contributing cause of HWD among these studies.

      Previous studies investigating the nature and consequences of genotyping error based on simulations or experimental samples specifically designed to assess genotyping error have proposed allelic dropout as one of the most frequent causes of gen-otypic error [2, 15, 16]. Intuitively, it is clear that heterozygotes, which get half a dose of each allele compared with homozygotes, may be more often missed or misclassified. In fact, even in the most sophisticated high-throughput algorithms, heterozygotes have a lower call rate than homozygotes [17]. Our investigation of a large set of published studies is consistent with this prediction. Further, our findings are consistent with the hypothesis that genotyping error is not stochastic, but more common at certain loci [1821]. These findings raise concerns about the level and widespread nature of genotyping errors in genetic association studies and the conclusions drawn from those studies. In light of this finding, the approach employed here could be useful to identify loci most prone to error. For example, Yonan and colleagues [22] recently used HWD to identify genotyping errors at the 5hydroxytryptamine transporter 5-HTTLPR variant and developed an alternate assay less prone to error.

      We propose that future genetic association meta-analyses examine the correlation between sample size and HWE to determine the level of genotyping error among included studies. Further, we believe that the method and points that this analysis highlight can be of utility to investigators performing individual association studies. First, this result should caution investigators against dismissing the possibility of genotyping error merely because their sample does not show significant deviation from HWE. Instead, investigators should further examine the magnitude and direction of deviation. For instance, a large F(is) statistic in the same direction among cases and controls raises the concern for genotyping error, and should prompt investigators to perform genotyping quality checks.
      Supplementary Table

      Included association studies stratified by locus

      Study

      locus

      std N

      a1/a1

      a1/a2

      a2/a2

      N

      p-value

      Brummett

      5-HTTLPR

      47.62162

      33

      91

      78

      202

      0.4612

      Comings

      5-HTTLPR

      47.72973

      58

      95

      51

      204

      0.3294

      Du

      5-HTTLPR

      46.75676

      40

      86

      60

      186

      0.3763

      Ebstein

      5-HTTLPR

      43.24324

      32

      66

      23

      121

      0.3611

      Flory

      5-HTTLPR

      48.86486

      37

      112

      76

      225

      0.7835

      Greenberg

      5-HTTLPR

      58.16216

      66

      217

      114

      397

      0.0328

      Gusatavsson

      5-HTTLPR

      46.16216

      35

      83

      57

      175

      0.6461

      Gusatavsson

      5-HTTLPR

      43.45946

      22

      66

      37

      125

      0.4725

      Hamer

      5-HTTLPR

      70.97297

      108

      336

      190

      634

      0.053

      Herbst

      5-HTTLPR

      59.67568

      79

      198

      148

      425

      0.3712

      Hu

      5-HTTLPR

      77.72973

      135

      390

      234

      759

      0.2373

      Jorm

      5-HTTLPR

      77.72973

      155

      350

      254

      759

      0.0896

      Katsuragi

      5-HTTLPR

      42.16216

      66

      31

      4

      101

      1

      Kumakiri-TCI

      5-HTTLPR

      44.48649

      85

      48

      11

      144

      0.26

      Lang

      5-HTTLPR

      49.02703

      41

      102

      85

      228

      0.2748

      Lesch

      5-HTTLR

      52.05405

      52

      141

      91

      284

      0.9039

      Lesch

      5-HTTLPR

      48.64865

      43

      106

      72

      221

      0.7841

      Mazzanti

      5-HTTLPR

      48.32432

      41

      106

      68

      215

      1

      Melke

      5-HTTLPR

      46.97297

      35

      84

      71

      190

      0.2915

      Murakami

      5-HTTLPR

      46.91892

      124

      55

      10

      189

      0.2523

      Nakamura

      5-HTTLPR

      46.75676

      128

      55

      3

      186

      0.4221

      Osher-TPQ

      5-HTTLPR

      44.7027

      39

      73

      36

      148

      0.8703

      Ricketts

      5-HTTLPR

      38.7027

      10

      14

      13

      37

      0.185

      Samachowiec

      5-HTTLPR

      43.51351

      18

      67

      41

      126

      0.356

      Schmidt

      5-HTTLPR

      39.78378

      12

      29

      16

      57

      1

      Sen

      5-HTTLPR

      59.13514

      83

      183

      149

      415

      0.0557

      Stoltenberg

      5-HTTLPR

      41.35135

      17

      45

      24

      86

      0.6704

      Strobel

      5-HTTLPR

      43.35135

      22

      67

      34

      123

      0.3619

      Tsai

      5-HTTLPR

      47.08108

      100

      71

      21

      192

      0.1629

      Umekage

      5-HTTLPR

      49.89189

      161

      70

      13

      244

      0.156

      O'Donnell

      ACE DI

      54.48314

      492

      845

      313

      1650

      0.1486

      O'Donnell

      ACE DI

      53.34439

      437

      719

      288

      1444

      0.8315

      Agerholm-Larsen

      ACE DI

      89.81205

      2113

      4006

      1922

      8041

      0.7849

      Barley

      ACE DI

      46.52294

      55

      109

      46

      210

      0.678

      Benetos

      ACE DI

      46.06965

      47

      56

      25

      128

      0.2764

      Berge

      ACE DI

      46.13599

      34

      77

      29

      140

      0.3092

      Busjahn

      ACE DI

      46.13046

      33

      79

      27

      139

      0.1272

      Cambien

      ACE DI

      49.41404

      200

      390

      143

      733

      0.0632

      Castellano

      ACE DI

      46.40685

      76

      90

      23

      189

      0.7523

      Celermajer

      ACE DI

      46.37922

      49

      89

      46

      184

      0.6599

      Friedl

      ACE DI

      45.72692

      16

      37

      13

      66

      0.4583

      Kauma

      ACE DI

      48.20896

      148

      264

      103

      515

      0.4783

      Kiema

      ACE DI

      46.64456

      75

      115

      42

      232

      0.8941

      Kiema

      ACE DI

      46.65561

      54

      127

      53

      234

      0.239

      Ludwig

      ACE DI

      47.58983

      117

      206

      80

      403

      0.6152

      Mattu

      ACE DI

      52.1393

      442

      556

      228

      1226

      0.025

      Puija

      ACE DI

      46.09176

      46

      70

      16

      132

      0.203

      Rigat

      ACE DI

      45.80431

      29

      37

      14

      80

      0.8164

      Tiret

      ACE DI

      46.44555

      60

      103

      33

      196

      0.3825

      Busch

      ADD1

      48.02101

      405

      76

      0

      481

      0.0608

      Clark

      ADD1

      46.77722

      162

      80

      14

      256

      0.347

      Ju

      ADD1

      49.49696

      166

      357

      225

      748

      0.3028

      Manunta

      ADD1

      45.95909

      80

      26

      2

      108

      1

      Morrison

      ADD1

      56.05307

      1227

      643

      64

      1934

      0.0747

      Mulatero

      ADD1

      46.28524

      117

      43

      7

      167

      0.2699

      Narita

      ADD1

      46.88778

      56

      150

      70

      276

      0.1494

      Nicod

      ADD1

      46.79934

      167

      83

      10

      260

      1

      Persu

      ADD1

      46.41791

      121

      63

      7

      191

      0.8258

      Ranade

      ADD1

      51.2272

      296

      530

      235

      1061

      0.95

      Shioji

      ADD1

      67.08184

      241

      560

      305

      06

      0.428

      Yamagishi

      ADD1

      60.96739

      599

      365

      859

      2823

      0.967

      berg

      bsm1

      41.67598

      2

      9

      8

      49

      0.504

      boschitsch

      bsm1

      48.04469

      36

      67

      60

      63

      0.0539

      garnero

      bsm1

      53.906

      38

      34

      96

      268

      0.523

      gennari

      bsm1

      61.84358

      7

      29

      20

      40

      0.087

      gomez

      bsm1

      47.93296

      27

      72

      62

      6

      0.5075

      hansen

      bsm1

      50.11173

      46

      98

      56

      200

      0.7787

      jorgensen

      bsm1

      69.60894

      77

      276

      96

      549

      0.209

      kiel

      bsm1

      45.2514

      22

      7

      74

      113

      22E-10

      kroger

      bsm1

      40.22346

      2

      4

      7

      23

      0.3787

      langdahl

      bsm1

      43.40782

      25

      34

      2

      80

      0.848

      marc

      bsm1

      44.63687

      9

      59

      24

      02

      0.634

      mcclure

      bsm1

      44.69274

      8

      43

      52

      03

      1

      melhus

      bsm1

      43.18436

      7

      35

      34

      76

      0.7943

      riggs

      bsm1

      44.02235

      5

      36

      40

      9

      0.765

      vandevyer

      bsm1

      71.78771

      107

      306

      75

      588

      0.2098

      aerssens

      COLIA1

      50.90116

      151

      73

      5

      239

      0.295

      alvarez

      COLIA1

      44.65116

      2

      3

      0

      24

      1

      de vernejoul

      COLIA1

      47.93605

      85

      5

      1

      37

      0.0267

      efstathiodou

      COLIA1

      47.18023

      73

      29

      9

      111

      0.043

      heegaard

      COLIA1

      47.18023

      82

      27

      2

      111

      1

      hustmyer

      COLIA1

      46.22093

      58

      6

      4

      78

      0.079

      keen

      COLIA1

      47.73256

      85

      40

      5

      130

      1

      langdahl

      COLIA1

      48.13953

      94

      48

      2

      44

      0.664

      liden

      COLIA1

      45.90116

      44

      20

      3

      67

      0.698

      mcguigan

      COLIA1

      46.51163

      70

      7

      1

      88

      1

      roux

      COLIA1

      47.06395

      8

      24

      2

      07

      1

      uitterlinden

      COLIA1

      82.87791

      905

      392

      42

      339

      1

      weichetova

      COLIA1

      47.61628

      94

      30

      2

      126

      1

      bagnoli

      CTSD

      42.01754

      1

      26

      99

      126

      1

      bertram

      CTSD

      46.92982

      1

      29

      152

      182

      1

      bhojak

      CTSD

      58.68421

      0

      56

      260

      316

      0.151

      crawford

      CTSD

      41.49123

      0

      20

      100

      120

      1

      crawford

      CTSD

      40.78947

      2

      28

      82

      112

      1

      emahazion

      CTSD

      44.03509

      3

      27

      119

      149

      0.3899

      ingegni

      CTSD

      41.49123

      1

      21

      98

      120

      1

      mateo

      CTSD

      61.31579

      8

      54

      284

      346

      0.0143

      matsui

      CTSD

      72.98246

      1

      7

      471

      479

      0.0372

      mcilroy

      CTSD

      47.36842

      1

      16

      170

      187

      0.3491

      menzer

      CTSD

      57.4564

      1

      33

      268

      302

      1

      papassotiropoulos

      CTSD

      61.75439

      0

      47

      304

      351

      0.3847

      papassotiropoulos

      CTSD

      47.10526

      0

      18

      166

      184

      1

      prince

      CTSD

      46.22807

      0

      22

      152

      174

      1

      styczynska

      CTSD

      39.73684

      0

      9

      91

      100

      1

      chang

      CYP17

      45.82569

      26

      79

      77

      182

      0.4248

      gsur

      CYP17

      43.25688

      12

      67

      47

      126

      0.1219

      habuchi

      CYP17

      52.75229

      69

      157

      107

      333

      0.4371

      haiman

      CYP17

      73.34862

      127

      350

      305

      782

      0.1312

      kittles

      CYP17

      42.56881

      10

      46

      55

      111

      1

      latil

      CYP17

      44.63303

      24

      84

      48

      156

      0.2511

      lunn

      CYP17

      44.77064

      18

      73

      68

      159

      0.8621

      stanford

      CYP17

      61.46789

      79

      256

      188

      523

      0.6477

      wadelius

      CYP17

      44.81651

      26

      88

      46

      160

      0.1979

      yamada

      CYP17

      46.65138

      29

      120

      51

      200

      0.004

      amadeo

      drd2

      43.48837

      0

      7

      36

      43

      1

      Anghelescu

      drd2

      56.27907

      3

      32

      63

      98

      1

      Bau

      drd2

      60

      6

      36

      72

      114

      0.5764

      blum

      drd2

      39.06977

      0

      4

      20

      24

      1

      blum

      drd2

      40.69767

      0

      6

      25

      31

      1

      bolos

      drd2

      63.02326

      8

      30

      89

      127

      0.034

      comings

      drd2

      58.60465

      0

      24

      84

      108

      0.3553

      cook

      drd2

      38.3953

      0

      6

      4

      20

      1

      geijer

      drd2

      52.32558

      5

      24

      52

      8

      0.3226

      gelernter

      drd2

      49.30233

      3

      2

      44

      68

      0.7138

      goldman

      drd2

      4.86047

      2

      11

      23

      36

      0.6232

      heinz

      drd2

      59.76744

      4

      35

      74

      113

      1

      Hietala

      drd2

      45.11628

      0

      11

      39

      50

      1

      lawford

      drd2

      44.18605

      3

      11

      32

      46

      0.1562

      neiswanger

      drd2

      40.4652

      0

      4

      26

      30

      1

      noble

      drd2

      46.97674

      3

      4

      4

      58

      0.3437

      Ovchiunikov

      drd2

      51.16279

      4

      23

      49

      76

      0.494

      parsian

      drd2

      39.30233

      0

      3

      22

      25

      1

      Pastorelli

      drd2

      48.37209

      2

      3

      49

      64

      0.2895

      Samochoweic

      drd2

      78.3953

      5

      5

      36

      92

      1

      suarez

      drd2

      53.95349

      2

      23

      63

      88

      1

      abbate

      gpIIIa

      43.2963

      3

      9

      5

      73

      0.4229

      aleksic

      gpIIIa

      60.74074

      0

      4

      403

      544

      0.000039

      anderson

      gpIIIa

      50.848

      9

      65

      202

      276

      0.2337

      anderson

      gpIIIa

      46.88889

      6

      42

      22

      170

      0.3835

      ardissino

      gpIIIa

      48

      4

      33

      63

      200

      0.324

      boncler

      gpIIIa

      43.55556

      0

      9

      6

      80

      0.5896

      bottiger

      gpIIIa

      53.18519

      9

      84

      247

      340

      0.5261

      carter

      gpIIIa

      44.81481

      0

      28

      86

      114

      0.2131

      carter

      gpIIIa

      48.59259

      3

      57

      156

      216

      0.5836

      carter

      gpIIIa

      43.92593

      2

      24

      64

      90

      1

      corral

      gpIIIa

      44.33333

      0

      35

      66

      101

      0.038

      durante-mangoni

      gpIIIa

      43.22222

      0

      9

      52

      71

      0.3451

      garcia

      gpIIIa

      44.2963

      1

      12

      87

      100

      0.3864

      gardemann

      gpIIIa

      84.7037

      31

      297

      863

      1191

      0.3654

      grand maison

      gpIIIa

      44.2963

      1

      23

      76

      100

      1

      hermann

      gpIIIa

      47.11111

      4

      43

      129

      176

      0.7646

      hermann

      gpIIIa

      59.96296

      10

      143

      370

      523

      0.5047

      hooper

      gpIIIa

      47.44444

      2

      39

      144

      185

      1

      joven

      gpIIIa

      49.85185

      3

      85

      66

      250

      0.0483

      kekomaki

      gpIIIa

      42.22222

      2

      7

      35

      44

      0.1123

      kekomaki

      gpIIIa

      43.62963

      1

      17

      64

      82

      1

      laule

      gpIIIa

      76.59259

      20

      254

      698

      972

      0.7073

      mamotte

      gpIIIa

      61.7037

      12

      136

      422

      570

      0.7302

      marian

      gpIIIa

      46.66667

      7

      38

      119

      64

      0.135

      moshfegh

      gpIIIa

      43.88889

      6

      14

      69

      89

      0.0023

      osborn

      gpIIIa

      46.77778

      8

      27

      32

      67

      0.0015

      pastinen

      gpIIIa

      46.18519

      2

      26

      123

      151

      0.6399

      ridker

      gpIIIa

      66.66667

      22

      164

      518

      704

      0.0513

      samani

      gpIIIa

      49.2963

      5

      97

      133

      235

      0.0086

      scaglione

      gpIIIa

      44.22222

      1

      27

      70

      98

      0.6863

      senti

      gpIIIa

      45.62963

      3

      28

      105

      136

      0.4363

      weiss

      gpIIIa

      43.11111

      1

      12

      55

      68

      0.525

      zotz

      gpIIIa

      43.96296

      0

      23

      68

      91

      0.3467

      Combarros

      IL-1

      52.10145

      195

      104

      7

      306

      0.408

      Du

      IL-1

      43.76812

      126

      62

      3

      191

      0.2122

      Green

      IL-1

      66.37681

      221

      27

      65

      503

      0.3238

      Grimaldi

      IL-1

      54.2029

      142

      63

      30

      335

      0.109

      Hedley

      IL-1

      55.36232

      153

      68

      30

      35

      0.113

      Ki

      IL-1

      36.66667

      72

      21

      0

      93

      0.5969

      Minster

      IL-1

      46.73913

      115

      99

      18

      232

      0.75

      Nicoll

      IL-1

      42.02899

      82

      74

      11

      167

      0.3481

      Pirskanen

      IL-1

      67.10145

      248

      209

      56

      513

      0.2582

      Rebeck

      IL-1

      43.47826

      97

      74

      16

      187

      0.7202

      Tsai

      IL-1

      42.24638

      147

      22

      1

      170

      0.5822

      chenevix-Trench

      LmycECOR1

      57.46667

      46

      72

      43

      161

      0.2068

      chernitsa

      LmycECOR1

      46.26667

      18

      38

      21

      77

      1

      crossen

      LmycECOR1

      49.33333

      43

      43

      14

      100

      0.5194

      dlugosz

      LmycECOR1

      44.66667

      11

      38

      16

      65

      0.2145

      dolcetti

      LmycECOR1

      46.4

      24

      35

      19

      78

      0.3718

      ejarque

      LmycECOR1

      50.66667

      40

      45

      25

      110

      0.0825

      fernandez

      LmycECOR1

      49.46667

      30

      49

      22

      101

      0.842

      ge

      LmycECOR1

      39.46667

      6

      12

      8

      26

      0.7061

      hseih

      LmycECOR1

      47.73333

      22

      39

      27

      88

      0.2921

      isbir

      LmycECOR1

      47.06667

      39

      29

      15

      83

      0.0323

      isbir

      LmycECOR1

      42.8

      23

      26

      2

      51

      0.1768

      ishizaki

      LmycECOR1

      49.33333

      17

      63

      20

      100

      0.0157

      kato

      LmycECOR1

      49.06667

      17

      61

      20

      98

      0.0254

      kondratieva

      LmycECOR1

      49.6

      28

      52

      22

      102

      1

      kuminoto

      LmycECOR1

      68.13333

      59

      134

      48

      241

      0.0934

      murakami

      LmycECOR1

      79.6

      69

      183

      75

      327

      0.0358

      saranath

      LmycECOR1

      49.46667

      30

      49

      22

      101

      0.842

      shibuta

      LmycECOR1

      50.26667

      34

      55

      18

      107

      0.6938

      shibuta

      LmycECOR1

      50.26667

      34

      55

      18

      107

      0.6938

      shih

      LmycECOR1

      53.33333

      43

      54

      33

      130

      0.0767

      taylor

      LmycECOR1

      46.13333

      22

      31

      23

      76

      0.1118

      tefre

      LmycECOR1

      53.2

      35

      59

      35

      129

      0.3782

      togo

      LmycECOR1

      76.8

      85

      143

      78

      306

      0.2544

      weston

      LmycECOR1

      43.33333

      10

      22

      23

      55

      0.2616

      weston

      LmycECOR1

      40.8

      11

      17

      8

      36

      0.7464

      weston

      LmycECOR1

      37.73333

      2

      4

      7

      13

      0.5079

      yaylim

      LmycECOR1

      40.93333

      14

      16

      7

      37

      0.5121

      young

      LmycECOR1

      42.4

      16

      29

      3

      48

      0.0606

      Adams

      MTHFR C677T

      47.57246

      29

      97

      96

      222

      0.557

      brugada

      MTHFR C677T

      45.14493

      12

      73

      70

      155

      0.2683

      Brulhart

      MTHFR C677T

      56.05072

      73

      195

      188

      456

      0.0715

      Christensen

      MTHFR C677T

      43.91304

      13

      61

      47

      121

      0.4287

      de Franchis

      MTHFR C677T

      48.87681

      39

      129

      90

      258

      0.6041

      Deloughery

      MTHFR C677T

      61.12319

      94

      262

      240

      596

      0.117

      Gallagher

      MTHFR C677T

      43.33333

      7

      45

      53

      105

      0.6343

      Izumi

      MTHFR C677T

      46.81159

      25

      102

      74

      201

      0.2965

      Kluijtmans

      MTHFR C677T

      43.55072

      6

      42

      63

      111

      1

      Kluijtmans

      MTHFR C677T

      84.81884

      106

      527

      617

      1250

      0.6841

      Ma

      MTHFR C677T

      50.03623

      39

      116

      135

      290

      0.0868

      malinow

      MTHFR C677T

      43.22464

      8

      45

      49

      102

      0.8129

      markus

      MTHFR C677T

      45.36232

      22

      63

      76

      161

      0.1545

      morita

      MTHFR C677T

      67.71739

      79

      361

      338

      778

      0.2587

      Narang

      MTHFR C677T

      41.34058

      5

      19

      26

      50

      0.7298

      salden

      MTHFR C677T

      45.47101

      18

      75

      71

      164

      0.8626

      Schmitz

      MTHFR C677T

      46.34058

      27

      90

      71

      188

      1

      Schwartz

      MTHFR C677T

      51.77536

      43

      141

      154

      338

      0.2251

      tosetto

      MTHFR C677T

      44.23913

      17

      71

      42

      130

      0.1486

      van bockxmeer

      MTHFR C677T

      44.71014

      15

      58

      70

      143

      0.5591

      Verhoef

      MTHFR C677T

      43.15217

      7

      48

      45

      100

      0.3479

      verhoef

      MTHFR C677T

      57.64493

      72

      200

      228

      500

      0.013

      Wilcken

      MTHFR C677T

      47.68116

      24

      113

      88

      225

      0.1929

      Awata

      Neurod1

      71.75824

      1

      55

      327

      383

      0.7094

      Cinek

      Neurod1

      61.42857

      42

      130

      117

      289

      0.5308

      Dupont

      Neurod1

      42.1978

      18

      53

      43

      114

      0.8444

      Dupont

      Neurod1

      42.1978

      18

      53

      43

      114

      0.8444

      Hansen

      Neurod1

      58.35165

      48

      108

      105

      261

      0.0374

      Iwata

      Neurod1

      48.79121

      0

      17

      157

      174

      1

      Jackson

      Neurod1

      64.3956

      2

      73

      241

      316

      0.1963

      Kanatsuka

      Neurod1

      49.12088

      0

      22

      155

      177

      1

      Malecki

      Neurod1

      44.94505

      14

      75

      50

      139

      0.1004

      Malecki

      Neurod1

      48.46154

      25

      68

      78

      171

      0.1277

      Mockizuki

      Neurod1

      42.96703

      0

      12

      109

      121

      1

      Owerback

      Neurod1

      38.46154

      10

      36

      34

      80

      1

      Yamada

      Neurod1

      43.07692

      4

      33

      85

      122

      0.7447

      Ye

      Neurod1

      43.2967

      0

      3

      111

      124

      1

      antikainen

      PON1 Q192R

      45.24735

      87

      75

      7

      169

      0.0753

      aubo

      PON1 Q192R

      47.73852

      154

      23

      33

      30

      0.2833

      aynacioglu

      PON1 Q192R

      44.11661

      11

      43

      5

      05

      0.652

      ayub

      PON1 Q192R

      43.14488

      32

      5

      3

      50

      0.4242

      cascorbi

      PON1 Q192R

      59.62898

      521

      39

      7

      983

      0.872

      chen

      PON1 Q192R

      49.52297

      208

      66

      37

      411

      0.634

      ferre

      PON1 Q192R

      46.06007

      106

      93

      6

      25

      0.692

      gardemann

      PON1 Q192R

      51.71378

      279

      26

      40

      535

      0.94

      hasselwander

      PON1 Q192R

      49.11661

      179

      78

      3

      388

      0.1905

      heijman

      PON1 Q192R

      52.93286

      291

      263

      50

      604

      0.4386

      hermann

      PON1 Q192R

      54.64664

      362

      265

      74

      70

      0.08

      hong

      PON1 Q192R

      45.63604

      75

      84

      32

      191

      0.3597

      imai

      PON1 Q192R

      49.87633

      59

      82

      90

      431

      0.1672

      ko

      PON1 Q192R

      46.11307

      30

      96

      92

      28

      0.5562

      lawlor

      PON1 Q192R

      91.4841

      1430

      1115

      24

      2786

      0.2662

      letellier

      PON1 Q192R

      43.9576

      55

      38

      3

      96

      0.3843

      leus

      PON1 Q192R

      44.27562

      56

      48

      0

      114

      1

      liu

      PON1 Q192R

      44.52297

      25

      74

      29

      128

      0.1104

      mackness

      PON1 Q192R

      47.24382

      156

      99

      27

      282

      0.0698

      odawara

      PON1 Q192R

      44.41696

      25

      53

      44

      22

      0.2648

      ombres

      PON1 Q192R

      45.86572

      06

      84

      4

      204

      0.7264

      osei-hyiaman

      PON1 Q192R

      46.34276

      8

      44

      6

      23

      0.1172

      pati

      PON1 Q192R

      43.67491

      60

      2

      8

      80

      0.000

      pfohl

      PON1 Q192R

      45.26502

      73

      77

      20

      170

      1

      rice

      PON1 Q192R

      52.98587

      312

      24

      54

      607

      0.4298

      robertson

      PON1 Q192R

      85.08834

      37

      90

      97

      2424

      0.0263

      ruiz

      PON1 Q192R

      46.90813

      40

      110

      3

      263

      0.1968

      salonen

      PON1 Q192R

      44.18728

      59

      43

      7

      09

      1

      sangera

      PON1 Q192R

      46.57244

      4

      23

      80

      244

      0.6933

      sangera

      PON1 Q192R

      45.17668

      77

      66

      22

      65

      0.299

      sen-banerjee

      PON1 Q192R

      51.41343

      279

      226

      13

      518

      0.000013

      senti

      PON1 Q192R

      49.25795

      193

      65

      38

      396

      0.7234

      serrato

      PON1 Q192R

      46.62544

      120

      99

      28

      247

      0.3007

      suehiro

      PON1 Q192R

      46.71378

      34

      24

      94

      252

      0.5929

      tuban

      PON1 Q192R

      47.57951

      136

      43

      22

      30

      0.0794

      wang

      PON1 Q192R

      50.65371

      193

      230

      52

      475

      0.1919

      watzinger

      PON1 Q192R

      46.85512

      147

      96

      7

      260

      0.8684

      yamada

      PON1 Q192R

      62.89753

      523

      56

      29

      68

      0.9473

      zama

      PON1 Q192R

      44.29329

      17

      6

      37

      115

      0.4408

      Febbo

      SRD5A2

      73.11111

      78

      330

      39

      799

      0.5038

      Hsing

      SRD5A2

      51.06667

      105

      36

      62

      303

      0.159

      Latil

      SRD5A2

      44.53333

      8

      64

      84

      56

      0.4069

      Lunn

      SRD5A2

      44.17778

      13

      58

      77

      148

      0.6865

      Lunn

      SRD5A2

      37.95556

      1

      5

      2

      8

      1

      Margiotti

      SRD5A2

      42.75556

      9

      40

      67

      116

      0.4555

      Nam

      SRD5A2

      44.8

      21

      69

      72

      62

      0.488

      Pearce

      SRD5A2

      64.26667

      76

      263

      26

      600

      0.4703

      Pearce

      SRD5A2

      50.22222

      43

      56

      85

      284

      0.058

      Pearce

      SRD5A2

      55.86667

      21

      159

      23

      411

      0.4226

      Soderstrom

      SRD5A2

      44.66667

      16

      66

      77

      159

      0.728

      Yamada

      SRD5A2

      46.62222

      50

      97

      56

      203

      0.5742

      abbar

      TPH

      58.38095

      30

      33

      118

      28

      0.5079

      bellivier

      TPH

      40.57143

      11

      45

      38

      94

      0.8226

      du

      TPH

      39.61905

      13

      52

      9

      84

      0.047

      furlong

      TPH

      73.2381

      67

      208

      62

      437

      1

      geijer

      TPH

      40.95238

      13

      47

      38

      98

      1

      kunugi

      TPH

      51.52381

      55

      05

      49

      209

      1

      ono

      TPH

      44.19048

      26

      7

      35

      32

      0.3875

      paik

      TPH

      54.09524

      66

      116

      54

      236

      0.896

      rujescu

      TPH

      62.66667

      40

      55

      3

      326

      0.635

      souery

      TPH

      47.52381

      27

      74

      66

      67

      0.46

      tsai

      TPH

      50.66667

      33

      113

      54

      200

      0.0624

      turecki

      TPH

      43.90476

      18

      7

      40

      129

      0.1507

      zaisman

      TPH

      42.28571

      34

      54

      24

      112

      0.8488

      Blazer

      VDR Taq1

      50.06579

      35

      74

      59

      68

      0.2079

      Blazer

      VDR Taq1

      39.93421

      3

      2

      9

      4

      0.026

      Correa-Cerro

      VDR Taq1

      45.26316

      11

      52

      32

      95

      0.1957

      Furuya

      VDR Taq1

      42.96053

      1

      8

      4

      60

      1

      Gsur

      VDR Taq1

      51.51316

      22

      87

      8

      90

      1

      Habuchi

      VDR Taq1

      61.18421

      3

      8

      253

      337

      0.3282

      Hamasaki

      VDR Taq1

      47.76316

      8

      34

      9

      33

      0.0823

      Kibel

      VDR Taq1

      41.31579

      7

      5

      3

      35

      0.4978

      Kibel

      VDR Taq1

      39.40789

      1

      3

      2

      6

      1

      Luscombe

      VDR Taq1

      49.14474

      30

      67

      57

      154

      0.2436

      Ma

      VDR Taq1

      77.76316

      86

      299

      204

      589

      0.1706

      Medeiros

      VDR Taq1

      52.56579

      4

      92

      73

      206

      0.2529

      Suzuki

      VDR Taq1

      45.92105

      2

      20

      83

      05

      0.684

      Tayeb

      VDR Taq1

      63.94737

      62

      8

      36

      379

      0.95

      Taylor

      VDR Taq1

      49.67105

      36

      73

      53

      62

      0.2677

      Taylor

      VDR Taq1

      39.53947

      1

      6

      1

      8

      0.4779

      Watanabe

      VDR Taq1

      52.30263

      6

      36

      60

      202

      0.042

      Declarations

      Acknowledgments

      The authors are very grateful to Pratima Naik for her contribution to this study and to Scott Stoltenberg and Laura Scott for advice and helpful discussion. They also thank the reviewers for their thorough and helpful comments, which helped them significantly to improve the manuscript.

      Authors’ Affiliations

      (1)
      Molecular & Behavioral Neuroscience Institute, University of Michigan
      (2)
      Departments of Psychiatry and an Genetics, University of Michigan

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      Copyright

      © Henry Stewart Publications 2008

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